Showing papers by "Susan C. Anenberg published in 2023"

Sources of air pollution-related health impacts and benefits of radially applied transportation policies in 14 US cities

Abstract: As the world becomes increasingly urbanized, growing populations are exposed to poor ambient air quality and at risk of the associated health outcomes. Urban air quality is affected both by local sources of air pollution and sources outside city borders. Policy-makers who develop air quality policies need to know whether it is most effective to focus on local policies or to spend resources fostering larger regional air quality management cooperation. Identifying the fraction of air pollution exposure from emissions as a function of distance from the city is a critical element of air quality management design. We estimate the health burden associated with exposure to fine particulate matter (PM2.5), ozone (O3), and nitrogen dioxide (NO2) from county-level anthropogenic sources in and around 14 US cities; this analysis is a test-bed to conduct future global analyses. We use adjoint sensitivities calculated from the chemical transport model GEOS-Chem, high resolution satellite-derived surface concentrations of PM2.5 and NO2, and health impact assessment methods. For the 70.2 million people living in these cities, we estimate that 27,740 PM2.5- and O3-related premature deaths and 126,600 NO2-related new asthma cases were attributable to air pollution exposure in 2011. Development within the GEOS-Chem adjoint framework enables sectoral attribution and policy analysis in addition to the rote assessment of impact. We find that 70% of deaths and nearly 100% of these asthma cases were attributable to anthropogenic emissions. There is great variability in the sources of the anthropogenically-related health impacts; within-urban emissions make up 5% in Austin to 56% in Los Angeles and Phoenix (median: 31%) of urban premature deaths and 18% in Austin to 82% in Los Angeles (median: 59.5%) of new asthma cases, with the remaining portions attributable to emissions from outside the urban area. For each city, we estimate the air quality related health benefits associated with the adoption of a vehicle-miles-traveled fee in that city and in multiple spatial regions surrounding the city. The findings suggest that the proportion of urban air pollution that is regional is greater for premature deaths than new asthma cases and for the eastern US than the western US.

A global spatial-temporal land use regression model for nitrogen dioxide air pollution

Abstract: Introduction: The World Health Organization (WHO) recently revised its health guidelines for Nitrogen dioxide (NO2) air pollution, reducing the annual mean NO2 level to 10 μg/m3 (5.3 ppb) and the 24-h mean to 25 μg/m3 (13.3 ppb). NO2 is a pollutant of global concern, but it is also a criteria air pollutant that varies spatiotemporally at fine resolutions due to its relatively short lifetime (~hours). Current models have limited ability to capture both temporal and spatial NO2 variation and none are available with global coverage. Land use regression (LUR) models that incorporate timevarying predictors (e.g., meteorology and satellite NO2 measures) and land use characteristics (e.g., road density, emission sources) have significant potential to address this need. Methods: We created a daily Land use regression model with 50 × 50 m2 spatial resolution using 5.7 million daily air monitor averages collected from 8,250 monitor locations. Results: In cross-validation, the model captured 47%, 59%, and 63% of daily, monthly, and annual global NO2 variation. Daily, monthly, and annual root mean square error were 6.8, 5.0, and 4.4 ppb and absolute bias were 46%, 30%, and 21%, respectively. The final model has 11 variables, including road density and built environments with fine (30 m or less) spatial resolution and meteorological and satellite data with daily temporal resolution. Major roads and satellite-based estimates of NO2 were consistently the strongest predictors of NO2 measurements in all regions. Discussion: Daily model estimates from 2005–2019 are available and can be used for global risk assessments and health studies, particularly in countries without NO2 monitoring.

CO2 emissions from C40 cities: citywide emission inventories and comparisons with global gridded emission datasets

Abstract: Under the leadership of the C40 Cities Climate Leadership Group (C40), approximately 1100 global cities have signed to reach net-zero emissions by 2050. Accurate greenhouse gas emission calculations at the city-scale have become critical. This study forms a bridge between the two emission calculation methods: (a) the city-scale accounting used by C40 cities—the Global Protocol for Community-Scale Greenhouse Gas Emission Inventories (GPC) and (b) the global-scale gridded datasets used by the research community—the Emission Database for Global Atmospheric Research (EDGAR) and Open‐Source Data Inventory for Anthropogenic CO2 (ODIAC). For the emission magnitudes of 78 C40 cities, we find good correlations between the GPC and EDGAR (R 2 = 0.80) and the GPC and ODIAC (R 2 = 0.72). Regionally, African cities show the largest variability in the three emission estimates. For the emission trends, the standard deviation of the differences is ±4.7% yr−1 for EDGAR vs. GPC and is ±3.9% yr−1 for ODIAC vs. GPC: a factor of ∼2 larger than the trends that many C40 cities pledged (net-zero by 2050 from 2010, or −2.5% yr−1). To examine the source of discrepancies in the emission datasets, we assess the impact of spatial resolutions of EDGAR (0.1°) and ODIAC (1 km) on estimating varying-sized cities’ emissions. Our analysis shows that the coarser resolution of EDGAR can artificially decrease emissions by 13% for cities smaller than 1000 km2. We find that data quality of emission factors (EFs) used in GPC inventories vary regionally: the highest quality for European and North American and the lowest for African and Latin American cities. Our study indicates that the following items should be prioritized to reduce the discrepancies between the two emission calculation methods: (a) implementing local-specific/up-to-date EFs in GPC inventories, (b) keeping the global power plant database current, and (c) incorporating satellite-derived CO2 datasets (i.e. NASA OCO-3).

Inequitable Exposures to U.S. Coal Power Plant–Related PM2.5: 22 Years and Counting

Abstract: Background: Emissions from coal power plants have decreased over recent decades due to regulations and economics affecting costs of providing electricity generated by coal vis-à-vis its alternatives. These changes have improved regional air quality, but questions remain about whether benefits have accrued equitably across population groups. Objectives: We aimed to quantify nationwide long-term changes in exposure to particulate matter (PM) with an aerodynamic diameter ≤2.5μm (PM2.5) associated with coal power plant SO2 emissions. We linked exposure reductions with three specific actions taken at individual power plants: scrubber installations, reduced operations, and retirements. We assessed how emissions changes in different locations have influenced exposure inequities, extending previous source-specific environmental justice analyses by accounting for location-specific differences in racial/ethnic population distributions. Methods: We developed a data set of annual PM2.5 source impacts (“coal PM2.5”) associated with SO2 emissions at each of 1,237 U.S. coal-fired power plants across 1999–2020. We linked population-weighted exposure with information about each coal unit’s operational and emissions-control status. We calculate changes in both relative and absolute exposure differences across demographic groups. Results: Nationwide population-weighted coal PM2.5 declined from 1.96μg/m3 in 1999 to 0.06 μg/m3 in 2020. Between 2007 and 2010, most of the exposure reduction is attributable to SO2 scrubber installations, and after 2010 most of the decrease is attributable to retirements. Black populations in the South and North Central United States and Native American populations in the western United States were inequitably exposed early in the study period. Although inequities decreased with falling emissions, facilities in states across the North Central United States continue to inequitably expose Black populations, and Native populations are inequitably exposed to emissions from facilities in the West. Discussion: We show that air quality controls, operational adjustments, and retirements since 1999 led to reduced exposure to coal power plant related PM2.5. Reduced exposure improved equity overall, but some populations continue to be inequitably exposed to PM2.5 associated with facilities in the North Central and western United States. https://doi.org/10.1289/EHP11605

Thank You to Our 2022 Peer Reviewers

Abstract: Key Points The editors thank the 2022 peer reviewers In 2022, GeoHealth benefited from 333 reviews provided by 245 of our peers A number of individuals submitted multiple reviews for GeoHealth in 2022

Erratum: Inequitable Exposures to U.S. Coal Power Plant–Related PM2.5: 22 Years and Counting

Abstract: and Counting Lucas R.F. Henneman, Munshi Md Rasel, Christine Choirat, Susan C. Anenberg, and Corwin Zigler Environ Health Perspect 131(3):037005 (2023), https://doi.org/10.1289/EHP11605 Table 1 incorrectly labeled low-operation year population-weighted exposure as “High-operation years” in the “Avoided: reduced operation after scrubber” naming convention. In addition, Figure 2 was presented in poor quality in the pdf version (not the html).

Global Atmospheric Composition Needs from Future Ultraviolet-Visible-Near-Infrared (UV-Vis-NIR) NOAA Satellite Instruments

Abstract: © 2023 American Meteorological Society. For information regarding reuse of this content and general copyright information, consult the AMS Copyright Policy (www.ametsoc.org/PUBSReuseLicenses). Corresponding authors: Monika Kopacz, monika.kopacz@noaa.gov; Victoria Breeze, victoria.breeze@noaa.gov

Quantifying disparities in air pollution exposures across the United States using home and work addresses

Abstract: While human mobility plays a crucial role in determining air pollution exposures and health risks, research to-date has assessed risks based solely on residential location. Here we leveraged a database of ~ 130 million workers in the US and published PM2.5 data between 2011-2018 to explore how incorporating information on both workplace and residential location changes our understanding of disparities in air pollution exposure. In general, we observed higher workplace exposures (W) relative to home exposures (H), as well as increasing exposures for non-white and less educated workers relative to the national average. Workplace exposure disparities were higher among racial and ethnic groups and job-types than by income, education, age, and sex. Not considering workplace exposures can lead to systematic underestimations in disparities to exposure among these subpopulations. We also quantified the error in assigning workers H, instead of a weighted home-and-work (HW) exposure. We observed that biases in associations between PM2.5 and health impacts by using H instead of HW were highest among urban, younger populations.