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Effective policies for adaptation to climate change require understanding how impacts are related to exposures and vulnerability, the dimensions of the climate system that will change most and where human impacts will be most draconian, and the institutions best suited to respond. Here, we propose a simple method for more credibly pairing empirical statistical damage estimates derived from recent weather and outcome observations with projected future climate changes and proposed responses. We first analyze agricultural production and loan repayment data from Brazil to understand vulnerability to historical variation in the more predictable components of temperature and rainfall (trend and seasonality) as well as to shocks (both local and over larger spatial scales). This decomposed weather variation over the past two decades explains over 50% of the yield variation in major Brazilian crops and, critically, can be constructed in the same way for future climate projections. Combining our estimates with bias-corrected downscaled climate simulations for Brazil, we find increased variation in yields and revenues (including more bad years and worse outcomes) and higher agricultural loan default at midcentury. Results in this context point to two particularly acute dimensions of vulnerability: Intensified seasonality and local idiosyncratic shocks both contribute to worsening outcomes, along with a reduced capacity for spatially correlated (covariate) shocks to ameliorate these effects through prices. These findings suggest that resilience strategies should focus on institutions such as water storage, financial services, and reinsurance.

ImportanceThe etiology of Kawasaki disease (KD) remains elusive, with immunologic and epidemiologic data suggesting different triggers in individuals who are genetically susceptible. KD remains the most common cause of acquired heart disease in pediatric patients, and Japan is the country of highest incidence, with an increasing number of cases.ObjectiveTo investigate whether an analysis of the epidemiologic KD record in Japan stratified by age and prefecture (subregion) may yield new clues regarding mechanisms of exposure to etiologic agents associated with KD.Design, setting, and participantsThis cross-sectional study was conducted using a dataset of patients with KD with detailed information on location and age at onset created through nationwide surveys of hospitals caring for pediatric patients with KD throughout Japan. Pediatric patients hospitalized in Japan for KD from 1970 to 2020 were included. Data were analyzed from January 2022 to January 2024.ExposurePediatric patients with KD.Main outcomes and measuresThe KD dataset was analyzed by patient age (infants [aged

The United States government has indicated a desire to advance environmental justice through climate policy. As fossil fuel combustion produces both conventional pollutants and greenhouse gas (GHG) emissions, climate mitigation strategies may provide an opportunity to address historical inequities in air pollution exposure. To test the impact of climate policy implementation choices on air quality equity, we develop a broad range of GHG reduction scenarios that are each consistent with the US Paris Accord target and model the resulting air pollution changes. Using idealized decision criteria, we show that least cost and income-based emission reductions can exacerbate air pollution disparities for communities of color. With a suite of randomized experiments that facilitates exploration of a wider climate policy decision space, we show that disparities largely persist despite declines in average pollution exposure, but that reducing transportation emissions has the most potential to reduce racial inequities.

The magnitude and distribution of physical and societal impacts from long-lived greenhouse gases are insensitive to the emission source location; the same is not true for major coemitted short-lived pollutants such as aerosols. Here, we combine novel global climate model simulations with established response functions to show that a given aerosol emission from different regions produces divergent air quality and climate changes and associated human system impacts, both locally and globally. The marginal global damages to infant mortality, crop productivity, and economic growth from aerosol emissions and their climate effects differ by more than an order of magnitude depending on source region, with certain regions creating global external climate changes and impacts much larger than those felt locally. The complex distributions of aerosol-driven societal impacts emerge from geographically distinct and region-specific aerosol-climate interactions, estimation of which is enabled by the full Earth System Modeling Framework used here.

Nitrogen oxides (NOx) are among the most widely emitted pollutants in the world, yet their impacts on agriculture remain poorly known. NOx can directly damage crop cells and indirectly affect growth by promoting ozone (O3) and aerosol formation. We use satellite measures of both crop greenness and NOx during 2018-2020 to evaluate crop impacts for five major agricultural regions. We find consistent negative associations between NO2 and greenness across regions and seasons. These effects are strongest in conditions where O3 formation is NOx limited but remain significant even in locations where this pathway is muted, suggesting a role for direct NOx damage. Using simple counterfactuals and leveraging published relationships between greenness and growth, we estimate that reducing NOx levels to the current fifth percentile in each region would raise yields by ~25% for winter crops in China, ~15% for summer crops in China, and up to 10% in other regions.

Abstract. Irrigation has important implications for sustaining global food production by enabling crop water demand to be met even under dry conditions.Added water also cools crop plants through transpiration; irrigation mightthus play an important role in a warmer climate by simultaneously moderating water and high temperature stresses. Here we used satellite-derived evapotranspiration estimates, land surface temperature (LST) measurements, and crop phenological stage information from Nebraska maize to quantify how irrigation relieves both water and temperature stresses. Unlike air temperature metrics, satellite-derived LST revealed a significant irrigation-induced cooling effect, especially during the grain filling period (GFP) of crop growth. This cooling appeared to extend the maize growing season, especially for GFP, likely due to the stronger temperature sensitivity of phenological development during this stage. Our analysis also revealed that irrigation not only reduced water and temperature stress but also weakened the response of yield to these stresses. Specifically, temperature stress was significantly weakened for reproductive processes in irrigated maize. Attribution analysis further suggested that water and high temperature stress alleviation was responsible for 65±10 % and 35±5.3 % of the irrigation yield benefit, respectively. Our study underlines the relative importance of high temperature stress alleviation in yield improvement and the necessity of simulating crop surface temperature to better quantify heat stress effects in crop yield models. Finally, considering the potentially strong interaction between water and heat stress, future research on irrigation benefits should explore the interaction effects between heat and drought alleviation.

In a single-site study (San Diego, CA, USA), we previously showed that Kawasaki Disease (KD) cases cluster temporally in bursts of approximately 7 days. These clusters occurred more often than would be expected at random even after accounting for long-term trends and seasonality. This finding raised the question of whether other locations around the world experience similar temporal clusters of KD that might offer clues to disease etiology. Here we combine data from San Diego and nine additional sites around the world with hospitals that care for large numbers of KD patients, as well as two multi-hospital catchment regions. We found that across these sites, KD cases clustered at short time scales and there were anomalously long quiet periods with no cases. Both of these phenomena occurred more often than would be expected given local trends and seasonality. Additionally, we found unusually frequent temporal overlaps of KD clusters and quiet periods between pairs of sites. These findings suggest that regional and planetary range environmental influences create periods of higher or lower exposure to KD triggers that may offer clues to the etiology of KD.

Surface deformation in California's Central Valley (CV) has long been linked to changes in groundwater storage. Recent advances in remote sensing have enabled the mapping of CV deformation and associated changes in groundwater resources at increasingly higher spatiotemporal resolution. Here, we use interferometric synthetic aperture radar (InSAR) from the Sentinel-1 missions, augmented by continuous Global Positioning System (cGPS) positioning, to characterize the surface deformation of the San Joaquin Valley (SJV, southern two-thirds of the CV) for consecutive dry (2016) and wet (2017) water years. We separate trends and seasonal oscillations in deformation time series and interpret them in the context of surface and groundwater hydrology. We find that subsidence rates in 2016 (mean -42.0 mm/yr; peak -345 mm/yr) are twice that in 2017 (mean -20.4 mm/yr; peak -177 mm/yr), consistent with increased groundwater pumping in 2016 to offset the loss of surface-water deliveries. Locations of greatest subsidence migrated outwards from the valley axis in the wetter 2017 water year, possibly reflecting a surplus of surface-water supplies in the lowest portions of the SJV. Patterns in the amplitude of seasonal deformation and the timing of peak seasonal uplift reveal entry points and potential pathways for groundwater recharge into the SJV and subsequent groundwater flow within the aquifer. This study provides novel insight into the SJV aquifer system that can be used to constrain groundwater flow and subsidence models, which has relevance to groundwater management in the context of California's 2014 Sustainable Groundwater Management Act (SGMA).

ObjectiveTo test the hypothesis that cases of Kawasaki disease within a temporal cluster have a similar pattern of host response that is distinct from cases of Kawasaki disease in different observed clusters and randomly constructed clusters.Study designWe designed a case-control study to analyze 47 clusters derived from 1332 patients with Kawasaki disease over a 17-year period (2002-2019) from a single clinical site and compared the cluster characteristics with those of 2 control groups of synthetic Kawasaki disease clusters. We defined a "true" Kawasaki disease cluster as at least 5 patients within a 7-day moving window. The observed and synthetic Kawasaki disease clusters were compared with respect to demographic and clinical characteristics and median values for standard laboratory data using univariate analysis and a multivariate, rotated empirical orthogonal function analysis.ResultsIn a univariate analysis, the median values for age, coronary artery z-score, white blood cell count, erythrocyte sedimentation rate, C-reactive protein, and age-adjusted hemoglobin for several of the true Kawasaki disease clusters exceeded the 95th percentile for the 2 synthetic clusters. REOF analyses revealed distinct patterns of demographic and clinical measures within clusters.ConclusionsCases of Kawasaki disease within a cluster were more similar with respect to demographic and clinical features and levels of inflammation than would be expected by chance. These observations suggest that different triggers and/or different intensities of exposures result in clusters of cases of Kawasaki disease that share a similar response pattern. Analyzing cases within clusters or cases who share demographic and clinical features may lead to new insights into the etiology of Kawasaki disease.

Recent dramatic and deadly increases in global wildfire activity have increased attention on the causes of wildfires, their consequences, and how risk from wildfire might be mitigated. Here we bring together data on the changing risk and societal burden of wildfire in the United States. We estimate that nearly 50 million homes are currently in the wildland-urban interface in the United States, a number increasing by 1 million houses every 3 y. To illustrate how changes in wildfire activity might affect air pollution and related health outcomes, and how these linkages might guide future science and policy, we develop a statistical model that relates satellite-based fire and smoke data to information from pollution monitoring stations. Using the model, we estimate that wildfires have accounted for up to 25% of PM2.5 (particulate matter with diameter

We use a combination of economic and wellbeing metrics to evaluate the impacts of a climate resilience program designed for family farmers in the semiarid region of Brazil. Most family farmers in the region are on the verge of income and food insufficiency, both of which are exacerbated in prolonged periods of droughts. The program assisted farmers in their milk and sheepmeat production, implementing a set of climate-smart production practices and locally-adapted technologies. We find that the program under evaluation had substantive and significant impacts on production practices, land management, and quality of life in general, using several different quasi-experimental strategies to estimate the average treatment effect on the treated farmers. We highlight the strengths and limitations of each evaluation strategy and how the set of analyses and outcome indicators complement each other. The evaluation provides valuable insights into the economic and environmental sustainability of family farming in semiarid regions, which are under growing pressure from climate change and environmental degradation worldwide.

We use a combination of economic and wellbeing metrics to evaluate the impacts of a climate resilience program designed for family farmers in the semiarid region of Brazil. Most family farmers in the region are on the verge of income and food insufficiency, both of which are exacerbated in prolonged periods of droughts. The program assisted farmers in their milk and sheepmeat production, implementing a set of climate-smart production practices and locally-adapted technologies. We find that the program under evaluation had substantive and significant impacts on production practices, land management, and quality of life in general, using several different quasi-experimental strategies to estimate the average treatment effect on the treated farmers. We highlight the strengths and limitations of each evaluation strategy and how the set of analyses and outcome indicators complement each other. The evaluation provides valuable insights into the economic and environmental sustainability of family farming in semiarid regions, which are under growing pressure from climate change and environmental degradation worldwide.

Racial and ethnic minorities in the United States often experience higher-than-average exposures to air pollution. However, the relative contribution of embedded institutional biases to these disparities can be difficult to disentangle from physical environmental drivers, socioeconomic status, and cultural or other factors that are correlated with exposures under status quo conditions. Over the spring and summer of 2020, rapid and sweeping COVID-19 shelter-in-place orders around the world created large perturbations to local and regional economic activity that resulted in observable changes in air pollution concentrations, compositions, and distributions. Here, we use the pandemic-related emergency order and subsequent economic slowdown to causally estimate pollution exposure disparities in California. Using both public ground-based sensor data and a citizen-science network of monitors for respirable particulate matter (PM2.5), along with satellite records of nitrogen dioxide (NO2), we show that the initial sheltering-in-place period produced disproportionate air pollution reduction benefits for Asian, Hispanic/Latinx, and low- income communities. By linking these pollution data with weather, geographic, socioeconomic, and mobility data in difference-in-differences models, we demonstrate that these disparate pollution reductions cannot be explained by environmental conditions, geography, income, or local economic activity and are instead driven by non-local activity. This study thus provides causally-identified evidence of systemic racial and ethnic bias in pollution control under business-as-usual conditions.

Achieving sustainable agricultural groundwater use remains a significant challenge worldwide in part because data on groundwater withdrawals are limited. A new generation of interferometric synthetic aperture radar (InSAR) data provide high spatial- and temporal- resolution measurements of subsidence and uplift of the earth’s surface, which are known to reflect change in groundwater storage below. Here, we establish for the first time a quantitative link between local irrigation water demand and InSAR-derived vertical land surface displacements in California’s San Joaquin Valley, with the goal of increasing the utility of remotely sensed displacements for understanding and managing groundwater at fine scales. We relate 100 m, sub-monthly displacements to estimates of irrigation water demand generated from land cover and weather data by performing a suite of physical process-motivated statistical analyses that leverage (i) temporal variations in surface water supplies created by climate, and (ii) spatial variations in water demand created by different land uses. Between 2015 and 2017, cultivated land experienced up to seven times the total subsidence, and up to nine times the dry year subsidence rate, of uncultivated land. In uncultivated areas, subsidence rates differed minimally across dry and wet years. In contrast, within cultivated areas, dry year subsidence rates were more than double wet year rates, indicating increased agricultural groundwater pumping under diminished precipitation and surface water supplies. Mean subsidence, and the marginal response of subsidence to water demand, were greatest for cultivated lands and for field and pasture crops in particular, and were also proportional to distance from surface water supply infrastructure. These findings demonstrate that land surface observations have the potential for use in the quantification of connected surface water and groundwater processes at policy-relevant scales.

ObjectiveTo examine the impacts of a Solar Market Garden 1-year solar-powered drip irrigation (SMG) programme in Kalalé district of northern Benin on mothers' nutritional status and micronutrient levels.DesignUsing a quasi-experimental design, sixteen villages were assigned to four groups: (i) SMG women's groups (WG); (ii) comparison WG; (iii) SMG non-WG (NWG); and (iv) comparison NWG. Difference-in-differences (DID) estimates were used to assess impacts on mothers' food consumption, diversity, BMI, prevalence of underweight (BMI < 18·5 kg/m2) and anaemia, and deficiencies of iron (ID) and vitamin A (VAD).SettingKalalé district, northern Benin.ParticipantsNon-pregnant mothers aged 15-49 years (n 1737).ResultsThe SMG programme significantly increased mothers' intake of vegetables (DID = 25·31 percentage points (pp); P < 0·01), dietary diversity (DID = 0·74; P < 0·01) and marginally increased their intake of flesh foods (DID = 10·14 pp; P < 0·1). Mean BMI was significantly increased among SMG WG compared with the other three groups (DID = 0·44 kg/m2; P < 0·05). The SMG programme also significantly decreased the prevalence of anaemia (DID = 12·86 pp; P < 0·01) but no impacts were found for the prevalence of underweight, ID and VAD.ConclusionsImproving mothers' dietary intake and anaemia prevalence supports the need to integrate gender-based agriculture to improve nutritional status. However, it may take more than a year, and additional nutrition and health programmes, to impact the prevalence of maternal underweight, ID and VAD.

The strategic engineering of solar energy technologies—from individual rooftop modules to large solar energy power plants—can confer significant synergistic outcomes across industrial and ecological boundaries. Here, we propose techno–ecological synergy (TES), a framework for engineering mutually beneficial relationships between technological and ecological systems, as an approach to augment the sustainability of solar energy across a diverse suite of recipient environments, including land, food, water, and built-up systems. We provide a conceptual model and framework to describe 16 TESs of solar energy and characterize 20 potential techno–ecological synergistic outcomes of their use. For each solar energy TES, we also introduce metrics and illustrative assessments to demonstrate techno–ecological potential across multiple dimensions. The numerous applications of TES to solar energy technologies are unique among energy systems and represent a powerful frontier in sustainable engineering to minimize unintended consequences on nature associated with a rapid energy transition.

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Kawasaki Disease (KD) is the most common cause of pediatric acquired heart disease, but its etiology remains unknown. We examined 1164 cases of KD treated at a regional children's hospital in San Diego over a period of 15 years and uncovered novel structure to disease incidence. KD cases showed a well-defined seasonal variability, but also clustered temporally at much shorter time scales (days to weeks), and spatiotemporally on time scales of up to 10 days and spatial scales of 10-100 km. Temporal clusters of KD cases were associated with strongly significant regional-scale air temperature anomalies and consistent larger-scale atmospheric circulation patterns. Gene expression analysis further revealed a natural partitioning of KD patients into distinct groups based on their gene expression pattern, and that the different groups were associated with certain clinical characteristics that also exhibit temporal autocorrelation. Our data suggest that one or more environmental triggers exist, and that episodic exposures are modulated at least in part by regional weather conditions. We propose that characterization of the environmental factors that trigger KD in genetically susceptible children should focus on aerosols inhaled by patients who share common disease characteristics.

Poor air quality is thought to be an important mortality risk factor globally1-3, but there is little direct evidence from the developing world on how mortality risk varies with changing exposure to ambient particulate matter. Current global estimates apply exposure-response relationships that have been derived mostly from wealthy, mid-latitude countries to spatial population data4, and these estimates remain unvalidated across large portions of the globe. Here we combine household survey-based information on the location and timing of nearly 1 million births across sub-Saharan Africa with satellite-based estimates5 of exposure to ambient respirable particulate matter with an aerodynamic diameter less than 2.5 μm (PM2.5) to estimate the impact of air quality on mortality rates among infants in Africa. We find that a 10 μg m-3 increase in PM2.5 concentration is associated with a 9% (95% confidence interval, 4-14%) rise in infant mortality across the dataset. This effect has not declined over the last 15 years and does not diminish with higher levels of household wealth. Our estimates suggest that PM2.5 concentrations above minimum exposure levels were responsible for 22% (95% confidence interval, 9-35%) of infant deaths in our 30 study countries and led to 449,000 (95% confidence interval, 194,000-709,000) additional deaths of infants in 2015, an estimate that is more than three times higher than existing estimates that attribute death of infants to poor air quality for these countries2,6. Upward revision of disease-burden estimates in the studied countries in Africa alone would result in a doubling of current estimates of global deaths of infants that are associated with air pollution, and modest reductions in African PM2.5 exposures are predicted to have health benefits to infants that are larger than most known health interventions.

We present a rationale for, and results from, the pilot of a direct individual-to-institution remittance system in the context of school fee payment in rural Benin. Data confirm that school fees act as an impediment to educational attainment, and in very rural poor settings such as northern Benin, students often depend on extended family and kinship networks to pay fees. But existing remittance options are costly, in terms of fees, time, and risk. We pilot a new technology bundle in a single public high school in northeastern Benin, and evaluate its effectiveness. Here we describe the technical and institutional implementation of the project, as well as our findings from the first year of operation. We discuss takeaways and implications for scale-up.

Semi-arid ecosystems play a key role in global agricultural production, seasonal carbon cycle dynamics, and longer-run climate change. Because semi-arid landscapes are heterogeneous and often sparsely vegetated, repeated and large-scale ecosystem assessments of these regions have to date been impossible. Here, we assess the potential of high-spatial resolution visible band imagery for semi-arid ecosystem mapping. We use WorldView satellite imagery at 0.3–0.5 m resolution to develop a reference data set of nearly 10,000 labeled examples of three classes—trees, shrubs/grasses, and bare land—across 1000 km 2 of the semi-arid Sertão region of northeast Brazil. Using Google Earth Engine, we show that classification with low-spectral but high-spatial resolution input (WorldView) outperforms classification with the full spectral information available from Landsat 30 m resolution imagery as input. Classification with high spatial resolution input improves detection of sparse vegetation and distinction between trees and seasonal shrubs and grasses, two features which are lost at coarser spatial (but higher spectral) resolution input. Our total tree cover estimates for the study area disagree with recent estimates using other methods that may underestimate treecover because they confuse trees with seasonal vegetation (shrubs and grasses). This distinction is important for monitoring seasonal and long-run carbon cycle and ecosystem health. Our results suggest that newer remote sensing products that promise high frequency global coverage at high spatial but lower spectral resolution may offer new possibilities for direct monitoring of the world’s semi-arid ecosystems, and we provide methods that could be scaled to do so.

BackgroundEvidence on effectiveness of women's empowerment (WE) to reduce undernutrition is limited in sub-Sahara Africa, and few studies incorporate multidimensional measures of WE.ObjectiveTo examine whether a WE status, in sum and across leadership, decision-making, mobility, economic security, male involvement in housework, and nonfamily group domains, is associated with women and their children nutritional status in Kalalé district of northern Benin.MethodsData were obtained from the 2014 Solar Market Garden baseline study: 767 paired reproductive-age women aged 15 to 49 years and children 6 to 59 months old. Exploratory principal component (cross-validate with confirmatory) factor analysis was first conducted to identify the structure of empowerment. Then, using a new survey-based index, regression analysis was conducted to examine associations between WE measures and maternal dietary diversity score (DDS) and body mass index (BMI), as well as their child's DDS, height-for-age z score (HAZ), weight-for-height z score (WHZ), and weight-for-age z score (WAZ).ResultsPositive associations were observed between women's composite empowerment, leadership, maternal DDS and BMI, and female child's DDS. However, opposite signs were found between economic security and child's DDS. Mobility was positively associated with female children's WHZ and male children's HAZ and WAZ, while decision-making was correlated with male child's WHZ and female children's WAZ.ConclusionsWomen's empowerment can be associated with undernutrition. Efforts to improve nutrition may benefit from empowerment initiatives that promote women's self-confidence and decision-making in Benin. However, additional qualitative and longitudinal research may enhance understanding of WE in the present area.

Abstract Although development organizations agree that reliable access to energy and energy services—one of the 17 Sustainable Development Goals—is likely to have profound and perhaps disproportionate impacts on women, few studies have directly empirically estimated the impact of energy access on women’s empowerment. This is a result of both a relative dearth of energy access evaluations in general and a lack of clarity on how to quantify gender impacts of development projects. Here we present an evaluation of the impacts of the Solar Market Garden—a distributed photovoltaic irrigation project—on the level and structure of women’s empowerment in Benin, West Africa. We use a quasi-experimental design (matched-pair villages) to estimate changes in empowerment for project beneficiaries after one year of Solar Market Garden production relative to non-beneficiaries in both treatment and comparison villages (n = 771). To create an empowerment metric, we constructed a set of general questions based on existing theories of empowerment, and then used latent variable analysis to understand the underlying structure of empowerment locally. We repeated this analysis at follow-up to understand whether the structure of empowerment had changed over time, and then measured changes in both the levels and likelihood of empowerment over time. We show that the Solar Market Garden significantly positively impacted women’s empowerment, particularly through the domain of economic independence. In addition to providing rigorous evidence for the impact of a rural renewable energy project on women’s empowerment, our work lays out a methodology that can be used in the future to benchmark the gender impacts of energy projects.

ObjectiveTo identify the magnitude of anaemia and deficiencies of Fe (ID) and vitamin A (VAD) and their associated factors among rural women and children.DesignCross-sectional, comprising a household, health and nutrition survey and determination of Hb, biochemical (serum concentrations of ferritin, retinol, C-reactive protein and α1-acid glycoprotein) and anthropometric parameters. Multivariate logistic regression examined associations of various factors with anaemia and micronutrient deficiencies.SettingKalalé district, northern Benin.SubjectsMother-child pairs (n 767): non-pregnant women of reproductive age (15-49 years) and children 6-59 months old.ResultsIn women, the overall prevalence of anaemia, ID, Fe-deficiency anaemia (IDA) and VAD was 47·7, 18·3, 11·3 and 17·7 %, respectively. A similar pattern for anaemia (82·4 %), ID (23·6 %) and IDA (21·2 %) was observed among children, while VAD was greater at 33·6 %. Greater risk of anaemia, ID and VAD was found for low maternal education, maternal farming activity, maternal health status, low food diversity, lack of fruits and vegetables consumption, low protein foods consumption, high infection, anthropometric deficits, large family size, poor sanitary conditions and low socio-economic status. Strong differences were also observed by ethnicity, women's group participation and source of information. Finally, age had a significant effect in children, with those aged 6-23 months having the highest risk for anaemia and those aged 12-23 months at risk for ID and IDA.ConclusionsAnaemia, ID and VAD were high among rural women and their children in northern Benin, although ID accounted for a small proportion of anaemia. Multicentre studies in various parts of the country are needed to substantiate the present results, so that appropriate and beneficial strategies for micronutrient supplementation and interventions to improve food diversity and quality can be planned.

Historically, human uses of land have transformed and fragmented ecosystems.sup.1,2, degraded biodiversity.sup.3,4, disrupted carbon and nitrogen cycles.sup.5,6 and added prodigious quantities of greenhouse gases (GHGs) to the atmosphere.sup.7,8. However, in contrast to fossil-fuel carbon dioxide (CO.sub.2) emissions, trends and drivers of GHG emissions from land management and land-use change (together referred to as 'land-use emissions') have not been as comprehensively and systematically assessed. Here we present country-, process-, GHG- and product-specific inventories of global land-use emissions from 1961 to 2017, we decompose key demographic, economic and technical drivers of emissions and we assess the uncertainties and the sensitivity of results to different accounting assumptions. Despite steady increases in population (+144 per cent) and agricultural production per capita (+58 per cent), as well as smaller increases in emissions per land area used (+8 per cent), decreases in land required per unit of agricultural production (-70 per cent) kept global annual land-use emissions relatively constant at about 11 gigatonnes CO.sub.2-equivalent until 2001. After 2001, driven by rising emissions per land area, emissions increased by 2.4 gigatonnes CO.sub.2-equivalent per decade to 14.6 gigatonnes CO.sub.2-equivalent in 2017 (about 25 per cent of total anthropogenic GHG emissions). Although emissions intensity decreased in all regions, large differences across regions persist over time. The three highest-emitting regions (Latin America, Southeast Asia and sub-Saharan Africa) dominate global emissions growth from 1961 to 2017, driven by rapid and extensive growth of agricultural production and related land-use change. In addition, disproportionate emissions are related to certain products: beef and a few other red meats supply only 1 per cent of calories worldwide, but account for 25 per cent of all land-use emissions. Even where land-use change emissions are negligible or negative, total per capita CO.sub.2-equivalent land-use emissions remain near 0.5 tonnes per capita, suggesting the current frontier of mitigation efforts. Our results are consistent with existing knowledge--for example, on the role of population and economic growth and dietary choice--but provide additional insight into regional and sectoral trends. Trends in the rate of region- and sector-specific land-use greenhouse gas emissions in 1961-2017 show an acceleration of about 20% per decade after 2001., Author(s): Chaopeng Hong [sup.1] , Jennifer A. Burney [sup.2] , Julia Pongratz [sup.3] [sup.4] , Julia E. M. S. Nabel [sup.4] , Nathaniel D. Mueller [sup.5] [sup.6] , Robert B. [...]

Greenhouse gas emissions from fossil fuel combustion and land use are changing the radiative budget of the Earth and changing its climate. The negative impacts of this climate change on natural and human systems are already emergent. The solution is to eliminate greenhouse gas emissions altogether as soon as possible, but the rate at which these emissions can decrease is limited by human reliance on fossil fuels for energy and the infrastructural, socio-economic, and behavioral inertia of current systems around the world. In this chapter, we discuss the physical impacts as well as the many challenges and obstacles to ‘bending the curve’, and provide a framework of possible solutions.

Roughly one-third of anthropogenic GHG emissions are caused by agricultural and forestry activities and landuse change (collectively, 'land-use emissions'). Understanding the ultimate drivers of these emissions requires attributing emissions to specific land-use activities and products. Although quantities of land-use emissions are matters of fact, the methodological choices and assumptions required to attribute those emissions to activities and products depend on research goals and data availability. In this review, we explore several possible accounting methods. Our results highlight the sensitivity of accounting to temporal distributions of emissions and the consequences of replacing spatially-explicit data with aggregate proxies such as production or harvested area data. Different accounting options emphasize different causes of land-use emissions (e.g., proximate or indirect drivers of deforestation). To support public policies that effectively balance competing objectives, analysts should carefully consider and communicate implications of accounting choices.

Solar radiation management is increasingly considered to be an option for managing global temperatures.sup.1,2, yet the economic effects of ameliorating climatic changes by scattering sunlight back to space remain largely unknown.sup.3. Although solar radiation management may increase crop yields by reducing heat stress.sup.4, the effects of concomitant changes in available sunlight have never been empirically estimated. Here we use the volcanic eruptions that inspired modern solar radiation management proposals as natural experiments to provide the first estimates, to our knowledge, of how the stratospheric sulfate aerosols created by the eruptions of El Chichón and Mount Pinatubo altered the quantity and quality of global sunlight, and how these changes in sunlight affected global crop yields. We find that the sunlight-mediated effect of stratospheric sulfate aerosols on yields is negative for both C4 (maize) and C3 (soy, rice and wheat) crops. Applying our yield model to a solar radiation management scenario based on stratospheric sulfate aerosols, we find that projected mid-twenty-first century damages due to scattering sunlight caused by solar radiation management are roughly equal in magnitude to benefits from cooling. This suggests that solar radiation management--if deployed using stratospheric sulfate aerosols similar to those emitted by the volcanic eruptions it seeks to mimic--would, on net, attenuate little of the global agricultural damage from climate change. Our approach could be extended to study the effects of solar radiation management on other global systems, such as human health or ecosystem function.Analysis of the El Chichón and Mount Pinatubo volcanic eruptions suggests that solar radiation management strategies using stratospheric sulfate aerosols would do little to counterbalance the effects of climate change on global crop yields., Author(s): Jonathan Proctor [sup.1] [sup.2] , Solomon Hsiang [sup.1] [sup.3] , Jennifer Burney [sup.4] , Marshall Burke [sup.3] [sup.5] , Wolfram Schlenker [sup.3] [sup.6] Author Affiliations:(1) Global Policy Laboratory, Goldman [...]