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ObjectivesTo investigate relationships between race and COVID-19 hospitalizations, intensive care unit (ICU) admissions, and mortality over time and which characteristics, may mediate COVID-19 associations.MethodsWe analyzed hospital admissions, ICU admissions, and mortality among positive COVID-19 cases within the ten-hospital Franciscan Ministries of Our Lady Health System around the Mississippi River Industrial Corridor in Louisiana over four waves of the pandemic from March 1, 2020 – August 31, 2021. Associations between race and each outcome were tested, and multiple mediation analysis was performed to test if other demographic, socioeconomic, or air pollution variables mediate the race-outcome relationships.ResultsRace was associated with each outcome over the study duration and during most waves. Early in the pandemic, hospitalization, ICU admission, and mortality rates were greater among Black patients, but as the pandemic progressed these rates became greater in White patients. However, Black patients were still disproportionately represented in these measures. Age was a significant mediator for all outcomes across waves, while comorbidity and emissions of naphthalene and chloroprene acted as mediators for the full study period.ConclusionsThe role of race evolved throughout the pandemic in Louisiana, but Black patients bore a disproportionate impact. Naphthalene and chloroprene air pollution partially explained the long-term associations. Our findings imply that air pollution might contribute to the increased COVID-19 hospitalizations and mortality among Black residents in Louisiana but likely do not explain most of the effect of race.What is already known on this topicEarly in the pandemic, there was evidence of disparities in COVID-19 cases, hospitalizations, intensive care unit (ICU) admissions, and mortality due to race. Studies were emerging to indicate that strength of these relationships was waning over time.What this study addsThis study tests relationships between race and hospitalizations, ICU admissions, and mortality and finds that Black patients continue to be disproportionately represented, although that inequity diminished over time. This study, the first to use multiple mediation analysis to study COVID-19 associations, suggests that the relationship between race and health outcome can be explained by mediators including age and, to a lesser extent, comorbidity and air pollution.How this study might affect research, practice or policyThis study supports the need for healthcare resources to be available to Louisiana’s communities of color, for policy to support increased access to health care in the Industrial Corridor region, and for policy to support the reduction of air pollution emissions to disproportionately impacting the health of the Industrial Corridor’s communities of color.

Background People with certain underlying respiratory and cardiovascular conditions might be at an increased risk for severe illness from COVID-19. Diesel Particulate Matter (DPM) exposure may affect the pulmonary and cardiovascular systems. The study aims to assess if DPM was spatially associated with COVID-19 mortality rates across three waves of the disease and throughout 2020. Methods We tested an ordinary least squares (OLS) model, then two global models, a spatial lag model (SLM) and a spatial error model (SEM) designed to explore spatial dependence, and a geographically weighted regression (GWR) model designed to explore local associations between COVID-19 mortality rates and DPM exposure, using data from the 2018 AirToxScreen database. Results The GWR model found that associations between COVID-19 mortality rate and DPM concentrations may increase up to 77 deaths per 100,000 people in some US counties for every interquartile range (0.21 μg/m3) increase in DPM concentration. Significant positive associations between mortality rate and DPM were observed in New York, New Jersey, eastern Pennsylvania, and western Connecticut for the wave from January to May, and in southern Florida and southern Texas for June to September. The period from October to December exhibited a negative association in most parts of the US, which seems to have influenced the year-long relationship due to the large number of deaths during that wave of the disease. Conclusions Our models provided a picture in which long-term DPM exposure may have influenced COVID-19 mortality during the early stages of the disease. That influence appears to have waned over time as transmission patterns evolved.

Louisiana ranks among the bottom five states for air pollution and mortality. Our objective was to investigate associations between race and Coronavirus Disease 2019 (COVID-19) hospitalizations, intensive care unit (ICU) admissions, and mortality over time and determine which air pollutants and other characteristics may mediate COVID-19-associated outcomes. In our cross-sectional study, we analyzed hospitalizations, ICU admissions, and mortality among positive SARS-CoV-2 cases within a healthcare system around the Louisiana Industrial Corridor over four waves of the pandemic from 1 March 2020 to 31 August 2021. Associations between race and each outcome were tested, and multiple mediation analysis was performed to test if other demographic, socioeconomic, or air pollution variables mediate the race–outcome relationships after adjusting for all available confounders. Race was associated with each outcome over the study duration and during most waves. Early in the pandemic, hospitalization, ICU admission, and mortality rates were greater among Black patients, but as the pandemic progressed, these rates became greater in White patients. However, Black patients were disproportionately represented in these measures. Our findings imply that air pollution might contribute to the disproportionate share of COVID-19 hospitalizations and mortality among Black residents in Louisiana.

A community-integrated geographic information systems (CIGIS) study assimilating qualitative and quantitative information about human exposures and health was conducted in Colfax, Louisiana, which hosts a commercial open burn/open detonation thermal treatment (TT) facility that destroys hazardous waste from Superfund sites, explosives, military ordnances, and propellants. Fifty-eight percent of residents identified as Black, and median annual income was $16,318, with 90% of the population living below the poverty line. We conducted oral history interviews of twenty-nine residents and mined public records to document the community’s experiences. Interviews focused on themes of Colfax’s history, changing community fabric, resident health, and air pollution. The oral histories and public comments by community members provided information about lived experiences, including several health conditions, toleration of noise and vibration, property damage, and resulting changes to activity levels. These statements provided insight into the extent of suffering experienced by the local community. We also ran dispersion models for dates in 2020 when the waste stream composition, mass, and burn/smoldering times were provided in the facility’s public records. The dispersion models placed the air pollution at the homes of residents during some of the time, and waste stream records from the TT facility agree with community testimony about health effects based on the known health effects of those compounds. CIGIS integration of our community-based qualitative data and maps with quantitative air pollution dispersion model output illustrated alignment between community complaints of impacts to health and property, known toxicological information about waste stream compounds, and dispersion model output.

Long-lived environmentally persistent free radical (EPFR) exposures have been shown in toxicology studies to lead to respiratory and cardiovascular effects, which were thought to be due to the persistence of EPFR and their ability to produce reactive oxygen species. To characterize EPFR exposure and resulting health impacts, it is necessary to identify and systematize analysis protocols. Both direct measurement and solvent extraction methods have been applied to analyze environmental samples containing EPFR. The use of different protocols and solvents in EPFR analyses makes it difficult to compare results among studies. In this work, we reviewed EPFR studies that involved solvent extraction and carefully reported the details of the extraction methodology and retrieval recovery. EPFR recovery depends on the structure of the radical species and the solvent. For the limited number of studies available for review, the polar solvents had superior recovery in more studies. Radicals appeared to be more oxygen-centered following extraction for fly ash and particulate matter (PM) samples. Different solvent extraction methods to retrieve EPFR may produce molecular products during the extraction, thus potentially changing the sample toxicity. The number of studies reporting detailed methodologies is limited, and data in these studies were not consistently reported. Thus, inference about the solvent and protocol that leads to the highest EPFR extraction efficiency for certain types of radicals is not currently possible. Based on our review, we proposed reporting criteria to be included for future EPFR studies.

Objectives. To investigate potential changes in burdens from coal-fired electricity-generating units (EGUcfs) that emit fine particulate matter (PM2.5, defined as matter with a nominal mean aerodynamic diameter of ≤ 2.5 µm) among racial/ethnic and economic groups after reduction of operations in 92 US EGUcfs. Methods. PM2.5 burdens calculated for EGUs listed in the 2008, 2011, and 2014 National Emissions Inventory were recalculated for 2017 after omitting emissions from 92 EGUcfs. The combined influence of race/ethnicity and poverty on burden estimates was characterized. Results. Omission of 92 EGUcfs decreased PM2.5 burdens attributable to EGUs by 8.6% for the entire population and to varying degrees for every population subgroup. Although the burden decreased across all subgroups, the decline was not equitable. After omission of the 92 EGUcfs, burdens were highest for the below-poverty and non-White subgroups. Proportional disparities between White and non-White subgroups increased. In our combined analysis, the burden was highest for the non-White–high-poverty subgroup. Conclusions. Our results indicate that subgroups living in poverty experience the greatest absolute burdens from EGUcfs. Changes as a result of EGUcf closures suggest a shift in burden from White to non-White subgroups. Policymakers could use burden analyses to jointly promote equity and reduce emissions.

Objectives. To quantify nationwide disparities in the location of particulate matter (PM)-emitting facilities by the characteristics of the surrounding residential population and to illustrate various spatial scales at which to consider such disparities. Methods. We assigned facilities emitting PM in the 2011 National Emissions Inventory to nearby block groups across the 2009 to 2013 American Community Survey population. We calculated the burden from these emissions for racial/ethnic groups and by poverty status. We quantified disparities nationally and for each state and county in the country. Results. For PM of 2.5 micrometers in diameter or less, those in poverty had 1.35 times higher burden than did the overall population, and non-Whites had 1.28 times higher burden. Blacks, specifically, had 1.54 times higher burden than did the overall population. These patterns were relatively unaffected by sensitivity analyses, and disparities held not only nationally but within most states and counties as well. Conclusions. Disparities in burden from PM-emitting facilities exist at multiple geographic scales. Disparities for Blacks are more pronounced than are disparities on the basis of poverty status. Strictly socioeconomic considerations may be insufficient to reduce PM burdens equitably across populations.

Background The current single-pollutant approach to regulating ambient air pollutants is effective at protecting public health, but efficiencies may be gained by addressing issues in a multipollutant context since multiple pollutants often have common sources and individuals are exposed to more than one pollutant at a time. Objective We performed a cross-disciplinary review of the effects of multipollutant exposures on cardiovascular effects. Methods A broad literature search for references including at least two criteria air pollutants (particulate matter [PM], ozone [O3], oxides of nitrogen, sulfur oxides, carbon monoxide) was conducted. References were culled based on scientific discipline then searched for terms related to cardiovascular disease. Most multipollutant epidemiologic and experimental (i.e., controlled human exposure, animal toxicology) studies examined PM and O3 together. Discussion Epidemiologic and experimental studies provide some evidence for O3 concentration modifying the effect of PM, although PM did not modify O3 risk estimates. Experimental studies of combined exposure to PM and O3 provided evidence for additivity, synergism, and/or antagonism depending on the specific health endpoint. Evidence for other pollutant pairs was more limited. Conclusions Overall, the evidence for multipollutant effects was often heterogeneous, and the limited number of studies inhibited making a conclusion about the nature of the relationship between pollutant combinations and cardiovascular disease.

The objective of this research is to learn how the near-road gradient, in which NO2 and NOX (NO + NO2) concentrations are elevated, varies with changes in meteorological and traffic variables. Measurements of NO2 and NOX were obtained east of I-15 in Las Vegas and fit to functions whose slopes (dCNO2/dx and dCNOX/dx, respectively) characterize the size of the near-road zone where NO2 and NOX concentrations from mobile sources on the highway are elevated. These metrics were used to learn about the near-road gradient by modeling dCNO2/dx and dCNOX/dx as functions of meteorological variables (e.g., wind direction, wind speed), traffic (vehicle count), NOX concentration upwind of the road, and O3 concentration at two fixed-site ambient monitors. Generalized additive models (GAM) were used to model dCNO2/dx and dCNOX/dx versus the independent variables because they allowed for nonlinearity of the variables being compared. When data from all wind directions were included in the analysis, variability in O3 concentration comprised the largest proportion of variability in dCNO2/dx, followed by variability in wind direction. In a second analysis constrained to winds from the west, variability in O3 concentration remained the largest contributor to variability in dCNO2/dx, but the relative contribution of variability in wind speed to variability in dCNO2/dx increased relative to its contribution for the all-wind analysis. When data from all wind directions were analyzed, variability in wind direction was by far the largest contributor to variability in dCNOX/dx, with smaller contributions from hour of day and upwind NOX concentration. When only winds from the west were analyzed, variability in upwind NOX concentration, wind speed, hour of day, and traffic count all were associated with variability in dCNOX/dx. Increases in O3 concentration were associated with increased magnitude near-road dCNO2/dx, possibly shrinking the zone of elevated concentrations occurring near roads. Wind direction parallel to the highway was also related to an increased magnitude of both dCNO2/dx and dCNOX/dx, again likely shrinking the zone of elevated concentrations occurring near roads. Wind direction perpendicular to the road decreased the magnitude of dCNO2/dx and dCNOX/dx and likely contributed to growth of the zone of elevated concentrations occurring near roads. Thus, variability in near-road concentrations is influenced by local meteorology and ambient O3 concentration.

The nitrogen dioxide/oxides of nitrogen (NO2/NOX) ratio is an important surrogate for NO to NO2 chemistry in dispersion models when estimating NOX impacts in a near-road environment. Existing dispersion models use different techniques and assumptions to represent NO to NO2 conversion and do not fully characterize all of the important atmospheric chemical and mechanical processes. Thus, “real-world” ambient measurements must be analyzed to assess the behavior of NO2/NOX ratios near roadways. An examination of NO2/NOX ratio data from a field study conducted in Las Vegas, Nevada (NV), from mid-December, 2008 through mid-December, 2009 provides insights into the appropriateness of assumptions about the NO2/NOX ratio included in dispersion models. Data analysis indicates multiple factors affect the downwind NO2/NOX ratio. These include spatial gradient, background ozone (O3), source emissions of NO and NO2, and background NO2/NOX ratio. Analysis of the NO2/NOX ratio spatial gradient indicates that under high O3 conditions, the change in the ratio is fairly constant once a certain O3 threshold (≥ 30 ppb) is reached. However, under low O3 conditions (< 30 ppb), there are differences between weekdays and weekends, most likely due to a decline in O3 concentrations during the weekday morning hours, reducing the O3 available to titrate the emitted NO, allowing lower NO2/NOX ratios. These results suggest that under high O3 conditions, NOX chemistry is driving the NO2/NOX ratios whereas under low O3 conditions, atmospheric mixing is the driving factor.

This paper describes a new regression modeling approach to estimate on-road nitrogen dioxide (NO2) and oxides of nitrogen (NOX) concentrations and near-road spatial gradients using data from a near-road monitoring network. Field data were collected in Las Vegas, NV at three monitors sited 20, 100, and 300 m from Interstate-15 between December, 2008 and January, 2010. Measurements of NO2 and NOX were integrated over 1-hour intervals and matched with meteorological data. Several mathematical transformations were tested for regressing pollutant concentrations against distance from the roadway. A logit-ln model was found to have the best fit (R2 = 94.7%) and also provided a physically realistic profile. The mathematical model used data from the near-road monitors to estimate on-road concentrations and the near-road gradient over which mobile source pollutants have concentrations elevated above background levels. Average and maximum on-road NO2 concentration estimates were 33 ppb and 105 ppb, respectively. Concentration gradients were steeper in the morning and late afternoon compared with overnight when stable conditions preclude mixing. Estimated on-road concentrations were also highest in the late afternoon. Median estimated on-road and gradient NO2 concentrations were lower during summer compared with winter, with a steeper gradient during the summer, when convective mixing occurs during a longer portion of the day On-road concentration estimates were higher for winds perpendicular to the road compared with parallel winds and for atmospheric stability with neutral-to-unstable atmospheric conditions. The concentration gradient with increasing distance from the road was estimated to be sharper for neutral-to-unstable conditions when compared with stable conditions and for parallel wind conditions compared with perpendicular winds. A regression of the NO2/NOX ratios yielded on-road ratios ranging from 0.25 to 0.35, substantially higher than the anticipated tail-pipe emissions ratios. The results from the ratios also showed that the diurnal cycle of the background NO2/NOX ratios were a driving factor in the on-road and downwind NO2/NOX ratios.

This paper describes a new regression modeling approach to estimate on-road nitrogen dioxide (NO2) and oxides of nitrogen (NOX) concentrations and near-road spatial gradients using data from a near-road monitoring network. Field data were collected in Las Vegas, NV at three monitors sited 20, 100, and 300 m from Interstate-15 between December, 2008 and January, 2010. Measurements of NO2 and NOX were integrated over 1-hour intervals and matched with meteorological data. Several mathematical transformations were tested for regressing pollutant concentrations against distance from the roadway. A logit-ln model was found to have the best fit (R2 = 94.7%) and also provided a physically realistic profile. The mathematical model used data from the near-road monitors to estimate on-road concentrations and the near-road gradient over which mobile source pollutants have concentrations elevated above background levels. Average and maximum on-road NO2 concentration estimates were 33 ppb and 105 ppb, respectively. Concentration gradients were steeper in the morning and late afternoon compared with overnight when stable conditions preclude mixing. Estimated on-road concentrations were also highest in the late afternoon. Median estimated on-road and gradient NO2 concentrations were lower during summer compared with winter, with a steeper gradient during the summer, when convective mixing occurs during a longer portion of the day On-road concentration estimates were higher for winds perpendicular to the road compared with parallel winds and for atmospheric stability with neutral-to-unstable atmospheric conditions. The concentration gradient with increasing distance from the road was estimated to be sharper for neutral-to-unstable conditions when compared with stable conditions and for parallel wind conditions compared with perpendicular winds. A regression of the NO2/NOX ratios yielded on-road ratios ranging from 0.25 to 0.35, substantially higher than the anticipated tail-pipe emissions ratios. The results from the ratios also showed that the diurnal cycle of the background NO2/NOX ratios were a driving factor in the on-road and downwind NO2/NOX ratios.

In epidemiologic studies of health effects of air pollution, measurements or models are used to estimate exposure. Exposure estimates have errors that propagate to effect estimates in exposure-response models. We critically evaluate how types of exposure measurement error influenced bias and precision of effect estimates to understand conditions affecting interpretation of exposure-response models for epidemiologic studies of exposure to PM

Background: It is difficult to discern the proportion of blood lead (PbB) attributable to ambient air lead (PbA), given the multitude of lead (Pb) sources and pathways of exposure. The PbB–PbA relationship has previously been evaluated across populations. This relationship was a central consideration in the 2008 review of the Pb national ambient air quality standards. Objectives: The objectives of this study were to evaluate the relationship between PbB and PbA concentrations among children nationwide for recent years and to compare the relationship with those obtained from other studies in the literature. Methods: We merged participant-level data for PbB from the National Health and Nutrition Examination Survey (NHANES) III (1988–1994) and NHANES 9908 (1999–2008) with PbA data from the U.S. Environmental Protection Agency. We applied mixed-effects models, and we computed slope factor, d[PbB]/d[PbA] or the change in PbB per unit change in PbA, from the model results to assess the relationship between PbB and PbA. Results: Comparing the NHANES regression results with those from the literature shows that slope factor increased with decreasing PbA among children 0–11 years of age. Conclusion: These findings suggest that a larger relative public health benefit may be derived among children from decreases in PbA at low PbA exposures. Simultaneous declines in Pb from other sources, changes in PbA sampling uncertainties over time largely related to changes in the size distribution of Pb-bearing particulate matter, and limitations regarding sampling size and exposure error may contribute to the variability in slope factor observed across peer-reviewed studies. Citation: Richmond-Bryant J, Meng Q, Davis A, Cohen J, Lu SE, Svendsgaard D, Brown JS, Tuttle L, Hubbard H, Rice J, Kirrane E, Vinikoor-Imler LC, Kotchmar D, Hines EP, Ross M. 2014. The Influence of declining air lead levels on blood lead–air lead slope factors in children. Environ Health Perspect 122:754–760; http://dx.doi.org/10.1289/ehp.1307072

There is abundant literature finding that susceptibility factors, including race and ethnicity, age, and housing, directly influence blood lead levels. No study has explored how susceptibility factors influence the blood lead-air lead relationship nationally. The objective is to evaluate whether susceptibility factors act as effect measure modifiers on the blood lead-air lead relationship. Participant level blood lead data from the 1999 to 2008 National Health and Nutrition Examination Survey were merged with air lead data from the US Environmental Protection Agency. Linear mixed effects models were run with and without an air lead interaction term for age group, sex, housing age, or race/ethnicity to determine whether these factors are effect measure modifiers for all ages combined and for five age brackets. Age group and race/ethnicity were determined to be effect measure modifiers in the all-age model and for some age groups. Being a child (1-5, 6-11, and 12-19 years) or of Mexican-American ethnicity increased the effect estimate. Living in older housing (built before 1950) decreased the effect estimate for all models except for the 1-5-year group, where older housing was an effect measure modifier. These results are consistent with the peer-reviewed literature of time-activity patterns, ventilation, and toxicokinetics.

Nutrients that regulate methylation processes may modify susceptibility to the effects of air pollutants. Data from the National Birth Defects Prevention Study (United States, 1997-2006) were used to estimate associations between maternal exposure to nitrogen dioxide (NO2), dietary intake of methyl nutrients, and the odds of congenital heart defects in offspring. NO2 concentrations, a marker of traffic-related air pollution, averaged across postconception weeks 2-8, were assigned to 6,160 nondiabetic mothers of cases and controls using inverse distance-squared weighting of air monitors within 50 km of maternal residences. Intakes of choline, folate, methionine, and vitamins B6 and B12 were assessed using a food frequency questionnaire. Hierarchical regression models, which accounted for similarities across defects, were constructed, and relative excess risks due to interaction were calculated. Relative to women with the lowest NO2 exposure and high methionine intake, women with the highest NO2 exposure and lowest methionine intake had the greatest odds of offspring with a perimembranous ventricular septal defect (odds ratio = 3.23, 95% confidence interval: 1.74, 6.01; relative excess risk due to interaction = 2.15, 95% confidence interval: 0.39, 3.92). Considerable departure from additivity was not observed for other defects. These results provide modest evidence of interaction between nutrition and NO2 exposure during pregnancy.

Uncharacterized microscale spatial and temporal variability in urban air pollutant concentration dynamics may contribute uncertainty or bias to epidemiological model results. In this study, a method for quantifying this variability is presented. Urban buildings were treated as a matrix of bluff bodies to estimate the retention of air pollution in the street canyons downstream of the buildings. This method was based primarily on bluff body theoretical work that derived functional relationships between nondimensional contaminant residence time ( H ) within a wake and the following fluid properties of the air: 1) Reynolds Number (Re), 2) street canyon height ( D ) to width ( W ) aspect ratio ( D / W ), and 3) turbulence intensity, defined as the square root of turbulence kinetic energy ( k ) divided by the freestream wind speed ( U ). Empirical relationships between these variables were built from sulfur hexafluoride (SF 6 ) concentration and meteorological data collected during the Midtown Manhattan 2005 (MID05) Study held in August, 2005 in Manhattan, NY, along with geographical information system (GIS) data describing the building topography. Results were then compared with results from a similar previous analysis using data collected during the Joint Urban 2003 (JU2003) study in Oklahoma City, OK. For the MID05 data, Re ranged from 1.65 × 10 6 to 7.74 × 10 7 , with a median of 1.13 × 10 7 . The range of Re was consistent with earlier observations from the JU2003 study, although the measured winds tended to be more turbulent (median k = 2.2 m 2 s −2 ) compared with JU2003 (median k = 0.45 m 2 s −2 ). Values for H ranged from 7.2 to 1186, with a median H of 80.9. The distribution of H was substantially wider for MID05 than for JU2003, with model estimates exceeding observations of H by an order of magnitude for single obstacle wind tunnel studies with Re ∼ 10 4 . Inverse relationships were validated between H and Re and between H and D / W for the MID05 data and for a pooled data analysis from the MID05 and JU2003 studies. The model of H vs. Re for pooled MID05 and JU2003 data provided a good fit overall but produced a positively biased estimate of the Oklahoma City model results. The model of H vs. D / W for pooled MID05 and JU2003 data did not provide a good fit, suggesting that the building topographies of the two cities are too different to produce a reasonable comparison. These inter-study comparisons suggest that the topographic relationships may contain underlying site-specific features that would require elucidation prior to generalizing to other urban sites. Overall, results from this work present a foundational method for generating estimates of H based on readily available sources of data such as building coordinates and dimensions and meteorological parameters.

a b s t r a c t Epidemiological studies of health effects associated with ambient air pollution are subject to uncertainty in the effects estimates related to the spatial and temporal variability of ambient air pollution. This study examines meteorological and concentration decay data for an urban canopy in Oklahoma City, OK to develop a modeling approach that can be used to estimate spatiotemporal variability in contaminant retention that could add bias or uncertainty to epidemiological results. Concentration and microscale turbulent wind data from the Joint Urban 2003 study were reanalyzed to examine scaling relationships between contaminant residence time in urban street canyons, urban boundary layer winds, and urban topography. Street-level sulfur hexa fluoride (SF6) concentration time series were reviewed to find time periods that included a peak and decay. Exponential decay curves were fitted to each period, and a characteristic residence time was derived from each model slope. That residence time was nondimensionalized by the ratio of mean urban boundary layer wind speed to height of the building just upwind of the street canyon in which the concentration was measured. Sonic detection and ranging (SODAR) data were used to assess atmospheric turbulence conditions at times concurrent with the concentration decay measurements. Reynolds number ( Re ) was calculated from the 15-min average wind velocity and ranged from 2.1 ! 10 6 to 7.6 ! 10 7 . Nondimensional residence time ( H) ranged from 3.7 to 996 with a median of 13.3. Inverse relationships were validated between H and Re and between H and the street canyon aspect ratio. These relationships provided a mechanism to understand time-varying ventilation within a street canyon. The results shown here were intended to demonstrate how scaling relationships derived from the transport equation can be used to provide rapid estimates of characteristic decay times for the purpose of estimating variability in the concentrations encountered in an urban environment. This could be a useful tool to reduce uncertainty in air pollution epidemiological study results related to spatial and temporal variability in urban concentrations. Published by Elsevier Ltd.

The final 2008 lead (Pb) national ambient air quality standards (NAAQS) revision maintains Pb in total suspended particulate matter as the indicator. However, the final rule permits the use of low-volume PM10 (particulate matter sampled with a 50% cut-point of 10 μm) Federal Reference Method (FRM) monitors in lieu of total suspended particulate (TSP) monitors for some non-source-oriented monitoring. PM10 FRM monitors are known to provide more reliable concentration measurements than TSP samplers because they are omni-directional samplers and so are not biased by wind conditions. However, by design they exclude the upper tail of the particle size distribution. Hence, each monitor produces uncertainties about measured concentrations of Pb-bearing PM. Uncertainties in reported Pb data are also related to spatiotemporal variation of the concentration and size distribution of Pb-bearing PM. Therefore, a comprehensive literature review was performed to summarize the current knowledge regarding the concentration and size distribution of Pb particles in the atmosphere. The objectives of this review were to compile data that could shed light on these uncertainties, to provide insights useful during future Pb NAAQS reviews, and to identify areas where more research is needed. Results of this review indicated that Pb size distribution data are relatively limited and often outdated. Thirty-nine articles were found to have sufficiently detailed information regarding airborne Pb concentrations, study location, sample collection methods, and analytical techniques; only 16 of those papers reported Pb concentration data for multiple size fractions. For the most part, U.S. and European studies from the last forty years illustrate that the largest mode of the size distribution of airborne particle-bound Pb has shifted to larger sizes while airborne Pb concentrations have decreased in urban areas. This shift occurred as tetraethyl Pb additives in gasoline were phased out and industrial emissions and resuspended road dust became more important sources of Pb. Several studies also suggested the occurrence of long-range transport of Pb-bearing PM from industrial emissions. Uncertainties associated with these studies include influence of wind speed and direction on captured concentrations and variability in analytical techniques used to quantify Pb concentrations on the reported size distributions.

The objective of the proposed research is to assess the exposure of subway riders and workers to threat agents introduced in the subway environment. This article presents the study plan, considerations, and expected outcomes of a novel approach to study this issue. A modular scale model of a subway station has been erected from Metropolitan Transportation Authority of New York design specifications. This model will be used in a series of experiments to analyze airflow and dispersion patterns in the wake of a moving train and in an empty tunnel. Particle image velocimetry will be used to measure transient velocity profiles and concentration profiles.

Air pollution health studies of fine particulate matter (diameter ≤2.5 μm, PM2.5) often use outdoor concentrations as exposure surrogates. Failure to account for variability of indoor infiltration of ambient PM2.5 and time indoors can induce exposure errors. We developed and evaluated an exposure model for individuals (EMI), which predicts five tiers of individual-level exposure metrics for ambient PM2.5 using outdoor concentrations, questionnaires, weather, and time-location information. We linked a mechanistic air exchange rate (AER) model to a mass-balance PM2.5 infiltration model to predict residential AER (Tier 1), infiltration factors (Tier 2), indoor concentrations (Tier 3), personal exposure factors (Tier 4), and personal exposures (Tier 5) for ambient PM2.5. Using cross-validation, individual predictions were compared to 591 daily measurements from 31 homes (Tiers 1-3) and participants (Tiers 4-5) in central North Carolina. Median absolute differences were 39% (0.17 h(-1)) for Tier 1, 18% (0.10) for Tier 2, 20% (2.0 μg/m(3)) for Tier 3, 18% (0.10) for Tier 4, and 20% (1.8 μg/m(3)) for Tier 5. The capability of EMI could help reduce the uncertainty of ambient PM2.5 exposure metrics used in health studies.

Background Metabolic syndrome (MetS) is the co-occurrence of several conditions that increase risk of chronic disease and mortality. Multivariate models for calculating risk of MetS-related diseases based on combinations of biomarkers are promising for future risk estimation if based on large population samples. Given biomarkers’ nonspecificity and commonality in predicting diseases, we hypothesized that unique combinations of the same clinical diagnostic criteria can be used in different multivariate models to develop more accurate individual and cumulative risk estimates for specific MetS-related diseases. Methods We utilized adult biomarker and cardiovascular disease (CVD) data from the National Health and Nutrition Examination Survey as part of a cross-sectional analysis. Serum C-reactive protein (CRP), glycohemoglobin, triglycerides, high-density lipoprotein cholesterol, low-density lipoprotein cholesterol, total cholesterol, fasting glucose, and apolipoprotein-B were modeled. CVDs included congestive heart failure, coronary heart disease, angina, myocardial infarction, and stroke. Decile analysis for disease prevalence in each biomarker group and multivariate logistic regression for estimation of odds ratios were employed to measure the joint association between multiple biomarkers and CVD diagnoses. Results Of the biomarkers considered, glycohemoglobin, triglycerides, and CRP were consistently associated with the CVD outcomes of interest in decile analysis and were selected for the final models. Associations were overestimated when using single-marker models in comparison with full models; individual odds ratios decreased an average of 16.4% from the single-biomarker models to the joint association models for CRP, 6.6% for triglycerides, and 1.4% for glycohemoglobin. However, joint associations were stronger than any single-marker estimate. Additionally, reduced models produced unique combinations of biomarkers for specific CVD outcomes. Conclusion The reduced joint association modeling results suggest that unique combinations of biomarkers with their related measure of association can be used to produce more accurate cumulative risk estimates for each CVD. Additionally, our results indicate that the use of multiple biomarkers in a single multivariate model may provide increased accuracy of individual biomarker association estimates by controlling for statistical artifacts and spurious relationships due to co-biomarker confounding. Electronic supplementary material The online version of this article (doi:10.1186/s12963-015-0041-5) contains supplementary material, which is available to authorized users.

Monitoring of aerosols is typically performed over 3 h to diurnal time scales for outdoor concentration levels and 15 min to 8 h scales indoors. At these scales, concentration is assumed to be well mixed with little spatio-temporal variability around the sampler. Less attention has been given to the potential for acute exposure to contaminants during the initial minutes after a point-source release, where point-wise concentrations may greatly exceed the well-mixed conditions. Here, we seek to demonstrate that the commonly used well-mixed assumption is flawed in the first minutes after a contaminant is released because point-wise concentration levels are initially highly non-uniform and are influenced by turbulent structures caused by the presence of obstacles in the room. This assumption was examined by releasing 3 μm aerosols in a test room with HEPA filter ventilation and by varying controlled conditions of room furnishings (furnished vs. unfurnished) and contaminant release locations (at the inlet vent or under a desk). For each experiment, aerosol concentrations were measured simultaneously at seven locations by nephelometry. Complementary computational fluid dynamics simulations were performed to lend confidence to the experiments and to provide detailed pictures of the velocity and particle concentration profiles. The experimental and numerical results corroborated the hypothesis. For both release locations in the furnished room, a completely well-mixed condition did not occur 600 s after the release, and aerosol dispersion was dictated by the turbulent airflow pattern. For the empty room, there was significantly less spatial variability in the point-wise measured concentrations after 300 s than for the furnished room. This information may aid in evaluating the potential for occupant exposure to aerosolized hazardous substances and in supporting optimization of detector placement.

The objective of this work is to evaluate the performance of the steady state Reynolds Averaged Navier-Stokes (RANS) computational fluid dynamics (CFD) models for estimating concentration of low Stokes number aerosols (Stk = O(10−4)) in the wake of a bluff body. These simulations are compared with experimental data. In the simulations and experiments, particles are released upstream of the body and convected downstream, where some are entrained into the wake. The air velocity is computed using a steady state renormalized group k ∼ ϵ model. Lagrangian particle trajectory simulations are performed in conjunction with each airflow model to calculate concentrations. The experiments are performed in an aerosol wind tunnel in which phase Doppler velocimetry measurements are obtained for the velocity field and aerosol concentration. The RANS model yields a wake concentration deficit that extends downstream past x/D = 10, while the experiments produce elevated concentrations immediately downstream of the near wak...

This work illustrates the discrete vortex method (DVM) as a tool for simulating environmental fluid mechanics problems involving transport in the wake of a bluff body. The DVM was used to model both the long-time-averaged and instantaneous features of flow past a circular cylinder. Simulations were performed for Re = 140, 000. Verification testing was accomplished by refining time-step and vortex element circulation. The DVM was validated through comparison with experimental data from Cantwell and Coles. Verification testing demonstrated that, while global convergence is not possible for an unsteady flow simulation, it is possible to have ‘convergence to physical results’. This verification entails identifying a range of parameters in which a flow containing coherent structures and matching physical conditions is attainable. Validation tests demonstrated excellent agreement between experimental and simulated results for time-averaged velocity and shear stress profiles, as well as Strouhal number.

A novel aerosol generation system has been constructed for use in a large wind tunnel for two distinct research projects. One project requires a uniform aerosol concentration over the wind tunnel cross section, while the other project demands a stratified aerosol concentration distribution. The system consists of an array of venturi nozzles, which entrains particulate matter from a moving conveyor belt and disperses it into the tunnel under the force provided by a compressed air source. For the stratified release configuration, only the bottom row of nozzles was used and a confinement sleeve was installed to prevent mixing with clean air; the mixing fans were omitted from this configuration. The uniform release arrangement was tested by gravimetrically measuring particle concentration over the cross section of the tunnel for tunnel speeds of 0.1 and 1.0 m/s; uniformity was achieved within a coefficient of variation of 6.4%. The stratified distribution results show a high concentration near the floor, whic...

Verification testing was performed for various Reynolds-averaged Navier–Stokes methods for uniform flow past a circular cylinder at Re= 5232. The standard and renormalized group (RNG) versions of the k–e method were examined, along with the Boussinesq, Speziale and Launder constitutive relationships. Wind tunnel experiments for flow past a circular cylinder were also performed to obtain a comparative data set. Preliminary studies demonstrate poor convergence for the Speziale relationship. Verification testing with the standard and RNG k–e models suggests that the simulations exhibit global monotonic convergence for the Boussinesq models. However, the global order of accuracy of the methods was much lower than the expected order of accuracy of 2. For this reason, pointwise convergence ratios and orders of accuracy were computed to show that not all sampling locations had converged (standard k–e model: 19% failed to converge; RNG k–e model: 14% failed to converge). When the non-convergent points were removed from consideration, the average orders of accuracy are closer to the expected value (standard k–e model: 1.41; RNG k–e model: 1.27). Poor iterative and global grid convergence was found for the RNG k–e/Launder model. The standard and RNG k–e models with the Boussinesq relationship were compared with experimental data and yielded results significantly different from the experiments. Copyright © 2003 John Wiley & Sons, Ltd.

The peer-reviewed literature on the health and ecological effects of lead (Pb) indicates common effects and underlying modes of action across multiple organisms for several endpoints. Based on such observations, the United States (U.S.) Environmental Protection Agency (EPA) applied a cross-species approach in the 2013 Integrated Science Assessment (ISA) for Lead for evaluating the causality of relationships between Pb exposure and specific endpoints that are shared by humans, laboratory animals, and ecological receptors (i.e., hematological effects, reproductive and developmental effects, and nervous system effects). Other effects of Pb (i.e., cardiovascular, renal, and inflammatory responses) are less commonly assessed in aquatic and terrestrial wildlife limiting the application of cross-species comparisons. Determinations of causality in ISAs are guided by a framework for classifying the weight of evidence across scientific disciplines and across related effects by considering aspects such as biological plausibility and coherence. As illustrated for effects of Pb where evidence across species exists, the integration of coherent effects and common underlying modes of action can serve as a means to substantiate conclusions regarding the causal nature of the health and ecological effects of environmental toxicants.

The objective of this work is to examine associations between blood lead (PbB) and air lead (PbA) in particulate matter measured at different size cuts by use of PbB concentrations from the National Health and Nutrition Examination Survey and PbA concentrations from the U.S. Environmental Protection Agency for 1999-2008. Three size fractions of particle-bound PbA (TSP, PM10, and PM2.5) data with different averaging times (current and past 90-day average) were utilized. A multilevel linear mixed effect model was used to characterize the PbB-PbA relationship. At 0.15 μg/m(3), a unit decrease in PbA in PM10 was significantly associated with a decrease in PbB of 0.3-2.2 μg/dL across age groups and averaging times. For PbA in PM2.5 and TSP, slopes were generally positive but not significant. PbB levels were more sensitive to the change in PbA concentrations for children (1-5 and 6-11 years) and older adults (≥ 60 years) than teenagers (12-19 years) and adults (20-59 years). For the years following the phase-out of Pb in gasoline and a resulting upward shift in the PbA particle size distribution, PbA in PM10 was a statistically significant predictor of PbB. The results also suggest that age could affect the PbB-PbA association, with children having higher sensitivity than adults.

Although lead (Pb) emissions to the air have substantially decreased in the United States since the phase-out of leaded gasoline by 1995, amounts of lead in some soils remain elevated. Lead concentrations in residential and recreational soils are of concern because health effects have been associated with Pb exposure. Elevated soil Pb is especially harmful to young children due to their higher likelihood of soil ingestion. The purpose of this study is to create a comprehensive compilation of U.S. soil Pb data published from 1970 through 2012 as well as to analyze the collected data to reveal spatial and/or temporal soil Pb trends in the U.S. over the past 40 years. A total of 84 soil Pb studies across 62 U.S. cities were evaluated. Median soil Pb values from the studies were analyzed with respect to year of sampling, residential location type (e.g., urban, suburban), and population density. In aggregate, there was no statistically significant correlation between year and median soil Pb; however, within single cities, soil Pb generally declined over time. Our analysis shows that soil Pb quantities in city centers were generally highest and declined towards the suburbs and exurbs of the city. In addition, there was a statistically significant, positive relationship between median soil Pb and population density. In general, the trends examined here align with previously reported conclusions that soil Pb levels are higher in larger urban areas and Pb tends to remain in soil for long periods of time.

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

National and local declines in lead (Pb) in blood (PbB) over the past several years coincide with the decline in ambient air Pb (PbA) concentrations. The objective of this work is to evaluate how the relationship between PbB levels and PbA levels has changed following the phase out of leaded gasoline and tightened controls on industrial Pb emissions over the past 30 years among a national population sample. Participant-level data from the National Health and Nutrition Examination Survey (NHANES) were employed for two time periods (1988-1994 and 1999-2008), and the model was corrected for housing, demographic, socioeconomic, and other covariates present in NHANES. NHANES data for PbB and covariates were merged with PbA data from the U.S. Environmental Protection Agency. Linear mixed effects models (LMEs) were run to assess the relationship of PbB with PbA; sample weights were omitted, given biases encountered with the use of sample weights in LMEs. The 1988-1994 age-stratified results found that ln(PbB) was statistically significantly associated with ln(PbA) for all age groups. The consistent influence of PbA on PbB across age groups for the years 1988-1994 suggests a ubiquitous exposure unrelated to age of the sample population. The comparison of effect estimates for ln(PbA) shows a statistically significant effect estimate and ANOVA results for ln(PbB) for the 6- to 11-year and 12- to 19-year age groups during 1999-2008. The more recent finding suggests that PbA has less consistent influence on PbB compared with other factors.

A study was performed to assess the relationship between black carbon (BC), passing traffic, and vehicular idling outside New York City (NYC) schools during student dismissal. Monitoring was performed at three school sites in East Harlem, the Bronx, and Brooklyn for 1 month per year over a two-year period from November 2006–October 2008. Monitoring at each site was conducted before and after the Asthma Free School Zone (AFSZ) asthma reduction education program was administered. Real-time equipment with a one-minute averaging interval was used to obtain the BC data, while volume counts of idling and passing school busses, trucks, and automobiles were collected each minute by study staff. These data were matched to ambient PM2.5 and meteorology data obtained from the New York State Department of Environmental Conservation. A generalized additive model (GAM) model was run to examine the relationship between BC concentration and each variable while accounting for site-to-site differences. F-tests were employed to assess the significance of each of the predictor variables. The model results suggested that variability in ambient PM2.5 concentration contributed 24% of the variability in transformed BC concentration, while variability in the number of idling busses and trucks on the street during dismissal contributed 20% of the variability in transformed BC concentration. The results of this study suggest that a combination of urban scale and local traffic control approaches in combination with cessation of school bus idling will produce improved local BC concentration outside schools.

High-density housing in close proximity to freeways in conjunction with high concentrations of traffic emissions may contribute to significant degradation of indoor air quality. Densely populated areas may also be targeted for intentional releases of biological or chemical agents because an urban release could result in higher morbidity and mortality from the attack. Since people tend to spend the majority of their time indoors, it is paramount to explore the relationships between outdoor and indoor air quality and, specifically, the time scales that characterize transport of airborne contaminants from outdoors to indoors. In the Brooklyn Traffic Real-Time Ambient Pollutant Penetration and Environmental Dispersion (B-TRAPPED) study, a three-story row house with a flat face and roof and multiple rooms was used to investigate outdoor-to-indoor contaminant time scales. The building was located in the Sunset Park neighborhood of Brooklyn, NY, USA, in the vicinity of a major expressway and a heavily trafficked arterial road. It was found that the building shell has a profound impact on the indoor concentrations. A strong hourly periodicity (see Eisner et al., this issue, DOI: 10.1039/b907132f) in concentration outside the building during the morning “rush hour” was used as evidence to suggest that indoor contaminants originated from outdoor air penetration. Although the indoor concentrations followed a similar pattern, indoor concentrations were found to be more persistent than outdoor concentrations. Stronger persistency is used here to describe the tendency of the indoor concentration to continue to rise even if the outdoor concentration has started to drop, or vice versa. This may be an important factor in assessing negative health risks to inhabitants or first responders. A cross-correlation technique was employed to study the correlation between outdoor and indoor time series. In the high-density housing residential building used in the study, it was found that a long lag time exists (11 min) before indoor and outdoor concentrations reach maximal correlation.

The Brooklyn Traffic Real-Time Ambient Pollutant Penetration and Environmental Dispersion (B-TRAPPED) study, conducted in Brooklyn, NY, USA, in 2005, was designed with multiple goals in mind, two of which were contaminant source characterization and street canyon transport and dispersion monitoring. In the portion of the study described here, synchronized wind velocity and azimuth as well as particulate matter (PM) concentrations at multiple locations along 33rd Street were used to determine the feasibility of using traffic emissions in a complex urban topography as a sole tracer for studying urban contaminant transport. We demonstrate in this paper that it is possible to link downwind concentrations of contaminants in an urban street canyon to the vehicular traffic cycle using Eigen-frequency analysis. In addition, multivariable circular histograms are used to establish directional frequency maxima for wind velocity and contaminant concentration.

Wind tunnel experiments were performed to examine the effect of a tall tower on the flow around an otherwise uniform array of buildings. Additionally, preliminary CFD simulations were run to visualize the flow with more resolution. The model used in both the wind tunnel and CFD studies was designed to simulate an area of Brooklyn, NY, USA, where blocks of residential row houses form a neighborhood bordering a major urban highway. This area was the site of a field study that, along with the work reported here, had the goal of improving the understanding of airflow and dispersion patterns within urban microenvironments. Results reveal that a tall tower has a dramatic effect on the flow in the street canyons in the neighboring blocks, enhancing the exchange between the street canyon flow and the freestream flow aloft. In particular, vertical motion down the windward side and up the leeward side of the tower resulted in strong flows in the lateral street canyons and increased winds in the street canyons in the immediate vicinity of the tower. These phenomena were visible in both the wind tunnel and CFD results, although some minor differences in the flow fields were noted.

article i nfo An air quality study was performed outside a cluster of schools in the East Harlem neighborhood of New York City. PM2.5 and black carbon concentrations were monitored using real-time equipment with a one-minute averaging interval. Monitoring was performed at 1:45-3:30 PM during school days over the period October 31-November 17, 2006. The designated time period was chosen to capture vehicle emissions during end-of- day dismissals from the schools. During the monitoring period, minute-by-minute volume counts of idling and passing school buses, diesel trucks, and automobiles were obtained. These data were transcribed into time series of number of diesel vehicles idling, number of gasoline automobiles idling, number of diesel vehicles passing, and number of automobiles passing along the block adjacent to the school cluster. Multivariate regression models of the log-transform of PM2.5 and black carbon (BC) concentrations in the East Harlem street canyon were developed using the observation data and data from the New York State Department of Environmental Conservation on meteorology and background PM2.5. Analysis of variance was used to test the contribution of each covariate to variability in the log-transformed concentrations as a means to judge the relative contribution of each covariate. The models demonstrated that variability in background PM2.5 contributes 80.9% of the variability in log(PM2.5) and 81.5% of the variability in log(BC). Local traffic sources were demonstrated to contribute 5.8% of the variability in log(BC) and only 0.43% of the variability in log(PM2.5). Diesel idling and passing were both significant contributors to variability in log(BC), while diesel passing was a significant contributor to log(PM2.5). Automobile idling and passing did not contribute significant levels of variability to either concentration. The remainder of variability in each model was explained by temperature, along-canyon wind, and cross-canyon wind, which were all significant in the models.

The goal of this research was to examine the characteristics of the spatial velocity and concentration profiles which might result in health care workers’ exposure to a pathogenic agent in an airborne infection isolation room (AIIR). Computational fluid dynamics simulations were performed for this purpose. This investigation expanded on the work of Huang and Tsao [The influence of air motion on bacteria removal in negative pressure isolation rooms. HVAC & R Research 2005; 11: 563–85], who studied how ventilation conditions impact dispersion of pathogenic nuclei in an AIIR by investigating the airflow conditions impacting dispersion of infectious agents in the AIIR. The work included a careful quality assurance study of the computed airflow, and final simulations were performed on a fine tetrahedral mesh with approximately 1.3×10 6 cells. The 1 μm diameter particles were released from a 0.001225 m 2 area representing the nose and mouth. Two cases were investigated during the current study: continuous exhalation of pathogen-laden air from the patient and expulsion of pathogenic particles by a single cough or sneeze. Slow decay of particle concentration in the AIIR during the single cough/sneeze simulation and tendency for particle accumulation near the AIIR walls observed in the continuous breathing simulation suggest that unintended exposures are possible despite the ventilation system. Based on these findings, it is recommended that extra care be taken to assure proper functionality of personal protective equipment used in an AIIR.

The objective of this study is to test a technique used to analyze contaminant transport in the wake of a bluff body under controlled experimental conditions for application to aerosol transport in a complex furnished room. Specifically, the hypothesis tested by our work is that the dispersion of contaminants in a room is related to the turbulence kinetic energy and length scale. This turbulence is, in turn, determined by the size and shape of furnishings within the room and by the ventilation characteristics. This approach was tested for indoor dispersion through computational fluid dynamics simulations and laboratory experiments. In each, 3 mum aerosols were released in a furnished room with varied contaminant release locations (at the inlet vent or under a desk). The realizable k approximately epsilon model was employed in the simulations, followed by a Lagrangian particle trajectory simulation used as input for an in-house FORTRAN code to compute aerosol concentration. For the experiments, concentrations were measured simultaneously at seven locations by laser photometry, and air velocity was measured using laser Doppler velocimetry. The results suggest that turbulent diffusion is a significant factor in contaminant residence time in a furnished room. This procedure was then expanded to develop a simplified correlation between contaminant residence time and the number of enclosing surfaces around a point containing the contaminant. Practical Implications The work presented here provides a methodology for relating local aerosol residence time to properties of room ventilation and furniture arrangement. This technique may be used to assess probable locations of high concentration by knowing only the particle release location, furniture configuration, inlet and outlet locations, and air speeds, which are all observable features. Applications of this method include development of 'rules of thumb' for first responders entering a room where an agent has been released and selection of sampler locations to monitor conditions in sensitive areas.

This article is the second in a two-paper series presenting results from wind tunnel and computational fluid dynamics (CFD) simulations of flow and dispersion in an idealized model urban neighborhood. Pollutant dispersion results are presented and discussed for a model neighborhood that was characterized by regular city blocks of three-story row houses with a single 12-story tower located at the downwind edge of one of these blocks. The tower had three significant effects on pollutant dispersion in the surrounding street canyons: drawing the plume laterally towards the tower, greatly enhancing the vertical dispersion of the plume in the wake of the tower, and significantly decreasing the residence time of pollutants in the wake of the tower. In the wind tunnel, tracer gas released in the avenue lee of the tower, but several blocks away laterally, was pulled towards the tower and lifted in the wake of the tower. The same lateral movement of the pollutant was seen in the next avenue, which was approximately 2.5 tower heights downwind of the tower. The tower also served to ventilate the street canyon directly in its wake more rapidly than the surrounding areas. This was evidenced by CFD simulations of concentration decay where the residence time of pollutants lee of the 12-story tower was found to be less than half the residence time behind a neighboring three-story building. This same phenomenon of rapid vertical dispersion lee of a tower among an array of smaller buildings was also demonstrated in a separate set of wind tunnel experiments using an array of cubical blocks. A similar decrease in the residence time was observed when the height of one block was increased.

This paper presents data analysis from the Brooklyn Traffic Real-Time Ambient Pollutant Penetration and Environmental Dispersion (B-TRAPPED) study to assess the transport of ultrafine particulate matter (PM) across urban intersections. Experiments were performed in a street canyon perpendicular to a highway in Brooklyn, NY, USA. Real-time ultrafine PM samplers were positioned on either side of an intersection at multiple locations along a street to collect time-series number concentration data. Meteorology equipment was positioned within the street canyon and at an upstream background site to measure wind speed and direction. Time-series analysis was performed on the PM data to compute a transport velocity along the direction of the street for the cases where background winds were parallel and perpendicular to the street. The data were analyzed for sampler pairs located (1) on opposite sides of the intersection and (2) on the same block. The time-series analysis demonstrated along-street transport, including across the intersection when background winds were parallel to the street canyon and there was minimal transport and no communication across the intersection when background winds were perpendicular to the street canyon. Low but significant values of the cross-correlation function (CCF) underscore the turbulent nature of plume transport along the street canyon. The low correlations suggest that flow switching around corners or traffic-induced turbulence at the intersection may have aided dilution of the PM plume from the highway. This observation supports similar findings in the literature. Furthermore, the time-series analysis methodology applied in this study is introduced as a technique for studying spatiotemporal variation in the urban microscale environment.

The Brooklyn traffic real-time ambient pollutant penetration and environmental dispersion (B-TRAPPED) study was a multidisciplinary field research project that investigated the transport, dispersion, and infiltration processes of traffic emission particulate matter (PM) pollutants in a near-highway urban residential area. The urban PM transport, dispersion, and infiltration processes were described mathematically in a theoretical model that was constructed to develop the experimental objectives of the B-TRAPPED study. In the study, simultaneous and continuous time-series PM concentration and meteorological data collected at multiple outdoor and indoor monitoring locations were used to characterize both temporal and spatial patterns of the PM concentration movements within microscale distances (