Abstract: Receptor models are widely used to identify and quantify major emissions sources of fine particulate matter (PM2.5), the chemical composition and specifically the so-called tracers allow the identification of specific processes that emit this pollutant. In this work, the Positive Matrix Factorization (PMF) model was used as a tool to identify and quantify the contribution of potential PM2.5 emission sources in the industrial corridor Tula-Vito Apaxco de Tula, Hidalgo, Mexico. Environmental data from three sampling campaigns with 24-hour average measurement were used in 7 sites with different land use, such as urban, industrial and rural areas as well as in two seasons of the year, dry-warm and dry-cold. The methodological process included: 1) collection and analysis of PM2.5 concentrations and chemical composition; 2) validation and processing of data for input to the model; and 3) identification and quantification of possible sources. The results revealed that during the highest PM2.5 concentrations, there was a higher contribution of organic carbon (26 %) and secondary inorganic aerosols (NH4 + , NO3 – y SO4 2- ) (32 %). The chemical composition of the particles collected during the three sampling campaigns was 51 % secondary inorganic aerosols, 28 % organic carbon, 9 % elements of geological material, 8 % elemental carbon, 3 % trace elements and 1 % salts. The PMF model indicated that fossil fuel burning is the main contributor of PM2.5 at approximately 30 % during the two study periods. This finding is consistent with the industrial activities present in the area, such as refineries, thermoelectric plants, cement and metallurgical plants. Other notable sources included vehicular emissions, secondary inorganic aerosols and industrial dusts. These results are valuable for policy makers as they provide essential information to address emission reduction in the industrial area and mitigate health risks.

Keywords: Receptor model, Positive Matrix Factorization, fine particulate matter, emission sources, industrial zone.