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V. Faye McNeill

Publications and source records attributed to V. Faye McNeill.

Leveraging Scientific Community Knowledge for Air Quality Model Chemistry Parameterizations

Air pollution contributes to adverse health outcomes. Approximately 121 million people in the United States—one third of the population—live where National Ambient Air Quality Standards (NAAQS) are violated. In most cases, the criteria pollutants exceeding standards are ozone (O 3 ) and fine particles (PM 2.5 ). In addition, 188 substances known or suspected to cause cancer or other serious health effects are designated as hazardous air pollutants (HAPs). Essentially, all O 3 and significant portions of PM 2.5 and HAPs are produced in the atmosphere through chemical and physical processes. In the case of PM 2.5 , subcomponents formed primarily from precursor gases—sulfate, nitrate, ammonium, and secondary organic aerosol (SOA)—account for 60% of the U.S. county-level annual mean concentration. In addition, 47% of the cancer risk and 25% of the noncancer risk from HAPs have been attributed to atmospheric chemistry rather than direct emissions. In this article, we introduce the role of chemical mechanisms in air quality models, a new atmospheric science community effort, and needs for further mechanism development.

Havala O.T. Pye↗

First Measurements of Ambient PM2.5 in Kinshasa, Democratic Republic of Congo and Brazzaville, Republic of Congo Using Field-calibrated Low-cost Sensors

Estimates of air pollution mortality in sub-Saharan Africa are limited by a lack of surface observations of fine particulate matter (PM2.5). Despite being large metropolises, Kinshasa, Democratic Republic of the Congo (DRC), population 14.3 million, and Brazzaville, Republic of the Congo (ROC), population 2.4 million, have no reference air pollution monitors at the time of writing. Recently, a few reference monitors have been deployed in other parts of sub-Saharan Africa, including Kampala, Uganda. A low-cost PurpleAir PM2.5 monitor was collocated next to the Kampala US Embassy BAM-1020 (Met One Beta Attenuation Monitor) starting in August 2019. Raw PurpleAir data are strongly correlated with the BAM (r(exp 2) = 0.88), but have a mean absolute error of approximately 14 μg/cu.m. Two calibration models, multiple linear regression and a random forest approach, decrease mean absolute error (MAE) from 14.3 μg/cu.m to 3.4 µg/cu.m or less and improve the the r(exp 2) from 0.88 to 0.96. Given )the similarity in climate and emissions in Kampala, we apply the collocated field correction factors to four PurpleAir sensors in Kinshasa, DRC and one in neighboring Brazzaville, ROC deployed beginning April 2018. Annual average PM2.5 for 2019 in Kinshasa is estimated at 43.5 µg/cu.m, more than 4 times higher than WHO Interim Target 1 of 10 µg/cu.m. Surface PM2.5 and aerosol optical depth were each about 40% lower during the 2020 COVID19 lockdown period compared to the same time period in 2019, which cannot be explained by changes in meteorology or wildfire emissions alone. Our results highlight the need for clean air solutions implementation in the Congo.

Celeste McFarlane↗