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This study evaluated the 12-year trends in serum levels of 28 organochlorine pesticides (OCPs) in 880 adults living in Seoul, Korea. The OCP levels decreased from 2006 to 2017, and p,p'-dichlorodiphenyldichloroethylene was a predominant compound. OCP levels were higher in females than in males, and showed positive associations with BMI and age. The OCP concentrations had inverted U-shaped associations with low-density lipoprotein cholesterol and total cholesterol. Concentrations of β-hexachlorocyclohexane were significantly higher in patients with hypertension than in participants that were normotensive. OCP levels showed positive associations with uric acid, creatinine, and thyroid-stimulating hormone, but negative associations with free thyroxine. Participants with diabetes had significantly higher OCP levels than those without it. Principal component analysis suggested possible differences in disease manifestation depending on the composition of OCPs. These results suggest that OCPs might disturb renal transport and thyroid homeostasis. To our knowledge, the inverted U-shaped associations of heptachlor epoxide and endosulfan with cholesterol, the epidemiological associations of trans-nonachlor and endosulfan with thyroid hormones, and the association of p,p'-DDE with hyperuricemia have not been previously reported in general population. This is the first long-term study to show trends of 28 OCPs in serum and associations with various health indicators in Korea., (Copyright © 2021 Elsevier B.V. All rights reserved.)

Background: Volatile organic compounds (VOCs) have been detected in feminine hygiene products (FHPs), especially in tampons and sanitary pads. However, little is known about whether menstrual products can contribute to VOC exposure in women. Our objectives were to: (1) examine the variations of urinary VOC concentrations during menstrual cycles; (2) evaluate the relationships between the use of menstrual products and urinary VOC concentrations; and (3) link urinary VOC concentrations to those measured in menstrual products. Methods: We measured urinary concentrations of 98 target VOCs in 25 reproductive-aged women with 100 repeated measures collected between October 2018 and February 2019. First-morning-void urine samples were collected four times for each woman during one menstrual cycle. Urinary VOC concentrations were measured using gas chromatography-mass spectroscopy. Results: Of 98 target VOCs measured in the urine samples, 36 VOCs were detected. We did not see statistically significant variations in VOC concentrations across the menstrual cycle. After multivariable adjustment, tampon users had significantly higher concentrations of 2-butanone ( β  = 1.58 log ng/g, 95% confidence interval [CI]: 0.16-3.00, p  = 0.03) and methyl isobutyl ketone ( β  = 0.63 log ng/g, 95% CI: 0.03-1.22, p  = 0.04), compared with pad users. Higher n-nonane, benzene, and toluene estimated from menstrual products were associated with higher urinary concentrations in women. Conclusion: The use of FHPs during menses might be a potential source of VOCs. A larger cohort study is warranted to confirm our results and evaluate clinical implications.

Penalized regression methods are used in many biomedical applications for variable selection and simultaneous coefficient estimation. However, missing data complicates the implementation of these methods, particularly when missingness is handled using multiple imputation. Applying a variable selection algorithm on each imputed dataset will likely lead to different sets of selected predictors. This paper considers a general class of penalized objective functions which, by construction, force selection of the same variables across imputed datasets. By pooling objective functions across imputations, optimization is then performed jointly over all imputed datasets rather than separately for each dataset. We consider two objective function formulations that exist in the literature, which we will refer to as "stacked" and "grouped" objective functions. Building on existing work, we (a) derive and implement efficient cyclic coordinate descent and majorization-minimization optimization algorithms for continuous and binary outcome data, (b) incorporate adaptive shrinkage penalties, (c) compare these methods through simulation, and (d) develop an R package miselect. Simulations demonstrate that the "stacked" approaches are more computationally efficient and have better estimation and selection properties. We apply these methods to data from the University of Michigan ALS Patients Biorepository aiming to identify the association between environmental pollutants and ALS risk. Supplementary materials are available online.

Most epidemiologic studies fail to capture the impact of spatiotemporal fluctuations in traffic on exposure to traffic-related air pollutants in the near-road population. Using a case-crossover design and the Research LINE source (R-LINE) dispersion model with spatiotemporally resolved highway traffic data, we quantified associations between primary pollutants generated by highway traffic-particulate matter with an aerodynamic diameter less than or equal to 2.5 μm (PM2.5), oxides of nitrogen (NOx), and black carbon (BC)-and daily nonaccidental, respiratory, cardiovascular, and cerebrovascular mortality among persons who had resided within 1 km (0.6 mile) of major highways in the Puget Sound area of Washington State between 2009 and 2013. We estimated these associations using conditional logistic regression, adjusting for time-varying covariates. Although highly resolved modeled concentrations of PM2.5, NOx, and BC from highway traffic in the hours before death were used, we found no evidence of an association between mortality and the preceding 24-hour average PM2.5 exposure (odds ratio = 0.99, 95% confidence interval: 0.96, 1.02) or exposure during shorter averaging periods. This work did not support the hypothesis that mortality risk was meaningfully higher with greater exposures to PM2.5, NOx, and BC from highways in near-road populations, though we did incorporate a novel approach to estimate exposure to traffic-generated air pollution based on detailed traffic congestion data., (© The Author(s) 2021. Published by Oxford University Press on behalf of the Johns Hopkins Bloomberg School of Public Health. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.)

Electronic waste (e-waste) disposal and recycling activities such as burning and smelting can emit particulate matter (PM), polycyclic aromatic hydrocarbons (PAHs), and other pollutants that expose workers and nearby communities. At informal e-waste recycling facilities, both emission controls and protective measures for workers are absent. This study characterizes personal exposures (breathing zone) of PM and PAHs of e-waste workers at the large Agbogbloshie e-waste site in Accra, Ghana. We collected gravimetric and optical measurements of PM 2.5 and PM 10 using shift samples for workers and for an age- and gender-matched reference population. PM 2.5 filters were analyzed for 26 PAHs using gas chromatography/mass spectroscopy. Among e-waste workers, PM 2.5 and PM 10 concentrations were 99 ± 56 and 218 ± 158 µg/m 3 (median ± interquartile range, optical measurements), respectively; these levels were 78 and 57% higher, respectively, than levels measured at a fixed site that was centrally located at the waste site. In the reference community, breathing zone PM 2.5 and PM 10 levels were lower, 49 ± 20 and 131 ± 108 µg/m 3 , respectively, and the fraction of coarse PM was larger. We detected all 26 target PAHs, of which naphthalene and phenanthrene were the most abundant. PAH concentrations were weakly correlated to PM levels, but PAH abundances, representing the fraction of PAH mass to the total PM 2.5 mass collected, were strongly and inversely correlated to PM levels, suggesting multiple and different sources of PAHs and PM that affected exposures. Both PM and PAH levels were elevated for workers performing burning and dismantling, and both exceeded standards or risk-based guidelines, e.g., lifetime excess cancer risks for several PAHs were in the 10 -4 to 10 -6 range, indicating the need to reduce emissions as well as provide respiratory protection. The study emphasizes the importance of using personal and shift samples to accurately characterize worker exposure., (Copyright © 2021 The Authors. Published by Elsevier Ltd.. All rights reserved.)

Background: Informal electronic waste recycling activities are major contributors to ambient air pollution, yet studies assessing the effects or relationship between direct/continuous exposure of informal e-waste workers to particulate matter and cardiovascular function are rare., Methods: Repeated measurements of fractions of PM 2.5 , PM 10-2.5 , and PM 10 in personal air of informal e-waste workers, (n = 142) and a comparable group (n = 65) were taken over a period of 20 months (March 2017 to November, 2018). Concurrently, 5-min resting electrocardiogram was performed on each participant to assess resting heart rate variability indices. Linear mixed-effects models were used to assess the association between PM fractions and cardiac function., Results: SDNN, RMSSD, LF, HF and LH/HF ratio were all associated with PM. Significant associations were observed for PM 2.5 and Mean NN (p = 0.039), PM10 and SDNN (p = 0.035) and PM 10-2.5 and LH/HF (p = 0.039). A 10 μg/m 3 increase in the concentrations of PM 2.5 , PM 10-2.5 , and PM 10 in personal air was associated with reduced HRV indices and increased resting HR. A 10 μg/m 3 per interquartile (IQR) increase in PM 10-2.5 and PM 10 , decreased SDNN by 11% [(95% CI: - 0.002- 0.000); (p = 0.187)] and 34% [(95% CI: - 0.002-0.001); (p = 0.035)] respectively. However, PM 2.5 increased SDNN by 34% (95% CI: - 1.32-0.64); (p = 0.493). Also, 10 μg/m 3 increase in PM 2.5 , PM 10-2.5 and PM 10 decreased RMSSD by 27% [(- 1.34-0.79); (p = 0.620)], 11% [(- 1.73, 0.95); (p = 0.846)] and 0.57% [(- 1.56-0.46); (p = 0.255%)]., Conclusion: Informal e-waste workers are at increased risk of developing cardiovascular disease from cardiac autonomic dysfunction as seen in reduced HRV and increased heart rate., (© 2021. The Author(s).)

Objective: This study assessed the associations between blood and urine levels of toxic metals; cadmium (Cd) and lead (Pb), and methylation levels of the LINE-1 gene among e-waste and control populations in Ghana., Methods: The study enrolled 100 male e-waste workers and 51 all-male non-e-waste workers or controls. The concentrations of Cd and Pb were measured in blood and urine using inductively coupled plasma mass spectrometry, while LINE1 methylation levels were assessed by pyrosequencing of bisulfite-converted DNA extracted from whole blood. Single and multiple metals linear regression models were used to determine the associations between metals and LINE1 DNA methylation., Results: Blood lead (BPb) and urine lead (UPb) showed higher median concentrations among the e-waste workers than the controls (76.82 µg/L vs 40.25 µg/L, p ≤ 0.001; and 6.89 µg/L vs 3.43 µg/L, p ≤ 0.001, respectively), whereas blood cadmium (BCd) concentration was lower in the e-waste workers compared to the controls (0.59 µg/L vs 0.81 µg/L, respectively, p = 0.003). There was no significant difference in LINE1 methylation between the e-waste and controls (85.16 ± 1.32% vs 85.17 ± 1.11%, p = 0.950). In our single metal linear regression models, BPb was significantly inversely associated with LINE1 methylation in the control group (β BPb  = - 0.027, 95% CI - 0.045, - 0.010, p = 0.003). In addition, a weak association between BPb and LINE1 was observed in the multiple metals analysis in the e-waste worker group (β BPb  = - 0.005, 95% CI - 0.011, 0.000, p = 0.058)., Conclusion: Continuous Pb exposure may interfere with LINE1 methylation, leading to epigenetic alterations, thus serving as an early epigenetic marker for future adverse health outcomes., (© 2021. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

Informal e-waste recycling processes emit various air pollutants. While there are a number of pollutants of concern, little information exists on volatile organic compounds (VOCs) releases at e-waste sites. To assess occupational exposures and estimate health risks, we measured VOC levels at the Agbogbloshie e-waste site in Ghana, the largest e-waste site in Africa, by collecting both fixed-site and personal samples for analyzing a wide range of VOCs. A total of 54 VOCs were detected, dominated by aliphatic and aromatic compounds. Mean and median concentrations of the total target VOCs were 46 and 37 μg/m 3 at the fixed sites, and 485 and 162 μg/m 3 for the personal samples. Mean and median hazard ratios were 2.1 and 1.4, respectively, and cancer risks were 4.6 × 10 -4 and 1.5 × 10 -4 . These risks were predominantly driven by naphthalene and benzene; chloroform and formaldehyde were also high in some samples. Based on the VOC composition, the major sources were industry, fuel evaporation and combustion. The concentration gradient across sites and the similarity of VOC profiles indicated that the e-waste site emissions reached neighboring communities. Our results suggest the need to protect e-waste workers from VOC exposure, and to limit emissions that can expose nearby populations., (Copyright © 2021 Elsevier B.V. All rights reserved.)

Noise exposure can affect sleep, health and cognitive performance, and it disproportionately affects communities of color. This study has the objective of evaluating both conventional and supplemental noise metrics in a community noise survey examining Southwest Detroit, Michigan, a densely populated and industrialized area with extensive truck traffic on residential streets. Sound pressure level (SPL) monitors were deployed at 21 residential sites within 900 m of a major interstate highway. With assistance from youth volunteers, continuous SPL measurements were obtained for 1.5-7 days at each site, and short-term vehicle counts on local roads were recorded. We calculated conventional noise metrics, including the day-evening-night average sound level L DEN and the 90th percentile 1-hr maximum L 10 (h), and evaluated the effect of distance from highways, traffic volume, time-of-day, and other factors. Supplemental metrics potentially appropriate for intermittent traffic noise were calculated, including fraction of time over specific SPL thresholds using a new metric called F DEN , which is the fraction of time over 60, 65 and 70 dB during night, evening and daytime periods, respectively, and a peak noise metric called L 2P (h), which utilizes the 98th percentile SPL within time blocks to increase robustness. The conventional metrics indicated five sites that exceeded 70 dB, and the highest noise levels were found within ~50 m of truck routes, arterials and freeway ramps. The estimated impact of truck traffic ranged up to 17 dB for hourly averages and to 33 dB for 1-s peaks. The conventional metrics did not always capture short-term noise exposures, which may be especially important to annoyance and sleep issues. In addition to showing widespread exposure to traffic noise in the study community that warrants consideration of noise abatement strategies, the study demonstrates the benefits of supplemental noise metrics and community engagement in noise assessment., (Copyright © 2021 Elsevier Inc. All rights reserved.)

Hotel housekeepers represent a large, low-income, predominantly minority, and high-risk workforce. Little is known about their exposure to chemicals, including volatile organic compounds (VOCs). This study evaluates VOC exposures of housekeepers, sources and factors affecting VOC levels, and provides preliminary estimates of VOC-related health risks. We utilized indoor and personal sampling at two hotels, assessed ventilation, and characterized the VOC composition of cleaning agents. Personal sampling of hotel staff showed a total target VOC concentration of 57 ± 36 µg/m 3 (mean ± SD), about twice that of indoor samples. VOCs of greatest health significance included chloroform and formaldehyde. Several workers had exposure to alkanes that could cause non-cancer effects. VOC levels were negatively correlated with estimated air change rates. The composition and concentrations of the tested products and air samples helped identify possible emission sources, which included building sources (for formaldehyde), disinfection by-products in the laundry room, and cleaning products. VOC levels and the derived health risks in this study were at the lower range found in the US buildings. The excess lifetime cancer risk (average of 4.1 × 10 -5 ) still indicates a need to lower exposure by reducing or removing toxic constituents, especially formaldehyde, or by increasing ventilation rates., (© 2020 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.)

The Michigan Pollution Assessment Laboratory (MPAL) is a mobile air quality monitoring platform designed to measure conventional, toxic, and greenhouse gas (GHG) air pollutants. The spatially and temporally resolved data collected can be used for multiple purposes, such as mapping spatial patterns and identifying peaks. The truck-based platform includes instrumentation for 11 gaseous pollutants and for particulate matter (PM), size distribution (7 nm to 20 μm), PM 10 , black and brown carbon, and trace metals. MPAL is equipped with meteorological instruments, a high-accuracy GPS, forward and reverse cameras, and a data logging and display system. We selected commercially available instrumentation based on sensitivity, response time, and robustness. The vehicle's power system allows ~ 6.5 h of continuous operation with all instruments operating. This article details the design, construction, and evaluation of MPAL and summarizes data collected in its first year (March 2019 to March 2020) of operation. We completed a series of runs on 84 days in Detroit, Michigan, an area with a diverse set of traffic, industrial, and commercial emission sources, and collected 265,816 1-s observations (excluding collocations, zero checks, and other quality assurance measurements). Using data from these runs as well as special tests, we present results of performance evaluations that examined the response time, PM losses, and wind measurements and compare results to stationary regulatory monitoring data. We highlight key issues and provide practical solutions to help evaluate and resolve these issues and share many lessons learned in developing and using a mobile platform.

Background: Epidemiologic studies on associations between metals and insulin resistance and β-cell dysfunction have been cross-sectional and focused on individual metals., Objective: We assessed the association of exposure to metal mixtures, based on assessment of 15 urinary metals, with both baseline levels and longitudinal changes in homeostatic model assessments for insulin resistance (HOMA-IR) and β-cell function (HOMA-β)., Methods: We examined 1262 women, aged 45-56 years at baseline (1999-2000), who were followed through 2015-2016, from the Study of Women's Health Across the Nation. Urinary concentrations of 15 metals (arsenic, barium, cadmium, cobalt, cesium, copper, mercury, manganese, molybdenum, nickel, lead, antimony, tin, thallium, and zinc) were determined at baseline. HOMA-IR and HOMA-β were repeatedly measured over 16 years of follow-up. A two-stage modeling was used to account for correlations in dependent and independent variables: In stage-1, linear mixed effects models were used to estimate the participant-specific baseline HOMA levels from random intercepts and participant-specific rates of changes from random slopes. In stage-2, adaptive elastic-net (AENET) models were fit to identify components of metal mixtures associated with participant-specific baseline levels and rates of changes in HOMA-IR and HOMA-β, respectively. An environmental risk score (ERS) was used to integrate metal mixture effects from AENET results., Results: In multivariable adjusted AENET models, urinary zinc was associated with higher HOMA-IR at baseline, whereas molybdenum was associated with lower HOMA-IR at baseline. The estimated changes in baseline HOMA-IR for one standard deviation increase in log-transformed urinary metal concentrations were 5.76% (3.05%, 8.55%) for zinc and -3.25% (-5.45%, -1.00%) for molybdenum, respectively. Urinary zinc was also associated with lower HOMA- β at baseline. Arsenic was associated with a slightly faster rate of decline in HOMA-β in the AENET model evaluating associations between metals and rate of changes. Significant associations of ERS with both HOMA-IR and HOMA-β at baseline were observed. ERS for the rate of changes was not calculated and examined in relation to rates of changes in HOMA-IR and HOMA-β because only a single metal was selected by AENET., Conclusion: Exposure to metal mixtures may be exerting effects on insulin resistance and β-cell dysfunction, which might be mechanisms by which metal exposures lead to elevated diabetes risks., (Copyright © 2020 The Author(s). Published by Elsevier Ltd.. All rights reserved.)

Feminine hygiene products (FHPs) are used on highly permeable and sensitive vaginal and vulvar tissues by many women. These products contain a variety of chemicals, and few regulations require disclosure of their ingredients. The objectives of this study are to identify volatile organic compounds (VOCs) that may be present in these products and to evaluate the potential for exposure and health risk associated with product use. We collected 79 commercially available FHPs, including washes, tampons, menstrual pads, wipes, sprays, powders and moisturizers, and analyzed their composition using purge and trap sampling, thermal desorption, gas chromatography and mass spectroscopy. Exposures and risks were modeled using reasonable upper bound exposure scenarios. The highest VOC concentrations (as total target VOCs) were found in washes, sprays and powders, with median concentrations from 25,000 to 34,000 ng/g. Benzene (maximum: 3,604 ng/g) was detected in 83% of the collected products, and 1,4-dioxane (maximum: 24,354 ng/g) in 50% of the products. VOC composition depended on the FHP type, manufacturer and brand. Products labeled as "organic," "natural," or "for sensitive skin" did not necessarily have lower VOC concentrations. For most FHPs, calculated risks were low; however, menstrual pads had hazard ratios of up to 11, sprays and powders had hazard ratios of up to 2.2 and excess cancer risks of up to 2.1 × 10 -6 , and washes had excess cancer risks of up to 3.3 × 10 -6 . Our data suggest that all tested FHPs contained some toxic VOCs, and that risks of using some products should be addressed. We recommend the elimination of toxic ingredients and the disclosure of all chemicals that are used in these products., (Copyright © 2020 The Authors. Published by Elsevier Ltd.. All rights reserved.)

Context: Previous epidemiologic studies of per- and polyfluoroalkyl substances (PFASs) and menopausal timing conducted in cross-sectional settings were limited by reverse causation because PFAS serum concentrations increase after menopause., Objectives: To investigate associations between perfluoroalkyl substances and incident natural menopause., Design and Setting: A prospective cohort of midlife women, the Study of Women's Health Across the Nation, 1999-2017., Participants: 1120 multiracial/ethnic premenopausal women aged 45-56 years., Methods: Serum concentrations of perfluoroalkyls were quantified by high-performance liquid chromatography isotope dilution tandem mass spectrometry. Natural menopause was defined as the bleeding episode prior to at least 12 months of amenorrhea not due to surgery or hormone use. Cox proportional hazards models were used to calculate hazard ratios (HRs) and 95% confidence intervals (CIs)., Results: Participants contributed 5466 person-years of follow-up, and 578 had incident natural menopause. Compared with the lowest tertile, women at the highest tertile of baseline serum concentrations had adjusted HR for natural menopause of 1.26 (95% CI: 1.02-1.57) for n-perfluorooctane sulfonic acid (n-PFOS) (Ptrend = .03), 1.27 (95% CI: 1.01-1.59) for branched-PFOS (Ptrend = .03), and 1.31 (95% CI: 1.04-1.65) for n-perfluorooctanoic acid (Ptrend = .01). Women were classified into four clusters based on their overall PFAS concentrations as mixtures: low, low-medium, medium-high, and high. Compared with the low cluster, the high cluster had a HR of 1.63 (95% CI: 1.08-2.45), which is equivalent to 2.0 years earlier median time to natural menopause., Conclusion: This study suggests that select PFAS serum concentrations are associated with earlier natural menopause, a risk factor for adverse health outcomes in later life., (© Endocrine Society 2020. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.)

Older buildings in the United States often contain lead paint, and their demolition poses the risk of community lead exposure. We investigated associations between demolitions and elevated blood lead levels (EBLLs) among Detroit children aged <6 years, 2014-2018, and evaluated yearly variation given health and safety controls implemented during this time. Case-control analysis included incident EBLL cases (≥5 µg/dL) and non-EBLL controls from test results reported to the Michigan Department of Health and Human Services. Exposure was defined as the number of demolitions (0, 1, 2+) within 400 feet of the child's residence 45 days before the blood test. We used logistic regression to calculate odds ratios (ORs) and 95% confidence intervals (CIs), and test effect modification by year. Associations between demolition and EBLL differed yearly ( p = 0.07): 2+ demolitions were associated with increased odds of EBLLs in 2014 (OR: 1.75; 95% CI: (1.17, 2.55), 2016 (2.36; 1.53, 3.55) and 2017 (2.16; 1.24, 3.60), but not in 2018 (0.94; 0.41, 1.86). This pattern remained consistent in sensitivity analyses. The null association in 2018 may be related to increased health and safety controls. Maintenance of controls and monitoring are essential, along with other interventions to minimize lead exposure, especially for susceptible populations.

Air quality information is scarce in low- and middle-income countries. This study describes the application of moderate cost approaches that can provide spatial and temporal information on concentrations of particulate matter (PM) needed to assess community and occupational exposures. We evaluated PM levels at the Agbogbloshie e-waste and scrap yard site in Accra, Ghana, and at upwind and downwind locations, obtaining both optical and gravimetric measurements, local meteorological data and satellite aerosol optical depth. Due to overload issues, the gravimetric 24-hr samplers were modified for periodic sampling and some optical data were screened for quality assurance. Exceptionally high concentrations (e.g., 1-hr average PM 10 exceeding 2000 μg/m 3 ) were sometimes encountered near combustion sources, including open fires at the e-waste site and spoil piles. 24-hr PM 2.5 levels averaged 31, 88 and 57 μg/m 3 at upwind, e-waste and downwind sites, respectively, and PM 10 averaged 145, 214 and 190 μg/m 3 , considerably exceeding air quality standards. Upwind levels likely reflected biomass burning that is prevalent in the surrounding informal settlements; levels at the e-waste and downwind sites also reflected contributions from biomass combustion and traffic. The highest PM levels occurred in evenings, influenced by diurnal changes in emission rates, atmospheric dispersion and wind direction shifts. We demonstrate that moderate cost instrumentation, with some modifications, appropriate data cleaning protocols, and attention to understanding local sources and background levels, can be used to characterize spatial and temporal variation in PM levels in urban and industrial areas., Competing Interests: The authors declare no conflicts of interest relevant to this study., (©2020. The Authors.)

Background: Informal recycling of electronic waste (e-waste) releases particulate matter (PM) into the ambient air. Human exposure to PM has been reported to induce adverse effects on cardiovascular health. However, the impact of PM on the cardiovascular health of e-waste recyclers in Ghana has not been studied. Although intake of micronutrient-rich diet is known to modify these PM-induced adverse health effects, no data are available on the relationship between micronutrient status of e-waste recyclers and the reported high-level exposure to PM. We therefore investigated whether the intake of micronutrient-rich diets ameliorates the adverse effects of ambient exposure to PM 2.5 on blood pressure (BP)., Methods: This study was conducted among e-waste and non-e-waste recyclers from March 2017 to October 2018. Dietary micronutrient (Fe, Ca, Mg, Se, Zn, and Cu) intake was assessed using a 2-day 24-h recall. Breathing zone PM 2.5 was measured with a real-time monitor. Cardiovascular indices such as systolic BP (SBP), diastolic BP (DBP), and pulse pressure (PP) were measured using a sphygmomanometer. Ordinary least-squares regression models were used to estimate the joint effects of ambient exposure to PM 2.5 and dietary micronutrient intake on cardiovascular health outcomes., Results: Fe was consumed in adequate quantities, while Ca, Se, Zn, Mg, and Cu were inadequately consumed among e-waste and non-e-waste recyclers. Dietary Ca, and Fe intake was associated with reduced SBP and PP of e-waste recyclers. Although PM 2.5 levels were higher in e-waste recyclers, exposures in the control group also exceeded the WHO 24-h guideline value (25 μg/m 3 ). Exposure to 1 μg/m 3 of PM 2.5 was associated with an increased heart rate (HR) among e-waste recyclers. Dietary Fe intake was associated with a reduction in systolic blood pressure levels of e-waste recyclers after PM exposure., Conclusions: Consistent adequate dietary Fe intake was associated with reduced effects of PM 2.5 on SBP of e-waste recyclers overtime. Nonetheless, given that all other micronutrients are necessary in ameliorating the adverse effects of PM on cardiovascular health, nutrition-related policy dialogues are required. Such initiatives would help educate informal e-waste recyclers and the general population on specific nutrients of concern and their impact on the exposure to ambient air pollutants.

Background : Direct and continuous exposure to particulate matter (PM), especially in occupational settings is known to impact negatively on respiratory health and lung function. Objective : To determine the association between concentrations of PM (2.5, 2.5-10 and 10 µm) in breathing zone and lung function of informal e-waste workers at Agbogbloshie. Methods : To evaluate lung function responses to PM (2.5, 2.5-10 and 10 µm), we conducted a longitudinal cohort study with three repeated measures among 207 participants comprising 142 healthy e-waste workers from Agbogbloshie scrapyard and 65 control participants from Madina-Zongo in Accra, Ghana from 2017-2018. Lung function parameters (FVC, FEV1, FEV1/FVC, PEF, and FEF 25-75) and PM (2.5, 2.5-10 and 10 µm) concentrations were measured, corresponding to prevailing seasonal variations. Socio-demographic data, respiratory exposures and lifestyle habits were determined using questionnaires. Random effects models were then used to examine the effects of PM (2.5, 2.5-10 and 10 µm) on lung function. Results : The median concentrations of PM (2.5, 2.5-10 and 10 µm) were all consistently above the WHO ambient air standards across the study waves. Small effect estimates per IQR of PM (2.5, 2.5-10 and 10 µm) on lung function parameters were observed even after adjustment for potential confounders. However, a 10 µg increase in PM (2.5, 2.5-10 and 10 µm) was associated with decreases in PEF and FEF 25-75 by 13.3% % [β = -3.133; 95% CI: -0.243, -0.022) and 26.6% [β = -0.266; 95% CI: -0.437, 0.094]. E-waste burning and a history of asthma significantly predicted a decrease in PEF by 14.2% [β = -0.142; 95% CI: -0.278, -0.008) and FEV1 by 35.8% [β = -0.358; 95% CI: -0.590, 0.125] among e-waste burners. Conclusions : Direct exposure of e-waste workers to PM predisposes to decline in lung function and risk for small airway diseases such as asthma and COPD.

Introduction: The adverse health effects associated with exposure to traffic-related air pollutants (TRAPs) remain a key public health issue. Often, exposure assessments have not represented the small-scale variation and elevated concentrations found near major roads and in urban settings. This research explores approaches aimed at improving exposure estimates of TRAPs that can reduce exposure measurement error when used in health studies. We consider dispersion models designed specifically for the near-road environment, as well as spatiotemporal and data fusion models. These approaches are implemented and evaluated utilizing data collected in recent modeling, monitoring, and epidemiological studies conducted in Detroit, Michigan., Approach: Dispersion models, which estimate near-road pollutant concentrations and individual exposures based on first principles - and in particular, high fidelity models - can provide great flexibility and theoretical strength. They can represent the spatial variability of TRAP concentrations at locations not measured by conventional and spatially sparse air quality monitoring networks. A number of enhancements to dispersion modeling and mobile on-road emissions inventories were considered, including the representation of link-based road networks and updated estimates of temporal allocation of traffic activity, emission factors, and meteorological inputs. The recently developed Research LINE-source model (RLINE), a Gaussian line-source dispersion model specifically designed for the near-road environment, was used in an operational evaluation that compared predicted concentrations of nitrogen oxides (NO x ), carbon monoxide (CO), and PM 2.5 (particulate matter ≤ 2.5 µm in aerodynamic diameter) with observed concentrations at air quality monitoring stations located near high-traffic roads. Spatiotemporal and data fusion models provided additional and complementary approaches for estimating TRAP exposures. We formulated both nonstationary universal kriging models that exploit the spatial correlation in the monitoring data, and data fusion models that leverage the information contained in both the monitoring data and the output of numerical models, specifically RLINE. These models were evaluated using observations of nitric oxide (NO), NO x , black carbon (BC), and PM 2.5 monitored along transects crossing major roads in Detroit. We also examined model assumptions, including the appropriateness of the covariance functions, errors in RLINE outputs, and the effects of jointly modeling two pollutants and using an updated emission inventory., Results: For CO and NO x , dispersion model performance was best when monitoring sites were close to major roads, during downwind conditions, during weekdays, and during certain seasons. The ability to discern local and particularly the traffic-related portion of PM 2.5 was limited, a result of high background levels, the sparseness of the monitoring network, and large uncertainties for certain sources (e.g., area, fugitive) and some processes (e.g., formation of secondary aerosols). Sensitivity analyses of alternative meteorological inputs and updated emission factors showed some performance gain when using local (on-site) meteorological data and updated inventories. Overall, the operational evaluation suggested RLINE's usefulness for estimating spatially and temporally resolved exposure estimates. The application of the universal kriging models confirmed that wind speed and direction are important drivers of nonstationarity in pollutant concentrations, and that these models can predict exposure estimates that have lower prediction errors than do stationary model counterparts. The application of the Bayesian data fusion models suggested that the RLINE output had a spatially varying additive bias for NO x and PM 2.5 and provided little additional information for NO x , besides what is already contained in traffic and geographical information system (GIS) covariates, but had improved estimates of PM 2.5 concentrations. Results of the nonstationary Bayesian data fusion model that used RLINE output across a field spanning the measurement sites were similar to a regression-based Bayesian data fusion approach that used only RLINE output at the monitoring locations, with the latter being computationally less burdensome. Using the regression-based Bayesian data fusion model, we found that RLINE with the updated emission inventory provided results that were more useful for estimating NO x concentration at unmonitored sites, but the updated emission inventory did not improve predictions of PM 2.5 concentrations. Joint modeling of NO x and PM 2.5 was not useful, a result of differences in RLINE's utility in predicting PM 2.5 and NO x - useful for the former, but not for the latter - and differences in the spatial dependence structures of the two pollutants. Overall, information provided by RLINE was shown to have the potential to improve spatiotemporal estimates of TRAP concentrations., Conclusions: The study results should be interpreted and generalized cautiously given the limitations of the data used. Similar analyses in other settings are recommended for confirming and extending our findings. Still, the study highlights considerations that are relevant for exposure estimates used in health studies. The ability of a dispersion model to accurately reproduce and predict a pollutant depends on the pollutant as well as on spatial and temporal factors, such as the distance and direction from the road, time-of-day, and day-of-week. The nature and source of exposure measurement errors should be taken into consideration, particularly in health studies that take advantage of time- activity information that describes where and when individuals are exposed to pollution. Efforts to refine model inputs and improve model performance can be helpful; meteorological inputs may be the most critical. For both dispersion and spatiotemporal statistical models, sufficient and high-quality monitoring data are essential for developing and evaluating these models. Our analyses using Bayesian data fusion models confirm the presence of spatially varying errors in dispersion model outputs and allow quantification of both the magnitude and the spatial nature of these errors. This valuable information can be leveraged in health studies examining air pollution exposure as well as in studies informing regulatory responses., (© 2020 Health Effects Institute. All rights reserved.)

Background: Limited information exists regarding longitudinal trends in midlife women's exposure to perfluoroalkyl and polyfluoroalkyl substances (PFAS). Further, little is known about how patterns of exposure differ by race/ethnicity and reproductive characteristics including parity and menopause., Objective: We aimed to examine temporal variations in serum PFAS concentrations among midlife women from the Study of Women's Health Across the Nation., Methods: Serum concentrations of 11 PFAS homologues were measured in 75 White, Black and Chinese women with blood samples collected in 1999-2000, 2002-2003, 2005-2006, and 2009-2011. Rates of changes in PFAS concentrations were calculated assuming a first-order elimination model. Associations between PFAS concentrations and race/ethnicity, menstruation and parity were evaluated with linear mixed models, adjusting for age, body mass index and study site., Results: Serum concentrations of linear-chain perfluorooctanoic acid (n-PFOA), linear- and branched-chain perfluorooctane sulfonic acid (n-PFOS and sm-PFOS) decreased significantly (-6.0%, 95% CI: -8.3%, -3.6% per year for n-PFOA; -14.8%, 95% CI: -17.3%, -12.3% per year for n-PFOS; -16.9%, 95% CI: -19.1%, -14.6% per year for sm-PFOS); whereas perfluorononanoic acid (PFNA) increased (16.0%, 95% CI: 10.6%, 21.6% per year). Detection rates of perfluorodecanoic acid (PFDeA) and perfluoroundecanoic acid (PFUA) doubled. Temporal trends varied significantly by race/ethnicity. Chinese women tended to have consistently higher PFNA concentrations at each follow-up visit, compared with White and Black women. Serum PFHxS concentrations significantly decreased in White and Black women, but not in Chinese. Menstruating women consistently had lower concentrations. Parity was associated with lower concentrations at baseline but the differences between nulliparous and parous women became smaller over time., Conclusions: Our results suggest longitudinal declines in serum concentrations of legacy PFAS and increases in serum concentrations of emerging compounds from 1999 to 2011 in midlife women. Temporal trends in PFAS concentrations are not uniform across race/ethnicity and parity groups., (Copyright © 2019 The Authors. Published by Elsevier Ltd.. All rights reserved.)

Background: Feminine hygiene products (FHPs) are personal care products widely used by women. A few studies have detected some volatile organic compounds (VOCs) in FHPs, but no previous epidemiological studies have linked use of these products to human exposure to VOCs using biomarkers. Therefore, we evaluated whether the use of FHPs was associated with VOC exposures among reproductive-aged women in the United States. Materials and Methods: Data on 2432 women aged 20-49 years from National Health and Nutrition Examination Survey 2001-2004 were utilized. Self-reported use of feminine products (tampons, sanitary napkins, vaginal douches, sprays, powders, wipes/towelettes, and other products) was obtained from questionnaires. Survey-weighted linear regression models were used to estimate percent changes in VOC whole blood concentrations and 95% confidence intervals (CIs). Results: Black women had significantly more use of vaginal douching and significantly higher whole blood concentrations of 1,4-dichlorobenzene (DCB) ( p  < 0.0001). After adjusting for confounders, we observed a dose-response relationship between the frequency of vaginal douching in the past 6 months and 1,4-DCB concentrations. Compared with never users, women with occasional use (≤1 time/month) of vaginal douching had 18% (95% CI: -12% to 59%) higher concentrations, and those with frequent use (≥2 time/month) had 81% (95% CI: 2% to 221%) higher concentrations of 1,4-DCB ( p for trend = 0.04). Use of feminine powder in the past month was significantly associated with 36% (95% CI: 0.4% to 83%) higher concentrations of ethylbenzene. Conclusions: Our findings suggest that differences in whole blood VOC concentrations might be explained by feminine hygiene practices. The presence of environmental chemicals in FHPs warrants further examination.

Background: Acute pollutant-related lung function changes among children varies across pollutants and lag periods. We examined whether short-term air pollutant fluctuations were related to daily lung function among a panel of children and whether these effects are modified by airway hyperresponsiveness, location and asthma severity., Methods: Students from randomly selected grade 4 classrooms at seven primary schools in Durban, participated, together with asthmatic children from grades 3-6 (n=423). The schools were from high pollutant exposed communities (south) and compared with schools from communities with lower levels of pollution (north), with similar socioeconomic profiles. Interviews, spirometry and methacholine challenge testing were conducted. Bihourly lung function measurements were performed over a 3-week period in four phases. During all schooldays, students blew into their personal digital monitors every 1.5-2 hours. Nitrogen dioxide (NO 2 ), nitrogen oxide (NO), sulphur dioxide and particulate matter (<10 μm diameter) (PM 10 ) were measured at each school. Generalised estimating equations assessed lag effects, using single-pollutant (single or distributed lags) models., Results: FEV 1 declines ranged from 13 to 18 mL per unit increase in IQR for NO and 14-23 mL for NO 2 . Among the 5-day average models, a 20 mL and 30 mL greater drop in FEV 1 per IQR for NO 2 and NO, respectively, among those with airway hyperresponsiveness compared with those without. Effects were seen among those with normal airways., Conclusions: This first panel study in sub-Saharan Africa, showed significant declines in lung function, in response to NO and NO 2 with effects modified by airway hyperresponsiveness or persistent asthma., Competing Interests: Competing interests: None declared., (© Author(s) (or their employer(s)) 2019. No commercial re-use. See rights and permissions. Published by BMJ.)

Objectives: Approximately 2 billion workers globally are employed in informal settings, which are characterized by substantial risk from hazardous exposures and varying job tasks and schedules. Existing methods for identifying occupational hazards must be adapted for unregulated and challenging work environments. We designed and applied a method for objectively deriving time-activity patterns from wearable camera data and matched images with continuous measurements of personal inhalation exposure to size-specific particulate matter (PM) among workers at an informal electronic-waste (e-waste) recovery site., Methods: One hundred and forty-two workers at the Agbogbloshie e-waste site in Accra, Ghana, wore sampling backpacks equipped with wearable cameras and real-time particle monitors during a total of 171 shifts. Self-reported recall of time-activity (30-min resolution) was collected during the end of shift interviews. Images (N = 35,588) and simultaneously measured PM2.5 were collected each minute and processed to identify activities established through worker interviews, observation, and existing literature. Descriptive statistics were generated for activity types, frequencies, and associated PM2.5 exposures. A kappa statistic measured agreement between self-reported and image-based time-activity data., Results: Based on image-based time-activity patterns, workers primarily dismantled, sorted/loaded, burned, and transported e-waste materials for metal recovery with high variability in activity duration. Image-based and self-reported time-activity data had poor agreement (kappa = 0.17). Most measured exposures (90%) exceeded the World Health Organization (WHO) 24-h ambient PM2.5 target of 25 µg m-3. The average on-site PM2.5 was 81 µg m-3 (SD: 94). PM2.5 levels were highest during burning, sorting/loading and dismantling (203, 89, 83 µg m-3, respectively). PM2.5 exposure during long periods of non-work-related activities also exceeded the WHO standard in 88% of measured data., Conclusions: In complex, informal work environments, wearable cameras can improve occupational exposure assessments and, in conjunction with monitoring equipment, identify activities associated with high exposures to workplace hazards by providing high-resolution time-activity data., (© The Author(s) 2019. Published by Oxford University Press on behalf of the British Occupational Hygiene Society.)

Objective: To determine whether persistent organic pollutants (POP) affect amyotrophic lateral sclerosis (ALS) survival., Methods: ALS participants seen at the University of Michigan (Ann Arbor, MI, USA) provided plasma samples for measurement of POPs. ALS disease and clinical features were collected prospectively from the medical records. Survival models used a composite summary measure of exposure due to multiple POPs (environmental risk score or ERS)., Results: 167 participants (40.7% female, n=68) with ALS were recruited, of which 119 died during the study period. Median diagnostic age was 60.9 years (IQR 52.7-68.2), median time from symptom onset to diagnosis was 1.01 years (IQR 0.67-1.67), bulbar onset 28.7%, cervical onset 33.5% and lumbar onset 37.7%. Participants in the highest quartile of ERS (representing highest composite exposure), adjusting for age at diagnosis, sex and other covariates had a 2.07 times greater hazards rate of mortality (p=0.018, 95% CI 1.13 to 3.80) compared with those in the lowest quartile. Pollutants with the largest contribution to the ERS were polybrominated diphenyl ethers 154 (HR 1.53, 95% CI 0.90 to 2.61), polychlorinated biphenyls (PCB) 118 (HR 1.50, 95% CI 0.95 to 2.39), PCB 138 (HR 1.69, 95% CI 0.99 to 2.90), PCB 151 (HR 1.46, 95% CI 1.01 to 2.10), PCB 175 (HR 1.53, 95% CI 0.98 to 2.40) and p,p'-DDE (HR 1.39, 95% CI 1.07 to 1.81)., Conclusions: Higher concentrations of POPs in plasma are associated with reduced ALS survival, independent of age, gender, segment of onset and other covariates. This study helps characterise and quantify the combined effects of POPs on ALS and supports the concept that environmental exposures play a role in disease pathogenesis., Competing Interests: Competing interests: None declared., (© Author(s) (or their employer(s)) 2019. No commercial re-use. See rights and permissions. Published by BMJ.)

Background: Little is known about the extent of exposure to metals and metal mixtures among midlife women., Objectives: We assessed exposure to multiple metals in the Study of Women's Health Across the Nation (SWAN), a multi-site, multi-racial/ethnic cohort of women at midlife., Methods: We measured urinary concentrations of 21 metals (arsenic, barium, beryllium, cadmium, cobalt, chromium, cesium, copper, mercury, manganese, molybdenum, nickel, lead, platinum, antimony, tin, thallium, uranium, vanadium, tungsten and zinc) using high-resolution inductively coupled plasma-mass spectrometry among 1335 white, black, Chinese and Japanese women aged 45-56 years at the third SWAN annual visit (1999-2000). Least squared geometric mean concentrations were compared across race/ethnicity, education, financial hardship, smoking, secondhand smoking, seafood intake and rice intake groups. Overall exposure patterns of multiple metals were derived using k-means clustering method., Results: The percentage of women with detectable concentrations of metals ranged from 100% for arsenic, cesium, molybdenum and zinc, to less than 5% for platinum; 15 metals had detection rates of 70% or more. Asian women, both Chinese and Japanese, had higher urinary concentrations of arsenic, cadmium, copper, mercury, molybdenum, lead and thallium, compared with other race/ethnic groups, independent of sociodemographic, lifestyle, dietary, and geographic characteristics. Seafood and rice intake were important determinants of urinary arsenic, cesium, mercury, molybdenum and lead levels. Two distinct overall exposure patterns- "high" vs. "low" -- were identified. Women in the "high" overall exposure pattern were more likely to be Asians, current smokers, and to report high consumption of seafood and rice. Black women were less likely to have the high exposure pattern., Conclusions: Metal exposure of midlife women differs by racial/ethnic, sociodemographic, lifestyle, dietary, and geographic characteristics. Asian women may be experiencing the highest exposures to multiple metals compared with other racial/ethnic groups in the United States., (Copyright © 2019 Elsevier GmbH. All rights reserved.)

Purpose: Exposures of nail salon technicians have received attention due to the potentially toxic materials used in nail products, which include volatile organic compounds (VOCs) such as formaldehyde and methyl methacrylate (MMA). This study characterized area and personal concentrations and other indoor air parameters in 17 nail salons in fall and winter seasons in three areas of Michigan., Methods: VOC samples were analyzed using thermal desorption, gas chromatography and mass spectroscopy, and the VOC composition of 35 nail products (e.g., polish, top coat, base coat) was measured using headspace sampling. Ventilation rates were derived using CO 2 concentrations, occupancy and building information, and VOC sources were apportioned by a novel application of chemical mass balance models., Results: We detected ethyl acetate, propyl acetate, butyl acetate, MMA, n-heptane and toluene in most salons, and benzene, D-limonene, formaldehyde, and ethyl methacrylate in some salons. While MMA was not measured in the consumer and professional products, and the use of pure MMA in salons has been not been permitted since the 1970s, MMA was found in air at concentrations from 100 to 36,000 µg/m 3 in 15 of 17 salons; thus its use appears to be commonplace in the industry. Personal measurements, representing exposures to workers and clients, were about twice those of the area measurements for many VOCs., Conclusion: This study identifies the products responsible for emissions, shows the widespread presence of MMA, and documents low ventilation rates in some salons. It also demonstrates that "informal" short-term sampling approaches can evaluate chemical exposures in nail salons, providing measurements that can be used to protect a potentially susceptible and vulnerable population. Additional controls, including restrictions on the VOC compositions and improved ventilation, can reduce exposures to salon workers and clients.

Nitrogen dioxide (NO 2 ) not only is linked to adverse effects on the respiratory system but also contributes to the formation of ground-level ozone (O 3 ) and fine particulate matter (PM 2.5 ). Our curbside monitoring data analysis in Detroit, MI, and Atlanta, GA, strongly suggests that a large fraction of NO 2 is produced during the "tailpipe-to-road" stage. To substantiate this finding, we designed and carried out a field campaign to measure the same exhaust plumes at the tailpipe-level by a portable emissions measurement system (PEMS) and at the on-road level by an electric vehicle-based mobile platform. Furthermore, we employed a turbulent reacting flow model, CTAG, to simulate the on-road chemistry behind a single vehicle. We found that a three-reaction (NO-NO 2 -O 3 ) system can largely capture the rapid NO to NO 2 conversion (with time scale ≈ seconds) observed in the field studies. To distinguish the contributions from different mechanisms to near-road NO 2 , we clearly defined a set of NO 2 /NO x ratios at different plume evolution stages, namely tailpipe, on-road, curbside, near-road, and ambient background. Our findings from curbside monitoring, on-road experiments, and simulations imply the on-road oxidation of NO by ambient O 3 is a significant, but so far ignored, contributor to curbside and near-road NO 2 .

Ambient air pollution has been associated with adverse respiratory outcomes, especially among children with asthma. This study reports on associations between daily ambient air pollutant concentrations and the respiratory symptoms of schoolchildren living in Durban, South Africa. This city is Africa's busiest port and a key hub for imported crude oil and exported refined petroleum and petrochemical products, and it experiences a mixture of air pollutants that reflects emissions from industry, traffic and biomass burning. Children in four communities in the highly industrialized southern portion of the city were compared to children of similar socio-economic profiles living in the north of the city. One school was selected in each community. A total of 423 children were recruited. Symptom logs were completed every 1.5-2 h over 3-week period in each of four seasons. Ambient concentrations of NO 2 , NO, SO 2 , CO, O 3, PM 2.5 and PM 10 were measured throughout the study. Generalized estimating equation (GEE) models were used to estimate odds ratios (ORs) and assess lag effects (1-5 days) using single pollutant (single lags or distributed lags) models. Concentrations of SO 2 and NO x were markedly higher in the south, while PM 10 did not vary. Significant increase in the odds ratios of cough were identified for the various lags analyzed. The OR of symptoms was further increased among those living in the south compared to the north. In conclusion, in this analysis of over 70,000 observations, we provide further evidence that exposure to PM 10 , SO 2 , NO 2 and NO is associated with significantly increased occurrence of respiratory symptoms among children. This was evident for cough, shortness of breath, and chest tightness, across the four pollutants and for different lags of exposure. This is the first study describing these changes in sub-Saharan Africa., (Copyright © 2017 Elsevier Ltd. All rights reserved.)

Air pollution episodes in China are frequent and a more comprehensive understanding of pollution sources and impacts is needed to design appropriate strategies and set emission reduction targets. This study analyzes PM 2.5 and PM 10 concentrations measured in 23 cities at 178 urban sites and at 23 corresponding "urban contrast" sites in China with the goals of understanding spatial and temporal trends and quantifying the regional component of PM pollution. The contrast sites, located an average of 29km from cities in the upwind direction, are intended to represent "background" levels. Using daily measurements from April 2013 to March 2014, we assess compliance with air quality standards, PM 2.5 /PM 10 ratios and urban "increments," defined as the increase in PM levels in the city compared to the contrast site. Spatial and temporal patterns at daily, monthly and annual levels are shown using distributions, correlations, spatial autocorrelation, and factor analyses. At the contrast sites, PM 2.5 and PM 10 concentrations averaged 56±26 and 91±44μgm -3 , respectively, and China's daily and annual average air quality standards were frequently exceeded. PM 2.5 and PM 10 concentrations in most cities exceeded levels at the corresponding contrast sites, but by an average of only 14±14 and 26±27μgm -3 , respectively. Seasonal changes in PM 2.5 and PM 10 concentrations and urban increments were striking, e.g., levels increased 2 to 3-fold in winter at several sites. The significance of exurban and regional sources of PM 2.5 is demonstrated by the small urban increments, the strong correlations across broad regions, and the correlation between daily levels at city and contrast sites. These sources will require control to achieve air quality goals, in particular, the PM 10 and PM 2.5 targets announced by the Chinese government in 2013., (Copyright © 2017 Elsevier B.V. All rights reserved.)

Only limited research has examined the development and application of visible light responsive photocatalytic oxidation (PCO), although such materials have great potential for mitigating concentrations of volatile organic compounds (VOCs) when applied to building surfaces. This study evaluates the performance and characteristics of a visible light responsive photocatalyst, specially, a co-alloyed TiNbON compound with a band energy of 2.3 eV. The PCO material was developed using urea-glass synthesis, characterized by scanning electron microscopy (SEM), diffuse reflectance spectra (DRS), powder X-ray diffraction (PXRD), and Brunauer-Emmett-Teller (BET) methods, and VOC removal efficiency was measured under visible light for toluene (1-5 ppm) at room temperature (21.5°C) and a range of relative humidity (RH: 25 to 65%), flow rate (0.78 to 7.84 cm/s), and irradiance (42 to 95 W/m 2 ). A systematic parametric evaluation of kinetic parameters was conducted. In addition, we compared TiNbON with a commercial TiO 2 -based material under black light, estimated TiNbON's long-term durability and stability, and tested its ability to thermally regenerate. Using mass transfer and kinetic analysis, three different Langmuir-Hinshelwood (LH) type reaction rate expressions were proposed and evaluated. A LH model considering one active site and competitive sorption of toluene and water was superior to others. The visible-light driven catalyst was able to remove up to 58 % of the toluene, generated less formaldehyde than the commercial TiO 2 , could be fully regenerated at 150°C, and had reasonable durability and stability. This evaluation of TiNbON shows the potential to remove VOCs and improve air quality for indoor applications. Further research is needed to evaluate the potential for harmful by-products, to identify optimal conditions, and to use field tests to show real-world performance.

Low ventilation rates (VRs) in schools have been associated with absenteeism, poorer academic performance, and teacher dissatisfaction. We measured VRs in 37 recently constructed or renovated and mechanically ventilated U.S. schools, including LEED and EnergyStar-certified buildings, using CO 2 and the steady-state, build-up, decay, and transient mass balance methods. The transient mass balance method better matched conditions (specifically, changes in occupancy) and minimized biases seen in the other methods. During the school day, air change rates (ACRs) averaged 2.0±1.3 hour -1 , and only 22% of classrooms met recommended minimum ventilation rates. HVAC systems were shut off at the school day close, and ACRs dropped to 0.21±0.19 hour -1 . VRs did not differ by building type, although cost-cutting and comfort measures resulted in low VRs and potentially impaired IAQ. VRs were lower in schools that used unit ventilators or radiant heating, in smaller schools and in larger classrooms. The steady-state, build-up, and decay methods had significant limitations and biases, showing the need to confirm that these methods are appropriate. Findings highlight the need to increase VRs and to ensure that energy saving and comfort measures do not compromise ventilation and IAQ., (© 2017 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.)

Objective: To determine if there was a significant difference between mold contamination and asthma prevalence in Detroit and non-Detroit Michigan homes, between newer and older homes, and if there is a correlation between mold contamination and measures of Medicaid use for asthma in the 25 Detroit zip codes., Methods: Settled dust was collected from homes (n = 113) of Detroit asthmatic children and from a representative group of Michigan homes (n = 43). The mold contamination for each home was measured using the Environmental Relative Moldiness Index (ERMI) scale and the mean ERMI values in Detroit and non-Detroit homes were statistically compared. Michigan Medicaid data (13 measures related to asthma) in each of the 25 zip codes in Detroit were tested for correlation to ERMI values for homes in those zip codes., Results: The mean ERMI value (14.5 ± 8.0) for Detroit asthmatic childrens' homes was significantly (Student's t-test, p < 0.001) greater than the mean ERMI value (2.1 ± 6.2) for the non-Detroit homes. Detroit homes > 60 years old had significantly (p = 0.01) greater mean ERMI values than Detroit homes ≤ 60 years old (15.87 vs. 11.25). The percentage of children that underwent spirometry testing for their persistent asthma (based on Medicaid data) was significantly, positively correlated with the mean ERMI values of the homes in the 25 zip codes., Conclusions: Applying Medicaid-use data for spirometry testing and locating a city's older housing stock might help find foci of homes with high ERMI values.

The objective of this study was to determine if the association between exposure to ambient air pollutants such as sulfur dioxide, nitrogen dioxde (NO 2 ), nitrous oxide (NO), and PM 10 , and variation in lung function measures was modified by genotype. A validated questionnaire was administered to 71 African children to evaluate prevalence of respiratory symptoms. Atopy was evaluated by skin-prick testing and bihourly measures of lung function (spirometry) were collected. Gaseous air pollutant concentrations were monitored continuously. CD14 polymorphism was genotyped and plasma CD14 levels were measured. There was no statistically significant association between the CD14 (159) CT+TT polymorphism with any asthma-related phenotype. There was a significant association between lung function (forced expiratory volume in 1 second intraday variability) and NO 2 and NO among participants carrying the CD14 CT/TT genotype for lags 1, 2, and the 5-day average. Similarly, statistically significant gene-pollutant interactions ( p < 0.05) were found with NO and CD14 CT/TT at lag 2 and for the 5-day average. While there was no association with any respiratory phenotype (as determined by symptoms), the CD14 CT/TT genotype appeared to be protective to increased exposure to NO 2 and NO.

The ventilation rate (VR) is a key parameter affecting indoor environmental quality (IEQ) and the energy consumption of buildings. This paper reviews the use of CO₂ as a "natural" tracer gas for estimating VRs, focusing on applications in school classrooms. It provides details and guidance for the steady-state, build-up, decay and transient mass balance methods. An extension to the build-up method and an analysis of the post-exercise recovery period that can increase CO₂ generation rates are presented. Measurements in four mechanically-ventilated school buildings demonstrate the methods and highlight issues affecting their applicability. VRs during the school day fell below recommended minimum levels, and VRs during evening and early morning were on the order of 0.1 h -1 , reflecting shutdown of the ventilation systems. The transient mass balance method was the most flexible and advantageous method given the low air change rates and dynamic occupancy patterns observed in the classrooms. While the extension to the build-up method improved stability and consistency, the accuracy of this and the steady-state method may be limited. Decay-based methods did not reflect the VR during the school day due to heating, ventilation and air conditioning (HVAC) system shutdown. Since the number of occupants in classrooms changes over the day, the VR expressed on a per person basis (e.g., L·s -1 ·person -1 ) depends on the occupancy metric. If occupancy measurements can be obtained, then the transient mass balance method likely will provide the most consistent and accurate results among the CO₂-based methods. Improved VR measurements can benefit many applications, including research examining the linkage between ventilation and health.

Exposure to volatile organic compounds (VOCs) has been an indoor environmental quality (IEQ) concern in schools and other buildings for many years. Newer designs, construction practices and building materials for "green" buildings and the use of "environmentally friendly" products have the promise of lowering chemical exposure. This study examines VOCs and IEQ parameters in 144 classrooms in 37 conventional and high performance elementary schools in the U.S. with the objectives of providing a comprehensive analysis and updating the literature. Tested schools were built or renovated in the past 15 years, and included comparable numbers of conventional, Energy Star, and Leadership in Energy and Environmental Design (LEED)-certified buildings. Indoor and outdoor VOC samples were collected and analyzed by thermal desorption, gas chromatography and mass spectroscopy for 94 compounds. Aromatics, alkanes and terpenes were the major compound groups detected. Most VOCs had mean concentrations below 5 µg/m³, and most indoor/outdoor concentration ratios ranged from one to 10. For 16 VOCs, the within-school variance of concentrations exceeded that between schools and, overall, no major differences in VOC concentrations were found between conventional and high performance buildings. While VOC concentrations have declined from levels measured in earlier decades, opportunities remain to improve indoor air quality (IAQ) by limiting emissions from building-related sources and by increasing ventilation rates., Competing Interests: The authors declare no conflict of interest.

High concentrations of particulate matter (PM 2.5 ) and frequent air pollution episodes in Beijing have attracted widespread attention. This paper utilizes data from the new air pollution network in China to examine the current spatial and temporal variability of PM 2.5 at 12 monitoring sites in Beijing over a recent 2-year period (April 2013) to March 2015). The long term (2-year) average concentration was 83 µg·m -3 , well above Chinese and international standards. Across the region, annual average concentrations varied by 20 µg·m -3 (25% of the average level), with lower levels in suburban areas compared to periurban and urban areas, which had similar concentrations. The spatial variation in PM 2.5 concentrations was associated with several land use and economic variables, including the fraction of vegetated land and building construction activity, which together explained 71% of the spatial variation. Daily air quality was characterized as "polluted" (above 75 µg·m -3 ) on 36 to 47% of days, depending on site. There were 77 pollution episodes during the study period (defined as two or more consecutive days with Beijing-wide 24-hour average concentrations over 75 µg·m -3 ), and 2 to 5 episodes occurred each month, including summer months. The longest episode lasted 9 days and daily concentrations exceeded 450 µg·m -3 . Daily PM 2.5 levels were autocorrelated (r lag1 = 0.516) and associated with many meteorological variables, including barometric pressure, relative humidity, hours of sunshine, surface and ambient temperature, precipitation and scavenging coefficient, and wind direction. Parsimonious models with meteorological and autoregressive terms explained over 60% of the variation in daily PM 2.5 levels. The first autoregressive term and hours of sunshine were the most important variables in these models, however, the latter variable is PM 2.5 -dependent and thus not an explanatory variable. The present study can serve as a baseline to compare the improved air quality in Beijing expected in future years.

Background: The study of gene-environment interactions enables us to further understand the pathogenesis of asthma and inflammation. The TNF-α gene has been associated with airway pathology in asthma but there is limited information in relation to pollutant exposure and the TNF-α 308G/A polymorphism., Objective: To determine the risk conferred by the TNF-α 308(G/A) polymorphism on respiratory outcome and to evaluate whether the association between exposure to ambient air pollutants such as SO2, NO2, NO, and PM10 and variation in lung function measures is modified by genotype., Methods: The sample comprised 129 African children (between 9-11 years old). A questionnaire based on guidelines from the British Medical Research Council and the American Thoracic Society was administered to all caregivers to evaluate the prevalence of respiratory symptoms. Atopy was evaluated by skin prick testing. Bihourly measures of lung function (spirometry) were collected at school five days per week over three week periods in each of four seasons (2004-2005) using digital hand-held devices. During each of the four intensive 3-week phases, gaseous air pollutant concentrations were monitored continuously. Polymerase Chain Reaction-Restriction Fragment Length Polymorphism (PCR-PFLP) analysis was used to detect the TNF-α 308 genotype and plasma TNF-α levels were measured using the human TNF-α Max Standard™ Enzyme-linked immuno-absorbent assay (ELISA) kit., Results: The TNF-α variant A allele was common among this sample of African children (40% with an allelic frequency of 0.24). There was no significant association with the TNF-α G/A polymorphism and any respiratory linked phenotype, nor cytokine levels. However, when exposure to pollutants were analyzed with genotypic and phenotypic data, we found relatively modest interaction effects for the TNF-α 308 genotype. GEE models showed that children with the TNF-α 308 A allele had increased deterioration of lung function post pollution exposure to SO2 [β=2.62, CI:0.51-4.71, p=0.02 and pint=0.03] and NO [β=3.28, CI:0.68-5.89, p=0.01, pint=0.03]., Conclusion: The TNF-α 308 (G/A) polymorphism may be associated with increased pollutant-associated effects on FEV1 intraday variability for both SO2 and NO. The A allele may increase susceptibility to the adverse effects of air pollutants.

The in utero environment has the potential to influence epigenetic programming and subsequently the health of offspring. Even though pregnant women living in urban Africa are exposed to multiple chemicals and infectious agents that may impact their developing children, the neonatal epigenome has not been studied in these regions. We assessed whether prenatal exposures to air pollution and maternal human immunodeficiency virus (HIV) are associated with changes to DNA methylation throughout the epigenome using a pilot sample from the Mother and Child Environmental (MACE) birth cohort, of which 36% of the mothers are HIV positive. Families living in a high air pollution region (south Durban, n = 11) and a low air pollution region (north Durban, n = 11) with comparable socioeconomic characteristics were selected for analysis. DNA methylation was quantified in cord blood plasma DNA at >430 000 CpG sites using the Infinium HumanMethylation450 BeadChip. Sites associated with living in south Durban or maternal HIV infection (p < 0.001) were more likely to be hypomethylated and located in CpG islands. Top differentially methylated sites by region of Durban were enriched in pathways related to xenobiotic metabolism, oxygen and gas transport, and sensory perception of chemical stimuli when performing gene set enrichment testing with LRpath. Differentially methylated sites by maternal HIV status were enriched in cytochrome P450s, pathways involved in detection of chemical stimuli, metabolic processes, and viral regulation and processing. Given the small sample size of the study, future work examining the impact of prenatal exposures to air pollution, maternal infection, and antiviral treatment on the epigenome and downstream health implications is merited in Sub-Saharan African populations.

Importance: Persistent environmental pollutants may represent a modifiable risk factor involved in the gene-time-environment hypothesis in amyotrophic lateral sclerosis (ALS)., Objective: To evaluate the association of occupational exposures and environmental toxins on the odds of developing ALS in Michigan., Design, Setting, and Participants: Case-control study conducted between 2011 and 2014 at a tertiary referral center for ALS. Cases were patients diagnosed as having definitive, probable, probable with laboratory support, or possible ALS by revised El Escorial criteria; controls were excluded if they were diagnosed as having ALS or another neurodegenerative condition or if they had a family history of ALS in a first- or second-degree blood relative. Participants completed a survey assessing occupational and residential exposures. Blood concentrations of 122 persistent environmental pollutants, including organochlorine pesticides (OCPs), polychlorinated biphenyls (PCBs), and brominated flame retardants (BFRs), were measured using gas chromatography-mass spectrometry. Multivariable models with self-reported occupational exposures in various exposure time windows and environmental toxin blood concentrations were separately fit by logistic regression models. Concordance between the survey data and pollutant measurements was assessed using the nonparametric Kendall τ correlation coefficient., Main Outcomes and Measures: Occupational and residential exposures to environmental toxins, and blood concentrations of 122 persistent environmental pollutants, including OCPs, PCBs, and BFRs., Results: Participants included 156 cases (mean [SD] age, 60.5 [11.1] years; 61.5% male) and 128 controls (mean [SD] age, 60.4 [9.4] years; 57.8% male); among them, 101 cases and 110 controls had complete demographic and pollutant data. Survey data revealed that reported pesticide exposure in the cumulative exposure windows was significantly associated with ALS (odds ratio [OR] = 5.09; 95% CI, 1.85-13.99; P = .002). Military service was also associated with ALS in 2 time windows (exposure ever happened in entire occupational history: OR = 2.31; 95% CI, 1.02-5.25; P = .046; exposure ever happened 10-30 years ago: OR = 2.18; 95% CI, 1.01-4.73; P = .049). A multivariable model of measured persistent environmental pollutants in the blood, representing cumulative occupational and residential exposure, showed increased odds of ALS for 2 OCPs (pentachlorobenzene: OR = 2.21; 95% CI, 1.06-4.60; P = .04; and cis-chlordane: OR = 5.74; 95% CI, 1.80-18.20; P = .005), 2 PCBs (PCB 175: OR = 1.81; 95% CI, 1.20-2.72; P = .005; and PCB 202: OR = 2.11; 95% CI, 1.36-3.27; P = .001), and 1 BFR (polybrominated diphenyl ether 47: OR = 2.69; 95% CI, 1.49-4.85; P = .001). There was modest concordance between survey data and the measurements of persistent environmental pollutants in blood; significant Kendall τ correlation coefficients ranged from -0.18 (Dacthal and "use pesticides to treat home or yard") to 0.24 (trans-nonachlor and "store lawn care products in garage")., Conclusions and Relevance: In this study, persistent environmental pollutants measured in blood were significantly associated with ALS and may represent modifiable ALS disease risk factors.

PM 2.5 concentrations throughout much of the U.S. have decreased over the last 15 years, but emissions and concentration trends can vary by location and source type. Such trends should be understood to inform air quality management and policies. This work examines trends in emissions, concentrations and source apportionments in two large Midwest U.S. cities, Detroit, Michigan, and Chicago, Illinois. Annual and seasonal trends were investigated using National Emission Inventory (NEI) data for 2002 to 2011, speciated ambient PM 2.5 data from 2001 to 2014, apportionments from positive matrix factorization (PMF) receptor modeling, and quantile regression. Over the study period, county-wide data suggest emissions from point sources decreased (Detroit) or held constant (Chicago), while emissions from on-road mobile sources were constant (Detroit) or increased (Chicago), however changes in methodology limit the interpretation of inventory trends. Ambient concentration data also suggest source and apportionment trends, e.g., annual median concentrations of PM 2.5 in the two cities declined by 3.2 to 3.6 %/yr (faster than national trends), and sulfate concentrations (due to coal-fired facilities and other point source emissions) declined even faster; in contrast, organic and elemental carbon (tracers of gasoline and diesel vehicle exhaust) declined more slowly or held constant. The PMF models identified nine sources in Detroit and eight in Chicago, the most important being secondary sulfate, secondary nitrate and vehicle emissions. A minor crustal dust source, metals sources, and a biomass source also were present in both cities. These apportionments showed that the median relative contributions from secondary sulfate sources decreased by 4.2 to 5.5% per year in Detroit and Chicago, while contributions from metals sources, biomass sources, and vehicles increased from 1.3 to 9.2% per year. This first application of quantile regression to trend analyses of speciated PM 2.5 data reveals that source contributions to PM 2.5 varied as PM 2.5 concentrations decreased, and that the fraction of PM 2.5 due to emissions from vehicles and other local emissions has increased. Each data source has uncertainties, but emissions, monitoring and PMF data provide complementary information that can help to discern trends and identify contributing sources. Study results emphasize the need to target specific sources in policies and regulations aimed at decreasing PM 2.5 concentrations in urban areas.

Unlabelled: Basements can influence indoor air quality by affecting air exchange rates (AERs) and by the presence of emission sources of volatile organic compounds (VOCs) and other pollutants. We characterized VOC levels, AERs, and interzonal flows between basements and occupied spaces in 74 residences in Detroit, Michigan. Flows were measured using a steady-state multitracer system, and 7-day VOC measurements were collected using passive samplers in both living areas and basements. A walk-through survey/inspection was conducted in each residence. AERs in residences and basements averaged 0.51 and 1.52/h, respectively, and had strong and opposite seasonal trends, for example, AERs were highest in residences during the summer, and highest in basements during the winter. Airflows from basements to occupied spaces also varied seasonally. VOC concentration distributions were right-skewed, for example, 90th percentile benzene, toluene, naphthalene, and limonene concentrations were 4.0, 19.1, 20.3, and 51.0 μg/m(3), respectively; maximum concentrations were 54, 888, 1117, and 134 μg/m(3). Identified VOC sources in basements included solvents, household cleaners, air fresheners, smoking, and gasoline-powered equipment. The number and type of potential VOC sources found in basements are significant and problematic, and may warrant advisories regarding the storage and use of potentially strong VOCs sources in basements., Practical Implications: Few IAQ studies have examined basements. A sizable volume of air can flow between the basement and living area, and AERs in these two zones can differ considerably. In many residences, the basement contains significant emission sources and contributes a large fraction of VOC concentrations found in the living area. Exposures can be lowered by removing VOC sources from the basement; other exposure management options, such as local ventilation or isolation, are unlikely to be practical., (© 2014 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.)

Patterns of traffic activity, including changes in the volume and speed of vehicles, vary over time and across urban areas and can substantially affect vehicle emissions of air pollutants. Time-resolved activity at the street scale typically is derived using temporal allocation factors (TAFs) that allow the development of emissions inventories needed to predict concentrations of traffic-related air pollutants. This study examines the spatial and temporal variation of TAFs, and characterizes prediction errors resulting from their use. Methods are presented to estimate TAFs and their spatial and temporal variability and used to analyze total, commercial and non-commercial traffic in the Detroit, Michigan, U.S. metropolitan area. The variability of total volume estimates, quantified by the coefficient of variation (COV) representing the percentage departure from expected hourly volume, was 21, 33, 24 and 33% for weekdays, Saturdays, Sundays and holidays, respectively. Prediction errors mostly resulted from hour-to-hour variability on weekdays and Saturdays, and from day-to-day variability on Sundays and holidays. Spatial variability was limited across the study roads, most of which were large freeways. Commercial traffic had different temporal patterns and greater variability than noncommercial vehicle traffic, e.g., the weekday variability of hourly commercial volume was 28%. The results indicate that TAFs for a metropolitan region can provide reasonably accurate estimates of hourly vehicle volume on major roads. While vehicle volume is only one of many factors that govern on-road emission rates, air quality analyses would be strengthened by incorporating information regarding the uncertainty and variability of traffic activity.

Exposure to traffic-related air pollutants is highest very near roads, and thus exposure estimates are sensitive to positional errors. This study evaluates positional and PM2.5 concentration errors that result from the use of automated geocoding methods and from linearized approximations of roads in link-based emission inventories. Two automated geocoders (Bing Map and ArcGIS) along with handheld GPS instruments were used to geocode 160 home locations of children enrolled in an air pollution study investigating effects of traffic-related pollutants in Detroit, Michigan. The average and maximum positional errors using the automated geocoders were 35 and 196 m, respectively. Comparing road edge and road centerline, differences in house-to-highway distances averaged 23 m and reached 82 m. These differences were attributable to road curvature, road width and the presence of ramps, factors that should be considered in proximity measures used either directly as an exposure metric or as inputs to dispersion or other models. Effects of positional errors for the 160 homes on PM2.5 concentrations resulting from traffic-related emissions were predicted using a detailed road network and the RLINE dispersion model. Concentration errors averaged only 9%, but maximum errors reached 54% for annual averages and 87% for maximum 24-h averages. Whereas most geocoding errors appear modest in magnitude, 5% to 20% of residences are expected to have positional errors exceeding 100 m. Such errors can substantially alter exposure estimates near roads because of the dramatic spatial gradients of traffic-related pollutant concentrations. To ensure the accuracy of exposure estimates for traffic-related air pollutants, especially near roads, confirmation of geocoordinates is recommended.

Traffic activity encompasses the number, mix, speed and acceleration of vehicles on roadways. The temporal pattern and variation of traffic activity reflects vehicle use, congestion and safety issues, and it represents a major influence on emissions and concentrations of traffic-related air pollutants. Accurate characterization of vehicle flows is critical in analyzing and modeling urban and local-scale pollutants, especially in near-road environments and traffic corridors. This study describes methods to improve the characterization of temporal variation of traffic activity. Annual, monthly, daily and hourly temporal allocation factors (TAFs), which describe the expected temporal variation in traffic activity, were developed using four years of hourly traffic activity data recorded at 14 continuous counting stations across the Detroit, Michigan, U.S. region. Five sites also provided vehicle classification. TAF-based models provide a simple means to apportion annual average estimates of traffic volume to hourly estimates. The analysis shows the need to separate TAFs for total and commercial vehicles, and weekdays, Saturdays, Sundays and observed holidays. Using either site-specific or urban-wide TAFs, nearly all of the variation in historical traffic activity at the street scale could be explained; unexplained variation was attributed to adverse weather, traffic accidents and construction. The methods and results presented in this paper can improve air quality dispersion modeling of mobile sources, and can be used to evaluate and model temporal variation in ambient air quality monitoring data and exposure estimates.

We propose a new approach for measuring ventilation air exchange rates (AERs). The method belongs to the class of tracer gas techniques, but is formulated in the light of systems theory and signal processing. Unlike conventional CO 2 based methods that assume the outdoor ambient CO 2 concentration is constant, the proposed method recognizes that photosynthesis and respiration cycle of plants and processes associated with fuel combustion produce daily, quasi-periodic, variations in the ambient CO 2 concentrations. These daily variations, which are within the detection range of existing monitoring equipment, are utilized for estimating ventilation rates without the need of a source of CO 2 in the building. Using a naturally-ventilated residential apartment, AERs obtained using the new method compared favorably (within 10%) to those obtained using the conventional CO 2 decay fitting technique. The new method has the advantages that no tracer gas injection is needed, and high time resolution results are obtained.

Vehicle traffic is one of the most significant emission sources of air pollutants in urban areas. While the influence of mobile source emissions is felt throughout an urban area, concentrations from mobile emissions can be highest near major roadways. At present, information regarding the spatial and temporal patterns and the share of pollution attributable to traffic-related air pollutants is limited, in part due to concentrations that fall sharply with distance from roadways, as well as the few monitoring sites available in cities. This study uses a newly developed dispersion model (RLINE) and a spatially and temporally resolved emissions inventory to predict hourly PM2.5 and NOx concentrations across Detroit (MI, USA) at very high spatial resolution. Results for annual averages and high pollution days show contrasting patterns, the need for spatially resolved analyses, and the limitations of surrogate metrics like proximity or distance to roads. Data requirements, computational and modeling issues are discussed. High resolution pollutant data enable the identification of pollutant "hotspots", "project-level" analyses of transportation options, development of exposure measures for epidemiology studies, delineation of vulnerable and susceptible populations, policy analyses examining risks and benefits of mitigation options, and the development of sustainability indicators integrating environmental, social, economic and health information.

Polybrominated diphenyl ethers (PBDEs) are persistent and toxic flame-retardant chemicals widespread in the Great Lakes ecosystem. These chemicals are now being regulated and phased-out of the region; therefore it remains important to understand the extent of contamination in order to track the efficacy of recent actions. Here, Σ 4 PBDE congeners (PBDE-47, 99, 100, 153;wetweight basis unless indicated)were determined in liver tissues from Wisconsin river otters ( Lontra canadensis ; n = 35; 2009-2010) and Michigan bald eagles ( Haliaeetus leucocephalus ; n = 33; 2009-2011). In otters, Σ 4 PBDE ranged from0.5 to 72.9 ng/g, with a mean (±SD) and median (25th-75th percentile inter-quartile range) of 16.3 ± 16.4 ng/g and 11.3 (5.6-18.9) ng/g, respectively. The mean lipid-adjusted Σ 4 PBDE was 1377 ± 1485 ng/g. In eagles, Σ 4 PBDE ranged from 0 to 1,538.8 ng/g, with a mean and median of 74.3 ± 266.7 ng/g and 21.2 (5.7-28.9) ng/g, respectively. The mean lipid-adjusted Σ 4 PBDE was 5274.5 ± 19,896.1 ng/g. In both species, PBDE-47 accounted for >50% of the Σ 4 PBDE, followed by PBDE-99 and PBDE-100 (each ~17-19% of the total). The PBDE levels reported here in otters are similar to mammalian wildlife elsewhere, though the levels in eagles are among the highest worldwide across studied birds. The findings indicate that apex Great Lakes wildlife remain exposed to appreciable levels of PBDEs and more work is needed to understand whether such exposures are associated with adverse health outcomes.

Dried blood spots (DBSs) can provide accurate and valuable estimates of exposure to environmental toxicants, and the use of information derived from archived newborn DBSs has enormous potential to open up new research on the impacts of early chemical exposure on disease. Broad application of DBS for the purpose of quantitative exposure estimation requires robust and validated methods. This study investigates the suitability of DBS analyses for population studies of exposure to three chemical groups: polychlorinated biphenyls (PCBs), brominated flame retardants (BFRs), and chlorinated pesticides. It examines background (matrix) contamination, recovery and extraction variability, sensitivity, and storage stability. DBS samples prepared using 50 μL of adult blood were analyzed by GC/MS, and method performance was confirmed by using certified materials and paired DBS-blood samples from six volunteers. Several of the target compounds and their degradation products have not been previously measured in DBSs. All target compounds were detected in DBS samples collected from the volunteers. Sample DBS cards showed background contamination of several compounds. When stored at room temperature, target compounds, excluding PBDEs, were stable for up to one month. When refrigerated or frozen, stability was acceptable for all compounds up to one year, and multiyear storage appears acceptable at colder (e.g., -80°C) temperatures. Multicompartment models may be used to estimate or correct for storage losses. Considering concentrations of contaminants for adults and children reported in the literature, and experimental values of detection limits and background contamination, DBS samples are suitable for quantifying exposures to many PCBs, BFRs and persistent pesticides., (Copyright © 2014 Elsevier B.V. All rights reserved.)

Vehicles are major sources of air pollutant emissions, and individuals living near large roads endure high exposures and health risks associated with traffic-related air pollutants. Air pollution epidemiology, health risk, environmental justice, and transportation planning studies would all benefit from an improved understanding of the key information and metrics needed to assess exposures, as well as the strengths and limitations of alternate exposure metrics. This study develops and evaluates several metrics for characterizing exposure to traffic-related air pollutants for the 218 residential locations of participants in the NEXUS epidemiology study conducted in Detroit (MI, USA). Exposure metrics included proximity to major roads, traffic volume, vehicle mix, traffic density, vehicle exhaust emissions density, and pollutant concentrations predicted by dispersion models. Results presented for each metric include comparisons of exposure distributions, spatial variability, intraclass correlation, concordance and discordance rates, and overall strengths and limitations. While showing some agreement, the simple categorical and proximity classifications (e.g., high diesel/low diesel traffic roads and distance from major roads) do not reflect the range and overlap of exposures seen in the other metrics. Information provided by the traffic density metric, defined as the number of kilometers traveled (VKT) per day within a 300 m buffer around each home, was reasonably consistent with the more sophisticated metrics. Dispersion modeling provided spatially- and temporally-resolved concentrations, along with apportionments that separated concentrations due to traffic emissions and other sources. While several of the exposure metrics showed broad agreement, including traffic density, emissions density and modeled concentrations, these alternatives still produced exposure classifications that differed for a substantial fraction of study participants, e.g., from 20% to 50% of homes, depending on the metric, would be incorrectly classified into "low", "medium" or "high" traffic exposure classes. These and other results suggest the potential for exposure misclassification and the need for refined and validated exposure metrics. While data and computational demands for dispersion modeling of traffic emissions are non-trivial concerns, once established, dispersion modeling systems can provide exposure information for both on- and near-road environments that would benefit future traffic-related assessments.

Vehicle emissions represent one of the most important air pollution sources in most urban areas, and elevated concentrations of pollutants found near major roads have been associated with many adverse health impacts. To understand these impacts, exposure estimates should reflect the spatial and temporal patterns observed for traffic-related air pollutants. This paper evaluates the spatial resolution and zonal systems required to estimate accurately intraurban and near-road exposures of traffic-related air pollutants. The analyses use the detailed information assembled for a large (800 km 2 ) area centered on Detroit, Michigan, USA. Concentrations of nitrogen oxides (NO x ) due to vehicle emissions were estimated using hourly traffic volumes and speeds on 9,700 links representing all but minor roads in the city, the MOVES2010 emission model, the RLINE dispersion model, local meteorological data, a temporal resolution of 1 hr, and spatial resolution as low as 10 m. Model estimates were joined with the corresponding shape files to estimate residential exposures for 700,000 individuals at property parcel, census block, census tract, and ZIP code levels. We evaluate joining methods, the spatial resolution needed to meet specific error criteria, and the extent of exposure misclassification. To portray traffic-related air pollutant exposure, raster or inverse distance-weighted interpolations are superior to nearest neighbor approaches, and interpolations between receptors and points of interest should not exceed about 40 m near major roads, and 100 m at larger distances. For census tracts and ZIP codes, average exposures are overestimated since few individuals live very near major roads, the range of concentrations is compressed, most exposures are misclassified, and high concentrations near roads are entirely omitted. While smaller zones improve performance considerably, even block-level data can misclassify many individuals. To estimate exposures and impacts of traffic-related pollutants accurately, data should be geocoded or estimated at the most-resolved spatial level; census tract and larger zones have little if any ability to represent intraurban variation in traffic-related air pollutant concentrations. These results are based on one of the most comprehensive intraurban modeling studies in the literature and results are robust. Recommendations address the value of dispersion models to portray spatial and temporal variation of air pollutants in epidemiology and other studies; techniques to improve accuracy and reduce the computational burden in urban scale modeling; the necessary spatial resolution for health surveillance, demographic, and pollution data; and the consequences of low resolution data in terms of exposure misclassification.