The Environmental Protection Agency (EPA) provides access to information on a variety of topics related to the environment and strives to inform citizens of health risks. The EPA also has an extensive library network that consists of 26 libraries throughout the United States, which provide access to a plethora of information to EPA employees, scientists, and researchers. The EPA implemented a reorganization project to digitize their materials so they would be more accessible to a wider range of users, but this plan was drastically accelerated when the EPA was threatened with a budget cut. It chose to close and reduce the hours and services of some of their libraries. As a result, the agency was accused of denying users the “right to know” by making information unavailable, not providing an adequate strategic plan, and discarding vital materials. This case study explores the background of the digitization project, the practices implemented, and the critiques of the project.

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The Environmental Protection Agency

The coronavirus disease 2019 (COVID-19) pandemic has disproportionately affected racial and ethnic minority groups, with high rates of death in African American, Native American, and LatinX communities Although the mechanisms of these disparities are being investigated, they can be conceived as arising from biomedical factors as well as social determinants of health Minority groups are disproportionately affected by chronic medical conditions and lower access to healthcare that may portend worse COVID-19 outcomes Furthermore, minority communities are more likely to experience living and working conditions that predispose them to worse outcomes Underpinning these disparities are long-standing structural and societal factors that the COVID-19 pandemic has exposed Clinicians can partner with patients and communities to reduce the short-term impact of COVID-19 disparities while advocating for structural change

The Disproportionate Impact of COVID-19 on Racial and Ethnic Minorities in the United States.

Watts N, Amann M, Ayeb-Karlsson S, et al. The Lancet Countdown on health and climate change: from 25 years of inaction to a global transformation for public health. Lancet 2018; 391: 581–630—In this Review (published online first on Oct 30, 2017), Jonathan Chambers, Ian Hamilton, Robert Lowe, and Steve Pye's affiliation has been corrected to UCL Energy Institute, London, UK; Fereidoon Owfi and Mahnaz Rabbaniha's affiliation has been corrected to Iranian Fisheries Science Research Institute, AREEO, Tehran, Iran; Meisam Tabatabaei's affiliation has been corrected to Biofuel Research Team, Agricultural Biotechnology Research Institute of Iran, AREEO, Karaj, Iran; and Ali Mohammad Latifi's affiliation has been corrected to Applied Biotechnology Research Center, Baqiyatallah University of Medical Sciences, Tehran, Iran. In figures 31, 33, and 34, the formatting of the currency in the y-axis title has been corrected to US$2016. In figure 36, the y-axis title has been corrected to “Fossil fuel consumption subsidies (US$2016 billion)”. In figure 37, RGGI has been explained in the figure legend and an asterisk symbol has been removed from the figure. In Table 2, CO2 has been spelled out as carbon dioxide. These corrections have been made to the online version as of Nov 23, 2017, and the printed Review is correct.

The Lancet Countdown on health and climate change: from 25 years of inaction to a global transformation for public health (vol 391, pg 540, 2017)

Decades of research have demonstrated that diabetes affects racial and ethnic minority and low-income adult populations in the U.S. disproportionately, with relatively intractable patterns seen in these populations’ higher risk of diabetes and rates of diabetes complications and mortality (1). With a health care shift toward greater emphasis on population health outcomes and value-based care, social determinants of health (SDOH) have risen to the forefront as essential intervention targets to achieve health equity (2–4). Most recently, the COVID-19 pandemic has highlighted unequal vulnerabilities borne by racial and ethnic minority groups and by disadvantaged communities. In the wake of concurrent pandemic and racial injustice events in the U.S., the American College of Physicians, American Academy of Pediatrics, Society of General Internal Medicine, National Academy of Medicine, and other professional organizations have published statements on SDOH (5–8), and calls to action focus on amelioration of these determinants at individual, organizational, and policy levels (9–11).

In diabetes, understanding and mitigating the impact of SDOH are priorities due to disease prevalence, economic costs, and disproportionate population burden (12–14). In 2013, the American Diabetes Association (ADA) published a scientific statement on socioecological determinants of prediabetes and type 2 diabetes (15). Toward the goal ofunderstanding and advancing opportunities for health improvement among the population with diabetes through addressing SDOH, ADA convened the current SDOH and diabetes writing committee, prepandemic, to review the literature on 1 ) associations of SDOH with diabetes risk and outcomes and 2 ) impact of interventions targeting amelioration of SDOH on diabetes outcomes. This article begins with an overview of key definitions and SDOH frameworks. The literature review focuses primarily on U.S.-based studies of adults with diabetes and on five SDOH: socioeconomic status (education, income, occupation); neighborhood and physical environment (housing, built environment, toxic environmental …

/pdf/social-determinants-of-health-and-diabetes-a-scientific-5gt7qvg60y.pdf

Social Determinants of Health and Diabetes: A Scientific Review.

Fine particulate matter (PM2.5) air pollution exposure is the largest environmental health risk factor in the United States. Here, we link PM2.5 exposure to the human activities responsible for PM2.5 pollution. We use these results to explore "pollution inequity": the difference between the environmental health damage caused by a racial-ethnic group and the damage that group experiences. We show that, in the United States, PM2.5 exposure is disproportionately caused by consumption of goods and services mainly by the non-Hispanic white majority, but disproportionately inhaled by black and Hispanic minorities. On average, non-Hispanic whites experience a "pollution advantage": They experience ∼17% less air pollution exposure than is caused by their consumption. Blacks and Hispanics on average bear a "pollution burden" of 56% and 63% excess exposure, respectively, relative to the exposure caused by their consumption. The total disparity is caused as much by how much people consume as by how much pollution they breathe. Differences in the types of goods and services consumed by each group are less important. PM2.5 exposures declined ∼50% during 2002-2015 for all three racial-ethnic groups, but pollution inequity has remained high.

/pdf/inequity-in-consumption-of-goods-and-services-adds-to-racial-58ewewfs98.pdf

Inequity in consumption of goods and services adds to racial-ethnic disparities in air pollution exposure.

Racial-ethnic minorities in the United States are exposed to disproportionately high levels of ambient fine particulate air pollution (PM2.5), the largest environmental cause of human mortality. However, it is unknown which emission sources drive this disparity and whether differences exist by emission sector, geography, or demographics. Quantifying the PM2.5 exposure caused by each emitter type, we show that nearly all major emission categories-consistently across states, urban and rural areas, income levels, and exposure levels-contribute to the systemic PM2.5 exposure disparity experienced by people of color. We identify the most inequitable emission source types by state and city, thereby highlighting potential opportunities for addressing this persistent environmental inequity.

https://advances.sciencemag.org/content/advances/7/18/eabf4491.full.pdf

PM2.5 polluters disproportionately and systemically affect people of color in the United States.

To the extent that pollution and population are spatially correlated, air quality modeling with coarse-resolution horizontal grids may systematically underpredict exposures and disparities in exposure among demographic groups (i.e., environmental injustice). We use InMAP, a reduced-complexity air pollution model, to quantify how estimates of year-2014 fine particulate matter (PM2.5) exposure in the United States vary with model spatial resolution, for a variable-resolution grid. We test five grids, with population-weighted average grid cell edge lengths ranging from 5.9 to 69 km. We find that model-estimated PM2.5 exposure, and exposure disparities among racial-ethnic groups, are lower with coarse grids than with fine grids: switching from our coarsest- to finest-resolution grid increases the calculated population-weighted average exposure by 27% (from 6.6 to 8.3 μg m–3) and causes the estimated difference in average exposure between minorities and whites to increase substantially (from 0.4 to 1.6 μg m–3)...

Effect of Model Spatial Resolution on Estimates of Fine Particulate Matter Exposure and Exposure Disparities in the United States

Monitoring and control the Wire Arc Additive Manufacturing process using artificial intelligence techniques: a review

This directory contains data for performing InMAP model runs and evaluations. To the extent that any of the data is covered by third party licenses, it is the responsibility of the user to follow the terms of those licenses. A description of the contents of this directory is below:

- annual_all_2005.csv: U.S. EPA annual average measured air pollution data for year 2005, downloaded from EPA AirData at http://aqsdr1.epa.gov/aqsweb/aqstmp/airdata/download_files.html. 

- census2013blckgrp.shp and associated files: US Census Bureau estimates of average population counts for several demographic groups for years 2011-2015. Descriptive and license information regarding these files can be found in census2013blckgrp_README.txt

- InMAPData_v1.3.0.gob: InMAP variable grid resolution input data for the continental U.S. year 2005 for use as the "VariableGridData" variable in the InMAP configuration file. It was created with the 'inmap grid' command.

- InMAPData_v1.2.0.ncf: Regular-grid InMAP input data for the continental U.S. year 2005 for use as the "InMAPData" variable in the InMAP configuration file. It was created from WRF-Chem simulation outputs with the 'inmap preproc' command. This file has not changed since version 1.2. Information regarding the WRF-Chem simulations is available in: Tessum, C. W., Hill, J. D., & Marshall, J. D. (2015). Twelve-month, 12 km resolution North American WRF-Chem v3.4 air quality simulation: performance evaluation. Geosci. Model Dev., 8(4), 957–973. http://doi.org/10.5194/gmd-8-957-2015

- mortalityRates2013.shp and associated files: Year 2013 all-population, all-cause mortality rate data from the CDC WONDER database (http://wonder.cdc.gov). Descriptive information regarding these files can be found in mortalityRates2013_README.txt

- states.shp and related files: U.S. state boundaries for making evaluation maps.

- la_test directory: Files with the area surrounding the city of Los Angeles extracted for faster-running tests.

- 2005_emissions directory: Anthropogenic emissions from the 2005 U.S. EPA National Emissions Inventory (NEI), processed using the AEP model (https://github.com/ctessum/aep) (files Elevated.shp and GroundLevel.shp), and biogenic and wilfire emissions (file bioFireEmis.shp) calculated following the methods in Tessum, C. W., Hill, J. D., & Marshall, J. D. (2015). Twelve-month, 12 km resolution North American WRF-Chem v3.4 air quality simulation: performance evaluation. Geosci. Model Dev., 8(4), 957–973. http://doi.org/10.5194/gmd-8-957-2015

- singleSource directory: Regular-grid InMAP input data for los Angeles for year 2005 for use as the "InMAPData" variable in the InMAP configuration file. It was created from WRF-Chem simulation outputs with the 'inmap preproc' command, based on a 9 - 3 - 1 km nested WRF-Chem simulation which only included emissions from a single source in downtown Los Angeles. The directory includes four different InMAPData_*.ncf files, three corresponding to the three WRF-Chem domains and one for a nested InMAP simulation. The directory also contains an inmapEmis.shp shapefile and supporting files that contain emissions matching the emissions used in the WRF-Chem simulation. More information about this simulation can be found in the InMAP model description article.

- FuelScenarios directory: This directory contains two subdirectories. "Emissions" contains spatial emissions information corresponding to the emissions scenarios described at doi: 10.1073/pnas.1406853111. "Concentrations" contains changes in pollutant concentrations resulting from WRF-Chem simulations of the emissions scenarios, also described and discussed at doi: 10.1073/pnas.1406853111.

David Paolella

Papers

Inequity in consumption of goods and services adds to racial-ethnic disparities in air pollution exposure.

PM2.5 polluters disproportionately and systemically affect people of color in the United States.

Effect of Model Spatial Resolution on Estimates of Fine Particulate Matter Exposure and Exposure Disparities in the United States

Monitoring and control the Wire Arc Additive Manufacturing process using artificial intelligence techniques: a review

Evaluation Data For The Intervention Model For Air Pollution (Inmap) Version 1.3