Multi-year Gas and Particle Sensor Observations in Rural and Urban Malawi

ASHLEY BITTNER, Eben Cross, David Hagan, Jared Bowden, Jason West, Tim Glotfelty, Andrew Grieshop, North Carolina State University

     Abstract Number: 457
     Working Group: Remote and Regional Atmospheric Aerosol

Abstract
In situ air quality measurements are nearly nonexistent in much of southern Africa, including in Malawi, a small land-locked country. From 2017 to 2021, we deployed eight moderate-cost integrated sensor packages that measure CO, CO₂, O₃, NO, NO₂, particulate matter from 0.38 to 17 micrometers in diameter, and meteorological parameters (i.e., wind speed and direction, temperature, relative humidity, pressure, noise, and solar intensity) to four sites in Malawi. We deployed the sensor packages to three regions to characterize spatiotemporal trends and identify contributions from emission sources in urban and rural settings. Diurnal trends from rural village sites show peaks in the ambient CO and PM_2.5 concentration twice a day at mealtimes, likely due to emissions from nearby biomass cookstove activity. Peak concentrations were highest in the rural, residential villages although urban areas had higher background pollution levels. Pollutant concentrations were lower in the wet season for all sites, likely due to atmospheric removal processes (e.g., precipitation) combined with reduced outdoor cooking activity. Annual and seasonally averaged concentrations show that background pollution concentrations across Malawi increase during the hot, dry season, when prescribed burning for agricultural land management is common in the region. Annual cumulative burned area data from southeastern Africa show that most of the seasonal burning activity occurs outside Malawi’s borders, indicating the increase in pollution is likely due to transport of regional emissions from neighboring countries. Analysis will explore how seasonal pollution and weather patterns in Malawi may be influenced by regional wind patterns (via HYSPLIT simulation) and nearby geographical features. Surface observations will be compared to remote sensing and reanalysis data products and with results from chemical transport model simulations. Finally, we will characterize multi-year changes in pollutant concentrations and meteorological conditions (e.g., PM_2.5, temperature), including an exploration of potential impacts from the COVID-19 pandemic.