This study presents the first comprehensive assessment of air pollution by ${\mathrm{PM}}_{2.5}$ and ${\mathrm{PM}}_{10}$ 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 ${\mathrm{PM}}_{2.5}$ ranging between 41.10 ± 3.2 $\mathsf{\mu }{\mathrm{g}/\mathrm{m}}^3$ (2020) and 82.01 ± 5.1 $\mathsf{\mu }{\mathrm{g}/\mathrm{m}}^3$ (2018), while ${\mathrm{PM}}_{10}$ values ranged from 45.07 ± 2.8 $\mathsf{\mu }{\mathrm{g}/\mathrm{m}}^3$ (2020) to 72.35 ± 4.3 $\mathsf{\mu }{\mathrm{g}/\mathrm{m}}^3$ (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 ${\mathrm{PM}}_{2.5}$ in the 2020 rainy season and R² = 0.44 (p < 0.001) for ${\mathrm{PM}}_{10}$ in the 2018 annual model. These findings demonstrate the existence of nonlinear relationships between pollutants and predictor variables in Cusco’s atmospheric basin.

Air-quality standards (AQS) are key regulatory tools to protect public health by setting pollutant thresholds. However, most are based on sea-level data. High-altitude (HA) environments differ in atmospheric conditions, influencing pollutant behavior and human vulnerability. These differences have prompted proposals for altitude-specific AQS adjustments. This systematic review identifies models and criteria supporting such adaptations and examines regulatory air-quality frameworks in countries with substantial populations living at very high altitudes (VHA). This review follows PRISMA-P guidelines, focusing on studies examining AQS adjustment approaches based on altitude. The Population/Concept/Context (PCC) framework was used to define search terms: population (AQS), concept (air pollutants), and context (altitude), with equivalents. The literature was retrieved from PubMed, Scopus, Web of Science, and Gale OneFile: Environmental Studies and Policy. A total of 2974 articles were identified, with 2093 remaining after duplicate removal. Following title and abstract screening, 2081 papers were excluded, leaving 12 for full-text evaluation. Ultimately, six studies met the eligibility criteria. Three studies focused on adjustment models based on atmospheric conditions, such as temperature and pressure changes, while the other three examined human physiological responses, particularly the increased inhaled air volume. China, Peru, and Bolivia have the largest populations living above 3500 m a.s.l., yet none of these countries have specific air-quality regulations tailored to HA conditions. The review underscores the necessity for tailored AQS in HA environments, highlighting specific criteria related to both atmospheric conditions and human physiological responses.

The pandemic produced by SARS-CoV-2 generated various impacts on public health, the environment and other anthropogenic activities. The purpose of this study was to evaluate the reduction of air pollution due to \(PM_{2.5}\) and \(PM_{10}\) particulate matter in Cusco city at the beginning of the pandemic. Social confinement in Peru began on March 16, 2020, until the end of June. These health measures caused strict isolation that resulted in a significant decrease in vehicle flow on the streets and avenues of the city of Cusco. In the first days of May, even during the time of confinement, we managed to measure air quality at a sampling point located on the campus of the Universidad Nacional de San Antonio Abad de Cusco; a reduction in air pollution due to particulate matter was observed. The evaluation was carried out using an high-volume (HiVol) 3000 particulate matter sampler and the mass of particulate matter adhered to the filters was determined by gravimetry. The concentrations of particulate matter \(PM_{2.5}\) and \(PM_{10}\) obtained pre-pandemic were compared with those recorded at the beginning of the pandemic. The results revealed a significant average reduction in the concentration of \(PM_{10}\) and \(PM_{2.5}\), reaching − 57.43% and − 59.52%, respectively, compared to pre-pandemic values. At the same time, its relationship with meteorological parameters and Google mobility data was evaluated and it was concluded that these parameters did not significantly affect the reduction of particulate matter. This study reveals the positive effects of the pandemic in reducing air pollution and the confinement measures had as a secondary effect on the decrease in air pollution in Cusco City.

Air quality standards (AQS) are key regulatory tools to protect public health by setting pollutant thresholds. However, most are based on sea-level data. High-altitude (HA) environments differ in atmospheric conditions, influencing pollutant behavior and human vulnerability. These conditions have prompted proposals for altitude-specific AQS adjustments. This systematic review identifies models and criteria supporting such adapta-tions and examines regulatory air quality frameworks in countries with substantial populations living in HA. PRISMA-P guidelines and a Population/Concept/Context (PCC) framework were used to define the search terms: Population (Air Quality Standards), Concept (Air Pollutants), and Context (Altitude). Relevant literature was retrieved from MEDLINE, SCOPUS, Web of Science, and Gale OneFile: Environmental Studies and Poli-cy. A total of 2,093 articles were identified after duplicate removal. Following title and ab-stract screening, 2,081 papers were excluded, leaving 12 for full-text evaluation. Ultimately, six studies met the eligibility criteria. Three studies focused on adjustment models based on atmospheric conditions, such as temperature and pressure changes, while the other three examined human physiological responses, particularly the increased inhaled air volume. China, Peru, and Bolivia have the largest populations living above 3,500 m a.s.l., yet none of these countries have specific air quality regulations tailored to HA conditions. The review underscores the necessity for tailored AQS in HA environments.

En este artículo científico, se llevó a cabo una evaluación exhaustiva de la contaminación del aire por material particulado PM2.5 en diferentes áreas de monitoreo de la ciudad del Cusco durante los años 2017 y 2018. El objetivo central de la investigación fue analizar concentración de PM2.5 en varios puntos de la ciudad, utilizando un enfoque de muestreo predeterminado. Se recolectaron múltiples mediciones en cada punto, realizadas en intervalos de 24 horas, y obteniendo los valores de concentración mediante gravimetría y posteriormente se calculó el promedio de estas mediciones. Este proceso de recolección y análisis de datos siguió las pautas normativas establecidas por la Agencia de Protección Ambiental de Estados Unidos (EPA). Los resultados obtenidos revelaron un panorama preocupante de la contaminación del aire en la ciudad del Cusco. Más del 84% de los sitios monitoreados presentaron una calificación mala en los Índices de Calidad Ambiental (INCA) establecidos por el Ministerio del Ambiente del Gobierno Peruano. Estos hallazgos indican que la población de Cusco está expuesta a niveles perjudiciales de PM2.5. Un punto destacado de la investigación es el distrito de San Jerónimo en Cusco, donde se registró una concentración promedio de 125 ug/m3 de PM2.5. Esto coloca esta área en el umbral de cuidado, representado por el color rojo en los INCA. Estos niveles elevados de PM2.5 en San Jerónimo se correlacionan con el riesgo de desarrollar enfermedades pulmonares crónicas y cardiovasculares, concluyendo que según los INCA el aire de la ciudad del Cusco es mala.

The study utilizes data corresponding to the average monthly concentration of particulate matter 2.5 (P.M. 2.5), relative humidity, and precipitation during the period 2016-2018 collected by the High Vol station of the Energy and Atmosphere Center, and the meteorological center SENAHMI (Kayra-UNSAAC). In order to estimate the statistical relationship between two quantitative variables, the Pearson and Spearman correlation coefficients are used, which were obtained using the Python programming language. The obtained t-value is compared with the Student's t-distribution table for a certain level of significance $(α= 0.05)$. Positive and negative correlation values are established based on the obtained coefficients, and the interpretation of the Pearson and Spearman correlation values is used to determine if the data is related or not.