High-Resolution Spatial and Temporal Characterization of Particulate Matter in Kigali Using Mobile Sampling
THEOBARD HABINEZA, Albert A. Presto, Allen Robinson, Carnegie Mellon University
Abstract Number: 35
Working Group: Chemicals of Emerging Concern in Indoor and Outdoor Aerosol: Sources, Vectors, Reactivity, and Impacts
Abstract
Air pollution poses a significant threat to public health, the environment, and the climate, with impacts varying across neighborhoods due to localized point and mobile sources. Integrating mobile sampling with long-term stationary monitoring enables a multidimensional understanding of pollutant dynamics, essential for identifying localized emissions, temporal patterns, exposure disparities and environmental injustice. His study combined mobile and stationary monitoring of particulate matter mass (PM2.5 and PM10) and black carbon (BC) in Kigali, Rwanda, to identify pollution hotspots, overlaps between activities and pollution levels, and to achieve higher temporal and spatial resolution of PM and BC concentrations and composition. Three stationary BC monitoring sites (urban background, near-road, and urban) and mobile sampling across five neighborhood types (urban residential, urban traditional, traffic-dominated, commercial, and mixed) were conducted. As was expected, urban background recorded lower average BC concentration (2.2 µg/m³) making a 40% and 60% of the mean BC concentrations in urban roadside and urban site respectively. The diurnal patterns in BC all had peaks associated with the morning and afternoon rush hours. This morning peak was most intense at the near road site (6.8 µg/m³) where it was 2.2 times higher than the peak at the urban background and 1.6 times higher than at the urban site. Mobile sampling showed that traffic-dominated neighborhoods recorded the highest BC concentrations (median 12 µg/m³). The BC/PM2.5 ratio in high traffic neighborhoods was 18%. This is 4 times higher than in the urban residential neighborhood indicating contributions from idling vehicles and cooking activities. Traditional neighborhoods recorded higher PM levels (PM10 = 136 µg/m³, PM2.5 = 69 µg/m³) attributable to emissions from unpaved roads and charcoal-based cooking and lower in the urban residential area (PM2.5 52 ug/m³, PM10 = 80 ug/m³), Commercial areas exhibited numerous hot spots associated with micro-industries, schools, and incinerators. Findings underscore the need for targeted mitigation strategies, transitions to cleaner energy, and urban planning that separates residential, commercial, and industrial activities.