A Comprehensive Assessment of PM2.5 and PM10 Pollution in Cusco, Peru: Spatiotemporal Analysis and Development of the First Predictive Model (2017–2020)

Warthon J.; Zamalloa A.; Olarte A.; Warthon B.; Miranda I.; Zamalloa-Puma M.M.; Ccollatupa V.; Ormachea J.; Quispe Y.; Jalixto V.; Cruz D.; Salcedo R.; Valencia J.; Mio-Diaz M.; Ingles R.; Warthon G.; Tello R.; Uscca E.; Candia W.; Chura R.; Rubio J.; Alvarez M. · Sustainability (Switzerland) (2025) · DOI: 10.3390/su17020394

Resumen

This study presents the first comprehensive assessment of air pollution by (Formula presented.) and (Formula presented.) in the city of Cusco, aiming to determine atmospheric pollution levels, characterize air quality, and develop predictive models. The research, conducted during 2017–2020, systematically evaluated particulate matter (PM) contamination using a high-volume sampler (HiVol ECOTEC 3000) installed at 18 monitoring sites distributed across five urban districts. Multiple linear regression (MLR) models were developed and evaluated, incorporating meteorological, seasonal, and temporal variables under two approaches: direct linear (Model 1) and logarithmic transformation (Model 2). The model evaluation employed R², RMSE, MAE, MAPE, IOA, and CV statistical indicators. The results revealed concentrations significantly exceeding WHO guideline values, with (Formula presented.) ranging between 41.10 ± 3.2 (Formula presented.) (2020) and 82.01 ± 5.1 (Formula presented.) (2018), while (Formula presented.) values ranged from 45.07 ± 2.8 (Formula presented.) (2020) to 72.35 ± 4.3 (Formula presented.) (2017). A notable reduction was observed during 2020, attributable to COVID-19 pandemic restrictions. The Air Quality Index (AQI) indicated predominantly “Unhealthy” and “Very Unhealthy” levels during 2017–2018, improving to “Unhealthy for Sensitive Groups” in 2020. MLR models achieved maximum efficiency using logarithmic transformation, obtaining R² = 0.98 (p < 0.001) for (Formula presented.) in the 2020 rainy season and R² = 0.44 (p < 0.001) for (Formula presented.) in the 2018 annual model. These findings demonstrate the existence of nonlinear relationships between pollutants and predictor variables in Cusco’s atmospheric basin.

Instituciones: Universidad Nacional de San Antonio Abad del Cusco