Exploring spatial variability in air quality-related health impacts of food production
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https://hdl.handle.net/11299/272863
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Exposure to ambient air pollution is the leading environmental risk to human health globally, with food and agriculture contributing to a fifth of air quality related deaths. Most of these deaths are attributable to fine particulate matter PM2.5 pollution from synthetic fertilizers, animal manure, tillage and other on-farm activities, largely related to the production of animal-based foods. However, while it is known that reducing PM2.5 related emissions from agriculture is essential for improving the sustainability of food, less is known about its local impacts on air quality, what products are driving them, and how to design spatially optimized interventions. This thesis aims to fill the gaps in understanding of spatial variability of damages from food products, focusing on informing where these damages occur and exploring animal-based product- and country- level variability globally. I do this by 1) exploring the spatial distribution of health damages from US agriculture in food production by pollutant, agricultural activity, commodity, and food product; 2) identifying hotspot regions in the US by food consumption, production, and experienced damages; and 3) expanding analysis to the global health impacts of livestock production and related animal-based protein sources. I find that, in the US, rural populations experience a high burden of food-related PM2.5 pollution driven by animal-based foods, such as pork and beef. I also find that the Midwest US both causes and experiences the most PM2.5 related damages from US agriculture, and substantially more than it contributes through its consumption. Globally, I find high country-level variability in the health damages caused by animal-based protein production; for example, for beef, the largest country death per protein rate is 3,300% greater than the smallest. Overall, by identifying the hotspot areas for product- and county- level production in the US and animal-based product- and country- level production globally, my findings suggest specific localized interventions for improving agriculture related air quality. Taken together, my work shows that spatially targeted mitigation strategies can reduce both total health impacts and disparities in local impacts as compared to generalized interventions.
提供机构:
Data Repository for the University of Minnesota (DRUM)
创建时间:
2025-08-26



