Temporal variation of the PM2.5/PM10 ratio and its association with meteorological factors in a South American megacity: Metropolitan Area of Lima-Callao, Peru.

The Metropolitan Area of Lima-Callao (MALC) is a South American megacity that has suffered a serious deterioration in air quality due to high levels of particulate matter (PM2.5 and PM10). Studies on the behavior of the PM2.5/PM10 ratio and its temporal variability in relation to meteorological parameters are still very limited. The objective of this study was to analyze the temporal trends of the PM2.5/PM10 ratio, its temporal variability, and its association with meteorological variables over a period of 5 years (2015-2019). For this, the Theil-Sen estimator, bivariate polar plots, and correlation analysis were used. The regions of highest mean concentrations of PM2.5 and PM10 were identified at eastern Lima (ATE station-41.2 µg/m3) and southern Lima (VMT station-126.7 µg/m3), respectively. The lowest concentrations were recorded in downtown Lima (CDM station-16.8 µg/m3 and 34.0 µg/m3, respectively). The highest average PM2.5/PM10 ratio was found at the CDM station (0.55) and the lowest at the VMT station (0.27), indicating a predominance of emissions from the vehicular fleet within central Lima and a greater emission of coarse particles by resuspension in southern Lima. The temporal progression of the ratio of PM2.5/PM10 showed positive and highly significant trends in northern and central Lima with values of 0.03 and 0.1 units of PM2.5/PM10 per year, respectively. In the southern region of Lima, the trend was also significant, showcasing a value of 0.02 units of PM2.5/PM10 per year. At the hourly and monthly level, the PM2.5/PM10 ratio presented a negative and significant correlation with wind speed and air temperature, and a positive and significant correlation with relative humidity. These findings offer insights into identifying the sources of PM pollution and are useful for implementing regulations to reduce air emissions considering both anthropogenic sources and meteorological dispersion patterns.

Identifying contamination of heavy metals in soils of Peruvian Amazon plain: use of multivariate statistical techniques.

The Peruvian Amazon plain has abundant natural resources and is home to great biodiversity, which makes it an area with high economic potential. However, the use of its resources through various activities has contributed to the release of heavy metals (HMs) into its soils, generating severe pollution problems which have mainly affected the health of local populations and their ecosystems. Currently, there are no comprehensive studies that have identified the specific sources of contamination by HMs in the soils of this part of the Peruvian territory. In this sense, this research aims to identify the possible sources of contamination by HMs in the soils of the Peruvian Amazon plain to focus efforts on the establishment of adequate measures for the protection of the health of people and the ecosystem. In the present study, samples of topsoils (0-20 cm depth) and subsoils (100-150 cm depth) were collected for the analysis of 11 HMs (Co, Cr, Cu, Fe, Mn, Ni, Pb, V, Zn, Be, and Hg) in 48 sites located in four regions of the Peruvian Amazon plain (Loreto, Amazonas, San Martín, and Ucayali), over the year 2019. The enrichment factor and geoaccumulation index were applied to assess contamination levels of HMs. The results indicated that topsoils and subsoils presented a greater enrichment by the elements Be and Pb, and were classified as moderately contaminated. Likewise, the integral analysis of these indexes together with principal component analysis, hierarchical cluster analysis, correlation analysis, and coefficient of variation allowed the identification of potential sources of contamination by HMs. As a result, Fe, Co, Zn, Ni, V, and Cr were associated with natural or lithogenic sources (parent material, crude oil deposits, and organic matter decomposition). Hg was attributed to anthropogenic sources (illegal gold mining, atmospheric deposition, and vehicle emissions). Be, Pb, Cu, and Mn originated from natural sources (parent material, crude oil deposits, decomposition of organic matter, and forest fires) and anthropogenic (areas degraded by solid waste, illegal gold mining, agriculture, and hydrocarbons). These findings provide essential information to establish regulations and prevent and control HM contamination in soils of the Peruvian Amazon plain.