Drinking water contamination crises are more common in the United States than many people think. Water pollution worries in America are the highest they’ve been since 2001. Yet, they rise only to national attention when there is a particularly egregious failure, such as the one in Flint, Michigan or Washington D.C. fifteen years earlier. Among the most unsettling features of the Flint case is the fact that it almost certainly would have gone completely unnoticed were it not for the persistence of the local public outcry. The local effects of contaminated drinking water were summarily ignored or explained away by state regulators as the fussy aesthetic complaints of a population that was “anti-everything.” Reflection on these cases indicates a wide gap between local knowledge of environmental hazards and those charged with monitoring and enacting environmental regulation that could be improved by massively expanding the role of citizen data collection.
In a world where environmental regulation is itself increasingly politicized, a potentially powerful force for better public health protection from water contamination would be to expand local data collection and sharing by private citizens. There are two reasons for this. First, there are significant gaps in water contamination data at the local level that could be closed by expanding public data collection and sharing. The nature of city mandated lead testing can disproportionately collect data where risk is low. Selection bias in the testing might not reflect the high risk level for subpopulations in the city, and water main replacement can elevate lead levels sporadically. For example, though Chicago has the most lead service lines in the US, it still passes federal drinking water standards. But recent concentrated testing in high risk areas, and a response to report on misleading test results, revealed a wide spiking ranges of lead concentrations in the city. Minimally, this amounts to a confusing risk profile for citizens.
In other cities, the agencies responsible for doing this collection and reporting have shown themselves to be unreliable. During the DC lead crisis in 2001, the city utility’s testing and a follow-up report by the Centers for Disease Control and Prevention were both heavily criticized for intentionally misleading the public about the risks. Multiple officials from Michigan’s Department of Environmental Quality and Department of Health and Human Services have been criminally charged for intentionally misleading the public. Even if citizen data is not as scientifically rigorous, its presence make cover-ups more difficult because it contributes to the gaps in data and sounds the alarm for potential exposure.
Second, the gaps in public knowledge about drinking water safety tend to reflect relative political disempowerment, rather than suggesting a community is safe and doesn’t require more extensive monitoring. While a city on average might not have a problem with heavy metals in the soil or drinking water, some neighborhoods may be far more vulnerable than others. In a National CDC report, for example, lead poisoning in African-American children occurred at least twice more often than other groups tested.
When environmental risk is linked to decaying infrastructure, housing, and proximity to polluters, they are much more likely to be linked to race and poverty as well. Low income and people of color are disproportionately more likely to suffer from health disparities due to unequal hazardous exposure. More citizen sourced data collection serves the dual purpose of educating people at the local level about their specific risks, which can be obscured by the way problems are averaged over populations.
Existing small-scale experiments in mobilizing low-income communities to collect qualitative and quantitative data are evidence that this data can be put to good use at the local level. For example, Communities for a Better Environment (CBE) in Los Angeles organizes low-income communities of color by conducting bucket air sampling, affordable and accurate sampling technique used to monitor toxins in the air. Data collection encourages community understanding of their particular respiratory health concerns that put children in the neighborhood at risk. In Chicago’s Pilsen neighborhood, members of Pilsen’s Environmental Rights and Reform Organization (PERRO) mobilized residents to test their own soil for lead when officials ignored complaints. Such projects create a natural avenue of social mobilization by the people who are most directly affected. This can spur government action. In PERRO’s case, their data collection triggered EPA data collection, which eventually solidified the lawsuit that named H Kramer Brass factory responsible for remediating the toxic soil on designated properties. In Flint, local citizens’ qualitative and private water testing commanded the attention of university researchers and federal regulators to the omissions in state-level data collection.
Citizen data collection is not an alternative to professional science or government regulation. It is a tool for educating affected populations and providing an opportunity to build a network of millions of data collection points in a much broader array of places than we currently have. Smart phones can be powerful tools here, providing the capacity to use geolocation, images, reporting of private testing, and public sharing at the moment. They may someday be able to do some of the testing and data collection themselves.
This sort of future is not wishful thinking. In Beijing, Ma Jun, China’s leading environmentalist, founded the Institute of Public and Environmental Affairs (IPE) a nonprofit that publishes a free pollution mapping tool that enables the public to view pollution levels across 300 cities and 11 river basins. Though factory censors provide quantitative data for the system, IPE’s phone app allows Chinese citizens to post pictures and view violation reports for the first time in history.
The program has exposed over 90,000 air and water violations by local and multinational companies operating in China, and encourages Chinese consumers to use their buying power to influence corporate pollution outputs. Even though IPE has no regulatory authority within the government, they have nevertheless succeeded in getting more than 500 companies to disclose their plan to clean up their facilities.
Ma credits the public transparency and participation in data visibility with these gains in China. Mindful of the gaps in environmental risk exposure and data collection, transparency is a clear first step to cleaner water and a healthier relationship between the public and government. Ultimately public engagement with environmental data would create significant accountability, water health protection, and expansion of community input in environmental policies. To prevent the next Flint, cities should make it a priority to bridge public and government engagement to plug the data gaps.