Dataset Information

Monitoring air pollution close to a cement plant and in a multi-source industrial area through tree-ring analysis.

ABSTRACT: Thirty-two trace elements were examined in the tree rings of downy oak to evaluate the pollution levels close to a cement plant isolated in a rural context and an industrial area where multiple sources of air pollution are or were present. Tree cores were collected from trees growing 1 km from both the cement plant and the industrial area that are located 8 km from each other. The analysis of the trace elements was performed on annual tree rings from 1990 to 2016 using laser ablation inductively coupled plasma mass spectrometry. Trace elements Cs, Mg, Mn, S and Zn reflected the emission history of the cement plant. Their values have increased since early 2000s, when the cement plant started its activity. However, the lack of significant trends of pollutants in the tree rings from the industrial area and the possible effect of translocation and volatility of some elements left open questions. The very weak changes of the other trace elements in the period 1990-2016 suggest those elements do not mark any additional effect of the industrial activity on the background pollution. The results confirm that downy oak trees growing close to isolated industrial plants must be considered a pollution forest archive accessible through dendrochemistry.

SUBMITTER: Cocozza C

PROVIDER: S-EPMC8476389 | biostudies-literature | 2021 Oct

REPOSITORIES: biostudies-literature

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Monitoring air pollution close to a cement plant and in a multi-source industrial area through tree-ring analysis.

Cocozza Claudia C Alterio Edoardo E Bachmann Olivier O Guillong Marcel M Sitzia Tommaso T Cherubini Paolo P

Environmental science and pollution research international 20210527 38

Thirty-two trace elements were examined in the tree rings of downy oak to evaluate the pollution levels close to a cement plant isolated in a rural context and an industrial area where multiple sources of air pollution are or were present. Tree cores were collected from trees growing 1 km from both the cement plant and the industrial area that are located 8 km from each other. The analysis of the trace elements was performed on annual tree rings from 1990 to 2016 using laser ablation inductively ...[more]

PMID: 34046833

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Project description:ObjectiveTo understand how chronic exposure to industrial air pollution is associated with male fertility through semen parameters.DesignRetrospective cohort study.PatientsMen in the Subfertility, Health, and Assisted Reproduction cohort who underwent a semen analysis in the two largest healthcare systems in Utah from 2005-2017 with ≥1 measured semen parameter (N = 21,563).Intervention(s)Residential histories for each man were constructed using locations from administrative records linked through the Utah Population Database. Industrial facilities with air emissions of nine endocrine-disrupting compound chemical classes were identified from the Environmental Protection Agency Risk-Screening Environmental Indicators microdata. Chemical levels were linked with residential histories for the 5 years before each semen analysis.Main outcome measuresSemen analyses were classified as azoospermic or oligozoospermic (< 15 M/mL) using World Health Organization cutoffs for concentration. Bulk semen parameters such as concentration, total count, ejaculate volume, total motility, total motile count, and total progressive motile count were also measured. Multivariable regression models with robust standard errors were used to associate exposure quartiles for each of the nine chemical classes with each semen parameter, adjusting for age, race, and ethnicity, as well as neighborhood socioeconomic disadvantage.ResultsAfter adjustment for demographic covariates, several chemical classes were associated with azoospermia and decreased total motility and volume. For exposure in the 4th relative to 1st quartile, significant associations were observed for acrylonitrile (βtotal motility = -0.87 pp), aromatic hydrocarbons (odds ratio [OR]azoospermia = 1.53; βvolume = -0.14 mL), dioxins (ORazoospermia = 1.31; βvolume = -0.09 mL; βtotal motility = -2.65 pp), heavy metals (βtotal motility = -2.78pp), organic solvents (ORazoospermia = 1.75; βvolume = -0.10 mL), organochlorines (ORazoospermia = 2.09; βvolume = -0.12 mL), phthalates (ORazoospermia = 1.44; βvolume = -0.09 mL; βtotal motility = -1.21 pp), and silver particles (ORazoospermia = 1.64; βvolume = -0.11 mL). All semen parameters significantly decreased with increasing socioeconomic disadvantage. Men who lived in the most disadvantaged areas had concentration, volume, and total motility of 6.70 M/mL, 0.13 mL, and 1.79 pp lower, respectively. Count, motile count, and total progressive motile count all decreased by 30-34 M.Conclusion(s)Several significant associations between chronic low-level environmental exposure to endocrine-disrupting compound air pollution from industrial sources and semen parameters were observed. The strongest associations were seen for increased odds of azoospermia and declines in total motility and volume. More research is needed to further explore additional social and exposure factors as well as expand on the risk posed to male reproductive health by the studied chemicals.

Project description:Using daily fine particulate matter (PM2.5) composition data from the 2000-2005 U.S. EPA Chemical Speciation Network (CSN) for over 200 sites, we applied multivariate methods to identify and quantify the major fine particulate matter (PM2.5) source components in the U.S. Novel aspects of this work were: (1) the application of factor analysis (FA) to multi-city daily data, drawing upon both spatial and temporal variations of chemical species; and, (2) the exclusion of secondary components (sulfates, nitrates and organic carbon) from the source identification FA to more clearly discern and apportion the PM2.5 mass to primary emission source categories. For the quantification of source-related mass, we considered two approaches based upon the FA results: 1) using single key tracers for sources identified by FA in a mass regression; and, 2) applying Absolute Principal Component Analysis (APCA). In each case, we followed a two-stage mass regression approach, in which secondary components were first apportioned among the identified sources, and then mass was apportioned to the sources and to other secondary mass not explained by the individual sources. The major U.S. PM2.5 source categories identified via FA (and their key elements) were: Metals Industry (Pb, Zn); Crustal/Soil Particles (Ca, Si); Motor Vehicle Traffic (EC, NO2); Steel Industry (Fe, Mn); Coal Combustion (As, Se); Oil Combustion (V, Ni); Salt Particles (Na, Cl) and Biomass Burning (K). Nationwide spatial plots of the source-related PM2.5 impacts were confirmatory of the factor interpretations: ubiquitous sources, such as Traffic and Soil, were found to be spread across the nation, more unique sources (such as Steel and Metals Processing) being highest in select industrialized cities, Biomass Burning was highest in the U.S. Northwest, while Residual Oil combustion was highest in cities in the Northeastern U.S. and in cities with major seaports. The sum of these source contributions and the secondary PM2.5 components agreed well with the U.S. PM2.5 observed during the study period (mean=14.3 ug/m3; R2= 0.91). Apportionment regression analyses using single-element tracers for each source category gave results consistent with the APCA estimates. Comparisons of nearby sites indicated that the PM2.5 mass and the secondary aerosols were most homogenous spatially, while traffic PM2.5 and its tracer, EC, were among the most spatially representative of the source-related components. Comparison of apportionment results to a previous analysis of the 1979-1982 IP Network revealed similar and correlated major U.S. source category factors, albeit at lower levels than in the earlier period, suggesting a consistency in the U.S. spatial patterns of these source-related exposures over time, as well. These results indicate that applying source apportionment methods to the nationwide CSN can be an informative avenue for identifying and quantifying source components for the subsequent estimation of source-specific health effects, potentially contributing to more efficient regulation of PM2.5.

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Monitoring air pollution close to a cement plant and in a multi-source industrial area through tree-ring analysis.

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Monitoring air pollution close to a cement plant and in a multi-source industrial area through tree-ring analysis.

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