Celeste McFarlane1,2, Paulson Kasereka Isevulambire3, Raymond Sinsi Lumbuenamo4, Arnold Murphy Elouma Ndinga5, Ranil Dhammapala6, Xiaomeng Jin7, V. Faye McNeill2,8, Carl Malings9,10, R. Subramanian9,11,12, Daniel M. Westervelt This email address is being protected from spambots. You need JavaScript enabled to view it.1,13

1 Lamont-Doherty Earth Observatory of Columbia University, New York, USA
2 Columbia University, Department of Chemical Engineering, New York, USA
3 Ecole Régionale postuniversitaire d’Aménagement et de Gestion Intégrés des Forêts et Territoire tropicaux (ERAIFT) Kinshasa, Democratic Republic of Congo
4 World Bank Group, Kinshasa, Democratic Republic of Congo
5 Département de chimie, Université Marien Ngouabi, Brazzaville, Republic of Congo
6 Washington State Department of Ecology, Washington, USA
7 Department of Chemistry, University of California Berkeley, USA
8 Columbia University, Department of Earth and Environmental Sciences, New York, USA
9 OSU-EFLUVE - Observatoire Sciences de l’Univers-Enveloppes Fluides de la Ville à l’Exobiologie, Université Paris-Est-Créteil, France
10 NASA Postdoctoral Program Fellow, Goddard Space Flight Center, Greenbelt, Maryland, USA
11 Center for Atmospheric Particle Studies, Carnegie Mellon University, Pittsburgh, PA 15218, USA
12 Kigali Collaborative Research Centre, Kigali, Rwanda
13 NASA Goddard Institute for Space Studies, New York, USA


Received: November 4, 2020
Revised: February 6, 2021
Accepted: March 22, 2021

 Copyright The Author(s). This is an open access article distributed under the terms of the Creative Commons Attribution License (CC BY 4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are cited.


Download Citation: ||https://doi.org/10.4209/aaqr.200619  


Cite this article:

McFarlane, C., Isevulambire, P.K., Lumbuenamo, R.S., Ndinga, A.M.E., Dhammapala, R., Jin, X., McNeill, V.F., Malings, C., Subramanian, R. Westervelt, D.M. (2021). First Measurements of Ambient PM2.5 in Kinshasa, Democratic Republic of Congo and Brazzaville, Republic of Congo Using Field-calibrated Low-cost Sensors. Aerosol Air Qual. Res. https://doi.org/10.4209/aaqr.200619


HIGHLIGHTS

  • We developed multiple linear regression applied to PM2.5 data in Kampala, Uganda.
  • Mean absolute error reduced from 14.8 µg m3 in the raw PM2.5 dataset to 3.4 µg m3.
  • The first ever measurements of ambient PM2.5 are presented in Congo.
  • Annual mean PM2.5 is 4 times the WHO Interim Target 1.
  • Surface PM2.5 and AOD were each about 40% lower in the region COVID19.
 

ABSTRACT


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 (r2 = 0.88), but have a mean absolute error of approximately 14 μg m-3. Two calibration models, multiple linear regression and a random forest approach, decrease mean absolute error (MAE) from 14.3 μg m-3 to 3.4 µg m-3 or less and improve the the r2 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 m-3, more than 4 times higher than WHO Interim Target 1 of 10 µg m-3. 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.


Keywords: Low-cost sensors, Particulate matter, Air quality, Africa




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