The Nile River is a unique environmental system and essential water resource for its basin riparian nations. Population growth, changes in precipitation patterns, damming and usage rights disputes present extreme challenges in utilizing and managing the basin’s primary water resource. These stress factors are of particular concern for highly populated Egypt, the furthest downstream recipient of the Nile’s water flow. Previously, colonial agreements had granted Egypt and Sudan the majority of water use rights on the Nile without neighboring Ethiopia receiving any specific allocation. Today, Ethiopia plans to increase its energy production through its Nile-powered Grand Ethiopian Renaissance Dam (GERD). While the 74-billion cubic meter (BCM) dam presents promising development opportunities for Ethiopia, the Nile’s altered flow will increase the existing water deficit for Egypt—the quantification and mitigation of which are still largely unconstrained and under intense debate. To address this deficiency, we estimate that the median total annual water budget deficit for Egypt during the filling period, considering seepage into the fractured rocks below and around the GERD reservoir, as well as the intrinsic water deficit and assuming no possible mitigation efforts by Egyptian authorities, will be ∼31 BCM yr ⁻¹, which would surpass one third of Egypt’s current total water budget. Additionally, we provide a feasibility index for the different proposed solutions to mitigate the above deficit and assess their economic impact on the GDP per capita. Our results suggest that the unmet annual deficit during the filling period can be partially addressed by adjusting the Aswan High Dam (AHD) operation, expanding groundwater extraction and by adopting new policies for cultivation of crops. If no prompt mitigation is performed, the short-term three-year filling scenario would generate a deficit that is equivalent to losses to the present cultivated area by up to 72% resulting in a total loss of the agricultural GDP by $51 billion during the above-mentioned filling period. Such figures are equivalent to a decrease in the total national GDP per capita by ∼8%, augmenting existing unemployment rates by 11%, potentially leading to severe socioeconomic instability.

Current anthropogenic climate change is the result of greenhouse gas accumulation in the atmosphere, which records the aggregation of billions of individual decisions. Here we consider a broad range of individual lifestyle choices and calculate their potential to reduce greenhouse gas emissions in developed countries, based on 148 scenarios from 39 sources. We recommend four widely applicable high-impact (i.e. low emissions) actions with the potential to contribute to systemic change and substantially reduce annual personal emissions: having one fewer child (an average for developed countries of 58.6 tonnes CO ₂-equivalent (tCO ₂e) emission reductions per year), living car-free (2.4 tCO ₂e saved per year), avoiding airplane travel (1.6 tCO ₂e saved per roundtrip transatlantic flight) and eating a plant-based diet (0.8 tCO ₂e saved per year). These actions have much greater potential to reduce emissions than commonly promoted strategies like comprehensive recycling (four times less effective than a plant-based diet) or changing household lightbulbs (eight times less). Though adolescents poised to establish lifelong patterns are an important target group for promoting high-impact actions, we find that ten high school science textbooks from Canada largely fail to mention these actions (they account for 4% of their recommended actions), instead focusing on incremental changes with much smaller potential emissions reductions. Government resources on climate change from the EU, USA, Canada, and Australia also focus recommendations on lower-impact actions. We conclude that there are opportunities to improve existing educational and communication structures to promote the most effective emission-reduction strategies and close this mitigation gap.

A key statistic describing climate change impacts is the ‘social cost of carbon dioxide’ (SCCO ₂), the projected cost to society of releasing an additional tonne of CO ₂. Cost-benefit integrated assessment models that estimate the SCCO ₂ lack robust representations of climate feedbacks, economy feedbacks, and climate extremes. We compare the PAGE-ICE model with the decade older PAGE09 and find that PAGE-ICE yields SCCO ₂ values about two times higher, because of its climate and economic updates. Climate feedbacks only account for a relatively minor increase compared to other updates. Extending PAGE-ICE with economy feedbacks demonstrates a manifold increase in the SCCO ₂ resulting from an empirically derived estimate of partially persistent economic damages. Both the economy feedbacks and other increases since PAGE09 are almost entirely due to higher damages in the Global South. Including an estimate of interannual temperature variability increases the width of the SCCO ₂ distribution, with particularly strong effects in the tails and a slight increase in the mean SCCO ₂. Our results highlight the large impacts of climate change if future adaptation does not exceed historical trends. Robust quantification of climate-economy feedbacks and climate extremes are demonstrated to be essential for estimating the SCCO ₂ and its uncertainty.

Combusting fossil fuels to produce electricity is the single largest contributor to sector-level, anthropogenic carbon pollution. Because sector-wide policies are often too unwieldy to implement, however, some researchers have recommended reducing electricity-based CO ₂ emissions by targeting the most extreme emitters of each nation’s electricity industry. Here, we use a unique international data source to measure national disproportionalities in power plant CO ₂ emissions and estimate the fraction of each country’s electricity-based CO ₂ emissions that would be reduced if its most profligate polluters lowered their emission intensities, switched to gas fuels, and incorporated carbon capture and storage systems. We find that countries’ disproportionalities vary greatly and have mostly grown over time. We also find that 17%–49% of the world’s CO ₂ emissions from electricity generation could be eliminated depending on the intensity standards, fuels, or carbon capture technologies adopted by hyper-emitting plants. This suggests that policies aimed at improving the environmental performance of ‘super polluters’ are effective strategies for transitioning to decarbonized energy systems.

Through this research, we systematically updated and expanded understanding of how the print media represent evidence of human contributions to climate change. We built on previous research that examined how the journalistic norm of balanced reporting contributed to informationally biased print media coverage in the United States (U.S.) context. We conducted a content analysis of coverage across 4856 newspaper articles over 15 years (2005–2019) and expanded previous research beyond U.S. borders by analyzing 17 sources in five countries: the United Kingdom (U.K.), Australia, New Zealand, Canada, and the U.S. We found that across all the years of analysis, 90% of the sample accurately represented climate change. In addition, our data suggests that scientifically accurate coverage of climate change is improving over time. We also found that media coverage was significantly less accurate in 2010 and significantly more accurate in 2015, in comparison to the sample average. Additionally, Canada’s National Post, Australia’s Daily Telegraph and Sunday Telegraph, and the U.K.’s Daily Mail and Mail on Sunday (all historically conservative outlets) had significantly less accurate coverage of climate change over this time period than their counterparts.

The consensus that humans are causing recent global warming is shared by 90%–100% of publishing climate scientists according to six independent studies by co-authors of this paper. Those results are consistent with the 97% consensus reported by Cook et al ( Environ. Res. Lett. 8 024024) based on 11 944 abstracts of research papers, of which 4014 took a position on the cause of recent global warming. A survey of authors of those papers ( N = 2412 papers) also supported a 97% consensus. Tol (2016 Environ. Res. Lett. 11 048001) comes to a different conclusion using results from surveys of non-experts such as economic geologists and a self-selected group of those who reject the consensus. We demonstrate that this outcome is not unexpected because the level of consensus correlates with expertise in climate science. At one point, Tol also reduces the apparent consensus by assuming that abstracts that do not explicitly state the cause of global warming (‘no position’) represent non-endorsement, an approach that if applied elsewhere would reject consensus on well-established theories such as plate tectonics. We examine the available studies and conclude that the finding of 97% consensus in published climate research is robust and consistent with other surveys of climate scientists and peer-reviewed studies.

We analyze the evolution of the scientific consensus on anthropogenic global warming (AGW) in the peer-reviewed scientific literature, examining 11 944 climate abstracts from 1991–2011 matching the topics ‘global climate change’ or ‘global warming’. We find that 66.4% of abstracts expressed no position on AGW, 32.6% endorsed AGW, 0.7% rejected AGW and 0.3% were uncertain about the cause of global warming. Among abstracts expressing a position on AGW, 97.1% endorsed the consensus position that humans are causing global warming. In a second phase of this study, we invited authors to rate their own papers. Compared to abstract ratings, a smaller percentage of self-rated papers expressed no position on AGW (35.5%). Among self-rated papers expressing a position on AGW, 97.2% endorsed the consensus. For both abstract ratings and authors’ self-ratings, the percentage of endorsements among papers expressing a position on AGW marginally increased over time. Our analysis indicates that the number of papers rejecting the consensus on AGW is a vanishingly small proportion of the published research.

Africa, a continent exceptionally rich in biodiversity, is rapidly urbanizing. Africa’s urbanization is manifest in the growth of its megacities as well as that of its smaller towns and cities. The conservation planning and practice will increasingly need to account for direct and indirect impacts of the continent’s urbanization. The objective of our study is to pinpoint the outstanding challenges and opportunities afforded by the growing cities on the continent to the conservation goals and practices. While there have been many studies on the impacts of urbanization and development on conservation in Africa these studies tended to focus on specific issues. Here, we provide a synthesis of this body of work supported by new analysis. Urban areas, growing both in population and in land cover, pose threats to the integrity of the continent’s ecosystems and biodiversity but their growth also create opportunities for conservation. The burgeoning urban populations, especially in Sub-Saharan Africa, increase the strain on already insufficient infrastructure and bring new governance challenges. Yet, Africa’s ecosystems can serve as foundations for green infrastructure to serve the needs of its urban populations while safeguarding fragile biodiversity. Overall, while worsening social problems overshadow the concerns for biodiversity there are also promising initiatives to bring these concerns into the fold to address social, institutional, and ecological challenges that emerge with the continued urbanization of the continent.

In recent years, there has been growing interest in defining what exactly constitutes “decent living standards” (DLS)—the material underpinnings of human well-being. We assess the gaps in providing decent health, shelter, nutrition, socialization, and mobility within countries, across the world. Our results show that more people are deprived of DLS than are income-poor, even when numbers are measured against medium income poverty thresholds. We estimate the cumulative energy needs for building out new infrastructure to support DLS provision for all by 2040 to be about 290 EJ, which amounts to less than three-quarters of current annual global energy demand, at the final energy level. The annual energy requirements to support decent living for the global population after 2040 is estimated to be 156 EJ yr ⁻¹. Present average energy demand levels in most countries exceed hypothetical DLS energy needs. Nevertheless, the required rate of increase in energy to provide decent living for all in the coming two decades would be unprecedented for many countries. Greater attention to equity would significantly reduce the need for growth. The per capita energy requirement of different countries to meet the same DLS levels varies by up to a factor of four due to differences in climate, urbanization, diets, and transport infrastructure. Transport energy dominates energy for decent living worldwide, while housing requirements dominate upfront energy investment needs. This study supports the claim that the increase in energy provision poverty eradication does not, in itself, pose a threat to mitigating climate change at a global scale. Distinguishing energy for affluence from energy for decent living could provide a basis for defining equitable access to sustainable development in energy terms.

Methane mitigation is essential for addressing climate change, but the value of rapidly implementing available mitigation measures is not well understood. In this paper, we analyze the climate benefits of fast action to reduce methane emissions as compared to slower and delayed mitigation timelines. We find that the scale up and deployment of greatly underutilized but available mitigation measures will have significant near-term temperature benefits beyond that from slow or delayed action. Overall, strategies exist to cut global methane emissions from human activities in half within the next ten years and half of these strategies currently incur no net cost. Pursuing all mitigation measures now could slow the global-mean rate of near-term decadal warming by around 30%, avoid a quarter of a degree centigrade of additional global-mean warming by midcentury, and set ourselves on a path to avoid more than half a degree centigrade by end of century. On the other hand, slow implementation of these measures may result in an additional tenth of a degree of global-mean warming by midcentury and 5% faster warming rate (relative to fast action), and waiting to pursue these measures until midcentury may result in an additional two tenths of a degree centigrade by midcentury and 15% faster warming rate (relative to fast action). Slow or delayed methane action is viewed by many as reasonable given that current and on-the-horizon climate policies heavily emphasize actions that benefit the climate in the long-term, such as decarbonization and reaching net-zero emissions, whereas methane emitted over the next couple of decades will play a limited role in long-term warming. However, given that fast methane action can considerably limit climate damages in the near-term, it is urgent to scale up efforts and take advantage of this achievable and affordable opportunity as we simultaneously reduce carbon dioxide emissions.

Marine plastic debris floating on the ocean surface is a major environmental problem. However, its distribution in the ocean is poorly mapped, and most of the plastic waste estimated to have entered the ocean from land is unaccounted for. Better understanding of how plastic debris is transported from coastal and marine sources is crucial to quantify and close the global inventory of marine plastics, which in turn represents critical information for mitigation or policy strategies. At the same time, plastic is a unique tracer that provides an opportunity to learn more about the physics and dynamics of our ocean across multiple scales, from the Ekman convergence in basin-scale gyres to individual waves in the surfzone. In this review, we comprehensively discuss what is known about the different processes that govern the transport of floating marine plastic debris in both the open ocean and the coastal zones, based on the published literature and referring to insights from neighbouring fields such as oil spill dispersion, marine safety recovery, plankton connectivity, and others. We discuss how measurements of marine plastics (both in situ and in the laboratory), remote sensing, and numerical simulations can elucidate these processes and their interactions across spatio-temporal scales.

The global response to the COVID-19 pandemic has brought with it significant changes to human mobility patterns and working environments. We aimed to explore how social distancing measures affected recreational use of urban green space during the partial lockdown in Oslo, Norway. Mobile tracking data from thousands of recreationists were used to analyze high resolution spatio-temporal changes in activity. We estimated that outdoor recreational activity increased by 291% during lockdown relative to a 3 yr average for the same days. This increase was significantly greater than expected after adjusting for the prevailing weather and time of year and equates to approx. 86 000 extra activities per day over the municipality (population of 690 000). Both pedestrians (walking, running, hiking) and cyclists appeared to intensify activity on trails with higher greenviews and tree canopy cover, but with differences in response modulated by trail accessibility and social distancing preferences. The magnitude of increase was positively associated with trail remoteness, suggesting that green spaces facilitated social distancing and indirectly mitigated the spread of COVID-19. Finally, pedestrian activity increased in city parks, peri-urban forest, as well as protected areas, highlighting the importance of access to green open spaces that are interwoven within the built-up matrix. These findings shed new light on the value of urban nature as resilience infrastructure during a time of crisis. The current pandemic also reveals some important dilemmas we might face regarding green justice on the path towards urban planning for future sustainable cities.

During the last decades, climate and land use changes led to an increased prevalence of megafires in Mediterranean-type climate regions (MCRs). Here, we argue that current wildfire management policies in MCRs are destined to fail. Focused on fire suppression, these policies largely ignore ongoing climate warming and landscape-scale buildup of fuels. The result is a ‘firefighting trap’ that contributes to ongoing fuel accumulation precluding suppression under extreme fire weather, and resulting in more severe and larger fires. We believe that a ‘business as usual’ approach to wildfire in MCRs will not solve the fire problem, and recommend that policy and expenditures be rebalanced between suppression and mitigation of the negative impacts of fire. This requires a paradigm shift: policy effectiveness should not be primarily measured as a function of area burned (as it usually is), but rather as a function of avoided socio-ecological damage and loss.

California has experienced devastating autumn wildfires in recent years. These autumn wildfires have coincided with extreme fire weather conditions during periods of strong offshore winds coincident with unusually dry vegetation enabled by anomalously warm conditions and late onset of autumn precipitation. In this study, we quantify observed changes in the occurrence and magnitude of meteorological factors that enable extreme autumn wildfires in California, and use climate model simulations to ascertain whether these changes are attributable to human-caused climate change. We show that state-wide increases in autumn temperature (∼1 °C) and decreases in autumn precipitation (∼30%) over the past four decades have contributed to increases in aggregate fire weather indices (+20%). As a result, the observed frequency of autumn days with extreme (95th percentile) fire weather—which we show are preferentially associated with extreme autumn wildfires—has more than doubled in California since the early 1980s. We further find an increase in the climate model-estimated probability of these extreme autumn conditions since ∼1950, including a long-term trend toward increased same-season co-occurrence of extreme fire weather conditions in northern and southern California. Our climate model analyses suggest that continued climate change will further amplify the number of days with extreme fire weather by the end of this century, though a pathway consistent with the UN Paris commitments would substantially curb that increase. Given the acute societal impacts of extreme autumn wildfires in recent years, our findings have critical relevance for ongoing efforts to manage wildfire risks in California and other regions.

Strategies toward ambitious climate targets usually rely on the concept of ‘decoupling’; that is, they aim at promoting economic growth while reducing the use of natural resources and GHG emissions. GDP growth coinciding with absolute reductions in emissions or resource use is denoted as ‘absolute decoupling’, as opposed to ‘relative decoupling’, where resource use or emissions increase less so than does GDP. Based on the bibliometric mapping in part I (Wiedenhofer et al, 2020 Environ. Res. Lett. 15 063002), we synthesize the evidence emerging from the selected 835 peer-reviewed articles. We evaluate empirical studies of decoupling related to final/useful energy, exergy, use of material resources, as well as CO ₂ and total GHG emissions. We find that relative decoupling is frequent for material use as well as GHG and CO ₂ emissions but not for useful exergy, a quality-based measure of energy use. Primary energy can be decoupled from GDP largely to the extent to which the conversion of primary energy to useful exergy is improved. Examples of absolute long-term decoupling are rare, but recently some industrialized countries have decoupled GDP from both production- and, weaklier, consumption-based CO ₂ emissions. We analyze policies or strategies in the decoupling literature by classifying them into three groups: (1) Green growth, if sufficient reductions of resource use or emissions were deemed possible without altering the growth trajectory. (2) Degrowth, if reductions of resource use or emissions were given priority over GDP growth. (3) Others, e.g. if the role of energy for GDP growth was analyzed without reference to climate change mitigation. We conclude that large rapid absolute reductions of resource use and GHG emissions cannot be achieved through observed decoupling rates, hence decoupling needs to be complemented by sufficiency-oriented strategies and strict enforcement of absolute reduction targets. More research is needed on interdependencies between wellbeing, resources and emissions.

Facing the dual challenges of air pollution and climate change, China has set ambitious goals and made decisive efforts to reduce its carbon emission and win the 'Battle for Blue Sky'. However, how the low-carbon transition and air quality targets could be simultaneously achieved at the sub-national levels remains unclear. The questions arise whether province-level climate change mitigation strategies could help ease the air pollution and close the air quality gap, and how these co-benefits can be compared with the cost of the green transition. Here, using an integrated modeling framework, we combined with local air pollutant emission inventories and issued policy documents to quantitatively evaluated the current situation and targets of the air quality and health co-benefits of deep carbon mitigation in Sichuan, a fast-developing inland province in China. We found that by 2035, without system-wide energy transformation induced by carbon mitigation policies, the improvement in air quality in Sichuan Province might be limited, even under stringent end-of-pipe emission control measures. On the contrary, the co-benefits of low-carbon policies would be significant. On top of stringent end-of-pipe controls, the implementation of carbon mitigation policy in line with China's enhanced climate target could further reduce the average PM_2.5 concentration in Sichuan by as much as 2.8 µg m⁻³, or the population-weighted PM_2.5 concentration by 5.9 µg m⁻³ in 2035. The monetized health co-benefits in Sichuan Province would amount to 23 billion USD under the stringent carbon mitigation scenario, exceeding 1.7 billion USD of the mitigation cost by 2035. The results indicate that significant air quality and health benefits could both be achieved from carbon mitigation at the provincial level. Both air-pollution or carbon-reduction oriented policies would be important for improving environmental quality and public health.

Technological characteristics and meteorological conditions are major determinants of the greenhouse gas (GHG) footprints of photovoltaic facilities. By accounting for technological and meteorological differences, we quantified the GHG footprints of 9992 utility-scale photovoltaic facilities worldwide. We obtained a median greenhouse gas footprint of 58.7 g CO₂-eq kWh⁻¹, with a 3-fold spread (28.2–94.6 g CO₂-eq kWh⁻¹, 2.5th and 97.5th percentiles). Differences in panel type appeared to be the most important determinant of variability in the GHG footprint, followed by irradiation and a facility's age. We also provided a meta-model based on these three predictors for users to determine the facility-specific greenhouse gas footprint. The total cumulative electricity produced by the utility-scale photovoltaic fleet worldwide is 457 TWh yr⁻¹, 99.6% of which is produced at footprints below 100 g CO₂-eq kWh⁻¹. Compared to earlier studies, the footprints we computed of global utility-scale facilities show a relatively large spread. In order to further improve the accuracy of facility-specific footprints, more information on panel type as well as production country is required.

Agricultural monitoring, seasonal crop forecasting and climate change adaptation planning all require identifying where, when, how and which crops are grown. Global gridded cropping system data products offer useful information for these applications. However, not only the main sources of information (satellites, censuses, surveys and models) but also the spatial and temporal resolutions of these data products are quite distant from each other because of different user requirements. This is a barrier to strengthening collaborations among the research communities working to increase the capacity of societies to manage climate risks for global food systems, from extreme weather disasters to climate change. A first step is to improve cropping system data products so they can be used more seamlessly across various applications than they are currently. Toward this goal, this article reviews global gridded data products of crop variables (area, yield, cropping intensity, etc) using systematic literature survey, identifies their current limitations, and suggests directions for future research. We found that cropland or crop type mapping and yield or production estimation/prediction together accounted for half of the research objectives of the reviewed studies. Satellite-based data products are dominant at the finer resolution in space and time (<10 km and daily to annual), while model-based data products are found at the coarser resolutions (>55 km and ⩾decadal). Census-based data products are seen at intermediate resolutions (10–55 km and annual to decadal). The suggested directions for future research include the hybridization of multiple sources of information, improvements to temporal coverage and resolution, the enrichment of management variables, the exploration of new sources of information, and comprehensiveness within a single data product.

Given the reported increasing trends in high Asian streamflow and rapidly increasing water demand in the Indian subcontinent, it is necessary to understand the long‐term changes and mechanisms of snow- and glacier-melt-driven streamflow in this area. Thus, we have developed a June–July streamflow reconstruction for the upper Indus River watershed located in northern Pakistan. This reconstruction used a temperature-sensitive tree-ring width chronology of Pinus wallichiana, and explained 40.9% of the actual June–July streamflow variance during the common period 1970–2008. The high level of streamflow (1990–2017) exceeds that of any other time and is concurrent with the impact of recent climate warming that has resulted in accelerated glacier retreats across high Asia. The streamflow reconstruction indicated a pronounced reduction in streamflow in the upper Indus River basin during solar minima (Maunder, Dalton, and Damon). Shorter periods (years) of low streamflow in the reconstruction corresponded to major volcanic eruptions. Extreme low and high streamflows were also linked with sea surface temperature. The streamflow reconstruction also provides a long-term context for recent high Asian streamflow variability resulting from seasonal snow and glaciers that is critically needed for water resources management and assessment.

Despite evidence of the air pollution effects on cognitive function, little is known about the acute impact of indoor air pollution on cognitive function among the working-age population. We aimed to understand whether cognitive function was associated with real-time indoor concentrations of particulate matter (PM_2.5) and carbon dioxide (CO₂). We conducted a prospective observational longitudinal study among 302 office workers in urban commercial buildings located in six countries (China, India, Mexico, Thailand, the United States of America, and the United Kingdom). For 12 months, assessed cognitive function using the Stroop color-word test and addition–subtraction test (ADD) via a mobile research app. We found that higher PM_2.5 and lower ventilation rates, as assessed by CO₂ concentration, were associated with slower response times and reduced accuracy (fewer correct responses per minute) on the Stroop and ADD for eight out ten test metrics. Each interquartile (IQR) increase in PM_2.5 (IQR = 8.8 g m⁻³) was associated with a 0.82% (95% CI: 0.42, 1.21) increase in Stroop response time, a 6.18% (95% CI: 2.08, 10.3) increase in Stroop interference time, a 0.7% (95% CI: −1.38, −0.01) decrease in Stroop throughput, and a 1.51% (95% CI: −2.65, −0.37) decrease in ADD throughput. For CO₂, an IQR increase (IQR = 315 ppm) was associated with a 0.85% (95% CI: 0.32, 1.39) increase in Stroop response time, a 7.88% (95% CI: 2.08, 13.86) increase in Stroop interference time, a 1.32% (95% CI: −2.3, −0.38) decrease in Stroop throughput, and a 1.13% (95% CI: 0.18, 2.11) increase in ADD response time. A sensitivity analysis showed significant association between PM_2.5 in four out of five cognitive test performance metrics only at levels above 12 g m⁻³. Enhanced filtration and higher ventilation rates that exceed current minimum targets are essential public health strategies that may improve employee productivity.

While a growing body of literature suggests beneficial impacts of greenness on several health outcomes, relatively few studies have examined greenness as an effect modifier to impacts of air pollution on health outcomes, and results from the existing studies are inconclusive. We performed a comprehensive, systematic review of previous literature on greenness as a potential effect modifier for associations between particulate matter air pollution and health. After initial screening of 7814 studies, we identified 20 eligible studies. We summarized findings on study characteristics based on several criteria: health outcome, air pollution exposure, source of air pollution data, study location, study period, and median year of the study period. We evaluated characteristics of effect modification by greenness on air pollution and health associations based on the number of greenness metrics applied, type of greenness metric (e.g. normalized difference vegetation index, land use), data source for greenness, and spatial resolution and buffer size. We also summarized evidence for effect modification by greenness based on strength and direction of evidence for each study and overall evidence of effect modification by greenness by several study characteristics. Our systematic review showed that only a limited number of studies have been conducted on greenness as an effect modifier for air pollution-health associations. We found differences in several study characteristics such as greenness assessment (e.g. greenness metrics applied, spatial resolution, and data sources) across studies. Collectively, the studies provide suggestive evidence for the hypothesis that areas with high greenness have lower impacts of air pollution on health, although some studies reported inconsistent findings. The findings from our review provide valuable knowledge on how greenness affects associations between air pollution and health and could help identify critical areas for future study.

Environmental merits are a common motivation for many urban agriculture (UA) projects. One powerful way of quantifying environmental impacts is with life cycle assessment (LCA): a method that estimates the environmental impacts of producing, using, and disposing of a good. LCAs of UA have proliferated in recent years, evaluating a diverse range of UA systems and generating mixed conclusions about their environmental performance. To clarify the varied literature, we performed a systematic review of LCAs of UA to answer the following questions: What is the scope of available LCAs of UA (geographic, crop choice, system type)? What is the environmental performance and resource intensity of diverse forms of UA? How have these LCAs been done, and does the quality and consistency allow the evidence to support decision making? We searched for original, peer-reviewed LCAs of agricultural production at UA systems, and selected and evaluated 47 papers fitting our analysis criteria, covering 88 different farms and 259 production systems. Focusing on yield, water consumption, greenhouse gas emissions, and cumulative energy demand, using functional units based on mass of crops grown and land occupied, we found a wide range of results. We summarized baseline ranges, identified trends across UA profiles, and highlighted the most impactful parts of different systems. There were examples of all types of systems—across physical set up, crop type, and socio-economic orientation—achieving low and high impacts and yields, and performing better or worse than conventional agriculture. However, issues with the quality and consistency of the LCAs, the use of conventional agriculture data in UA settings, and the high variability in their results prevented us from drawing definitive conclusions about the environmental impacts and resource use of UA. We provided guidelines for improving LCAs of UA, and make a strong case that more research on this topic is necessary to improve our understanding of the environmental impacts and benefits of UA.

Arctic amplification (AA)—referring to the enhancement of near-surface air temperature change over the Arctic relative to lower latitudes—is a prominent feature of climate change with important impacts on human and natural systems. In this review, we synthesize current understanding of the underlying physical mechanisms that can give rise to AA. These mechanisms include both local feedbacks and changes in poleward energy transport. Temperature and sea ice-related feedbacks are especially important for AA, since they are significantly more positive over the Arctic than at lower latitudes. Changes in energy transport by the atmosphere and ocean can also contribute to AA. These energy transport changes are tightly coupled with local feedbacks, and thus their respective contributions to AA should not be considered in isolation. It is here emphasized that the feedbacks and energy transport changes that give rise to AA are sensitively dependent on the state of the climate system itself. This implies that changes in the climate state will lead to changes in the strength of AA, with implications for past and future climate change.

Climate change and air pollution can interact to amplify risks to human health and crop production. This has significant implications for our ability to reach the Sustainable Development Goals (e.g. SDGs 2, 3, 13, 15) and for the design of effective mitigation and adaptation policies and risk management. To be able to achieve the SDG targets, closer integration of climate change and air pollution both in terms of impact assessment for human health and agricultural productivity and respective policy development is needed. Currently, studies estimating the impacts of climate and air pollutants on human health and crops mostly treat these stressors separately, and the methods used by the health and agricultural science communities differ. Better insights into the methods applied in the different communities can help to improve existing and develop new methods to advance our knowledge about the combined impacts of climate change and air pollution on human health and crops. This topical review provides an overview of current methodologies applied in the two fields of human health and agricultural crop impact studies, ranging from empirical regression-based and experimental methods to more complex process-based models. The latter are reasonably well developed for estimating impacts on agricultural crops, but not for health impacts. We review available literature addressing the combined effects of climate and air pollution on human health or agricultural productivity to provide insights regarding state-of-the-art knowledge and currently available methods in the two fields. Challenges to assess the combined effect of climate and air pollution on human health and crops, and opportunities for both fields to learn from each other, are discussed.

Agricultural monitoring, seasonal crop forecasting and climate change adaptation planning all require identifying where, when, how and which crops are grown. Global gridded cropping system data products offer useful information for these applications. However, not only the main sources of information (satellites, censuses, surveys and models) but also the spatial and temporal resolutions of these data products are quite distant from each other because of different user requirements. This is a barrier to strengthening collaborations among the research communities working to increase the capacity of societies to manage climate risks for global food systems, from extreme weather disasters to climate change. A first step is to improve cropping system data products so they can be used more seamlessly across various applications than they are currently. Toward this goal, this article reviews global gridded data products of crop variables (area, yield, cropping intensity, etc) using systematic literature survey, identifies their current limitations, and suggests directions for future research. We found that cropland or crop type mapping and yield or production estimation/prediction together accounted for half of the research objectives of the reviewed studies. Satellite-based data products are dominant at the finer resolution in space and time (<10 km and daily to annual), while model-based data products are found at the coarser resolutions (>55 km and ⩾decadal). Census-based data products are seen at intermediate resolutions (10–55 km and annual to decadal). The suggested directions for future research include the hybridization of multiple sources of information, improvements to temporal coverage and resolution, the enrichment of management variables, the exploration of new sources of information, and comprehensiveness within a single data product.

This study adopts a multi-level approach to examine the extent to which state- and household-level factors shape residential energy consumption in the United States, focusing on efficiency improvement and affluence. Analyzing the 2009 Residential Energy Consumption Survey, state-level energy efficiency data from the American Council for an Energy-Efficient Economy (ACEEE), and other sources, we find that state context significantly influences energy consumption at the household level. Households in states scoring high on energy efficiency consume significantly less residential energy than those in states scoring low on the measure. At the household level, the analysis reveals mixed relationships between investment in energy efficiency technologies and residential energy consumption, as some measures of efficiency technology are negatively related to residential energy consumption, others are positively related to it. In regard to affluence, state-level measures do not emerge as significant predictors of residential energy consumption. At the household level, however, affluence drives residential energy consumption, which, in turn, is a significant driver of carbon dioxide emissions. Our study makes an important contribution to the social scientific literature on energy consumption, illuminating distinct relationships at different levels. To the best of our knowledge, this is the first study that simultaneously examines the impacts of factors measured at both the household (micro) and state (meso) levels.

The increasing global demand for farmland products is placing unprecedented pressure on the global agricultural system and its water resources. Many regions of the world, that are affected by a chronic water scarcity relative to their population, strongly depend on the import of agricultural commodities and associated embodied (or virtual) water. The globalization of water through virtual water trade (VWT) is leading to a displacement of water use and a disconnection between human populations and the water resources they rely on. Despite the recognized importance of these phenomena in reshaping the patterns of water dependence through teleconnections between consumers and producers, their effect on global and regional water resources has just started to be quantified. This review investigates the global spatiotemporal dynamics, drivers, and impacts of VWT through an integrated analysis of surface water, groundwater, and root-zone soil moisture consumption for agricultural production; it evaluates how virtual water flows compare to the major ‘physical water fluxes’ in the Earth System; and provides a new reconceptualization of the hydrologic cycle to account also for the role of water redistribution by the hidden ‘virtual water cycle’.

Heat is the number one weather-related killer in the United States and indoor exposure is responsible for a significant portion of the resulting fatalities. Evolving construction practices combined with urban development in harsh climates has led building occupants in many cities to rely on air conditioning (AC) to a degree that their health and well-being are compromised in its absence. The risks are substantial if loss of AC coincides with a hot weather episode (henceforth, a heat disaster). Using simulations, we found that residential buildings in many US cities are highly vulnerable to heat disasters—with more than 50 million citizens living in cities at significant risk. This situation will be exacerbated by intensification of urban heat islands, climate change, and evolving construction practices. It is therefore crucial that future building codes consider thermal resiliency in addition to energy efficiency.

We examine the potential for climate change to impact fertility via adaptations in human behavior. We start by discussing a wide range of economic channels through which climate change might impact fertility, including sectoral reallocation, the gender wage gap, longevity, and child mortality. Then, we build a quantitative model that combines standard economic-demographic theory with existing estimates of the economic consequences of climate change. In the model, increases in global temperature affect agricultural and non-agricultural sectors differently. Near the equator, where many poor countries are located, climate change has a larger negative effect on agriculture. The resulting scarcity in agricultural goods acts as a force towards higher agricultural prices and wages, leading to a labor reallocation into this sector. Since agriculture makes less use of skilled labor, climate damage decreases the return to acquiring skills, inducing parents to invest less resources in the education of each child and to increase fertility. These patterns are reversed at higher latitudes, suggesting that climate change may exacerbate inequities by reducing fertility and increasing education in richer northern countries, while increasing fertility and reducing education in poorer tropical countries. While the model only examines the role of one mechanism, it suggests that climate change could have an impact on fertility, indicating the need for future work on this important topic.

We use a multiple-regime panel smooth transition regression to examine the economic and climatic sources of the nonuniform relationship between El Niño Southern Oscillation (ENSO) and maize yields around the globe. While the yield effect is predominantly observed in strongly teleconnected countries, it is amplified in lower income countries, which we attribute to possible lack of resilience to ENSO—induced weather shocks. Both El Niño-like and La Niña-like conditions result in maize yield reduction, but it is during El Niño events when maize yields drop by up to 20% in most affected countries. Because in many of these countries maize is an important agricultural crop, the presented results are of interest to researchers and policy makers in the areas of world nutrition and international aid. Moreover, because larger share of maize is produced by high income weakly teleconnected countries, the observed geographic heterogeneity of the El Niño impact offers possible benefits from global risk sharing. These findings also offer insights to climate change economics, as possible increased frequency of the ENSO cycle may negatively impact maize production in strongly teleconnected low income countries.