Assessing over decadal biomass burning influence on particulate matter composition in subequatorial Amazon: literature review, remote sensing, chemical speciation and machine learning application.

A study on aerosols in the Brazilian subequatorial Amazon region, Tangará da Serra (TS) and Alta Floresta (AF) was conducted and compared to findings in an additional site with background characteristics (Manaus, AM). TS and AF counties suffer from intense biomass burning periods in the dry season, and it accounts for high levels of particles in the atmosphere. Chemical characterization of fine and coarse particulate matter (PM) was performed to quantify water-soluble ions (WSI) and black carbon (BC). The importance of explanatory variables was assessed using three machine learning techniques. Average concentrations of PM in AF and TS were similar (PM2.0, 17±10 µg m-3 (AF) and 16±11 µg m-3 (TS) and PM10-2.0, 13±5 µg m-3 (AF) and 11±7 µg m-3 (TS)), but higher than the background site. BC and SO4 2- were the prevalent components as they represented 27%-68% of particulates chemical composition. The combination of the machine learning techniques provided a further understanding of the pathways for PM concentration variability, and the results highlighted the influence of biomass burning for key sample groups and periods. PM2.0, BC, and most WSI presented higher concentrations in the dry season, providing further support for the influence of biomass burning.

Biomonitoring of metals for air pollution assessment using a hemiepiphyte herb (Struthanthus flexicaulis).

This work presents first results on elemental characterization of a parasite plant, Struthanthus flexicaulis, collected in urban, industrial and rural areas of Rio de Janeiro state, Brazil, in order to evaluate this plant as a biomonitor of metals pollution. The results were also compared to those obtained for fine particulate matter (PM2.5) collected from filters in nearby locales. The concentrations of PM2.5 measured in the filters were between 8.0 and 18.0 µg m(-3); in some places, these measurements were higher than the 10 µg m(-3), concentration recommended by the World Health Organization (WHO). Samples of the leaves and filters with PM were submitted to acid extraction, and the extracts were employed to determine major elements (Ba, Ca, Fe, K, Mg, P and S) by ICP OES and minor elements (Cr, Cu, La, Mn, Pb, Sr, Ti and Zn) by ICP-MS. Elements' extraction efficiency was evaluated by applying the method to the certified reference materials (CMR) of tomato leaves (NIST 1573(rd)) and urban dust (NIST 1648a). The concentrations of Ca, K and Mg were higher in leaves, while Ba, Ca, K and Zn showed higher concentrations in the PM. As expected, rural sites presented lower metal content. Enrichment factor (EF) and principal component analysis with multiple linear regression analysis (PCA-MLRA) were applied to the concentrations of elements in PM2.5 and in the leaves. Anthropogenic sources could be identified with both tools, which supports the use of S. flexicaulis as a biomonitor.

Particle pollution in Rio de Janeiro, Brazil: increase and decrease of pro-inflammatory cytokines IL-6 and IL-8 in human lung cells.

Particle pollution from urban and industrialized regions in Rio de Janeiro (RJ), Brazil was analyzed for toxic and pro-inflammatory (cytokines: IL-6, IL-8, IL-10) responses in human bronchial epithelial cells. Trace elements contribution was studied. Airborne particulate matter was collected at: three industrial sites Ind-1 (PM10) and Ind-2a and 2b (PM2.5); Centro urban area (PM10) and two rural sites (PM2.5, PM10). PM10 acetone extracts were toxic and did not elicit cytokine release; aqueous extracts were less toxic and stimulated the release of IL-6 and IL-8. PM2.5 aqueous extracts from Ind-2 decreased the release of IL-6 and IL-8. Zinc concentration was higher at the industrial and rural reference sites (Ref-1-2) although metals were not associated to cytokines changes. These results demonstrate that PM from RJ can either increase or decrease cytokine secretion in vitro while being site specific and time dependent.