2019 Progress Report: Drinking water vulnerability and neonatal health outcomes in relation to oil and gas production in the Appalachian BasinEPA Grant Number: CR839249
Title: Drinking water vulnerability and neonatal health outcomes in relation to oil and gas production in the Appalachian Basin
Investigators: Deziel, Nicole Cardello , Saiers, James E. , Bell, Michelle L. , Ma, Xiaomei , Plata, Desiree , Warren, Joshua
Institution: Yale University
EPA Project Officer: Hahn, Intaek
Project Period: September 1, 2017 through August 31, 2020 (Extended to August 31, 2021)
Project Period Covered by this Report: September 1, 2018 through August 31,2019
Project Amount: $1,998,515
RFA: Oil and Gas Development in the Appalachian Basin (2016) RFA Text | Recipients Lists
Research Category: Water , Human Health
The assessment of potential exposures and associated human-health impacts of UO&G development is a long-standing challenge. The problem stems from (i) the scarcity of data needed to estimate the frequency and severity of groundwater contamination, (ii) the lack of models capable of predicting where and when this contamination is most likely to occur, and (iii) uncertainty in the effects that exposures to UO&G-contaminated waters have on human health. The goal of this project, which we refer to as theWATer andEnergyResources Study (WATER Study), is to address these deficiencies. Our work is guided by three objectives:
(1) advance a modeling framework to estimate drinking-water vulnerability to contamination by unconventional oil and gas (UOG) activities;
(2) evaluate the vulnerability framework by comparing its predictions with water-quality measurements collected from households in Pennsylvania (PA) and Ohio (OH);
(3) investigate the association between exposure to UOG-related water contaminants and adverse neonatal outcomes in PA and OH using our vulnerability index as an exposure surrogate, while also accounting for other UOG stressors and factors related to social disadvantage (e.g., income, education).
Objective 1: Drinking-Water Vulnerability Assessment
We are implementing a capture-zone approach to evaluate the vulnerability of residential drinkingwater supplies to contamination by UOG development. A capture zone represents the contributing area of a groundwater well; in other words, it is the portion of an aquifer from which the well draws its water. We use hydrologic models to simulate the capture zones of residential drinking-water wells and estimate vulnerability based on their proximity to UOG infrastructure (e.g., well pads). Work towards developing and testing this vulnerability framework has involved four major tasks: Database creation. A geographic information system (GIS) database was assembled for northeastern Pennsylvania. The database comprises thematic layers of local hydrogeology, topography, climatology, stream-water discharge, domestic and monitoring well locations, UOG well pads and other infrastructure. Satellite data and areal photographs were used to characterize the spatial distribution in surface lineaments, which, in turn was used to infer anisotropy in aquifer permeability and potential zones of naturally occurring fractures. These data were drawn from various agencies, including the PA Department of Environmental Protection (PADEP), US Geological Survey (USGS), and Susquehanna River Basin Commission.
Model development. Vulnerability assessments are based on computations of hydrologic models that simulate coupled subsurface flow and solute transport. Two types of flow and transport models were developed – an equivalent porous medium model and a discrete-fracture network model. Both of these models are fully three-dimensional and were constructed using a using a robust finite element hydrologic simulator. The physically based models were parallelized to run efficiently using Yale’s high-performance computing cluster.
Model calibration. The hydrologic models were calibrated against data on hydraulic heads (i.e., aquifer water levels) and estimates of groundwater discharge to streams that drain watersheds in northeastern Pennsylvania. Measurements of hydraulic head were extracted from the Pennsylvania Groundwater Information System (PaGWIS) database. Estimates of groundwater discharge were based on stream flow approximations, which, in turn, were determined by regression-based models that use watershed properties as predictor variables. The software PEST was employed during the calibration process for parameter inversion, sensitivity analysis, and uncertainty analysis.
Estimates of drinking-water vulnerability. The calibrated models have been used to estimate drinking-water vulnerability of 220 drinking water wells in northeastern Pennsylvania. We are currently evaluating the vulnerability estimates in context to our own measurements of groundwater quality, as well as to published measurements of groundwater quality made in the area (e.g., http://www.shalenetwork.org).
Objective 2: Drinking-Water Sampling and Analysis
The WATER Study team successfully completed all water collection, chemical analysis, and participant result reports for its first sampling campaign in Bradford County, PA (n=94 homes in summer 2018). The WATER Study Team successfully executed the second phase of its sampling campaign in 2019 by targeting households (n=161) in Belmont and Monroe Counties, OH, where UOG has been particularly intensive. Home visits involved administration of a detailed questionnaire to a head-of-household, followed by collection of untreated well water and treated water for those homes with water softening or other treatment systems, and collection of GPS coordinates of the homes and drinking-water wells. Analysis of the 2019 water samples for nearly 100 inorganic and organic analytes is in progress and will be completed this fall.
Protocols, Data Collection Instruments, Training, and Institutional Approvals. Written protocols and checklists created in 2018 were reviewed. All project personnel completed human-research training, and those personnel involved in household visits completed interview training and sample collection training.
Stakeholder Engagement. The project PIs informed the Project Officer and officials at state agencies, including the Pennsylvania Department of Environmental Protection, the Ohio Department of Natural Resources, the Ohio Department of Public Health, and the West Virginia
Office of Epidemiology and Prevention Services, of the project team’s intention to collect household water samples in Ohio. The study website (http://waterstudy.yale.edu) was updated to disseminate information about the study to federal and state agencies, as well as to the general public. A sample copy of the participant drinking water result reports was provided to these stakeholders as well.
Participant Recruitment. To recruit participants, informational postcards were created and mailed to households in several Belmont and Monroe County zip codes. In addition, project staff posted informational flyers at local businesses, distributed flyers at community events, posted to websites of local organizations and community groups, and advertisements were placed in local newspapers. A Facebook page was also created as an outreach and recruitment tool (https://www.facebook.com/WATer-and-Energy-Resources-Study-WATER-
335490740648150/A). Our call center at Yale was staffed to respond to inquiries from potential participants, screen individuals for study eligibility, and schedule household visits with eligible participants.
Household Water Collection and Surveys. Home visits commenced in May 2019 and were conducted by two sampling teams of 2-3 data collectors, each consisting of water sampler and an interviewer and, when available, a third person to provide additional assistance to the water sampler. The interviewer administered a 50-question survey to gain demographic information, as well as information on home and drinking-water characteristics. Water samples were collected from every household where a survey was conducted. One hundred sixty-one visits were completed from May through August 2019.
Laboratory Analyses. Water samples are being analyzed for major cations, major anions, trace metals, dissolved organic carbon (DOC), and dissolved in organic carbon (DIC) at Yale University. Concurrently at MIT, analyses are being conducted to quantify levels of more than 60 different volatile- and semi-volatile organic compounds (VOCs and SVOCs), integrated gasoline range organic (GRO) compounds, methane, ethane, propane, as well as a preliminary screen of and diesel range organic compounds in order to prioritize further compound-specific analysis. Additional samples were collected during the 2019 sampling campaign for analysis of concentrations of dissolved noble gases. All chemical analyses of 2018 water samples have been completed. Analyses of 2019 samples are projected for completion by December 2019.
Data Cleaning, Management, and Quality Assurance. The data management team has implemented procedures to ensure complete, accurate, and high-quality datasets. Questionnaires and protocols were reviewed for clarity, consistency, and utility of response data. Codebooks were created for each data collection instrument. Survey data collected in the field on paper forms were manually checked and hand-coded to identify errors or missing responses. Data from paper forms were entered into electronic databases, which were designed with variable restrictions to minimize errors. After data entry, algorithms were run to edit check data for inconsistencies, missing values and response error to ensure data validity. Errant data were corrected wherever possible with documentation. All data cleaning and processing for the 2018 sampling campaign has been completed. Cleaning and processing of the 2019 questionnaire, GPS, and collection form data is nearly complete. The final datasets are stored on secure servers at Yale University.
Report-Back to Participants. All participants of the first sampling campaign were mailed a detailed report of the results of the water samples collected at their home in March 2019. Reports were designed to be accessible to a lay audience. Reports included both text and color-coded tables with a legend and instructions on how to interpret the report. The report included Frequently Asked Questions and links to additional resources and study contact information.
Data Analysis. Multi-disciplinary analysis of the water sampling data from 2018 is underway. We have been conducting exploratory analyses of the distributions of chemicals in drinking water and how they compare to traditional proximity metrics and the newly developed vulnerability model. We have been analyzing the drinking water chemistry to evaluate likely sources of the different compounds measured. We have evaluated the distribution of the demographic and housing characteristics of the households enrolled in the 2018 sampling campaign.
Objective 3: Epidemiologic Analysis of Neonatal Health Outcomes
We are evaluating whether potential exposure to UOG-related water contaminants (as captured by the vulnerability index) is associated with incidence of adverse birth outcomes in the PA and OH study area, while accounting for the potential influence of socioeconomic and other chemical and non-chemical stressors on adverse birth outcomes. To carry out this aim, we are assembling data from numerous sources.
Health Outcome Data. All protocols and data requests to the PA and OH State Health Departments to obtain birth certificates (2010-2017, inclusive) were approved as of March 2019. All Ohio data have been provided. The Pennsylvania birth certificate data are scheduled to be securely delivered by November 2019.
UOG Exposure Data. Data pertaining to unconventional oil and gas well locations, permit, spud, and completion dates are being obtained from relevant state agencies and assembled.
Sociodemographic Data. Sociodemographic data from the US Census (decennial Census and American Community Survey) are being assembled.
Potential Covariates and Confounders. We are obtaining data on other possible environmental sources related to agricultural land use and air pollution.
Objective 1: Vulnerability Assessment
We will develop physically based models suitable for describing groundwater flow and chemical transport through aquifers that lie beneath our study area in eastern Ohio. Once tested and calibrated, these models will form the basis of vulnerability predictions for the 160 drinking water wells sampled during the 2019 field campaign. Although the general modeling framework used for Pennsylvania (see above) will be transferable to Ohio, we expect that differences in hydrologic setting will lead to notable differences in the characteristics of drinking-water vulnerability between the two regions.
Objective 2: Drinking-Water Sampling and Analysis
We will finalize data cleaning and processing from the 2019 field sampling campaign. We will complete laboratory analysis for the 2019 field study and mail participants their individual reports of their drinking water test results. We will continue data analysis to understand the distributions of chemicals in drinking water and how they compare to traditional proximity metrics and the newly developed vulnerability model. We will continue to conduct source apportionment evaluations. Based on the results of analyses from the 2018 and 2019 water sampling data, we will plan and launch a 2020 field sampling campaign (approximately 100 homes), as needed.
Objective 3: Epidemiologic Analysis of Neonatal Health Outcomes
We will complete construction of our data architecture. We will apply our inclusion criteria and identify our cases with respect to the relevant birth outcomes. We will select our controls. We will assign all subjects a UOG exposure estimate first by using traditional, simple proximity metrics while the vulnerability model is being calibrated and further developed. We will ultimately use the vulnerability model to assign exposures to study subjects.
Journal Articles on this Report : 1 Displayed | Download in RIS Format
|Other project views:||All 17 publications||3 publications in selected types||All 3 journal articles|
|| Silva GS, Warren JL, Deziel NC. Spatial modeling to identify sociodemographic predictors of hydraulic fracturing wastewater injection wells in Ohio census block groups. Environmental Health Perspectives 2018;126(6):067008 (8 pp.).