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International frameworks for climate mitigation that build from national actions have been developed under the United National Framework Convention on Climate Change and advanced most recently through the Paris Climate Agreement. In parallel, sub-national actors have set greenhouse gas (GHG) reduction goals and developed corresponding climate mitigation plans. Within the U.S., multi-state coalitions have formed to facilitate coordination of related science and policy. Here, utilizing the forum of the NASA Carbon Monitoring System's Multi-State Working Group, we collected and reviewed climate mitigation plans for 11 states in the Regional Greenhouse Gas Initiative region of the Eastern U.S. For each state we reviewed the (a) policy framework for climate mitigation, (b) GHG reduction goals, (c) inclusion of forest activities in the state's climate action plan, (d) existing science used to quantify forest carbon estimates, and (e) stated needs for forest carbon monitoring science. Across the region, we found important differences across all categories. While all states have GHG reduction goals and framework documents, nearly three-quarters of all states do not account for forest carbon when planning GHG reductions; those that do account for forest carbon use a variety of scientific methods with various levels of planning detail and guidance. We suggest that a common, efficient, standardized forest carbon monitoring system would provide important benefits to states and the geographic region as a whole. In addition, such a system would allow for more effective transparency and progress tracking to support state, national, and international efforts to increase ambition and implementation of climate goals.

In the past century, oil palm has developed from a sustenance crop in West Africa to a major global agricultural commodity, with substantial impacts on biodiversity, the environment, society, and livelihoods. Although the oil palm industry contributes to local and national economies across the tropics, there are significant concerns about the negative effects of oil palm cultivation on biodiversity and ecosystem functioning, as well on local communities and farmers. There is a growing awareness of the need for managing agricultural landscapes more sustainably, and the importance of ecological, social, and also interdisciplinary research to inform this. To understand the current status of research across these areas for oil palm, we carried out a systematic mapping exercise to quantify social, ecological, and interdisciplinary socio-ecological research on oil palm cultivation, assess trends in the research, and to identify priority knowledge gaps in the literature. Literature was searched using adapted preferred reporting items for systematic reviews and meta-analyses and Collaboration for Environmental Evidence protocols. We reviewed 4959 publications on the ecological, social, and socioecological effects of oil palm cultivation. Each publication was classified according to study context (the study site location and type), comparators (the type of comparison the study makes), intervention (the potential action or decision being studied), and outcome (the effects of the intervention on the population). This resulted in 443 classified papers, which we then analyzed in more detail, to identify co-occurrence of different research foci between the disciplines and in socio-ecological research. We found a global increase in oil palm research over the past three decades, with a clear bias to Malaysia and Indonesia, mirroring global production trends. Over 70% of the research was focused on ecological outcomes, 19% on social, and less than 10% interdisciplinary. The majority of studies were conducted within industrial plantations, with comparisons to non-modified habitats, such as forests. Research has focused most on the effects of cultivation on yield, invertebrate biodiversity, and livelihood. To place our findings in context of production of palm oil and sustainability priorities, we used information on regional oil palm production in Tonnes, priorities of sustainable certification bodies, and recognized causes of yield gaps. The most pressing knowledge gaps included a lack of studies on the effects of plantation inputs on pollination and herbivory, the relationship between ecological factors and human health and wellbeing, and comparisons of different management practices within oil palm plantations. We advocate that these gaps become the focus of future research attention, as they lie in identified priority research areas and outcomes are likely to be critical to informing the development of more sustainable palm oil production.

The impact of prenatal and early childhood exposure of ambient particulate matters (PMs) on the risk of autism spectrum disorder (ASD) in children remained inconclusive, particularly at low levels below current National Ambient Air Quality Standards. The study summarizes the epidemiological association between PM exposure and risks of ASD in children. PubMed, Embase, Web of Science, Cochrane Library, Compendex, Biosis Previews, and Agricultural & Environmental Science Databases for studies published before February 2020. Original studies with the following information were included: (a) exposure of ambient PM (including PM_2.5 and/or PM₁₀); (b) ASD as the outcome of interest in children; (c) effect estimates of relative risk (RR), odds ratio (OR), or hazard ratio. The risks of ASD are summarized at different exposure windows (i.e. first, second, third trimesters, and early childhood period) by using a random-effects model. Exposure-response meta-regression was performed across various background levels of PM_2.5. We used Newcastle–Ottawa Scale for quality assessment. Eleven studies (two cohort and nine case-control studies) and 313 301 children were enrolled. Overall, the risk of ASD increased by 64% (pooled RR = 1.64, 95% CI = 1.16–2.34) and 31% (pooled RR = 1.31, 95% CI = 1.08–1.58), with exposure to 10 μg m⁻³ increment of PM_2.5 during early childhood and prenatal periods, respectively. Stratifying by three trimesters of prenatal period, the risk of ASD increased 35% per 10 μg m⁻³ difference of PM_2.5 exposure during the third trimester (pooled RR = 1.35, 95% CI = 1.18–1.55), but not during the first and second trimesters. The risks of ASD persisted at the background PM_2.5 levels from 8 μg m⁻³ (pooled RR = 1.30, 95% CI = 1.02–1.66) and onward. Our findings suggested an association between PM_2.5 exposure and risks of ASD, particularly within specific exposure windows, even at low background levels of PM_2.5.

Both bottom-up and top-down initiatives are essential for addressing climate change effectively. These include initiatives aiming to achieve widespread behavioral change towards reduction of greenhouse gas emissions as well as pursuing education regarding adaptation measures. While awareness of the issue of climate change is now pervasive, and actions are being taken at all levels of society, there is still much to do if international goals are to be met. Games and gamification offer one approach to foster both behavioral change and education. In this paper, we investigate the state-of-the-art of game-based climate change engagement through a systematic literature review of 64 research outputs comprising 56 different gamified approaches. Our analysis of the literature reveals a trend of promising findings in this nascent and growing area of research, suggesting the potential to impact multiple engagement dimensions simultaneously, as well as create an engaging gameful experience. Overall, the corpus appears to offer a fruitful balance in foci between climate science, mitigation, and adaptation, as well as a variety of formats in game-based approaches (i.e. digital, analog, and hybrid). However, shortcomings were also observed, such as geographic and demographic imbalances and the short duration of interventions. The reviewed studies yield a large number of results indicating climate change engagement through gamification, especially in the form of cognitive engagement, affect towards climate change-related topics, and in-game behavioral engagement with others. Nevertheless, heterogeneity in terms of contexts, designs, outcomes, and methods, as well as limited rigor in research designs and reporting, hinders drawing overall conclusions. Based on our review, we provide guidelines regarding contexts, interventions, results, and research quality and internal validity for advancing the space of game-based interventions for climate change engagement.

Ocean activities are rapidly expanding as Blue Economy discussions gain traction, creating new potential synergies and conflicts between sectors. To better manage ocean sectors and their development, we need to understand how they interact and the respective outcomes of these interactions. To provide a first comprehensive picture of the situation, we review 3187 articles to map and analyze interactions between economically important ocean sectors and find 93 unique direct and 61 indirect interactions, often mediated via the ocean ecosystem. Analysis of interaction outcomes reveals that some sectors coexist synergistically (e.g. renewable energy, tourism), but many interactions are antagonistic, and negative effects on other sectors are often incurred via degradation of marine ecosystems. The analysis also shows that ocean ecosystems are fundamental for supporting many ocean sectors, yet 13 out of 14 ocean sectors have interactions resulting in unidirectional negative ecosystem impact. Fishing, drilling, and shipping are hubs in the network of ocean sector interactions, and are involved in many of the antagonistic interactions. Antagonistic interactions signal trade-offs between sectors. Qualitative analysis of the literature shows that these tradeoffs relate to the cumulative nature of many ecosystem impacts incurred by some sectors, and the differential power of ocean sectors to exert their rights or demands in the development of the ocean domain. There are also often time lags in how impacts manifest. The ocean governance landscape is not currently well-equipped to deal with the full range of trade-offs, and opportunities, likely to arise in the pursuit of a Blue Economy in a rapidly changing ocean context. Based on our analysis, we therefore propose a set principles that can begin to guide strategic decision-making, by identifying both tradeoffs and opportunities for sustainable and equitable development of ocean sectors.

Greenhouse gas emissions from meat and dairy production are often highly uncertain; these emissions are typically estimated using inventory-based, 'bottom-up' models, which contain uncertainties that are difficult to quantify. Modeled emissions estimates can be corroborated using atmospheric measurements—taken above and downwind of animal production regions—to produce 'top-down' emissions estimates. Top-down and bottom-up estimates of animal methane show good agreement when considering global emissions. However, in the US, where animal production is predominantly highly intensified with confined feeding operations, animal methane emissions may be 39%–90% higher than bottom-up models predict (expressed as mean differences across studies). Animal emissions may grow in the future as meat and dairy demand increases in developing countries. We examine East and Southeast Asia as a test case, where emissions from increased meat and dairy production are expected to be offset by improved efficiency from intensive methods. We adjust the share of direct emissions projected to come from intensive systems by the intensities derived from US top-down estimates. We find that region-wide emissions from meat and milk production could reach 1.52 (1.41–1.62) GtCO₂eq by 2050, an amount 21% (13%–29%) higher than previously predicted. Therefore, intensification may not be as effective in mitigating emissions in developing countries as is commonly assumed.

There is increasing global interest in employing nature-based solutions, such as reforestation and wetland restoration, to help reduce water risks to economies and society, including water pollution, floods, droughts and water scarcity, that are likely to become worse under future climates. Africa is exposed to many such water risks. Nature-based solutions for adaptation should be designed to benefit biodiversity and can also provide multiple co-benefits, such as carbon sequestration. A systematic review of over 10 000 publications revealed 150 containing 492 quantitative case studies related to the effectiveness of nature-based solutions for downstream water quantity and water quality (including sediment load) in Africa. The solutions assessed included landscape-scale interventions and patterns (forests and natural wetlands) and site-specific interventions (constructed wetlands and urban interventions e.g. soakaways). Consistent evidence was found that nature-based solutions can improve water quality. In contrast, evidence of their effectiveness for improving downstream water resource quantity was inconsistent, with most case studies showing a decline in water yield where forests (particularly plantations of non-native species) and wetlands are present. The evidence further suggests that restoration of forests and floodplain wetlands can reduce flood risk, and their conservation can prevent future increases in risk; in contrast, this is not the case for headwater wetlands. Potential trade-offs identified include nature-based solutions reducing flood risk and pollution, whilst decreasing downstream water resource quantity. The evidence provides a scientific underpinning for policy and planning for nature-based solutions to water-related risks in Africa, though implementation will require local knowledge.

India's falling aquifer levels, erratic monsoons, arable land constraints, stagnating crop yields, growing food demand, and rising greenhouse gas (GHG) emissions necessitate that strategic interventions be planned and implemented to maintain food security in the country. In this paper, we present two novel system dynamics simulation models—termed 'Sustainable Alternative Futures for India' (SAFARI) and SAFARI-R (a regionally disaggregated version of SAFARI)—that can be used to develop and analyse specific interventions required at the national and regional levels to sustainably maintain food security. Our simulation results show that increasing micro-irrigation coverage, limiting sugarcane cultivation, and improving water recycling in domestic and industrial sectors can help achieve food production sufficiency within the limitations posed by the availability of natural resources. Alternatively, a behavioural shift towards eating (and cultivating) coarse cereals instead of rice (which is water intensive) is another effective intervention, especially when combined with micro-irrigation or crop yield improvements, and reduced sugarcane cultivation. When compared to a scenario where current practices continue, these alternative pathways to food security can reduce annual water consumption for irrigation by 18%–24%, electricity demand for irrigation by 60%–65%, and the agriculture sector's total (direct + indirect) GHG emissions by 17%–25%, by 2050. Further, simulations on SAFARI-R indicate that the north, centre, and west zones of the country are considerably pressed for water, while the south and east zones could run out of land. As a way to meet the food demand in these zones in future, the possibility of crop redistribution is explored along with other strategies such as reducing groundwater dependence.

Quaternary alkylammonium compounds (QAACs) are used as disinfectants and surfactants worldwide, with their usage currently increasing as a result of the COVID-19 pandemic. QAACs are released into the environment with manure, sewage sludge and wastewater. The fate of QAACs in soils is poorly understood, although QAACs are inflicted in the selection of antibiotic-resistant bacteria. We studied the temporal accumulation of QAACs in soils of the Mezquital Valley that have been irrigated with Mexico City wastewater from 0 to 88 years. Concentrations of 16 QAACs, including alkyltrimethylammonium compounds (ATMACs), dialkyldimethylammonium compounds (DADMACs) and benzylalkyldimethylethylammonium compounds (BACs), were determined using HPLC-MS/MS after ultrasonic extraction. The most abundant QAAC-homologues in the soils were BACs > ATMACs > DADMACs. The concentrations of QAACs increased linearly and slowly during the first years of irrigation (∑QAAC: 2–23 µg kg⁻¹), but after 40 years of wastewater irrigation we observed an exponential increase in QAAC concentrations (up to 155 µg kg⁻¹). QAACs accumulate in soils of the Mezquital Valley during long-term wastewater irrigation. In contrast to pharmaceuticals, no apparent 'steady state' concentration is reached after decades of wastewater irrigation.

Summer heatwave events have exhibited increasing trends, with sudden increases occurring since the early 2000s over northeastern China and along the northern boundary of Mongolia. However, the mechanism behind heatwaves remains unexplored. To quantitatively examine the feedback attribution of concurrent events related to surface temperature anomalies, the coupled atmosphere–surface climate feedback-response analysis method based on the total energy balance within the atmosphere–surface column was applied. The results demonstrate that the contributions of the latent heat flux and surface dynamic processes served as positive feedback for surface warming by reducing the heat release from the surface to the atmosphere because of deficient soil moisture based on dry conditions. Cloud feedback also led to warm temperature anomalies through increasing solar insolation caused by decreasing cloud amounts associated with anomalous high-pressure systems. In contrast, the sensible heat flux played a role in reducing the warm temperature anomalies by the emission of heat from the surface. Atmospheric dynamic feedback led to cold anomalies. The influence of ozone, surface albedo, and water vapor processes is very weak. This study provides a better understanding of combined extreme climate events in the context of radiative and dynamic feedback processes.

Regional heterogeneity in direct and snow albedo forcing of aerosols over the Himalayan cryosphere was investigated using a regional climate model coupled with the community land model having snow, ice and aerosol radiation module. Deposition of absorbing aerosols like dust (natural) and black carbon (BC) (anthropogenic) decreases the snow albedo (snow darkening) over the Himalayas. Western Himalayas experiences a large reduction in the snow albedo (0.037) despite having lower BC mass concentration compared to central (0.014) and eastern (0.005) Himalayas. The contribution of BC and dust to the snow albedo reduction is comparable over the western and eastern Himalayas. The inclusion of aerosol-induced snow darkening in to the model reduces its bias with respect to the satellite derived surface albedo by 59%, 53% and 35% over western, central and eastern Himalayas respectively during the spring season. Since surface albedo decides the sign and magnitude of aerosol direct radiative forcing, aerosol induced snow darkening significantly affects the direct radiative effects of aerosols. Hence, the aerosol-induced decrease in snow albedo causes an early reversal in the sign of aerosol direct radiative forcing at the top of the atmosphere from warming to cooling over the western and central Himalayas, which can have implications in the radiation balance and water security over the region.

The recent COVID-19 pandemic with its countermeasures, e.g. lock-downs, resulted in decreases in emissions of various trace gases. Here we investigate the changes of ozone over Europe associated with these emission reductions using a coupled global/regional chemistry climate model. We conducted and analysed a business as usual and a sensitivity (COVID19) simulation. A source apportionment (tagging) technique allows us to make a sector-wise attribution of these changes, e.g. to natural and anthropogenic sectors such as land transport. Our simulation results show a decrease of ozone of 8% over Europe in May 2020 due to the emission reductions. The simulated reductions are in line with observed changes in ground-level ozone. The source apportionment results show that this decrease is mainly due to the decreased ozone precursors from anthropogenic origin. Further, our results show that the ozone reduction is much smaller than the reduction of the total NO_x emissions (around 20%), mainly caused by an increased ozone production efficiency. This means that more ozone is produced for each emitted NO_x molecule. Hence, more ozone is formed from natural emissions and the ozone productivities of the remaining anthropogenic emissions increase. Our results show that politically induced emissions reductions cannot be transferred directly to ozone reductions, which needs to be considered when designing mitigation strategies.

Global assessments of climate extremes typically do not account for the unique characteristics of individual crops. A consistent definition of the exposure of specific crops to extreme weather would enable agriculturally-relevant hazard quantification. To this end, we develop a database of both the temperature and moisture extremes facing individual crops by explicitly accounting for crop characteristics. To do this, we collate crop-specific temperature and moisture parameters from the agronomy literature, which are then combined with time-varying crop locations and high-resolution climate information to quantify crop-specific exposure to extreme weather. Specifically, we estimate crop-specific temperature and moisture shocks during the growing season for a 0.25^∘ spatial grid and daily time scale from 1961 to 2014 globally. We call this the Agriculturally-Relevant Exposure to Shocks (ARES) model and make all ARES output available with this paper. Our crop-specific approach leads to a smaller average value of the exposure rate and spatial extent than does a crop-agnostic approach. Of the 17 crops included in this study, 13 had an increase in exposure to extreme heat, while 9 were more exposed to extreme cold over the past half century. All crops in this study show a statistically significant increase in exposure to both extreme wetness and dryness. Cassava, sunflowers, soybeans, and oats had the greatest increase in hot, cold, dry, and wet exposure, respectively. We compare ARES model results with the EM-DAT disaster database. Our results highlight the importance of crop-specific characteristics in defining weather shocks in agriculture.

The timing of lake ice breakup and freezeup are important indicators of climate change in Arctic and boreal regions because they respond rapidly and directly to variations in climate conditions. Despite its importance, lake ice phenology remains poorly documented in most lakes of Alaska. To fill this data gap, we constructed a remote sensing-derived lake ice phenology database covering all lakes in Alaska larger than 1 km² (n = 4241) over the period 2000–2019. This dataset, which includes lake ice on/off dates and lake ice duration, was based on an automatic method using daily moderate resolution imaging spectroradiomenter (MODIS) imagery to measure lake ice fraction. This method extracts lake ice pixels from MODIS images using a dynamic threshold that was calibrated against Landsat Fmask. Different filters that account for clouds, polar night, and other sources of error were applied to increase the accuracy of lake ice phenology estimation. Trend analysis shows earlier breakup (−5.5 d decade⁻¹) for 440 lakes and later breakup (7.5 d decade⁻¹) for four lakes (p < 0.05). A total of 289 lakes had significant trends toward later freezeup (2.9 d decade⁻¹) and 11 lakes towards earlier freezeup (−3.3 d decade⁻¹). Most lakes with significant trends are north of the Brooks Range. This dataset can contribute to increased understanding of interactions between lake processes and climate change, and it supports the study of biogeochemical, limnological and ecological regimes in Alaska and pan-Arctic regions.

Paddy rice agriculture plays an important role in food security and has a considerable influence on natural systems. In the context of climate change, understanding the nature and drivers of shifts in the northern limit of paddy rice (NLPR) is crucial for adaptation strategies and food security. However, quantitative studies on the effect of climate change on paddy rice distribution shifts have not been well performed. Here, we mapped the NLPR in China using Landsat imagery from 1984 to 2013, analyzed the latitudinal and elevational dynamics of the NLPR using Fishnet analysis, and explored the factors driving the changes in rice area across the NLPR regions using a linear regression model. Our results show that between 1984 and 2013, the NLPR shifted 24.93 km northward (the greatest movement was 88.01 km occurring at approximately 133° E) and elevational limits increased by 39.15 m (the greatest movement was 117.08 m occurring at approximately 129° E). While socioeconomic factors (e.g. benefits, policies, irrigation, and mulch) played significant roles in rice area changes, the changes in rice area across the NLPR regions had the strongest positive association with the increase in the previous temperature, indicating that rice cultivation in the NLPR regions has moved to higher latitudes over the 30 year study period to adapt to climate change. Our study highlighted that quantifying the interactions between climate change and crop production systems can facilitate a better understanding of the human responses to changes in the growing conditions in the face of climate change and ensuring regional and global food security.

Long-term assessment of severe wildfires and associated air pollution and related climate patterns in and around the Arctic is essential for assessing healthy human life status. To examine the relationships, we analyzed the National Aeronautics and Space Administration (NASA) modern-era retrospective analysis for research and applications, version 2 (MERRA-2). Our investigation based on this state-of-the-art atmospheric reanalysis data reveals that 13 out of the 20 months with the highest PM_2.5 (corresponding to the highly elevated organic carbon in the particulate organic matter [POM] form) monthly mean mass concentration over the Arctic for 2003–2017 were all in summer (July and August), during which POM of $\geqslant$0.5 μg m⁻³ and PM_2.5 were positively correlated. This correlation suggests that high PM_2.5 in the Arctic is linked to large wildfire contributions and characterized by significant anticyclonic anomalies (i.e. clockwise atmospheric circulation) with anomalous surface warmth and drier conditions over Siberia and subpolar North America, in addition to Europe. A similar climate pattern was also identified through an independent regression analysis for the July and August mean data between the same atmospheric variables and the sign-reversed Scandinavian pattern index. We named this pattern of recent atmospheric circulation anomalies the circum-Arctic wave (CAW) pattern as a manifestation of eastward group-velocity propagation of stationary Rossby waves (i.e. large-scale atmospheric waves). The CAW induces concomitant development of warm anticyclonic anomalies over Europe, Siberia, Alaska, and Canada, as observed in late June 2019. Surprisingly, the extended regression analysis of the 1980–2017 period revealed that the CAW pattern was not prominent before 2003. Understanding the CAW pattern under future climate change and global warming would lead to better prediction of co-occurrences of European heatwaves and large-scale wildfires with air pollution over Siberia, Alaska, and Canada in and around the Arctic in summer.

This paper investigates the environmental trade offs resulting from the adoption of autonomous vehicles (AVs) as a function of modal shifts and use phase. An empirical approach is taken to formulate a mode choice model informed from a stated preference (SP) survey conducted in Madison, Wisconsin. A life cycle analysis based on well-to-wheel model is then conducted to quantify the use phase environmental impacts across different categories. The mode choice analysis reveals the potential users of AVs and its attractiveness as a mode of transportation, ultimately competing with traditional modes available. This translates into modal shifts that are shown to result in an expected increase in environmental impacts across all studied categories: energy consumption (5.93%), greenhouse gas emissions (5.72%), particulate matter (6.80%), sulfur (6.85%) and nitrogen oxides (5.70%). The adoption of electric AVs (E-AVs) is then analyzed as an offsetting strategy to combat the increase in environmental impacts. The analysis reveals that E-AVs are capable of offsetting the foreseen impacts, yet their effectiveness is dependent on the electricity generation mix and adoption rate.

Fifteen years ago, Pacala and Socolow argued that global carbon emissions could be stabilised by mid-century using a portfolio of existing mitigation strategies. We assess historic progress for each of their proposed mitigation strategies and convert this into the unit of 'wedges'. We show that the world is on track to achieve 1.5 ± 0.9 wedges relative to seven required to stabilise emissions, or 14 required to achieve net-zero emissions by mid-century. Substantial progress has been made in some domains that are not widely recognised (improving vehicle efficiency and declining vehicle use); yet this is tempered by negligible or even negative progress in many others (particularly tropical tree cover loss in Asia and Africa). By representing global decarbonisation efforts using the conceptually simple unit of wedges, this study helps a broader audience to understand progress to date and engage with the need for much greater effort over the coming decades.

The importance of glacier meltwater as a source of mountain-block recharge remains poorly quantified, yet it may be essential to the integrity of alpine aquatic ecosystems by maintaining baseflow in streams and perennial flow in springs. We test the hypothesis that meltwater from alpine glaciers is a critical source of recharge for mountain groundwater systems using traditional stable isotopic source-identification techniques combined with a novel application of microbial DNA. We find that not only is alpine glacier meltwater a critical source of water for many springs, but that alpine springs primarily supported by glacial meltwater contain microbial taxa that are unique from springs primarily supported by seasonal recharge. Thus, recharge from glacial meltwater is vital in maintaining flow in alpine springs and it supports their distinct microbiomes.

The growing worldwide impact of flood events has motivated the development and application of global flood hazard models (GFHMs). These models have become useful tools for flood risk assessment and management, especially in regions where little local hazard information is available. One of the key uncertainties associated with GFHMs is the estimation of extreme flood magnitudes to generate flood hazard maps. In this study, the 1-in-100 year flood (Q100) magnitude was estimated using flow outputs from four global hydrological models (GHMs) and two global flood frequency analysis datasets for 1350 gauges across the conterminous US. The annual maximum flows of the observed and modelled timeseries of streamflow were bootstrapped to evaluate the sensitivity of the underlying data to extrapolation. Results show that there are clear spatial patterns of bias associated with each method. GHMs show a general tendency to overpredict Western US gauges and underpredict Eastern US gauges. The GloFAS and HYPE models underpredict Q100 by more than 25% in 68% and 52% of gauges, respectively. The PCR-GLOBWB and CaMa-Flood models overestimate Q100 by more than 25% at 60% and 65% of gauges in West and Central US, respectively. The global frequency analysis datasets have spatial variabilities that differ from the GHMs. We found that river basin area and topographic elevation explain some of the spatial variability in predictive performance found in this study. However, there is no single model or method that performs best everywhere, and therefore we recommend a weighted ensemble of predictions of extreme flood magnitudes should be used for large-scale flood hazard assessment.

Prior to delineation of fire perimeters from airborne and satellite imagery, fire management agencies in Canada employed conventional methods to map area burned based on sketch mapping, digitization from a global positioning system unit, and point buffering from geographic coordinates. These techniques usually provide a less precise representation of a wildland fire's size and shape than those derived from image data. The aim of this study is to assess the discrepancy in fire size from these techniques that contribute to uncertainty in area burned. We paired independently generated fire perimeters derived from Landsat satellite imagery with conventional perimeters (n = 2792; mean area difference per fire = 40.1%), and developed a set of prediction models to estimate a Landsat area burned from conventional perimeters by considering the mapping source, method, agency, and time period. A two-fold cross validation predicting the logarithm of area burned from the models, indicated an R² = 0.95 (MAE = 0.10 ha; RMSE = 0.19 ha). From this, we created an adjusted area burned time series from 1950 to 2018 using the model-predicted estimates from conventional perimeters (75% of agency-reported area) in combination with unchanged estimates from agency perimeters derived from airborne and satellite imagery (13% of fires). The predicted estimates reduced the size of individual fires over 2000 ha on average in some years, contributing to an annual average reduction of approximately 11% of the area burned reported in the national agency fire database. By retrospectively applying a robust statistical adjustment to the fire size data, the historical overestimation in annual area burned—up to 1.4 Mha in a single year—could be substantially minimized.

Although increasing evidence has reported that unfavorable temperature may lead to increased premature mortality, a systematic assessment is lacking on the impact of ambient temperature on years of life lost (YLL) and life expectancy in China. Daily data on mortality, YLL, meteorological factors and air pollution were obtained from 93 Chinese cities during 2013–2016. A two-stage analytic approach was applied for statistical analysis. At the first stage, a distributed lag non-linear model with a Gaussian link was used to estimate the city-specific association between ambient temperature and YLLs. At the second stage, a meta-analysis was used to obtain the effect estimates at regional and national levels. We further estimated the corresponding YLLs and average life expectancy loss per deceased person attributable to the non-optimum temperature exposures based on the established associations. We observed 'U' or 'J' shaped associations between daily temperature and YLL. The heat effect appeared on the current day and lasted for only a few days, while the cold effect appeared a few days later and lasted for longer. In general, 6.90% (95% confidence interval (CI): 4.62%, 9.18%) of YLLs could be attributed to non-optimum temperatures at the national level, with differences across different regions, ranging from 5.36% (95% CI: −3.36%, 6.89%) in east region to 9.09% (95% CI: −5.55%, 23.73%) in northwest region. For each deceased person, we estimated that non-optimum temperature could cause a national-averaged 1.02 years (95% CI: 0.68, 1.36) of life loss, with a significantly higher effect due to cold exposure (0.89, 95% CI: 0.59, 1.19) than that of hot exposure (0.13, 95% CI: 0.09, 0.16). This national study provides evidence that both cold and hot weather might result in significant YLL and lower life expectancy. Regional adaptive policies and interventions should be considered to reduce the mortality burden associated with the non-optimum temperature exposures.

With large parts of the world moving toward renewable energies, there is an urgent need to organize this large-scale transition effectively. This paper presents a new methodology to guide the planning and siting of renewable electricity generation for countries or larger geographical regions. Its flexible approach accounts for the specific boundary conditions, constraints and available resources of the region of interest and enables solutions that optimize the interplay between the various types of generation. Evolution strategy permits a simultaneous optimization of the placement and the share of renewable electricity generation technologies that are to be added to a system, while most efficiently combining the new with the existing electricity generation and respecting the constraints of the electrical grid. Using Switzerland as case study, we demonstrate the method's ability to devise national installation scenarios that are efficient, realistic with respect to land use and grid infrastructure and reduce significantly the need for seasonal storage. We show how the spatio-temporal variability of weather-driven electricity generation can be exploited to benefit the electrical system as a whole.

Much of the world's data are stored, managed, and distributed by data centers. Data centers require a tremendous amount of energy to operate, accounting for around 1.8% of electricity use in the United States. Large amounts of water are also required to operate data centers, both directly for liquid cooling and indirectly to produce electricity. For the first time, we calculate spatially-detailed carbon and water footprints of data centers operating within the United States, which is home to around one-quarter of all data center servers globally. Our bottom-up approach reveals one-fifth of data center servers direct water footprint comes from moderately to highly water stressed watersheds, while nearly half of servers are fully or partially powered by power plants located within water stressed regions. Approximately 0.5% of total US greenhouse gas emissions are attributed to data centers. We investigate tradeoffs and synergies between data center's water and energy utilization by strategically locating data centers in areas of the country that will minimize one or more environmental footprints. Our study quantifies the environmental implications behind our data creation and storage and shows a path to decrease the environmental footprint of our increasing digital footprint.

COVID-19 lockdowns make it possible to investigate the extent to which an unprecedented increase in renewables' penetration may have brought unexpected limitations and vulnerabilities of current power systems to the surface. We empirically investigate how power systems in five European countries have dealt with this unexpected shock, drastically changing electricity load, the scheduling of dispatchable generation technologies, electricity day-ahead wholesale prices, and balancing costs. We find that low-cost dispatchable generation from hydro and nuclear sources has fulfilled most of the net-load even during peak hours, replacing more costly fossil-based generation. In Germany, the UK, and Spain coal power plants stood idle, while gas-fired generation has responded in heterogeneous ways across power systems. Falling operational costs of generators producing at the margin and lower demand, both induced by COVID-19 lockdowns, have significantly decreased wholesale prices. Balancing and other ancillary services' markets have provided the flexibility required to respond to the exceptional market conditions faced by the grid. Balancing costs for flexibility services have increased heterogeneously across countries, while ancillary markets' costs, measured only in the case of Italy, have increased substantially. Results provide valuable evidence on current systems' dynamics during high renewables' shares and increased demand volatility. New insights into the market changes countries will be facing in the transition towards a clean, secure, and affordable power system are offered.

Open burning is illegal in Ukraine, yet Ukraine has, on average, 300 times more fire activity per year (2001–2019) than most European countries. In 2016 and 2017, 47% of Ukraine was identified as cultivated area, with a total of 70% of land area dedicated to agricultural use. Over 57% of all active fires in Ukraine detected using space-borne Visible Infrared Imaging Radiometer Suite (VIIRS) during 2016 and 2017 were associated with pre-planting field clearing and post-harvest crop residue removal, meaning that the majority of these fires are preventable. Due to the small size and transient nature of cropland burns, satellite-based burned area (BA) estimates are often underestimated. Moreover, traditional spectral-based BA algorithms are not suitable for distinguishing burned from plowed fields, especially in the black soil regions of Ukraine. Therefore, we developed a method to estimate agricultural BA by calibrating VIIRS active fire data with exhaustively mapped cropland reference areas (42 958 fields). Our study found that cropland BA was significantly underestimated (by 30%–63%) in the widely used Moderate Resolution Imaging Spectroradiometer-based MCD64A1 BA product, and by 95%–99.9% in Ukraine's National Greenhouse Gas Inventory. Although crop residue burns are smaller and emit far less emissions than larger wildfires, reliable monitoring of crop residue burning has a number of important benefits, including (a) improving regional air quality models and the subsequent understanding of human health impacts due to the proximity of crop residue burns to urban locations, (b) ensuring an accurate representation of predominantly smaller fires in regional emission inventories, and (c) increasing awareness of often illegal managed open burning to provide improved decision-making support for policy and resource managers.

Charcoal is a key energy source for urban households in sub-Saharan Africa and charcoal production is the main cause of forest degradation across the region. We used multitemporal high-resolution remote sensing optical imagery to quantify the extent and intensity of forest degradation associated with charcoal production and its impact on forest carbon stocks for the main supplying area of an African capital. This analysis documents the advance of forest degradation and quantifies its aboveground biomass removals over a seven-year period, registering that, between 2013 and 2016, the average annual area under charcoal production was 103 km² and the annual aboveground biomass removals reached 1081 000 (SD = 2461) Mg. Kiln densities in the study area rose to 2 kilns-ha, with an average of 90.7 Mg ha⁻¹ of extracted aboveground biomass. Charcoal production was responsible for the degradation of 55.5% of the mopane woodlands in the study area between 2013 and 2019. We estimated post-disturbance recovery times using an ecosystem model calibrated for the study area. The simulations showed that recovery times could require up to 150 years for current aboveground biomass extraction rates. The results of the remote sensing analysis and the simulations of the ecosystem model corroborate the unsustainability of the present patterns of charcoal production. The detailed characterization of the spatial and temporal patterns of charcoal production was combined with household survey information to quantify the impact of the urban energy demand of the Maputo urban area on forest carbon stocks. The analysis shows that Maputo charcoal demand was responsible for the annual degradation of up to 175.3 km² and that the contribution of the study area to this demand fluctuated between 75% and 33% over the study period. The extent, advance pace and distance from urban centers documented in this study support the idea that forest degradation from charcoal production cannot merely be considered a peri-urban process. The intensity of the aboveground biomass (AGB) removals and its contribution to forest carbon stocks changes is significant at the national and regional levels.

To increase the adoption and reliability of low impact development (LID) practices for stormwater runoff management and other co-benefits, we must improve our understanding of how climate (i.e. patterns in incoming water and energy) affects LID hydrologic behavior and effectiveness. While others have explored the effects of precipitation patterns on LID performance, the role of energy availability and well-known ecological frameworks based on the aridity index (ratio of potential evapotranspiration (ET) to precipitation, PET:P) such as Budyko theory are almost entirely absent from the LID scientific literature. Furthermore, it has not been tested whether these natural system frameworks can predict the fate of water retained in the urban environment when human interventions decrease runoff. To systematically explore how climate affects LID hydrologic behavior, we forced a process-based hydrologic model of a baseline single-family parcel and a parcel with infiltration-based LID practices with meteorological records from 51 U.S. cities. Contrary to engineering design practice which assumes precipitation intensity is the primary driver of LID effectiveness (e.g. through use of design storms), statistical analysis of our model results shows that the effects of LID practices on long-term surface runoff, deep drainage, and ET are controlled by the relative balance and timing of water and energy availability (PET:P, 30 d correlation of PET and P) and measures of precipitation intermittency. These results offer a new way of predicting LID performance across climates and evaluating the effectiveness of infiltration-based, rather than retention-based, strategies to achieve regional hydrologic goals under current and future climate conditions.

Numerous studies have investigated the hotspots for reducing carbon emissions associated with household consumption, including reducing household carbon footprints (CFs) and greener lifestyle choices, such as living car-free, eating less meat, and having one less child. However, estimating the effect of each of these actions requires the simultaneous consideration of lifestyle choices and household characteristics that could also affect the household CF. Here, we quantify the reduction in household CFs for 25 factors associated with individual lifestyle choices or socioeconomic characteristics. This study linked approximately 42 000 microdata on consumption expenditure with the Japanese subnational 47 prefecture-level multi-regional input–output table, which are both the finest-scale data currently available. We improved the accuracy of household CF calculations by considering regional heterogeneity, and successfully estimated the magnitude of household CF reduction associated with individual lifestyle choices and socioeconomics. For example, it was found that moving from a cold region to a region with mild climate would have considerable potential for reducing the CO₂ emissions of a household, all other factors being equal. In addition, a household residing in a house that meets the most recent energy standards emits 1150 kg less CO₂ per year than if they reside in a house that meets previous energy standards. Ownership and use of durable goods also had the potential for reducing the CO₂ emissions of a household; a normal-sized car, a personal computer, a compact car, and a bidet were associated with CO₂ emissions of 922, 712, 421, and 345 kg per year, respectively. The findings therefore have important implications for climate change mitigation and policy measures associated with lifestyle.

Heat and water stress can drastically reduce crop yields, particularly when they co-occur, but their combined effects and the mitigating potential of irrigation have not been simultaneously assessed at the regional scale. We quantified the combined effects of temperature and precipitation on county-level maize and soybean yields from irrigated and rainfed cropping in the USA in 1970–2010, and estimated the yield changes due to expected future changes in temperature and precipitation. We hypothesized that yield reductions would be induced jointly by water and heat stress during the growing season, caused by low total precipitation (P_GS) and high mean temperatures (T_GS) over the whole growing season, or by many consecutive dry days (CDD_GS) and high mean temperature during such dry spells (T_CDD) within the season. Whole growing season (T_GS, P_GS) and intra-seasonal climatic indices (T_CDD, CDD_GS) had comparable explanatory power. Rainfed maize and soybean yielded least under warm and dry conditions over the season, and with longer dry spells and higher dry spell temperature. Yields were lost faster by warming under dry conditions, and by lengthening dry spells under warm conditions. For whole season climatic indices, maize yield loss per degree increase in temperature was larger in wet compared with dry conditions, and the benefit of increased precipitation greater under cooler conditions. The reverse was true for soybean. An increase of 2 °C in T_GS and no change in precipitation gave a predicted mean yield reduction across counties of 15.2% for maize and 27.6% for soybean. Irrigation alleviated both water and heat stresses, in maize even reverting the response to changes in temperature, but dependencies on temperature and precipitation remained. We provide carefully parameterized statistical models including interaction terms between temperature and precipitation to improve predictions of climate change effects on crop yield and context-dependent benefits of irrigation.

Winter soil cover by vegetation is associated with multiple benefits. In this study, winter soil cover rate before spring-sown crops was estimated for mainland France from multispectral imagery. For 67% and 84% of the area under spring-sown crops for years 2018 and 2019, soil cover during the previous winter was estimated through the computation of the Normalized Difference Vegetation Index (NDVI), using Sentinel-2 multispectral images. At country scale, winter soil cover rate before spring-sown crops was estimated between 37% and 48% for 2018 and between 31% and 43% for 2019, depending on the NDVI threshold for a soil to be considered covered by at least 50% of vegetation. Spatial patterns were relatively similar between the two years studied, highlighting strong heterogeneities between French departments. Cropping systems may explain some of these heterogeneities, as it has been shown that there is a large variability in the soil cover rate between spring-sown crops, but also depending on the previous crop. Winter soil cover rate was higher for crops associated with livestock production, such as maize silage (between 59% and 74% of plots covered before this crop). It was also shown that winter soil cover could be ensured by other means than cover crops: temporary grasslands were the previous crop with the highest soil cover, probably due to late ploughing. For these reasons, mixed systems combining livestock and crop productions may be a solution to increase winter soil cover before spring-sown crops.

Global chronic nitrogen (N) deposition to forests can alleviate ecosystem N limitation, with potentially wide ranging consequences for biodiversity, carbon sequestration, soil and surface water quality, and greenhouse gas emissions. However, the ability to predict these consequences requires improved quantification of hard-to-measure N fluxes, particularly N gas loss and soil N retention. Here we combine a unique set of long-term catchment N budgets in the central Europe with ecosystem ¹⁵N data to reveal fundamental controls over dissolved and gaseous N fluxes in temperate forests. Stream leaching losses of dissolved N corresponded with nutrient stoichiometry of the forest floor, with stream N losses increasing as ecosystems progress towards phosphorus limitation, while soil N storage increased with oxalate extractable iron and aluminium content. Our estimates of soil gaseous losses based on ¹⁵N stocks averaged 2.5 ± 2.2 kg N ha⁻¹ yr⁻¹ and comprised 20% ± 14% of total N deposition. Gaseous N losses increased with forest floor N:P ratio and with dissolved N losses. Our relationship between gaseous and dissolved N losses was also able to explain previous ¹⁵N-based N loss rates measured in tropical and subtropical catchments, suggesting a generalisable response driven by nitrate (NO₃⁻) abundance and in which the relative importance of dissolved N over gaseous N losses tended to increase with increasing NO₃⁻ export. Applying this relationship globally, we extrapolated current gaseous N loss flux from forests to be 8.9 Tg N yr⁻¹, which represent 39% of current N deposition to forests worldwide.

To reach its goal of net greenhouse gas neutrality by 2050, the European Union seeks to massively expand wind and solar power. Relying on weather-dependent power generation, however, poses substantial risks if climate variability is not adequately understood and accounted for in energy system design. Here we quantify European wind and solar generation variability over the last century, finding that both vary on a multidecadal scale, but wind more strongly. We identify hotspots and study dominant patterns of (co-)variability, finding that solar generation varies mostly uniformly across Europe while the leading wind variability modes reveal cross-border balancing potential. Combined wind and solar power generation in the current European system exhibits multidecadal variability of around 5% and can be further reduced through European cooperation or locally optimized wind shares, albeit the latter comes at the expense of significantly enhancing seasonal to interannual variability. Improved spatial planning therefore offers multiple options to mitigate long-term renewable generation variability but requires careful assessments of the trade-offs between climate-induced variations on different timescales.

Heat pumps are a key technology for improving energy efficiency as they can significantly reduce energy costs and emissions. Given the significant role of heat pumps in carbon neutrality pathways, and pressure for related national energy efficiency programs, it is important to examine economic profitability of heat pump investments and their relative environmental and social benefits. This paper aims to answer the following main research question: are areas with lower housing prices and income less likely to invest into energy efficiency? The paper finds that in Finland heat pumps are already very profitable and converting buildings' heating systems into heat pumps creates major environmental and economic benefits for the residents. The cost of heating and heat pump investment costs does not vary between locations whereas housing prices, rents and income do. Neighborhoods with lower housing prices have less motivation and capability to invest into heat pumps. Urban areas with positive housing price development, higher income and better financing options will likely invest into energy efficiency without subsidies. Potential subsidies should be allocated into areas with lower housing prices, because emissions are evenly distributed, and lower income areas pay relatively more for energy. Energy efficiency subsidies could be tied into housing prices or more specifically into property tax, which is universally collected in most countries. Property tax could be used to guide energy efficiency investments into locations where they would not be carried out otherwise. For areas that do not need subsidies, this paper recommends that awareness should be increased, because the economic and carbon emission reduction potential of energy efficiency measures is still not well understood.

Decadal predictions have gained immense importance over the last decade because of their use in near-term adaption planning. Computationally expensive coupled model intercomparison project phase 5 general circulation models (GCMs) are initialized every 5 years and they generate the decadal hindcasts with moderate skill. Here we test the hypothesis that computationally inexpensive data-driven models, such as multi-variate singular spectrum analysis (MSSA), which takes care of trends and oscillations, performs similar to GCMs. We pick up one of the most complex variables having low predictability, Indian summer monsoon rainfall (ISMR) and its possible causal sea surface temperatures (SST). We find that the MSSA approach performs similar to the GCMs in simulating SSTs beyond their nonlinear limits of predictability, which is ∼12 months. These SSTs are used for decadal predictions of ISMR and show improved skills compared to the GCMs. We conclude that data-driven models are possible alternatives to computationally expensive GCMs for decadal predictions.

Vegetation distribution, composition and health in arid regions are largely dependent on water availability controlled by climate, local topography and geology. Despite a general understanding of climatic and geologic drivers in plant communities, trends in plant responses to water distribution and storage across areas under different local controls are poorly understood. Here we investigate the multi-decadal interactions between spatial heterogeneity of geologic controls and temporal variation of climate, and their impacts on water availability to vegetation and plant responses (via normalized difference vegetation index, NDVI) in a monsoon-driven arid region of southeastern Arizona. We find that grasslands display low NDVI and respond directly to monsoonal rainfall. In the uplands, vegetation on west-facing slopes and in canyons share similar NDVI averages and variability, suggesting that they both use water from surface-groundwater flow paths through fractured rocks. Along the San Pedro River, streamflow, groundwater, and NDVI in deciduous riparian woodlands are strongly responsive to monsoonal rainfall, but water availability stratifies between wet (perennial), intermediate, and dry reaches, underlain by different local geologic controls that affect water table elevation. These controls interact with the driving climate to affect water availability in the shallow alluvial aquifer of the riparian zone, a primary water source to the gallery phreatophytes. A recent shift toward a strengthened monsoon in the region has led to an increase in water availability for grasslands and for dry reaches of the San Pedro, while the benefit is more muted along wetter reaches, where the riparian forest shows signs of having reached its maturity, with diminished trends in NDVI. These results have implications for the future vulnerability of dryland vegetation to climate change, which may be either dampened or intensified by local controls such as geology.

The stratospheric, tropospheric and surface impacts from the 11 year ultraviolet solar spectral irradiance (SSI) variability have been extensively studied using climate models and observations. Here, we demonstrate using idealized model simulations that the Pacific Decadal Oscillation (PDO), which has been shown to impact the tropospheric and stratospheric circulation from sub-decadal to multi-decadal timescales, strongly modulates the solar-induced atmospheric response. To this end, we use a high-top version of the coupled ocean–atmosphere Norwegian Climate Prediction Model forced by the SSI dataset recommended for Coupled Model Intercomparison Project 6. We perform a 24-member ensemble experiment over the solar cycle 23 in an idealized framework. To assess the PDO modulation of the solar signal, we divide the model data into the two PDO phases, PDO+ and PDO−, for each solar (maximum or minimum) phase. By compositing and combining the four categories, we hence determine the component of the solar signal that is independent of the PDO and the modulation of the solar signal by the PDO, along with the solar signal in each PDO phase. Reciprocally, we determine the PDO effect in each solar phase. Our results show that the intensification of the polar vortex under solar maximum is much stronger in the PDO− phase. This signal is transferred into the troposphere, where we find a correspondingly stronger polar jet and weaker Aleutian Low. We further show that the amplification of the solar signal by the PDO− phase is driven by anomalous meridional advection of solar-induced temperature anomalies over northern North America and the North Pacific, which contributes to a decreased meridional eddy heat flux and hence to a decreased vertical planetary wave flux into the stratosphere.

Global warming leads to drastic changes in the diversity and structure of Arctic plant communities. Studies of functional diversity within the Arctic tundra biome have improved our understanding of plant responses to warming. However, these studies still show substantial unexplained variation in diversity responses. Complementary to functional diversity, phylogenetic diversity has been useful in climate change studies, but has so far been understudied in the Arctic. Here, we use a 25 year warming experiment to disentangle community responses in Arctic plant phylogenetic β diversity across a soil moisture gradient. We found that responses varied over the soil moisture gradient, where meadow communities with intermediate to high soil moisture had a higher magnitude of response. Warming had a negative effect on soil moisture levels in all meadow communities, however meadows with intermediate moisture levels were more sensitive. In these communities, soil moisture loss was associated with earlier snowmelt, resulting in community turnover towards a more heath-like community. This process of 'heathification' in the intermediate moisture meadows was driven by the expansion of ericoid and Betula shrubs. In contrast, under a more consistent water supply Salix shrub abundance increased in wet meadows. Due to its lower stature, palatability and decomposability, the increase in heath relative to meadow vegetation can have several large scale effects on the local food web as well as climate. Our study highlights the importance of the hydrological cycle as a driver of vegetation turnover in response to Arctic climate change. The observed patterns in phylogenetic β diversity were often driven by contrasting responses of species of the same functional growth form, and could thus provide important complementary information. Thus, phylogenetic diversity is an important tool in disentangling tundra response to environmental change.

A growing body of evidence shows that more intensive dairy systems can be good for both nature and people. Little research considers whether such systems correspond with local priorities and preferences. Using a mixed methods approach, this study examined the effects of three intensification scenarios on milk yield and emission intensities in Kenya and Tanzania. Scenarios included (a) an incremental change to feed management; (b) adaptive change by replacing poor quality grass with nutrient-rich fodder crops; and (c) multiple change involving concurrent improvements to breeds, feeds and concentrate supplementation. These scenarios were co-constructed with diverse stakeholder groups to ensure these resonate with local preferences and priorities. Modelling these scenarios showed that milk yield could increase by 2%–15% with incremental changes to over 200% with multiple changes. Greenhouse gas emission intensities are lowest under the multiple change scenario, reducing by an estimated 44%. While raising yields, incremental change conversely raises emission intensities by 9%. Our results suggest that while future interventions that account for local priorities and preferences can enhance productivity and increase the uptake of practices, far-reaching shifts in practices are needed to reduce the climatic footprint of the dairy sector. Since top-down interventions does not align with local priorities and preferences in many situations, future low-emission development initiatives should place more emphasis on geographic and stakeholder heterogeneity when designing targeting and implementation strategies. This suggests that in low-income countries, bottom-up approaches may be more likely to improve dairy productivity and align with mitigation targets than one-size-fits-all approaches.

Flash droughts can be distinguished by rapid intensification from near-normal soil moisture to drought conditions in a matter of weeks. Here, we provide the first characterisation of a climatology of flash drought across Australia using a suite of indices. The experiment is designed to capture a range of conditions related to drought: evaporative demand describes the atmospheric demand for moisture from the surface; precipitation, the supply of moisture from the atmosphere to the surface; and evaporative stress, the supply of moisture from the surface relative to the demand from the atmosphere. We show that regardless of the definition, flash droughts occur in all seasons. They can terminate as rapidly as they start, but in some cases can last many months, resulting in a seasonal-scale drought. We show that flash-drought variability and its prevalence can be related to phases of the El Niño–Southern Oscillation, highlighting scope for seasonal-scale prediction. Using a case study in southeast Australia, we show that monitoring precipitation is less useful for capturing the onset of flash drought as it occurs. Instead, indices like the Evaporative Demand Drought Index and Evaporative Stress Index are more useful for monitoring flash-drought development.

The Atlantic warm pool (AWP) has profound impacts on extreme weather events and climate variability. Factors influencing the AWP and its predictability are still not fully understood. Other than local ocean–atmosphere feedbacks and El Niño Southern Oscillation, we find an extratropical precursor from the Northeast Pacific (known as the Blob), which leads the AWP by 1 year with a robust correlation (r = 0.68). A suite of Northeast Pacific pacemaker experiments successfully reproduces the leading influence of the Blob on the AWP. The preceding summer Blob-related sea surface temperature (SST) warming signal can be transmitted towards the lower latitudes through the seasonal footprint mechanism, leading to the central Pacific warming in the winter and following spring. Such a strong tropical Pacific SST heating excites an anomalous atmospheric wave train that resembles the Pacific/North American (PNA) teleconnection pattern. At the downstream portion of the PNA, the low sea surface pressure anomalies can be found over the AWP region during the following spring. The anomalous low initiates the AWP SST warming, and the AWP warmer SST can persist into summer and is further amplified due to ocean–atmosphere feedbacks. Our results show that the North Pacific Blob may act as a useful predictor of the AWP 1 year in advance through trans-basin interactions. A Blob-based prediction model shows considerable hindcast skill for the observed AWP SST anomaly.

Environmental degradation has been associated with increased burden of diseases such as malaria, diarrhea, and malnutrition. As a result, some have argued that continuing ecosystem change could undermine successes in global health investments. Here we conduct an empirical study to investigate this concern. Child deaths due to diarrhea have more than halved since the year 2000, partly due to increased access to improved water, sanitation and hygiene (WASH). We examine how the effectiveness of a water quality treatment may vary as a function of upstream watershed condition. We use data on occurrence of diarrhea and point-of-use water treatment methods from the Demographic and Health Surveys for Haiti and Honduras. We integrate these data with a variable that reflects the influence of upstream tree cover on surface water quality. Point-of-use chlorination is significantly associated with 3.4 percentage points reduction in prevalence of diarrheal disease on average. However, we only detect a significant reduction in diarrheal prevalence when upstream watersheds are moderately forested. At low upstream tree coverage, point-of-use water chlorination does not have significant effects, suggesting that forest clearing could undermine its effectiveness at reducing childhood diarrhea. Our results suggest that forested watersheds may reduce water-borne sediments and contaminants, and thus improve raw water quality in ways that moderate the effectiveness of water quality treatment. Watershed protection should be considered in WASH investments, as deforested watersheds could undermine their effectiveness, particularly in parts of low-income countries where access to improved WASH services is challenging.

Floods that cause yearly economic losses and casualties have increased in frequency with global warming. Assessing the mortality risks of populations due to flooding is important and necessary for risk management and disaster reduction. Thus, this paper develops a method for assessing global mortality risks due to river flooding. Global historical annual death tolls are first estimated during the historical period 1986–2005 (T₀) by using available mortality vulnerability functions of river flooding. Then, the best vulnerability function is selected according to lower root mean square errors (RMSE) and the differences in the multi-year mean (DMYM) values. Next, the adjustment coefficient K_c for each country (region) is calculated to use in the revision of the selected vulnerability function. Finally, the mortality risks are estimated based on an adjusted vulnerability function. As a case, the paper assessed and analysed the global mortality risks due to river flooding during 2016–2035 (2030s) and 2046–2065 (2050s) for the combined scenario of the Representative Concentration Pathway 4.5 (RCP4.5) and the Shared Socioeconomic Pathway 2 (SSP2), and the RCP8.5-SSP5 scenario. The results show that the estimation errors of the death tolls in most countries (regions) decrease after adjusting the vulnerability function. Under the current defense capacity and vulnerability level, the average annual death tolls of RCP4.5-SSP2 and RCP8.5-SSP5 in the 2030s will increase by 1.05 times and 0.93 times compared with the historical period. They will increase 1.89 and 2.20 times, respectively for the two scenarios during 2050s. High-risk areas are distributed in the south-eastern Eurasia.

Climate science provides strong evidence of the necessity of limiting global warming to 1.5 °C, in line with the Paris Climate Agreement. The IPCC 1.5 °C special report (SR1.5) presents 414 emissions scenarios modelled for the report, of which around 50 are classified as '1.5 °C scenarios', with no or low temperature overshoot. These emission scenarios differ in their reliance on individual mitigation levers, including reduction of global energy demand, decarbonisation of energy production, development of land-management systems, and the pace and scale of deploying carbon dioxide removal (CDR) technologies. The reliance of 1.5 °C scenarios on these levers needs to be critically assessed in light of the potentials of the relevant technologies and roll-out plans. We use a set of five parameters to bundle and characterise the mitigation levers employed in the SR1.5 1.5 °C scenarios. For each of these levers, we draw on the literature to define 'medium' and 'high' upper bounds that delineate between their 'reasonable', 'challenging' and 'speculative' use by mid century. We do not find any 1.5 °C scenarios that stay within all medium upper bounds on the five mitigation levers. Scenarios most frequently 'over use' CDR with geological storage as a mitigation lever, whilst reductions of energy demand and carbon intensity of energy production are 'over used' less frequently. If we allow mitigation levers to be employed up to our high upper bounds, we are left with 22 of the SR1.5 1.5 °C scenarios with no or low overshoot. The scenarios that fulfil these criteria are characterised by greater coverage of the available mitigation levers than those scenarios that exceed at least one of the high upper bounds. When excluding the two scenarios that exceed the SR1.5 carbon budget for limiting global warming to 1.5 °C, this subset of 1.5 °C scenarios shows a range of 15–22 Gt CO₂ (16–22 Gt CO₂ interquartile range) for emissions in 2030. For the year of reaching net zero CO₂ emissions the range is 2039–2061 (2049–2057 interquartile range).

Rising emissions of anthropogenic greenhouse gases (GHG) have led to tropospheric warming and stratospheric cooling over recent decades. As a thermodynamic consequence, the troposphere has expanded and the rise of the tropopause, the boundary between the troposphere and stratosphere, has been suggested as one of the most robust fingerprints of anthropogenic climate change. Conversely, at altitudes above ∼55 km (in the mesosphere and thermosphere) observational and modeling evidence indicates a downward shift of the height of pressure levels or decreasing density at fixed altitudes. The layer in between, the stratosphere, has not been studied extensively with respect to changes of its global structure. Here we show that this atmospheric layer has contracted substantially over the last decades, and that the main driver for this are increasing concentrations of GHG. Using data from coupled chemistry-climate models we show that this trend will continue and the mean climatological thickness of the stratosphere will decrease by 1.3 km following representative concentration pathway 6.0 by 2080. We also demonstrate that the stratospheric contraction is not only a response to cooling, as changes in both tropopause and stratopause pressure contribute. Moreover, its short emergence time (less than 15 years) makes it a novel and independent indicator of GHG induced climate change.

Rain-on-snow (ROS) events occur primarily in cold climates such as high latitudes and high elevations where they pose a considerable threat to nature and society. The frequency and intensity of ROS events are expected to change in the future, but little is known about how they will change in the near future (mid-century) and their link to hydrological extremes (e.g. 95% high flows). Here we use kilometre-scale regional climate simulations over Norway, a ROS 'hot spot', to determine potential changes in ROS frequency and intensity in the middle of the century under RCP8.5. Analysis shows that ROS will intensify in the future and ROS frequency will increase at high elevations and occur less frequently at lower elevations. Furthermore, high-flows that coincide with ROS events are expected to increase in winter and autumn. In general, this study shows that ROS changes in winter and autumn are related to changes in rain while ROS changes in spring and summer are related to changes in the snowpack. Since rainfall in Norway is dominated by large scale processes in autumn and winter (e.g. North Atlantic storm tracks), it is likely that future changes in ROS climatology in autumn and winter are related to changes in the large scale atmospheric system. This contrasts with spring and summer when local-scale processes drive snowmelt and hence future changes to ROS in those seasons.

We analyze the projected sea level rise (SLR) for the 21st century for the China Seas (the Bohai Sea, Yellow Sea, East China Sea, and South China Sea) using the Coupled Model Intercomparison Project Phase 5 dataset. We find that the projected SLR over the shallow continental shelves of the China Seas is nearly the same as the global mean sea level change in all future emission scenarios, with a magnitude of 43.6 cm (20.8–67.7 cm, 90% confidence interval) in RCP2.6 and 74.5 cm (41.7–112.8 cm, 90% confidence interval) in RCP8.5 by the year 2100 relative to 1986–2005. We further analyze the causes of SLR and find that more than 90% of the total projected SLR over the continental shelves of the China Seas will result from mass contributions and only a minor contribution will result from local steric height adjustments. This increase in water mass over the continental shelves is not only caused by the loss of land ice, but also from the change in sterodynamic, which tends to push water mass onto the continental shelves from the open oceans.

Sea level rise increases coastal cities' exposure to tidal flooding and elevates the risk of transportation routes being compromised at high tide. Using Miami, Florida as a case study, we combine tide gauge, elevation, road network, and worker location data with a route optimization algorithm to model how tidal flooding affected commute times between 2002–2004 and 2015–2017. Results suggest tidal flooding increases annual commutes by 15 min on average and 274 min among the most heavily impacted areas. Additionally, approximately 14 000 commuters may be unable to reach their workplace due to tidal flooding at least once per year. Accommodation via dynamic adjustments in residential and work locations may reduce tidal commuting delays by as much as 70%, particularly among the highest earners. Many of the most affected areas do not experience flooding directly, expanding the purview of vulnerability beyond simple residential risk. Using 2060 extreme sea-level rise scenarios without accommodating behavior, mean annual commute delays are expected to reach 220 min with over 55 000 commuters potentially unable to reach their destinations.

To reduce local air pollution, many ports in developed countries require berthed ships to use shore-based electricity instead of burning diesel to meet their electricity requirement for loads such as lights, cargo-handling equipment, and air conditioning. The benefits of this strategy in developing countries remain understudied. Based on government data for all major ports in India, we find that switching from high-sulfur fuel to shore power reduces hoteling emissions of particulate matter (PM_2.5) by 88%; SO₂ by 39%; NO_x by 85%; but increases CO₂ emissions by 12%. Switching from low-sulfur fuel reduces hoteling emissions of PM_2.5 by 46% and NO_x by 84% but increases SO₂ emissions by 240% and CO₂ emissions by 17%. The lifetime cost savings from the switch to electricity are $73 M for high-sulfur fuel and $370 M for low-sulfur fuel. We estimate that switching from high-sulfur fuel to shore power might avoid at most a couple of dozen premature deaths each year, whereas switching from low-sulfur fuel could lead to a slight increase in premature mortality. Therefore, policymakers must first clean up power generation for shore power to be a viable strategy to improve air quality in Indian port cities.

Extensive literature has highlighted the difficulty in operating baseload power plants—especially coal-fired units—in a decarbonized electric power system with a high share of variable renewable energy, with some of it recommending immediate coal phaseouts. However, the coal fleet across China is large and young, making its imminent phaseout unrealistic. Moreover, power system operators and policy makers face other constraints in their pursuit of energy system decarbonization—chief among them the need to achieve high levels of reliability—something coal units could provide. We assess the persistence of coal in a decarbonizing power system under various retrofit scenarios that seek to enhance the flexibility of coal units: after all, energy transitions do not occur in a vacuum and owners of coal power plants will likely pursue innovations to extend the lifetimes and profits of their assets, even as the wider energy transition unfolds. We evaluate the economic and environmental impacts of improving coal power unit flexibility in Jiangsu's power system under four levels of renewable energy penetration and three scopes of coal flexibility retrofits. Our results show that coal units persist even at very high renewable penetrations, and retrofits help them reduce power system costs, enable renewable energy integration, and marginally cut emissions. Smaller coal units become peaker rather than baseload units, providing the power system with flexibility rather than just energy. Our results show how challenging the low-carbon transition is likely to be without outright phaseouts of coal generation.

Forests play an important role in maintaining rainfall patterns worldwide by recycling water back to the atmosphere through evapotranspiration. We present a novel spatiotemporal data-driven model and assessment of the impacts of various deforestation scenarios on rainfall patterns in sub-Saharan Africa, where rainfed agriculture is the main source of income and provides food for a large part of the population. Our model is based on the convolutional long short term memory neural network and uses a combination of climate and vegetation time-series data to predict rainfall and to perform simulation experiments. Our results show that complete deforestation (i.e. conversion of all humid forests to short grasslands) would greatly reduce rainfall magnitude in the deforested areas. Above the equator, the large majority of areas not currently forested would also receive less rainfall. However, complete deforestation would slightly increase rainfall in some parts of Southern Africa and decrease it in other parts. The impacts of partial deforestation also differ across Africa. In West Africa, even moderate tree cover loss (i.e. 30%) reduces rainfall magnitude whereas in Central and Southern Africa, a threshold of 70% tree cover loss is required to reduce rainfall magnitude. Deforestation of remaining humid rainforest areas is thus likely to dramatically affect rainfed agriculture across the continent, in particular in the maize-based cropping systems north of the equator.

Essential nutrients, including carbohydrates, proteins, fats, vitamins, and minerals, are required for human health and development. Inadequate intake can negatively affect development and result in a wide range of adverse health outcomes. Rice, maize, and wheat provide over 60% of the world's food energy intake. Atmospheric carbon dioxide (CO₂), water, nitrogen, and soil micronutrients are the basis of this plant material. Since 1850–1900, CO₂ concentrations have increased about 50%, with most of that increase since 1950. Higher CO₂ concentrations increase photosynthesis, which then increases plant biomass, but also alters the nutritional quality of wheat, rice, and other C3 plants. We review the possible impacts of rising CO₂ concentrations on human health, highlight uncertainties, and propose a research agenda to maintain the nutritional quality of C3 plants. We also synthesize options for addressing this critical challenge to nutritional safety and security. A complete research agenda requires addressing data and knowledge gaps surrounding plant biology and policy responses. Data on key nutrients are lacking, leading to a limited mechanistic understanding of the response of the plant ionome to elevated CO₂ concentrations. Regular data are largely missing on nutritional status and food safety in low- and middle-income countries, limiting assessments of the magnitude of the risks. Research opportunities to fill gaps in data and understanding include herbaria studies, field-based natural and manipulative studies, leveraging natural plant variability, and innovations in seed quality. Improved models of cereal crop nutritional quality can project the magnitude and direction of possible future challenges; incorporating the effects of climate change into those models can further improve their robustness. Transdisciplinary research involving at least ecologists, plant physiologists, economists, and experts in human nutrition is essential for developing a systems-based understanding of the potential impacts of rising CO₂ concentrations for human nutrition and the attendant consequences for achieving the sustainable development goal on food security.

Tropical deforestation is mainly driven by agricultural expansion, land grabbing, illegal logging, urbanization, cattle ranching as well as mining. However, extraction of minerals and its impacts in high biodiversity regions are still poorly known, particularly in Colombia, a tropical megadiverse hotspot. Here, using high-resolution datasets of forest cover changes and detailed geospatial mining data for Colombia, we show a growing contribution of legal mining to national deforestation: 3.4% over the 2001–2018 period, with a peak at 5.6% in 2017. During this period, around 121 819 ha have been deforested inside legal mining concessions, and an estimation of over 400 000 ha deforested by both legal and illegal. Gold and coal are the most important legally-mined materials in Colombia associated to deforestation, particularly in the recent years with 511% and 257% tree cover loss increases respectively (average over 2016–2018 compared to 2001–2015 average of mined material deforestation average). Three Colombian departments summed out ∼70% of the national deforestation occurring in legal concessions: in 2018, up to 23% of deforestation in Antioquia was taking place in legal mines (gold producer). Finally, we found that only 1% (respectively, 3%) of the concessions contribute to 60% (>90%) of the legal mining-related deforestation, mainly driven by large clearings to agriculture. Environmental law enforcement, monitoring activities and engaging the mining industry in effective forest conservation and landscape restoration strategies are urgently needed in Colombia for preserving biodiversity and ecosystem services.

Understanding the causes and consequences of environmental change is one of the key challenges facing researchers today as both types of information are required for decision making and adaptation planning. This need is particularly poignant in high latitude regions where permafrost thaw is causing widespread changes to local environments and the land-users who must adapt to changing conditions to sustain their livelihoods. The inextricable link between humans and their environments is recognized through socio-ecological systems research, yet many of these approaches employ top-down solutions that can lead to local irrelevance and create tensions amongst groups. We present and employ a framework for the use both of scientific and community-based knowledge sources that provides an enriched and thematic understanding of how permafrost thaw will affect northern land-users. Using geospatial modeling of permafrost vulnerability with community-based data from nine rural communities in Alaska, we show that permafrost thaw is a major driver of hazards for land-users and accounts for one-third to half of the hazards reported by community participants. This study develops an integrated permafrost-land-user system, providing a framework for thematic inquiry for future studies that will add value to large-scale institutional efforts and locally relevant observations of environmental change.

To reduce human exposure to particulate matter (PM), governments have enacted various preventive measures, to which a warning system is central. To the best of our knowledge, we are the first to assess the effectiveness of mobile-based warning systems on respiratory health outcomes, examining two types of ${\text{P}}{{\text{M}}_{2.5}}$ (particles less than $2.5\,\mu {\text{m}}$ in diameter) alerts via text messaging systems: Wireless Emergency Alert (WEA) and Air Quality Information Text (AIT) as employed in South Korea from January 2015 to October 2019. We used a generalized additive model to control the non-linear relationship between the ${\text{P}}{{\text{M}}_{2.5}}$ level and the number of hospital visits and admissions for four respiratory sicknesses—chronic obstructive pulmonary disease, respiratory tract infection, asthma, and pneumonia—while deciphering how such visits and admissions are reduced by the warning systems. Our results found that both systems reduced the number of new patients with the four sicknesses at a 5% statistical significance level. Of the two, WEA was found to be more effective than AIT. The former reduced the number of new patients by 16.4%, while the latter did so by 2.8%. WEA is for everyone with a cell phone connection. By sending simple and direct alerts to a broader range of people, WEA would help people to reduce the chance of short-term exposure to PM in general. The findings provide evidence with policy implications regarding air pollution adaptation.

Groundwater extraction has grown tremendously in Saudi Arabia to meet the irrigation water demand since the 1980s, and irrigation is one of the major anthropogenic factors modulating regional hydroclimate. However, the link between irrigation and hydroclimate is not well understood in a dry region such as Saudi Arabia. In this study, we utilize three different regional climate models to explore the physical mechanisms behind the irrigation impacts in this region. The results are robust across models and show that when irrigation is applied, wetter soil results in higher evapotranspiration and cools the lower atmosphere, leading to an anomalous pressure field and alters vapor transportation. Precipitation decreases locally because of the local cooling effect, whereas additional water vapor convergence enhances precipitation west to the irrigated region. This west–east contrast of precipitation change indicates a possible link between irrigation expansion in the 1980s and subsequent decadal precipitation variations in central Saudi Arabia. We further find from observations a decadal west–east contrast of precipitation changes in Saudi Arabia to support the similar finding in the models. This study implies the importance of including anthropogenic water management in climate models and provides a better understanding of how irrigation impacts local-to-regional climate.

Decreased availability of forage, as well as increased pesticide exposure, are important factors in the decline of honey bee health. Here, we isolate land cover transitions and their effect on honey production at 160 commercial apiaries in the Northern Great Plains. We found that land cover changes from 2008 to 2012 caused an annual decline in honey yields of 0.9% in the study area. Transitions from grassland to soybean (but not corn) were particularly detrimental to honey yields, potentially due to bee contact with pesticides within and around agricultural fields. When our results are applied to known apiary locations across all of North Dakota (U.S.A.), we estimate a 2.5% (1.6 million USD) decline in 2012 honey yields due to land cover changes occurring between 2008 and 2012. Even when controlling for changes in land cover, we found that on average colonies in the study area experienced a 14% annual decline in honey yields. We discuss possible explanations for these non-land-cover-related honey yield declines, including changing economic conditions (e.g. pollination services), changes in land management (e.g. pesticides), and increases in pests or diseases.

Aircraft produce condensation trails, which are thought to increase high-level cloudiness under certain conditions. However the magnitude of such an effect and whether this contributes substantially to the radiative forcing due to the aviation sector remain uncertain. The very substantial, near-global reduction in air traffic in response to the COVID-19 outbreak offers an unprecedented opportunity to identify the anthropogenic contribution to the observed cirrus coverage and thickness. Here we show, using an analysis of satellite observations for the period March–May 2020, that in the 20% of the Northern Hemisphere mid-latitudes with the largest air traffic reduction, cirrus fraction was reduced by ∼9 ± 1.5% on average, and cirrus emissivity was reduced by ∼2 ± 5% relative to what they should have been with normal air traffic. The changes are corroborated by a consistent estimate based on linear trends over the period 2011–2019. The change in cirrus translates to a global radiative forcing of 61 ± 39 mW m⁻². This estimate is somewhat smaller than previous assessments.

A global surge in 'artisanal', smallscale mining (ASM) threatens biodiverse tropical forests and exposes residents to dangerous levels of mercury. In response, governments and development agencies are investing millions (USD) on ASM formalization; registering concessions and demarcating extraction zones to promote regulatory adherence and direct mining away from ecologically sensitive areas. The environmental outcomes of these initiatives are seldom systematically assessed. We examine patterns of mining-related deforestation associated with formalization efforts in a gold-rich region of the Peruvian Amazon. We track changes from 2001 to 2014 when agencies: (a) issued 1701 provisional titles and (b) tried to restrict mining to a >5000 km² 'corridor'. We use fixed-effect regression models and matching methods to control for gold price, geology, and accessibility. Mining increased dramatically during this period, clearing ∼40 000 ha of forest. After the mining corridor was declared and enforcement increased, new mining sites were opened more frequently within titled areas and inside the corridor than elsewhere. However, mining also increased in protected area buffer zones and native communities, and the proportion of mining area occurring outside the corridor grew, concentrated in a few hotspots. Interviews (n = 47) revealed that the hoped-for regulatory adherence failed to materialize because miners who were issued provisional titles started operations without complying with attendant environmental rules. Overlapping land claims for agriculture and forest extraction proved a major obstacle for obtaining full legal rights to mine. Miners resented the slow, costly formalization process but many sought titles to bolster territorial claims, avoid policing, obtain credit and recruit paying 'guest' miners who generally ignored regulations. We find that responses to formalization varied with changing context and while formalization may curb mining in some circumstances, it may exacerbate it in others. Without adequate enforcement, interagency coordination, and attention to competing land claims, formalizing ASM may accelerate ecological destruction.

Global coastlines potentially contain significant amounts of plastic debris, with harmful implications for marine and coastal ecosystems, fisheries and tourism. However, the global amount, distribution and origin of plastic debris on beaches and in coastal waters is currently unknown. Here we analyze beaching and resuspension scenarios using a Lagrangian particle transport model. Throughout the first 5 years after entering the ocean, the model indicates that at least 77% of positively buoyant marine plastic debris (PBMPD) released from land-based sources is either beached or floating in coastal waters, assuming no further plastic removal from beaches or the ocean surface. The highest concentrations of beached PBMPD are found in Southeast Asia, caused by high plastic inputs from land and limited offshore transport, although the absolute concentrations are generally overestimates compared to field measurements. The modeled distribution on a global scale is only weakly influenced by local variations in resuspension rates due to coastal geomorphology. Furthermore, there are striking differences regarding the origin of the beached plastic debris. In some exclusive economic zones (EEZ), such as the Indonesian Archipelago, plastic originates almost entirely from within the EEZ while in other EEZs, particularly remote islands, almost all beached plastic debris arrives from remote sources. Our results highlight coastlines and coastal waters as important reservoirs of marine plastic debris and limited transport of PBMPD between the coastal zone and the open ocean.

Soil water and root distribution following revegetation are key research topics in water-limited ecosystems. However, little is known about the interaction between soil water and root distribution in deep soils under different precipitation conditions. Knowledge of the root–soil water relationship of revegetated land and its response to precipitation is crucial for the management of water resources and ecological restoration worldwide, including on the Chinese Loess Plateau. In this study, we investigated soil water and root distribution under apple orchard and black locust down a 10 m soil profile and exposed to different amounts of annual precipitation on the Loess Plateau. The results showed that soil water content (SWC) under two typical planted forests both significantly decreased as the mean annual precipitation (MAP) decreased. SWC spatial variation is demarcated by a 500–550 mm precipitation threshold, being relatively high when MAP > 550 mm but extremely low when MAP < 500 mm. In apple orchards, the depth above which 50% of the roots were present increased with increasing precipitation, but in black locust it became shallower. The results of a linear mixed model revealed a significant relationship between fine root length density and SWC depletion degree for black locust irrespective of the amount of precipitation, but it was only found in the 200–1000 cm soil layers with MAP > 550 mm and the 0–200 cm soil layers with MAP < 550 mm for apple orchards. The MAP × depth interaction was significant with respect to SWC depletion degree for MAP > 550 mm, but not for MAP < 550 mm in both vegetation types. These findings add to our current understanding of the root–soil water relationship of species used for revegetation and highlight the need to assess the long-term effect of revegetation on soil water consumption in water-limited ecosystems.

A reduction in the overall carbon intensity (CI) of a crop-based biofuel can be achieved by cutting down the CI of the biofuel's feedstock, which in turn correlates significantly to agricultural management practices. Proposals are being made to incentivize low-carbon biofuel feedstocks under U.S. fuel regulatory programs to promote sustainable farming practices by individual farms. For such an incentive scheme to function properly, robust data collection and verification are needed at the farm level. This study presents our collaboration with U.S. private sector companies to collect and verify the corn production data necessary for feedstock-specific CI calculation at the farm level, through a carefully designed questionnaire, to demonstrate the practicality and feasibility of data collection at scale. We surveyed 71 farms that produced 0.2 million metric tons of corn grain in 2018 in a Midwestern U.S. state to obtain information on key parameters affecting corn ethanol feedstock CI, such as grain yields, fertilizer/chemical application rates, and agronomic practices. Feedstock-specific CI was calculated in the unit of grams (g) CO₂ equivalent (CO₂e) of greenhouse gases per kilogram (kg) of corn produced. Results showed large CI variations—from 119 to 407 g CO₂e kg⁻¹ of corn—due to the farm-level inventory, while the production-weighted average CI for all surveyed farms was 210 g CO₂e kg⁻¹, comparable to the national average CI of 204 g CO₂e kg⁻¹. The nitrogen fertilizer type applied and rate were identified as key factors contributing most to CI variations at the farm level. The estimated N₂O emissions from fertilizer and biomass nitrogen inputs to soil accounted for 51% of the overall farm-level CI and therefore need to be better monitored at farm level with high resolution. We concluded that this feedstock-specific, farm-level CI evaluation has the potential to be used to incentivize low-carbon feedstock for biofuel production.

Winter storm Uri brought severe cold to the southern United States in February 2021, causing a cascading failure of interdependent systems in Texas where infrastructure was not adequately prepared for such cold. In particular, the failure of interconnected energy systems restricted electricity supply just as demand for heating spiked, leaving millions of Texans without heat or electricity, many for several days. This motivates the question: did historical storms suggest that such temperatures were known to occur, and if so with what frequency? We compute a temperature-based proxy for heating demand and use this metric to answer the question 'what would the aggregate demand for heating have been had historic cold snaps occurred with today's population?'. We find that local temperatures and the inferred demand for heating per capita across the region served by the Texas Interconnection were more severe during a storm in December 1989 than during February 2021, and that cold snaps in 1951 and 1983 were nearly as severe. Given anticipated population growth, future storms may lead to even greater infrastructure failures if adaptive investments are not made. Further, electricity system managers should prepare for trends in electrification of heating to drive peak annual loads on the Texas Interconnection during severe winter storms.

Forests are subject to a range of management practices but it is unclear which produce the most rapid rates of regrowth across heterogeneous moisture gradients produced by regional climate and complex terrain. We analyzed recovery rates of satellite derived net primary productivity (NPP) over 27 years for 26 069 individual silvicultural treatments (stands) across the western U.S. at a 30 m resolution. Rates of NPP recovery and forest regrowth were on average 116% higher in wet landscapes with lower annual climatic water deficits (8.59 ± 5.07 gC m⁻² yr⁻², median ± inter-quartile range) when compared to dry landscapes (3.97 ± 2.67 gC m⁻² yr⁻²). This extensive spatial analysis indicates that hydroclimate is a dominant driver of forest regrowth and that responses can be highly nonlinear depending upon local climate conditions. Differences in silvicultural treatment also strongly controlled rates of regrowth within hydroclimatic settings; microclimates produced by shelterwood treatments maximized regrowth in dry landscapes whereas regrowth following clearcutting was among the fastest in wet landscapes due to enhanced energy availability. Conversely, commercial thinning regrowth rates were insensitive to hydroclimate and relatively consistent across the western U.S. Planting had a differential effect on forest structure and rates of regrowth across hydroclimate with negative effects in wet environments and positive effects in dry environments. In aggregate, this study provides a novel remote sensing approach for characterizing forest regrowth dynamics across climatic gradients and the common treatment options employed.

Increasing population and a severe water crisis are imposing growing pressure on Iranian cropping systems to increase crop production to meet the rising demand for food. Little is known about the separate contribution of trends and variability of the harvested area and yield to crop production in severely drought-prone areas such as Iran. In this study we (a) quantify the importance of harvested area and yield on trends and variability of crop production for the 12 most important annual crops under rainfed and irrigated conditions and (b) test how well the variability in annual crop areas can be explained by drought dynamics. We use remote sensing based land cover and evapotranspiration products derived from the Moderate Resolution Imaging Spectroradiometer to quantify the extent of cropland and drought severity as well as survey-based, crop-specific reports for the period 2001–2016 in Iran. The intensity of drought stress was estimated using the annual ratio between actual and potential evapotranspiration. We found that trends in the production of specific crops are predominantly explained by trends in harvested crop area. Besides, the variability in the harvested area contributed significantly more to the variability in crop production than the variability in crop yields, particularly under rainfed conditions (seven out of nine crops). In contrast, variability in the production of heavily subsidized crops such as wheat was predominantly explained by yield variability. Variability in the annual cropland area was largely explained by drought, in particular for the more arid regions in the south of the country. This highlights the importance of better and proactive drought management to stabilize crop areas and yields for sufficient food production in Iran.

We investigate linear trends in Antarctic skin temperatures (temperatures from about the top millimeter of the surface) over the four seasons using ERA5 ensemble mean reanalysis data. During 1950–2020, statistically significant warming occurred over East and West Antarctica in spring, autumn and winter, and over the Antarctic Peninsula in autumn and winter. A surface energy budget analysis revealed that increases in downward longwave radiation related to increases in air temperature and total column integrated cloud had a key role in Antarctic surface warming. There were negative sea level pressure trends around the periphery of Antarctica throughout the year, and the associated circulation contributed to warm advection from the middle latitudes to West Antarctica and the Antarctic Peninsula. Over the interior of East Antarctica, increase in moisture advection from lower latitudes enhanced the low-level cloud cover. A two-dimensional parameter diagram showed that skin temperature trends for time segments longer than 30 years starting before 1960 exhibited statistically significant warming in autumn and winter in East and West Antarctica and the Antarctic Peninsula. In spring, West Antarctica also showed statistically significant warming for long segments. In summer, the Antarctic Peninsula had statistically significant warming trends for long segments and cooling trends for segments less than 30 years. For all the studied time intervals, when skin temperatures had statistically significant positive trends, increases in downward longwave radiation contributed more than 70% of the warming and vice versa. This result demonstrates that on all time and space scales, changes in downward longwave radiation associated with variations in air temperature and atmospheric moisture loading play a dominant role controlling skin temperatures.

The elevated summer heat sources over the Tibetan Plateau (TP) profoundly influence Asian monsoon and atmospheric general circulation. Model simulations and future changes of condensational latent heat released from precipitation and surface sensible heat (SH) over the eastern TP are investigated with 22 CMIP6 models' outputs. The models reproduce the mean precipitation pattern well, but the mean intensity is 65% excessive. The SH has scarcely been evaluated. We find that nearly half of the models cannot realistically capture the SH's spatial structure. The best six models in simulating the SH are the same models that best simulate surface air temperature. The models with high performance are selected to make a multi-model ensemble mean projection. Under the medium emission scenario (SSP2-4.5), the TP's future summer precipitation will likely increase, despite its weakening thermal forcing effect. The increasing precipitation is primarily due to the future enhancement in vertical moisture transport and surface evaporation. However, the greenhouse gases-induced top-heavy heating stabilizes the atmosphere and diminishes the TP's thermal forcing effect, weakening the circulation and upward motion. As such, the precipitation sensitivity is only a 2.7% increase per degree Celsius global warming. The projected SH will be likely unchanged in accord with the likely unaltered surface wind speed. These results have important implications for the future change of the water supplies in the heavily populated South and East Asian countries. They could help the modeling groups further improve the climate model performance in the highland regions.

The urgent need to accelerate the transition towards low-carbon energy is well understood. Government support for energy innovation has been an increasing focus of both policy and academic attention in recent years. The debate has focused on direct spending by governments on research and development (R&D). However, governments also support R&D indirectly, through tax credits. This source of government support has been overlooked in the academic and policy debate on energy innovation, in part because publicly available data on R&D tax credit expenditures typically do not enable the identification of spending specific to energy. This article provides the first published data on R&D tax credits in the energy sector, drawing on administrative data from Australia, Canada, Norway and the UK. This data shows that indirect support through tax credits can be a large source of support for innovation in fossil fuel extraction companies, though this differs by country. As a result, publicly available data on direct R&D spending by government can significantly understate government support for innovation in fossil fuel extraction. The article also presents patent data to show, for the UK and for Norway, that less than 5% of R&D activity in fossil fuel extraction firms is devoted to low-carbon technologies. The article concludes with the recommendation that governments should consider removing tax credit support for R&D activities that facilitate the extraction of fossil fuels.

Air pollution over the Seto Inland Sea (SIS) is among the most severe of any region in Japan and is considered to be affected by both long-range and local pollution. To unravel the long-term trends of aerosol pollution over this region, in this study, measurements from the moderate resolution imaging spectroradiometer instrument onboard the Terra satellite were analyzed over two decades, from 2001 to 2020. Fine-mode aerosol optical depth (AOD_f) was calculated to estimate the amount of aerosol produced by anthropogenic emissions. The results showed that the AOD_f over the SIS increased from 2001 to 2004, had a flat trend from 2005 to 2009, and decreased from 2010 to 2020. To clarify the impact of long-range transport from the Asian continent to the SIS, the AOD_f over the Yellow Sea was also investigated and was found to increase and level off during the 2000s, after which it decreased, especially after 2014. This decrease can be attributed to emission regulations in China. The above analysis suggests that the aerosol pollution status in the SIS during the late 2010s was similar to that during the early 2000s. Over the SIS, the lowest AOD_f value was found in 2020, with the values in January–March and June–July approximately 30% and 30%–60% lower than the average values during the same periods in 2018–2019, respectively. The reduction found in January–March could be related to the decline in the long-range transport with restrictions on human activity due to the COVID-19 pandemic. Meanwhile, the reduction during June–July could be related to the decline of local emission sources. Considering the large SO₂ decline in 2020, regulations on SO₂ emitted from ships that started from 1 January 2020 are one possible factor for the improvement of aerosol pollution over the SIS in 2020.

There is a strong link between nitrate (NO₃-N) leaching from fertilized annual crops and the rate of nitrogen (N) fertilizer input. However, this leaching-fertilizer relationship is poorly understood and the degree to which soil type, weather, and cropping system influence it is largely unknown. We calibrated the Agricultural Production Systems sIMulator process-based cropping system model using 56 site-years of data sourced from eight field studies across six states in the U.S. Midwest that monitored NO₃-N leaching from artificial subsurface drainage in two cropping systems: continuous maize and two-year rotation of maize followed by unfertilized soybean (maize-soybean rotation). We then ran a factorial simulation experiment and fit statistical models to the leaching-fertilizer response. A bi-linear model provided the best fit to the relationship between N fertilizer rate (kg ha⁻¹) and NO₃-N leaching load (kg ha⁻¹) (from one year of continuous maize or summed over the two-year maize-soybean rotation). We found that the cropping system dictated the slopes and breakpoint (the point at which the leaching rate changes) of the model, but the site and year determined the intercept i.e. the magnitude of the leaching. In both cropping systems, the rate of NO₃-N leaching increased at an N fertilizer rate higher than the N rate needed to optimize the leaching load per kg grain produced. Above the model breakpoint, the rate of NO₃-N leaching per kg N fertilizer input was 300% greater than the rate below the breakpoint in the two-year maize-soybean rotation and 650% greater in continuous maize. Moreover, the model breakpoint occurred at only 16% above the average agronomic optimum N rate (AONR) in continuous maize, but 66% above the AONR in the maize-soybean rotation. Rotating maize with soybean, therefore, allows for a greater environmental buffer than continuous maize with regard to the impact of overfertilization on NO₃-N leaching.

Global terrestrial vegetation is greening, particularly in mountain areas, providing strong feedbacks to a series of ecosystem processes. This greening has been primarily attributed to climate change. However, the spatial variability and magnitude of such greening do not synchronize with those of climate change in mountain areas. By integrating two data sets of satellite-derived normalized difference vegetation index (NDVI) values, which are indicators of vegetation greenness, in the period 1982–2015 across the Tibetan Plateau (TP), we test the hypothesis that climate-change-induced greening is regulated by terrain, baseline climate and soil properties. We find a widespread greening trend over 91% of the TP vegetated areas, with an average greening rate (i.e. increase in NDVI) of 0.011 per decade. The linear mixed-effects model suggests that climate change alone can explain only 26% of the variation in the observed greening. Additionally, 58% of the variability can be explained by the combination of the mountainous characteristics of terrain, baseline climate and soil properties, and 32% of this variability was explained by terrain. Path analysis identified the interconnections of climate change, terrain, baseline climate and soil in determining greening. Our results demonstrate the important role of mountainous effects in greening in response to climate change.

Western North American fires have been increasing in magnitude and severity over the last few decades. The complex coupling of fires with the atmospheric energy budget and meteorology creates short-term feedbacks on regional weather altering the amount of pollution to which Americans are exposed. Using a combination of model simulations and observations, this study shows that the severe fires in the summer of 2017 increased atmospheric aerosol concentrations leading to a cooling of the air at the surface, reductions in sensible heat fluxes, and a lowering of the planetary boundary layer height over land. This combination of lower-boundary layer height and increased aerosol pollution from the fires reduces air quality. We estimate that from start of August to end of October 2017, ∼400 premature deaths occurred within the western US as a result of short-term exposure to elevated PM_2.5 from fire smoke. As North America confronts a warming climate with more fires the short-term climate and pollution impacts of increased fire activity should be assessed within policy aimed to minimize impacts of climate change on society.

Heatwaves have implications for human health and ecosystem function. Over cities, the impacts of a heatwave event may be compounded by urban heat, where temperatures over the urban area are higher than their rural surroundings. Coastal cities often rely upon sea breezes to provide temporary relief. However, topographic features contributing to the development of Foehn-like conditions can offset the cooling influence of sea breezes. Using convection-permitting simulations (⩽4 km) we examine the potential for both mechanisms to influence heatwave conditions over the large coastal city of Sydney, Australia that is bordered by mountains. Heatwave onset in the hot period of January–February 2017 often coincides with a hot continental flow over the mountains into the city. The temperature difference between the coast and the urban–rural interface can reach 15.79 °C. Further, the urban heat island contributes on average an additional 1 °C in the lowest 1 km of the atmosphere and this often extends beyond the city limits. The cumulative heat induced by the urban environment reaches 10 °C over the city and 3 °C over adjacent inland areas. Strong sea breezes are important for heat dispersion with city temperature gradients reducing to within 1 °C. The resolution permits a comparison between urban types and reveals that the diurnal cycle of temperature, moisture content and wind are sensitive to the urban type. Here we show that convection permitting simulations can resolve the interaction between local breezes and the urban environment that are not currently resolved in coarser resolution models.

In agriculture, sustainability is framed as an aspiration to achieve multiple goals including positive production, environmental and social outcomes. These aspirations include: increasing production of nutritious food; minimising risk and maximising resilience in response to climate variability, fluctuating markets and extreme weather events; minimising impacts on global warming by reducing emissions; efficiently using limited resources; minimising negative on-site and off-site impacts; preserving biodiversity on farm and in nature; and achieving positive social outcomes reflected in farmers' incomes (revenue and profit). Here we used cropping systems simulation to assess multiple (11) sustainability indicators for 26 crop rotations to quantify their sustainability throughout Australia's subtropical cropping zone. Results were first expressed via a series of maps quantifying the minimal environmental impacts of attributes such as N applied, N leached, runoff and GHG emissions of the 26 crop rotations while identifying the locations of the optimal rotation for each attribute. Inspection of these maps showed that different rotations were optimal, depending on both location and the attribute mapped. This observation demonstrated that an 11-way sustainability win-win across all attributes was not likely to happen anywhere in the cropping zone. However, rotations that minimised environmental impacts were often among the more profitable rotations. A more holistic visualisation of the sustainability of six contrasting sites, using sustainability polygons, confirmed that trade-offs between sustainability indicators are required and highlighted that cropping in different sites is inherently more or less sustainable, regardless of the rotations used. Given that trade-offs between the various sustainability attributes of crop rotations are unavoidable, we plotted trade-off charts to identify which rotations offer an efficient trade-off between profit and other sustainability indicators. We propose that these maps, sustainability polygons and trade-off charts can serve as boundary objects for discussions between stakeholders interested in achieving the sustainable intensification of cropping systems.

The Great Barrier Reef (GBR) is a globally significant coral reef system supporting productive and diverse ecosystems. The GBR is under increasing threat from climate change and local anthropogenic stressors, with its general condition degrading over recent decades. In response to this, a number of techniques have been proposed to offset or ameliorate environmental changes. In this study, we use a coupled hydrodynamic-biogeochemical model of the GBR and surrounding ocean to simulate artificial ocean alkalinisation (AOA) as a means to reverse the impact of global ocean acidification on GBR reefs. Our results demonstrate that a continuous release of 90 000 t of alkalinity every 3 d over one year along the entire length of the GBR, following the Gladstone-Weipa bulk carrier route, increases the mean aragonite saturation state ($\Omega_\mathrm{ar}$) across the GBR's 3860 reefs by 0.05. This change offsets just over 4 years (∼4.2) of ocean acidification under the present rate of anthropogenic carbon emissions. The injection raises $\Omega_\mathrm{ar}$ in the 250 reefs closest to the route by ${\geqslant}0.15$, reversing further projected Ocean Acidification. Following cessation of alkalinity injection $\Omega_\mathrm{ar}$ returns to the value of the waters in the absence of AOA over a 6 month period, primarily due to transport of additional alkalinity into the Coral Sea. Significantly, our study provides for the first time a model of AOA applied along existing shipping infrastructure that has been used to investigate shelf scale impacts. Thus, amelioration of decades of OA on the GBR is feasible using existing infrastructure, but is likely to be extremely expensive, include as yet unquantified risks, and would need to be undertaken continuously until such time, probably centuries in the future, when atmospheric CO₂ concentrations have returned to today's values.

Long-term mitigation scenarios developed by integrated assessment models underpin major aspects of recent IPCC reports and have been critical to identify the system transformations that are required to meet stringent climate goals. However, they have been criticized for proposing pathways that may prove challenging to implement in the real world and for failing to capture the social and institutional challenges of the transition. There is a growing interest to assess the feasibility of these scenarios, but past research has mostly focused on theoretical considerations. This paper proposes a novel and versatile multidimensional framework that allows evaluating and comparing decarbonization pathways by systematically quantifying feasibility concerns across geophysical, technological, economic, socio-cultural and institutional dimensions. This framework enables to assess the timing, disruptiveness and scale of feasibility concerns, and to identify trade-offs across different feasibility dimensions. As a first implementation of the proposed framework, we map the feasibility concerns of the IPCC 1.5 °C Special Report scenarios. We select 24 quantitative indicators and propose feasibility thresholds based on insights from an extensive analysis of the literature and empirical data. Our framework is, however, flexible and allows evaluations based on different thresholds or aggregation rules. Our analyses show that institutional constraints, which are often not accounted for in scenarios, are key drivers of feasibility concerns. Moreover, we identify a clear intertemporal trade-off, with early mitigation being more disruptive but preventing higher and persistent feasibility concerns produced by postponed mitigation action later in the century.

Low-temperature weather accompanied by strong chill wind is considered as a great risk factor for human health in winter, especially in some extreme weather conditions. Based on the observation data and the NCEP/NCAR reanalysis data of air temperature and wind velocity in 1961–2019, the warming pause of wind chill temperature (WCT) in the 21st century in China is first revealed in this paper. A significant increasing trend of WCT is found during 1961–1999 (P1), and a slight decreasing trend in 1999–2019 (P2) is detected by a 21 year running trend analysis. The extreme cold WCT day (WCD) with the WCT index below the 10th percentile also shows a decreasing trend in P1 but a slight increasing trend in P2. Both the WCT and the extreme WCD consistently display the warming pause in seven climatic regions in China. That means the slowdown or even decrease of human bioclimatic temperature in recent two decades may lead to an increasing risk of frostbite and other cold-related diseases in the country. Both the decreasing trend of mean temperature and the increasing trend of the wind speed contribute to the slowdown of the human-perceived warming in the 21st century, and this conjoint contribution could be linked to the East Asian winter monsoon circulations over Siberia, i.e. the Siberian high. The variation of averaged sea level pressure over the central region of the Siberian high shows high consistency with both the WCT and the extreme WCD in the whole study period, by a decreasing rate of −1.28 hPa per decade in P1 and an increasing rate of 1.26 hPa per decade in P2.

The 2 °C and 1.5 °C temperature targets of the Paris Agreement can be interpreted as targets never to be exceeded, or as end-of-century targets. Recent literature proposes to move away from the latter, in favour of avoiding a temperature overshoot and the associated net negative emissions. To inform this discussion, we investigate under which conditions avoiding an overshoot is economically attractive. We show that some form of overshoot is attractive under a wide range of assumptions, even when considering the extra damages due to additional climate change in the optimisation process. For medium assumptions regarding mitigation costs and climate damages, avoiding net negative emissions leads to an increase in total costs until 2100 of 5% to 14%. However, avoiding overshoot only leads to some additional costs when mitigation costs are low, damages are high and when using a low discount rate. Finally, if damages are not fully reversible, avoiding net negative emissions can even become attractive. Under these conditions, avoiding overshoot may be justified, especially when non-monetary risks are considered.

Spatial data of urban green spaces (UGS) are critical for cities worldwide to evaluate their progress towards achieving the urban sustainable development goals on UGS. However, UGS maps at the global scale with acceptable accuracies are not readily available. In this study, we mapped UGS of all 1039 mid- and large-sized cities across the globe in 2015 with dense remote sensing data (i.e. 51 494 Landsat images) and Google Earth Engine (GEE) platform. Also, we quantified the spatial distribution and accessibility of UGS within the cities. By combining the greenest pixel compositing method and the percentile-based image compositing method, we were able to obtain the maximum extent of UGS in cities while better differentiating UGS from other vegetation such as croplands. The mean overall classification accuracy reached 89.26% (SD = 3.26%), which was higher than existing global land cover products. Our maps showed that the mean UGS coverage in 1039 cities was 38.46% (SD = 20.27%), while the mean UGS accessibility was 82.67% (SD = 22.89%). However, there was a distinctive spatial equity issue as cities in high-income countries had higher coverage and better accessibility than cities in low-income countries. Besides developing a protocol for large-scale UGS mapping, our study results provide key baseline information to support international endeavors to fulfill the relevant urban sustainable development goals.

A heat danger day is defined as an extreme when the heat stress index (a combined temperature and humidity measure) exceeding 41 °C, warranting public heat alerts. This study assesses future heat risk (i.e. heat danger days times the population at risk) based on the latest Coupled Model Intercomparison Project phase 6 projections. In recent decades (1995–2014) China's urban agglomerations (Beijing-Tianjin-Hebei, Yangtze River Delta, Middle Yangtze River, Chongqing-Chengdu, and Pearl River Delta (PRD)) experienced no more than three heat danger days per year, but this number is projected to increase to 3–13 days during the population explosion period (2041–2060) under the high-emission shared socioeconomic pathways (SSP3-7.0 and SSP5-8.5). This increase will result in approximately 260 million people in these agglomerations facing more than three heat danger days annually, accounting for 19% of the total population of China, and will double the current level of overall heat risk. During the period 2081–2100, there will be 8–67 heat danger days per year, 60%–90% of the urban agglomerations will exceed the current baseline number, and nearly 310 million people (39% of the total China population) will be exposed to the danger, with the overall heat risk exceeding 18 times the present level. The greatest risk is projected in the PRD region with 67 heat danger days to occur annually under SSP5-8.5. With 65 million people (68% of the total population) experiencing increased heat danger days, the overall heat risk in the region will swell by a factor of 50. Conversely, under the low-emission pathways (SSP1-2.6 and SSP2-4.5), the annual heat danger days will remain similar to the present level or increase slightly. The result indicates the need to develop strategic plans to avoid the increased heat risk of urban agglomerations under high emission-population pathways.

Extreme climatic events and variability are on the rise around the world, with varying implications for populations across socio-economic conditions. Effective strategies for climate adaptation and development depend on understanding these differential sensitivities to climatic variability. This study focuses on a vulnerable population living in forest-fringe villages of central India, where seasonal migration is a common livelihood strategy for poor households to supplement their incomes with remittances. We quantify the relative sensitivity of a decision to migrate for the first time to climate and socio-economic variables and how the sensitivities vary for different segments of the population. We surveyed 5000 households in 500 forest-fringe villages to identify patterns of migration from 2013 to 2017. Using a mixed-effects logistic regression model, we predicted the probability of first-time migration of a household member based on climate variables and household- and district-level characteristics. We find that households in more agricultural and prosperous districts experience lower rates of migration but are more sensitive to climatic variability than households in poorer districts. The probability of first-time migration from a household in the most prosperous district increases by approximately 40% with one standard deviation in mean maximum temperature or rainfall from the 1981–2017 mean. However, the probability of migration does not vary as a function of climatic variability for households in the poorest district. We attribute this difference in sensitivities to the greater dependence on agriculture and irrigation in more prosperous districts and poverty-driven dependence on migration regardless of the climate in poorer districts. Households investing remittances from migration in agricultural intensification could become increasingly sensitive to climate variability, particularly with water shortages and projected increases in climate variability in the region. Promotion of non-agricultural livelihood options and climate-resilient agriculture could the reduce sensitivity of migration to climate variability in the study region.

The media widely covers large carnivores and their impacts on human livelihood and plays an important role in their conservation. Yet, we know little about how species identity affects news selection, framing, accuracy and information flow. We investigated the online coverage of two cases of attacks or alleged attacks on humans alternatingly attributed to wolves and dogs in Greece and Germany. The period during which wolves were considered the primary suspects for the attacks was covered by up to two times more articles than when dogs were suspected. Wolves were presented as more likely suspects for the attacks than dogs, and wolf articles contained more inaccuracies measured as title-text mismatches. Press agencies played a significant role in the selection and dissemination of wolf news. We suggest that conservation scientists, journalists and policy makers work together to ensure an accurate representation in the media of human–carnivore coexistence and its challenges.

Arctic cyclones, as a prevalent feature in the coupled dynamics of the Arctic climate system, have large impacts on the atmospheric transport of heat and moisture and deformation and drifting of sea ice. Previous studies based on historical and future simulations with climate models suggest that Arctic cyclogenesis is affected by the Arctic amplification of global warming, for instance, a growing land-sea thermal contrast. We thus hypothesize that biogeophysical feedbacks (BF) over the land, here mainly referring to the albedo-induced warming in spring and evaporative cooling in summer, may have the potential to significantly change cyclone activity in the Arctic. Based on a regional Earth system model (RCA-GUESS) which couples a dynamic vegetation model and a regional atmospheric model and an algorithm of cyclone detection and tracking, this study assesses for the first time the impacts of BF on the characteristics of Arctic cyclones under three IPCC Representative Concentration Pathways scenarios (i.e. RCP2.6, RCP4.5 and RCP8.5). Our analysis focuses on the spring- and summer time periods, since previous studies showed BF are the most pronounced in these seasons. We find that BF induced by changes in surface heat fluxes lead to changes in land-sea thermal contrast and atmospheric stability. This, in turn, noticeably changes the atmospheric baroclinicity and, thus, leads to a change of cyclone activity in the Arctic, in particular to the increase of cyclone frequency over the Arctic Ocean in spring. This study highlights the importance of accounting for BF in the prediction of Arctic cyclones and the role of circulation in the Arctic regional Earth system.

New mobile platforms such as vehicles, drones, aircraft, and satellites have emerged to help identify and reduce fugitive methane emissions from the oil and gas sector. When deployed as part of leak detection and repair (LDAR) programs, most of these technologies use multi-visit LDAR (MVL), which consists of four steps: (a) rapidly screen all facilities, (b) triage by emission rate, (c) follow-up with close-range methods at the highest-emitting sites, and (d) conduct repairs. The proposed value of MVL is to identify large leaks soon after they arise. Whether MVL offers an improvement over traditional single-visit LDAR (SVL), which relies on undirected close-range surveys, remains poorly understood. We use the Leak Detection and Repair Simulator (LDAR-Sim) to examine the performance and cost-effectiveness of MVL relative to SVL. Results suggest that facility-scale MVL programs can achieve fugitive emission reductions equivalent to SVL, but that improved cost-effectiveness is not guaranteed. Under a best-case scenario, we find that screening must cost < USD 100 per site for MVL to achieve 30% cost reductions relative to SVL. In scenarios with non-target vented emissions and screening quantification uncertainty, triaging errors force excessive close-range follow-up to achieve emissions reduction equivalence. The viability of MVL as a cost-effective alternative to SVL for reducing fugitive methane emissions hinges on accurate triaging after the screening phase.

Two small, oligotrophic lakes at the IISD-Experimental Lakes Area in northwestern Ontario, Canada were fertilized weekly with only phosphorus (P) in the summer and early fall of 2019. The P fertilization rates were high enough (13.3 µg l⁻¹ added weekly) to produce dense, month-long blooms of N₂-fixing Dolichospermum species in both lakes within 9–12 weeks after fertilization began, turning them visibly green without the addition of nitrogen. P-only fertilization increased average seasonal chlorophyll a concentrations and cyanobacteria biomass well above the pre-fertilization levels of 2017 and 2018. Nitrogen (N) content in the epilimnion of thermally stratified Lake 304 and the water column of shallow Lake 303 doubled and P storage in the water column temporarily increased during the blooms. These whole-lake fertilization experiments demonstrate that large cyanobacteria blooms can develop rapidly under high P loading without anthropogenic N inputs, suggesting that aggressive N control programs are unlikely to prevent bloom formation and that P controls should remain the cornerstone for cyanobacteria management.

The increasing production of manure is a challenge for livestock management systems as well as the global environment. Being traditionally, and still dominantly, used as fertilizers, land application of manure could preserve soil fertility and improve soil carbon sequestration. However, manure application also increases nitrous oxide (N₂O) emissions that might outweigh the benefits of carbon gains. Here we quantify soil carbon change and greenhouse gas (GHG) emissions from corn production systems in the United States from a life-cycle perspective. We show that utilizing manure can reduce mineral fertilizers use, and therefore avoid GHG emissions that would otherwise occur due to mineral fertilizer production and application. As a result, corn produced under manure has a reduced intensity of GHG emissions (1.5 t CO₂e ha⁻¹ or 0.15 t CO₂e t⁻¹ corn grain), about 15% less than those under sole mineral fertilizers. Owing to a sizeable amount of avoided emissions counterbalancing N₂O, the soil carbon gain derived from manure use can largely contribute to net climate change mitigation. It should be noted that GHG emissions estimation can be largely improved as more robust and recent data become available to better represent spatially specific land management and to integrate ecosystem models with life-cycle model. Future studies are merited to further assess the alternative fate of manure, and expand the system boundary to assess agriculture and livestock sectors holistically.

The energy content of wind-waves is propagated across the oceans in the form of swell waves, the main drivers of long-term changes in coastal morphology and offshore hazards. A state-of-the-art swell tracking algorithm is applied to a global ensemble of CMIP5 dynamic wave climate projections, to assess future changes in remotely originated swell events towards the end of the 21st century, and how they propagate. The contribution of multiple wave generation areas is considered. It is found that the projected climate change signal is effectively propagated from the winds along the extratropical storm tracks to remote locations, in the tropical and subtropical latitudes, through swell waves. The statistically significant projected changes in swell wave heights and swell predominance at the remote swell arrival locations are comparable with the ones at the wave generation areas. Furthermore, different incoming directions for swell events at remote locations are shown to often carry opposite climate change signals, propagated from different remote origins. These results highlight the need for a directional approach on wave climate projections, critical for improved vulnerability assessments and adaptation measures from the climate community.

Climate change is expected to increase fire activity in many regions of the globe, but the relative role of human vs. lightning-caused ignitions on future fire regimes is unclear. We developed statistical models that account for the spatiotemporal ignition patterns by cause in the eastern slopes of the Cascades in Oregon, USA. Projected changes in energy release component from a suite of climate models were used with our model to quantify changes in frequency and extent of human and lightning-caused fires and record-breaking events based on sizes of individual fires between contemporary (2006 −2015) and mid-century conditions (2031–2060). No significant change was projected for the number of human-caused fire ignitions, but we projected a 14% reduction in lightning-caused ignitions under future conditions. Mean fire sizes were 31% and 22% larger under future conditions (2031–2060) for human and lightning-caused ignitions, respectively. All but one climate model projected increased frequency of record-breaking events relative to the contemporary period, with the largest future fires being about twice the size of those of the contemporary period. This work contributes to understanding the role of lightning- and human-caused fires on future fire regimes and can help inform successful adaptation strategies in this landscape.

The call for a decent life for all within planetary limits poses a dual challenge: provide all people with the essential resources needed to live well and, collectively, not exceed the source and sink capacity of the biosphere to sustain human societies. We examine the corridor of possible distributions of household energy and carbon footprints that satisfy both minimum energy use for a decent life and available energy supply compatible with the 1.5 °C target in 2050. We estimated household energy and carbon footprints for expenditure deciles for 28 European countries in 2015 by combining data from national household budget surveys with the environmentally-extended multi-regional input–output model EXIOBASE. We found a top-to-bottom decile ratio (90:10) of 7.2 for expenditure, 3.1 for net energy and 2.6 for carbon. The lower inequality of energy and carbon footprints is largely attributable to inefficient energy and heating technologies in the lower deciles (mostly Eastern Europe). Adopting best technology across Europe would save 11 EJ of net energy annually, but increase environmental footprint inequality. With such inequality, both targets can only be met through the use of CCS, large efficiency improvements, and an extremely low minimum final energy use of 28 GJ per adult equivalent. Assuming a more realistic minimum energy use of about 55 GJ ae⁻¹ and no CCS deployment, the 1.5 °C target can only be achieved at near full equality. We conclude that achieving both stated goals is an immense and widely underestimated challenge, the successful management of which requires far greater room for maneuver in monetary and fiscal terms than is reflected in the current European political discourse.

The partitioning of belowground biomass (BGB) to aboveground biomass (AGB) is commonly described as the root-to-shoot ratio (R/S). Although a number of studies have shown that biodiversity can influence AGB and BGB in grasslands at the local and global scale, the global-scale patterns reflecting how plant diversity affects R/S and the factors controlling such effects remain unclear. In this study, we explored the global patterns and associated drivers of biomass partitioning responding to plant diversity by conducting a meta-analysis of 333 observations from 30 studies in grasslands worldwide. Overall, plant diversity significantly increased AGB, BGB, and total biomass, whereas significantly decreased R/S. The effects of plant diversity on biomass partitioning varied with experimental types. The effect size for AGB and BGB in the field was larger than in greenhouse experiments, but the effect size for R/S did not significantly differ between field and greenhouse experiments. Moreover, there was no significant relationship between R/S and species richness and experimental duration in greenhouse experiments. However, the effect size for AGB, BGB, and R/S increased logarithmically with species richness and experimental duration in the field experiments. Specifically, the effect size for R/S in the field experiments switched from negative to neutral as the species richness and experimental duration increased. Furthermore, the effect size for R/S was positively correlated with complementary effects of BGB, and it increased logarithmically with mean annual temperature (MAT) and precipitation. Structural equation models showed that species richness, experimental duration, and MAT impact R/S indirectly by changing the BGB. Overall, our findings suggest that plant mixtures invest less in BGB than monocultures, and highlight that low investment in BGB will disappear gradually over time as species richness increases.

Mariculture has a profound potential to sustainably meet the escalating demands for food and livelihoods. However, the socioeconomic impacts of small-scale aquaculture (SSA) are poorly understood, particularly for marine SSA in China, a leading global producer of aquaculture products. Using detailed household surveys, we comprehensively evaluated profitability, income inequality, and subjective well-being of marine SSA households in a representative coastal city in Southeastern China. Our results show that mariculture practices increased income but exacerbated income inequality in animal mariculture households (AMHs) and seaweed mariculture households (SMHs). Earnings from AMHs (544 549 yuan) were four times higher than those of SMHs (141 172 yuan) although AMHs were twice as likely to make a loss (27.4% versus 12.5%). Natural capital (11.37%) and the cultured variety (12.40%) were the main contributors to mariculture income inequality for AMHs, while manufactured capital (27.59%) and previous mariculture experience (8.59%) were significant for SMHs. The well-being of AMHs was better than that of SMHs. Our results suggest that secure access to sea areas, provision of financial options to mariculture smallholders, as well as diversification in mariculture type and variety could promote the socioeconomic sustainability of mariculture development.

Protected areas (PAs) represent one of our most important conservation strategies for halting biodiversity loss. The number of PAs has increased remarkably over the last few decades. Yet, biodiversity is still being lost at alarming rates, even within many of those PAs. Understanding the factors that influence the levels of human pressure within PAs remains a key objective. In this study, we examined the factors associated with the human settlements' levels within the world's PAs. Using the random forests technique, an ensemble machine learning method, and a vast number of PAs (81 100–137 523), we assessed the importance of nine factors, including the PAs' management objective as reflected by their International Union for Conservation of Nature (IUCN) Category. The IUCN classifies PAs into six categories ranging from strict nature reserves to areas in which multiple human uses are permitted. The prevalent but untested assumption is that human settlements' levels within PAs vary according to their management objective, with less strict PAs having higher levels. Our results, however, show that the differences between the categories were for the most part minor. The most important predictor of human settlements was accessibility measured as the time required to reach the PA from the nearest major city. These findings were consistent across all of the world's subregions. Other less important factors included the extent of croplands within PAs, elevation, and slope. Our findings suggest that PAs nearer urban centers tend to have higher human settlements' levels regardless of their other characteristics, such as management objective and year of establishment. Managing those PAs successfully will be necessary to achieve the post-2020 global biodiversity targets and will require conservation strategies that acknowledge and engage the local communities.

The Corona pandemic led to changes in consumptions patterns, which are both positive and negative. Past research suggests that crises present opportunities for adopting sustainable consumption practices. Alternatively, they tend to increase frugality which can marginalize environmental considerations. This study extends research conducted in 2018 evaluating the environmental impacts of consumption patterns among Israel's different socioeconomic deciles. The present research returned to the same respondents, during the first lockdown, assessing how consumptions patterns among different socioeconomic deciles, and support for different environmental policy options were influenced by the Corona crisis. The findings show that the poorest deciles increased their environmentally destructive behavior, while wealthier deciles showed modest improvements. All deciles displayed greater frugality in purchasing. Support was greater for policy interventions framed as environmental than for taxes on daily consumer products. The findings confirm the need for environmental programs which make sustainable consumption more readily accessible to poorer socioeconomic groups.

Adoption of liquefied petroleum gas (LPG) is the primary policy approach in India to transition rural poor communities toward clean cooking behavior. Prior clean cooking studies show that affordability, accessibility, and awareness impact LPG adoption in India. There is scarce research that explores the association of personal networks of community members in their LPG adoption. In this cross-sectional study, we use standard egocentric personal network analyses and multivariate logistic regression models to examine the association of structure and composition of personal networks with LPG adoption in poor communities. Our results show that higher proportions of peers owning LPG are associated with higher likelihood of LPG ownership in the respondents (OR = 41.30, 95% confidence interval: 16.86–101.20, p = 0.00). This study on personal network characteristics in clean cooking research offers a germane foundation for further large scale personal network studies on clean cooking adoption in poor communities.

Urbanization causes the expansion of urban land and changes to urban environments, both of which have significant impacts on the carbon uptake of urban vegetation. Although previous studies have proposed that the impact of the changes in the environmental conditions of vegetation carbon uptake by urban expansion are generally indirect, the processes of this impact are still unclear. In this study, we quantified the indirect effects of urbanization on urban vegetation carbon uptake for unchanged vegetation areas. We extracted unchanged vegetation areas based on multisource remote sensing data from the Google Earth Engine cloud computing platform. The influence of urbanization on vegetation carbon uptake and urban environmental factors in 2004, 2010, and 2016 along with the urban–rural gradient was calculated. In addition, we investigated the relative contribution of urban environmental factors to vegetation carbon uptake to study the relationship between them using a boosted regression tree method. The results showed that urbanization promoted vegetation carbon uptake, which varied with different years in Shanghai. Besides, the promoting effect of urbanization on the carbon uptake of vegetation was mainly due to the increase in temperature and the fragmentation of vegetation landscape patterns in Shanghai. The changes of soil moisture and radiation had little effect on the vegetation carbon uptake. Among the influencing factors, the relative contribution of the vegetation landscape pattern to vegetation carbon uptake was about 85%. Considering the crucial role of landscape patterns in the carbon uptake of vegetation, urban managers should consider reducing the negative influence of urbanization on vegetation through landscape design, which will further promote the sustainable development of urban ecology.

Many of the world's major river deltas face a sustainability crisis, as they come under threat of increases in salinity and the extent of tidal zones forced by combinations of sea-level rise, changes in river discharge and channel geometry. The relative contribution of these factors to future increases in tidal extent remains unconstrained, with most prior work emphasising the role of climate-driven sea-level rise. Here we use new field data from the Mekong delta to measure variations of river discharge and changes of channel geometry, and project them into the future. We combine these with projections of future sea-level rise into a 2D hydrodynamic numerical model and quantify the influence of the different driving factors on future tidal extension into the delta. We show that within the next two decades, tidal extension into the Mekong delta will increase by up to 56 km due to channel deepening (92%), dominantly driven by anthropogenic sediment starvation. Furthermore, even under strong mitigation scenarios, sediment starvation still drives a long-term commitment to future tidal extension. Specifically, by 2098 eustatically rising sea-levels are predicted to contribute only modestly to the projected extension. These findings demonstrate the urgent need for policy makers to adopt evidence-based measures to reverse negative sediment budgets that drive tidal extension into sediment starved deltas.

Predicting regional climate variability is a key goal of initialised decadal predictions and the North Atlantic has been a major focus due to its high level of predictability and potential impact on European climate. These predictions often focus on decadal variability in sea surface temperatures (SSTs) in the North Atlantic subpolar gyre (NA SPG). In order to understand the value of initialisation, and justify the high costs of such systems, predictions are routinely measured against technologically simpler benchmarks. Here, we present a new model-analogue benchmark that aims to leverage the latent information in uninitialised climate model simulations to make decadal predictions of NA SPG SSTs. This system searches through more than one hundred thousand simulated years in Coupled Model Intercomparison Project archives and yields skilful predictions in its target region comparable to initialised systems. Analysis of the underlying behaviour of the system suggests the origins of this skill are physically plausible. Such a system can provide a useful benchmark for initialised systems within the NA SPG and also suggests that the limits in initialised decadal prediction skill in this region have not yet been reached.

Water competition between the food and energy sector is a critical component of the food-energy-water nexus. However, few studies have systematically characterized the geospatial and, especially, the sub-annual variations in such competition and the associated environmental impacts and targeted mitigation opportunities. This study characterizes competing water uses for crop-specific irrigated agriculture and fuel-specific power generation across global major river basins to reveal their resulting impacts on local water scarcity for global population under both current and a warming climate. Under annual (and most seasonal) accounting, almost all basins currently suffering from extremely high water scarcity are dominated by agricultural water consumption (e.g. accommodating 26%–49% of basin-total population across seasons), which are often simultaneously exposed to potentially decreasing seasonal water availability under a 4 °C warming scenario. Only 13%–20% of population are located in basins dominated by seasonal power sector water uses, which are predominantly with low water scarcity. Agriculture sector provides the most basin-specific water mitigation opportunities across mid-latitude basins in all four seasons. Nevertheless, power sector becomes more important in affecting seasonal water scarcity and provides unique seasonal water mitigation opportunities, particularly in basins among higher northern latitudes in winter. This analysis highlights irrigated agriculture is currently and will likely remain the key in global water management for basins facing the severest water scarcity, yet increasing attention on the seasonal and spatial variations in cross-sector water use competition is needed to better identify region- and season- specific mitigation opportunities.

To reverse the trend of rising CO₂ emissions in the European Union's (EU) transportation sector, several European governments have introduced programs that promote electric vehicles (EVs). One frequently cited impediment to their uptake is insufficient charging infrastructure. Drawing on panel data from Germany, this paper estimates the relationship between public charging infrastructure and the uptake of EVs. We specify models with fixed effects and instrumental variables to gauge the robustness of our findings in the face of alternative channels through which endogeneity bias may emerge. We find that charging infrastructure has a statistically significant and positive impact on EV uptake, with the magnitude of the estimate increasing with population density. The evidence further suggests that although the incidence of charging points in Germany far exceeds the EU's recommended minimum ratio of one point to ten EVs, inadequate infrastructure coverage remains a binding constraint on EV uptake. We use the model estimates to illustrate the relative cost effectiveness of normal and fast chargers by region, which supports a geographically differentiated targeting of subsidies for charging infrastructure.

More than half of the world's population now lives in urban areas, and trends in rural-to-urban migration are expected to continue through the end of the century. Although cities create efficiencies that drive innovation and economic growth, they also alter the local surface energy balance, resulting in urban temperatures that can differ dramatically from surrounding areas. Here we introduce a global 1 km resolution data set of seasonal and diurnal anomalies in urban surface temperatures relative to their rural surroundings. We then use satellite-observable parameters in a simple model informed by the surface energy balance to understand the dominant drivers of present urban heating, the heat-related impacts of projected future urbanization, and the potential for policies to mitigate those damages. At present, urban populations live in areas with daytime surface summer temperatures that are 3.21 ^∘C (−3.97, 9.24, 5th–95th percentiles) warmer than surrounding rural areas. If the structure of cities remains largely unchanged, city growth is projected to result in additional daytime summer surface temperature heat anomalies of 0.19 ^∘C (−0.01, 0.47) in 2100—in addition to warming due to climate change. This is projected to raise the urban population living under extreme surface temperatures by approximately 20% compared to current distributions. However we also find a significant potential for mitigation: 82% of all urban areas have below average vegetation and/or surface albedo. Optimizing these would reduce urban daytime summer surface temperatures for the affected populations by an average of −0.81 ^∘C (−2.55, −0.05).

Wet heatwaves can have more impact on human health than hot dry heatwaves. However, changes in these have received little scientific attention. Using the ECMWF Reanalysis v5 reanalysis dataset, wet-bulb temperatures (T_w) were used to investigate the spatial-temporal variation of wet heatwaves in Eurasia for 1979–2017. Wet heatwaves were defined as three day or longer periods when T_w was above the 90th percentile of the summer distribution and characterized by amplitude, duration and frequency. Maximum values of amplitude, close to 31 °C, occur in the Indus–Ganges plain, the lower Yangtze valley, and the coasts of the Persian Gulf and Red Sea. Significant positive trends in the frequency and amplitude of wet heatwaves have occurred over most of Eurasia though with regional variations. Changes in heatwave amplitude (HWA) are largely driven by changes in summer mean T_w. For Eurasia as a whole, increases in temperature contribute more than six times the impact of changes in relative humidity (RH) to changes in T_w HWA. Changes in T_w have a strong dependence on climatological RH with an increase in RH of 1% causing a T_w increase of 0.2 °C in arid regions, and only increasing T_w by 0.1 °C in humid regions. During T_w heatwaves in Europe, parts of Tibet, India, East Asia and parts of the Arabian Peninsula both temperature and humidity contribute to the increase in T_w, with temperature the dominant driver. During wet heatwaves in part of Russia, changes in humidity are weak and the increase in T_w is mainly caused by an increase in temperature. In the Mediterranean and Central Asia, RH has fallen reducing the increase in T_w from general warming.

Equilibrium climate sensitivity (ECS) and transient climate response (TCR) are both measures of the sensitivity of the climate system to external forcing, in terms of temperature response to CO₂ doubling. Here it is shown that, of the two, TCR in current-generation coupled climate models is better correlated with the model projected temperature change from the pre-industrial state, not only on decadal time scales but throughout much of the 21st century. For strong mitigation scenarios the difference persists until the end of the century. Historical forcing on the other hand has a significant degree of predictive power of past temperature evolution in the models, but is not relevant to the magnitude of temperature change in their future projections. Regional analysis shows a superior predictive power of ECS over TCR during the latter half of the 21st century in areas with slow warming, illustrating that although TCR is a better predictor of warming on a global scale, it does not capture delayed regional feedbacks, or pattern effects. The transient warming at CO₂ quadrupling (T140) is found to be correlated with global mean temperature anomaly for a longer time than TCR, and it also better describes the pattern of regional temperature anomaly at the end of the century. Over the 20th century, there is a weak correlation between total forcing and ECS, contributing to, but not determining, the model agreement with observed warming. ECS and aerosol forcing in the models are not correlated.

Whether river flows remain stationary is of great concern to hydrologists, water engineers, and society in general, yet is subject to substantial debate. Here we provide the first comprehensive assessment of the long-term stationarity of annual streamflow for 11 069 catchments globally. Our observation-based evidence shows that the long-term annual streamflow remains stationary in 79% of catchments with minimal human disturbance, indicating that historical climate change alone has not led to non-stationarity in annual streamflow series in most catchments. In direct contrast, we found streamflow has remained stationary in only 38% of those catchments where substantial human interventions have occurred. These results demonstrate the scale of the human impact on the freshwater system, and highlight the ongoing need for dealing with the impacts of direct human interventions to ensure successful water management into the future.

The range of sub-daily extreme precipitation due to internal variability is quantified within the single model initial-condition large ensemble featuring 50 members of the Canadian regional climate model, version 5 (CRCM5) under the high-emission scenario representative concentration pathway 8.5. Ten-year return levels of sub-daily precipitation are calculated for three future periods (2010–2039, 2040–2069, 2070–2099) and hourly to 24-hourly aggregations over a European domain. The return levels are found to increase by 4%–8% for every future 30 year period averaged for the study area, where short-duration rainfall intensities increase to a greater extent than longer-duration rainfall intensities. The ranges between the median of the 50 members and the 5th and 95th quantile amount to −15.6%–19.3%, −16.0%–20.1%, and −16.5%–20.9% for the near, mid and far future, respectively. It is also shown that the scaling of the precipitation increase with temperature (Clausius–Clapeyron scaling) exhibits substantial variations between the 50 CRCM5 members at regional aggregations. These findings illustrate the large impact of internal variability on the uncertainty of extreme precipitation return level estimates. Here, regions of significant changes are identified, where future median extreme precipitation exceeds the 95th quantile of the reference period (1980–2009). These regions are located in northern Europe, central Europe and the eastern part of the Mediterranean.

With a global pollinator crisis brewing, it is urgent that we preserve forests supporting wild bees and the services they provide, even in context where agricultural expansion is unavoidable. Though the maintenance of pollination services are known to be synergistic with biodiversity conservation and agricultural economic development, there are few decision support tools that explicitly show how to balance these competing objectives. We developed a novel, spatially explicit method that includes pollination supply, flow, demand, and benefits into an agricultural expansion context to improve land use decisions for agricultural outcomes that minimize environmental impacts. We provide the first study showing the trade-offs between yields and forest retention that uses all the components of pollination services across five planning scenarios (i.e. (a) baseline, (b) absence of pollinators, (c) pollinators present, (d) pollination and non-aggregated forest, (e) pollination and aggregated forest) using data on coffee from Costa Rica. The scenario that showed the highest trade-offs was when pollination services are considered unimportant, which led to a decrease on average yields (∼−23% compared to baseline), whilst also decimating remaining forest (−100% compared to baseline). Better forest retention was achieved in a scenario where pollination services were considered and more forest aggregation was required. In this case, total production incremented by ∼29% while ∼74% of forest patches were preserved. The flexibility of our framework allows adaptation to any crop that benefit from pollination services in different landscape contexts.

Carbon dioxide removal (CDR) features heavily in low-carbon scenarios, where it often substitutes for emission reductions in both the near-term and long-term, enabling temperature targets to be met at lower cost. There are major concerns around the scale of CDR deployment in many low-carbon scenarios, and the risk that anticipated future CDR could dilute incentives to reduce emissions now, a phenomenon known as mitigation deterrence. Here we conduct an in-depth analysis into the relationship between emissions reduction and emissions removal in a global integrated assessment model. We explore the impact of CDR on low-carbon scenarios, illustrating how the pathway for the 2020s is highly sensitive to assumptions around CDR availability. Using stochastic optimisation, we demonstrate that accounting for uncertainty in future CDR deployment provides a strong rationale to increase rates of mitigation in the 2020s. A 20% chance of CDR deployment failure requires additional emissions reduction in 2030 of 3–17 GtCO₂. Finally, we introduce new scenarios which demonstrate the risks of mitigation deterrence and the benefits of formally separating CDR and emissions reduction as climate strategies. Continual mitigation deterrence across the time-horizon leads to the temperature goals being breached by 0.2–0.3 °C. If CDR is treated as additional to emissions reduction, up to an additional 700–800 GtCO₂ can be removed from the atmosphere by 2100, reducing end-of-century warming by up to 0.5 °C. This could put sub-1.5 °C targets within reach but requires that CDR is additional to, rather than replaces, emission reductions.

Most global dietary forecasts predict a reduction in nutritional deficiencies over the next several decades driven by significant increases in environmentally unsustainable livestock and animal source food consumption. Here, we explore a more environmentally sensitive alternative to improve global nutrition, consuming insects. Our study focuses on Africa and Asia, two continents with a history of eating insects and high rates of nutritional deficiency. We model the impact of adding modest amounts (2.5, 5 and 10 g per day, dry weight) of regionally appropriate and farmable species on total nutrient intake and population-wide risk of deficiency for specific nutrients of concern: protein, zinc, folate, and vitamin B12. We also estimate the total potential change in dietary iron. Five grams per day of insect consumption could alleviate a considerable amount of risk of nutritional deficiency: 67 million (95% uncertainty interval: 49–84 million) fewer people at risk of protein deficiency, 166 million (120–220 million) fewer people at risk of zinc deficiency, 237 million (120–439 million) fewer people at risk of folate deficiency, and 251 million (28–2271) fewer people at risk for vitamin B12 deficiency. For iron, per capita supplies could increase by 3% (0.8%–6.0%) with insects, and even more so for vulnerable groups in countries currently suffering severe rates of anemia: 4.2% (0.5%–8.8%) for women of childbearing age and 4.1% (0.4%–10.0%) for children under 5. Doubling or halving insect intake per capita causes the benefits for nutritional deficiency risk to roughly double or halve accordingly. Effects are most pronounced in South and Central Asia, though sub-Saharan Africa, East Asia, and Southeast Asia also see considerable reduction in nutritional risk. These results demonstrate the potential for insects to fill a crucial role in providing nutrition for these populous and rapidly developing regions while safeguarding the global environment.

Air pollution is a major environmental risk factor and contributor to chronic, noncommunicable diseases (NCDs). However, most public health approaches to NCD prevention focus on behavioural and biomedical risk factors, rather than environmental risk factors such as air pollution. This article discusses the implications of such a focus. It then outlines the opportunities for those in public health and environmental science to work together across three key areas to address air pollution, NCDs and climate change: (a) acknowledging the shared drivers, including corporate determinants; (b) taking a 'co-benefits' approach to NCD prevention; and (c) expanding prevention research and evaluation methods through investing in systems thinking and intersectoral, cross-disciplinary collaborations.

The troposphere is one of the atmospheric layers where most weather phenomena occur. Temperature variations in the troposphere, especially at 500 hPa, a typical level of the middle troposphere, are significant indicators of future weather changes. Numerical weather prediction is effective for temperature prediction, but its computational complexity hinders a timely response. This paper proposes a novel temperature prediction approach in framework of physics-informed deep learning. The new model, called PGnet, builds upon a generative neural network with a mask matrix. The mask is designed to distinguish the low-quality predicted regions generated by the first physical stage. The generative neural network takes the mask as prior for the second-stage refined predictions. A mask-loss and a jump pattern strategy are developed to train the generative neural network without accumulating errors during making time-series predictions. Experiments on ERA5 demonstrate that PGnet can generate more refined temperature predictions than the state-of-the-art.

Rainfall and irrigation trigger large pulses of the powerful greenhouse gas N₂O from intensively managed pastures, produced via multiple, simultaneously occurring pathways. These N₂O pulses can account for a large fraction of total N₂O losses, demonstrating the importance to determine magnitude and source partitioning of N₂O under these conditions. This study investigated the response of different pathways of N₂O production to wetting across three different textured pasture soils. Soil microcosms were fertilised with an ammonium nitrate (NH₄NO₃) solution which was either single or double ¹⁵N labelled, wetted to four different water-filled pore space (WFPS) levels, and incubated over two days. The use of a ¹⁵N pool mixing model together with soil N gross transformations enabled the attribution of N₂O to specific pathways, and to express N₂O emissions as a fraction of the underlying N transformation. Denitrification and nitrification mediated pathways contributed to the production of N₂O in all soils, regardless of WFPS. Denitrification was the main pathway of N₂O production accounting for >50% of cumulative N₂O emissions even at low WFPS. The contribution of autotrophic nitrification to N₂O emissions decreased with the amount of wetting, while the contribution of heterotrophic nitrification remained stable or increased. Following the hole-in-the-pipe model, 0.1%–4% of nitrified N was lost as N₂O, increasing exponentially with WFPS, while the percentage of denitrified N emitted as N₂O decreased, providing critical information for the representation of N₂O/WFPS relationships in simulation models. Our findings demonstrate that the wetting of pasture soils promotes N₂O production via denitrification and via the oxidation of organic N substrates driven by high carbon and N availability upon wetting. The large contribution of heterotrophic nitrification to N₂O emissions should be considered when developing N₂O abatement strategies, seeking to reduce N₂O emissions in response to rainfall and irrigation from intensively managed pastures.

This study focuses on metal speciation research in Arctic lakes with technogenic pollution and other areas where natural processes prevail (background lakes and lakes with marine influence). Element speciation in 75 lakes in the Kola Peninsula was investigated in 2014 and 2018 taking into account the influence of different geochemical factors. The geochemical features of lake water in the investigated regions are documented and discussed. Membrane filtration was used with the following features: mechanical suspension and oxidized contaminants (>8 μm, 1.2 μm) for lakes near smelters and those subject to marine effects; light suspension colloids (0.45–0.1 μm) for the natural waters of background lakes; low molecular weight complexes, inorganic ions, bacteria, and viruses (less than 0.1 μm) for identification of labile and non-labile components. It has been proven that the bioavailable speciation (unbound with organic components) is determined by the physicochemical properties of organic matter, such as zeta potential, molecular weight, and colloid stability. In conventional background lakes, Fe and Al complexes with humic substances dominate, and the most associative elements of the lanthanide/actinide group repeat the tendency of Fe. In lakes with a clear marine influence, the complexation potential of organic substances is reduced due to Na ions, which deactivate humic functional groups. Multivariate statistical methods showed significant differences between the selected gradations of lake waters and the genetic similarities and differences in the behavior of element speciation.

Changes of croplands often reflect the combined impacts of both natural environment changes and social agriculture activities. Such reflections manifested more significantly in agro-pastoral transition zones, e.g. in the North and West of China. In this study, cropland changes at the Yellow River–Huangshui River Valley, as a typical agro-pastoral transition zone in northwestern China, is analyzed in terms of the changes of the total amount and spatial pattern over the past 300 years (majorly in the Qing Dynasty). The reconstructed cropland data indicated a fluctuation of cropland areas in accordance with changes of regional climate conditions, natural hazards, agriculture activities and socio-economic development. A significant decrease of cropland in the middle of the 19th century was detected, which appeared a good consistency with the frequent natural disasters in the same period and the climate cooling trend across the whole 19th century. Though in the worsening conditions, three major copping strategies maintained and developed the local socio-agriculture system: (a) land reclamation policy encouraged immigrants and military farming; (b) construction of water conservancy facilities increased agricultural productivity; (c) increasing local Tibetans learned and transformed to implementing both agriculture and pastoral productions with flexibilities depending on climate conditions. The study demonstrates that the social-agriculture system held certain resilience, which can be maintained and enhanced with appropriate political, engineering, economic, and social-cultural measures.

New estimates of greenhouse gas (GHG) emissions from the food system were developed at the country level, for the period 1990–2018, integrating data from crop and livestock production, on-farm energy use, land use and land use change, domestic food transport and food waste disposal. With these new country-level components in place, and by adding global and regional estimates of energy use in food supply chains, we estimate that total GHG emissions from the food system were about 16 CO₂eq yr⁻¹ in 2018, or one-third of the global anthropogenic total. Three quarters of these emissions, 13 Gt CO₂eq yr⁻¹, were generated either within the farm gate or in pre- and post-production activities, such as manufacturing, transport, processing, and waste disposal. The remainder was generated through land use change at the conversion boundaries of natural ecosystems to agricultural land. Results further indicate that pre- and post-production emissions were proportionally more important in developed than in developing countries, and that during 1990–2018, land use change emissions decreased while pre- and post-production emissions increased. We also report results on a per capita basis, showing world total food systems per capita emissions decreasing during 1990–2018 from 2.9 to 2.2 t CO₂eq cap⁻¹, with per capita emissions in developed countries about twice those in developing countries in 2018. Our findings also highlight that conventional IPCC categories, used by countries to report emissions in the National GHG inventory, systematically underestimate the contribution of the food system to total anthropogenic emissions. We provide a comparative mapping of food system categories and activities in order to better quantify food-related emissions in national reporting and identify mitigation opportunities across the entire food system.

On-road vehicular emissions contribute to the formation of fine particulate matter and ozone which can lead to increased adverse health outcomes near the emission source and downwind. In this study, we present a transportation-specific modeling platform utilizing the community multiscale air quality model (CMAQ) with the decoupled direct method (DDM) to estimate the air quality and health impacts of on-road vehicular emissions from five vehicles classes; light-duty autos, light-duty trucks (LDT), medium-duty trucks, heavy-duty trucks (HDT), and buses (BUS), on PM_2.5 and O₃ concentrations at a 12 × 12 kilometer scale for 12 states and Washington D.C. as well as four large metropolitan statistical areas in the Northeast and Mid-Atlantic U.S. in 2016. CMAQ-DDM allows for the quantification of sensitivities from individual precursor emissions (NO${}_\mathrm{X}$, SO₂, NH₃, volatile organic compounds, and PM_2.5) in each state to pollution levels and health effects in downwind states. In the region we considered, LDT are responsible for the most PM_2.5-attributable premature mortalities at 1234 with 46% and 26% of those mortalities from directly emitted primary particulate matter and NH₃, respectively; and O₃-attributable premature mortalities at 1129 with 80% of those mortalities from NO${}_\mathrm{X}$ emissions. Based on a detailed source-receptor matrix of sensitivities with subsequent monetization of damages that we computed, we find that the largest damages-per-ton estimate is approximately $4 million per ton of directly emitted primary particulate matter from BUS in the New York-Newark-Jersey City metropolitan statistical area. We find that on-road vehicular NH₃ emissions are the second largest contributor to PM_2.5 concentrations and health impacts in the study region, and that reducing 1 ton of NH₃ emissions from LDT is ∼75 times and from HDT is ∼90 times greater in terms of damages reductions than a 1 ton reduction of NO${}_\mathrm{X}$. By quantifying the impacts by each combination of source region, vehicle class, and emissions precursor this study allows for a comprehensive understanding of the largest vehicular sources of air quality-related premature mortalities in a heavily populated part of the U.S. and can inform future policies aimed at reducing those impacts.

Local and state policymakers have become increasingly interested in developing policies that both reduce greenhouse gas (GHG) emissions and improve local air quality, along with public health. Interest in developing transportation-related policies has grown as transportation became the largest contributing sector to GHG emissions in the United States in 2017. Information on current emissions and health impacts, along with trends over time, is helpful to policymakers who are developing strategies to reduce emissions and improve public health, especially in areas with high levels of transportation-related emissions. Here, we provide a comprehensive assessment of the public health and climate social costs of on-road emissions by linking emissions data generated by the U.S. Environmental Protection Agency to reduced complexity models that provide impacts per ton emitted for pollutants which contribute to ambient fine particulate matter, and the social costs of GHG emissions from on-road transportation. For 2017, social costs totaled $184 billion (min: $78 billion; max: $280 billion) for all on-road emissions from the eight health and climate pollutants that we assessed in the continental U.S. (in $2017 USD). Within this total social cost estimate, health pollutants constituted $93 billion of the social costs (min: $52 billion; max: $146 billion), and climate pollutants constituted $91 billion (min: $26 billion; max: $134 billion). The majority of these social costs came from CO₂ followed by NO_x emissions from privately owned individual vehicles in urban counties (CO₂ contributed $51 billion and NO_x contributed $16 billion in social costs from individual vehicles in urban counties). However, it is important to note that not all the attention should be placed solely on individual vehicles. Although the climate social costs of individual vehicle emissions are higher than those from commercial vehicles in urban counties (by two to eight times depending on the climate pollutant), the health social costs of individual vehicle emissions are roughly equal to those from commercial vehicles in urban counties. Regardless of each pollutant's contributions to the social costs, the highest social benefits from reducing 1 ton of CO₂ and its co-pollutants would occur in urban counties, given their high population density.

Energy, water, and agricultural resources across the globe are highly interconnected. This interconnectivity poses science challenges, such as understanding and modeling interconnections, as well as practical challenges, such as efficiently managing interdependent resource systems. Using the US as an example, this study seeks to define and explore how interconnectivity evolves over space and time under a range of influences. Concepts from graph theory and input–output analysis are used to visualize and quantify key intersectoral linkages using two new indices: the 'Interconnectivity Magnitude Index' and the 'Interconnectivity Spread Index'. Using the Global Change Analysis Model (GCAM-USA), we explore the future evolution of these indices under four scenarios that explore a range of forces, including socioeconomic and technological change. Analysis is conducted at both national and state level spatial scales from 2015 to 2100. Results from a Reference scenario show that resource interconnectivity in the US is primarily driven by water use amongst different sectors, while changes in interconnectivity are driven by a decoupling of the water and electricity systems, as power plants become more water-efficient over time. High population and GDP growth results in relatively more decoupling of sectors, as a larger share of water and energy is used outside of interconnected sector feedback loops. Lower socioeconomic growth results in the opposite trend. Transitioning to a low-carbon economy increases interconnectivity because of the expansion of purpose-grown biomass, which strengthens the connections between water and energy. The results highlight that while some regions may experience similar sectoral stress projections, the composition of the intersectoral connectivity leading to that sectoral stress may call for distinctly different multi-sector co-management strategies. The methodology we introduce here can be applied in diverse geographical and sectoral contexts to enable better understanding of where, when, and how coupling or decoupling between sectors could evolve and be better managed.

Increasing temperature and its impact on population health is an emerging significant public health issue in the context of climate change in Australia. While previous studies have primarily focused on risk assessment, very few studies have evaluated heat-attributable emergency department (ED) visits and associated healthcare costs, or projected future health and economic burdens. This study used a distributed lag non-linear model to estimate heat attributable ED visits and associated healthcare costs from 13 hospitals in Perth, Western Australia, and to project the future healthcare costs in 2030s and 2050s under three climate change scenarios—Representative Concentration Pathways (RCPs)2.6, RCP4.5 and RCP8.5. There were 3697 ED visits attributable to heat (temperatures above 20.5 °C) over the study period 2012–2019, accounting for 4.6% of the total ED visits. This resulted in AU$ 2.9 million in heat-attributable healthcare costs. The number of ED visits projected to occur in the 2030s and 2050s ranges from 5707 to 9421 under different climate change scenarios, which would equate to AU$ 4.6–7.6 million in heat associated healthcare costs. The heat attributable fraction for ED visits and associated healthcare costs would increase from 4.6% and 4.1% in 2010s to 5.0%–6.3% and 4.4%–5.6% in 2030s and 2050s, respectively. Future heat attributable ED visits and associated costs will increase in Perth due to climate change. Excess heat will generate a substantial population health challenge and economic burdens on the healthcare system if there is insufficient heat adaptation. It is vital to reduce greenhouse gas emissions, develop heat-related health interventions and optimize healthcare resources to mitigate the negative impact on the healthcare system and population health in the face of climate change.

Extreme weather disasters (EWDs) can jeopardize domestic food supply and disrupt commodity markets. However, historical impacts on European crop production associated with droughts, heatwaves, floods, and cold waves are not well understood—especially in view of potential adverse trends in the severity of impacts due to climate change. Here, we combine observational agricultural data (FAOSTAT) with an extreme weather disaster database (EM-DAT) between 1961 and 2018 to evaluate European crop production responses to EWD. Using a compositing approach (superposed epoch analysis), we show that historical droughts and heatwaves reduced European cereal yields on average by 9% and 7.3%, respectively, associated with a wide range of responses (inter-quartile range +2% to −23%; +2% to −17%). Non-cereal yields declined by 3.8% and 3.1% during the same set of events. Cold waves led to cereal and non-cereal yield declines by 1.3% and 2.6%, while flood impacts were marginal and not statistically significant. Production losses are largely driven by yield declines, with no significant changes in harvested area. While all four event frequencies significantly increased over time, the severity of heatwave and drought impacts on crop production roughly tripled over the last 50 years, from −2.2% (1964–1990) to −7.3% (1991–2015). Drought-related cereal production losses are shown to intensify by more than 3% yr⁻¹. Both the trend in frequency and severity can possibly be explained by changes in the vulnerability of the exposed system and underlying climate change impacts.

Historical snow cover over the Northern Hemisphere was examined in the satellite-based NOAA-CDR data for the period of 1970–2019. Observed annual snow cover fraction (SNF) has reduced over most areas by up to 2%/decade, while annual snow cover area (SCA) has reduced by 2 × 10⁵ km²/decade. However, SCA in the October–December season has increased by about 5 × 10⁵ km²/decade. CMIP5 and CMIP6 historical experiments were validated against the NOAA-CDR data. Snow cover was generally well simulated in both CMIPs, with CMIP6 models performing better. The biases in SCA reduction were larger and smaller during summer and winter, respectively. The observed increase of October–November–December SCA in the 2000s was not reproduced. Climate projections of future snow cover were evaluated in CMIP6. SNF is projected to decrease in the next 80 years, under all four scenarios evaluated (SSP126, SSP245, SSP370 and SSP585). The higher the greenhouse emissions in the shared socio-economic pathways, the faster the reduction. Under the SSP585 scenario, the rate of SCA reduction is projected to exceed −1.2 × 10⁶ km²/decade. By 2081–2100, annual (January–March) SCA is projected to decrease by more than 30% (20%). Under the SSP126 scenario, annual (January–March) SCA is projected to only reduce by about 10% (5%) relative 1995–2014 values. The reduction of Greenhouse gas emissions is critical to controlling the loss of snow cover; future snow cover only stabilizes under the SSP126 scenario, but continue to decrease under the other three scenarios.

The seasonal snowpack plays a critical role in Arctic and boreal hydrologic and ecologic processes. Though snow depth can be markedly different from one season to another there are strong repeated relationships between ecotype and snowpack depth. In the diverse vegetative cover of the boreal forest of Interior Alaska, a warming climate has shortened the winter season. Alterations to the seasonal snowpack, which plays a critical role in regulating wintertime soil thermal conditions, have major ramifications for near-surface permafrost. Therefore, relationships between vegetation and snowpack depth are critical for identifying how present and projected future changes in winter season processes or land cover will affect permafrost. Vegetation and snow cover areal extent can be assessed rapidly over large spatial scales with remote sensing methods, however, measuring snow depth remotely has proven difficult. This makes snow depth–vegetation relationships a potential means of assessing snowpack characteristics. In this study, we combined airborne hyperspectral and LiDAR data with machine learning methods to characterize relationships between ecotype and the end of winter snowpack depth. More than 26 000 snow depth measurements were collected between 2014 and 2019 at three field sites representing common boreal ecoregion land cover types. Our results show hyperspectral measurements account for two thirds or more of the variance in the relationship between ecotype and snow depth. Of the three modeling approaches we used, support vector machine yields slightly stronger statistical correlations between snowpack depth and ecotype for most winters. An ensemble analysis of model outputs using hyperspectral and LiDAR measurements yields the strongest relationships between ecotype and snow depth. Our results can be applied across the boreal biome to model the coupling effects between vegetation and snowpack depth.

Smallholders are a substantial part of the oil palm sector and thus are key to achieving more sustainable production. However, so far their yields remain below potential. The Roundtable on Sustainable Oil Palm (RSPO) aims to include smallholders in sustainability certification to strengthen rural livelihoods and reduce negative environmental impacts. This study aims to determine if and how certified smallholders perform differently from their non-certified counterparts in terms of management practices and yields, and to what extent this is related to RSPO certification. Certified smallholders had significantly better management practices in terms of planting material (tenera) and fertiliser use (16.8 vs 4.8 bags ha⁻¹ yr⁻¹) and had significantly higher yields (22.5 vs 14.5 ton fresh fruit bunches ha⁻¹1 yr⁻¹1, corrected for palm age). Planting material and harvesting frequency significantly explained higher yields. These differences could not be attributed to certification per se but were probably due to pre-certification conditions, including strong group organisation. It remains a question as to how sustainability certification can be a driver of change by including smallholders who have relatively larger yield gaps, and who lag behind in eligibility criteria for certification.

Modern dietary habits in communities are linked and are part of the global food supply chain. To achieve sustainable food production and consumption, communicating the impact associated with food production and dietary choices at community level to consumers is important. However, previous footprint studies have primarily focussed on food consumption at the national level and neglected community–level consumption activities. This study surveyed the diets of a small island community and linked the results with multi-region land footprint analysis in Ollei Village, Republic of Palau. The analysis was used to determine the extent to which the dietary lifestyles of communities depend on external land use through the global supply chain. We showed that the global food supply chain has reached this corner of the world, and the dietary habits of the community are already heavily dependent on processed and imported foods. The community and country are highly dependent on large land use in some major producer/exporting countries through the global food supply chain. In addition, the amount of external land used for food production exceeds the biocapacity of the agricultural land in the community and country. This study bridges the gap between community–level consumption activities and national-scale footprint analysis, and quantitatively assesses the impact of consumption activities at the community level on the global environment. The results and approach of this study could contribute to the development and implementation of vertically integrated food policies between the national and community level in Palau.

Achieving and maintaining food and nutrition security is an important Sustainable Development Goal, especially in countries with largely vulnerable population with high occurrence of hunger and malnutrition. By studying a small-scale agricultural system in India, we aim to understand the current state of dietary diversity and food insecurity among the farmer communities. The study landscape has witnessed a steady rise in multiple cropping (i.e. harvesting more than once a year) along with irrigation over the last two decades. Whether this multiple cropping can be expected to improve year-round food security is not well understood. We specifically examine if planting multiple food crops within a year is associated with dietary diversity and food security. We collected information on demographic and economic variables, farming activities and livelihood choices, from 200 unique households for three seasons (monsoon/rainy, winter, summer) during 2016–2018 (n = 600). Based on both a 24 h and a 30 days recall, we calculated several indicators, including the household dietary diversity score, the minimum dietary diversity for women, and household food insecurity access scale. At least 43% of the sample population experiences moderate to severe food insecurity in all seasons. Cereals (mainly rice) remain the most important food item irrespective of the season, with negligible consumption of other nutrient-rich food such as tubers, fish, eggs, and meats. Around 81% of women in all seasons do not consume a minimally diverse diet. Multiple cropping is associated with higher food security only during monsoon, while selling monsoon crops is associated with winter food security. Households practicing multiple cropping consume more pulses (a plant-based protein source) compared to single-cropping or non-farming households (p < 0.05). We find that multiple cropping cannot be used as a cure-all strategy. Rather a combination of income and nutrition strategies, including more diverse home garden, diverse income portfolio, and access to clean cooking fuel, is required to achieve year-round dietary diversity or food security.

The COVID-19 pandemic and ensuing lockdown of many US States resulted in rapid changes to motor vehicle traffic and their associated emissions. This presents a challenge for air quality modelling and forecasting during this period, in that transportation emission inventories need to be updated in near real-time. Here, we update the previously developed fuel-based inventory of vehicle emissions (FIVE) to account for changes due to COVID-19 lockdowns. We first construct a 2020 business-as-usual (BAU) case inventory and adjust the emissions for a COVID-19 case using monthly fuel sales information. We evaluate cellular phone-based mobility data products (Google COVID-19 Community Mobility, Apple COVID-19 Mobility Trends) in comparison to embedded traffic monitoring sites in four US cities. We find that mobility datasets tend to overestimate traffic reductions in April 2020 (i.e. lockdown period), while fuel sales adjustments are more similar to changes observed by traffic monitors; for example, mobility-based methods for scaling emissions result in an approximately two-times greater estimate of on-road nitrogen oxide (NO_x) reductions in April 2020 than we find using a fuel-based method. Overall, FIVE estimates a 20%–25% reduction in mobile source NO_x emissions in April 2020 versus BAU, and a smaller 6%–7% drop by July. Reductions in April showed considerable spatial heterogeneity, ranging from 6% to 39% at the state level. Similar decreases are found for carbon monoxide (CO) and volatile organic compounds. Decreases to mobile source NO_x emissions are expected to lower total US anthropogenic emissions by 9%–12% and 3%–4% in April and July, respectively, with larger relative impacts in urban areas. Changes to diurnal and day-of-week patterns of light- and heavy-duty vehicular traffic are evaluated and found to be relatively minor. Beyond the applicability to modelling air quality in 2020, this work also represents a methodology for quickly updating US transportation inventories and for calibrating mobility-based estimates of emissions.