Air Qual Atmos Health. 2026;19(8):168. doi: 10.1007/s11869-026-02060-y. Epub 2026 Jul 29.
ABSTRACT
Particulate Matter (PM2.5) exposure contributes to the global disease burden, yet its monitoring remains sparse and uneven, with limited ground sensor infrastructure. Road-traffic proxy indicators can provide indirect estimates of PM2.5 where measurements are limited but require context-specific validation. We evaluated three PM2.5 road-traffic-related proxies: (i) population-Weighted Road Network Density (wRND), (ii) Euclidean (straight line) distance from highways (EH), and (iii) Euclidean distance from main roads (EM). We validated these proxies using high-resolution outdoor filtered PM2.5 personal exposure measurements collected over 1 year from 343 postpartum participants in The Gambia, Kenya, and Mozambique. Proxy-PM2.5 associations were assessed using Spearman correlation, and predictive utility was tested using country-specific and global Random Forest (RF) models (3-fold cross-validation), reporting R2, RMSE, and feature importance. Spatial mapping showed heterogeneous proxy-PM2.5 relationships across and within sites, with elevated PM2.5 occurring in both low- and high-proxy contexts. wRND-PM2.5 correlations were weak overall and statistically significant only in Mozambique (r = 0.351; p = 0.005), with non-significant associations in Kenya (r = – 0.041; p = 0.673) and The Gambia (r = – 0.020; p = 0.909). EH-PM2.5 correlations were positive in The Gambia (r = 0.335; p = 0.053) and Mozambique (r = 0.292; p = 0.020) but negative and significant in Kenya (r = – 0.224; p = 0.018). Single-variable RF models performed poorly across all countries (R2 < 0.45) and the Global model (R2 = 0.42). Combining proxies improved performance in Kenya (R2 = 0.52; RMSE = 31.7 µg/m3) and Mozambique (R2 = 0.60; RMSE = 8.9 µg/m3), Global R2 = 0.46; RMSE = 29.1 µg/m3), although in The Gambia, the combined model (R2 = 0.53; RMSE = 37.6 µg/m3) did not exceed the best single-proxy model. Road-network proxies provided limited but context-dependent signals of personal PM₂.₅ exposure. Their performance varied substantially across countries, indicating that road-based indicators should not be used as stand-alone exposure measures in heterogeneous sub-Saharan African settings. Instead, they are most defensible as locally validated components of hybrid exposure models that also incorporate meteorology, land use, biomass burning, household energy, and other non-traffic sources.
SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s11869-026-02060-y.
PMID:42534776 | PMC:PMC13421249 | DOI:10.1007/s11869-026-02060-y
