BACKGROUND AND AIM: Previous studies investigating associations between prenatal air pollution and childhood behavior mainly focused on PM2.5, while little is known about the effect of air pollution mixtures and exposure timing throughout pregnancy. We used individual-level daily exposure data and implemented novel weighting approaches to assess effects of prenatal exposure to a mixture of seven air pollutants on behavioral outcomes in children from a Northeastern United States urban pregnancy cohort. METHODS: Participants included 234 full-term singleton children (≥37 weeks gestation). Children completed the Behavior Assessment System for Children 2nd Edition (BASC-2) at age 6.5±0.9 years. Daily exposure levels for nitrogen dioxide (NO₂), ozone (O₃), and constituents of fine particles [elemental carbon (EC), organic carbon (OC), nitrate (NO₃−), sulfate (SO₄²−), ammonium (NH₄+)] were estimated based on residential addresses using satellite-hybrid models and 3D chemical-transport models. Time-weighted exposure levels of the seven air pollutants in the mixture were estimated using Bayesian Kernel Machine Regression Distributed Lag Models. We subsequently used in multivariable linear regressions including time-weighted exposures for all pollutants in the mixture., adjusted for sex, maternal age, education, and temperature. Effect modification by sex was also examined. RESULTS: Participants were primarily Hispanic (59%) and Black (25%), with ≤12 years of education (68%). Time-weighted O₃ level (per one standard deviation increase) was associated with 4.77% increase in External Problems (95%CI= 0.7%–9%), 4.41% increase in Aggression (95%CI=0.9%–8.1%), 4.36% increase in Internal Problems (95%CI=0.5%–8.3%), and 4.18% increase in Anxiety (95%CI=0.1%–8.4%). When stratified by sex, these associations were only significant in boys. Time-weighted OC level was significantly associated with Internal Problems in girls only (4.6% increase, 95%CI=1.7%–7.7%). CONCLUSIONS: In a prenatal air pollution mixture, ozone is associated with child behavioral problems, and the association is specific to sex and measured outcome scale. KEYWORDS: mixture, air pollution, prenatal, children behavior

BACKGROUND AND AIM: Exposure to diesel exhaust (DE) has been associated with adverse respiratory health outcomes and bus drivers could be at significant risk. We leveraged exposure data collected from real-time personal monitoring and geospatial location information to identify the factors influencing DE exposure in New York bus drivers. METHODS: DE exposure was estimated via black carbon (BC; a component of DE) measurements recorded using a micro-Aethalometer (microAeth®Model-AE51) every minute over six 24-hour periods in four bus drivers during September-October 2014. Driving routes originated from two Westchester bus depots and traversed lower Westchester. Each driver's location was continuously recorded every minute using a global positioning system (GPS) device. Information on fuel type, smoking status, worker activities, and meteorological variables were collected. Road density indices were calculated based on an 100-meter buffer. We performed multivariable-adjusted regression models to assess the factors associated with BC levels. RESULTS: BC data were collected for a total of 2682 working minutes and 4328 non-working minutes. Overall median BC level was 578 ng/m3 (IQR: 189-1487 ng/m3) [working hours: 1166 (612-2168) ng/m3; non-working hours: 351 (132-860) ng/m3]. Multivariable-adjusted models predicted that compared to times working in office, workers were on average exposed to an additional 1403.5 ng/m3 and 2150.4 ng/m3 of BC when they were in the depot yard and driving the bus, respectively. Driving a diesel-powered vehicle was associated with 2.7-fold increase in BC levels compared to gasoline-powered. For every 10% increase in the sum of road length index, BC level increased by 19% (95%CI=15-24%). Further, for every 10% increase in average speed, BC level increased by 20% (95%CI=17-23%). CONCLUSIONS: Driving a diesel-powered vehicle presented significantly more BC exposure comparing to gasoline-powered vehicle. Roadway density and driving speed contributed to elevated BC levels. KEYWORDS:diesel, transportation, bus driver, occupational exposure

INTRODUCTION:Prenatal exposure to fine particulate matter air pollution (PM2.5) is an important, under-studied risk factor for neurodevelopmental dysfunction. We describe the relationships between prenatal PM2.5 exposure and vigilance and inhibitory control, executive functions related to multiple health outcomes in Mexico City children. METHODS:We studied 320 children enrolled in Programming Research in Obesity, GRowth, Environment and Social Stressors, a longitudinal birth cohort study in Mexico City. We used a spatio-temporal model to estimate daily prenatal PM2.5 exposure at each participant's residential address. At age 9-10 years, children performed three Go/No-Go tasks, which measure vigilance and inhibitory control ability. We used Latent class analysis (LCA) to classify performance into subgroups that reflected neurocognitive performance and applied multivariate regression and distributed lag regression modeling (DLM) to test overall and time-dependent associations between prenatal PM2.5 exposure and Go/No-Go performance. RESULTS:LCA detected two Go/No-Go phenotypes: high performers (Class 1) and low performers (Class 2). Predicting odds of Class 1 vs Class 2 membership based on prenatal PM2.5 exposure timing, logistic regression modeling showed that average prenatal PM2.5 exposure in the second and third trimesters correlated with increased odds of membership in low-performance Class 2 (OR = 1.59 (1.16, 2.17), p = 0.004). Additionally, DLM analysis identified a critical window consisting of gestational days 103-268 (second and third trimesters) in which prenatal PM2.5 exposure predicted poorer Go/No-Go performance. DISCUSSION:Increased prenatal PM2.5 exposure predicted decreased vigilance and inhibitory control at age 9-10 years. These findings highlight the second and third trimesters of gestation as critical windows of PM2.5 exposure for the development of vigilance and inhibitory control in preadolescent children. Because childhood development of vigilance and inhibitory control informs behavior, academic performance, and self-regulation into adulthood, these results may help to describe the relationship of prenatal PM2.5 exposure to long-term health and psychosocial outcomes. The integrative methodology of this study also contributes to a shift towards more holistic analysis.

Background: Temperament is a psychological construct that reflects both personality and an infant's reaction to social stimuli. It can be assessed early in life and is stable over time Temperament predicts many later life behaviors and illnesses, including impulsivity, emotional regulation and obesity. Early life exposure to neurotoxicants often results in developmental deficits in attention, social function, and IQ, but environmental predictors of infant temperament are largely unknown. We propose that prenatal exposure to both chemical and non-chemical environmental toxicants impacts the development of temperament, which can itself be used as a marker of risk for maladaptive neurobehavior in later life.In this study, we assessed associations among prenatal and early life exposure to lead, mercury, poverty, maternal depression and toddler temperament.Methods: A prospective cohort of women living in the Mexico City area were followed longitudinally beginning in the second trimester of pregnancy. Prenatal exposure to lead (blood, bone), mercury, and maternal depression were assessed repeatedly and the Toddler Temperament Scale (TTS) was completed when the child was 24 months old. The association between each measure of prenatal exposure and performance on individual TTS subscales was evaluated by multivariable linear regression. Latent profile analysis was used to classify subjects by TTS performance. Multinomial regression models were used to estimate the prospective association between prenatal exposures and TTS performance.Results: 500 mother-child pairs completed the TTS and had complete data on exposures and covariates. Three latent profiles were identified and categorized as predominantly difficult, intermediate, or easy temperament. Prenatal exposure to maternal depression predicted increasing probability of difficult toddler temperament. Maternal bone lead, a marker of cumulative exposure, also predicted difficult temperament. Prenatal lead exposure modified this association, suggesting that joint exposure in pregnancy to both was most toxic.Conclusions: Maternal depression predicts difficult temperament and concurrent prenatal exposure to maternal depression and lead predicts a more difficult temperament phenotype in 2 year olds. The role of temperament as an intermediate variable in the path from prenatal exposures to neurobehavioral deficits and other health effects deserves further study.

Background Disrupted maternal prenatal cortisol production influences offspring development. Factors influencing the hypothalamic-pituitary-adrenal axis include social (e.g., stressful life events) and physical/chemical (e.g., toxic metals) pollutants. Mercury (Hg) is a common contaminant of fish and exposure is widespread in the US. No prior study has examined the joint associations of stress and mercury with maternal cortisol profiles in pregnancy. Objectives To investigate potential synergistic influences of prenatal stress and Hg exposures on diurnal cortisol in pregnant women. Methods Analyses included 732 women (aged 27.4 ± 5.6 years) from a Mexico City pregnancy cohort. Participants collected saliva samples on two consecutive days (mean 19.52 ± 3.00 weeks gestation) and reported life stressors over the past 6 months. Hg was assessed in toe nail clippings collected during pregnancy. Results There were no main effects of Hg or psychosocial stress exposure on diurnal cortisol ( p s > .20) but strong evidence of interaction effects on cortisol slope (interaction B = .006, SE = .003, p = .034) and cortisol at times 1 and 2 (interaction B = -.071, SE = .028, p = .013; B = -.078, SE = .032, p = .014). Women above the median for Hg and psychosocial stress exposure experienced a blunted morning cortisol response compared to women exposed to higher stress but lower Hg levels. Conclusions Social and physical environmental factors interact to alter aspects of maternal diurnal cortisol during pregnancy. Research focusing solely on either domain may miss synergistic influences with potentially important consequences to the offspring.

Ultrafine particles (UFP) have complex spatial and temporal patterns that can be difficult to characterize, especially in areas with multiple source types. In this study, we utilized mobile monitoring and statistical modeling techniques to determine the contributions of both roadways and aircraft to spatial and temporal patterns of UFP in the communities surrounding an airport. A mobile monitoring campaign was conducted in five residential areas surrounding T.F. Green International Airport (Warwick, RI, USA) for one week in both spring and summer of 2008. Monitoring equipment and geographical positioning system (GPS) instruments were carried following scripted walking routes created to provide broad spatial coverage while recognizing the complexities of simultaneous spatial and temporal heterogeneity. Autoregressive integrated moving average models (ARIMA) were used to predict UFP concentrations as a function of distance from roadway, landing and take-off (LTO) activity, and meteorology. We found that distance to the nearest Class 2 roadway (highways and connector roads) was inversely associated with UFP concentrations in all neighborhoods. Departures and arrivals on a major runway had a significant influence on UFP concentrations in a neighborhood proximate to the end of the runway, with a limited influence elsewhere. Spatial patterns of regression model residuals indicate that spatial heterogeneity was partially explained by traffic and LTO terms, but with evidence that other factors may be contributing to elevated UFP close to the airport grounds. Regression model estimates indicate that mean traffic contributions exceed mean LTO contributions, but LTO activity can dominate the contribution during some minutes. Our combination of monitoring and statistical modeling techniques demonstrated contributions from major surrounding runways and LTO activity to UFP concentrations near a mid-sized airport, providing a methodology for source attribution within a community with multiple distinct sources. (C) 2014 Elsevier Ltd. All rights reserved.

Following Hurricane Sandy, which hit New York City and New Jersey in October 2012, industrial hygienists from the Mount Sinai and Belleview/New York University occupational medicine clinics conducted monitoring for diesel exhaust and silica in lower Manhattan and Rockaway Peninsula. Average daytime elemental carbon levels at three stations in lower Manhattan on December 4, 2012, ranged from 9 to18 μg/m3. Sub-micron particle counts at various times on the same day were over 200,000 particles per cubic centimeter on many streets in lower Manhattan. In Rockaway Peninsula on December 12, 2012, all average daytime elemental carbon levels were below a detection limit of approximately 7 μg/m3. The average daytime crystalline silica dust concentration was below detection at two sites on Rockaway Peninsula, and was 0.015 mg/m3 quartz where sand was being replaced on the beach. The daily average levels of elemental carbon and airborne particulates that we measured are in the range of levels that have been found to cause respiratory effects in sensitive subpopulations like asthmatic patients after 2 hr of exposure. Control of exposure to diesel exhaust must be considered following natural disasters where diesel-powered equipment is used in cleanup and recovery. Although peak silica exposures were not likely captured in this study, but were reported by a government agency to have exceeded recommended guidelines for at least one cleanup worker, we recommend further study of silica exposures when debris removal operations or traffic create visible levels of suspended dust from soil or sand.

Introduction: Preterm infants admitted to the neonatal intensive care unit (NICU) are exposed to the chemical-laden hospital environment during a developmentally sensitive time period. Epidemiologic studies show an association between in utero exposure to common organic chemicals and suboptimal intrauterine growth. Animal studies show an association between exposure to organic chemicals and poor growth in infancy. Hypothesis: Environmental chemical exposure in the NICU is associated with poor growth velocity during the NICU hospitalization. Method: We conducted a pilot prospective observational study of 20 preterm infants admitted to a tertiary care NICU. Data on 61 more subjects are pending analyses. We collected serial urine specimens and compared biomarkers of 25 organic chemicals to growth parameters from birth to discharge (22-131days, median 49). We fitted a multivariable-adjusted functional mixed model with penalized splines for each chemical to identify the effect on growth during the NICU hospitalization. Result: Biomarkers of methyl-paraben and monoethyl phthalate were inversely associated with weight gain. This effect was seen even at low urinary biomarker levels (median (ng/mL) = 14.98; 11.52). As with nutritional growth restriction, height and head circumference were not impacted. Conclusion: Our findings indicate an inverse association between phthalate and paraben exposure and growth in hospitalized preterm neonates. As weight gain during infancy is an important predictor of neurodevelopmental outcome, these findings have potential implications to NICU care.

Background: While commercial aircraft are known sources of ultrafine particulate matter (UFP), the relationship between airport activity and local real-time UFP concentrations has not been quantified. Understanding these associations will facilitate interpretation of the exposure and health risk implications of UFP related to aviation emissions.Objectives: We used time-resolved UFP data along with flight activity and meteorological information to determine the contributions of aircraft departures and arrivals to UFP concentrations.Methods: Aircraft flight activity and near-field continuous UFP concentrations (>= 6 nm) were measured at five monitoring sites over a 42-day field campaign at Los Angeles International Airport (LAX). We developed regression models of UFP concentrations as a function of time-lagged landing and take-off operations (LTO) activity, in the form of arrivals or departures weighted by engine-specific estimates of fuel consumption.Results: Our regression models demonstrate a strong association between departures and elevated total UFP concentrations at the end of the departure runway, with diminishing magnitude and time-lagged impacts with distance from the source. LTD activity contributed a median (95th, 99th percentile) UFP concentration of approximately 150,000 particles/cm(3) (2,000,000, 7,100,000) at a monitor at the end of the departure runway, versus 19,000 particles/cm(3) (80,000, 140,000), and 17,000 particles/cm(3) (50,000, 72,000) for monitors 250 m and 500 m further downwind, respectively.Conclusions: We demonstrated significant contributions from aircraft departure activities to UFP concentrations in close proximity to departure runways, with evidence of rapid plume evolution in the near field. Our methods can inform source attribution and interpretation of dispersion modeling outputs. (C) 2012 Elsevier B.V. All rights reserved.

This study was conducted to evaluate the effects of transported Asian dust and other environmental parameters on the levels and compositions of ambient fungi in the atmosphere of northern Taiwan. We monitored Asian dust events in Taipei County, Taiwan from January 2003 to June 2004. We used duplicate Burkard portable air samplers to collect ambient fungi before, during, and after dust events. Six transported Asian dust events were monitored during the study period. Elevated concentrations of Aspergillus (A. niger, specifically), Coelomycetes, Rhinocladiella, Sporothrix and Verticillium were noted (p < 0.05) during Asian dust periods. Botryosporium and Trichothecium were only recovered during dust event days. Multiple regression analysis showed that fungal levels were positively associated with temperature, wind speed, rainfall, non-methane hydrocarbons and particulates with aerodynamic diameters ≤10 μm (PM(10)), and negatively correlated with relative humidity and ozone. Our results demonstrated that Asian dust events affected ambient fungal concentrations and compositions in northern Taiwan. Ambient fungi also had complex dynamics with air pollutants and meteorological factors. Future studies should explore the health impacts of ambient fungi during Asian dust events, adjusting for the synergistic/antagonistic effects of weather and air pollutants.

Aircraft contribute to emissions of ultrafine particulate matter (UFP) and other air pollutants, with corresponding impacts on community-level exposures near active airports. However, it is challenging to isolate the contribution of aircraft from local road traffic and other nearby combustion sources. In this study, we used high-resolution monitoring and flight activity data to quantify contributions from landing and take-off operations (LTO) to UFP concentrations. UFP concentrations were monitored with 1-min resolution at four monitoring sites surrounding T.F. Green Airport in Warwick, RI, in three one-week campaigns across different seasons in 2007 and 2008. Along with pollutant monitoring, wind data were collected and runway-specific LTO data were obtained from airport officials. We developed regression models in which wind speed and direction were included as a nonparametric smooth spatial term using thin-plate splines applied to wind velocity vectors and fitted using linear mixed models. To better pinpoint the timing in the LTO cycle most contributing to elevated concentrations, we used regression models with lag terms for flight activity (ranging from 5 min before to 5 min after the departure or arrival). Results suggest positive associations between UFP concentrations and LTO activities, especially for departures when an aircraft moves near or passes a monitoring site. Departures of jet engine aircrafts on a runway proximate to one of the monitors have a maximal impact 1 min prior to take-off, with median absolute contributions during those minutes of 7400 particles cm(-3) (range: 1100-70,000 particles cm(-3)). Across all observations, our models indicate median (95th, 99th percentile) percent contribution for all LTO activities of 9.8% (54%, 72%) and 6.6% (39%, 55%) for the two sites proximate to the airport's principal runway, and 4.7% (24%, 36%) and 1.8% (22%, 31%) for the remaining two sites. Our analysis illustrates the complexity of aviation impacts on local air quality and allows for quantification of the marginal contribution of LTO activity relative to other nearby sources. (C) 2011 Elsevier Ltd. All rights reserved.

PP-30-044 Background/Aims: Airport activities can potentially contribute to pollutant levels in nearby communities, but it is challenging to isolate the contributions of aircraft emissions from other sources near airports. As part of the Air Quality and Source Apportionment Study (AQSAS), ambient air pollutant and meteorological data were collected for 42 days during July and August of 2008 at fixed sites surrounding Los Angeles International Airport (LAX). In this analysis, we present the results of regression modeling that examines the association between one-minute average size-binned ultrafine particle concentrations and runway-specific Landing and Take-off (LTO) operations data and meteorology. Methods: In our regression models, wind speed and direction were included as a nonparametric smooth spatial term, using thin-plate splines applied to wind velocity vectors and fitted using linear mixed models. To better pinpoint the timing in the LTO cycle most contributing to elevated concentrations, we used distributed lag models for flight activity, ranging from 5 minutes before to 5 minutes after take-off or landing. Given the short-term measurements, we account for temporal autocorrelation by computing standard errors using a moving-block bootstrap. Results: Generalized additive models for wind speed and direction suggest that ultrafine particle levels are associated with airport activities and local traffic sources, with a significant effect of wind direction only given high wind speeds. Model predictors varied significantly by size fraction, with smaller particle sizes demonstrating a greater signal from airport sources and larger particle sizes demonstrating a greater signal from local traffic. Distributed lag modeling suggests that departures contribute more significantly to ultrafine particle concentrations than arrivals, with the time patterns of contributions varying across monitors in a manner consistent with taxiways and flight paths. Conclusion: Our analytical approach allows for an enhanced understanding of ultrafine particle contributions from both aircraft and other sources proximate to large airports.

Understanding the impact of aviation emissions on air quality is becoming more important due to the projected growth in aviation transport and decrease in emissions from other anthropogenic sources. Atmospheric chemistry-transport models are often used to determine the marginal impact of emissions on air quality and public health, but the uncertainties related to modeling assumptions are rarely formally characterized from the perspective of public health impact calculations. In this study, we estimate the incremental contribution of commercial aviation emissions to air quality near three U.S. airports - Atlanta Hartsfield, Chicago O'Hare, and Providence T.F. Green - using the Community Multiscale Air Quality Model (CMAQ), a comprehensive chemistry-transport air quality model. To evaluate the significance of model resolution and geographic scales of influence, we ran a one-atmosphere version of CMAQ (with air toxics) at 36- and 12-km resolutions, and calculated the total population exposure per unit emissions at various distances from each airport. Total population exposure per unit emissions was systematically higher for air toxics with increased model grid resolution, and the distance at which most of the population exposure was estimated varied by compound and airport. A 108 x 108 km domain centered on the airport captured most population exposure for reactive gases (e.g., formaldehyde) at airports with high nearby population density, but more than half of the fine particulate matter (PM2 (5)) exposure occurred outside of a 324 x 324 km domain centered on the airport, given contributions from secondary formation. Our findings provide insight about the model resolution and spatial scales necessary for population risk assessment from airports and other combustion sources, and demonstrate the robustness of risk-based prioritization across multiple grid resolutions.

BACKGROUND:There is growing concern in communities surrounding airports regarding the contribution of various emission sources (such as aircraft and ground support equipment) to nearby ambient concentrations. We used extensive monitoring of nitrogen dioxide (NO2) in neighborhoods surrounding T.F. Green Airport in Warwick, RI, and land-use regression (LUR) modeling techniques to determine the impact of proximity to the airport and local traffic on these concentrations.METHODS:Palmes diffusion tube samplers were deployed along the airport's fence line and within surrounding neighborhoods for one to two weeks. In total, 644 measurements were collected over three sampling campaigns (October 2007, March 2008 and June 2008) and each sampling location was geocoded. GIS-based variables were created as proxies for local traffic and airport activity. A forward stepwise regression methodology was employed to create general linear models (GLMs) of NO2 variability near the airport. The effect of local meteorology on associations with GIS-based variables was also explored.RESULTS:Higher concentrations of NO2 were seen near the airport terminal, entrance roads to the terminal, and near major roads, with qualitatively consistent spatial patterns between seasons. In our final multivariate model (R2 = 0.32), the local influences of highways and arterial/collector roads were statistically significant, as were local traffic density and distance to the airport terminal (all p < 0.001). Local meteorology did not significantly affect associations with principal GIS variables, and the regression model structure was robust to various model-building approaches.CONCLUSION:Our study has shown that there are clear local variations in NO2 in the neighborhoods that surround an urban airport, which are spatially consistent across seasons. LUR modeling demonstrated a strong influence of local traffic, except the smallest roads that predominate in residential areas, as well as proximity to the airport terminal.

PP-30-019 Background/Aims: Previous studies have demonstrated significant contributions from aircraft to ultrafine particle counts near airports, but studies to date have not characterized spatial patterns in residential settings near airports and have not formally isolated the contribution of aircraft from other local sources. In this study, our objective was to determine the contribution of landing and takeoff (LTO) activity to concentrations of ultrafine particles as well as fine particulate matter (PM2.5) near TF Green Airport in Warwick, RI. Methods: A mobile monitoring protocol was implemented in 2 one-week campaigns in the spring and summer of 2008. Field teams were outfitted with backpacks containing water-based condensation particle counters to measure ultrafine particle levels, continuous monitors for PM2.5, and a GPS. Mobile sampling routes captured neighborhoods in all compass directions and were implemented to ensure sufficient spatiotemporal coverage. Regression models included as predictors of concentrations meteorological characteristics, source terms, and distance variables. To better pinpoint the timing in the LTO cycle most contributing to elevated concentrations, and to capture variability across aircraft and the spatiotemporal complexity of our data, we used distributed lag models for flight activity and incorporated emissions proxies for all individual aircraft. Results: Results suggest significant positive associations between ultrafine particle concentrations and both departures and arrivals, with departures having larger effects and the distributed lag modeling indicating the strongest association with predeparture taxing and the take-off process. Causal linkages with the LTO cycle were further enhanced by generalized additive models for wind speed and direction, which demonstrate an enhanced signal from LTO activities at higher wind speeds with a greater indication of local traffic contributions at low wind speeds. Conclusion: Our analysis allows for quantification of the marginal contribution of airport sources and characterization of spatiotemporal concentration patterns, providing insight for urban communities regarding the impact of airport activities on local air quality.

This study was conducted to investigate the temporal and spatial distributions, compositions, and determinants of ambient aeroallergens in Taipei, Taiwan, a subtropical metropolis. We monitored ambient culturable fungi in Shin-Jhuang City, an urban area, and Shi-Men Township, a rural area, in Taipei metropolis from 2003 to 2004. We collected ambient fungi in the last week of every month during the study period, using duplicate Burkard portable samplers and Malt Extract Agar. The median concentration of total fungi was 1339 colony-forming unitsm−3 of air over the study period. The most prevalent fungi were non-sporulating fungi, Cladosporium, Penicillium, Curvularia and Aspergillus at both sites. Airborne fungal concentrations and diversity of fungal species were generally higher in urban than in rural areas. Most fungal taxa had significant seasonal variations, with higher levels in summer. Multivariate analyses showed that the levels of ambient fungi were associated positively with temperature, but negatively with ozone and several other air pollutants. Relative humidity also had a significant non-linear relationship with ambient fungal levels. We concluded that the concentrations and the compositions of ambient fungi are diverse in urban and rural areas in the subtropical region. High ambient fungal levels were related to an urban environment and environmental conditions of high temperature and low ozone levels.

Characteristics and determinants of ambient aeroallergens are of much concern in recent years because of the apparent health impacts of allergens. Yet relatively little is known about the complex behaviors of ambient aeroallergens. To address this issue, we monitored ambient fungal spores in Hualien, Taiwan from 1993–1996 to examine the compositions and temporal variations of fungi, and to evaluate possible determinants. We used a Burkard seven-day volumetric spore trap to collect daily fungal spores. Air pollutants, meteorological factors, and Asian dust events were included in the statistical analyses to predict fungal levels. We found that the most dominant fungal categories were ascospores, followed by Cladosporium and Aspergillus/Penicillium. The majority of the fungal categories had significant diurnal and seasonal variations. Total fungi, Cladosporium, Ganoderma, Arthrinium/Papularia, Cercospora, Periconia, Alternaria, Botrytis, and PM10 had significantly higher concentrations (p<0.05) during the period affected by Asian dust events. In multiple regression models, we found that temperature was consistently and positively associated with fungal concentrations. Other factors correlated with fungal concentrations included ozone, particulate matters with an aerodynamic diameter less than 10 μm (PM10), relative humidity, rainfall, atmospheric pressure, total hydrocarbons, carbon monoxide, nitrogen dioxide, and sulfur dioxide. Most of the fungal categories had higher levels in 1994 than in 1995–96, probably due to urbanization of the study area. In this study, we demonstrated complicated interrelationships between fungi and air pollution/meteorological factors. In addition, long-range transport of air pollutants contributed significantly to local aeroallergen levels. Future studies should examine the health impacts of aeroallergens, as well as the synergistic/antagonistic effects of weather, and local and global-scale air pollutions.