Table of contents

Engineering, economic, social sciences, geophysical, and integrated modeling studies have approached the assessment of water security in Central Asia (CA) in distinct ways. Different indicators and indexes have been introduced to assess the most vulnerable aspects of water use in this region. Until now, though, the suggested approaches are often represented in a fragmented manner, while the relevant indicators cannot fully attribute the vulnerability status of a country or on a regional level. This can result in diverging perceptions of the water security situation in policy dialogues, also affecting bilateral and multilateral relations among the countries in CA. In this study, we conduct a bibliometric review on the approaches and methods that directly or indirectly touch upon the water security perceptions in CA. We employ data mining techniques to explore trends in the conceptualization of water security in the region since the breakup of the Soviet Union by also identifying the water interests and priorities set by each country. The findings reveal that within the last decade, the water security-related studies have given much importance to technical and infrastructural means to protect human livelihoods against global environmental changes but also to foster economic growth. The water governance and management aspects are largely overlooked in favour of more techno-centric approaches. These findings are expected to clarify further the perception of the water security concept within CA by indicating the geophysical, institutional, and historical challenges that need to be met for a mutual understanding among the countries in the region.

Is reducing paid working time (WT) a potential win-win climate change mitigation strategy, which may simultaneously serve environmental sustainability and human well-being? While some researchers and commentators frequently refer to such 'double-dividends', most climate and environmental discussions ignore this topic. The societal relevance of paid WT and the potential role of its reduction as a demand-side measure for mitigating the climate- and ecological crisis calls for a critical review of the evidence. Here we systematically review the empirical, quantitative literature on the relationships between paid WT and a number of environmental indicators: resource use (incl. energy), greenhouse gas emissions and the ecological footprint. We applied two comprehensive search queries in two scientific databases; screened ∼2500 articles published until December 2019, and used citation snowballing to identify relevant research. However, we only found 15 fully relevant studies, as well as a number of partially relevant ones. This literature employs substantially different scopes, indicators and statistical methods, each with important caveats, which inhibits a formal quantitative evidence synthesis but usefully informs a critical discussion of the research frontier. Most studies conclude that reductions in paid WT reduce environmental pressures, primarily by decreasing incomes and consumption expenditures. However, existing research does not provide reliable guidance beyond the established link between expenditures and environmental impacts. Quantifying the effects of time use changes and macro-economic feedbacks through productivity, employment, and the complementarity or substitution between human labour and natural resources in production processes has proven to be difficult. To better understand the environmental impacts of specific types of WT reductions, new forms of data collection as well as studies at different scales and scopes are required. The critical discussion of the existing literature helps to conceptually map the pathways investigated so far and to identify crucial next steps towards more robust insights.

As ozone pollution in the troposphere has become increasingly severe, more publications have focused on the emissions of biogenic volatile organic compounds (BVOCs), which are important precursors for ozone formation. However, most reviews describe the research status of certain specific aspects rather than holistically quantifying research hotspots and development trends, which limit the overall understand of BVOCs emissions. In this paper, bibliometric analysis was used to study the publication output and hotspots of BVOCs emissions research from 1991 to 2019. Then, the evolutionary trends in BVOCs emission sources research were explored further by combining evolution tree and Markov chain methods. We found that the USA consistently took the leading position in BVOCs research, which cooperated with Germany and China closely. Environmental Science & Ecology and Meteorology & Atmospheric Sciences were the most active research subject categories. Current literatures mainly focused on the plant stress response, the atmospheric chemistry of BVOCs emissions, and their measurement by field determination and model-based estimation. Most publications researched BVOCs emitted by plants, in particular Pinaceae, while the growth of publications researching microbial volatile organic compounds (mVOCs) was slow. In the future, we should consider the role of mVOCs and combine field observation with model estimation to improve the credibility of BVOCs estimates and provide scientific guidance for air pollution control. And, with climate change, it will be worth exploring the driving variables of BVOCs emissions and its interaction in earth system to unravel how BVOCs emissions will respond to the changing earth system.

Large quantities of mineral phosphorus (P) fertilizer are often applied to intensively cultivated organic soils. Although erosion and runoff can contribute to loss of P, the large amount of fertilizer applied causes a rapid build-up of this nutrient, resulting in the downward movement of excess P in the soil profile and subsequent loss through tile drainage water. For arable organic soils, these losses often occur through subsurface tile drains, a common requirement to maintain a favorable air–water balance in the crop root zone, as well as to prevent soil subsidence. As such, subsurface drainage is a major pathway for agricultural P loss, contributing to persistent eutrophication of rivers, lakes, and estuaries globally. Although studies have been conducted on P mitigation within organic soils, application of drainage water management (DWM) as a P mitigation strategy in these soils, has not been extensively studied. The objective of this paper is to address this gap in knowledge by reviewing previous studies on P losses from subsurface drained agricultural organic soils while evaluating potential mitigation strategies. Specifically, this paper assesses the unique properties of organic soils that could influence P fate and transport, such as the distribution of P pools within the soil pools; variable pore geometry, hydrophobicity, and shrinkage; P loads exiting tile drains; and DWM practices in mitigating P losses. It is concluded that P retention is affected by the dynamic nature of soil water movement in organic soils and that substantial P loads enter surrounding water bodies via subsurface drainage effluent. There is evidence that DWM is an effective best management practice in the abatement of subsurface P losses.

Understanding past and projected drought patterns across Central America's 'Dry Corridor' (CADC) is crucial for adaptation planning and impact mitigation, especially in small-scale agricultural communities. We analyzed historical and predicted drought patterns in the CADC by calculating Standardized Precipitation Index (SPI) values from local rain gauge records, reanalysis data and a 20-member ensemble of bias-corrected, downscaled CMIP-5 GCMs at both seasonal (3 month) and annual (12 month) scales. Trends in drought frequency, duration, intensity were assessed for three, 30 year future periods compared to historical values. Our results suggest a decrease in mean annual rainfall of 8%–14% in the CADC under moderate to high emissions scenarios, respectively, by end-of-century (2071–2100) relative to a historical baseline (1950–2005). However, projected changes to drought characteristics under these scenarios are more pronounced, with seasonal-scale droughts projected to lengthen by 12%–30%, intensify by 17%–42% and increase in frequency by 21%–24% by end-of-century. Annual-scale, longer-term droughts are projected to lengthen by 68% under moderate emissions, potentially triple in length under high emissions and to intensify by 27%–74%. These results were similar yet slightly more pronounced for some drought metrics when just considering rainy/cropping season months (May–Oct). End-of-century changes to rainfall reliability and drought occurrence such as these would severely impact millions of vulnerable inhabitants in the CADC and should be considered in adaptation policymaking efforts.

Sedge-mediated gas transport to the atmosphere has been recognized as a significant CH₄ pathway in northern peatlands; however, in the Tropics, this pathway remains unquantified. In Southeast Asia, degraded tropical peatlands covered with sedges and ferns have increased to approximately 10% of the total peatland area due to an increased drainage and fires. In view of this, we investigated the role of sedge, Scleria sumatrensis, in CH₄ emissions from a fire-degraded tropical peatland in Brunei. At our site, we found that this sedge-mediated transport contributed >70% of the total CH₄ emission, making it a significant CH₄ emission pathway. We also observed significant seasonal and spatial variation with values ranging from 0.78 ± 0.14 to 4.86 ± 0.66 mgCH₄ m⁻² h⁻¹. This variation was mainly attributed to water table level along with changes in sedge cover and pore-water properties (pH, salinity, cations, and anions). More importantly, these numbers are three times higher when compared to intact peat-swamp forests and 17 times higher when compared to similar degraded tropical peatland covered with shrubs.

Yield stability is important for food security and a sustainable crop production, especially under changing climatic conditions. It is well known that the variability of yields is linked to changes in meteorological conditions. However, little is known about the long-term effects of agronomic management strategies, such as the supply of important nutrients. We analysed the stability of four major European crops grown between 1955 and 2008 at a long-term fertilization experiment located in Germany. Six fertilizer treatments ranged from no fertilization over the omission of individual macronutrients to complete mineral fertilization with all major macronutrients (nitrogen, phosphorus, potassium and calcium). Yield stability was estimated for each crop × treatment combination using the relative yield deviation in each year from the corresponding (nonlinear) trend value (relative yield anomalies (RYA)). Stability was lowest for potato, followed by sugar beet and winter wheat and highest for winter rye. Stability was highest when soils had received all nutrients with the standard deviation of RYA being two to three times lower than for unfertilized plots. The omission of nitrogen and potassium was associated with a decrease in yield stability and a decrease in the number of simultaneous positive and negative yield anomalies among treatments. Especially in root crops nutrient supply strongly influenced both annual yield anomalies and changes in anomalies over time. During the second half of the observation period yield stability decreased for sugar beet and increased for winter wheat. Potato yields were more stable during the second period, but only under complete nutrient supply. The critical role of potassium supply for yield stability suggests potential links to changes in the water balance during the last decades. Results demonstrate the need to explicitly consider the response of crops to long-term nutrient supply for understanding and predicting changes in yield stability.

Dense shelf water (DSW) produced in the western Ross Sea (RS) is one of the major sources of Antarctic bottom water (AABW). Thus the understanding of long-term variability of DSW salinity and its controlling factors in the western RS is critical to assess the variability of globally distributed AABW. Here we analyze a long time record of hydrographic data (1984–2020) collected in the western RS, as well as sea ice drift vectors, surface wind speed, sea level pressure and Amundsen Sea low (ASL) indices. We confirm recent findings that there is a rapid increase of DSW salinity in the western RS after a minimum in 2013, although the DSW has experienced substantial freshening in the past few decades, indicating a significant multidecadal variability of DSW salinity in the western RS. Over the past four decades, multidecadal variability in the DSW salinity has been strongly coupled with westward zonal flow changes along the coastal current, and the post-2013 rapid enhancement of DSW salinity is accompanied by reduced freshwater input due to weakening of the westward zonal flow from the upstream Amundsen Sea (AS) into the RS. Large-scale circulation determining the strength of the zonal flow is closely linked to the ASL variability. The accelerated deepening of the ASL and the resulting southwestward extension of low pressure induce an eastward coastal current anomaly. This reduces the freshwater input from the AS to the RS and is responsible for the subsequent enhancement of DSW salinity in recent years in the western RS. These dynamical processes demonstrated here explain how the ASL changes modulate the DSW salinity in the western RS, and will help to understand the implication of climate changes in the Southern Ocean on AABW formation.

Nutrient and sediment transport exhibit strong spatial and temporal inequality, with a small percentage of locations and events contributing to the vast majority of total annual loads. The processes for determining how to reduce total annual loads at a watershed scale often target spatial, but not temporal, components of inequality. We introduce a framework using Lorenz Inequality and corresponding Gini Coefficient to quantify the temporal inequality of nutrient and sediment transport across the Chesapeake Bay watershed. This long-impaired, 166 000 km² watershed has been federally mandated since 2010 to continually reduce nutrient and sediment loads reaching the Bay. Data were obtained for 108 sites in the Chesapeake Bay's non-tidal network from 2010 to 2018. The Lorenz Inequality and Gini Coefficient analyses were conducted using daily-scale data for flow and loads of total nitrogen (TN), total phosphorus (TP), and total suspended sediment (TSS) at each gaging station. We leverage these results to create a 'temporal targeting framework' that identifies periods of time and corresponding flow conditions that must be targeted to achieve desired or mandated load reduction goals across the watershed. Among the 108 sites, the degree of temporal inequality for TP and TSS (0.37–0.98) was much greater than for flow and TN (0.29–0.77), likely due to the importance of overland versus baseflow in the transport pathways of the respective constituents. These findings stress the importance of informed design and implementation of best management practices effective in 'hot moments,' and not just 'hot spots,' across impaired watersheds to achieve and maintain water quality restoration goals. The 'temporal targeting framework' detailed in this manuscript provides a useful and convenient method for watershed planners to create low- and high-flow load targeting tables specific to a watershed and constituent.

Fossil fuel (FF) burning, the main energy source of the modern world's economy, remains the major source of anthropogenic carbon dioxide (CO₂) and pollutants in the atmosphere. Based on 18 years (2001–2018) of aerosol optical depth (AOD) data from Moderate Resolution Imaging Spectroradiometer satellite, FFCO₂ emissions from the Open-Data Inventory for Anthropogenic Carbon dioxide, and gross domestic product (GDP) data from the World Bank, we found that air quality, FF consumption, and economy are strongly bonded at the continental scale but decoupled at the national level under favorable policies. The comparison of AOD vs PM_2.5 and NO₂ over urbanized areas shows that the pollutants leading to the AOD load can vary significantly by country. A strong connection between GDP and FFCO₂ emissions indicates that economic growth deeply replies on FF consumption in most countries. Meanwhile, air pollution is more associated with the growing trend than the level of development of a country. With more mature technologies and renewable energy, economies can keep growing without compromising their environment and population health.

Long-duration droughts are usually tied to persistent local or remote forcings; for example, persistent droughts over California are frequently observed along with the 'ridiculously resilient ridge' over the West Coast. It is now evident that some oceanic forcings (e.g. El Niño–Southern Oscillation) have global reaches and affect multiple regions concurrently during their progression. Here, we show robust significant temporal concordancy of persistent droughts in many regions, revealing multiple teleconnections (distant regions experiencing droughts concurrently), such as the 'Western North America–Mediterranean (WNA–MED)' and the 'Southeast Asia–Southern Africa (SEA–SAF)' teleconnections. Composite pressure and sea surface temperature anomalies during concurrent droughts in WNA and the MED reveal a persistent weather regime that resembles the positive phase of Arctic Oscillation and negative phase of Pacific Decadal Oscillation. During concordant droughts of SEA and SAF, composite pressure anomalies remarkably resemble the El Niño pattern, which we infer as the leading cause of the teleconnection. The insights gained here offer a new dimension to understanding droughts and improving their long-term predictability.

Vegetation properties of arctic tundra vary dramatically across its full latitudinal extent, yet few studies have quantified tundra ecosystem properties across latitudinal gradients with field-based observations that can be related to remotely sensed proxies. Here we present data from field sampling of six locations along the Eurasia Arctic Transect in northwestern Siberia. We collected data on the aboveground vegetation biomass, the normalized difference vegetation index (NDVI), and the leaf area index (LAI) for both sandy and loamy soil types, and analyzed their spatial patterns. Aboveground biomass, NDVI, and LAI all increased with increasing summer warmth index (SWI—sum of monthly mean temperatures > 0 °C), although functions differed, as did sandy vs. loamy sites. Shrub biomass increased non-linearly with SWI, although shrub type biomass diverged with soil texture in the southernmost locations, with greater evergreen shrub biomass on sandy sites, and greater deciduous shrub biomass on loamy sites. Moss biomass peaked in the center of the gradient, whereas lichen biomass generally increased with SWI. Total aboveground biomass varied by two orders of magnitude, and shrubs increased from 0 g m⁻² at the northernmost sites to >500 g m⁻² at the forest-tundra ecotone. Current observations and estimates of increases in total aboveground and shrub biomass with climate warming in the Arctic fall short of what would represent a 'subzonal shift' based on our spatial data. Non-vascular (moss and lichen) biomass is a dominant component (>90% of the photosynthetic biomass) of the vegetation across the full extent of arctic tundra, and should continue to be recognized as crucial for Earth system modeling. This study is one of only a few that present data on tundra vegetation across the temperature extent of the biome, providing (a) key links to satellite-based vegetation indices, (b) baseline field-data for ecosystem change studies, and (c) context for the ongoing changes in arctic tundra vegetation.

The potential effect of climate change on regional suitability for cocoa cultivation is a serious economic concern for West Africa—especially for Ghana and Côte d'Ivoire, whose cocoa cultivation accounts for respectively ∼19% and ∼45% of world production. Here, we present a modelling and observational study of cocoa net primary productivity (NPP) in present day and future West African climates. Our analysis uses a data assimilation technique to parameterise a process-based land-surface model. The parameterisation is based on laboratory observations of cocoa, grown under both ambient and elevated CO₂. Present day and end of 21st century cocoa cultivation scenarios are produced by driving the parameterised land-surface model with output from a high-resolution climate model. This represents a significant advance on previous work, because unlike the CMIP5 models, the high-resolution model used in this study accurately captures the observed precipitation seasonality in the cocoa-growing regions of West Africa—a key sensitivity for perennials like cocoa. We find that temperature is projected to increase significantly and precipitation is projected to increase slightly, although not in all parts of the region of interest. We find, furthermore, that the physiological effect of higher atmospheric CO₂ concentration ameliorates the impacts of high temperature and variation in precipitation thereby reducing some of the negative impacts of climate change and maintaining NPP in West Africa, for the whole 21st Century, even under a high emissions scenario. Although NPP is an indicator of general vegetation condition, it is not equivalent to yield or bean quality. The study presented here is, nevertheless, a strong basis for further field and modelling studies of cultivation under elevated CO₂ conditions.

Actions tackling with climate change can cause co-benefits and trade-offs with Sustainable Development Goals (SDGs) concerned with air pollution, water scarcity, food security, land use, and sustainable energy. Such interactions can be greatly influenced by socioeconomic conditions. The impacts of socioeconomic conditions on multiple SDGs have not been evaluated separately from climate policies. This paper employs a Representative Concentration Pathways–Shared Socio-economic Pathways (RCP-SSP) framework and the Asia-Pacific Integrated Model/computable general equilibrium (AIM/CGE) integrated assessment model to identify the global multi-sectoral consequences of socioeconomic conditions through 2050 under future SSP scenarios. Results show that changes of socioeconomic conditions consistent with the SSP1 pathway could always improve SDG indicators, with or without climate policies. In many respects, socioeconomic conditions are more important than climate policies in achieving SDGs, particularly SDGs concerned with food security and energy affordability, as well as in simultaneously achieving multiple SDGs. We conclude that the advantages of a joint effort to implement climate policies and promulgate socioeconomic changes should be recognized by policy makers.

The Tibetan Plateau (TP), as a whole, has undergone a moistening process since the late 1990s. However, the southern Tibetan Plateau (STP) is an exception, where summer monsoon precipitation amount has decreased, and lakes have shrunk. The cause for the precipitation decrease is not clear yet. Here we show that the monsoon (June to September) mean precipitation changes in the STP from 1979 to 2018 features a decadal variation component with a peak of around 10 years that is superposed on an upward 'trend' from 1979 to 1998 and a downward 'trend' afterward. We find that the decadal variation of the STP precipitation is associated with a large-scale dipolar sea surface temperature (SST) pattern between the equatorial central Pacific and the Indo-Pacific warm pool. A wet STP corresponds to negative SST anomaly in the equatorial central Pacific and positive SST anomaly in the Indo-Pacific warm pool. This equatorial SST gradient in the western Pacific generates pronounced easterly anomalies and a dipolar rainfall anomaly (i.e. a positive rainfall anomaly over the Maritime Continent and a negative anomaly in the equatorial western and central Pacific). Due to less precipitation over the equatorial western Pacific, the suppressed heat source appears to excite an anomalous anticyclonic band along 15–20° N extending from the Philippine Sea to the Bay of Bengal by emanating westward propagating descending transient Rossby waves. The low-level anticyclonic circulation over the Bay of Bengal further enhances northward moisture transport toward the STP and promote upward motion in the STP through changing local meridional circulation. Besides, the linearized atmospheric general circulation model experiments demonstrate that the dipole heating source can generate a high-pressure zone under the control of anticyclone over the western Pacific, which can extend westward to the Indian monsoon region.

Satellite-derived and reported sulfur dioxide (SO₂) emissions from the Canadian oil sands are shown to have been consistent up to 2013. Post-2013, these sources of emissions data diverged, with reported emissions dropping by a factor of two, while satellite-derived emissions for the region remained relatively constant, with the discrepancy (satellite-derived emissions minus reported emissions) peaking at 50 kt(SO₂) yr⁻¹ around 2016. The 2013–2014 period corresponds to when new flue-gas desulfurization units came on-line. Previous work has established a high level of consistency between at-stack SO₂ emissions observations and satellite estimates, and surface monitoring network SO₂ concentrations over the same multi-year period show similar trends as the satellite data, with a slight increase in concentrations post-2013. No clear explanation for this discrepancy currently exists. The implications of the discrepancy towards estimated total sulfur deposition to downwind ecosystems were estimated relative to 2013 emissions levels, with the satellite-derived values leaving the area of regional critical load exceedances of aquatic ecosystems largely unchanged from 2013 values, 335 000 km², and reported values potentially decreasing this area to 185 000 km².

Anthropogenic carbon emissions from fires impact the global carbon budget and contribute to global warming. However, due to the lack of inventory data, little was known about how carbon emissions differed between human-caused and lightning-caused fires previously. In this study, the Fire Program Analysis fire-occurrence database (FPA FOD) and the Global Fire Emissions Database (GFED) were combined to analyze the influences of human-caused fires on carbon emissions. We found that the GFED burned area was larger than that of the FPA FOD since the FPA FOD did not cover human-caused fire usages like prescribed fires. Carbon emissions over the conterminous United States were increasing significantly from 1997 to 2015. Human-caused fires released 9.99 Tg C yr⁻¹ over the conterminous United States, which were approximately twice those of carbon emissions from lightning-caused fires, 5.44 Tg C yr^−1. Carbon emissions of lightning-caused fires were increasing while those of human-caused fires were decreasing significantly with rising temperatures. Emissions in ecoregions such as the Eastern Temperate Forests, the Great Plains, the Marine West Coast Forests, and the Northern Forests were dominated by human-caused fire emissions, whose proportions were over 86%. These results highlight the importance of human activities on carbon emissions, offering new insights into the role of humans in climate change mitigation.

Since the Green Revolution in the mid-1960s, a widespread transition to a rice–wheat rotation in the Indian state of Punjab has led to steady increases in crop yield and production. After harvest of the summer monsoon rice crop, the burning of excess crop residue in Punjab from October to November allows for rapid preparation of fields for sowing of the winter wheat crop. Here we use daily satellite remote sensing data to show that the timing of peak post-monsoon fire activity in Punjab and regional aerosol optical depth (AOD) has shifted later by approximately two weeks in Punjab from 2003 to 2016. This shift is consistent with delays of 11–15 d in the timing of maximum greenness of the monsoon crop and smaller delays of 4–6 d in the timing of minimum greenness during the monsoon-to-winter crop transition period. The resulting compression of the harvest-to-sowing period coincides with a 42% increase in total burning and 55% increase in regional AOD. Potential drivers of these trends include agricultural intensification and a recent groundwater policy that delays sowing of the monsoon crop. The delay and amplification of burning into the late post-monsoon season suggest greater air quality degradation and public health consequences across the densely populated Indo-Gangetic Plain.

The Asian tropopause aerosol layer (ATAL) is characterized by enhanced aerosol concentrations in the Asian summer monsoon anticyclone in the upper troposphere and lower stratosphere at 13–18 km altitude. A growing body of evidence suggests that the aerosol enhancement is closely connected with deep convection during the monsoon. However, the origin of the aerosols is under debate, and the key factors that determine the ATAL variability remain poorly understood. We investigated the formation and dissipation mechanisms of the ATAL and the inter-annual variation from a dynamical viewpoint using satellite observations and meteorological reanalysis data from 2012 to 2018. We identified the northern Bay of Bengal and adjacent land area, where air pollution from the Indian subcontinent converges, as the major convection source area of aerosols to the ATAL. The spatial extent of the ATAL, represented by the mean attenuated scattering ratio from satellite measurements, appears to be related to a secondary circulation driven by the stratospheric quasi-biennial oscillation. The aerosols are not homogeneously distributed within the ATAL, and descending motion in the western part is found to play an important role in dissipation of the layer. These findings elucidate the ATAL dynamics and associated regional and global air pollution transports.

Scenarios used by the Intergovernmental Panel on Climate Change (IPCC) are central to climate science and policy. Recent studies find that observed trends and International Energy Agency (IEA) projections of global CO₂ emissions have diverged from emission scenario outlooks widely employed in climate research. Here, we quantify the bases for this divergence, focusing on Kaya Identity factors: population, per-capita gross domestic product (GDP), energy intensity (energy consumption/GDP), and carbon intensity (CO₂ emissions/energy consumption). We compare 2005–2017 observations and IEA projections to 2040 of these variables, to 'baseline' scenario projections from the IPCC's Fifth Assessment Report (AR5), and from the shared socioeconomic pathways (SSPs) used in the upcoming Sixth Assessment Report (AR6). We find that the historical divergence of observed CO₂ emissions from baseline scenario projections can be explained largely by slower-than-projected per-capita GDP growth—predating the COVID-19 crisis. We also find carbon intensity divergence from baselines in IEA's projections to 2040. IEA projects less coal energy expansion than the baseline scenarios, with divergence expected to continue to 2100. Future economic growth is uncertain, but we show that past divergence from observations makes it unlikely that per-capita GDP growth will catch up to baselines before mid-century. Some experts hypothesize high enough economic growth rates to allow per-capita GDP growth to catch up to or exceed baseline scenarios by 2100. However, we argue that this magnitude of catch-up may be unlikely, in light of: headwinds such as aging and debt, the likelihood of unanticipated economic crises, the fact that past economic forecasts have tended to over-project, the aftermath of the current pandemic, and economic impacts of climate change unaccounted-for in the baseline scenarios. Our analyses inform the rapidly evolving discussions on climate and development futures, and on uses of scenarios in climate science and policy.

Despite the improving techniques for seasonal prediction of tropical storm frequency, attention seems focused on accuracy rather than on forecast interpretation. This study aims to show how seasonal predictions from a hybrid model, i.e. statistical/dynamical model, can be interpreted with probability distributions. The tropical storm frequency in the western North Pacific is modeled with environmental predictors through multiple linear regression. For a demonstration of the probabilistic structure of the prediction result, the forty-two member ensemble predictions from the Glosea5 model for June–July–August in 2020 are used as the dynamical input. Rather than dealing with the expected frequency, this study introduces the predictive probability for a single value of the frequency. From as many probability distributions, a marginal probability distribution is obtained as the final predictive probability distribution. The probability distribution is then compared to the climatological reference by terciles. Additionally, predictive probability distributions made with the individual predictors provide helpful information on how each contributes to the final prediction. This probabilistic interpretation procedure is expected to be effectively used for improving any hybrid approach.

Modelling frameworks that aim to support policymakers in deriving effective measures to reduce environmental impacts should provide both: quantitative information on locally occurring consumption patterns and production systems as well as assessment of policy scenario outcomes. Regionalised models that can deliver on these aims are emerging, but are currently limited in resolution or have other restrictions. An advanced model can be achieved by exploiting the advantages and overcoming the limitations of top-down and bottom-up approaches. In this article, we describe a highly detailed, spatially-resolved modelling framework that quantifies local activities and simultaneously analyses system-wide environmental and economic effects of planned interventions. We combined an existing, highly detailed bottom-up model for Switzerland (focusing on individual households) with a macro-economic top-down approach by developing a new Swiss sub-national, multi-region input-output model. We conducted two case studies to demonstrate its abilities and to highlight its usefulness. First, production-based greenhouse gas emissions and consumption-based carbon footprints were computed for all Swiss cantons and regional differences, interdependencies as well as embodied carbon flows among regions were investigated. We find that rural cantons have higher production-based emissions per gross domestic product than more urban cantons because of different economic structures. In contrast, certain 'city-cantons' entail highest consumption carbon footprints per inhabitant due to high per-capita gross capital formation. Furthermore, this case study discusses the importance of providing regionalised information on effects of measures along the economic value chains. Second, a detailed scenario assuming a realistic lifestyle change for an actual household and a thorough physical retrofit of its home was set up. Regionalised environmental and economic consequences along the supply chains were evaluated. This case study exemplifies how the modelling framework can be used to inform policymakers about expected benefits and downsides of detailed scenarios and emphasises the importance of considering rebound effects.

Nitrogen dioxide (NO₂) is a major urban air pollutant and is associated with new onset asthma among children worldwide. Since NO₂ concentrations are spatially heterogeneous and correlated with population, the spatial resolution of concentration estimates and disease burden calculations could strongly influence the magnitude and spatial distribution of estimated NO₂-attributable pediatric asthma (PA) cases. Here, we investigate the effect of spatial resolution of exposure and population data on estimated NO₂ attributable PA incidence. We use epidemiologically derived health impact functions to estimate NO₂-attributable asthma incidence for the U.S. and India, two countries with different degrees of urbanicity, using population and NO₂ concentration estimates at 100 m resolution and aggregated to coarser spatial resolutions: 500 m, 1 km, 10 km, and 100 km. Estimated NO₂-attributable PA burdens differ by <1% for resolutions of 100 m up to 1 km for both countries. However, performing the analysis at 10 km and 100 km results in 5% and 17% fewer new asthma cases among children in India and 6% and 32% fewer in the U.S., respectively. We performed a similar analysis for the 13 000 urban areas and present the results for the 500 most populated cities at 1 km and 10 km resolution, finding that the coarser resolution leads to lower estimated NO₂-attributable asthma incidence in nearly all cities, especially for cities with smaller land areas. We conclude that 1 km spatial resolution is a good balance between accuracy and computational efficiency in estimating NO₂-attributable asthma burdens at national and urban levels, and that coarser resolutions may result in underestimates.

The Southern Hemisphere (SH) eddy-driven jet stream has been shown to move poleward in climate models in response to greenhouse gas forcing, but the magnitude of the shift is uncertain. Here we address the fact that the latest Coupled Model Intercomparison Project phase 6 (CMIP6) models simulate, on average, a smaller jet shift in response to an abrupt quadrupling in CO₂ than the predecessor models (Coupled Model Intercomparison Project phase 5 (CMIP5)), despite producing larger global average surface warming. We focus on the response in the first decade when the majority of the long-term jet shift occurs and when the difference between CMIP5 and CMIP6 models emerges. We hypothesise the smaller poleward jet shift is related to the weaker increase in the meridional sea surface temperature (SST) gradient across the southern extratropics in CMIP6 models. We impose the multi-model mean SST patterns alongside a quadrupling in CO₂ in an intermediate complexity general circulation model (IGCM4) and show that many of the regional and seasonal differences in lower tropospheric zonal winds between CMIP5 and CMIP6 models are reproduced by prescribing the SST patterns. The main exception is in austral summer when the imposed SST patterns and CO₂ increase in IGCM4 produce weaker differences in zonal wind response compared to those simulated by CMIP5/6 models. Further IGCM4 experiments that prescribe only SH extratropical SSTs simulate a weaker jet shift for CMIP6 SSTs than for CMIP5, comparable to the full experiment. The results demonstrate that SH SST patterns are an important source of uncertainty for the shift of the midlatitude circulation in response to CO₂ forcing. The study also provides an alternative explanation than was proposed by Curtis et al (2020 Environ. Res. Lett.15 64011), who suggested model improvements in jet biases could account for the smaller jet shift in CMIP6 models in the extended austral winter season.

The dynamics of interactions between the environmental and the meteorological variables in an urban region is extremely complex due to continuously evolving coupled human–natural processes in an urban setting. We attempt to understand the same with the networks of variables using information theory, known as process network. We monitored local meteorological variables at half-hourly scale using an eddy covariance observation system combined with available concentration of pollutants from other sources. Both the datasets are for Powai, Mumbai, India, from January to April 2020 that includes pre-lockdown and lockdown periods associated with interventions in response to COVID-19. Analysis of the weekly process networks developed with the same data shows that they are more dominated by memory during the lockdown period. We find that a high concentration of pollutants under no-lockdown scenarios, during specific work commute hours, interrupts the memory of the network. A seasonal transition in temperature during the pre-lockdown period failed to make any major changes. Our analysis shows that the dynamics of pollutant concentration drives the interaction between the variables of urban environmental meteorological system.

Despite much attention in the literature, knowledge about the dynamics surrounding urban densification and urban greening is still in dire need for architects, urban planners and scientists that strive to design, develop, and regenerate sustainable and resilient urban environments. Here, we investigate countrywide patterns of changes in residential density and residential nature at high spatial resolution over a time period of >20 years (1995–2016), combining a dataset of address-level population data covering all of Denmark (>2 million address points) with satellite image-derived normalised difference vegetation index (NDVI) data. Our results show that many residential environments across Denmark have witnessed simultaneous densification and greening since the mid-1990s. In fact, the most common change within 500 m neighbourhoods around individual address points is of joint increases in population and NDVI (28%), followed by increasing NDVI with stable population figures (21%). In contrast, only 8% of neighbourhoods around address points have seen a decline in either population or NDVI. Results were similar in low- middle- and high-density environments, suggesting that trends were driven by climate change but also to some degree enabled by urban planning policies that seek to increase rather than decrease nature in the cities.

We investigate the potential in producing biodegradable bio-plastics to support the emergent 'net-zero' greenhouse gas (GHG) emissions targets in the UK. A 'cradle to grave' life cycle assessment was developed to evaluate GHG mitigation potentials of bio-based polybutylene succinate plastics produced from wheat straw-only (single feedstock) or wheat straw plus Miscanthus (mixed feedstocks) agricultural supply systems. For scenarios using mixed feedstocks, significant carbon mitigation potentials were identified at catchment and national levels (emission reduction of 30 kg CO₂eq kg⁻¹ plastic compared to petroleum-based alternatives), making the system studied a significant net carbon sink at marginal GHG abatement costs of £0.5–14.9 t⁻¹ CO₂eq. We show that an effective 'net-zero' transition of the UK's agricultural sector needs spatially explicit, diversified and integrated cropping strategies. Such integration of perennial bio-materials into food production systems can unlock cost-effective terrestrial carbon sequestration. Research & Development and scale-up will lower costs helping deliver a sustainable bioeconomy and transition to 'net-zero'.

Food loss (wasted and spoiled food) increases the burden on resources and environmental impacts throughout the entire food chain. This study describes and deploys a model and identifies data sources for estimation of greenhouse gas (GHG) emissions associated with food loss from farm production, delivery and refrigeration, retail sale, household consumption, and waste management in the United States using four California-grown high-value produce as case studies. The ratios of food wasted to food produced are 50%, 60%, 50%, and 64% for avocados, celery, lemons, and strawberries, respectively, and the differences are largely influenced by consumer-level and on-farm food loss. From the consumption perspective, this means, for example, that 1.8 units of strawberries are wasted for every unit consumed. The packaging material is a significant environmental offender, contributing, e.g. 52% to the total emissions (without food loss) for strawberries. End-of-life analysis of wasted food and packaging covers the common waste management practices: landfilling, composting, anaerobic digestion, incineration, and recycling. Uncertainties in the data are assessed through Monte Carlo simulation. With the consideration of food loss, the total GHG emissions from the entire life cycle of strawberries, celery, avocados, and lemons increase by 93%, 62%, 56%, and 53% to 0.26, 0.038, 0.061, and 0.058 kg CO₂ eq. per one serving size, respectively. Emissions from the annually wasted strawberries, avocados, celery, and lemons in California amount to 76, 24, 12, and 12 000 tons of CO₂ eq., respectively. Fourteen percent of the world's population could have a serving of strawberries just from the annually wasted strawberries in California. However, wasteful consumer action can be even more significant. Emissions from a typical driving scenario to a store to purchase only one produce exceeds the emissions associated with all four produce combined. Reducing food waste during consumption and the environmental impacts of packaging should be prioritized.

Rivers are essential to human livelihoods and agricultural production, yet human usage and irrigation are jeopardizing river sustainability. It is thus crucial to investigate the fine-scaled spatiotemporal dynamics of anthropogenic pressures on rivers. Most research, however, is conducted at the grid-scale, which impedes detailed investigations. In this study, by tracking anthropogenic pressures at the scale of river reaches (the length of river between river confluences) in South and Southeast Asia from 1990 to 2014, we provide new insights into anthropogenic pressures on river reaches using a simple and straightforward approach. We selected human usage (represented by built-up area) and irrigation (represented by irrigated area) as two fundamental indicators of anthropogenic pressure. We divided the study area into 5 × 5 km grids and calculated anthropogenic pressures on each grid to its nearest river reach. Pressures were calculated as the ratio of built-up and irrigated area to the distance between grids and reaches. Groundwater was also included to adjust for additional irrigation-induced pressures on reaches. Anthropogenic pressures on each reach were then calculated by summing pressures from the two indicators of all grids attached to it. Results indicate that >50% of reaches are affected by anthropogenic activities and that average pressures increase by ∼15% from 1990 to 2014, with hotspots concentrated in eastern Pakistan and northern India. Irrigation is the dominant pressure on ∼33% of reaches, while human usage is dominant for ∼24% of reaches. Anthropogenic pressures within transboundary river basins vary longitudinally, increasing as distance from the ocean declines. Pressures also vary significantly with reach size. Although large rivers suffer from greater anthropogenic pressures, they are rising more rapidly for small rivers. Empirically, this study reveals the increasing and heterogeneous nature of anthropogenic pressures on river reaches in South and Southeast Asia. Methodologically, it suggests that reach-scale river sustainability assessment can serve as a promising approach for researching and managing regional and transboundary rivers.

The COVID-19 pandemic continues to expand, while the relationship between weather conditions and the spread of the virus remains largely debatable. In this paper, we attempt to examine this question by employing a flexible econometric model coupled with fine-scaled hourly temperature variations and a rich set of covariates for 291 cities in the Chinese mainland. More importantly, we combine the baseline estimates with climate-change projections from 21 global climate models to understand the pandemic in different scenarios. We found a significant negative relationship between temperatures and caseload. A one-hour increase in temperatures from 25 °C to 28 °C tends to reduce daily cases by 15.1%, relative to such an increase from −2 °C to 1 °C. Our results also suggest an inverted U-shaped nonlinear relationship between relative humidity and confirmed cases. Despite the negative effects of heat, we found that rising temperatures induced by climate change are unlikely to contain a hypothesized pandemic in the future. In contrast, cases would tend to increase by 10.9% from 2040 to 2059 with a representative concentration pathway (RCP) of 4.5 and by 7.5% at an RCP of 8.5, relative to 2020, though reductions of 1.8% and 18.9% were projected for 2080–2099 for the same RCPs, respectively. These findings raise concerns that the pandemic could worsen under the climate-change framework.

The present study examines the role of the Southern Indian Ocean (SIO) warming on the cyclone destruction potential or Power Dissipation Index (PDI) during two contrasting periods of 1980–1998 and 1999–2016. The PDI in the SIO during 1999–2016 is found to have doubled compared to the same during 1980–1998. PDI was computed using the tropical cyclone track data in the SIO region for cyclone category three and above. The increasing trend in PDI during the latter period is primarily due to an increase in the intensity of cyclones and their duration. The increasing PDI is associated with a sea surface temperature warming and an upper ocean heat content increase as well as a significant slowdown in translation speeds. The increase in upper ocean heat content during the recent decades enhances the intensification of cyclones and their duration, which is consistent with the slowdown of cyclones. Analysis of the relevant atmospheric parameters indicates that processes in the atmosphere did not play a major role in the recent decades in increasing cyclone intensity. We show that in the SIO, ocean processes play a major role in the PDI rise during the recent period. Any continued increase in PDI will cause more loss of life and socioeconomic damage to the island countries such as Mozambique, Mauritius, Mascarene Islands and Madagascar, as well as the coastal inhabitants along East Africa.

Most of the excess energy stored in the climate system is taken up by the oceans leading to thermal expansion and sea level rise. Future sea level projections allow decision-makers to assess coastal risk, develop climate resilient communities and plan vital infrastructure in low-elevation coastal zones. Confidence in these projections depends on the ability of climate models to simulate the various components of future sea level rise. In this study we estimate the contribution from thermal expansion to sea level rise using the simulations of global mean thermosteric sea level (GMTSL) from 15 available models in the Coupled Model Intercomparison Project Phase 6 (CMIP6). We calculate a GMTSL rise of 18.8 cm [12.8–23.6 cm, 90% range] and 26.8 cm [18.6–34.6 cm, 90% range] for the period 2081–2100, relative to 1995–2014 for SSP245 and SSP585 scenarios respectively. In a comparison with a 20 model ensemble from Coupled Model Intercomparison Project Phase 5 (CMIP5), the CMIP6 ensemble mean of future GMTSL (2014–2100) is higher for both scenarios and shows a larger variance. By contrast, for the period 1901–1990, GMTSL from CMIP6 has half the variance of that from CMIP5. Over the period 1940–2005, the rate of CMIP6 ensemble mean of GMTSL rise is 0.2 ± 0.1 mm yr⁻¹, which is less than half of the observed rate (0.5 ± 0.02 mm yr⁻¹). At a multi-decadal timescale, there is an offset of ∼10 cm per century between observed/modelled thermosteric sea level over the historical period and modelled thermosteric sea level over this century for the same rate of change of global temperature. We further discuss the difference in GMTSL sensitivity to the changes in global surface temperature over the historical and future periods.

Sediment transfer, or connectivity, by aeolian processes between channel-proximal and upland deposits in river valleys is important for the maintenance of river corridor biophysical characteristics. In regulated river systems, dams control the magnitude and duration of discharge. Alterations to the flow regime driven by dams that increase the inundation duration of sediment, or which drive the encroachment of vegetation into areas formerly composed of labile sediment and result in channel narrowing, may reduce sediment transfer from near-channel deposits to uplands via aeolian processes. Employing spatial methods developed by Kasprak et al (2018 Prog. Phys. Geogr.), here we use data describing the areal extent of bare (i.e. subaerially exposed and non-vegetated) sediment along 168 km of the Colorado River downstream from Glen Canyon Dam in Grand Canyon, USA, in conjunction with inundation extent modeling to forecast how future flows of this highly regulated river will drive changes in the areal extent of sediment available for aeolian transport. We also compare modern bare sediment area to that which presumably would have existed under pre-dam hydrographs. Over the next two decades, the planned flow regime from Glen Canyon Dam will result in slight decreases in bare sediment area (−1%) on an annual scale. This is in contrast to pre-dam years, when unregulated low flows led to marked increases in bare sediment area as compared to the current discharge regime. Our findings also indicate that ∼75% of bare sediment in the study reach is inundated continuously at present, owing to increased baseflows in the post-dam flow regime; consequently, any reductions in flows below modern-day low discharges have the potential to expose large areas of bare sediment. We use vegetation modeling to quantify areas susceptible to vegetation encroachment under future flows, finding that 80% of bare sediment area is suitable for colonization by invasive tamarisk under the current flow regime. Our findings imply that the Colorado River in Grand Canyon, a system marked by widespread erosion of sediment resources and encroachment of riparian vegetation in the post-dam period, is likely to continue to see decreasing bare sediment extent over the coming decades in the absence of direct intervention through flow regime modification or widespread vegetation removal.

In forest restoration projects, assessing progress is critically important. This study was conducted to quantify the restoration progress for approximately 30 year old plantation plots of Acacia and Pterocarpus in Sakaerat, Thailand. For 22.5 × 22.5 m areas in the plantation plots, as a continuous measure of forest restoration, dry evergreen forest-likelihood was determined using 45 cm resolution satellite images and an artificial neural network architecture. The Acacia plot achieved a moderate mean evergreen forest likelihood of 0.451 (April 2016) to 0.679 (May 2019), but the values for the Pterocarpus plot were 0.076 or smaller. Two other Pterocarpus plots at cooler and moister sites had mean evergreen forest-likelihood values of up to 0.884 (April 2016), which were significantly greater than that (0.451) for the Acacia plot, but the values dropped in May 2019. Throughout the period of the four image acquisition times from March 2014 to May 2019, the plantation plots had significantly smaller evergreen forest-likelihood than the dry evergreen forest did. The current approach would be a helpful option for stakeholders of forest management by applying sub-m-resolution images and machine learning followed by quantification of the forest restoration effects relying on the appearance and texture of tree canopies at multiple data acquisition times.

Tundra vegetation dynamics are an excellent indicator of Arctic climate change. In many places in the Arctic, greening of tundra has been observed since the 1980s due to rapid increases in temperature. However, in some areas the opposite process has taken place in connection with a reduction in biomass production. The spatial patterns of tundra 'greening' and 'browning' constitute important issues in the contemporary analysis of polar ecosystems. The aim of our study was to assess recent tundra vegetation dynamics on the basis of changes in annual growth ring widths of the polar willow. Bjørnøya (Bear Island), located in the western part of the Barents Sea is an important site in the transition zone between the high and low Arctic. No dendrochronological studies have been conducted to date due to the island's isolation, which makes access very difficult. In 2012 and 2016, 43 samples of Salix polaris Wahlenb. were taken from the south-eastern part of Bear Island. An average chronology of the 29 most closely correlated measurement series was then compiled, covering 95 years (1922–2016); however, the time span 1946–2016 was used for the climate-growth analysis. Beginning in the mid-1980s, an increase in the width of annual increments was observed, whereas over the last decade (since 2005) the growth rate has declined rapidly. Simple correlation analyses showed that temperatures in spring and summer had the positive influence on the radial growth of the polar willow; however, the results of the moving correlation analysis made it possible to conclude that this relationship is more complex and time-dependent. Sensitivity of radial growth to temperature was strongest in the years 1955–2005, whereas the decrease in the strength of positive correlation with temperature since 2005 has been accompanied by a significant increase in the importance of summer precipitation.

Climate change and large-scale afforestation characterize the conditions in the Upper Dongjiang River Basin (UDRB), which is one of the most important headwater basins in southern China. It is important to understand whether, and to what extent, the observed runoff change can be attributed to forest and/or climate change. Using process- and relation-based methods, we found precipitation in spring (March–May) decreased notably, while precipitation in summer (June–August) showed an increase from the reference period (1961–1990) to the afforestation period (1991–2010). In comparison, annual averaged potential evapotranspiration did not change much. Both of the methods indicated forest had a positive effect while climate change exerted a negative impact on annual averaged runoff in the UDRB. As a result, the observed annual averaged runoff only showed a little decrease from the reference period to the afforestation period. The climate change impact on monthly averaged runoff basically followed the pattern of precipitation change. Except in July and August, climate change exerted negative or little impact on runoff in most of other months. In comparison, the forest effects on monthly averaged runoff change showed a totally different pattern. Except in May and June, forest exerted positive impact on runoff in other months. As a result, the observed monthly averaged runoff in May and June experienced notable reduction, while those in other months experienced increase or no change. The UDRB provides evidence that additional forest cover would not injure but even increase runoff, especially dry season runoff. The study has important implications for sustainable water management and afforestation in this subtropical region and for similar river basins.

The strong sub-seasonal modulation in the atmospheric teleconnection between the North Atlantic and East Asia during boreal winter has been examined. Negative precipitation anomalies and corresponding transient eddy vorticity fluxes over the mid-latitude Atlantic induce a wave packet that leads to cold temperatures over northern China, Korea, and Japan. This relationship is significant for the anomalies averaged from mid-January to mid-February, while it is less for January or February. In mid-January segment, the transient vorticity forcing (TVF) over the mid- to high-latitude Atlantic is the strongest, and consequently, the atmospheric response strengthens the anticyclone over central Eurasia to facilitate strong development of the Siberian High as well as cold temperatures in East Asia. Model simulations support the sub-seasonal linkage modulation through amplitude change of the TVF. It is proposed that intensified atmospheric baroclinicity associated with the deepened North American trough is responsible for the pronounced TVF and downstream influences in mid-January.

Heat extremes have a serious impact on humans and on agriculture around the world. As one of the prominent climate change 'hot spots,' the Mediterranean area, especially the eastern portion, is expected to be more vulnerable to heat exposure than other regions due to its high population density and urbanization rate. The Paris Agreement includes the goal of 'holding the increase in the global average temperature to well below 2 °C above preindustrial levels and pursuing efforts to limit the temperature increase to 1.5 °C above preindustrial levels'. It is interesting to study how heat extremes would change in the Mediterranean area in a +1.5 °C and +2 °C global warming world and how they would impact humans and agriculture. Based on high resolution climate scenario data from Coordinated Regional Downscaling Experiment Mediterranean, we calculate several heat extreme indices to study heat extreme changes in the future. We found that in most Mediterranean areas, both daytime and nighttime heat wave intensity and frequency will have a robust increase in the 21st century compared with that of the historical period, with the most prominent areas located in northwest Africa, the Iberian Peninsula, Italy and Middle East. Meanwhile, nighttime heat waves should be garnering more attention because more moderate and extreme events happen in nighttime than in daytime. If the global warming level is limited to 2 °C or even 1.5 °C, the percentage of population exposed to dangerous events (especially one-in-20 year events) and yield loss from maize harvested areas may be much less in the future than the percentage affected during 3 °C warming period. Moreover, limiting global warming to 1.5 °C instead of 2 °C would result in an additional 20%–25% reduction of exposure.

From 2016 to 2019, the Indian Pradhan Mantri Ujjwala Yojana (PMUY) distributed over 80 million liquefied petroleum gas (LPG) stoves, making it the largest clean cooking program ever. Yet, evidence shows widespread continued use of the traditional chulha, negating the potential health benefits of LPG. Here we use semi-structured interviews with female and male adults to understand the drivers of LPG usage in Mulbagal, Karnataka, the site of a proto-PMUY program. We find that respondents perceive the main value of LPG to be saving time, rather than better health. We also find that norms of low female power in the household, in addition to costs, delay saving for and ordering LPG cylinder refills. Namely, female cooks controlled neither the money nor the mobile phone required to order a timely refill. These factors together contribute to the 'refill gap': the period of non-use between refilling cylinders, which may range from days to even months. Our work reveals how gender norms can amplify affordability challenges in low-income households.

Most studies of deep decarbonization find that a diverse portfolio of low-carbon energy technologies will be required, including carbon capture and storage (CCS) that mitigates emissions from fossil fuel power plants and industrial sources. While many projects essential to commercializing the technology have been proposed, most (>80%) end in failure. Here we analyze the full universe of CCS projects attempted in the U.S. that have sufficient documentation (N=39)—the largest sample ever studied systematically. We quantify 12 project attributes that the literature has identified as possible determinants of project outcome. In addition to costs and technological readiness, which prior research has emphasized, we develop metrics for attributes that are widely thought to be important yet have eluded systematic measurement, such as the credibility of project revenues and policy incentives, and the role of regulatory complexity and public opposition. We build three models—two statistical and one derived through the elicitation of expert judgment—to evaluate the relative influence of these 12 attributes in explaining project outcome. Across models, we find the credibility of revenues and incentives to be among the most important attributes, along with capital cost and technological readiness. We therefore develop and elicit experts' judgment of 14 types of policy incentives that could alter these attributes and improve the prospects for investment in CCS. Knowing which attributes have been most responsible for past successes and failures allows developers to avoid past mistakes and identify clusters of near-term CCS projects that are more likely to succeed.

Evaluating irrigation performance in large systems is often limited by the availability of reliable water use data. Satellite-driven actual evapotranspiration (ET_a) estimates are used herein as water use surrogates to assess the year-to-year inter-seasonal irrigation performance in 46 canal commands in the Indus Basin irrigated system (IBIS), the largest in the world (∼160 000 km²). The accuracy and reliability of the ET_a estimates are verified using two previously published locally adjusted satellite-driven ET_a estimates, as well as field ET_a estimates. Inter-seasonal variability (canal command water use in time) and equity (inter- and intra-canal command water use) are assessed from 2000 to 2018 using violin-plots time-series for the two irrigation seasons, the wet 'Kharif' and dry 'Rabi'. The violin-plots probability density functions are used to assess intra-canal command equity; and their seasonal time-series to assess inter-seasonal variability. The long-term multi-year assessment conducted here, the first for the IBIS using consistent satellite-driven ET_a time-series, shows that canal commands with ready access to groundwater exhibit more equity and less inter-seasonal variability when compared to canal commands chiefly reliant on surface water supplies; with the latter showing intra-canal command inequities between head-end and tail-end irrigated areas. Also, ET_a in canal commands is mostly slightly increasing and there is low inter-seasonal variability in both irrigation seasons, except for two canal command at the system-end, which show higher inter-seasonal variability and inequity than their upstream counterparts. The methods employed here can be used in large irrigated systems elsewhere to assess ongoing irrigation performance and to verify results of targeted (non)structural irrigation management.

Effectively conserving ecosystem services in order to maintain human wellbeing is a global need that requires an understanding of where ecosystem services are produced by ecosystems and where people benefit from these services. However, approaches to effectively identify key locations that have the capacity to supply ecosystem services and actually contribute to meeting human demand for those services are lacking at broad spatial scales. We developed new methods that integrate measures of the capacity of ecosystems to provide services with indicators of human demand and ability to access these services. We then identified important areas for three ecosystem services currently central to protected area management in Canada—carbon storage, freshwater, and nature-based recreation—and evaluated how these hotspots align with Canada's current protected areas and resource development tenures. We find that locations of ecosystem service capacity overlap only weakly (27–36%) with actual service providing areas (incorporating human access and demand). Overlapping hotspots of provision for multiple ecosystem services are also extremely limited across Canada; only 1.2% (∼56 000 km²) of the total ecosystem service hotspot area in Canada consists of overlap between all three ecosystem services. Canada's current protected area network also targets service capacity to a greater degree than provision. Finally, one-half to two-thirds of current ecosystem service hotspots (54–66%) overlap with current and planned resource extraction activities. Our analysis demonstrates how to identify areas where conservation and ecosystem service management actions should be focused to more effectively target ecosystem services to ensure that critical areas for ecosystem services that directly benefit people are conserved. Further development of these methods at national scales to assess ecosystem service capacity and demand and integrate this with conventional biodiversity and conservation planning information will help ensure that both biodiversity and ecosystem services are effectively safeguarded.

In recent years, UK summer heatwaves have resulted in thousands of excess deaths, with both extreme temperatures and high humidity increasing health risks. Here, the UK Climate Projections 2018 (UKCP18) are compared to observational (HadUK-Grid) and reanalysis data (ERA5) to quantify model performance at capturing mean, extremes (95th to 99.5th percentiles) and variability in the climate state and heat stress metrics (simplified wet bulb global temperature, sWBGT; Humidex; apparent temperature). Simulations carried out for UKCP18 generally perform as well as or better than CMIP5 models in reproducing observed spatial patterns of UK climate relating to extreme heat, with RMSE values on average ∼30% less than for the CMIP5 models. Increasing spatial resolution in UKCP18 simulations is shown to yield a minor improvement in model performance (RMSE values on average ∼5% less) compared to observations, however there is considerable variability between ensemble members within resolution classes. For both UKCP18 and CMIP5 models, model error in capturing characteristics of extreme heat generally reduces when using heat stress metrics with a larger vapour pressure component, such as sWBGT. Finally, the 95th percentile of observed UK summer temperature is shown to have ∼60% greater interannual variability than the summer mean over the recent past (1981–2000). This effect is underestimated in UKCP18 models (∼33%) compared to HadUK-grid and ERA5. Compared to projected future changes in the global mean temperature, UK summer mean and 95th percentile temperatures are shown in increase at a faster rate than the global mean.

Larch trees are widely used in afforestation and timber plantations. Yet, little is known on how planted larch trees cope with increasing drought. We used a tree-ring network of 818 trees from 31 plantations spanning most of the distribution of Larix principis-rupprechtii to investigate how extreme drought influences larch radial growth in northern China. We found that summer drought, rather than temperature or precipitation, had the strongest relationship with radial growth throughout the region. Drought increased in frequency in recent decades, leaving a strong imprint on the radial growth of larch, particularly in dry sites. Across its distribution, radial growth in larch trees that experienced extreme droughts more frequently displayed lower resistance to drought, but higher recovery after it, suggesting these populations were better adapted to extreme droughts. Radial growth decreased with increasing drought, with particularly severe declines below a threshold Palmer Drought Severity Index (PDSI) value of −3 to −3.5. Extreme droughts (PDSI < −4.5) caused a reduction of 62% of radial growth and chronic drought events caused around 20% reduction in total radial growth compared with mean growth on the driest sites. Given that current climate projections for northern China indicate a strong increase in the frequency and severity of extreme drought, trees in large portions of the largest afforestation project in the world, particularly those in the drier edge, are likely to experience severe growth reductions in the future.

Future temperature variations under greenhouse gas (GHG) emission scenarios are critical to assess possible impacts on human society and make reasonable mitigation policies. Due to the huge running cost, Earth system models (ESMs) may be difficult to flexibly provide the temperature projections following some specific emission pathways for empirical analysis. This study develops the mean and variability filed emulators in the high-resolution land grids to approximate the temperature behavior conditioned on GHG emissions in ESM. The emulator of mean temperature response is modeled as a function of GHG emissions to represent the expected values for ESM output, and the associated high-dimensional spatial dependence across grid points is estimated by the nearest-neighbor Gaussian process. The variability emulator is constructed with the residuals between the mean temperature response and the ESM output, and the associated space-time correlation structure is decomposed by principal component analysis and discrete Fourier transform. The analysis shows that the emulators trained with the runs of ESM only from part of representative concentration pathways can efficiently reproduce the temperature variations under different emission scenarios. The emulated gridded temperatures would be easily taken for climate impact and risk assessment, and be incorporated in the integrated assessment model for climate policy analysis.

We present a statistical method to quantify the contribution of urbanization to precipitation changes during 1958–2017 across the greater Beijing–Tianjin–Hebei metropolitan region in northern China. We find distinct trends in precipitation in the past six decades: decreasing in annual and summer while increasing in other seasons. The spatial patterns of precipitation show discernible terrain-induced characteristics with high values in the buffer zones of plain and mountain areas and low values in the northwestern mountainous regions. Our results indicate that although urbanization has limited impacts on the trends and spatial patterns of precipitation, it has a positive contribution to the changes in precipitation for about 80% of the comparisons conducted, especially in autumn (100%), with the negative contribution being dominant in summer (66.67%). In addition, these results are sensitive to the classifications of urban and rural stations, suggesting that how to classify urban/rural areas is a crucial step to estimate the potential contribution of urbanization to precipitation changes. These findings also support that urbanization can diversify and enhance the variations in precipitation, with urban areas becoming a secondary center along with more increasing or less decreasing trends in precipitation.

Rangelands are a key global resource, providing a broad range of ecological services and economic benefits. California's predominantly annual rangelands cover ∼12% of the state's land area, and the forage production is highly heterogeneous, making balancing economic (grazing), conservation (habitat) and environmental (erosion/water quality) objectives a big challenge. Herein, we examined how climate and environmental factors regulate annual grassland forage production spatially across the state and among four ecoregions using machine learning models. We estimated annual forage production at 30 m resolution over a 14 year period (2004–2017) using satellite images and data fusion techniques. Our satellite-based estimation agreed well with independent field measurements, with a R² of 0.83 and RMSE of 682 kg ha⁻¹. Forage production (14 year average) showed large spatial variability (2940 ± 934 kg ha^-1 yr^-1; CV = 35%) across the study area. The gradient boosted regression tree with 11 feature variables explained 67% of the variability in forage production across the state. Precipitation amount, especially in November (germination) and April (rapid growth), was found as the dominant driver for spatial variation in forage production, especially in drier ecoregions and during drier years. Seasonal distribution of precipitation and minimum air temperature showed a relatively stronger control on forage production in wetter regions and during wet years. Additionally, solar energy became more important in wetter ecoregions. Drought reduced forage production from the long-term mean, i.e. a 33% ± 19% decrease in production (2397 ± 926 kg ha^-1yr^-1; CV = 38%) resulting from a 29% ± 5% decrease in precipitation. The machine learning based spatial analysis using 'big data' provided insights on impacts of climate and environmental factors on forage production variation at various scales. This study demonstrates a cost-effective approach for rapid mapping and assessment of annual forage production with the potential for near real-time application.

Land-use and -cover change (LUCC) is globally important to climate change mitigation. However, using land-based strategies to support aggressive subnational greenhouse gas emissions reduction targets is challenging due to competing land use priorities and uncertainty in ecosystem carbon dynamics and climate change effects. We used the California natural and working lands carbon and greenhouse gas model to quantify the direct ecosystem carbon emissions (CO₂ and CH₄) impacts, trade-offs, and climate change interactions of two policy scenarios identified by the State of California for fulfilling multiple land use goals, including the competing goals of mitigating wildfire severity and landscape carbon emissions, among others. Here we show that emissions from desired forest management to reduce the amount of combustible biomass (fuel reduction) initially outweighed emissions reductions from other strategies (e.g. less intensive forest management, restoration, land conservation); however, avoided emissions and enhanced carbon sequestration from the other strategies gradually outweighed fuel reduction emissions. Thus, in jurisdictions with large-scale wildfire mitigation goals, practices that reduce emissions and/or increase carbon sequestration can simultaneously offset fuel reduction emissions. Our analysis highlights the complexities inherent in LUCC planning, underscoring the need for governments to begin the task now.

This study explores the potential of atmospheric moisture content, its transport and its divergence over the ocean and land as proxies for the variability of Indian summer monsoon rainfall (ISMR) for the period 1950–2019. The analyses using multiple linear regression reveal that the interannual and intraseasonal variability of ISMR and the mean ISMR is largely controlled by Arabian Sea moisture flux and Ganga river basin moisture content, and these parameters exhibit statistically significant high correlations in most regions. The regression model and the parameters are statistically significant and the model could explain rainfall variability of about 12%–50% in various regions. The model shows a false alarm rate (FAR) of 0.25–0.45 and a probability of detection (POD) of 0.43–0.50 for wet years in West Central, North West and North Central India. The FAR and POD are about 0.06–0.32 and 0.60–0.70, respectively for dry years in those regions. The model reproduces flood and drought years of about 32%–50% and 55%–70% in those regions. Also, the moisture indices could clearly identify the majority of wet and dry years that occurred during the period. The ISMR variability associated with moisture indices is unaffected by El Niño Southern Oscillation. Henceforth, this study demonstrates the significance of atmospheric moisture on regional rainfall distribution and suggests that these parameters can be used in both statistical and dynamical models to better predict monsoon and global precipitation.

Increasing meteorological drought frequency and rising water demand drive groundwater exploitation beyond sustainable limits. In heavily-stressed aquifers mitigation strategies, such as Managed Aquifer Recharge (MAR), are needed to restore depleted groundwater storage. MAR is also designed to overcome short dry periods. However, wider impacts of MAR as a drought mitigation strategy remain to be quantified. The objective of this study is to assess impacts of MAR in heavily-stressed aquifers using a case study of the Central Valley in California (USA). The novelty of this study lies in its analytical approach based on long-term observational data of precipitation, groundwater levels, and MAR operations. The impact of MAR operations is assessed regionally and for different temporal scales. Results show spatially-coherent clusters of groundwater level time series in the Central Valley representing three main patterns that manifest themselves in different groundwater drought characteristics and long-term trends. The first regional pattern shows lengthened groundwater droughts and declining groundwater levels over time, indicating effects of over abstraction in aquifer sections without MAR. The second regional pattern shows reduced groundwater drought duration and magnitude related to periodically rising groundwater levels, showing short-term MAR impacts. The third regional pattern shows alleviated groundwater droughts and groundwater levels show a long-term rise, representing long-term MAR impacts. Mitigated groundwater droughts and long-term rise in groundwater levels reveal the value of long-term MAR operations and their contribution toward sustainable groundwater management. Increased institutional support is recommended to ensure longevity of MAR and thereby amplify its success as regional drought mitigation strategy in heavily-stressed aquifers.

The dipole pattern of summer precipitation over the Tibetan Plateau (TP) during 1961–2014 is evaluated based on observations and 18 models provided by the Coupled Model Intercomparison Project Phase 6. Of the 18 models, 10 can capture the opposite variation characteristics in the south and north TP. Observational data reveals that the south–north seasaw of TP summer precipitation is essentially driven by a Rossby wave propagating from the Western Europe to East Asia, which is associated with North Atlantic oscillation (NAO). The models successfully simulated the dipole pattern that is closely related to the reproduction of the NAO–TP relationship. Further analysis demonstrates that the reliable simulations of horizontal dynamic processes of moisture transport, which is linked to the NAO–TP relationship, highly contributes to their success in reproducing the dipolar pattern of TP summer precipitation. While unrealistic local vertical circulation and evaporation simulation lead to the failed reproductions. These findings provide significant information for model development and future climate change projections.

For decades, meteorologists and governments have been warning communities in coastal areas for an imminent tropical cyclone (TC) using the Saffir-Simpson Hurricane Wind Scale (SSHWS). The SSHWS categorizes a TC based on its maximum wind speed, and is used in defining evacuation strategies and humanitarian response. However, the SSHWS considers only the wind hazard of a TC, whereas a TC can also cause severe conditions through its high storm surges and extreme rainfall, triggering coastal and inland flooding. Consequently, the SSHWS fails to mirror the TC's total severity. This becomes evident when looking at past events such as Hurricane Harvey (2017), which was classified as a Tropical Storm while it caused widespread flooding in the Houston (TX) area, with precipitation totals exceeding 1.5 m. Without including storm surge and rainfall information, adequate risk communication with the SSHWS can be challenging, as the public can (mistakenly) perceive a low-category TC as a low-risk TC. To overcome this, we propose the new Tropical Cyclone Severity Scale (TCSS) that includes all three major TC hazards in its classification. The new scale preserves the categorization as used in the SSHWS, to maintain familiarity amongst the general public. In addition, we extend the scale with a Category 6, to support communication about the most extreme TCs with multiple hazards. The TCSS is designed to be applied on a local-scale, hereby supporting local-scale risk communication efforts and evacuation strategies prior to a TC landfall. The scale can be used for risk communication on both the total TC risk and on the categories of the separate hazards, which can be valuable especially in cases when one hazard is the predominant risk factor, such as excess rainfall triggering flooding.

Enhanced riverine delivery of terrestrial nitrogen (N) has polluted many freshwater and coastal ecosystems, degrading drinking water and marine resources. An emerging view suggests a contribution of land N memory effects—impacts of antecedent dry conditions on land N accumulation that disproportionately increase subsequent river N loads. To date, however, such effects have only been explored for several relatively small rivers covering a few episodes. Here we introduce an index for quantifying land N memory effects and assess their prevalence using regional observations and global terrestrial-freshwater ecosystem model outputs. Model analyses imply that land N memory effects are globally prevalent but vary widely in strength. Strong effects reflect large soil dissolved inorganic N (DIN) surpluses by the end of dry years. During the subsequent wetter years, the surpluses are augmented by soil net mineralization pulses, which outpace plant uptake and soil denitrification, resulting in disproportionately increased soil leaching and eventual river loads. These mechanisms are most prominent in areas with high hydroclimate variability, warm climates, and ecosystem disturbances. In 48 of the 118 basins analyzed, strong memory effects produce 43% (21%–88%) higher DIN loads following drought years than following average years. Such a marked influence supports close consideration of prevalent land N memory effects in water-pollution management efforts.

The Mongolian Plateau (MP) experienced the most severe decadal drought of the past two millennia from 2000 to 2009 and several shorter-term droughts in the 2010s. Using satellite-based near-infrared reflectance of vegetation (${\text{NI}}{{\text{R}}_{\text{V}}}$), we examined changes in vegetation productivity of the MP from 2000 to 2018. During this time, soil moisture in March (${\text{S}}{{\text{M}}^{{\text{Mar}}}}$) mainly determined spring ${\text{NI}}{{\text{R}}_{\text{V}}}$, and early-summer (June and July) precipitation mainly determined summer ${\text{NI}}{{\text{R}}_{\text{V}}}{\text{.}}$ Our study revealed three distinct periods: the severely dry period of 2000–2009, recovery in 2010–2012, and a relatively stable period with occasional short-term droughts after 2012. While vegetation productivity experienced a significant decrease during the severe decadal drought, summer and spring productivity quickly recovered after 2010, following an increase in growing season (GS) rainfall and winter snowfall. Greater ${\text{S}}{{\text{M}}^{{\text{Mar}}}}$, which resulted from previous GS precipitation, contributed to smaller declines in vegetation productivity during the short-term droughts in 2014, 2015 and 2017. The decline in vegetation productivity during the severe decadal drought damaged livestock operations in Mongolia, but had a limited effect on operations in Inner Mongolia of China, where human intervention is stronger. Given evidence that drought impacts are increasing worldwide, it is important to understand the factors determining ecosystem drought responses. Many drought studies have focused on GS precipitation, but our results show that pre-GS SM can play an important role in determining drought impacts. Our results also demonstrate that strong interventions will be needed in order to sustain livestock operations during intensifying drought.

This study provides a comprehensive assessment of the environmental and economic impacts of climate change on global and regional forests from now through 2200. By integrating the representative concentration pathway (RCP) 2.6 and RCP 8.5 emission scenarios with climate models, a vegetation model, socio-economic scenarios, and a forest economic model, the study explores long run adjustments of both ecosystems and markets to climate change that have not been studied before. The ecological model suggests that global forest productivity increases under RCP 8.5. The overall supply of timber expands faster than demand through the 23rd century lowering timber prices and creating net benefits in the timber sector. Consumers benefit the most from the lower prices but these same low prices tend to damage forest owners, especially in the tropics. Even without a formal sequestration policy, average global forest carbon is projected to increase by 6%–8% by 2100. Under the RCP 2.6, forest carbon remains stable through 2200 but under RCP 8.5 it is simulated to increase by another 8% with a very heterogeneous distribution across world regions. Under both RCPs, global forest area is projected to increase relative to a no-climate change case until 2150, but possibly decline thereafter.

Anthropogenic warming may impact mean and extreme precipitation trends by enhancing the water cycle, potentially bringing threats to human societies. The design of national-level policy for disaster prevention and mitigation depends on the reliable detection of anthropogenic forcing in mean and extreme precipitation changes there. The anthropogenic signal might be obscured by strong internal variability at a regional scale. The goal of this study is to investigate the emergence of anthropogenic signal in mean and extreme precipitation trends across China by using two large ensembles (CanESM2-LE and Community Earth System Model (CESM)-LE) of simulations during 1961–2010. Results show that the signal could not be detected in either mean or extreme precipitation trend during the current climate period (1961–2010). Following the RCP8.5 scenario, the signal is projected to emerge in mean precipitation around the 2020s and 2030s in the CanESM2-LE and CESM-LE, respectively, much earlier than in extreme precipitation. For extreme precipitation, the signal could be steadily detected no earlier than the 2030s for CanESM2-LE and the 2040s for CESM-LE. These projected times of emergence in precipitation changes highlight the urgency of preparing for an uncharted hydrological future dominated by anthropogenic warming.

Soils are warming as air temperatures rise across the Arctic and Boreal region concurrent with the expansion of tall-statured shrubs and trees in the tundra. Changes in vegetation structure and function are expected to alter soil thermal regimes, thereby modifying climate feedbacks related to permafrost thaw and carbon cycling. However, current understanding of vegetation impacts on soil temperature is limited to local or regional scales and lacks the generality necessary to predict soil warming and permafrost stability on a pan-Arctic scale. Here we synthesize shallow soil and air temperature observations with broad spatial and temporal coverage collected across 106 sites representing nine different vegetation types in the permafrost region. We showed ecosystems with tall-statured shrubs and trees (>40 cm) have warmer shallow soils than those with short-statured tundra vegetation when normalized to a constant air temperature. In tree and tall shrub vegetation types, cooler temperatures in the warm season do not lead to cooler mean annual soil temperature indicating that ground thermal regimes in the cold-season rather than the warm-season are most critical for predicting soil warming in ecosystems underlain by permafrost. Our results suggest that the expansion of tall shrubs and trees into tundra regions can amplify shallow soil warming, and could increase the potential for increased seasonal thaw depth and increase soil carbon cycling rates and lead to increased carbon dioxide loss and further permafrost thaw.

By some counts, up to 98% of environmental news stories are negative in nature. Implicit in this number is the conventional wisdom among many communicators that increasing people's understanding, awareness, concern or even fear of climate change are necessary precursors for action and behavior change. In this article we review scientific theories of mind and brain that explain why this conventional view is flawed. In real life, the relationship between beliefs and behavior often goes in the opposite direction: our actions change our beliefs, awareness and concerns through a process of self-justification and self-persuasion. As one action leads to another, this process of self-persuasion can go hand in hand with a deepening engagement and the development of agency—knowing how to act. One important source of agency is learning from the actions of others. We therefore propose an approach to climate communication and storytelling that builds people's agency for climate action by providing a wide variety of stories of people taking positive action on climate change. Applied at scale, this will shift the conceptualization of climate change from 'issue-based' to 'action-based'. It will also expand the current dominant meanings of 'climate action' (i.e. 'consumer action' and 'activism') to incorporate all relevant practices people engage in as members of a community, as professionals and as citizens. We close by proposing a systematic approach to get more reference material for action-based stories from science, technology and society to the communities of storytellers—learning from health communication and technologies developed for COVID-19.

Phosphorus (P) leaching from agriculture is a major driver of water eutrophication in downstream rivers and lakes. In drained lowland areas with intensive agriculture, a reduction in the fertilizer applications may be insufficient to improve the water quality in the short term as the P accumulated in the soil during decades of high fertilization may continue leaching for many years. A complementary approach to reduce P exports from agriculture is to implement edge-of-field mitigation measures at the farm scale. The selection of effective measures requires a detailed insight into the chemical and hydrological transport mechanisms. Here, we determined the main P sources, processes, and transport routes at the farm scale to support the selection of appropriate mitigation measures. We quantified the legacy P, the different P pools stored in the upper soil, and related it to the yearly P export downstream. To do this, we combined high-resolution monitoring data from the soil, groundwater, surface water, and ditch sediments. The legacy P in the topsoil was high, about 2500 kg ha⁻¹. The predominant subsurface flow and the subsoils' P sorption capacity retained the P mobilized from the topsoil and explained the relative moderate flux of P to surface waters (0.04 kg ha⁻¹ during the 2018–2019 drainage season). The dissolved P entering the drainage ditch via groundwater discharge was bound to iron-containing particles formed due to the oxidation of dissolved ferrous iron. Once leached from the soil to the drainage ditch, resuspension of P-rich sediment particles during flow peaks were the most important P transport mechanism (78%). Therefore, we expect that hydraulic constructions that reduce flow velocities and promote sedimentation of P-containing particles could reduce the export of P further downstream.

We present a long term assessment trend of atmospheric inorganic nitrogen deposition in Sub Saharan Africa (2000–2015) using observational and model data. This work proposes a compilation of International Network to study Deposition and Atmospheric chemistry in Africa wet and dry nitrogen deposition fluxes collected at the wet savanna site of Lamto (Côte d'Ivoire). Total deposition calculation takes in account: (a) gaseous (NO₂, NH₃, HNO₃) dry deposition fluxes estimated by considering nitrogen compound concentrations at the monthly scale and modeling average monthly dry deposition velocities, (b) particulate PM10 (pNO₃⁻, pNH₄⁺) dry deposition fluxes calculated using the same inferential method and (c) wet deposition (WD) fluxes including ions concentration measurements (NO₃⁻, NH₄⁺) in rainwater combined with rainfall amount. We demonstrate for the first time the monthly and annual decreasing trends for dry nitrogen deposition of N-NO₂ (−2.33% month⁻¹ and −2.54% yr⁻¹) and N-NH₃ (−2.55% month⁻¹ and −2.89% yr⁻¹), but increasing trends for dry deposition of N-HNO₃ (+1.00% month⁻¹) and WD of N-NO₃⁻ (+1.67% month⁻¹ and +2.13% yr⁻¹) and N-NH₄⁺ (+2.33% month⁻¹ and +3.36% yr⁻¹). Dry season N-NO₂ deposition flux decline shows agreement with long term trend in NOx emissions by biomass burning. Increasing trends for wet N deposition signals a gradual increase of nitrogen fertilizers use in agricultural practices in the Lamto area. Results also show no significant trend in total N deposition over the 16 year study period explained by the compensation of decreasing and increasing trends for dry and wet N deposition, respectively. However, at the annual scale, the mean total N deposition flux is estimated to 10.3 ± 1.2 kgN ha⁻¹ yr⁻¹ over the 16 year period, indicating an increase of 8% compared to the period 2000–2007.

Lifestyle changes are key factors of the climate mitigation challenge because they drive the demand for energy, goods and food. They have received growing attention in the development and assessment of mitigation pathways, one of the key approaches used to inform mitigation policies. This paper contributes to this emerging literature by examining the political and scientific implications of integrating lifestyle changes into mitigation pathways. We analyse a large sample of pathways, supplemented by interviews with practitioners, to provide a perspective relevant to both scenario production practices themselves and the science-policy process in which they are included. We use three illustrative pathways to describe what it means to explore lifestyle changes and how this exploration can be conducted (indicators, dimensions, precision). We summarize the observed benefits of the explorations of lifestyle changes in scenario production by considering three main contributions of scenarios to policy decision-making: explicit knowledge, mediation tools and framing power. We also discuss why the integration of lifestyle changes poses a potential challenge to the robustness and reliability of pathway production methodologies, which is a condition for their policy-relevance. We therefore argue that the implications of this integration need to be carefully characterized in order to maximize the policy relevance of the analysis without compromising the robustness of the scenario development and assessment process. The nature of lifestyles, which reflect values and preferences and require a multidisciplinary approach, raises significant policy neutrality challenges and scientific challenges. Overcoming these challenges can lead to more policy-relevant pathways: we describe existing approaches in the literature and analyse their contributions and limitations.

In 2018, the Beijing–Tianjin–Hebei (BTH) area launched the Blue Sky Protection Campaign (BSPC) to control atmospheric pollution. CO₂ emissions could be significantly reduced due to the co-effects of implementing the BSPC. This paper employs the Greenhouse Gas and Air Pollution Interactions and Synergies Asia model to quantitatively evaluate the CO₂ reductions when implementing the BSPC in the BTH region. The results indicate that CO₂ emissions can be reduced by 20.7 Mt (equivalently, a 19.7% reduction in the corresponding baseline scenario), 6.8 Mt (3.8%), and 80.2 Mt (9.2%) by 2020 for Beijing, Tianjin, and Hebei, respectively, as a co-benefit of the BSPC. By 2030, it is estimated that the CO₂ emission reductions will be 37.8 Mt (26.6%), 4.85 Mt (2.5%), and 69.9 Mt (8.6%) for Beijing, Tianjin, and Hebei, respectively. NO_x presents the highest co-effects with CO₂ in each region. From the key sector perspective, sectors of power and heating in Beijing, residential combustion in Tianjin, and industrial combustion in Hebei are the most important sector that presents the highest co-effects on CO₂ emission reductions due to the application of BSPC. We suggest that the implementation of BSPC, specifically the energy control measures in the power and heating, residential combustion, and industrial combustion sectors for Beijing, Tianjin, and Hebei, respectively, have high synergies and can simultaneously reduce CO₂ and other atmospheric emissions. The results contribute to city-level policymaking on facilitating air pollution control and climate change mitigation among different governmental departments.

Few environmental issues have resulted in such a heated policy-science controversy in Sweden as the 1990s acidification debate in the north of the country. The belief that exceptionally high stream acidity levels during hydrological events was caused by anthropogenic deposition resulted in a governmentally funded, multi-million dollar surface-water liming program. This program was heavily criticized by a large part of the scientific community arguing that the acidity of northern streams was primarily caused by naturally occurring organic acids. Here, we revisit the acid deposition legacy in northern Sweden two decades after the culmination of the controversy by examining the long-term water chemistry trends in the Svartberget/Krycklan research catchment that became a nexus for the Swedish debate. In this reference stream, trends in acidic episodes do show a modest recovery that matches declines in acid deposition to pre-industrial levels, although stream acidity continues to be overwhelmingly driven by organic acidity. Yet there are legacies of acid deposition related to calcium losses from soils, which are more pronounced than anticipated. Finally, assessment of these trends are becoming increasingly complicated by new changes and threats to water resources that must be recognized to avoid unnecessary, expensive, and potentially counterproductive measures to adapt and mitigate human influences. Here we make the argument that while the acidification era is ending, climate change, land-use transitions, and long-range transport of other contaminants warrant close monitoring in the decades to come.

Obtaining a better understanding of groundwater dynamics in permafrost zones is a critical issue in permafrost hydrology. This includes assessing the impacts of climate change on permafrost thaw and ground ice-melt. Both permafrost thaw and ground ice-melt can be related to groundwater discharges (i.e. spring discharges), and spring water is an important local water resource; accordingly, changes in these processes can have large impacts on local people and their subsistence activities. To detect permafrost thaw and ground ice-melt in the permafrost zone of Mongolia, groundwater ages of several spring discharges were determined using two transient tracers: tritium (³H) and chlorofluorocarbons (CFCs). Spring water samples were collected seasonally from 2015 to 2019 at seven spring sites around the Khangai Mountains in central Mongolia. The sites included two thermokarst landscapes on the northern and southern sides of the mountains. The ³H and CFC concentrations in the spring water in the thermokarst landscapes were very low, especially on the southern side of the mountains, and the estimated mean groundwater age for these sites was older than that for the other sampled springs. Consequently, the young water ratios of the thermokarst sites were lower than those for the other springs. This ratio, however, showed a gradual increase with time, which indicates that recently recharged rainwater began to contribute to the spring discharge at the thermokarst sites. An atmospheric water budget analysis indicated that net recharge from modern and recent precipitation to shallow groundwater in the summer season was almost zero on the southern side of the mountains. Thus, we inferred that the spring water at the thermokarst sites on the southern side of the mountains contained large amounts of ground ice-melt water.

Cold spells have been associated with mortality from a few broad categories of diseases or specific diseases. However, there is a lack of data about the health effects of cold spells on mortality from a wide spectrum of plausible diseases which can reveal a more comprehensive contour of the mortality burden of cold spells. We collected daily mortality data in Guangzhou during 2010–2018 from the Guangzhou Center for Disease Control and Prevention. The quasi-Poisson generalized linear regression model mixed with the distributed lag non-linear model (DLNM) was conducted to examine the health impacts of cold spells for 11 broad causes of death groupings and from 35 subcategories in Guangzhou. Then, we examined the effect modification by age group (0–64 and 65+ years) and sex. Effects of cold spells on mortality generally delayed for 3–5 d and persisted up to 27 d. Cold spells were significantly responsible for increased mortality risk for most categories of deaths, with cumulative relative risk (RR) over 0–27 lagged days of 1.57 [95% confidence interval (CI): 1.48–1.67], 1.95 (1.49–2.55), 1.58 (1.39–1.79), 1.54 (1.26–1.88), 1.92 (1.15–3.22), 1.75, (1.14–2.68), 2.02 (0.78–5.22), 1.92 (1.49–2.48), 1.48 (1.18–1.85), and 1.18 (1.06–1.30) for non-accidental causes, cardiovascular diseases, respiratory diseases, digestive diseases, nervous system diseases, genitourinary diseases, mental diseases, endocrine diseases, external cause and neoplasms, respectively. The magnitudes of the effects of cold spells on mortality varied remarkably among the 35 subcategories, with the largest cumulative RR of 2.87 (1.72–4.79) estimated for pulmonary heart diseases. The elderly and females were at a higher risk of mortality for most diseases after being exposed to cold spells. Increased mortality from a wide range of diseases was significantly linked with cold spells. Our findings may have important implications for formulating effective preventive strategies and early warning response plans that mitigate the health burden of cold spells.

It is widely anticipated that climate change will negatively affect both food security and diet diversity. Diet diversity is especially critical for children as it correlates with macro and micronutrient intake important for child development. Despite these anticipated links, little empirical evidence has demonstrated a relationship between diet diversity and climate change, especially across large datasets spanning multiple global regions and with more recent climate data. Here we use survey data from 19 countries and more than 107 000 children, coupled with 30 years of precipitation and temperature data, to explore the relationship of climate to child diet diversity while controlling for other agroecological, geographic, and socioeconomic factors. We find that higher long-term temperatures are associated with decreases in overall child diet diversity, while higher rainfall in the previous year, compared to the long-term average rainfall, is associated with greater diet diversity. Examining six regions (Asia, Central America, North Africa, South America, Southeast Africa, and West Africa) individually, we find that five have significant reductions in diet diversity associated with higher temperatures while three have significant increases in diet diversity associated with higher precipitation. In West Africa, increasing rainfall appears to counterbalance the effect of rising temperature impacts on diet diversity. In some regions, the statistical effect of climate on diet diversity is comparable to, or greater than, other common development efforts including those focused on education, improved water and toilets, and poverty reduction. These results suggest that warming temperatures and increasing rainfall variability could have profound short- and long-term impacts on child diet diversity, potentially undermining widespread development interventions aimed at improving food security.