State-of-the-Science Data and Methods Need to Guide Place-Based Efforts to Reduce Air Pollution Inequity.

BACKGROUND: Recently enacted environmental justice policies in the United States at the state and federal level emphasize addressing place-based inequities, including persistent disparities in air pollution exposure and associated health impacts. Advances in air quality measurement, models, and analytic methods have demonstrated the importance of finer-scale data and analysis in accurately quantifying the extent of inequity in intraurban pollution exposure, although the necessary degree of spatial resolution remains a complex and context-dependent question. OBJECTIVE: The objectives of this commentary were to a) discuss ways to maximize and evaluate the effectiveness of efforts to reduce air pollution disparities, and b) argue that environmental regulators must employ improved methods to project, measure, and track the distributional impacts of new policies at finer geographic and temporal scales. DISCUSSION: The historic federal investments from the Inflation Reduction Act, the Infrastructure Investment and Jobs Act, and the Biden Administration's commitment to Justice40 present an unprecedented opportunity to advance climate and energy policies that deliver real reductions in pollution-related health inequities. In our opinion, scientists, advocates, policymakers, and implementing agencies must work together to harness critical advances in air quality measurements, models, and analytic methods to ensure success. https://doi.org/10.1289/EHP13063.

Identifying Patterns and Sources of Fine and Ultrafine Particulate Matter in London Using Mobile Measurements of Lung-Deposited Surface Area.

We performed more than a year of mobile, 1 Hz measurements of lung-deposited surface area (LDSA, the surface area of 20-400 nm diameter particles, deposited in alveolar regions of lungs) and optically assessed fine particulate matter (PM2.5), black carbon (BC), and nitrogen dioxide (NO2) in central London. We spatially correlated these pollutants to two urban emission sources: major roadways and restaurants. We show that optical PM2.5 is an ineffective indicator of tailpipe emissions on major roadways, where we do observe statistically higher LDSA, BC, and NO2. Additionally, we find pollutant hot spots in commercial neighborhoods with more restaurants. A low LDSA (15 µm2 cm-3) occurs in areas with fewer major roadways and restaurants, while the highest LDSA (25 µm2 cm-3) occurs in areas with more of both sources. By isolating areas that are higher in one source than the other, we demonstrate the comparable impacts of traffic and restaurants on LDSA. Ratios of hyperlocal enhancements (ΔLDSA:ΔBC and ΔLDSA:ΔNO2) are higher in commercial neighborhoods than on major roadways, further demonstrating the influence of restaurant emissions on LDSA. We demonstrate the added value of using particle surface in identifying hyperlocal patterns of health-relevant PM components, especially in areas with strong vehicular emissions where the high LDSA does not translate to high PM2.5.

Comparison of Mobile and Fixed-Site Black Carbon Measurements for High-Resolution Urban Pollution Mapping.

Urban concentrations of black carbon (BC) and other primary pollutants vary on small spatial scales (<100m). Mobile air pollution measurements can provide information on fine-scale spatial variation, thereby informing exposure assessment and mitigation efforts. However, the temporal sparsity of these measurements presents a challenge for estimating representative long-term concentrations. We evaluate the capabilities of mobile monitoring in the represention of time-stable spatial patterns by comparing against a large set of continuous fixed-site measurements from a sampling campaign in West Oakland, California. Custom-built, low-cost aerosol black carbon detectors (ABCDs) provided 100 days of continuous measurements at 97 near-road and 3 background fixed sites during summer 2017; two concurrently operated mobile laboratories collected over 300 h of in-motion measurements using a photoacoustic extinctiometer. The spatial coverage from mobile monitoring reveals patterns missed by the fixed-site network. Time-integrated measurements from mobile lab visits to fixed-site monitors reveal modest correlation (spatial R2 = 0.51) with medians of full daytime fixed-site measurements. Aggregation of mobile monitoring data in space and time can mitigate high levels of uncertainty associated with measurements at precise locations or points in time. However, concentrations estimated by mobile monitoring show a loss of spatial fidelity at spatial aggregations greater than 100 m.

Quantifying methane emissions from the largest oil-producing basin in the United States from space.

Using new satellite observations and atmospheric inverse modeling, we report methane emissions from the Permian Basin, which is among the world's most prolific oil-producing regions and accounts for >30% of total U.S. oil production. Based on satellite measurements from May 2018 to March 2019, Permian methane emissions from oil and natural gas production are estimated to be 2.7 ± 0.5 Tg a-1, representing the largest methane flux ever reported from a U.S. oil/gas-producing region and are more than two times higher than bottom-up inventory-based estimates. This magnitude of emissions is 3.7% of the gross gas extracted in the Permian, i.e., ~60% higher than the national average leakage rate. The high methane leakage rate is likely contributed by extensive venting and flaring, resulting from insufficient infrastructure to process and transport natural gas. This work demonstrates a high-resolution satellite data-based atmospheric inversion framework, providing a robust top-down analytical tool for quantifying and evaluating subregional methane emissions.

Characterizing Elevated Urban Air Pollutant Spatial Patterns with Mobile Monitoring in Houston, Texas.

Diverse urban air pollution sources contribute to spatially variable atmospheric concentrations, with important public health implications. Mobile monitoring shows promise for understanding spatial pollutant patterns, yet it is unclear whether uncertainties associated with temporally sparse sampling and instrument performance limit our ability to identify locations of elevated pollution. To address this question, we analyze 9 months of repeated weekday daytime on-road mobile measurements of black carbon (BC), particle number (PN), and nitrogen oxide (NO, NO2) concentrations within 24 census tracts across Houston, Texas. We quantify persistently elevated, intermittent, and extreme concentration behaviors at 50 m road segments on surface streets and 90 m segments on highways relative to median statistics across the entire sampling domain. We find elevated concentrations above uncertainty levels (±40%) within portions of every census tract, with median concentration increases ranging from 2 to 3× for NO2, and >9× for NO. In contrast, PN exhibits elevated concentrations of 1.5-2× the domain-wide median and distinct spatial patterns relative to other pollutants. Co-located elevated concentrations of primary combustion tracers (BC and NOx) near 30% of metal recycling and concrete batch plant facilities within our sampled census tracts are comparable to those measured within 200 m of highways. Our results demonstrate how extensive mobile monitoring across multiple census tracts can quantitatively characterize urban air pollution source patterns and are applicable to developing effective source mitigation policies.

Assessment of methane emissions from the U.S. oil and gas supply chain.

Methane emissions from the U.S. oil and natural gas supply chain were estimated by using ground-based, facility-scale measurements and validated with aircraft observations in areas accounting for ~30% of U.S. gas production. When scaled up nationally, our facility-based estimate of 2015 supply chain emissions is 13 ± 2 teragrams per year, equivalent to 2.3% of gross U.S. gas production. This value is ~60% higher than the U.S. Environmental Protection Agency inventory estimate, likely because existing inventory methods miss emissions released during abnormal operating conditions. Methane emissions of this magnitude, per unit of natural gas consumed, produce radiative forcing over a 20-year time horizon comparable to the CO2 from natural gas combustion. Substantial emission reductions are feasible through rapid detection of the root causes of high emissions and deployment of less failure-prone systems.

Nanowire networks and hollow nanospheres of Ag-Au bimetallic alloys at room temperature.

Due to their physicochemical properties, metallic nanoalloys have potential applications in biomedicine, electrocatalysis and electrochemical sensors, among many other fields. New alternative procedures have emerged in order to reduce production costs and the use of toxic substances. In this study we present a novel low-toxicity synthesis method for the fabrication of nanowire networks (NWNs) and Ag-Au hollow nanospheres. The synthesis process is performed at room temperature without any sophisticated equipment, such as special cameras or furnaces, etc. Transmission electron microscopy showed that the NWNs contain random alloys with a diameter of between 10-13 nm. The radius for the hollow nanospheres is approximately located between 70-130 nm. The absorption bands in the UV-vis spectrum associated with the surface plasmon in Ag-Au bimetallic nanoparticles are highlighted at 385 nm for the NWNs and 643 nm for the hollow nanospheres. The study was performed with low-toxicity substances, such as rongalite, ascorbic acid and sucrose, and showed high efficiency for the fabrication of these types of nanostructures, as well as good stability for long periods of time.

Super-emitters in natural gas infrastructure are caused by abnormal process conditions.

Effectively mitigating methane emissions from the natural gas supply chain requires addressing the disproportionate influence of high-emitting sources. Here we use a Monte Carlo simulation to aggregate methane emissions from all components on natural gas production sites in the Barnett Shale production region (Texas). Our total emission estimates are two-thirds of those derived from independent site-based measurements. Although some high-emitting operations occur by design (condensate flashing and liquid unloadings), they occur more than an order of magnitude less frequently than required to explain the reported frequency at which high site-based emissions are observed. We conclude that the occurrence of abnormal process conditions (for example, malfunctions upstream of the point of emissions; equipment issues) cause additional emissions that explain the gap between component-based and site-based emissions. Such abnormal conditions can cause a substantial proportion of a site's gas production to be emitted to the atmosphere and are the defining attribute of super-emitting sites.

Aerial Surveys of Elevated Hydrocarbon Emissions from Oil and Gas Production Sites.

Oil and gas (O&G) well pads with high hydrocarbon emission rates may disproportionally contribute to total methane and volatile organic compound (VOC) emissions from the production sector. In turn, these emissions may be missing from most bottom-up emission inventories. We performed helicopter-based infrared camera surveys of more than 8000 O&G well pads in seven U.S. basins to assess the prevalence and distribution of high-emitting hydrocarbon sources (detection threshold ∼ 1-3 g s(-1)). The proportion of sites with such high-emitting sources was 4% nationally but ranged from 1% in the Powder River (Wyoming) to 14% in the Bakken (North Dakota). Emissions were observed three times more frequently at sites in the oil-producing Bakken and oil-producing regions of mixed basins (p < 0.0001, χ(2) test). However, statistical models using basin and well pad characteristics explained 14% or less of the variance in observed emission patterns, indicating that stochastic processes dominate the occurrence of high emissions at individual sites. Over 90% of almost 500 detected sources were from tank vents and hatches. Although tank emissions may be partially attributable to flash gas, observed frequencies in most basins exceed those expected if emissions were effectively captured and controlled, demonstrating that tank emission control systems commonly underperform. Tanks represent a key mitigation opportunity for reducing methane and VOC emissions.

Reconciling divergent estimates of oil and gas methane emissions.

Published estimates of methane emissions from atmospheric data (top-down approaches) exceed those from source-based inventories (bottom-up approaches), leading to conflicting claims about the climate implications of fuel switching from coal or petroleum to natural gas. Based on data from a coordinated campaign in the Barnett Shale oil and gas-producing region of Texas, we find that top-down and bottom-up estimates of both total and fossil methane emissions agree within statistical confidence intervals (relative differences are 10% for fossil methane and 0.1% for total methane). We reduced uncertainty in top-down estimates by using repeated mass balance measurements, as well as ethane as a fingerprint for source attribution. Similarly, our bottom-up estimate incorporates a more complete count of facilities than past inventories, which omitted a significant number of major sources, and more effectively accounts for the influence of large emission sources using a statistical estimator that integrates observations from multiple ground-based measurement datasets. Two percent of oil and gas facilities in the Barnett accounts for half of methane emissions at any given time, and high-emitting facilities appear to be spatiotemporally variable. Measured oil and gas methane emissions are 90% larger than estimates based on the US Environmental Protection Agency's Greenhouse Gas Inventory and correspond to 1.5% of natural gas production. This rate of methane loss increases the 20-y climate impacts of natural gas consumed in the region by roughly 50%.

Constructing a Spatially Resolved Methane Emission Inventory for the Barnett Shale Region.

Methane emissions from the oil and gas industry (O&G) and other sources in the Barnett Shale region were estimated by constructing a spatially resolved emission inventory. Eighteen source categories were estimated using multiple data sets, including new empirical measurements at regional O&G sites and a national study of gathering and processing facilities. Spatially referenced activity data were compiled from federal and state databases and combined with O&G facility emission factors calculated using Monte Carlo simulations that account for high emission sites representing the very upper portion, or fat-tail, in the observed emissions distributions. Total methane emissions in the 25-county Barnett Shale region in October 2013 were estimated to be 72,300 (63,400-82,400) kg CH4 h(-1). O&G emissions were estimated to be 46,200 (40,000-54,100) kg CH4 h(-1) with 19% of emissions from fat-tail sites representing less than 2% of sites. Our estimate of O&G emissions in the Barnett Shale region was higher than alternative inventories based on the United States Environmental Protection Agency (EPA) Greenhouse Gas Inventory, EPA Greenhouse Gas Reporting Program, and Emissions Database for Global Atmospheric Research by factors of 1.5, 2.7, and 4.3, respectively. Gathering compressor stations, which accounted for 40% of O&G emissions in our inventory, had the largest difference from emission estimates based on EPA data sources. Our inventory's higher O&G emission estimate was due primarily to its more comprehensive activity factors and inclusion of emissions from fat-tail sites.

Toward a Functional Definition of Methane Super-Emitters: Application to Natural Gas Production Sites.

Emissions from natural gas production sites are characterized by skewed distributions, where a small percentage of sites-commonly labeled super-emitters-account for a majority of emissions. A better characterization of super-emitters is needed to operationalize ways to identify them and reduce emissions. We designed a conceptual framework that functionally defines superemitting sites as those with the highest proportional loss rates (methane emitted relative to methane produced). Using this concept, we estimated total methane emissions from natural gas production sites in the Barnett Shale; functionally superemitting sites accounted for roughly three-fourths of total emissions. We discuss the potential to reduce emissions from these sites, under the assumption that sites with high proportional loss rates have excess emissions resulting from abnormal or otherwise avoidable operating conditions, such as malfunctioning equipment. Because the population of functionally superemitting sites is not expected to be static over time, continuous monitoring will likely be necessary to identify them and improve their operation. This work suggests that achieving and maintaining uniformly low emissions across the entire population of production sites will require mitigation steps at a large fraction of sites.

Influence of methane emissions and vehicle efficiency on the climate implications of heavy-duty natural gas trucks.

While natural gas produces lower carbon dioxide emissions than diesel during combustion, if enough methane is emitted across the fuel cycle, then switching a heavy-duty truck fleet from diesel to natural gas can produce net climate damages (more radiative forcing) for decades. Using the Technology Warming Potential methodology, we assess the climate implications of a diesel to natural gas switch in heavy-duty trucks. We consider spark ignition (SI) and high-pressure direct injection (HPDI) natural gas engines and compressed and liquefied natural gas. Given uncertainty surrounding several key assumptions and the potential for technology to evolve, results are evaluated for a range of inputs for well-to-pump natural gas loss rates, vehicle efficiency, and pump-to-wheels (in-use) methane emissions. Using reference case assumptions reflecting currently available data, we find that converting heavy-duty truck fleets leads to damages to the climate for several decades: around 70-90 years for the SI cases, and 50 years for the more efficient HPDI. Our range of results indicates that these fuel switches have the potential to produce climate benefits on all time frames, but combinations of significant well-to-wheels methane emissions reductions and natural gas vehicle efficiency improvements would be required.

Greater focus needed on methane leakage from natural gas infrastructure.

Natural gas is seen by many as the future of American energy: a fuel that can provide energy independence and reduce greenhouse gas emissions in the process. However, there has also been confusion about the climate implications of increased use of natural gas for electric power and transportation. We propose and illustrate the use of technology warming potentials as a robust and transparent way to compare the cumulative radiative forcing created by alternative technologies fueled by natural gas and oil or coal by using the best available estimates of greenhouse gas emissions from each fuel cycle (i.e., production, transportation and use). We find that a shift to compressed natural gas vehicles from gasoline or diesel vehicles leads to greater radiative forcing of the climate for 80 or 280 yr, respectively, before beginning to produce benefits. Compressed natural gas vehicles could produce climate benefits on all time frames if the well-to-wheels CH(4) leakage were capped at a level 45-70% below current estimates. By contrast, using natural gas instead of coal for electric power plants can reduce radiative forcing immediately, and reducing CH(4) losses from the production and transportation of natural gas would produce even greater benefits. There is a need for the natural gas industry and science community to help obtain better emissions data and for increased efforts to reduce methane leakage in order to minimize the climate footprint of natural gas.