The impacts of agricultural and urban emissions on health and on the PM2.5 composition in the most polluted Mexican city

Abstract

This study presents an integrated assessment of fine particulate matter (PM_2.5) in the Toluca Valley Metropolitan Area (TVMA), the most polluted urban region in Mexico. A year-long monitoring campaign at two representative sites combined detailed chemical characterization, carbonaceous tracers, receptor modeling, trajectory analysis, and machine learning to identify emission sources, investigate the processes controlling PM_2.5 variability, and assess their implications for human health and air quality management. Chemical characterization reconstructed 98% of the PM_2.5 mass, dominated by OC, SO₄²⁻, NH₄⁺, EC, NO₃⁻, Cl⁻, and K⁺, shifting from an alkaline potential at the urban site to an acidic balance at the periurban site. Carbonaceous tracers, together with Positive Matrix Factorization (PMF) suggested diesel exhaust, soil resuspension, biomass burning, and secondary aerosol formation as the dominant sources. HYSPLIT backward trajectories and an exploratory Random Forest analysis indicated that pollutant accumulation is driven by regional air-mass recirculation and nonlinear meteorological controls. The annual mean PM_2.5 concentration exceeded the updated WHO guideline by a factor of eight, and health risk assessment identified Pb, Ni, Cr, Mn, and Cd as the principal contributors to non-carcinogenic risk (HI > 1), particularly during the cold-dry season, highlighting the importance of reducing the overall particulate burden. By integrating complementary analytical approaches, this research demonstrates that PM_2.5 pollution in the TVMA results from the interaction of local emissions, regional transport, and meteorological processes, providing a robust basis for developing multi-sector emission-control strategies and improving air quality management in urbanizing metropolitan regions.