Project updates


The Drinking Water Tool: 

A Community Water Center and Water Equity Science Shop collaboration

 

February 18, 2020

On February 12, 2020 the Community Water Center released the Drinking Water Tool, an interactive website featuring data layers created, in part, by the UC Berkeley Superfund Community Engagement Core – Water Equity Science Shop (UCB-CEC WESS). The Drinking Water Tool provides information about the ways that communities across the state might be vulnerable to groundwater challenges that could affect their access to long-term safe and affordable drinking water. This tool allows users to learn where their water comes from based on their address, determine whether a future drought could impact their drinking water supply, learn about the groundwater quality and supply, and learn how to advocate for safe clean and affordable drinking water.

The WESS played a pivotal role in the planning, development, and creation of the data underlying the Drinking Water Tool. SRP Trainee Clare Pace and the WESS team integrated existing datasets in novel ways to identify areas in California that are reliant on domestic wells and therefore uniquely vulnerable to drinking water access and quality challenges. The WESS’s domestic well community layer is one of the first statewide datasets to define the boundaries of communities that are likely to rely on private domestic wells in California. This information will contribute to  statewide efforts to achieve the Human Right to Water (AB 685) and is currently being used to inform development of Groundwater Sustainability Plans under California’s Sustainable Groundwater Management Act (SGMA, SB 1319, SB 1168) and the Department of Water Resource’s County Drought Advisory Group –CDAG (AB 1668).

Additional Links:

  • Recording of Drinking Water Tool Launch Webinar
  • WESS’s associated white paper: Locating Domestic Well Communities in California: a Methodological Overview. Domestic Well Layer (Version 1), Water Equity Science Shop.  Clare Pace, Carolina Balazs, Lara Cushing, Rachel Morello-Frosch. 
  • CWC Press release on 2/12/2020.
  • Watsonville’s KSBW-8 report on the Drinking Water Tool on 2/12/2020. 

Drinking Water tool displaying Domestic Well Communities with a count of domestic wells in a 1×1 mile grid


Noise Pollution in the United States

Day-night average noise and average nighttime noise at the census tract level in the contiguous United States. Noise levels represent an average summer day between 2000-2014. To view an interactive map open this url in your browser: https://dlab-geo.github.io/citynoise/

About the interactive map:

The noise map displays census tract level estimates of noise, categorized as below, slightly exceeding, and exceeding the U.S. EPA day-night average sound level (Ldn) limit of <55 decibels (dB). Points (census tract centroids) display values in the small-scale map and census tract boundaries appear when the user zooms in to a specific city. Available on the large-scale (zoomed in) map, users can click a specific census tract and see which noise category the tract falls into: (1) Ldn: low = <55 dB; medium = 55-58 dB; and high = 58+ dB; and (2) Median nighttime noise: low = < 40 dB; medium = 40-43 dB; and high = 43+ dB.

A bit about the noise data:

The noise exposure data was obtained from a geospatial model of environmental sound levels derived from empirical acoustical data and modeling of land features (topography, climate, hydrology, and anthropogenic activity) (Mennitt and Fristrup 2016). We have previously used this model in a nationwide environmental justice analysis (Casey et al. 2017). Noise exposures were estimated from a random forest model that utilizes a tree-based machine learning algorithm to combine spatial data with over 1.5 million hours of long-term noise measurements at 492 urban and rural sites in the contiguous U.S. from 2000–2014 to produce ambient sound estimates at a 270m resolution. Complete information on explanatory variables in the model are provided by the National Park Service (Sherrill 2012). The model has been shown to perform well under cross-validation tests, with a median absolute deviation of 1.7 dB in urban areas (Casey et al. 2017). The main map provides low, medium, and high cut-points based on cross-sectional day-night average sound (Ldn), 24-hour average noise with penalties added for evening and nighttime noise. We also display average nighttime noise, L50, night, where night is defined as 22:00–7:00 hours with low, medium, and high cut-points that correspond to the levels below, slightly exceeding, and exceeding the World Health Organization (WHO) recommended nighttime noise level of 40 dB. The WHO recommends nighttime Leq fall below 40 dB. They describe 40 dB as the lowest observable adverse effect level for nighttime noise (WHO 2011).

Previous research:

Drs. Casey, Morello-Frosch, and colleagues recently identified large racial/ethnic and socioeconomic disparities in noise pollution across the United States (Casey et al. 2017). We do not yet know whether disproportionate noise exposure among vulnerable populations can help explain health disparities. In a current study, we combine our nationwide noise model, American Community Survey data, and the 500 Cities Health Data to evaluate associations between nighttime and 24-hour noise exposures and census tract level prevalence of hypertension, poor sleep, and poor mental health.

Funders: This research is based upon work supported by the Urban Institute through funds provided by the Robert Wood Johnson Foundation. We thank them for their support but acknowledge that the findings and conclusions presented in this report are those by the author(s) alone and do not necessarily reflect the opinions of the Urban Institute or the Robert Wood Johnson Foundation.

Collaborators:

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