article · ACS ES&T Air
Kinshasa, with a population of 16.3 million, has historically experienced limited air quality monitoring. To address this, an aggregated multisensor network was deployed, combining a MetOne Beta Attenuation Monitor reference device with a QuantAQ Modulair sensor measuring several particulate sizes and gaseous pollutants. The low-cost sensor demonstrated strong initial correlation with the reference monitor, and applying a multiple linear regression correction factor further reduced the mean absolute error. By combining particle size data, gaseous pollutant measurements, and wind data through non-negative matrix factorisation, the investigation identified three primary particulate matter sources. These include secondary particles from local combustion linked with carbon monoxide, primary submicron particles from combustion, and regional biomass burning. These initial findings from the multisensor network highlight the sources driving fine particulate pollution and underline the need to implement clean air solutions in the Democratic Republic of the Congo.
Fine particulate pollution poses significant public health risks, yet major cities such as Kinshasa have historically lacked comprehensive air quality tracking. Demonstrating that calibrated, low-cost sensors can reliably identify pollution levels and their underlying sources provides an accessible pathway for tracking urban air quality. This evidence can assist environmental agencies and policymakers in designing targeted mitigation measures to improve public health across the region.
The methodology demonstrates applied, field-tested monitoring using low-cost sensor hardware combined with statistical calibration and source apportionment algorithms. Environmental authorities, municipal governments, and air quality monitoring enterprises could utilise this approach to deploy affordable sensor networks in resource-constrained urban environments. As an applied deployment combining commercial sensors with tailored calibration models, it offers a near-term pathway for urban environmental management and pollution tracking services.
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Despite having a population of 16.3 million, Kinshasa, Democratic Republic of the Congo (DRC), has had little attention toward air quality monitoring. We deployed a MetOne Beta Attenuation Monitor (BAM-1020) for reference PM2.5 and a QuantAQ Modulair, the latter of which includes measurements of gas-phase NO2, O3, CO, and CO2, in addition to PM1, PM2.5, and PM10. Here we present the first results from this aggregated, multisensor, multispecies network in DRC. We first compare the Modulair against the BAM-1020, finding an r2 of 0.76 and a mean absolute error (MAE) of 6.97 μg m–3 (hourly data). We develop a correction factor using multiple linear regression, improving MAE to 5.54 μg m–3. We leverage gaseous pollutant concentrations, particle size distribution data, and anemometer data to draw conclusions about the sources of PM2.5 in Kinshasa. We link factors resolved from a non-negative matrix factorization method using the gaseous and particle bin concentrations to source profiles. We find a 3-factor solution that points to a CO-dominated, supermicron particle source indicative of secondary particles from local combustion, along with a submicron particle-dominated source indicative of primary particles from combustion and a regional biomass burning source. Our results highlight the need for the implementation of clean air solutions in the DRC.
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DOI: 10.1021/acsestair.3c00024
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