Population allocation at the housing unit level: estimates around underground natural gas storage wells in PA, OH, NY, WV, MI, and CA

Background Spatially accurate population data are critical for determining health impacts from many known risk factors. However, the utility of the increasing spatial resolution of disease mapping and environmental exposures is limited by the lack of receptor population data at similar sub-census block spatial scales. Methods Here we apply an innovative method (Population Allocation by Occupied Domicile Estimation – ABODE) to disaggregate U.S. Census populations by allocating an average person per household to geospatially-identified residential housing units (RHU). We considered two possible sources of RHU location data: address point locations and building footprint centroids. We compared the performance of ABODE with the common proportional population allocation (PPA) method for estimating the nighttime residential populations within 200 m radii and setback areas (100 – 300 ft) around active underground natural gas storage (UGS) wells (n = 9834) in six U.S. states. Results Address location data generally outperformed building footprint data in predicting total counts of census residential housing units, with correlations ranging from 0.67 to 0.81 at the census block level. Using residentially-sited addresses only, ABODE estimated upwards of 20,000 physical households with between 48,126 and 53,250 people living within 200 m of active UGS wells – likely encompassing the size of a proposed UGS Wellhead Safety Zone. Across the 9834 active wells assessed, ABODE estimated between 5074 and 10,198 more people living in these areas compare to PPA, and the difference was significant at the individual well level (p = < 0.0001). By either population estimation method, OH exhibits a substantial degree of hyperlocal land use conflict between populations and UGS wells – more so than other states assessed. In some rare cases, population estimates differed by more than 100 people for the small 200 m2 well-areas. ABODE’s explicit accounting of physical households confirmed over 50% of PPA predictions as false positives indicated by non-zero predictions in areas absent physical RHUs. Conclusions Compared to PPA – in allocating identical population data at sub-census block spatial scales –ABODE provides a more precise population at risk (PAR) estimate with higher confidence estimates of populations at greatest risk. 65% of UGS wells occupy residential urban and suburban areas indicating the unique land use conflicts presented by UGS systems that likely continue to experience population encroachment. Overall, ABODE confirms tens of thousands of homes and residents are likely located within the proposed UGS Wellhead Safety Zone – and in some cases within state’s oil and gas well surface setback distances – of active UGS wells

Developing a Modular Unmanned Aerial Vehicle (UAV) Platform for Air Pollution Profiling

The unmanned aerial vehicle (UAV) offers great potential for collecting air quality data with high spatial and temporal resolutions. The objective of this study is to design and develop a modular UAV-based platform capable of real-time monitoring of multiple air pollutants. The system comprises five modules: the UAV, the ground station, the sensors, the data acquisition (DA) module, and the data fusion (DF) module. The hardware was constructed with off-the-shelf consumer parts and the open source software Ardupilot was used for flight control and data fusion. The prototype UAV system was tested in representative settings. Results show that this UAV platform can fly on pre-determined pathways with adequate flight time for various data collection missions. The system simultaneously collects air quality and high precision X-Y-Z data and integrates and visualizes them in a real-time manner. While the system can accommodate multiple gas sensors, UAV operations may electronically interfere with the performance of chemical-resistant sensors. Our prototype and experiments prove the feasibility of the system and show that it features a stable and high precision spatial-temporal platform for air sample collection. Future work should be focused on gas sensor development, plug-and-play interfaces, impacts of rotor wash, and all-weather designs

Climate and health benefits of increasing renewable energy deployment in the United States

The type, size, and location of renewable energy (RE) deployment dramatically affects benefits to climate and health. Here, we develop a ten-region model to assess the magnitude of health and climate benefits across the US We then use this model to assess the benefits of deploying varying capacities of wind, utility-scale solar photovoltaics (PV), and rooftop solar PV in different regions in the US—a total of 284 different scenarios. Total benefits ranged from $2.2 trillion for 3000 MW of wind in the Upper Midwest to$4.2 million for 100 MW of wind in California. Total benefits and highest cost effectiveness for CO _2 reduction were generally highest for RE deployment in the Upper Midwest and Great Lakes and Mid-Atlantic US and lowest in California. Health was a substantial portion of total benefits in nearly all regions of the US Benefits were sensitive to methane leakage throughout the gas supply chain

Hazardous air pollutants in transmission pipeline natural gas: an analytic assessment

Natural gas production occurs in specific regions of the US, after which it is processed and transported via an interconnected network of high-pressure interstate pipelines. While the presence of hazardous air pollutants (HAPs) in unprocessed, upstream natural gas has been documented, little has been published on their presence in the midstream natural gas supply. We systematically evaluated publicly available, industry-disclosed HAP composition data sourced from Federal Energy Regulatory Commission (FERC) natural gas infrastructure applications submitted between 2017 and 2020. Natural gas composition data from these filings represent approximately 45% of the US onshore natural gas transmission system by pipeline mileage. Given that reporting natural gas HAP composition data is not required by FERC, only 49% of approved expansion projects disclosed natural gas HAP composition data. Of those applications that disclosed composition data, HAP concentrations were typically reported as higher for separator flash gas and condensate tank vapor compared to liquefied natural gas and transmission-grade natural gas, with mean benzene concentrations of 1106, 7050, 77, and 37 ppm respectively. We also identified one pipeline operator that reports real-time HAP concentrations for its natural gas at five pipeline interconnection points. Similar to the FERC applications, this operator reported benzene, toluene, ethylbenzene, xylenes and hydrogen sulfide as present in transmission pipeline natural gas. Notably, mercury was also reported as detectable in 14% of real-time natural gas measurements but was not reported in any FERC applications. Given that transmission infrastructure releases natural gas during uncontrolled leaks and loss of containment events as well as during routine operations (e.g. blowouts and compressor station blowdowns), these gas composition data may serve as a critical component of air quality and health-focused evaluations of natural gas releases

Fine-Scale Source Apportionment Including Diesel-Related Elemental and Organic Constituents of PM2.5 across Downtown Pittsburgh

Health effects of fine particulate matter (PM2.5) may vary by composition, and the characterization of constituents may help to identify key PM2.5 sources, such as diesel, distributed across an urban area. The composition of diesel particulate matter (DPM) is complicated, and elemental and organic carbon are often used as surrogates. Examining multiple elemental and organic constituents across urban sites, however, may better capture variation in diesel-related impacts, and help to more clearly separate diesel from other sources. We designed a &ldquo;super-saturation&rdquo; monitoring campaign of 36 sites to capture spatial variance in PM2.5 and elemental and organic constituents across the downtown Pittsburgh core (~2.8 km2). Elemental composition was assessed via inductively-coupled plasma mass spectrometry (ICP-MS), organic and elemental carbon via thermal-optical reflectance, and organic compounds via thermal desorption gas-chromatography mass-spectrometry (TD-GCMS). Factor analysis was performed including all constituents&mdash;both stratified by, and merged across, seasons. Spatial patterning in the resultant factors was examined using land use regression (LUR) modelling to corroborate factor interpretations. We identified diesel-related factors in both seasons; for winter, we identified a five-factor solution, describing a bus and truck-related factor [black carbon (BC), fluoranthene, nitrogen dioxide (NO2), pyrene, total carbon] and a fuel oil combustion factor (nickel, vanadium). For summer, we identified a nine-factor solution, which included a bus-related factor (benzo[ghi]fluoranthene, chromium, chrysene, fluoranthene, manganese, pyrene, total carbon, total elemental carbon, zinc) and a truck-related factor (benz[a]anthracene, BC, hopanes, NO2, total PAHs, total steranes). Geographic information system (GIS)-based emissions source covariates identified via LUR modelling roughly corroborated factor interpretations

Spatial Patterns in Rush-Hour vs. Work-Week Diesel-Related Pollution across a Downtown Core

Despite advances in monitoring and modelling of intra-urban variation in multiple pollutants, few studies have attempted to separate spatial patterns by time of day, or incorporated organic tracers into spatial monitoring studies. Due to varying emissions sources from diesel and gasoline vehicular traffic, as well as within-day temporal variation in source mix and intensity (e.g., rush-hours vs. full-day measures), accurately assessing diesel-related air pollution within an urban core can be challenging. We allocated 24 sampling sites across downtown Pittsburgh, Pennsylvania (2.8 km2) to capture fine-scale variation in diesel-related pollutants, and to compare these patterns by sampling interval (i.e., &ldquo;rush-hours&rdquo; vs. &ldquo;work-week&rdquo; concentrations), and by season. Using geographic information system (GIS)-based methods, we allocated sampling sites to capture spatial variation in key traffic-related pollution sources (i.e., truck, bus, overall traffic densities). Programmable monitors were used to collect integrated work-week and rush-hour samples of fine particulate matter (PM2.5), black carbon (BC), trace elements, and diesel-related organics (polycyclic aromatic hydrocarbons (PAHs), hopanes, steranes), in summer and winter 2014. Land use regression (LUR) models were created for PM2.5, BC, total elemental carbon (EC), total organic carbon (OC), elemental (Al, Ca, Fe), and organic constituents (total PAHs, total hopanes), and compared by sampling interval and season. We hypothesized higher pollution concentrations and greater spatial contrast in rush-hour, compared to full work-week samples, with variation by season and pollutant. Rush-hour sampling produced slightly higher total PM2.5 and BC concentrations in both seasons, compared to work-week sampling, but no evident difference in spatial patterns. We also found substantial spatial variability in most trace elements and organic compounds, with comparable spatial patterns using both sampling paradigms. Overall, we found higher concentrations of traffic-related trace elements and organic compounds in rush-hour samples, and higher concentrations of coal-related elements (e.g., As, Se) in work-week samples. Mean bus density was the strongest LUR predictor in most models, in both seasons, under each sampling paradigm. Within each season and constituent, the bus-related terms explained similar proportions of variance in the rush-hour and work-week samples. Rush-hour and work-week LUR models explained similar proportions of spatial variation in pollutants, suggesting that the majority of emissions may be produced during rush-hour traffic across downtown. Results suggest that rush-hour emissions may predominantly shape overall spatial variance in diesel-related pollutants

Composition, Emissions, and Air Quality Impacts of Hazardous Air Pollutants in Unburned Natural Gas from Residential Stoves in California

The presence of hazardous air pollutants (HAPs) entrained in end-use natural gas (NG) is an understudied source of human health risks. We performed trace gas analyses on 185 unburned NG samples collected from 159 unique residential NG stoves across seven geographic regions in California. Our analyses commonly detected 12 HAPs with significant variability across region and gas utility. Mean regional benzene, toluene, ethylbenzene, and total xylenes (BTEX) concentrations in end-use NG ranged from 1.6-25 ppmv─benzene alone was detected in 99% of samples, and mean concentrations ranged from 0.7-12 ppmv (max: 66 ppmv). By applying previously reported NG and methane emission rates throughout California's transmission, storage, and distribution systems, we estimated statewide benzene emissions of 4,200 (95% CI: 1,800-9,700) kg yr-1 that are currently not included in any statewide inventories─equal to the annual benzene emissions from nearly 60,000 light-duty gasoline vehicles. Additionally, we found that NG leakage from stoves and ovens while not in use can result in indoor benzene concentrations that can exceed the California Office of Environmental Health Hazard Assessment 8-h Reference Exposure Level of 0.94 ppbv─benzene concentrations comparable to environmental tobacco smoke. This study supports the need to further improve our understanding of leaked downstream NG as a source of health risk

Temporal Trends of Racial and Socioeconomic Disparities in Population Exposures to Upstream Oil and Gas Development in California

People living near oil and gas development are exposed to multiple environmental stressors that pose health risks. Some studies suggest these risks are higher for racially and socioeconomically marginalized people, which may be partly attributable to disparities in exposures. We examined whether racially and socioeconomically marginalized people in California are disproportionately exposed to oil and gas wells and associated hazards. We longitudinally assessed exposure to wells during three time periods (2005-2009, 2010-2014, and 2015-2019) using sociodemographic data at the census block group-level. For each block group and time period, we assessed exposure to new, active, retired, and plugged wells, and cumulative production volume. We calculated risk ratios to determine whether marginalized people disproportionately resided near wells (within 1&nbsp;km). Averaged across the three time periods, we estimated that 1.1 million Californians (3.0%) lived within 1&nbsp;km of active wells. Nearly 9 million Californians (22.9%) lived within 1&nbsp;km of plugged wells. The proportion of Black residents near active wells was 42%-49% higher than the proportion of Black residents across California, and the proportion of Hispanic residents near active wells was 4%-13% higher than their statewide proportion. Disparities were greatest in areas with the highest oil and gas production, where the proportion of Black residents was 105%-139% higher than statewide. Socioeconomically marginalized residents also had disproportionately high exposure to wells. Though oil and gas production has declined in California, marginalized communities persistently had disproportionately high exposure to wells, potentially contributing to health disparities

Assessment of Effluent Contaminants from Three Facilities Discharging Marcellus Shale Wastewater to Surface Waters in Pennsylvania

Unconventional natural gas development in Pennsylania has created a new wastewater stream. In an effort to stop the discharge of Marcellus Shale unconventional natural gas development wastewaters into surface waters, on May 19, 2011 the Pennsylvania Department of Environmental Protection (PADEP) requested drilling companies stop disposing their wastewater through wastewater treatment plants (WWTPs). This research includes a chemical analysis of effluents discharged from three WWTPs before and after the aforementioned request. The WWTPs sampled included two municipal, publicly owned treatment works and a commercially operated industrial wastewater treatment plant. Analyte concentrations were quanitified and then compared to water quality criteria, including U.S. Environmental Protection Agency MCLs and “human health criteria.” Certain analytes including barium, strontium, bromides, chlorides, total dissolved solids, and benzene were measured in the effluent at concentrations above criteria. Analyte concentrations measured in effluent samples before and after the PADEP’s request were compared for each facility. Analyte concentrations in the effluents decreased in the majority of samples after the PADEP’s request (<i>p</i> < .05). This research provides preliminary evidence that these and similar WWTPs may not be able to provide sufficient treatment for this wastewater stream, and more thorough monitoring is recommended

Temporal Trends of Racial and Socioeconomic Disparities in Population Exposures to Upstream Oil and Gas Development in California

Abstract People living near oil and gas development are exposed to multiple environmental stressors that pose health risks. Some studies suggest these risks are higher for racially and socioeconomically marginalized people, which may be partly attributable to disparities in exposures. We examined whether racially and socioeconomically marginalized people in California are disproportionately exposed to oil and gas wells and associated hazards. We longitudinally assessed exposure to wells during three time periods (2005–2009, 2010–2014, and 2015–2019) using sociodemographic data at the census block group‐level. For each block group and time period, we assessed exposure to new, active, retired, and plugged wells, and cumulative production volume. We calculated risk ratios to determine whether marginalized people disproportionately resided near wells (within 1 km). Averaged across the three time periods, we estimated that 1.1 million Californians (3.0%) lived within 1 km of active wells. Nearly 9 million Californians (22.9%) lived within 1 km of plugged wells. The proportion of Black residents near active wells was 42%–49% higher than the proportion of Black residents across California, and the proportion of Hispanic residents near active wells was 4%–13% higher than their statewide proportion. Disparities were greatest in areas with the highest oil and gas production, where the proportion of Black residents was 105%–139% higher than statewide. Socioeconomically marginalized residents also had disproportionately high exposure to wells. Though oil and gas production has declined in California, marginalized communities persistently had disproportionately high exposure to wells, potentially contributing to health disparities