A comprehensive study of the COVID-19 impact on PM2.5 levels over the contiguous United States: A deep learning approach.

We investigate the impact of the COVID-19 outbreak on PM2.5 levels in eleven urban environments across the United States: Washington DC, New York, Boston, Chicago, Los Angeles, Houston, Dallas, Philadelphia, Detroit, Phoenix, and Seattle. We estimate daily PM2.5 levels over the contiguous U.S. in March-May 2019 and 2020, and leveraging a deep convolutional neural network, we find a correlation coefficient, an index of agreement, a mean absolute bias, and a root mean square error of 0.90 (0.90), 0.95 (0.95), 1.34 (1.24) µg/m3, and 2.04 (1.87) µg/m3, respectively. Results from Google Community Mobility Reports and estimated PM2.5 concentrations show a greater reduction of PM2.5 in regions with larger decreases in human mobility and those in which individuals remain in their residential areas longer. The relationship between vehicular PM2.5 (i.e., the ratio of vehicular PM2.5 to other sources of PM2.5) emissions and PM2.5 reductions (R = 0.77) in various regions indicates that regions with higher emissions of vehicular PM2.5 generally experience greater decreases in PM2.5. While most of the urban environments ⸺ Washington DC, New York, Boston, Chicago, Los Angeles, Houston, Dallas, Philadelphia, Detroit, and Seattle ⸺ show a decrease in PM2.5 levels by 21.1%, 20.7%, 18.5%, 8.05%, 3.29%, 3.63%, 6.71%, 4.82%, 13.5%, and 7.73%, respectively, between March-May of 2020 and 2019, Phoenix shows a 5.5% increase during the same period. Similar to their PM2.5 reductions, Washington DC, New York, and Boston, compared to other cities, exhibit the highest reductions in human mobility and the highest vehicular PM2.5 emissions, highlighting the great impact of human activity on PM2.5 changes in eleven regions. Moreover, compared to changes in meteorological factors, changes in pollutant concentrations, including those of black carbon, organic carbon, SO2, SO4, and especially NO2, appear to have had a significantly greater impact on PM2.5 changes during the study period.

Cardiovascular impacts and micro-environmental exposure factors associated with continuous personal PM2.5 monitoring.

The US Environmental Protection Agency's (US EPA) Detroit Exposure and Aerosol Research Study (DEARS) has provided extensive data on human exposures to a wide variety of air pollutants and their impact on human health. Previous analyses in the DEARS revealed select cardiovascular (CV) health outcomes such as increase in heart rate (HR) associated with hourly based continuous personal fine particulate matter (PM2.5) exposures in this adult, non-smoking cohort. Examination of time activity diary (TAD), follow-up questionnaire (FQ) and the continuous PM2.5 personal monitoring data provided the means to more fully examine the impact of discreet human activity patterns on personal PM2.5 exposures and changes in CV outcomes. A total of 329 343 min-based PM2.5 personal measurements involving 50 participants indicated that ∼75% of these total events resulted in exposures <35 µg/m(3). Cooking and car-related events accounted for nearly 10% of the hourly activities that were identified with observed peaks in personal PM2.5 exposures. In-residence cooking often resulted in some of the highest incidents of 1 min exposures (33.5-17.6 µg/m(3)), with average peaks for such events in excess of 209 µg/m(3). PM2.5 exposure data from hourly based personal exposure activities (for example,, cooking, cleaning and household products) were compared with daily CV data from the DEARS subject population. A total of 1300 hourly based lag risk estimates associated with changes in brachial artery diameter and flow-mediated dilatation (BAD and FMD, respectively), among others, were defined for this cohort. Findings indicate that environmental tobacco smoke (ETS) exposures resulted in significant HR changes between 3 and 7 h following the event, and exposure to smells resulted in increases in BAD on the order of 0.2-0.7 mm/µg/m(3). Results demonstrate that personal exposures may be associated with several biological responses, sometimes varying in degree and direction in relation to the extent of the exposure.

The Near-Road Exposures and Effects of Urban Air Pollutants Study (NEXUS): study design and methods.

The Near-Road Exposures and Effects of Urban Air Pollutants Study (NEXUS) was designed to examine the relationship between near-roadway exposures to air pollutants and respiratory outcomes in a cohort of asthmatic children who live close to major roadways in Detroit, Michigan USA. From September 2010 to December 2012 a total of 139 children with asthma, ages 6-14, were enrolled in the study on the basis of the proximity of their home to major roadways that carried different amounts of diesel traffic. The goal of the study was to investigate the effects of traffic-associated exposures on adverse respiratory outcomes, biomolecular markers of inflammatory and oxidative stress, and how these exposures affect the frequency and severity of respiratory viral infections in a cohort of children with asthma. An integrated measurement and modeling approach was used to quantitatively estimate the contribution of traffic sources to near-roadway air pollution and evaluate predictive models for assessing the impact of near-roadway pollution on children's exposures. Two intensive field campaigns were conducted in Fall 2010 and Spring 2011 to measure a suite of air pollutants including PM2.5 mass and composition, oxides of nitrogen (NO and NO2), carbon monoxide, and black carbon indoors and outdoors of 25 participants' homes, at two area schools, and along a spatial transect adjacent to I-96, a major highway in Detroit. These data were used to evaluate and refine models to estimate air quality and exposures for each child on a daily basis for the health analyses. The study design and methods are described, and selected measurement results from the Fall 2010 field intensive are presented to illustrate the design and successful implementation of the study. These data provide evidence of roadway impacts and exposure variability between study participants that will be further explored for associations with the health measures.

The Environmental Protection Agency's Community-Focused Exposure and Risk Screening Tool (C-FERST) and its potential use for environmental justice efforts.

OBJECTIVES: Our primary objective was to provide higher quality, more accessible science to address challenges of characterizing local-scale exposures and risks for enhanced community-based assessments and environmental decision-making. METHODS: After identifying community needs, priority environmental issues, and current tools, we designed and populated the Community-Focused Exposure and Risk Screening Tool (C-FERST) in collaboration with stakeholders, following a set of defined principles, and considered it in the context of environmental justice. RESULTS: C-FERST is a geographic information system and resource access Web tool under development for supporting multimedia community assessments. Community-level exposure and risk research is being conducted to address specific local issues through case studies. CONCLUSIONS: C-FERST can be applied to support environmental justice efforts. It incorporates research to develop community-level data and modeled estimates for priority environmental issues, and other relevant information identified by communities. Initial case studies are under way to refine and test the tool to expand its applicability and transferability. Opportunities exist for scientists to address the many research needs in characterizing local cumulative exposures and risks and for community partners to apply and refine C-FERST.

Assessment and application of national environmental databases and mapping tools at the local level to two community case studies.

Communities are concerned over pollution levels and seek methods to systematically identify and prioritize the environmental stressors in their communities. Geographic information system (GIS) maps of environmental information can be useful tools for communities in their assessment of environmental-pollution-related risks. Databases and mapping tools that supply community-level estimates of ambient concentrations of hazardous pollutants, risk, and potential health impacts can provide relevant information for communities to understand, identify, and prioritize potential exposures and risk from multiple sources. An assessment of existing databases and mapping tools was conducted as part of this study to explore the utility of publicly available databases, and three of these databases were selected for use in a community-level GIS mapping application. Queried data from the U.S. EPA's National-Scale Air Toxics Assessment, Air Quality System, and National Emissions Inventory were mapped at the appropriate spatial and temporal resolutions for identifying risks of exposure to air pollutants in two communities. The maps combine monitored and model-simulated pollutant and health risk estimates, along with local survey results, to assist communities with the identification of potential exposure sources and pollution hot spots. Findings from this case study analysis will provide information to advance the development of new tools to assist communities with environmental risk assessments and hazard prioritization.

Tools available to communities for conducting cumulative exposure and risk assessments.

This paper summarizes and assesses over 70 tools that could aid with gathering information and taking action on environmental issues related to community-based cumulative risk assessments (CBCRA). Information on tool use, development and research needs, was gathered from websites, documents, and CBCRA program participants and researchers, including 25 project officers who work directly with community groups. The tools were assessed on the basis of information provided by project officers, community members, CBCRA researchers, and by case study applications. Tables summarize key environmental issues and tool features: (1) a listing of CBCRA-related environmental issues of concern to communities; (2) web-based tools that map environmental information; (3) step-by-step guidance documents; (4) databases of environmental information; and (5) computer models that simulate human exposure to chemical stressors. All tools described here are publicly available, with the focus being on tools developed by the US Environmental Protection Agency. These tables provide sources of information to promote risk identification and prioritization beyond risk perception approaches, and could be used by CBCRA participants and researchers. The purpose of this overview is twofold: (1) To present a comprehensive, though not exhaustive, summary of numerous tools that could aid with performing CBCRAs; and (2) To use this toolset as a sample of the current state of CBCRA tools to critically examine their utility and guide research for the development of new and improved tools.

In-vehicle measurement of ultrafine particles on compressed natural gas, conventional diesel, and oxidation-catalyst diesel heavy-duty transit buses.

Many metropolitan transit authorities are considering upgrading transit bus fleets to decrease ambient criteria pollutant levels. Advancements in engine and fuel technology have lead to a generation of lower-emission buses in a variety of fuel types. Dynamometer tests show substantial reductions in particulate mass emissions for younger buses (<10 years) over older models, but particle number reduction has not been verified in the research. Recent studies suggest that particle number is a more important factor than particle mass in determining health effects. In-vehicle particle number concentration measurements on conventional diesel, oxidation-catalyst diesel and compressed natural gas transit buses are compared to estimate relative in-vehicle particulate exposures. Two primary consistencies are observed from the data: the CNG buses have average particle count concentrations near the average concentrations for the oxidation-catalyst diesel buses, and the conventional diesel buses have average particle count concentrations approximately three to four times greater than the CNG buses. Particle number concentrations are also noticeably affected by bus idling behavior and ventilation options, such as, window position and air conditioning.