Application of an in vitro new approach methodology to determine relative cancer potency factors of air pollutants based on whole mixtures.

Air pollution is an example of a complex environmental mixture with different biological activities, making risk assessment challenging. Current cancer risk assessment strategies that focus on individual pollutants may overlook interactions among them, potentially underestimating health risks. Therefore, a shift towards the evaluation of whole mixtures is essential for accurate risk assessment.

PSCF method for source identification of particulate matter in an agricultural background region in Brazil.

The use of mathematical and statistical models to investigate potential sources of pollutants that have been transported by air masses to a study site is important for establishing control and monitoring measures for air pollutants such as PM and PM. During the study period, from 2018 to 2021, the concentrations of PM and PM recorded in Ribeirão Preto (SP, Brazil) were higher during spring and winter, with a tendency to increase the amplitude and its maximum values relative to daily averages. The source-receptor model, Potential Source Contribution Function (PSCF), was used to identify probable sources of these pollutants, and the regions known as and Intermediate Geographic Region of Juiz de Fora (MG, Brazil) were the main regions associated with high PSCF probability values (> 0.

Occurrence of polar organic compounds in atmospheric particulate matter: a system review in South America.

Particulate matter (PM) is one of the existing air pollutants, which can cause damages to human health, public property, and the environment. The chemical composition of this pollutant greatly varies, mainly its organic fraction. Thus, our objective was to carry out a literature review based on articles, considering studies conducted in South America, whose authors address the characterization of the polar organic fraction of PM.

A review of multivariate analysis: is there a relationship between airborne particulate matter and meteorological variables?

Among statistical tools for the study of atmospheric pollutants, trajectory regression analysis (TRA), cluster analysis (CA), and principal component analysis (PCA) can be highlighted. Therefore, this article presents a systematic review of such techniques based on (i) air mass influences on particulate matter (PM) and (ii) the study of the relationship between PM and meteorological variables. This article aims to review studies that use TRA and to review studies that adopt CA and/or PCA to identify the associations and relationship between meteorological variables and atmospheric pollutants.

Source apportionment of metallic elements in urban atmospheric particulate matter and assessment of its water-soluble fraction toxicity.

Clean air is essential for the maintenance of human life and environmental balance. The atmospheric particulate matter (PM) is one of the main air pollutants and is characterized by the heterogeneity of its composition, being able to accumulate numerous components, such as metallic elements, which contribute to increasing its toxicity. The objectives of this study were to assess of the air quality in two urban environments, to carry out the source apportionment of the metallic elements Al, Ba, Cd, Pb, Cu, Cr, Fe, Mn, Ni, and Zn in the PM and PM, and evaluate the toxicity of PM and PM water-soluble fractions using Lactuca sativa as bioindicator.