In response to climate change, water scarcity, and pollution, urban and rural environmental justice (EJ) community members are gardening and conserving water via rainwater harvesting systems. Communities adopting these environmental health preventions/interventions have concerns and asked, “What is the quality of my harvested rainwater?”. In reply, The University of Arizona in partnership with Sonora Environmental Research Institute, Inc., designed Project Harvest (PH), a bilingual (English and Spanish) co-created community science (CS) project focused on evaluating (i) potential microbial, metal(loid) and organic pollutants in roof-harvested rainwater (RHRW), soil, and plants irrigated with RHRW, (ii) learning outcomes, and (iii) social action (Ramírez-Andreotta et al., 2019). PH has generated 5 years (2016–2021) of learning research and 2.5 years (2017–2020) of environmental quality data and through a community-first reporting model and extensive engagement, continues to champion placed-based topics and local experts, address community questions, inform participant decision-making, improve environmental health literacy (EHL), and link research to action in Arizona. We trained 198 individuals and ~150 community scientists were retained. They engaged in up to 21 monitoring, community gatherings, and data sharing events. The program: (1) supported/trained/mentored 4 PhD, 10 Master, and 17 undergraduate students and (2) hired/trained/provided professional development (2016-2021) for 7 community health workers.

Using a mix-methods approach, we have proven how pollution and learning become visible through sense-making. Community scientists: (1) set the research agenda and framed the data to meet their needs/expectations, (2) built knowledge and refined their mental models of environmental/pollution science based on their lived experience, and (3) constructed their own explanations through collaborative discourse. With the EHL framework, we have demonstrated the outcomes of community-driven science, which includes relationship building, growing a stronger connection to science, evidence-based decision making, and working towards community change by taking action to protect individual and community health (Ramírez-Andreotta et al., in review). In Davis et al. (2020), we observed a lack of association between participant self-efficacy and race, income, or education level, respectively; however specific types of motivation, participation support, and barriers to participation were found to be more relevant among participants of certain demographic groups or communities, compared to others. Recommendations for engaging diverse community scientists are to: (a) Consider existing relationships and community-identified problems as participant motivation, (b) Design participant methods to include personal support structures and relationship-building, and, (c) Design for participant time and technology access as significant limitations to participation. In Moses et al. (2022), we demonstrated that race/ethnicity and community were significantly associated (p < 0.05) with participant responses regarding proximity to potential sources of pollution, roof material, RHRW device material, capacity, and age, garden amendments, supplemental irrigation, and previous contaminant testing. This study illuminated the idiosyncratic differences in how underserved communities perceive environmental pollution and historical past land uses. Highlighted in Davis and Ramírez-Andreotta (2021), participatory research with EJ communities may be more likely to result in structural change when (a) community members hold formal leadership roles; (b) project design includes decision-makers and policy goals; and (c) long term partnerships are sustained. Future efforts need to include structural change as a goal, employing participatory assessment of community benefit, and increased hiring of faculty of color at research institutions.

Concomitantly, this work generated one of the largest RHRW quality datasets. Across four EJ communities, community scientists collected between 570-590 unique RHRW samples and over 100 soil and/or garden plants samples irrigated with harvested rainwater samples for metal(loid) and/or microbial analyses. RHRW were analyzed for 25 contaminants: Metal(loid)s (aluminum, arsenic, barium, beryllium, cadmium, chromium, copper, manganese, nickel, lead, and zinc), industrial compounds (nonylphenol, perfluorooctanoic acid, perfluorooctane sulfonic acid, perfluorobutane sulfonic acid, and perfluorononanoic acid), pesticides (atrazine, pentachlorophenol, chlorpyrifos, 2,4-dichlorophenoxyacetic acid, prometon, simazine, carbaryl), and microorganisms (total coliforms, E. coli). Based on contaminant concentrations and domestic activities, intended uses should be carefully considered. We highlight that rainwater is not “pure” and has been impacted by industry and/or anthropogenic activity. Yearly, data was reported back to participants in English and Spanish via gatherings, printed booklets, art installations, and interactive website (Kaufmann et al., 2021; PH, n.d.). We advocate for sustained monitoring and efforts dedicated to engagement, especially in EJ communities. The CS research design and extensive data sharing process in PH has proven that community scientists are successfully interpreting their environmental monitoring data, considering how to use their RHRW based on contaminant concentrations, descriptions, regulatory standards, and/or health advisories, and taking action to protect their environmental health. Eight publications have stemmed from this funding and an additional 10 manuscripts are in review or preparation. Co-created CS is a transformative model that fosters free choice learning and meaningful engagement with communities at risk and can be implemented with communities to prepare for compound events and the public health risks posed by the confluence of climate change, environmental pollution, and social injustices.

Last Modified: 10/19/2022
Modified by: Monica D Ramirez-Andreotta