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Thought for food To have any hope of meeting the central goal of the Paris Agreement, which is to limit global warming to 2°C or less, our carbon emissions must be reduced considerably, including those coming from agriculture. Clark et al. show that even if fossil fuel emissions were eliminated immediately, emissions from the global food system alone would make it impossible to limit warming to 1.5°C and difficult even to realize the 2°C target. Thus, major changes in how food is produced are needed if we want to meet the goals of the Paris Agreement. Science , this issue p. 705

Air quality in the United States has dramatically improved, yet exposure to air pollution is still associated with 100000–200000 deaths annually. Reducing the number of deaths effectively, efficien...

Each year, millions of premature deaths worldwide are caused by exposure to outdoor air pollution, especially fine particulate matter (PM2.5). Designing policies to reduce these deaths relies on air quality modeling for estimating changes in PM2.5 concentrations from many scenarios at high spatial resolution. However, air quality modeling typically has substantial requirements for computation and expertise, which limits policy design, especially in countries where most PM2.5-related deaths occur. Lower requirement reduced-complexity models exist but are generally unavailable worldwide. Here, we adapt InMAP, a reduced-complexity model originally developed for the United States, to simulate annual-average primary and secondary PM2.5 concentrations across a global-through-urban spatial domain: “Global InMAP”. Global InMAP uses a variable resolution grid, with horizontal grid cell widths ranging from 500 km in remote locations to 4km in urban locations. We evaluate Global InMAP performance against both measurements and a state-of-the-science chemical transport model, GEOS-Chem. Against measurements, InMAP predicts total PM2.5 concentrations with a normalized mean error of 62%, compared to 41% for GEOS-Chem. For the emission scenarios considered, Global InMAP reproduced GEOS-Chem pollutant concentrations with a normalized mean bias of 59%–121%, which is sufficient for initial policy assessment and scoping. Global InMAP can be run on a desktop computer; simulations here took 2.6–8.4 hours. This work presents a global, open-source, reduced-complexity air quality model to facilitate policy assessment worldwide, providing a screening tool for reducing air pollution-related deaths where they occur most.

Agriculture is essential for feeding the large and growing world population, but it can also generate pollution that harms ecosystems and human health. Here, we explore the human health effects of air pollution caused by the production of maize—a key agricultural crop that is used for animal feed, ethanol biofuel and human consumption. We use county-level data on agricultural practices and productivity to develop a spatially explicit life-cycle-emissions inventory for maize. From this inventory, we estimate health damages, accounting for atmospheric pollution transport and chemistry, and human exposure to pollution at high spatial resolution. We show that reduced air quality resulting from maize production is associated with 4,300 premature deaths annually in the United States, with estimated damages in monetary terms of US$39 billion (range: US$14–64 billion). Increased concentrations of fine particulate matter (PM2.5) are driven by emissions of ammonia—a PM2.5 precursor—that result from nitrogen fertilizer use. Average health damages from reduced air quality are equivalent to US$121 t−1 of harvested maize grain, which is 62% of the US$195 t−1 decadal average maize grain market price. We also estimate life-cycle greenhouse gas emissions of maize production, finding total climate change damages of US$4.9 billion (range: US$1.5–7.5 billion), or US$15 t−1 of maize. Our results suggest potential benefits from strategic interventions in maize production, including changing the fertilizer type and application method, improving nitrogen use efficiency, switching to crops requiring less fertilizer, and geographically reallocating production. Agriculture sustains a large and growing human population, but generates widespread impacts. This study assesses the health effects of air pollution caused by maize production. Reduced air quality leads to 4,300 premature deaths annually in the United States, akin to US$39 billion in damages, and climate change damages of US$4.9 billion.

Significance Poor air quality is the largest environmental health risk in the United States and worldwide, and agriculture is a major source of air pollution. Nevertheless, air quality has been largely absent from discussions about the health and environmental impacts of food. We estimate the air quality–related health impacts of agriculture in the United States, finding that 80% of the 15,900 annual deaths that result from food-related fine particulate matter (PM2.5) pollution are attributable to animal-based foods. By estimating these impacts and exploring how to reduce them, this work fills a critical knowledge gap. Our results are relevant to food producers, processors, and distributors, and to policymakers and members of the public interested in minimizing the negative consequences of food., Agriculture is a major contributor to air pollution, the largest environmental risk factor for mortality in the United States and worldwide. It is largely unknown, however, how individual foods or entire diets affect human health via poor air quality. We show how food production negatively impacts human health by increasing atmospheric fine particulate matter (PM2.5), and we identify ways to reduce these negative impacts of agriculture. We quantify the air quality–related health damages attributable to 95 agricultural commodities and 67 final food products, which encompass >99% of agricultural production in the United States. Agricultural production in the United States results in 17,900 annual air quality–related deaths, 15,900 of which are from food production. Of those, 80% are attributable to animal-based foods, both directly from animal production and indirectly from growing animal feed. On-farm interventions can reduce PM2.5-related mortality by 50%, including improved livestock waste management and fertilizer application practices that reduce emissions of ammonia, a secondary PM2.5 precursor, and improved crop and animal production practices that reduce primary PM2.5 emissions from tillage, field burning, livestock dust, and machinery. Dietary shifts toward more plant-based foods that maintain protein intake and other nutritional needs could reduce agricultural air quality–related mortality by 68 to 83%. In sum, improved livestock and fertilization practices, and dietary shifts could greatly decrease the health impacts of agriculture caused by its contribution to reduced air quality.

Each year, millions of premature deaths worldwide are caused by exposure to outdoor air pollution, especially fine particulate matter (PM2.5). Designing policies to reduce deaths relies on air quality modeling for estimating changes in PM2.5 concentrations from many policy scenarios at high spatial resolution. However, air quality modeling typically has high requirements for computation and expertise, which limits policy design, especially in countries where most PM2.5-related deaths occur. Lower requirement reduced-complexity models exist but are generally unavailable worldwide. Here, we adapt InMAP, a reduced-complexity model originally developed for the United States, to simulate annual-average primary and secondary PM2.5 concentrations across a global-through-urban spatial domain: “Global InMAP”. Global InMAP uses a variable resolution grid, with 4 km horizontal grid cell widths in cities. We evaluate Global InMAP performance both against measurements and a state-of-the-science chemical transport model, GEOS-Chem. For the emission scenarios considered, Global InMAP reproduced GEOS-Chem pollutant concentrations with a normalized mean bias of 59%–121%. Global InMAP can be run on a desktop computer; simulations here took 2.6–4.4 hours. This work presents a global, open-source, reduced-complexity air quality model to facilitate air pollution policy assessment worldwide, providing a tool for reducing the deaths where they occur most.

Cropping system diversification can reduce the negative environmental impacts of agricultural production, including soil erosion and nutrient discharge. Less is known about how diversification affects energy use, climate change, and air quality, when considering farm operations and supply chain activities. We conducted a life cycle study using measurements from a nine-year Iowa field experiment to estimate fossil energy (FE) use, greenhouse gas (GHG) emissions, PM2.5-related emissions, human health impacts, and other agronomic and economic metrics of contrasting crop rotation systems and herbicide regimes. Rotation systems consisted of 2-year corn-soybean, 3-year corn-soybean-oat/clover, and 4-year corn-soybean-oat/alfalfa-alfalfa systems. Each was managed with conventional and low-herbicide treatments. FE consumption was 56% and 64% lower in the 3-year and 4-year rotations than in the 2-year rotation, and GHG emissions were 54% and 64% lower. Diversification reduced combined monetized damages from GHG and PM2.5-related emissions by 42% and 57%. Herbicide treatment had no significant impact on environmental outcomes, while corn and soybean yields and whole-rotation economic returns improved significantly under diversification. Results suggest that diversification via shifting from conventional corn-soybean rotations to longer rotations with small grain and forage crops substantially reduced FE use, GHG emissions, and air quality damages, without compromising economic or agronomic performance.

Switchgrass is a promising bioenergy feedstock, but industrial-scale production may lead to negative environmental effects. This study considers one such potential consequence: the life cycle monetized damages to human health from air pollution. We estimate increases in mortality from long-term exposure to fine particulate matter (PM2.5), which is emitted directly (“primary PM2.5”) and forms in the atmosphere (“secondary PM2.5”) from precursors of nitrogen oxides (NOx), sulfur oxides (SOx), ammonia (NH3), and volatile organic compounds (VOCs). Changes in atmospheric concentrations of PM2.5 (primary + secondary) from on-site production and supporting supply chain activities are considered at 2694 locations (counties in the Central and Eastern US), for two biomass yields (9 and 20 Mg ha−1), three nitrogen fertilizer rates (50, 100, and 150 kg ha−1), and two nitrogen fertilizer types (urea and urea ammonium nitrate). Results indicate that on-site processes dominate life-cycle emissions of NH3, NOx, primary PM2.5, and VOCs, whereas SOx is primarily emitted in upstream supply chain processes. Total air quality impacts of switchgrass production, which are dominated by NH3 emissions from fertilizer application, range widely depending on location, from 2 to 553 $ Mg−1 (mean: 45) of dry switchgrass at a biomass yield of 20 Mg ha−1 and fertilizer application of 100 kg ha−1 N applied as urea. Switching to urea ammonium nitrate solution lowers damages to 2 to 329 $ Mg−1 (mean: 28). This work points to human health damage from air pollution as a potentially large social cost from switchgrass production and suggests means of mitigating that impact via strategic geographical deployment and management. Furthermore, by distinguishing the origin of atmospheric emissions, this paper advances the current emerging literature on ecosystem services and disservices from agricultural and bioenergy systems.

Significance Racial–ethnic disparities in pollution exposure and in consumption of goods and services in the United States are well documented. Some may find it intuitive that, on average, black and Hispanic minorities bear a disproportionate burden from the air pollution caused mainly by non-Hispanic whites, but this effect has not previously been directly established, let alone quantified. Our “pollution inequity” metric is generalizable to other pollution types and provides a simple and intuitive way of expressing a disparity between the pollution that people cause and the pollution to which they are exposed. Our results are timely, given public debate on issues relating to race, equity, and the regulation of pollution., Fine particulate matter (PM2.5) air pollution exposure is the largest environmental health risk factor in the United States. Here, we link PM2.5 exposure to the human activities responsible for PM2.5 pollution. We use these results to explore “pollution inequity”: the difference between the environmental health damage caused by a racial–ethnic group and the damage that group experiences. We show that, in the United States, PM2.5 exposure is disproportionately caused by consumption of goods and services mainly by the non-Hispanic white majority, but disproportionately inhaled by black and Hispanic minorities. On average, non-Hispanic whites experience a “pollution advantage”: They experience ∼17% less air pollution exposure than is caused by their consumption. Blacks and Hispanics on average bear a “pollution burden” of 56% and 63% excess exposure, respectively, relative to the exposure caused by their consumption. The total disparity is caused as much by how much people consume as by how much pollution they breathe. Differences in the types of goods and services consumed by each group are less important. PM2.5 exposures declined ∼50% during 2002–2015 for all three racial–ethnic groups, but pollution inequity has remained high.