Data Science for Environmental Justice: Community-Based Rainwater Harvesting and Environmental Monitoring in Arizona

Abstract

As climate change exacerbates water stress already experienced by 2.3 billion people worldwide, rainwater harvesting for household gardening becomes an increasingly common practice. However, the quality of harvested rainwater is not well studied, and the human health risks associated with its use are unknown. There is currently no United States federal standard to assess harvested rainwater. This thesis discusses Project Harvest, a co-created community science project studying the quality of harvested rainwater, primarily used for garden irrigation, in four environmental justice communities in Arizona, USA. Participants collected 577 rooftop harvested rainwater samples from 2017-2020, where arsenic (As) concentrations ranged from 0.108 to 120 ug L-1 and lead (Pb) concentrations ranged from 0.013 to 350 ug L-1 with the highest concentrations in the community of Hayden/Winkelman > Tucson > Globe/Miami > Dewey-Humboldt. Rooftop harvested rainwater data were analyzed with linear mixed models showing summer concentrations of As and Pb were significantly higher than winter; and, contamination was significantly higher closer extractive industry sites in three of the four study communities (ASARCO Copper Smelter in Hayden/Winkelman, Davis-Monthan United States Air Force Base in Tucson, and Freeport McMoRan Copper and Gold Mine in Globe/Miami). Additionally, rainwater harvesting infrastructure such as roof material, presence of cistern screen, and cistern first flush were not significant when controlling for relevant spatiotemporal variables. These results indicate that As and Pb concentrations vary seasonally and by proximity to industrial activity, not by individual decision making about homes. In general, individuals are not responsible for environmental contamination, rather governments, corporations, and other external powers are responsible. Future work will integrate harvested rainwater, residential soil, and garden plant data to better understand sociobiophysical drivers of environmental change. Further research should explicitly address the role of industry and racial capitalism in environmental injustice and integrate transdisciplinary datasets to address community-driven questions.