The weekly cycle of photosynthesis in Europe reveals the negative impact of particulate pollution on ecosystem productivity.

Aerosols can affect photosynthesis through radiative perturbations such as scattering and absorbing solar radiation. This biophysical impact has been widely studied using field measurements, but the sign and magnitude at continental scales remain uncertain. Solar-induced fluorescence (SIF), emitted by chlorophyll, strongly correlates with photosynthesis. With recent advancements in Earth observation satellites, we leverage SIF observations from the Tropospheric Monitoring Instrument (TROPOMI) with unprecedented spatial resolution and near-daily global coverage, to investigate the impact of aerosols on photosynthesis. Our analysis reveals that on weekends when there is more plant-available sunlight due to less particulate pollution, 64% of regions across Europe show increased SIF, indicating more photosynthesis. Moreover, we find a widespread negative relationship between SIF and aerosol loading across Europe. This suggests the possible reduction in photosynthesis as aerosol levels increase, particularly in ecosystems limited by light availability. By considering two plausible scenarios of improved air quality-reducing aerosol levels to the weekly minimum 3-d values and levels observed during the COVID-19 period-we estimate a potential of 41 to 50 Mt net additional annual CO2 uptake by terrestrial ecosystems in Europe. This work assesses human impacts on photosynthesis via aerosol pollution at continental scales using satellite observations. Our results highlight i) the use of spatiotemporal variations in satellite SIF to estimate the human impacts on photosynthesis and ii) the potential of reducing particulate pollution to enhance ecosystem productivity.

Multicriteria Suitability Index for Prioritizing Early-Stage Deployments of Wastewater-Derived Fertilizers in Sub-Saharan Africa.

Recycling nutrients from wastewater could simultaneously decrease the carbon intensity of traditional ammonia supply chains and increase the accessibility of local fertilizer. Despite the theoretical potential, techno-economic viability of wastewater nutrient recovery in sub-Saharan Africa has been poorly characterized at subnational scales. This work proposes a multicriteria suitability index to describe techno-economic viability of wastewater-derived fertilizer technologies with district-scale resolution. This index, with a range from 0 to 1 (highest suitability), incorporates key drivers, including population density, soil conditions, sanitation levels, and fertilizer prices. We found that suitability varies widely within and across countries in sub-Saharan Africa and that the primary limiting factor is the absence of sanitation infrastructure. Regions with a minimum of 10% cropland area and a suitability index of at least 0.9 were identified as highly suitable target regions for initial deployment. While they comprise only 1% of the analyzed area, these regions are home to 39 million people and contain up to 3.7 million hectares of cropland. Wastewater-derived fertilizer technologies could deliver an average of 25 kg of nitrogen per hectare of cropland, generating additional food equivalent to the annual consumption of 6 million people. Screening for high suitability can inform selection of effective lighthouse demonstration sites that derisk technology deployment and promote the transition to a more circular nutrient economy.

Warming temperatures exacerbate groundwater depletion rates in India.

Climate change will likely increase crop water demand, and farmers may adapt by applying more irrigation. Understanding the extent to which this is occurring is of particular importance in India, a global groundwater depletion hotspot, where increased withdrawals may further jeopardize groundwater resources. Using historical data on groundwater levels, climate, and crop water stress, we find that farmers have adapted to warming temperatures by intensifying groundwater withdrawals, substantially accelerating groundwater depletion rates in India. When considering increased withdrawals due to warming, we project that the rates of net groundwater loss for 2041-2080 could be three times current depletion rates, even after considering projected increases in precipitation and possible decreases in irrigation use as groundwater tables fall. These results reveal a previously unquantified cost of adapting to warming temperatures that will likely further threaten India's food and water security over the coming decades.

Sustainable irrigation and climate feedbacks.

Agricultural irrigation induces greenhouse gas emissions directly from soils or indirectly through the use of energy or construction of dams and irrigation infrastructure, while climate change affects irrigation demand, water availability and the greenhouse gas intensity of irrigation energy. Here, we present a scoping review to elaborate on these irrigation-climate linkages by synthesizing knowledge across different fields, emphasizing the growing role climate change may have in driving future irrigation expansion and reinforcing some of the positive feedbacks. This Review underscores the urgent need to promote and adopt sustainable irrigation, especially in regions dominated by strong, positive feedbacks.

Soil micronutrients linked to human health in India.

Trace soil minerals are a critical determinant of both crop productivity and the mineral concentration of crops, therefore potentially impacting the nutritional status of human populations relying on those crops. We link health data from nearly 0.3 million children and one million adult women across India with over 27 million soil tests drawn from a nationwide soil health program. We find that soil zinc availability is positively associated with children's linear height growth, and soil iron availability is positively associated with hemoglobin levels. The link between soil zinc and childhood stunting is particularly robust-a one standard deviation increase in satisfactory soil zinc tests is associated with approximately 11 fewer children stunted per 1000. We also find that this zinc-stunting relationship is strongest in wealthier households. Our results suggest that soil mineral availability impacts human nutritional status and health in at least some areas of India, and that agronomic fortification may be a beneficial intervention.

Recent cover crop adoption is associated with small maize and soybean yield losses in the United States.

Cover crops are gaining traction in many agricultural regions, partly driven by increased public subsidies and by private markets for ecosystem services. These payments are motivated by environmental benefits, including improved soil health, reduced erosion, and increased soil organic carbon. However, previous work based on experimental plots or crop modeling indicates cover crops may reduce crop yields. It remains unclear, though, how recent cover crop adoption has affected productivity in commercial agricultural systems. Here we perform the first large-scale, field-level analysis of observed yield impacts from cover cropping as implemented across the US Corn Belt. We use validated satellite data products at sub-field scales to analyze maize and soybean yield outcomes for over 90,000 fields in 2019-2020. Because we lack data on cover crop species or timing, we seek to quantify the yield impacts of cover cropping as currently practiced in aggregate. Using causal forests analysis, we estimate an average maize yield loss of 5.5% on fields where cover crops were used for 3 or more years, compared with fields that did not adopt cover cropping. Maize yield losses were larger on fields with better soil ratings, cooler mid-season temperatures, and lower spring rainfall. For soybeans, average yield losses were 3.5%, with larger impacts on fields with warmer June temperatures, lower spring and late-season rainfall, and, to a lesser extent, better soils. Estimated impacts are consistent with multiple mechanisms indicated by experimental and simulation-based studies, including the effects of cover crops on nitrogen dynamics, water consumption, and soil oxygen depletion. Our results suggest a need to improve cover crop management to reduce yield penalties, and a potential need to target subsidies based on likely yield impacts. Ultimately, avoiding substantial yield penalties is important for realizing widespread adoption and associated benefits for water quality, erosion, soil carbon, and greenhouse gas emissions.

Globally ubiquitous negative effects of nitrogen dioxide on crop growth.

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.

Prior crop season management constrains farmer adaptation to warming temperatures: Evidence from the Indo-Gangetic Plains.

Climate change induced heat stress is predicted to negatively impact wheat yields across the Indo-Gangetic Plains (IGP) of India. Research suggests that early sowing of wheat can substantially reduce this impact. However, a large proportion of farmers sow wheat late across this region, likely resulting in large-scale yield loss. We examined the extent of late wheat sowing across the IGP and which perceptional, management, biophysical, and socio-economic factors are associated with delayed sowing using household survey data from 2429 farmers and the cumulative logit model. Our results indicate that despite understanding that early sowing can be helpful to avoid terminal heat stress, over 50% of farmers sow wheat later than their perceived ideal wheat sowing date. We find that variables related to how wheat fields are prepared prior to sowing are associated with wheat sowing date. Specifically, farmers who had shorter fallow periods prior to sowing wheat and those who used zero tillage were 95% and 65% more likely to sow wheat earlier, respectively. In addition, we found that how farmers managed their rice crop in the preceding cropping season impacted wheat sowing date - farmers who transplanted and harvested rice later and/or planted longer duration rice varieties sowed their wheat later. Our results suggest that policies that promote earlier sowing of rice, such as improved access to irrigation and direct seeding machinery, and reduced field preparation time, such as wider adoption of zero tillage technologies, can help farmers across the IGP sow wheat earlier. This is critical given that warming temperatures will only increase the negative impacts of terminal heat stress on wheat yields across this region over the coming decades.

Scalable deep learning to identify brick kilns and aid regulatory capacity.

Improving compliance with environmental regulations is critical for promoting clean environments and healthy populations. In South Asia, brick manufacturing is a major source of pollution but is dominated by small-scale, informal producers who are difficult to monitor and regulate-a common challenge in low-income settings. We demonstrate a low-cost, scalable approach for locating brick kilns in high-resolution satellite imagery from Bangladesh. Our approach identifies kilns with 94.2% accuracy and 88.7% precision and extracts the precise GPS coordinates of every brick kiln across Bangladesh. Using these estimates, we show that at least 12% of the population of Bangladesh (>18 million people) live within 1 km of a kiln and that 77% and 9% of kilns are (illegally) within 1 km of schools and health facilities, respectively. Finally, we show how kilns contribute up to 20.4 µg/[Formula: see text] of [Formula: see text] (particulate matter of a diameter less than 2.5 µm) in Dhaka when the wind blows from an unfavorable direction. We document inaccuracies and potential bias with respect to local regulations in the government data. Our approach demonstrates how machine learning and Earth observation can be combined to better understand the extent and implications of regulatory compliance in informal industry.

Using satellite imagery to understand and promote sustainable development.

Accurate and comprehensive measurements of a range of sustainable development outcomes are fundamental inputs into both research and policy. We synthesize the growing literature that uses satellite imagery to understand these outcomes, with a focus on approaches that combine imagery with machine learning. We quantify the paucity of ground data on key human-related outcomes and the growing abundance and improving resolution (spatial, temporal, and spectral) of satellite imagery. We then review recent machine learning approaches to model-building in the context of scarce and noisy training data, highlighting how this noise often leads to incorrect assessment of model performance. We quantify recent model performance across multiple sustainable development domains, discuss research and policy applications, explore constraints to future progress, and highlight research directions for the field.

Mapping twenty years of corn and soybean across the US Midwest using the Landsat archive.

Field-level monitoring of crop types in the United States via the Cropland Data Layer (CDL) has played an important role in improving production forecasts and enabling large-scale study of agricultural inputs and outcomes. Although CDL offers crop type maps across the conterminous US from 2008 onward, such maps are missing in many Midwestern states or are uneven in quality before 2008. To fill these data gaps, we used the now-public Landsat archive and cloud computing services to map corn and soybean at 30 m resolution across the US Midwest from 1999-2018. Our training data were CDL from 2008-2018, and we validated the predictions on CDL 1999-2007 where available, county-level crop acreage statistics, and state-level crop rotation statistics. The corn-soybean maps, which we call the Corn-Soy Data Layer (CSDL), are publicly hosted on Google Earth Engine and also available for download online.

Using publicly available satellite imagery and deep learning to understand economic well-being in Africa.

Accurate and comprehensive measurements of economic well-being are fundamental inputs into both research and policy, but such measures are unavailable at a local level in many parts of the world. Here we train deep learning models to predict survey-based estimates of asset wealth across ~ 20,000 African villages from publicly-available multispectral satellite imagery. Models can explain 70% of the variation in ground-measured village wealth in countries where the model was not trained, outperforming previous benchmarks from high-resolution imagery, and comparison with independent wealth measurements from censuses suggests that errors in satellite estimates are comparable to errors in existing ground data. Satellite-based estimates can also explain up to 50% of the variation in district-aggregated changes in wealth over time, with daytime imagery particularly useful in this task. We demonstrate the utility of satellite-based estimates for research and policy, and demonstrate their scalability by creating a wealth map for Africa's most populous country.

On the role of anthropogenic climate change in the emerging food crisis in southern Africa in the 2019-2020 growing season.

Anthropogenic climate change likely influences the beginning of 2020 growing season's water deficit in parts of southern Africa, with severe consequences to food security.

Changes in the drought sensitivity of US maize yields.

As climate change leads to increased frequency and severity of drought in many agricultural regions, a prominent adaptation goal is to reduce the drought sensitivity of crop yields. Yet many of the sources of average yield gains are more effective in good weather, leading to heightened drought sensitivity. Here we consider two empirical strategies for detecting changes in drought sensitivity and apply them to maize in the United States, a crop that has experienced myriad management changes including recent adoption of drought-tolerant varieties. We show that a strategy that utilizes weather-driven temporal variations in drought exposure is inconclusive because of the infrequent occurrence of substantial drought. In contrast, a strategy that exploits within-county spatial variability in drought exposure, driven primarily by differences in soil water storage capacity, reveals robust trends over time. Yield sensitivity to soil water storage increased by 55% on average across the US Corn Belt since 1999, with larger increases in drier states. Although yields have been increasing under all conditions, the cost of drought relative to good weather has also risen. These results highlight the difficulty of simultaneously raising average yields and lowering drought sensitivity.

The role of irrigation in changing wheat yields and heat sensitivity in India.

Irrigation has been pivotal in wheat's rise as a major crop in India and is likely to be increasingly important as an adaptation response to climate change. Here we use historical data across 40 years to quantify the contribution of irrigation to wheat yield increases and the extent to which irrigation reduces sensitivity to heat. We estimate that national yields in the 2000s are 13% higher than they would have been without irrigation trends since 1970. Moreover, irrigated wheat exhibits roughly one-quarter of the heat sensitivity estimated for fully rainfed conditions. However, yield gains from irrigation expansion have slowed in recent years and negative impacts of warming have continued to accrue despite lower heat sensitivity from the widespread expansion of irrigation. We conclude that as constraints on expanding irrigation become more binding, furthering yield gains in the face of additional warming is likely to present an increasingly difficult challenge.

Water Use Efficiency as a Constraint and Target for Improving the Resilience and Productivity of C3 and C4 Crops.

The ratio of plant carbon gain to water use, known as water use efficiency (WUE), has long been recognized as a key constraint on crop production and an important target for crop improvement. WUE is a physiologically and genetically complex trait that can be defined at a range of scales. Many component traits directly influence WUE, including photosynthesis, stomatal and mesophyll conductances, and canopy structure. Interactions of carbon and water relations with diverse aspects of the environment and crop development also modulate WUE. As a consequence, enhancing WUE by breeding or biotechnology has proven challenging but not impossible. This review aims to synthesize new knowledge of WUE arising from advances in phenotyping, modeling, physiology, genetics, and molecular biology in the context of classical theoretical principles. In addition, we discuss how rising atmospheric CO2 concentration has created and will continue to create opportunities for enhancing WUE by modifying the trade-off between photosynthesis and transpiration.

Strengthened scientific support for the Endangerment Finding for atmospheric greenhouse gases.

We assess scientific evidence that has emerged since the U.S. Environmental Protection Agency's 2009 Endangerment Finding for six well-mixed greenhouse gases and find that this new evidence lends increased support to the conclusion that these gases pose a danger to public health and welfare. Newly available evidence about a wide range of observed and projected impacts strengthens the association between the risk of some of these impacts and anthropogenic climate change, indicates that some impacts or combinations of impacts have the potential to be more severe than previously understood, and identifies substantial risk of additional impacts through processes and pathways not considered in the Endangerment Finding.

Anticipated burden and mitigation of carbon-dioxide-induced nutritional deficiencies and related diseases: A simulation modeling study.

BACKGROUND: Rising atmospheric carbon dioxide concentrations are anticipated to decrease the zinc and iron concentrations of crops. The associated disease burden and optimal mitigation strategies remain unknown. We sought to understand where and to what extent increasing carbon dioxide concentrations may increase the global burden of nutritional deficiencies through changes in crop nutrient concentrations, and the effects of potential mitigation strategies. METHODS AND FINDINGS: For each of 137 countries, we incorporated estimates of climate change, crop nutrient concentrations, dietary patterns, and disease risk into a microsimulation model of zinc and iron deficiency. These estimates were obtained from the Intergovernmental Panel on Climate Change, US Department of Agriculture, Statistics Division of the Food and Agriculture Organization of the United Nations, and Global Burden of Disease Project, respectively. In the absence of increasing carbon dioxide concentrations, we estimated that zinc and iron deficiencies would induce 1,072.9 million disability-adjusted life years (DALYs) globally over the period 2015 to 2050 (95% credible interval [CrI]: 971.1-1,167.7). In the presence of increasing carbon dioxide concentrations, we estimated that decreasing zinc and iron concentrations of crops would induce an additional 125.8 million DALYs globally over the same period (95% CrI: 113.6-138.9). This carbon-dioxide-induced disease burden is projected to disproportionately affect nations in the World Health Organization's South-East Asia and African Regions (44.0 and 28.5 million DALYs, respectively), which already have high existing disease burdens from zinc and iron deficiencies (364.3 and 299.5 million DALYs, respectively), increasing global nutritional inequalities. A climate mitigation strategy such as the Paris Agreement (an international agreement to keep global temperatures within 2°C of pre-industrial levels) would be expected to avert 48.2% of this burden (95% CrI: 47.8%-48.5%), while traditional public health interventions including nutrient supplementation and disease control programs would be expected to avert 26.6% of the burden (95% CrI: 23.8%-29.6%). Of the traditional public health interventions, zinc supplementation would be expected to avert 5.5%, iron supplementation 15.7%, malaria mitigation 3.2%, pneumonia mitigation 1.6%, and diarrhea mitigation 0.5%. The primary limitations of the analysis include uncertainty regarding how food consumption patterns may change with climate, how disease mortality rates will change over time, and how crop zinc and iron concentrations will decline from those at present to those in 2050. CONCLUSIONS: Effects of increased carbon dioxide on crop nutrient concentrations are anticipated to exacerbate inequalities in zinc and iron deficiencies by 2050. Proposed Paris Agreement strategies are expected to be more effective than traditional public health measures to avert the increased inequality.

The important but weakening maize yield benefit of grain filling prolongation in the US Midwest.

A better understanding of recent crop yield trends is necessary for improving the yield and maintaining food security. Several possible mechanisms have been investigated recently in order to explain the steady growth in maize yield over the US Corn-Belt, but a substantial fraction of the increasing trend remains elusive. In this study, trends in grain filling period (GFP) were identified and their relations with maize yield increase were further analyzed. Using satellite data from 2000 to 2015, an average lengthening of GFP of 0.37 days per year was found over the region, which probably results from variety renewal. Statistical analysis suggests that longer GFP accounted for roughly one-quarter (23%) of the yield increase trend by promoting kernel dry matter accumulation, yet had less yield benefit in hotter counties. Both official survey data and crop model simulations estimated a similar contribution of GFP trend to yield. If growing degree days that determines the GFP continues to prolong at the current rate for the next 50 years, yield reduction will be lessened with 25% and 18% longer GFP under Representative Concentration Pathway 2.6 (RCP 2.6) and RCP 6.0, respectively. However, this level of progress is insufficient to offset yield losses in future climates, because drought and heat stress during the GFP will become more prevalent and severe. This study highlights the need to devise multiple effective adaptation strategies to withstand the upcoming challenges in food security.

Increasing drought and diminishing benefits of elevated carbon dioxide for soybean yields across the US Midwest.

Elevated atmospheric CO2 concentrations ([CO2 ]) are expected to increase C3 crop yield through the CO2 fertilization effect (CFE) by stimulating photosynthesis and by reducing stomatal conductance and transpiration. The latter effect is widely believed to lead to greater benefits in dry rather than wet conditions, although some recent experimental evidence challenges this view. Here we used a process-based crop model, the Agricultural Production Systems sIMulator (APSIM), to quantify the contemporary and future CFE on soybean in one of its primary production area of the US Midwest. APSIM accurately reproduced experimental data from the Soybean Free-Air CO2 Enrichment site showing that the CFE declined with increasing drought stress. This resulted from greater radiation use efficiency (RUE) and above-ground biomass production at elevated [CO2 ] that outpaced gains in transpiration efficiency (TE). Using an ensemble of eight climate model projections, we found that drought frequency in the US Midwest is projected to increase from once every 5 years currently to once every other year by 2050. In addition to directly driving yield loss, greater drought also significantly limited the benefit from rising [CO2 ]. This study provides a link between localized experiments and regional-scale modeling to highlight that increased drought frequency and severity pose a formidable challenge to maintaining soybean yield progress that is not offset by rising [CO2 ] as previously anticipated. Evaluating the relative sensitivity of RUE and TE to elevated [CO2 ] will be an important target for future modeling and experimental studies of climate change impacts and adaptation in C3 crops.