Search

With the increasing environmental impacts of human activities, the problem of polygenic multipollutants in groundwater has attracted the attention of researchers. Identifying the hydrobiogeochemical characteristics of the surface sewage that replenishes groundwater is crucial to addressing this problem. The input of polygenic multipollutants into groundwater leads to not only the mechanical superposition of pollutants but also the formation of secondary pollutant types. The evolution of polygenic multipollutants is influenced by aquifer characteristics, carbon sources, microbial abundance, etc. Therefore, this study took a sewage leakage point in Northwest China as the research object, carried out a controlled laboratory experiment on the impact of sewage discharge on groundwater, and, combined with long-term field monitoring results, determined the main hydrobiogeochemical processes of polygenic multipollutants and their secondary pollutants. The results showed that the redox environment and the gradient change in pH were identified as the most critical controlling factors. In oxidative groundwater during the early stage of vertical infiltration, sewage carries a substantial amount of NH4+, which is oxidized to form the secondary pollutant NO3−. As O2 is consumed, the reduction intensifies, and secondary pollutants NO3−, Mn (IV), and Fe(III) minerals are successively reduced. Compared with the natural conditions of rainwater vertical infiltration, the reaction rates and intensities of various reactions significantly increase during sewage vertical infiltration. However, there is a notable difference in the groundwater pH between sewage and rainwater vertical infiltration. In O2 and secondary pollutant NO3− reduction, a large amount of CO2 is rapidly generated. Excessive CO2 dissolves to produce a substantial amount of H+, promoting the acidic dissolution of Mn (II) minerals and generation of Mn2+. Sewage provides a higher carbon load, enhancing Mn (II) acidic dissolution and stimulating the activity of dissimilatory nitrate reduction to ammonium, which exhibits a higher contribution to NO3− reduction. This results in a portion of NO3− converted from NH4+ being reduced back to NH4+ and retained in the groundwater, reducing the denitrification's capacity to remove secondary NO3−. This has important implications for pollution management and groundwater remediation, particularly monitored natural attenuation. [ABSTRACT FROM AUTHOR]

With the increasing environmental impacts of human activities, the problem of polygenic multipollutants in groundwater has attracted the attention of researchers. Identifying the hydrobiogeochemical characteristics of the surface sewage that replenishes groundwater is crucial to addressing this problem. The input of polygenic multipollutants into groundwater leads to not only the mechanical superposition of pollutants but also the formation of secondary pollutant types. The evolution of polygenic multipollutants is influenced by aquifer characteristics, carbon sources, microbial abundance, etc. Therefore, this study took a sewage leakage point in Northwest China as the research object, carried out a controlled laboratory experiment on the impact of sewage discharge on groundwater, and, combined with long-term field monitoring results, determined the main hydrobiogeochemical processes of polygenic multipollutants and their secondary pollutants. The results showed that the redox environment and the gradient change in pH were identified as the most critical controlling factors. In oxidative groundwater during the early stage of vertical infiltration, sewage carries a substantial amount of NH4+, which is oxidized to form the secondary pollutant NO3−. As O2 is consumed, the reduction intensifies, and secondary pollutants NO3−, Mn (IV), and Fe(III) minerals are successively reduced. Compared with the natural conditions of rainwater vertical infiltration, the reaction rates and intensities of various reactions significantly increase during sewage vertical infiltration. However, there is a notable difference in the groundwater pH between sewage and rainwater vertical infiltration. In O2 and secondary pollutant NO3− reduction, a large amount of CO2 is rapidly generated. Excessive CO2 dissolves to produce a substantial amount of H+, promoting the acidic dissolution of Mn (II) minerals and generation of Mn2+. Sewage provides a higher carbon load, enhancing Mn (II) acidic dissolution and stimulating the activity of dissimilatory nitrate reduction to ammonium, which exhibits a higher contribution to NO3− reduction. This results in a portion of NO3− converted from NH4+ being reduced back to NH4+ and retained in the groundwater, reducing the denitrification’s capacity to remove secondary NO3−. This has important implications for pollution management and groundwater remediation, particularly monitored natural attenuation.

Background: Ambulance emergency calls (AECs) are seen as a more suitable metric for syndromic surveillance due to their heightened sensitivity in reflecting the health impacts of air pollutants. Limited evidence has emphasized the combined effect of hourly air pollutants on AECs. This study aims to investigate the combined effects of multipollutants (i.e., PM2.5, PM10, Ozone, NO2, and SO2) on all-cause and cause-specific AECs by using the quantile g-computation method. Methods: We used ambulance emergency dispatch data, air pollutant data, and meteorological data from between 1 January 2013 and 31 December 2019 in Shenzhen, China, to estimate the associations of hourly multipollutants with AECs. We followed a two-stage analytic protocol, including the distributed lag nonlinear model, to examine the predominant lag for each air pollutant, as well as the quantile g-computation model to determine the associations of air pollutant mixtures with all-cause and cause-specific AECs. Results: A total of 3,022,164 patients were identified during the study period in Shenzhen. We found that each interquartile range increment in the concentrations of PM2.5, PM10, Ozone, NO2, and SO2 in 0–8 h, 0–8 h, 0–48 h, 0–28 h, and 0–24 h was associated with the highest risk of AECs. Each interquartile range increase in the mixture of air pollutants was significantly associated with a 1.67% (95% CI, 0.12–3.12%) increase in the risk of all-cause AECs, a 1.81% (95% CI, 0.25–3.39%) increase in the risk of vascular AECs, a 1.77% (95% CI, 0.44–3.11%) increase in reproductive AECs, and a 2.12% (95% CI, 0.56–3.71%) increase in AECs due to injuries. Conclusions: We found combined effects of pollutant mixtures associated with an increased risk of AECs across various causes. These findings highlight the importance of targeted policies and interventions to reduce air pollution, particularly for PM, Ozone, and NO2 emissions. [ABSTRACT FROM AUTHOR]

Background: Exposure to aldehydes has been linked to adverse health outcomes such as inflammation and oxidative stress, but research on the effects of these compounds is limited. This study is aimed at assessing the association between aldehyde exposure and markers of inflammation and oxidative stress. Methods: The study used data from the NHANES 2013–2014 survey (n = 766) and employed multivariate linear models to investigate the relationship between aldehyde compounds and various markers of inflammation (alkaline phosphatase (ALP) level, absolute neutrophil count (ANC), and lymphocyte count) and oxidative stress (bilirubin, albumin, and iron levels) while controlling for other relevant factors. In addition to generalized linear regression, weighted quantile sum (WQS) and Bayesian kernel machine regression (BKMR) analyses were applied to examine the single or overall effect of aldehyde compounds on the outcomes. Results: In the multivariate linear regression model, each 1 standard deviation (SD) change in propanaldehyde and butyraldehyde was significantly associated with increases in serum iron levels (beta and 95% confidence interval, 3.25 (0.24, 6.27) and 8.40 (0.97, 15.83), respectively) and the lymphocyte count (0.10 (0.04, 0.16) and 0.18 (0.03, 0.34), respectively). In the WQS regression model, a significant association was discovered between the WQS index and both the albumin and iron levels. Furthermore, the results of the BKMR analysis showed that the overall impact of aldehyde compounds was significantly and positively correlated with the lymphocyte count, as well as the levels of albumin and iron, suggesting that these compounds may contribute to increased oxidative stress. Conclusions: This study reveals the close association between single or overall aldehyde compounds and markers of chronic inflammation and oxidative stress, which has essential guiding value for exploring the impact of environmental pollutants on population health. [ABSTRACT FROM AUTHOR]

Do internal levels of persistent organic pollutants (POP) in serum and follicular fluid affect ovarian function of women attending IVF? This cohort study included 136 women undergoing IVF in the assisted reproductive technology (ART) service of University Hospital from Nantes (France). Representative POP were measured using gas and liquid chromatography coupled with tandem mass spectrometry. Polyfluoroalkylated and perfluoroalkylated substances were measured in serum and polychlorinated biphenyls and organochlorinated pesticides in follicular fluid. Statistical associations between POP and ovarian reserve markers (anti-Müllerian Hormone [AMH] and antral follicle count [AFC], and ovarian responsiveness markers (Ovarian Sensitivity Index [OSI] and Follicular Output RaTe [FORT]), were explored in single and multipollutant regression models. Twenty-seven out of 53 POP congeners were frequently detected in almost all women attending IVF. Adjusted models did not show statistically significant associations between POP and ovarian reserve markers. Positive associations were found between some POP, i.e. hexachlorobenzene with FORT (β 0.42, 95% CI 0.13 to 0.71, P = 0.005) or PCB52 with Ovarian Sensitivity Index (β 0.22; 95% CI, 0.07 to 0.38, P = 0.005). Negative associations between some polyfluoroalkylated and perfluoroalkylated substances, PCB189 and trans-nonachlor with AFC and AMH were found among current smokers. Globally, associations between POP and the markers of ovarian function or responsiveness were lacking. Nonetheless, the stratification analysis suggested that current smoking could be a risk modifier, and extension of the study to a larger population sample size is needed. [ABSTRACT FROM AUTHOR]

Background: Ambulance emergency calls (AECs) are seen as a more suitable metric for syndromic surveillance due to their heightened sensitivity in reflecting the health impacts of air pollutants. Limited evidence has emphasized the combined effect of hourly air pollutants on AECs. This study aims to investigate the combined effects of multipollutants (i.e., PM2.5, PM10, Ozone, NO2, and SO2) on all-cause and cause-specific AECs by using the quantile g-computation method. Methods: We used ambulance emergency dispatch data, air pollutant data, and meteorological data from between 1 January 2013 and 31 December 2019 in Shenzhen, China, to estimate the associations of hourly multipollutants with AECs. We followed a two-stage analytic protocol, including the distributed lag nonlinear model, to examine the predominant lag for each air pollutant, as well as the quantile g-computation model to determine the associations of air pollutant mixtures with all-cause and cause-specific AECs. Results: A total of 3,022,164 patients were identified during the study period in Shenzhen. We found that each interquartile range increment in the concentrations of PM2.5, PM10, Ozone, NO2, and SO2 in 0–8 h, 0–8 h, 0–48 h, 0–28 h, and 0–24 h was associated with the highest risk of AECs. Each interquartile range increase in the mixture of air pollutants was significantly associated with a 1.67% (95% CI, 0.12–3.12%) increase in the risk of all-cause AECs, a 1.81% (95% CI, 0.25–3.39%) increase in the risk of vascular AECs, a 1.77% (95% CI, 0.44–3.11%) increase in reproductive AECs, and a 2.12% (95% CI, 0.56–3.71%) increase in AECs due to injuries. Conclusions: We found combined effects of pollutant mixtures associated with an increased risk of AECs across various causes. These findings highlight the importance of targeted policies and interventions to reduce air pollution, particularly for PM, Ozone, and NO2 emissions.

Background: Epidemiological studies on the associations of legacy per- and polyfluoroalkyl substances (PFASs) and glucose homeostasis remain discordant. Understanding of PFAS alternatives is limited, and few studies have reported joint associations of PFASs and PFAS alternatives. Objectives: To investigate associations of novel PFAS alternatives (chlorinated perfluoroalkyl ether sulfonic acids, Cl-PFESAs and perfluorobutanoic acid, PFBA) and two legacy PFASs (Perfluorooctanoic acid, PFOA and perfluorooctane sulfonate, PFOS) with glucose-homeostasis markers and explore joint associations of 13 legacy and alternative PFASs with the selected outcomes. Methods: We used cross-sectional data of 1,038 adults from the Isomers of C8 Health Project in China. Associations of PFASs and PFAS alternatives with glucose-homeostasis were explored in single-pollutant models using generalized linear models with natural cubic splines for PFASs. Bayesian Kernel Machine Regression (BKMR) models were applied to assess joint associations of exposures and outcomes. Sex-specific analyses were also conducted to evaluate effect modification. Results: After adjusting for confounders, both legacy (PFOA, PFOS) and alternative (Cl-PFESAs and PFBA) PFASs were positively associated with glucose-homeostasis markers in single-pollutant models. For example, in the total study population, estimated changes with 95% confidence intervals (CI) of fasting glucose at the 95th percentile of 6:2Cl-PFESA and PFOS against the thresholds were 0.90 (95% CI: 0.59, 1.21) and 0.44 (95% CI: 0.26, 0.62). Positive joint associations were found in BKMR models with 6:2Cl-PFESA contributing most. Sex-specific associations existed in both single- and multi-pollutant models. Conclusions: Legacy and alternative PFASs were positively associated with glucose-homeostasis markers. 6:2Cl-PFESA was the primary contributor. Sex-specific associations were also identified. These results indicate that joint associations and effect modification should be considered in risk assessment. However, further studies are recommended to strengthen our findings and to elucidate the mechanisms of action of legacy and alternative PFASs.

Humans are exposed daily to complex mixtures of chemical pollutants through their environment and diet, some of which have the potential to disrupt the bodies’ natural endocrine functions and contribute to reproductive diseases like endometriosis. Increasing epidemiological and experimental evidence supports the association between endometriosis and certain persistent organic pollutants (POPs) like dioxins; however, little is known about the underlying linking mechanisms. The main objective of this study is to proof the methodological applicability and discovery potential of integrating ultra-trace mass spectrometry (MS) profiling of POP biomarkers and endogenous biomarker profiling (MS metabolomics and cytokines) in a case-control study for the etiological research of endometriosis. The approach is applied in a pilot clinical-based study conducted in France where women with and without surgically confirmed endometriosis were recruited. Serum samples were analysed with high-resolution MS for about 30 polychlorinated biphenyls (PCBs), organochlorinated pesticides and perfluoroalkyl substances (PFAS). About 600 serum metabolites and lipids were identified with targeted metabolomics using tandem MS with the Biocrates MxP® Quant 500 Kit. A panel of 4 pro-inflammatory cytokines were analysed using ELISA-based 4-PLEX analyser. Statistical analysis included a battery of variable selection approaches, multivariate logistic regression for single-chemical associations, Bayesian kernel machine regressions (BKMR) to identify mixture effects of POPs and a multiblock approach to identify shared biomarker signatures among high risk clusters. The results showed the positive associations between some POPs and endometriosis risk, including the pesticide trans-nonachlor Odds Ratio (95% Confidence Interval) 3.38 (2.06–5.98), p

Statistical methods for identifying harmful chemicals in a correlated mixture often assume linearity in exposure‐response relationships. Nonmonotonic relationships are increasingly recognized (eg, for endocrine‐disrupting chemicals); however, the impact of nonmonotonicity on exposure selection has not been evaluated. In a simulation study, we assessed the performance of Bayesian kernel machine regression (BKMR), Bayesian additive regression trees (BART), Bayesian structured additive regression with spike‐slab priors (BSTARSS), generalized additive models with double penalty (GAMDP) and thin plate shrinkage smoothers (GAMTS), multivariate adaptive regression splines (MARS), and lasso penalized regression. We simulated realistic exposure data based on pregnancy exposure to 17 phthalates and phenols in the US National Health and Nutrition Examination Survey using a multivariate copula. We simulated data sets of size N = 250 and compared methods across 32 scenarios, varying by model size and sparsity, signal‐to‐noise ratio, correlation structure, and exposure‐response relationship shapes. We compared methods in terms of their sensitivity, specificity, and estimation accuracy. In most scenarios, BKMR, BSTARSS, GAMDP, and GAMTS achieved moderate to high sensitivity (0.52‐0.98) and specificity (0.21‐0.99). BART and MARS achieved high specificity (≥0.90), but low sensitivity in low signal‐to‐noise ratio scenarios (0.20‐0.51). Lasso was highly sensitive (0.71‐0.99), except for quadratic relationships (≤0.27). Penalized regression methods that assume linearity, such as lasso, may not be suitable for studies of environmental chemicals hypothesized to have nonmonotonic relationships with outcomes. Instead, BKMR, BSTARSS, GAMDP, and GAMTS are attractive methods for flexibly estimating the shapes of exposure‐response relationships and selecting among correlated exposures. [ABSTRACT FROM AUTHOR]

Background The current single-pollutant approach to regulating ambient air pollutants is effective at protecting public health, but efficiencies may be gained by addressing issues in a multipollutant context since multiple pollutants often have common sources and individuals are exposed to more than one pollutant at a time. Objective We performed a cross-disciplinary review of the effects of multipollutant exposures on cardiovascular effects. Methods A broad literature search for references including at least two criteria air pollutants (particulate matter [PM], ozone [O 3 ], oxides of nitrogen, sulfur oxides, carbon monoxide) was conducted. References were culled based on scientific discipline then searched for terms related to cardiovascular disease. Most multipollutant epidemiologic and experimental (i.e., controlled human exposure, animal toxicology) studies examined PM and O 3 together. Discussion Epidemiologic and experimental studies provide some evidence for O 3 concentration modifying the effect of PM, although PM did not modify O 3 risk estimates. Experimental studies of combined exposure to PM and O 3 provided evidence for additivity, synergism, and/or antagonism depending on the specific health endpoint. Evidence for other pollutant pairs was more limited. Conclusions Overall, the evidence for multipollutant effects was often heterogeneous, and the limited number of studies inhibited making a conclusion about the nature of the relationship between pollutant combinations and cardiovascular disease. [ABSTRACT FROM AUTHOR]

In recent years, multipollutant approaches have been employed to investigate the association with health outcomes to better represent real-world conditions than more traditional analysis that considers a single pollutant. With regard to the exposure assessment of a mixture of air pollutants, it is critical to understand the spatial variability in multipollutant relations in order to assess their potential health implications. In this study, we investigated the spatial relations of multiple pollutant concentrations (i.e., NO x , NO y , black carbon, carbon monoxide, acetaldehyde, formaldehyde, toluene, xylenes/ethylbenzene, ozone, water-soluble organic carbon, and aerosol extinction) observed from the P-3B aircraft in the 2011 NASA field campaign in Baltimore/Washington D.C. areas during July 2011. The between-pollutant Pearson correlations and Z-scores (calculated from log-transformed concentrations) between near-highways and non-highways and between near-urban centers and non-urban centers varied by pollutant pair and space. We found generally lower correlations between NO x and other pollutants for near-highways (average r = 0.36) than for non-highways (average r = 0.41) and also for non-urban centers (average r = 0.37) than for near-urban centers (average r = 0.41). This indicated that the temporal associations between NO x and health outcomes might be less affected by other pollutants, which were also related to same health outcomes, for near-highways and non-urban centers. The analysis of between-pollutant Z-scores showed varying spatial relations for popular traffic-related pollutants with the Z-score differences of 0.43 (NO x -carbon monoxide), 0.29 (NO x -black carbon), and 0.17 (black carbon-carbon monoxide) between near-highways and non-highways. This result exhibited heterogeneous traffic-related pollutant mixtures with the proximity to highways, potentially leading to the diverse extent of health associations. Furthermore, a mixed effects model presented pollutant-specific associations between the concentrations and the proximity to highways and urban centers, showing larger declines for NO x , xylenes/ethylbenzene, toluene, and NO y than those for the pollutants related to secondary pollutant formation. The model also demonstrated the different sensitivity of each pollutant to meteorological parameters, which may modify the spatial and temporal variability in the relations between the pollutants. Our findings provide insights for exposure assessment studies to better understand the cumulative health consequences associated with multiple air pollutants simultaneously. [ABSTRACT FROM AUTHOR]

Industrialization and other human activity represent significant environmental hazards. Toxic contaminants can harm a comprehensive platform of living organisms in their particular environments. Bioremediation is an effective remediation process in which harmful pollutants are eliminated from the environment using microorganisms or their enzymes. Microorganisms in the environment often create a variety of enzymes that can eliminate hazardous contaminants by using them as a substrate for development and growth. Through their catalytic reaction mechanism, microbial enzymes may degrade and eliminate harmful environmental pollutants and transform them into non-toxic forms. The principal types of microbial enzymes which can degrade most hazardous environmental contaminants include hydrolases, lipases, oxidoreductases, oxygenases, and laccases. Several immobilizations, genetic engineering strategies, and nanotechnology applications have been developed to improve enzyme performance and reduce pollution removal process costs. Until now, the practically applicable microbial enzymes from various microbial sources and their ability to degrade multipollutant effectively or transformation potential and mechanisms are unknown. Hence, more research and further studies are required. Additionally, there is a gap in the suitable approaches considering toxic multipollutants bioremediation using enzymatic applications. This review focused on the enzymatic elimination of harmful contaminants in the environment, such as dyes, polyaromatic hydrocarbons, plastics, heavy metals, and pesticides. Recent trends and future growth for effectively removing harmful contaminants by enzymatic degradation are also thoroughly discussed. [Display omitted] • Microbial enzymes catalyze various reactions inside and outside living cells. • Immobilized enzymes are emerging as effective biodegradation and biosynthesis agents. • Recent advances in enzymology provide effective approaches to enhance biodegradation. • A paradigm shift from single pollutant to multipollutants control is required. • Genetic modification of wild strains may boost the output of enzyme manufacturing. [ABSTRACT FROM AUTHOR]

Background Exposure metrics that identify spatial contrasts in multipollutant air quality are needed to better understand multipollutant geographies and health effects from air pollution. Our aim is to improve understanding of: (1) long-term spatial distributions of multiple pollutants; and (2) demographic characteristics of populations residing within areas of differing air quality. Methods We obtained average concentrations for ten air pollutants (p = 10) across a 12 km grid (n = 253) covering Atlanta, Georgia for 2002–2008. We apply a self-organizing map (SOM) to our data to derive multipollutant patterns observed across our grid and classify locations under their most similar pattern (i.e, multipollutant spatial type (MST)). Finally, we geographically map classifications to delineate regions of similar multipollutant characteristics and characterize associated demographics. Results We found six MSTs well describe our data, with profiles highlighting a range of combinations, from locations experiencing generally clean air to locations experiencing conditions that were relatively dirty. Mapping MSTs highlighted that downtown areas were dominated by primary pollution and that suburban areas experienced relatively higher levels of secondary pollution. Demographics show the largest proportion of the overall population resided in downtown locations experiencing higher levels of primary pollution. Moreover, higher proportions of nonwhites and children in poverty reside in these areas when compared to suburban populations that resided in areas exhibiting relatively lower pollution. Conclusion Our approach reveals the nature and spatial distribution of differential pollutant combinations across urban environments and provides helpful insights for identifying spatial exposure and demographic contrasts for future health studies. [ABSTRACT FROM AUTHOR]

The impact of persistent organic pollutants (POPs) on reproductive health is still poorly understood, even though infertility management has high associated societal and economical costs. The aims of this study were to characterize the internal levels of polychlorinated biphenyls (PCBs), organochlorine pesticides (OCPs) and perfluoroalkylated substances (PFAS) in women undergoing in vitro fertilization (IVF); and evaluate their association with IVF outcomes, individually and as mixtures in a combined multipollutant approach. Thus, 136 women undergoing IVF treatment at Nantes University Hospital (France) were prospectively recruited between 2019 and 2020. Serum samples were analyzed using liquid chromatography with tandem-mass spectrometry for 14 PFAS. Follicular fluid was analyzed with gas chromatography coupled to high resolution mass spectrometry for 14 PCBs and 25 OCPs. Intermediate and clinical IVF outcomes were ascertained by embryologists and clinicians using standardized protocols. Multivariate Poisson regression models and Bayesian Kernel Machine Regressions (BKMR) were used to identify individual and joint associations between POPs and IVF outcomes adjusting for age, body mass index (BMI) and anti-Müllerian hormone. The results showed that most POPs were widely present in women, and globally not associated with clinically relevant IVF outcomes, like live birth rates. Nonetheless, negative associations between PCB138 and trans-nonachlor with useable blastocysts were identified, β −0.28 (95%CI [-0.52; −0.04] p = 0.02) and β −0.22 (95%CI [-0.40; −0.03] p = 0.02). Conversely, PCB28 showed positive associations with the number of useable blastocysts, pregnancy rate and live birth rate. The BKMR analysis suggested the lack of association of the mixture with intermediate and clinical outcomes. The study supports the need of conducting further studies in a larger population sample in order to ensure sufficient statistical power to identify modest effects and a robust stratification analysis to account for the large underlying disease heterogeneity. [Display omitted] • French Women undergoing IVF are exposed to mixtures of POPs, including PCBs, OCPs and PFAS • PCB138 and trans-nonachlor were negatively associated with useable blastocyst • No associations were identified between POPs and live birth rates • The cumulative association of the mixture was globally null [ABSTRACT FROM AUTHOR]

Air pollution consists of a complex mixture of particulate and gaseous components. Individual criteria and other hazardous air pollutants have been linked to adverse respiratory and cardiovascular health outcomes. However, assessing risk of air pollutant mixtures is difficult since components are present in different combinations and concentrations in ambient air. Recent mechanistic studies have limited utility because of the inability to link measured changes to adverse outcomes that are relevant to risk assessment. New approaches are needed to address this challenge. The purpose of this manuscript is to describe a conceptual model, based on the adverse outcome pathway approach, which connects initiating events at the cellular and molecular level to population-wide impacts. This may facilitate hazard assessment of air pollution mixtures. In the case reports presented here, airway hyperresponsiveness and endothelial dysfunction are measurable endpoints that serve to integrate the effects of individual criteria air pollutants found in inhaled mixtures. This approach incorporates information from experimental and observational studies into a sequential series of higher order effects. The proposed model has the potential to facilitate multipollutant risk assessment by providing a framework that can be used to converge the effects of air pollutants in light of common underlying mechanisms. This approach may provide a ready-to-use tool to facilitate evaluation of health effects resulting from exposure to air pollution mixtures. [ABSTRACT FROM AUTHOR]

Background: Characterizing multipollutant health effects is challenging. We use classification and regression trees to identify multipollutant joint effects associated with pediatric asthma exacerbations and compare these results with those from a multipollutant regression model with continuous joint effects. Methods: We investigate the joint effects of ozone, NO2 and PM2.5 on emergency department visits for pediatric asthma in Atlanta (1999-2009), Dallas (2006-2009) and St. Louis (2001-2007). Daily concentrations of each pollutant were categorized into four levels, resulting in 64 different combinations or 'Day-Types' that can occur. Days when all pollutants were in the lowest level were withheld as the reference group. Separate regression trees were grown for each city, with partitioning based on Day-Type in a model with control for confounding. Day-Types that appeared together in the same terminal node in all three trees were considered to be mixtures of potential interest and were included as indicator variables in a three-city Poisson generalized linear model with confounding control and rate ratios calculated relative to the reference group. For comparison, we estimated analogous joint effects from a multipollutant Poisson model that included terms for each pollutant, with concentrations modeled continuously. Results and discussion: No single mixture emerged as the most harmful. Instead, the rate ratios for the mixtures suggest that all three pollutants drive the health association, and that the rate plateaus in the mixtures with the highest concentrations. In contrast, the results from the comparison model are dominated by an association with ozone and suggest that the rate increases with concentration. Conclusion: The use of classification and regression trees to identify joint effects may lead to different conclusions than multipollutant models with continuous joint effects and may serve as a complementary approach for understanding health effects of multipollutant mixtures. [ABSTRACT FROM AUTHOR]

This research investigated the effects of transition metal oxide impregnation on the physical/chemical properties and the multipollutant (i.e., Hg/SO 2 /NO) control of a V 2 O 5 -WO 3 /TiO 2 -SiO 2 selective catalytic reduction (SCR) catalyst. Additional V, Mn, and Cu of 5 wt% as their precursor metal hydroxides were impregnated onto the catalyst surface. The impregnated metal oxides presenting in nanoscales caused an increase in total surface area of catalysts. SEM images suggested that the raw and treated catalysts presenting as bean-shaped nanoparticles within 10–30 nm. V 4+ /V 5+ , Mn 4+ , and Cu 2+ were the major valence states presenting on the surface of VO x -, MnO x -, and CuO x -impregnated catalysts, respectively. Hg 0 oxidation, SO 2 removal, and NO reduction of the SCR catalyst can be enhanced after the metal oxide impregnation. VO x - and CuO x -impregnated catalysts had not only excellent Hg 0 oxidation but also great NO reduction. However, the increase in SO 2 removal after metal oxide impregnation, assumed to be partly caused from enhancing SO 2 –SO 3 conversion, may be of concern considering the potential downstream corrosion. Langmuir–Hinshelwood model can successfully explain the Hg 0 oxidation by VO x - and MnO x -impregnated catalysts. Overall, multipollutant emission control using surface-impregnated SCR catalysts can be practically applied at 350 °C under the tested coal-combustion flue gas condition. [ABSTRACT FROM AUTHOR]

The effects of CuCl2 impregnation on the physical and chemical properties and the Hg0 removal effectiveness of zeolite MCM-41 (MCM) were examined. Multipollutant removal potentials of the resulting samples on simultaneous capture of SO2 and NO were also evaluated. Overall, CuCl2 impregnation within 2-16% reduced the total surface area and pore volume of MCM. The introduced CuCl2 caused the impregnated MCM becoming a microporous adsorbent. The Hg0 adsorption capacities of CuCl2-impregnated MCMs were greater than those of the untreated sample under both N2 and simulated flue gas conditions. When the CuCl2 impregnation content was≥8wt%, however, the Hg0 adsorption capacity decreased because CuCl2 impregnation in excess amounts hindered certain active sites or blocked the pores. Hg0 oxidation tests showed that the average oxidation percentages of MCM-4% and MCM-16% were 26.7% and 53.7% respectively in the flue gas condition, compared to<26% in the N2 condition. After CuCl2 impregnation, the SO2 removal of MCM samples decreased from 42.3% to approximately 38% but NO removal increased from 62.8% to up to 73%, showing that CuCl2-impregnated MCMs may have greater potentials in simultaneous removal of NO than SO2. Catalytic oxidation appeared to be important in SO2 and NO removal. [ABSTRACT FROM AUTHOR]

The National Environmental Respiratory Center Program was initiated as an experiment to explore strategies for identifying the components of complex air pollution mixtures that cause health effects associated statistically with air pollution. A strategy involving multivariate analysis of a composition-concentration-response database was adopted. A novel database was created by exposing rodents daily for up to six months to one of four combustion-related mixtures and measuring respiratory, cardiovascular and general toxicological responses after one week or six months of exposure. The mixtures included multiple concentrations of diesel and gasoline engine exhaust, hardwood smoke and simulated downwind coal combustion emissions. After reporting the biological effects of each mixture and comparing effects among them, 47 significant effects were selected for multiple additive regression tree analysis to identify putative causal components. Although the four mixtures provided a database marginally sufficient for the analysis, the results suggested the putative causes of 19 significant effects with acceptable confidence. This article describes and critiques the Program and its strategy. The integrated results are presented in two accompanying papers, and mixture-specific results were presented in preceding papers, which are cited. The experiment demonstrated the potential utility of the general approach and identified certain cause-effect relationships for confirmatory studies. A follow-up study provided support for causation by the components implicated for one of those relationships. The advantages and disadvantages of the Program's management and funding strategies are discussed. [ABSTRACT FROM AUTHOR]

Abstract: Background: Health effects associated with air pollution are typically evaluated using a single pollutant approach, yet people are exposed to mixtures consisting of multiple pollutants that may have independent or combined effects on human health. Development of exposure metrics that represent the multipollutant environment is important to understand the impact of ambient air pollution on human health. Objectives: We reviewed existing multipollutant exposure metrics to evaluate how they can be applied to understand associations between air pollution and health effects. Methods: We conducted a literature search using both targeted search terms and a relational search in Web of Science and PubMed in April and December 2013. We focused on exposure metrics that are constructed from ambient pollutant concentrations and can be broadly applied to evaluate air pollution health effects. Results: Multipollutant exposure metrics were identified in 57 eligible studies. Metrics reviewed can be categorized into broad pollutant grouping paradigms based on: 1) source emissions and atmospheric processes or 2) common health outcomes. Discussion: When comparing metrics, it is apparent that no universal exposure metric exists; each type of metric addresses different research questions and provides unique information on human health effects. Key limitations of these metrics include the balance between complexity and simplicity as well as the lack of an existing “gold standard” for multipollutant health effects and exposure. Conclusions: Future work on characterizing multipollutant exposure error and joint effects will inform development of improved multipollutant metrics to advance air pollution health effects research and human health risk assessment. [Copyright &y& Elsevier]

Background: Identifying and characterizing how mixtures of exposures are associated with health endpoints is challenging. We demonstrate how classification and regression trees can be used to generate hypotheses regarding joint effects from exposure mixtures. Methods: We illustrate the approach by investigating the joint effects of CO, NO2, O3, and PM2.5 on emergency department visits for pediatric asthma in Atlanta, Georgia. Pollutant concentrations were categorized as quartiles. Days when all pollutants were in the lowest quartile were held out as the referent group (n = 131) and the remaining 3,879 days were used to estimate the regression tree. Pollutants were parameterized as dichotomous variables representing each ordinal split of the quartiles (e.g. comparing CO quartile 1 vs. CO quartiles 2-4) and considered one at a time in a Poisson case-crossover model with control for confounding. The pollutant-split resulting in the smallest P-value was selected as the first split and the dataset was partitioned accordingly. This process repeated for each subset of the data until the P-values for the remaining splits were not below a given alpha, resulting in the formation of a “terminal node”. We used the case-crossover model to estimate the adjusted risk ratio for each terminal node compared to the referent group, as well as the likelihood ratio test for the inclusion of the terminal nodes in the final model. Results: The largest risk ratio corresponded to days when PM2.5 was in the highest quartile and NO2 was in the lowest two quartiles (RR: 1.10, 95% CI: 1.05, 1.16). A simultaneous Wald test for the inclusion of all terminal nodes in the model was significant, with a chi-square statistic of 34.3 (p = 0.001, with 13 degrees of freedom). Conclusions: Regression trees can be used to hypothesize about joint effects of exposure mixtures and may be particularly useful in the field of air pollution epidemiology for gaining a better understanding of complex multipollutant exposures. [ABSTRACT FROM AUTHOR]

Background: This paper presents an application of quantitative ion character-activity relationship (QICAR) to estimate associations of human cardiovascular (CV) diseases (CVDs) with a set of metal ion properties commonly observed in ambient air pollutants. QICAR has previously been used to predict ecotoxicity of inorganic metal ions based on ion properties. Objectives: The objective of this work was to examine potential associations of biological end points with a set of physical and chemical properties describing inorganic metal ions present in exposures using QICAR. Methods: Chemical and physical properties of 17 metal ions were obtained from peer-reviewed publications. Associations of cardiac arrhythmia, myocardial ischemia, myocardial infarction, stroke, and thrombosis with exposures to metal ions (measured as inference scores) were obtained from the Comparative Toxicogenomics Database (CTD). Robust regressions were applied to estimate the associations of CVDs with ion properties. Results: CVD was statistically significantly associated (Bonferroni-adjusted significance level of 0.003) with many ion properties reflecting ion size, solubility, oxidation potential, and abilities to form covalent and ionic bonds. The properties are relevant for reactive oxygen species (ROS) generation, which has been identified as a possible mechanism leading to CVDs. Conclusion: QICAR has the potential to complement existing epidemiologic methods for estimating associations between CVDs and air pollutant exposures by providing clues about the underlying mechanisms that may explain these associations. [ABSTRACT FROM AUTHOR]

With the advent of multicity studies, uniform statistical approaches have been developed to examine air pollution-mortality associations across cities. To assess the sensitivity of the air pollution-mortality association to different model specifications in a single and multipollutant context, the authors applied various regression models developed in previous multicity time-series studies of air pollution and mortality to data from Philadelphia, Pennsylvania (May 1992–September 1995). Single-pollutant analyses used daily cardiovascular mortality, fine particulate matter (particles with an aerodynamic diameter ≤2.5 µm; PM2.5), speciated PM2.5, and gaseous pollutant data, while multipollutant analyses used source factors identified through principal component analysis. In single-pollutant analyses, risk estimates were relatively consistent across models for most PM2.5 components and gaseous pollutants. However, risk estimates were inconsistent for ozone in all-year and warm-season analyses. Principal component analysis yielded factors with species associated with traffic, crustal material, residual oil, and coal. Risk estimates for these factors exhibited less sensitivity to alternative regression models compared with single-pollutant models. Factors associated with traffic and crustal material showed consistently positive associations in the warm season, while the coal combustion factor showed consistently positive associations in the cold season. Overall, mortality risk estimates examined using a source-oriented approach yielded more stable and precise risk estimates, compared with single-pollutant analyses. [ABSTRACT FROM PUBLISHER]

Objectives: The U.S. Environmental Protection Agency is working toward gaining a better understanding of the human health impacts of exposure to complex air pollutant mixtures and the key features that drive the toxicity of these mixtures, which can then be used for future scientific and risk assessments. Data sources: A public workshop was held in Chapel Hill, North Carolina, 22-24 February 2011, to discuss scientific issues and data gaps related to adopting multipollutant science and risk assessment approaches, with a particular focus on the criteria air pollutants. Expert panelists in the fields of epidemiology, toxicology, and atmospheric and exposure sciences led open discussions to encourage workshop participants to think broadly about available and emerging scientific evidence related to multipollutant approaches to evaluating the health effects of air pollution. Synthesis: Although there is clearly a need for novel research and analytical approaches to better characterize the health effects of multipollutant exposures, much progress can be made by using existing scientific information and statistical methods to evaluate the effects of single pollutants in a multipollutant context. This work will have a direct impact on the development of a multipollutant science assessment and a conceptual framework for conducting multipollutant risk assessments. Conclusions: Transitioning to a multipollutant paradigm can be aided through the adoption of a framework for multipollutant science and risk assessment that encompasses well-studied and ubiquitous air pollutants. Successfully advancing methods for conducting these assessments will require collaborative and parallel efforts between the scientific and environmental regulatory and policy communities. [ABSTRACT FROM AUTHOR]

This article explores the role that scientific information can play in improving implementation of National Ambient Air Quality Standards and discusses some of the key policy-relevant questions related to implementation that could be informed by advances in the scientific research. This article expands on the concept of urban exposure environments as useful constructs in helping to improve research into the roles of air pollution mixtures and population exposure patterns in air pollution health effects. Recommendations for potential research areas related to urban exposure environments are discussed, including (1) improving the understanding of the role that individual pollutants play within the overall mixture of pollutants that determine air quality and health outcomes in an urban area, (2) understanding the causes of heterogeneity (or similarity) across urban areas in the relative risks associated with air pollution, and (3) improving air quality characterization within urban exposure environments, recognizing the complex air pollution mixtures in many environments which may result from emissions from multiple sources, including regional and local contributors. Informed implementation policies focused on multipollutant risk-based management objectives guided by an improved understanding of multipollutant exposures are likely to lead to greater improvements in public health through more effective and efficient emissions controls. [ABSTRACT FROM AUTHOR]

'Air Pollution and Health: Bridging the Gap from Sources to Health Outcomes,' an international specialty conference sponsored by the American Association for Aerosol Research, was held to address key uncertainties in our understanding of adverse health effects related to air pollution and to integrate and disseminate results from recent scientific studies that cut across a range of air pollution-related disciplines. The Conference addressed the science of air pollution and health within a multipollutant framework (herein 'multipollutant' refers to gases and particulate matter mass, components, and physical properties), focusing on five key science areas: sources, atmospheric sciences, exposure, dose, and health effects. Eight key policy-relevant science questions integrated across various parts of the five science areas and a ninth question regarding findings that provide policy-relevant insights served as the framework for the meeting. Results synthesized from this Conference provide new evidence, reaffirm past findings, and offer guidance for future research efforts that will continue to incrementally advance the science required for reducing uncertainties in linking sources, air pollutants, human exposure, and health effects. This paper summarizes the Conference findings organized around the science questions. A number of key points emerged from the Conference findings. First, there is a need for greater focus on multipollutant science and management approaches that include more direct studies of the mixture of pollutants from sources with an emphasis on health studies at ambient concentrations. Further, a number of research groups reaffirmed a need for better understanding of biological mechanisms and apparent associations of various health effects with components of particulate matter (PM), such as elemental carbon, certain organic species, ultrafine particles, and certain trace elements such as Ni, V, and Fe(II), as well as some gaseous pollutants. Although much debate continues in this area, generation of reactive oxygen species induced by these and other species present in air pollution and the resulting oxidative stress and inflammation were reiterated as key pathways leading to respiratory and cardiovascular outcomes. The Conference also underscored significant advances in understanding the susceptibility of populations, including the role of genetics and epigenetics and the influence of socioeconomic and other confounding factors and their synergistic interactions with air pollutants. Participants also pointed out that short- and long-term intervention episodes that reduce pollution from sources and improve air quality continue to indicate that when pollution decreases so do reported adverse health effects. In the limited number of cases where specific sources or PM species were included in investigations, specific species are often associated with the decrease in effects. Other recent advances for improved exposure estimates for epidemiological studies included using new technologies such as microsensors combined with cell phone and integrated into real-time communications, hybrid air quality modeling such as combined receptor- and emission-based models, and surface observations used with remote sensing such as satellite data. [ABSTRACT FROM AUTHOR]

China’s strategies to control acidifying pollutants and particulate matter (PM) may be in conflict for soil acidification abatement. Acidifying pollutant emissions are estimated for 2005 and 2020 with anticipated control policies. PM emissions including base cations (BCs) are evaluated with two scenarios, a base case applying existing policy to 2020, and a control case including anticipated tightened measures. Depositions of sulfur (S), nitrogen (N) and BCs are simulated and their acidification risks are evaluated with critical load (CL). In 2005, the area exceeding CL covered 15.6% of mainland China, with total exceedance of 2.2 Mt S. These values decrease in the base scenario 2020, implying partial recovery from acidification. Under more realistic PM control, the respective estimates are 17.9% and 2.4 Mt S, indicating increased acidification risks due to abatement of acid-neutralizing BCs. China’s anthropogenic PM abatement will have potentially stronger chemical implications for acidification than developed countries. [Copyright &y& Elsevier]

Humans are exposed daily to complex mixtures of chemical pollutants through their environment and diet, some of which have the potential to disrupt the bodies' natural endocrine functions and contribute to reproductive diseases like endometriosis. Increasing epidemiological and experimental evidence supports the association between endometriosis and certain persistent organic pollutants (POPs) like dioxins; however, little is known about the underlying linking mechanisms. The main objective of this study is to proof the methodological applicability and discovery potential of integrating ultra-trace mass spectrometry (MS) profiling of POP biomarkers and endogenous biomarker profiling (MS metabolomics and cytokines) in a case-control study for the etiological research of endometriosis. The approach is applied in a pilot clinical-based study conducted in France where women with and without surgically confirmed endometriosis were recruited. Serum samples were analysed with high-resolution MS for about 30 polychlorinated biphenyls (PCBs), organochlorinated pesticides and perfluoroalkyl substances (PFAS). About 600 serum metabolites and lipids were identified with targeted metabolomics using tandem MS with the Biocrates MxP® Quant 500 Kit. A panel of 4 pro-inflammatory cytokines were analysed using ELISA-based 4-PLEX analyser. Statistical analysis included a battery of variable selection approaches, multivariate logistic regression for single-chemical associations, Bayesian kernel machine regressions (BKMR) to identify mixture effects of POPs and a multiblock approach to identify shared biomarker signatures among high risk clusters. The results showed the positive associations between some POPs and endometriosis risk, including the pesticide trans -nonachlor Odds Ratio (95% Confidence Interval) 3.38 (2.06–5.98), p < 0.0001 and PCB 114 OR (95% CI) 1.83 (1.17–2.93), p = 0.009. The BKMR approach showed a tendency of a positive cumulative effect of the mixture, however trans -nonachlor exhibited significant associations within the mixture and interacted with other PCBs, strengthening the effects at highest concentrations. Finally, the multiblock analysis, relating the various blocks of data, revealed a latent cluster of women with higher risk of endometrioma presenting higher concentrations of trans -nonachlor, PCB 114 and dioxin-like toxic equivalents from PCBs, together with an increased inflammatory profile (i.e. elevated interleukin-8 and monocyte chemoattractant protein-1). It was also highlighted a specific metabolic pattern characterized by dysregulation of bile acid homeostasis and lipase activity. Further research will be required with larger sample size to confirm these findings and gain insight on the underlying mechanisms between POPs and endometriosis. [ABSTRACT FROM AUTHOR]

[Display omitted] • We provided more evidence on associations between legacy PFASs and PFAS alternatives and glucose-homeostasis. • We explored the joint associations of legacy PFASs and PFAS alternatives. • 6:2 Cl-PFESA contributed the most in the joint associations. • Sex-specific associations were observed. Epidemiological studies on the associations of legacy per- and polyfluoroalkyl substances (PFASs) and glucose homeostasis remain discordant. Understanding of PFAS alternatives is limited, and few studies have reported joint associations of PFASs and PFAS alternatives. To investigate associations of novel PFAS alternatives (chlorinated perfluoroalkyl ether sulfonic acids, Cl-PFESAs and perfluorobutanoic acid, PFBA) and two legacy PFASs (Perfluorooctanoic acid, PFOA and perfluorooctane sulfonate, PFOS) with glucose-homeostasis markers and explore joint associations of 13 legacy and alternative PFASs with the selected outcomes. We used cross-sectional data of 1,038 adults from the Isomers of C8 Health Project in China. Associations of PFASs and PFAS alternatives with glucose-homeostasis were explored in single-pollutant models using generalized linear models with natural cubic splines for PFASs. Bayesian Kernel Machine Regression (BKMR) models were applied to assess joint associations of exposures and outcomes. Sex-specific analyses were also conducted to evaluate effect modification. After adjusting for confounders, both legacy (PFOA, PFOS) and alternative (Cl-PFESAs and PFBA) PFASs were positively associated with glucose-homeostasis markers in single-pollutant models. For example, in the total study population, estimated changes with 95% confidence intervals (CI) of fasting glucose at the 95th percentile of 6:2Cl-PFESA and PFOS against the thresholds were 0.90 (95% CI: 0.59, 1.21) and 0.44 (95% CI: 0.26, 0.62). Positive joint associations were found in BKMR models with 6:2Cl-PFESA contributing most. Sex-specific associations existed in both single- and multi-pollutant models. Legacy and alternative PFASs were positively associated with glucose-homeostasis markers. 6:2Cl-PFESA was the primary contributor. Sex-specific associations were also identified. These results indicate that joint associations and effect modification should be considered in risk assessment. However, further studies are recommended to strengthen our findings and to elucidate the mechanisms of action of legacy and alternative PFASs. [ABSTRACT FROM AUTHOR]

Recent federal policy proposals to reduce emissions of sulfur dioxide (SO2), nitrogen oxides (NO x ), and mercury from the US electricity sector promise important improvements in air quality and reductions in acid deposition. The cost of achieving these reductions depends on the form and stringency of the regulation. In this research, we analyze the economic benefits and costs of the US Environmental Protection Agency''s (EPA''s) Clean Air Interstate Rule (CAIR) as characterized in the supplemental rule proposed in June 2004, and the Clean Air Mercury Rule (CAMR) as proposed in February 2004. The assessment integrates a model of the electricity sector, two models of atmospheric transport of air pollutants, and a model of environmental and public health endpoints affected by pollution. We model explicitly the emissions of SO2, NO x , mercury and carbon dioxide (CO2) and the effects of changes in emissions of SO2 and NO x on environmental and public health. The manner in which mercury emissions are regulated will have important implications not only for the cost of the regulation, but also for emission levels for SO2 and NO x and where those emissions are located. We find the economic benefits of CAIR and CAMR are far greater than the costs. Recent estimates of benefits of reductions in mercury and acidification indicate that our model captures the lion''s share of quantifiable benefits. We also find that the EPA would have been justified on economic grounds in pursuing additional SO2 emissions reductions beyond the requirements of CAIR. [Copyright &y& Elsevier]

Cardiovascular disease (CVD) is the leading cause of mortality worldwide. Exposure to air pollution, specifically particulate matter of diameter ≤2.5 μm (PM 2.5), is a well-established risk factor for CVD. However, the contribution of gaseous pollutant exposure to CVD risk is less clear. To examine the vascular effects of exposure to individual volatile organic compounds (VOCs) and mixtures of VOCs. We measured urinary metabolites of acrolein (CEMA and 3HPMA), 1,3-butadiene (DHBMA and MHBMA3), and crotonaldehyde (HPMMA) in 346 nonsmokers with varying levels of CVD risk. On the day of enrollment, we measured blood pressure (BP), reactive hyperemia index (RHI – a measure of endothelial function), and urinary levels of catecholamines and their metabolites. We used generalized linear models for evaluating the association between individual VOC metabolites and BP, RHI, and catecholamines, and we used Bayesian Kernel Machine Regression (BKMR) to assess exposure to VOC metabolite mixtures and BP. We found that the levels of 3HPMA were positively associated with systolic BP (0.98 mmHg per interquartile range (IQR) of 3HPMA; CI: 0.06, 1.91; P = 0.04). Stratified analysis revealed an increased association with systolic BP in Black participants despite lower levels of urinary 3HPMA. This association was independent of PM 2.5 exposure and BP medications. BKMR analysis confirmed that 3HPMA was the major metabolite associated with higher BP in the presence of other metabolites. We also found that 3HPMA and DHBMA were associated with decreased endothelial function. For each IQR of 3HPMA or DHBMA, there was a −4.4% (CI: −7.2, −0.0; P = 0.03) and a −3.9% (CI: −9.4, −0.0; P = 0.04) difference in RHI, respectively. Although in the entire cohort the levels of several urinary VOC metabolites were weakly associated with urinary catecholamines and their metabolites, in Black participants, DHBMA levels showed strong associations with urinary norepinephrine and normetanephrine levels. Exposure to acrolein and 1,3-butadiene is associated with endothelial dysfunction and may contribute to elevated risk of hypertension in participants with increased sympathetic tone, particularly in Black individuals. • Volatile organic compounds (VOCs) are major components of environmental pollution. • Exposure to VOCs is associated with high blood pressure and endothelial dysfunction. • Exposure to VOCs is also associated with increased levels of catecholamines. • Black participants were more susceptible to vascular changes in response to exposure. • Exposure to VOCs may be a significant risk factor in the development of heart disease. [ABSTRACT FROM AUTHOR]

Daily commutes can contribute disproportionately to overall daily exposure to urban air pollutant concentrations. It is important to understand factors that contribute to the variability of exposures during commutes to develop strategies to mitigate exposure. We used low-cost Fairsense PMS1003 sensors to monitor exposure to multiple air pollutants: PM 2.5 , PM 10 , SO 2 , CO, O 3 and NO 2 , across four dominant transport modes: bike, taxi, subway and bus, on prescribed commuting routes covering a wide range of environments representative of downtown Zhengzhou during the morning and evening rush hours. Zhengzhou is a city in China that faces severe air quality challenges. We compared exposures in the different modes and evaluated factors that contributed to variability in exposure to the different pollutants during commute trips. There were statistically significant differences in exposures across commuting modes for most pollutants. Commuting in air-conditioned taxis had the lowest exposure to PM, but highest exposures to some primary gaseous pollutants (SO 2 and CO). In a multivariate analysis, the travel mode generally explained the greatest variability in pollutant exposure, in comparison to route, time of day (morning/evening), and background pollutant concentrations. When breathing rate was taken into account to compute pollutant doses, cycling emerged as the commuting mode with the highest inhaled dose. Image 1 [ABSTRACT FROM AUTHOR]

As secondary aerosols become larger fractions of ambient PM 2.5 , emission factors and source profiles need to reflect the photochemical aging of multipollutant emissions that account for changes in transport between source and receptor. Oxidation Flow Reactors (OFR) intend to simulate gas/particle transformation and volatilization with time-scales of hours to days in order to estimate mass gains or losses due to atmospheric aging. The commercially-available Potential Aerosol Mass (PAM)-OFR (Aerodyne Research, LLC, Billerica, MA, USA) is evaluated for its feasibility in establishing an emission limit certification protocol for China and for determining changes to source marker abundances used in source apportionment model applications. The OFR without ultraviolet radiation is reasonably inert to the passage of reactive gases, such as sulfur dioxide (SO 2), and particles >~100 nm. The largest uncertainty in estimating aging times is the commonly used assumption that the average atmospheric hydroxyl concentration (OH atm) is 1.5 × 106 molecules/cm3; measurements show that OH atm can vary by an order of magnitude in different environments. OH exposures (OH exp) estimated within the OFR are more precise than this assumption. Plug flow is a reasonable estimate of residence time within the OFR, as it does not differ much from the weighted-mean of the residence time distribution. A survey of previous studies shows that only a few examine the PAM-OFR performance, and that mass is both gained and lost with aging, depending on the combustion fuels, burning conditions, and aging times. At present, the OFR appears to be more practical for source profile aging than for emission certification, and further experiments are needed prior to application for multipollutant effects on particulate emission rates. [ABSTRACT FROM AUTHOR]

• Early prenatal exposure to 26 suspected endocrine disruptors was related to lower IQ in children. • The endocrine disruptor mixture disproportionately impacted boys. • Replacement analogue bisphenol F (BPF), may not be a safer alternative to BPA. • Preventing short-lived pollutant exposure among pregnant women may mitigate effects. Endocrine disrupting chemicals (EDCs) are xenobiotics with the ability to interfere with hormone action, even at low levels. Prior environmental epidemiology studies link numerous suspected EDCs, including phthalates and bisphenol A (BPA), to adverse neurodevelopmental outcomes. However, results for some chemicals were inconsistent and most assessed one chemical at a time. To evaluate the overall impact of prenatal exposure to an EDC mixture on neurodevelopment in school-aged children, and identify chemicals of concern while accounting for co-exposures. Among 718 mother-child pairs from the Swedish Environmental Longitudinal, Mother and child, Asthma and allergy study (SELMA) study, we used Weighted Quantile Sum (WQS) regression to assess the association between 26 EDCs measured in 1st trimester urine or blood, with Wechsler Intelligence Scale for Children (IV) Intelligence Quotient (IQ) scores at age 7 years. Models were adjusted for child sex, gestational age, mother's education, mother's IQ (RAVEN), weight, and smoking status. To evaluate generalizability, we conducted repeated holdout validation, a machine learning technique. Using repeated holdout validation, IQ scores were 1.9-points (CI = −3.6, −0.2) lower among boys for an inter-quartile-range (IQR) change in the WQS index. BPF made the largest contribution to the index with a weight of 14%. Other chemicals of concern and their weights included PBA (9%), TCP (9%), MEP (6%), MBzP (4%), PFOA (6%), PFOS (5%), PFHxS (4%), Triclosan (5%), and BPA (4%). While we did observe an inverse association between EDCs and IQ among all children when training and testing the WQS index estimate on the full dataset, these results were not robust to repeated holdout validation. Among boys, early prenatal exposure to EDCs was associated with lower intellectual functioning at age 7. We identified bisphenol F as the primary chemical of concern, suggesting that the BPA replacement compound may not be any safer for children. Future studies are needed to confirm the potential neurotoxicity of replacement analogues. [ABSTRACT FROM AUTHOR]

In this paper, we present a differential game model of watershed multi-pollutant transboundary pollution in which the pollutants can be either technological substitutes or complements, and the abatement costs of two pollutants are not separable. It is the first time that the multi-pollutant is derived in a cooperative differential game on transboundary pollution control. The results are discussed with some illustrative examples under the cases of the pollutants are substitutes and complements. Our results show that (i) the system always admits saddle point steady-state equilibrium under the non-cooperative and cooperative games,respectively; (ii) when the pollutants are substitutes or complements, the upstream region optimal emission levels in the cooperative game are lower than that in the non-cooperative game; while the downstream region optimal emission levels in the cooperative game are equal to that in the non-cooperative game; (iii) the upstream region optimal pollution stocks in the cooperative game are lower than that in the non-cooperative game under the case when the pollutants are substitutes or complements. • Developing a dynamic model of multi-pollutant transboundary pollution. • The pollutants can be either technological substitutes or complements. • The abatement costs of two pollutants are not separable. • The system always admits saddle point steady-state equilibrium. [ABSTRACT FROM AUTHOR]