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Significance Rising temperatures because of increased emissions of long-lived greenhouse gases (LLGHGs) have had and will continue to have significant negative impacts on crop yields. However, other climate changes caused by short-lived climate pollutants (SLCPs) are also significant for agricultural productivity. The SLCPs black carbon and ozone impact temperature, precipitation, radiation, and—in the case of ozone—are directly toxic to plants. To our knowledge, this study provides the first integrated historical examination of the role of both SLCPs and LLGHGs on wheat and rice yields in India, and finds that the majority of losses are attributable to SLCPs. Agricultural cobenefits from SLCP mitigation are expected to be large, and because SLCPs have short atmospheric lifetimes, almost immediate. Recent research on the agricultural impacts of climate change has primarily focused on the roles of temperature and precipitation. These studies show that India has already been negatively affected by recent climate trends. However, anthropogenic climate changes are a result of both global emissions of long-lived greenhouse gases (LLGHGs) and other short-lived climate pollutants (SLCPs). Two potent SLCPs, tropospheric ozone and black carbon, have direct effects on crop yields beyond their indirect effects through climate; emissions of black carbon and ozone precursors have risen dramatically in India over the past three decades. Here, to our knowledge for the first time, we present results of the combined effects of climate change and the direct effects of SLCPs on wheat and rice yields in India from 1980 to 2010. Our statistical model suggests that, averaged over India, yields in 2010 were up to 36% lower for wheat than they otherwise would have been, absent climate and pollutant emissions trends, with some densely populated states experiencing 50% relative yield losses. [Our point estimates for rice (−20%) are similarly large, but not statistically significant.] Upper-bound estimates suggest that an overwhelming fraction (90%) of these losses is due to the direct effects of SLCPs. Gains from addressing regional air pollution could thus counter expected future yield losses resulting from direct climate change effects of LLGHGs.

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 PM 2.5 (particulate matter with diameter <2.5 μm) in recent years across the United States, and up to half in some Western regions, with spatial patterns in ambient smoke exposure that do not follow traditional socioeconomic pollution exposure gradients. We combine the model with stylized scenarios to show that fuel management interventions could have large health benefits and that future health impacts from climate-change–induced wildfire smoke could approach projected overall increases in temperature-related mortality from climate change—but that both estimates remain uncertain. We use model results to highlight important areas for future research and to draw lessons for policy.

Poor air quality is thought to be an important mortality risk factor globally 1 – 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 data 4 , 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 estimates 5 of exposure to ambient respirable particulate matter with an aerodynamic diameter less than 2.5 μm (PM 2.5 ) to estimate the impact of air quality on mortality rates among infants in Africa. We find that a 10 μg m −3 increase in PM 2.5 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 PM 2.5 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 countries 2 , 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 PM 2.5 exposures are predicted to have health benefits to infants that are larger than most known health interventions. A 10 μg m −3 increase in the concentration of ambient respirable particulate matter is associated with a 9% rise in infant mortality in Africa and this increase is not affected by household wealth.

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 might thus 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.

Historically, human uses of land have transformed and fragmented ecosystems 1 , 2 , degraded biodiversity 3 , 4 , disrupted carbon and nitrogen cycles 5 , 6 and added prodigious quantities of greenhouse gases (GHGs) to the atmosphere 7 , 8 . However, in contrast to fossil-fuel carbon dioxide (CO 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 2 -equivalent until 2001. After 2001, driven by rising emissions per land area, emissions increased by 2.4 gigatonnes CO 2 -equivalent per decade to 14.6 gigatonnes CO 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 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.

As efforts to mitigate climate change increase, there is a need to identify cost-effective ways to avoid emissions of greenhouse gases (GHGs). Agriculture is rightly recognized as a source of considerable emissions, with concomitant opportunities for mitigation. Although future agricultural productivity is critical, as it will shape emissions from conversion of native landscapes to food and biofuel crops, investment in agricultural research is rarely mentioned as a mitigation strategy. Here we estimate the net effect on GHG emissions of historical agricultural intensification between 1961 and 2005. We find that while emissions from factors such as fertilizer production and application have increased, the net effect of higher yields has avoided emissions of up to 161 gigatons of carbon (GtC) (590 GtCO₂e) since 1961. We estimate that each dollar invested in agricultural yields has resulted in 68 fewer kgC (249 kgCO₂e) emissions relative to 1961 technology ($14.74/tC, or ˷$4/tCO₂e), avoiding 3.6 GtC (13.1 GtCO₂e) per year. Our analysis indicates that investment in yield improvements compares favorably with other commonly proposed mitigation strategies. Further yield improvements should therefore be prominent among efforts to reduce future GHG emissions.

Crop productivity is potentially affected by several air pollutants, although these are usually studied in isolation. A significant challenge to understanding the effects of multiple pollutants in many regions is the dearth of air quality data near agricultural fields. Here we empirically estimate the effect of four key pollutants (ozone (O 3 ), particulate matter (PM), sulfur dioxide (SO 2 ), and nitrogen dioxide (NO 2 )) on maize and soybean yields in the United States using a combination of administrative data and satellite-derived yield estimates. We identify clear negative effects of exposure to O 3 , PM, and SO 2 in both crops, using yields measured in the vicinity of monitoring stations. We also show that while stations measuring NO 2 are too sparse to reliably estimate a yield effect, the strong gradient of NO 2 concentrations near power plants allows us to more precisely estimate NO 2 effects using satellite measured yield gradients. The presence of some powerplants that turn on and others that shut down during the study period are particularly useful for attributing yield gradients to pollution. We estimate that total yield losses from these pollutants averaged roughly 5% for both maize and soybean over the past two decades. While all four pollutants have statistically significant effects, PM and NO 2 appear more damaging to crops at current levels than O 3 and SO 2 . Finally, we find that the significant improvement in air quality since 1999 has halved the impact of poor air quality on major crops and contributed to yield increases that represent roughly 20% of overall yield gains over that period.

Distributed irrigation systems are those in which the water access (via pump or human power), distribution (via furrow, watering can, sprinkler, drip lines, etc.), and use all occur at or near the same location. Distributed systems are typically privately owned and managed by individuals or groups, in contrast to centralized irrigation systems, which tend to be publicly operated and involve large water extractions and distribution over significant distances for use by scores of farmers. Here we draw on a growing body of evidence on smallholder farmers, distributed irrigation systems, and land and water resource availability across sub-Saharan Africa (SSA) to show how investments in distributed smallholder irrigation technologies might be used to (i) use the water sources of SSA more productively, (ii) improve nutritional outcomes and rural development throughout SSA, and (iii) narrow the income disparities that permit widespread hunger to persist despite aggregate economic advancement.

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

Pollution from wildfires constitutes a growing source of poor air quality globally. To protect health, governments largely rely on citizens to limit their own wildfire smoke exposures, but the effectiveness of this strategy is hard to observe. Using data from private pollution sensors, cell phones, social media posts and internet search activity, we find that during large wildfire smoke events, individuals in wealthy locations increasingly search for information about air quality and health protection, stay at home more and are unhappier. Residents of lower-income neighbourhoods exhibit similar patterns in searches for air quality information but not for health protection, spend less time at home and have more muted sentiment responses. During smoke events, indoor particulate matter (PM2.5) concentrations often remain 3–4× above health-based guidelines and vary by 20× between neighbouring households. Our results suggest that policy reliance on self-protection to mitigate smoke health risks will have modest and unequal benefits.Burke et al. show that smoke exposure is associated with behavioural changes and worsening sentiment, with important differences by income. They document substantial infiltration of smoke into homes, suggesting that current policy reliance on self-protection could be ineffective.