Abstract  Asthma occurs in more than 5% of the population in industrialized countries and is now characterized as a chronic inflammatory disease. The chronic aspiration of gastric fluid is considered by many investigators to be a primary inflammatory factor exacerbating or predisposing patients to asthma, with more than 50 medical papers per year linking asthma with gastroesophageal reflux disease (GERD), which can lead to aspiration events. However, the mechanisms involved in the inflammatory effects caused by gastric-fluid aspiration are not clear at the present time. The role of macrophages in the pathogenesis of disease seems likely given the involvement of those cells in a variety of chronic inflammatory diseases. To investigate the potential role of gastric fluid and the mechanisms potentially underlying chronic aspiration-associated pathogenesis, we examined the activation of murine macrophages (Raw 264.7 cell line) with gastric fluid. Inflammatory cytokine production and activation of the NF-[kappa]B signaling pathway were observed. Toll-like receptor (TLR)-4-dependent activation was observed under some conditions, indicating that bacterial components within the gastric fluid are involved in macrophage activation. Matrix metalloproteinase-9 (MMP-9) expression by macrophages was enhanced by gastric fluid, suggesting a potential mechanism by which remodeling of airways might be induced by gastric-fluid aspiration.

Abstract  Objectives First, we present a general analytical approach to estimating the association between medium-term changes in air pollution and health across small areas. As a specific illustration, we then applied the approach to data on London residents from a 4-year period to test whether reductions in traffic-related air pollution were associated with reductions in cardio-respiratory hospital admissions. Methods A binomial distribution was used to model change in admissions over time in each small area, which was measured as the proportion of admissions in 2003–2004 out of admissions over all study years (2001–2004). Annual average concentrations of nitrogen oxides (NOx) were modelled using an emissions-dispersion model. The association between change in NOx and change in hospital admissions was estimated using logistic regression and an instrumental variable approach. Results For some diagnostic groups, suggestive associations between reductions in NOx and reductions in admissions were observed, for example, OR=0.97 (95% CI 0.96 to 0.99) for an IQR decrease in NOx (3 μg/m3) and all respiratory admissions. Accounting for spatial dependence attenuated several of the associations; for respiratory admissions, the OR was 1.00 (95% CI 0.98 to 1.02), leaving only that for bronchiolitis significant (OR=0.91; 95% CI 0.84 to 0.99). In this particular illustration, the instrumental variable approach did not appear to add information. Conclusions In this illustration, there was relatively limited power to detect an association between changes in air pollution and hospital admissions over time. However, the analytical approach could deliver more robust estimates of the health effects of changes in air pollution in settings with greater spatial contrast in changes in air pollution over time.

Abstract  Indoor air quality has been recognised as a significant health, environment, and economic issue in many countries. Research findings have demonstrated that some air pollutants occur more frequently and at a higher concentration in indoor air than in outdoor air, including volatile organic compounds (VOCs). In this context, the indoor environment can be of crucial importance because modem society spends most of their time indoors, and exposure to VOCs may result in a spectrum of illnesses ranging from mild, such as irritation, to very severe effects, including cancer. These effects have been seen at very low levels of exposure in many epidemiological studies. In this review, we discuss the nature of the VOCs that are ubiquitous in indoor environment and the evidence for adverse health effects associated with exposure to some of these compounds.

Abstract  In recent decades the prevalence of asthma has been increasing in Western countries. Altered environment and lifestyle conditions have been implicated but the underlying mechanisms remain unclear. The Indoor Pollutants, Endotoxin, Allergens, Damp and Asthma (IPEADAM) study is a cross-sectional, case control study designed to analyse the home environments of 200 children in Manchester. In this paper the home concentrations and relationships to asthma development have been examined for a variety of indoor agents including environmental tobacco smoke (ETS), nitrogen dioxide (NO2), formaldehyde, volatile organic compounds (VOCs) and damp, which have been reported as potential factors in the development or the exacerbation of asthma. Levels of respirable particles and tobacco specific particles were found to be significantly higher in the homes with smokers present, but there were no differences in the levels of NO2, formaldehyde or VOCs. However, there were no significant differences in the levels of tobacco related pollutants in the homes of children with and without asthma. Similarly there were no statistically significant differences in the levels of NO2, formaldehyde, VOCs, temperature or relative humidity between the homes of children with and without asthma. This study has demonstrated that few differences exist between the home environments of English children, between 4-16 years of age, with asthma and those without the disease. The parameters examined in this study are unlikely to be related to the development of asthma. Avoidance of these pollutants may not be beneficial in preventing the development of asthma in this age group.

Abstract  BACKGROUND: Growing evidence indicates that ambient air pollution is associated with exacerbation of chronic diseases like chronic pulmonary disease. A prospective panel study was conducted to investigate short-term changes of blood markers of inflammation and coagulation in response to daily changes in air pollution in Erfurt, Germany. 12 clinical visits were scheduled and blood parameters were measured in 38 male patients with chronic pulmonary disease during winter 2001/2002. Additive mixed models with random patient intercept were applied, adjusting for trend, weekday, and meteorological parameters. Hourly data on ultrafine particles (UFP, 0.01-0.1 mum), accumulation mode particles (ACP, 0.1-1.0 mum), PM10 (particulate matter <10 mum in diameter), elemental (EC) and organic carbon (OC), gaseous pollutants (nitrogen monoxide [NO], nitrogen dioxide [NO2], carbon monoxide [CO], and sulphur dioxide [SO2]) were collected at a central monitoring site and meteorological data were received from an official network. For each person and visit the individual 24-hour average of pollutants immediately preceding the blood withdrawal (lag 0) up to day 5 (lag1-4) and 5-day running means were calculated. RESULTS: Increased levels of fibrinogen were observed for an increase in one interquartile range of UFP, PM10, EC, OC, CO, and NO revealing the strongest effect for lag 3. E-selectin increased in association with ACP and PM10 with a delay of one day. The ACP effect was also seen with the 5-day-mean. The pattern found for D-dimer was inconsistent. Prothrombin fragment 1+2 decreased with lag 4 consistently for all particulate pollutants. Von Willebrand factor antigen (vWF) showed a consistent decrease in association with almost all air pollutants with all lags except for lag 0. No associations were found for C-reactive protein, soluble intercellular adhesion molecule 1, serum amyloid A and factor VII. CONCLUSION: These results suggest that elevated concentrations of air pollution are associated with changes in some blood markers of inflammation and coagulation in patients with chronic pulmonary disease. The clinical implications of these findings need further investigation.

Abstract  In this article we discuss statistical techniques for modeling data from cohort studies that examine long-term effects of air pollution on children’s health by comparing data from multiple communities with a diverse pollution profile. Under a general multilevel modeling paradigm, we discuss models for different outcome types along with their connections to the generalized mixed effects models methodology. The model specifications include linear and flexible models for continuous lung function data, logistic and/or time-to-event models for symptoms data that account for misspecifications via hidden Markov models and Poisson models for school absence counts. The main aim of the modeling scheme is to be able to estimate effects at various levels (e.g., within subjects across time, within communities across subjects and between communities). We also discuss in detail various recurring issues such as ecologic bias, exposure measurement error, multicollinearity in multipollutant models, interrelationships between major endpoints and choice of appropriate exposure metrics. The key conceptual issues and recent methodologic advances are reviewed, with illustrative results from the Southern California Children’s Health Study, a 10-year study of the effects of air pollution on children’s respiratory health.

Abstract  An approach is developed and tested to extend discrete, source-based sensitivity results to provide a complete set of information for source-air quality impacts, including inversion of those results to develop receptor-oriented source-impact sensitivities. First, the decoupled direct sensitivity analysis method in 3D (DDM-3D) is used to calculate a finite number of forward sensitivities from discrete points. These results are then interpolated using tessellation to provide complete fields of forward, emissions-based sensitivities, i.e., how emissions in any one grid cell within the domain impact any other cell. Receptor-oriented sensitivities are then found by inverting the set of forward sensitivities and can be used to identify the area of influence (AOI). This economically provides results similar to what would be found using an adjoint model. The present approach is computationally less intensive than adjoint modeling for a large number of receptors, and provides both source-oriented and receptor-oriented pollutant response fields that can be used for air quality management and health impact analyses. The forward sensitivity interpolation procedure, as well as the receptor-oriented sensitivities, is evaluated using data withholding.

Abstract  In previous work, we showed that the intake fraction (iF) for nonreactive primary air pollutants was 20 times higher in central tendency for small-scale, urban-sited distributed electricity generation (DG) sources than for large-scale, central station (CS) power plants in California [Heath, G.A., Granvold, P.W., Hoats, A.S., Nazaroff, W.W., 2006. Intake fraction assessment of the air pollutant exposure implications of a shift toward distributed electricity generation. Atmospheric Environment 40, 7164-7177]. The present paper builds on that study, exploring pollutant- and technology-specific aspects of population inhalation exposure from electricity generation. We compare California's existing CS-based system to one that is more reliant on DG units sited in urban areas. We use Gaussian plume modeling and a GIS-based exposure analysis to assess 25 existing CSs and 11 DG sources hypothetically located in the downtowns of California's most populous cities. We consider population intake of three pollutantS-PM2.5, NOx and formaldehyde-directly emitted by five DG technologies-natural gas (NG)-fired turbines, NG internal combustion engines (ICE), NG microturbines, diesel ICEs, and fuel cells with on-site NG reformers. We also consider intake of these pollutants from existing CS facilities, most of which use large NG turbines, as well as from hypothetical facilities located at these same sites but meeting California's best-available control technology standards. After systematically exploring the sensitivity of iF to pollutant decay rate, the iFs for each of the three pollutants for all DG and CS cases are estimated. To efficiently compare the pollutant- and technology-specific exposure potential on an appropriate common basis, a new metric is introduced and evaluated: the intake-to-delivered-energy ratio (IDER). The IDER expresses the mass of pollutant inhaled by an exposed population owing to emissions from an electricity generation unit per quantity of electric energy delivered to the place of use. We find that the central tendency of IDER is much greater for almost every DG technology evaluated than for existing CS facilities in California. (C) 2007 Elsevier Ltd. All rights reserved.

Abstract  A modeling study was conducted on dispersion and dry deposition of ammonia taking one hog farm as a unit. The ammonia emissions used in this study were measured under our OPEN (Odor, Pathogens, and Emissions of Nitrogen) project over a waste lagoon and from hog barns. Meteorological data were also collected at the farm site. The actual layout of barns and lagoons on the farms was used to simulate dry deposition downwind of the farm. Dry deposition velocity, dispersion, and dry deposition of ammonia were studied over different seasons and under different stability conditions using the short-range dispersion/air quality model, AERMOD. Dry deposition velocities were highest under near-neutral conditions and lowest under stable conditions. The highest deposition at short range occurred under nighttime stable conditions and the lowest occurred during daytime unstable conditions. Significant differences in deposition over crop and grass surfaces were observed under stable conditions. [ABSTRACT FROM AUTHOR] Copyright of Journal of the Air & Waste Management Association (1995) is the property of Air & Waste Management Association and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts)

Abstract  Ordered mesoporous carbon supported MgO (Mg-OMC) materials were synthesized by the carbonization of sulfuric-acid-treated silica/triblock copolymer/sucrose/Mg(NO3)(2) composites. In the current approach, triblock copolymer P123 and sucrose were employed as both structure-directing agents for the self-assembly of rice husk ash silica solution and carbon precursor. Sulfuric acid was used to cross-link P123 and sucrose in the as-synthesized composites in order to improve the carbon yield. The synthesized Mg-OMC was characterized by X-ray diffraction, N-2 adsorption-desorption isotherm method, X-ray photoelectron spectroscopy, scanning electron microscope equipped with energy dispersive X-ray analysis and transmission electron microscopy. The thermal stability of Mg-OMC was verified by CO2-temperature programmed desorption, which confirmed the chemisorption of CO2 on MgO. The CO2 adsorption capacity of Mg-OMC-1 was observed to be 92 mg/g of sorbent which is comparable with that of the well established CO2 sorbents. (C) 2010 Elsevier Ltd. All rights reserved.

Abstract  Nanostructured porous tungsten oxide materials were synthesized by the means of electrochemical etching (anodization) of tungsten foils in aqueous NaF electrolyte. Formation of the sub-micrometer size mesoporous particles has been achieved by infiltrating the pores with water. The obtained colloidal anodic tungsten oxide dispersions have been used to fabricate resistive WO3 gas sensors by drop casting the sub-micrometer size mesoporous particles between Pt electrodes on Si/SiO2 substrate followed by calcination at 400 degrees C in air for 2 h. The synthesized WO3 films show slightly nonlinear current-voltage characteristics with strong thermally activated carrier transport behavior measured at temperatures between -20 degrees C and 280 degrees C. Gas response measurements carried out in CO, H-2, NO and O-2 analytes (concentration from 1 to 640 ppm) in air as well as in Ar buffers (O-2 only in Ar) exhibited a rapid change of sensor conductance for each gas and showed pronounced response towards H-2 and NO in Ar and air, respectively. The response of the sensors was dependent on temperature and yielded highest values between 170 degrees C and 220 degrees C. (C) 2010 Elsevier B.V. All rights reserved.

Abstract  [ 1] Recent decreases in nitrogen oxide (NOx = NO + NO2) emissions from eastern U. S. power plants and their effects on regional ozone are studied. Using the EPA 1999 National Emission Inventory as a reference emission data set, NOx and sulfur dioxide (SO2) emission rates at selected power plants are updated to their summer 2003 levels using Continuous Emission Monitoring System ( CEMS) measurements. The validity of the CEMS data is established by comparison to observations made on the NOAA WP-3 aircraft as part of the 2004 New England Air Quality Study. The impacts of power plant NOx emission decreases on O-3 are investigated using the WRF-Chem regional chemical forecast model. Summertime NOx emission rates decreased by approximately 50% between 1999 and 2003 at the subset of power plants studied. The impact of NOx emission reductions on ozone was moderate during summer 2004 because of relatively cool temperatures and frequent synoptic disturbances. Effects in individual plant plumes vary depending on the plant's NOx emission strength, the proximity of other NOx sources, and the availability of volatile organic compounds (VOCs) and sunlight. This study provides insight into the ozone changes that can be anticipated as power plant NOx emission reductions continue to be implemented throughout the United States.

Abstract  In occupational epidemiology, it is often possible to obtain repeated measurements of exposure from a sample of subjects (workers) who belong to exposure groups associated with different levels of exposure. Average exposures from a sample of workers can be assigned to all members of that group including those who are not sampled, leading to a group-based exposure assessment. We discuss how this group-based exposure assessment leads to approximate Berkson error model when the number of subjects with exposure measurements in each group is large, and how the error variance approximates the between-worker variability. Under the normality assumption of exposures and with moderately large number of workers in each group, there is attenuation in the estimate of the association parameter, the magnitude of which depends on the sizes of the between-worker variability and the true association parameter. Approximate equations for attenuation have been derived in logistic and Cox proportional-hazards models. These equations show that the attenuation in Cox proportional-hazards models is generally more severe than in logistic regression. Furthermore, when the between-worker variability is large, our simulation study found that the approximation by equation is poor for the Cox proportional-hazards model. If the number of subjects is small, the approximation does not hold for either model.

Abstract  Background: New approaches to link health surveillance data with environmental and population exposure information are needed to examine the health benefits of risk management decisions. Objective: We examined the feasibility of conducting a local assessment of the public health impacts of cumulative air pollution reduction activities from federal, state, local and voluntary actions in the City of New Haven, CT. Methods: Using a hybrid modeling approach that combines regional and local-scale air quality data, we estimated ambient concentrations for multiple air pollutants (e.g., PM2.5, NOx) for base year 2001 and projected emissions for 2010, 2020, and 2030. We assessed the feasibility of detecting health improvements in relation to air pollution reductions for 26 different pollutant/health outcome linkages using both sample size and exploratory epidemiological simulations to further inform decision-making needs. Results: Model projections suggested decreases (~10% to 60%) in pollutant concentrations, mainly due to decreases in pollutants from local sources between 2001 and 2010. Models indicated considerable spatial variability in the concentrations of most pollutants. Sample size analyses supported the feasibility of identifying linkages between reductions in NOx and improvements in all-cause mortality, prevalence of asthma in children and adults, and cardiovascular and respiratory hospitalizations. Conclusion: Substantial reductions in air pollution (e.g., ~60% shown for NOx) are needed to detect health impacts of environmental actions using traditional epidemiologic study designs in small communities like New Haven. In contrast, exploratory epidemiologic simulations suggest that it may be possible to demonstrate the health impacts of PM reductions by predicting intra-urban pollution gradients within New Haven using coupled models.

Abstract  Background: The link between concentrations of particulate matter and respiratory morbidity has been investigated in numerous studies. Objectives: The aim of this study was to analyze the role of different particle size fractions with respect to respiratory health in Beijing, China. Methods: Data on particle size distributions from 3 nm to 1 µm; PM10, NO2, and SO2 concentrations; and meteorological variables were collected daily during March 2004 to December 2006. Concurrently, daily counts of emergency room visits (ERV) for respiratory diseases were obtained from the Peking University Third Hospital. We estimated pollutant effects in single- and two-pollutant generalized additive models, controlling for meteorological and other time-varying covariates. Time-delayed associations were estimated using polynomial distributed lag, cumulative effects, and single lag models. Results: Associations of respiratory ERV with NO2 concentrations and 100 - 1000 nm particle number or surface area concentrations were of similar magnitude, i.e. ~ 5 % increase in respiratory emergency room visits with an interquartile range increase in air pollution concentration. In general, particles < 50 nm were not positively associated with ERV, whereas particles 50 - 100 nm were adversely associated with respiratory ERV, both being fractions of ultrafine particles. Effect estimates from two-pollutant models were most consistent for NO2. Conclusions: Present levels of air pollution in Beijing were adversely associated with respiratory ERV. NO2 concentrations seemed to be a better surrogate for evaluating overall respiratory health effects of ambient air pollution than PM10 or particle number concentrations in Beijing.

Abstract  BACKGROUND: Short-term changes in levels of fine ambient particulate matter (PM2.5) may increase the risk of acute ischemic stroke; however, results from prior studies have been inconsistent. We examined this hypothesis using data from a multicenter prospective stroke registry. METHODS: We analyzed data from 9202 patients hospitalized with acute ischemic stroke, having a documented date and time of stroke onset, and residing within 50 km of a PM2.5 monitor in 8 cities in Ontario, Canada. We evaluated the risk of ischemic stroke onset associated with PM2.5 in each city using a time-stratified case-crossover design, matching on day of week and time of day. We then combined these city-specific estimates using random-effects meta-analysis techniques. We examined whether the effects of PM2.5 differed across strata defined by patient characteristics and ischemic stroke etiology. RESULTS: Overall, PM2.5 was associated with a -0.7% change in ischemic stroke risk per 10-μg/m increase in PM2.5 (95% confidence interval = -6.3% to 5.1%). These overall negative results were robust to a number of sensitivity analyses. Among patients with diabetes mellitus, PM2.5 was associated with an 11% increase in ischemic stroke risk (1% to 22%). The association between PM2.5 and ischemic stroke risk varied according to stroke etiology, with the strongest associations observed for strokes due to large-artery atherosclerosis and small-vessel occlusion. CONCLUSIONS: These results do not support the hypothesis that short-term increases in PM2.5 levels are associated with ischemic stroke risk overall. However, specific patient subgroups may be at increased risk of particulate-related ischemic strokes.

Abstract  Air quality indices currently in use have been criticized because they do not capture additive effects of multiple pollutants, or reflect the apparent no-threshold concentration-response relationship between air pollution and health. We propose a new air quality health index (AQHI), constructed as the sum of excess mortality risk associated with individual pollutants from a time-series analysis of air pollution and mortality in Canadian cities, adjusted to a 0-10 scale, and calculated hourly on the basis of trailing 3-hr average pollutant concentrations. Extensive sensitivity analyses were conducted using alternative combinations of pollutants from single and multipollutant models. All formulations considered produced frequency distributions of the daily maximum AQHI that were right-skewed, with modal values of 3 or 4, and less than 10% of values at 7 or above on the 10-point scale. In the absence of a gold standard and given the uncertainty in how to best reflect the mix of pollutants, we recommend a formulation based on associations of nitrogen dioxide, ozone, and particulate matter of median aerodynamic diameter less than 2.5 μm with mortality from single-pollutant models. Further sensitivity analyses revealed good agreement of this formulation with others based on alternative sources of coefficients drawn from published studies of mortality and morbidity. These analyses provide evidence that the AQHI represents a valid approach to formulating an index with the objective of allowing people to judge the relative probability of experiencing adverse health effects from day to day. Together with health messages and a graphic display, the AQHI scale appears promising as an air quality risk communication tool. [ABSTRACT FROM AUTHOR] Copyright of Journal of the Air & Waste Management Association (1995) is the property of Air & Waste Management Association and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts)

Abstract  Pediatric asthma has many causes and can manifest differently in different children and at different times. Understanding the many factors related to the development and exacerbation of asthma is complicated by the complexity of the many environmental exposures related to asthma development and morbidity. Furthermore, the same environmental exposures that may cause increased symptoms at 1 point in time may be protective when the exposure occurs earlier or at high enough levels. We know that environmental exposures such as allergens, irritants, and pollutants are quite complex in their composition; further examination of this complexity may improve our understanding of this complex and highly prevalent disease. Pediatrics 2009; 123:S160-S167

Abstract  Indoor/outdoor measurements have been performed in the Oslo metropolitan area during summer and winter periods (2002-2003) at two different residential houses. The objective of the measurement study was to characterize, physically and chemically, the particulate matter (PM) and gaseous pollutants associated with actual human exposure in the selected places, and their indoor/outdoor relationship. In this paper, we focus on the PM measurements and examine the relationship between the indoor and outdoor PM concentrations taking into account the ventilation rate, indoor sources and meteorological conditions. The indoor/outdoor measurements indicate the important contribution of the outdoor air to the indoor air quality and the influence of specific indoor sources such as smoking and cooking to the concentration of PM inside houses. However, no specific correlation was found between the indoor/outdoor concentration ratio and the meteorological parameters.

Abstract  During two measurement campaigns, from August to September 2008 and 2009, we quantified the major ecosystem fluxes in a hemiboreal forest ecosystem in Jaryselja, Estonia. The main aim of this study was to separate the ecosystem flux components and gain insight into the performance of a multi-species multilayered tree stand. Carbon dioxide and water vapor fluxes were measured using the eddy covariance method above and below the canopy in conjunction with the microclimate. Leaf and soil contributions were quantified separately by cuvette and chamber measurements, including fluxes of carbon dioxide, water vapor, nitrogen oxides, nitrous oxide, methane, ozone, sulfur dioxide, and biogenic volatile organic compounds (isoprene and monoterpenes). The latter have been as well characterized for monoterpenes in detail. Based on measured atmospheric trace gas concentrations, the flux tower site can be characterized as remote and rural with low anthropogenic disturbances. Our results presented here encourage future experimental efforts to be directed towards year round integrated biosphere-atmosphere measurements and development of process-oriented models of forest-atmosphere exchange taking the special case of a multi-layered and multi-species tree stand into account. As climate change likely leads to spatial extension of hemiboreal forest ecosystems a deep understanding of the processes and interactions therein is needed to foster management and mitigation strategies. (C) 2010 Elsevier BM. All rights reserved.

Abstract  This study considered effects of reduced [O(3)] on wheat yield. Open-top chamber charcoal filtered air treatments were compared with non-filtered treatments for field-grown wheat. 30 experiments meeting requirements were found, representing nine countries in North America, Europe and Asia. 26 experiments reported improved yield and 4 experiments reduced yield by filtration, a significant positive effect. Average yield improvement was 9%. Average daytime [O(3)] was reduced by filtration from 35 to 13 nmol mol(-1). Filtration efficiency was 63% for O(3) and 56% for SO(2). For NO(x) it was observed that NO(2) was reduced and NO increased by filtration. Thus, filters convert NO(2) to NO. Most experiments reported low or very low [SO(2)] and [NO(x)]. Thus, O(3) can be concluded to be the main phytotoxic component in the experiments. Elevated [NO(2)] was observed in one experiment. The conclusion is that current [O(3)] over large parts of the world adversely affect wheat yield.

Abstract  We present the Chemistry of Atmosphere-Forest Exchange (CAFE) model, a vertically-resolved 1-D chemical transport model designed to probe the details of near-surface reactive gas exchange. CAFE integrates all key processes, including turbulent diffusion, emission, deposition and chemistry, throughout the forest canopy and mixed layer. CAFE utilizes the Master Chemical Mechanism (MCM) and is the first model of its kind to incorporate a suite of reactions for the oxidation of monoterpenes and sesquiterpenes, providing a more comprehensive description of the oxidative chemistry occurring within and above the forest. We use CAFE to simulate a young Ponderosa pine forest in the Sierra Nevada, CA. Utilizing meteorological constraints from the BEARPEX-2007 field campaign, we assess the sensitivity of modeled fluxes to parameterizations of diffusion, laminar sublayer resistance and radiation extinction. To characterize the general chemical environment of this forest, we also present modeled mixing ratio profiles of biogenic hydrocarbons, hydrogen oxides and reactive nitrogen. The vertical profiles of these species demonstrate a range of structures and gradients that reflect the interplay of physical and chemical processes within the forest canopy, which can influence net exchange.

Abstract  Hourly measurements of O(3), NO, NO(2), PAN, HNO(3) and NO(y) concentrations, and eddy-covariance fluxes of O(3) and NO(y) over a temperate deciduous forest from June to November, 2000 were used to evaluate the dry deposition velocities (V(d)) estimated by the WRF-Chem dry deposition module (WDDM), which adopted Wesely (1989) scheme for surface resistance (R(c)), and the Noah land surface model coupled with a photosynthesis-based Gas-exchange Evapotranspiration Model (Noah-GEM). Noah-GEM produced better V(d)(O(3)) variations due to its more realistically simulated stomata! resistance (R(s)) than WDDM. V(d)(O(3)) is very sensitive to the minimum canopy stomatal resistance (R(i)) which is specified for each seasonal category assigned in WDDM. Treating Sep-Oct as autumn in WDDM for this deciduous forest site caused a large underprediction of Vd(O(3)) due to the leafless assumption in 'autumn' seasonal category for which an infinite R(i) was assigned. Reducing R(i) to a value of 70 s m(-1), the same as the default value for the summer season category, the modeled and measured V(d)(O(3)) agreed reasonably well. HNO(3) was found to dominate the NO(y) flux during the measurement period: thus the modeled V(d)(NO(y)) was mainly controlled by the aerodynamic and quasi-laminar sublayer resistances (R(a) and R(b)), both being sensitive to the surface roughness length (z(0)). Using an aropriate value for z(0) (10% of canopy height), WDDM and Noah-GEM agreed well with the observed daytime V(d)(NO(y)). The differences in V(d)(HNO(3)) between WDDM and Noah-GEM were small due to the small differences in the calculated R(a) and R(b) between the two models: however, the differences in R(c) of NO(2) and PAN between the two models reached a factor of 1.1-1.5, which in turn caused a factor of 1.1-1.3 differences for V(d). Combining the measured concentrations and modeled V(d), NO(x), PAN and HNO(3) accounted for 19%, 4%, and 70% of the measured NO(y) fluxes, respectively. (C) 2011 Elsevier Ltd. All rights reserved.

Abstract  Background: A growing body of research suggests that prenatal exposure to air pollution may be harmful to fetal development. We assessed the association between exposure to air pollution during pregnancy and anthropometric measures at birth in four areas within the Spanish Children's Health and Environment (INMA) mother and child cohort study. Methods: Exposure to ambient nitrogen dioxide (NO2) and benzene was estimated for the residence of each woman (n = 2,337) for each trimester and for the entire pregnancy. Outcomes included birth weight, length, and head circumference. The association between residential outdoor air pollution exposure and birth outcomes was assessed with linear regression models controlled for potential confounders. We also performed sensitivity analyses for the subset of women who spent more time at home during pregnancy. Finally, we performed a combined analysis with meta-analysis techniques. Results: In the combined analysis, an increase of 10 µg/m3 in NO2 exposure during pregnancy was associated with a decrease in birth length of -0.9 mm [95% confidence interval (CI), -1.8 to -0.1 mm]. For the subset of women who spent ≥ 15 hr/day at home, the association was stronger (-0.16 mm; 95% CI, -0.27 to -0.04). For this same subset of women, a reduction of 22 g in birth weight was associated with each 10-µg/m3 increase in NO2 exposure in the second trimester (95% CI, -45.3 to 1.9). We observed no significant relationship between benzene levels and birth outcomes. Conclusions: NO2 exposure was associated with reductions in both length and weight at birth. This association was clearer for the subset of women who spent more time at home.

Abstract  Human exposure time-series modeling requires longitudinal time-activity diaries to evaluate the sequence of concentrations encountered, and hence, pollutant exposure for the simulated individuals. However, most of the available data on human activities are from cross-sectional surveys that typically sample 1 day per person. A procedure is needed for combining cross-sectional activity data into multiple-day (longitudinal) sequences that can capture day-to-day variability in human exposures. Properly accounting for intra- and interindividual variability in these sequences can have a significant effect on exposure estimates and on the resulting health risk assessments. This paper describes a new method of developing such longitudinal sequences, based on ranking 1-day activity diaries with respect to a user-chosen key variable. Two statistics, "D" and "A", are targeted. The D statistic reflects the relative importance of within- and between-person variance with respect to the key variable. The A statistic quantifies the day-to-day (lag-one) autocorrelation. The user selects appropriate target values for both D and A. The new method then stochastically assembles longitudinal diaries that collectively meet these targets. On the basis of numerous simulations, the D and A targets are closely attained for exposure analysis periods >30 days in duration, and reasonably well for shorter simulation periods. Longitudinal diary data from a field study suggest that D and A are stable over time, and perhaps over cohorts as well. The new method can be used with any cohort definitions and diary pool assignments, making it easily adaptable to most exposure models. Implementation of the new method in its basic form is described, and various extensions beyond the basic form are discussed.