Stuart Batterman

Optimizing Traffic Control to Reduce Fuel Consumption and Vehicular Emissions: Integrated Approach with VISSIM, CMEM, and VISGAOST

One way to reduce excessive fuel consumption and vehicular emissions on urban streets is to optimize signal timings. Historically, signal timing optimization tools were used to reduce traffic delay and stops. The concept of optimizing signal timings to reduce fuel consumption and emissions was addressed decades ago with tools that are now considered outdated. This study advocates a fresh approach to integrating existing state-of-the-art tools for reassessing and ultimately minimizing fuel consumption and emissions. VISSIM, CMEM, and VISGAOST were linked to optimize signal timings and minimize fuel consumption and CO2 emissions. As a case study, a 14-intersection network in Park City, Utah, was used. Signal timings were optimized for seven optimization objective functions to find the lowest fuel consumption and CO2 emissions. Findings show that a formula commonly used to estimate fuel consumption in traffic simulation tools inadequately estimates fuel consumption and cannot be used as a reliable objective function in signal timing optimizations. Some of the performance measures used as objective functions in the optimization process were proved to be ineffective. When CMEM-estimated fuel consumption is used as an objective function, estimated fuel savings are around 1.5%, a statistically significant decrease. Further research is needed to find an effective way to minimize fuel consumption and emissions by using the proposed approach.

A Critical Review of Naphthalene Sources and Exposures Relevant to Indoor and Outdoor Air

Both the recent classification of naphthalene as a possible human carcinogen and its ubiquitous presence motivate this critical review of naphthalene’s sources and exposures. We evaluate the environmental literature on naphthalene published since 1990, drawing on nearly 150 studies that report emissions and concentrations in indoor, outdoor and personal air. While naphthalene is both a volatile organic compound and a polycyclic aromatic hydrocarbon, concentrations and exposures are poorly characterized relative to many other pollutants. Most airborne emissions result from combustion, and key sources include industry, open burning, tailpipe emissions, and cigarettes. The second largest source is off-gassing, specifically from naphthalene’s use as a deodorizer, repellent and fumigant. In the U.S., naphthalene’s use as a moth repellant has been reduced in favor of para-dichlorobenzene, but extensive use continues in mothballs, which appears responsible for some of the highest indoor exposures, along with off-label uses. Among the studies judged to be representative, average concentrations ranged from 0.18 to 1.7 μg m−3 in non-smoker’s homes, and from 0.02 to 0.31 μg m−3 outdoors in urban areas. Personal exposures have been reported in only three European studies. Indoor sources are the major contributor to (non-occupational) exposure. While its central tendencies fall well below guideline levels relevant to acute health impacts, several studies have reported maximum concentrations exceeding 100 μg m−3, far above guideline levels. Using current but draft estimates of cancer risks, naphthalene is a major environmental risk driver, with typical individual risk levels in the 10−4 range, which is high and notable given that millions of individuals are exposed. Several factors influence indoor and outdoor concentrations, but the literature is inconsistent on their effects. Further investigation is needed to better characterize naphthalene’s sources and exposures, especially for indoor and personal measurements.

Brominated flame retardants in offices in Michigan, U.S.A.

Brominated flame retardants (BFRs) are now ubiquitous contaminants with large reservoirs and high concentrations in buildings. Most of the information documenting BFR levels has been obtained in residences, and other environments that can lead to exposure have received relatively little attention, including offices that contain numerous BFR sources and where individuals spend considerable time. The aim of this study is to characterize BFR concentrations, potential emission sources, and migration pathways in office environments. We measure BFR levels in floor dust, indoor air, ventilation filter dust, and carpets in ten commercial and institutional buildings in Michigan, U.S.A. The median concentration of total BDEs in settled dust was 8754 ng g(-1), at the upper range of levels previously reported. Especially elevated levels were found in offices in buildings that contained known or likely BFR sources, e.g., computer servers. A trends analysis in a newly constructed building showed remarkable increases in concentrations of BFRs in settled dust and indoor air, and apparent steady-state levels were reached 5 to 8 months after building completion, a particularly striking finding given that the building was constructed and furnished several years after the voluntary phase-out of the penta- and octa-mixtures. Airborne particulate matter collected in a buildings HVAC system filters contained PBDEs, including BDE-209, at levels exceeding the concentration of floor dust. In conjunction with estimates of building air flow rates, filter efficiency and other parameters, mass balance calculations for this building were used to estimate the emission rates and reservoirs of PBDEs. The widespread distribution of BFRs found in offices in both new and old buildings suggests the significance of workplace exposures, the need for controls to minimize human exposure, intra-building migration, and environmental releases of these chemicals, and the need for monitoring in new buildings to confirm the effectiveness of the PBDE phase-out.

Residence location as a measure of environmental exposure: a review of air pollution epidemiology studies.

Residence location has long been used to indicate environmental exposure in many epidemiological studies. This indicator is easy to establish, requires little exposure or monitoring data, and is potentially applicable to many types of investigations. The validity, accuracy and utility of residence location as an exposure indicator, however, is challenged by current concerns regarding multiple exposure pathways, persistent and toxic contaminants, and cumulative exposures from non-point, mobile and point sources. This paper reviews 45 epidemiological studies that use residence location to identify study populations and estimate air pollution exposures. Thirteen (29%) of the studies determined environmental exposures based on “proximity” measures, usually the distance from a subjects residence to a pollutant source. Other studies used “zones” presumed to have equal pollutant levels. Several studies combined zone and proximity approaches. Exposures were quantified using monitoring data in 27 (60%) studies and dispersion modeling in two (4%) studies. Sixteen (36%) studies did not use any environmental data to quantify exposure. A total of 31 (69%) of the studies reported significant associations between health endpoints and the pollutant exposures represented by residence location. In general, comprehensive and systematic approaches to identify and estimate population exposures were not used, and the exposure estimates were therefore deemed likely to have great uncertainty. Unless exposure levels among groups are verified, it cannot be determined whether nonsignificant associations between exposures and health endpoints indicate a lack of measurable health effects, or are merely a result of exposure misclassification. Site-specific and quantitative exposure assessments are needed to better quantify and confirm exposures within such studies, as well as to permit interpretations and comparisons across studies.

Statistical strategies for constructing health risk models with multiple pollutants and their interactions: possible choices and comparisons

BackgroundAs public awareness of consequences of environmental exposures has grown, estimating the adverse health effects due to simultaneous exposure to multiple pollutants is an important topic to explore. The challenges of evaluating the health impacts of environmental factors in a multipollutant model include, but are not limited to: identification of the most critical components of the pollutant mixture, examination of potential interaction effects, and attribution of health effects to individual pollutants in the presence of multicollinearity.MethodsIn this paper, we reviewed five methods available in the statistical literature that are potentially helpful for constructing multipollutant models. We conducted a simulation study and presented two data examples to assess the performance of these methods on feature selection, effect estimation and interaction identification using both cross-sectional and time-series designs. We also proposed and evaluated a two-step strategy employing an initial screening by a tree-based method followed by further dimension reduction/variable selection by the aforementioned five approaches at the second step.ResultsAmong the five methods, least absolute shrinkage and selection operator regression performs well in general for identifying important exposures, but will yield biased estimates and slightly larger model dimension given many correlated candidate exposures and modest sample size. Bayesian model averaging, and supervised principal component analysis are also useful in variable selection when there is a moderately strong exposure-response association. Substantial improvements on reducing model dimension and identifying important variables have been observed for all the five statistical methods using the two-step modeling strategy when the number of candidate variables is large.ConclusionsThere is no uniform dominance of one method across all simulation scenarios and all criteria. The performances differ according to the nature of the response variable, the sample size, the number of pollutants involved, and the strength of exposure-response association/interaction. However, the two-step modeling strategy proposed here is potentially applicable under a multipollutant framework with many covariates by taking advantage of both the screening feature of an initial tree-based method and dimension reduction/variable selection property of the subsequent method. The choice of the method should also depend on the goal of the study: risk prediction, effect estimation or screening for important predictors and their interactions.

Association of daily asthma emergency department visits and hospital admissions with ambient air pollutants among the pediatric Medicaid population in Detroit: Time-series and time-stratified case-crossover analyses with threshold effects

BACKGROUND Asthma morbidity has been associated with ambient air pollutants in time-series and case-crossover studies. In such study designs, threshold effects of air pollutants on asthma outcomes have been relatively unexplored, which are of potential interest for exploring concentration-response relationships. METHODS This study analyzes daily data on the asthma morbidity experienced by the pediatric Medicaid population (ages 2-18 years) of Detroit, Michigan and concentrations of pollutants fine particles (PM2.5), CO, NO2 and SO2 for the 2004-2006 period, using both time-series and case-crossover designs. We use a simple, testable and readily implementable profile likelihood-based approach to estimate threshold parameters in both designs. RESULTS Evidence of significant increases in daily acute asthma events was found for SO2 and PM2.5, and a significant threshold effect was estimated for PM2.5 at 13 and 11 μg m(-3) using generalized additive models and conditional logistic regression models, respectively. Stronger effect sizes above the threshold were typically noted compared to standard linear relationship, e.g., in the time series analysis, an interquartile range increase (9.2 μg m(-3)) in PM2.5 (5-day-moving average) had a risk ratio of 1.030 (95% CI: 1.001, 1.061) in the generalized additive models, and 1.066 (95% CI: 1.031, 1.102) in the threshold generalized additive models. The corresponding estimates for the case-crossover design were 1.039 (95% CI: 1.013, 1.066) in the conditional logistic regression, and 1.054 (95% CI: 1.023, 1.086) in the threshold conditional logistic regression. CONCLUSION This study indicates that the associations of SO2 and PM2.5 concentrations with asthma emergency department visits and hospitalizations, as well as the estimated PM2.5 threshold were fairly consistent across time-series and case-crossover analyses, and suggests that effect estimates based on linear models (without thresholds) may underestimate the true risk.

Sustainable Control of Water-Related Infectious Diseases: A Review and Proposal for Interdisciplinary Health-Based Systems Research

Objective Even when initially successful, many interventions aimed at reducing the toll of water-related infectious disease have not been sustainable over longer periods of time. Here we review historical practices in water-related infectious disease research and propose an interdisciplinary public health oriented systems approach to research and intervention design. Data sources On the basis of the literature and the authors’ experiences, we summarize contributions from key disciplines and identify common problems and trends. Practices in developing countries, where the disease burden is the most severe, are emphasized. Data extraction We define waterborne and water-associated vectorborne diseases and identify disciplinary themes and conceptual needs by drawing from ecologic, anthropologic, engineering, political/economic, and public health fields. A case study examines one of the classes of water-related infectious disease. Data synthesis The limited success in designing sustainable interventions is attributable to factors that include the complexity and interactions among the social, ecologic, engineering, political/economic, and public health domains; incomplete data; a lack of relevant indicators; and most important, an inadequate understanding of the proximal and distal factors that cause water-related infectious disease. Fundamental change is needed for research on water-related infectious diseases, and we advocate a systems approach framework using an ongoing evidence-based health outcomes focus with an extended time horizon. The examples and case study in the review show many opportunities for interdisciplinary collaborations, data fusion techniques, and other advances. Conclusions The proposed framework will facilitate research by addressing the complexity and divergent scales of problems and by engaging scientists in the disciplines needed to tackle these difficult problems. Such research can enhance the prevention and control of water-related infectious diseases in a manner that is sustainable and focused on public health outcomes.

Partition coefficients for the trihalomethanes among blood, urine, water, milk and air

Chloroform, bromodichloromethane, chlorodibromomethane, and bromoform comprise the trihalomethanes, a group of widespread and mildly lipophilic compounds that result from water chlorination and other sources. Many animal studies show the chronic toxicity and carcinogenicity of these compounds, and recent work has demonstrated the importance of both ingestion and inhalation exposure pathways. This study presents partition coefficients describing the equilibrium among biological compartments (air, water, blood, milk, urine) for the four THMs based on results of headspace gas chromatographic analyses performed under equilibrium conditions and at 37 degrees C. The calculated partition coefficients ranged from 2.92 to 4.14 for blood/water, 1.54-2.85 for milk/blood, and 3.41-4.93 for blood/urine, with the lowest being chloroform and the highest being bromoform. Both human and cow milk were tested, with similar results. The available samples of human milk may not fully account for differences in lipid content and possibly other factors that affect estimates of partition coefficients. Simultaneous measurements of milk and blood in exposed individuals are suggested to confirm laboratory results. Partition coefficients are predicted using the octanol-air partition coefficient, also measured in this study, and the octanol-water partition coefficient. Results are similar to literature estimates for liquid/air partitioning of chloroform and chlorodibromomethane, but they differ from predictions based on hydrophobicity and lipid content. High correlations between the derived partitioned coefficients and the molecular structure (number of Br atoms) and physical properties (molecular weight and boiling point) are found for these analogous chemicals. In humans, THMs are both stored and metabolized with relatively rapid clearance rates. The derived partition coefficients can help to interpret results of biological monitoring and predict the potential for the accumulation and transfer of chemicals, specifically by the application of physiologically-based pharmacokinetic models. THM exposures to potentially susceptible populations, e.g. nursing infants, can be predicted using either such models.

PCBs in air, soil and milk in industrialized and urban areas of KwaZulu-Natal, South Africa.

Information regarding polychlorinated biphenyls (PCBs) in environmental media in Africa is limited. This paper presents results of a monitoring program conducted in KwaZulu-Natal Province, South Africa designed to characterize levels, trends and sources of airborne PCBs. Particulate and vapor samples were sampled over the 2004-2005 period at three sites. The total PCB concentration averaged 128+/-47 pgm(-3), and levels were highest in winter. Tri- through hexa-congeners predominated, and the vapor fraction was predominant. Several tetra- through hexa-chlorinated congeners had levels comparable to those at urban sites in the northern hemisphere, but hepta- through deca-congeners resembled levels at background sites. PCB source areas, deduced using spatial and temporal patterns, compositional information and trajectory analyses, likely included local, regional and global sources. Soils at three rural sites showed high PCB concentrations, and milk from a local dairy showed PCB concentrations comparable to USA levels in year 2000.

HVAC Systems As Emission Sources Affecting Indoor Air Quality: A Critical Review

This study evaluates literature on heating, ventilating and air conditioning (HVAC) systems as contaminant emission sources that affect indoor air quality (IAQ). The various literature sources and methods for characterizing HVAC emission sources are reviewed. Characterization methods include in situ tests, longitudinal and cross-sectional studies, and laboratory studies. A critique of the literature reveals that few studies are well-controlled, comprehensive and quantitative. Significant gaps in the data are highlighted and procedures are suggested to improve the characterization of bioaerosol and VOC (volatile organic compound) emission sources. Several HVAC components are cited frequently as emission sources, and there is broad agreement regarding their significance. These sources include biological growth and bioaerosol generation in the presence of moisture provided by air washers and other recirculating water systems, or by poor control of humidity, badly designed humidifying systems, and inadequatel...