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Background: Asthma is the most common chronic allergic disease in children; it affects more than 300 million people worldwide. Information on the association between exposure to ambient heavy metals and incidence of pediatric asthma is limited., Objective: We sought to evaluate the effects of heavy metals during pregnancy and infancy periods with asthma and identify a sensitive time window, clarifying the effect of ambient heavy metals on lung development., Methods: A total of 171,281 children, who were born from 2004 to 2011 in Taichung City, were followed until 2014. Concentrations of ambient heavy metals such as arsenic (As), cadmium (Cd), mercury (Hg), and lead (Pb) were obtained from the Weather Research and Forecasting/Chem model, considering the top 75 emission sources in Taiwan. The distributed lag nonlinear model was used to investigate the relationship between combined exposure to heavy metals in 2.5 μm particulate matter and asthma in pregnant women and 1-year-old infants., Results: We identified 31,277 new asthma cases from the birth cohort. After adjustment for socioeconomic status, maternal age, maternal atopy, maternal anemia, and maternal kidney disease, distributed lag nonlinear model results revealed positive associations of asthma with exposure to Pb during gestational weeks 1 to 14 and 21 to 40, and 1 to 3 weeks after birth. Regarding the sensitivity analyses, coexposure to Pb and As, coexposure to Pb and Cd, and coexposure to Pb and Hg were positively associated with asthma onset as well., Conclusions: Our study suggested that combined exposure to Pb with As, Cd, and Hg during early and late gestational weeks was associated with the incidence of pediatric asthma., (Copyright © 2020 American Academy of Allergy, Asthma & Immunology. Published by Elsevier Inc. All rights reserved.)

Background: Evidence of the effects of long-term exposure to fine particulate matter (PM 2.5 ) air pollution on the development of dyslipidaemia is limited. This study aimed to investigate the association between long-term exposure to ambient PM 2.5 and incident dyslipidaemia in a large cohort., Methods: We studied 66,702 participants aged ≥18 years belonging to a cohort from a standard medical examination programme conducted in Taiwan between 2001 and 2014. The PM 2.5 concentration at each participant's address was estimated using a satellite-based spatiotemporal model at a high resolution (1 km 2 ). A time-varying Cox regression model was used to examine the association between long-term exposure to ambient PM 2.5 and the development of dyslipidaemia. Additionally, sensitivity analyses were conducted to examine the stability of these associations., Results: Compared with participants exposed to the 1st tertile of PM 2.5 , participants exposed to the 2nd and 3rd tertiles of PM 2.5 had respective hazard ratios of 1.02 [95% confidence interval (CI): 0.98-1.06] and 1.08 (95%CI: 1.04-1.13) for incident dyslipidaemia. Sensitivity analyses generally yielded similar results., Conclusion: Long-term exposure to ambient PM 2.5 is associated with a higher risk of dyslipidaemia. Global strategies for reducing air pollution are needed to prevent the development of dyslipidaemia., (Copyright © 2019 Elsevier Inc. All rights reserved.)

Aims/hypothesis: Information on the associations of long-term exposure to fine particulate matter (with an aerodynamic diameter less than 2.5 μm; PM 2.5 ) with the development of type 2 diabetes is scarce, especially for south-east Asia, where most countries are experiencing serious air pollution. This study aimed to investigate the long-term effects of exposure to ambient PM 2.5 on the incidence of type 2 diabetes in a population of Taiwanese adults., Methods: A total of 147,908 participants without diabetes, at least 18 years of age, were recruited in a standard medical examination programme between 2001 and 2014. They were encouraged to take medical examinations periodically and underwent at least two measurements of fasting plasma glucose (FPG). Incident type 2 diabetes was identified as FPG ≥7 mmol/l or self-reported physician-diagnosed diabetes in the subsequent medical visits. The PM 2.5 concentration at each participant's address was estimated using a satellite-based spatiotemporal model with a resolution of 1 × 1 km 2 . The 2 year average of PM 2.5 concentrations (i.e. the year of and the year before the medical examination) was treated as an indicator of long-term exposure to ambient PM 2.5 air pollution. We performed Cox regression models with time-dependent covariates to analyse the long-term effects of exposure to PM 2.5 on the incidence of type 2 diabetes. A wide range of covariates were introduced in the models to control for potential effects, including age, sex, education, season, year, smoking status, alcohol drinking, physical activity, vegetable intake, fruit intake, occupational exposure, BMI, hypertension and dyslipidaemia (all were treated as time-dependent covariates except for sex)., Results: Compared with the participants exposed to the first quartile of ambient PM 2.5 , participants exposed to the second, third and fourth quartiles of ambient PM 2.5 had HRs of 1.28 (95% CI 1.18, 1.39), 1.27 (95% CI 1.17, 1.38) and 1.16 (95% CI 1.07, 1.26), respectively, for the incidence of type 2 diabetes. Participants who drank occasionally or regularly (more than once per week) or who had a lower BMI (<23 kg/m 2 ) were more sensitive to the long-term effects of exposure to ambient PM 2.5 ., Conclusions/interpretation: Long-term exposure to ambient PM 2.5 appears to be associated with a higher risk of developing type 2 diabetes in this Asian population experiencing high levels of air pollution.

Unlabelled: There are four types of PM10 (particulate matter with an aerodynamic diameter <10 microm) episodes that occur frequently in central Taiwan: long-range transport with dust storms (DS), long-range transport with frontal pollution (FP), river dust (RD), and stagnant weather (SW). During the periods of the four episodes, poor visibility usually results. Multiple linear regression was applied to visibility using eight potential influential variables (temperature, relative humidity, wind speed, PM2.5, PM2.5-10, SO2, NO2, and NO) as independent variables. Of the eight variables, PM2.5 showed the greatest explainable percentage of about 48.6% and 58.1% for Taichung and Wuchi stations, respectively. This suggested that PM2.5 was the most important contributor to reduced visibility. Compared with other type of episodes, the aerosols tended to be offine size during the SWepisodes. This is the main reason that the poorest visibility occurred during the SWepisodes. Good correlation between visibility and secondary inorganic salts (NH4+, NO3, and SO4(2-)) were found at Taichung station (r = 0.71) and Wuchi station (r = 0.81), suggesting that secondary inorganic salts did contribute significantly to the degradation ofvisibility. The visibility degradation due to the effects ofNO3- was much higher than that due to SO4(2-) and NH4+ in the urban area, whereas the visibility degradation due to the effects of NO3 , SO42-, and NH4+ did not show significant diference in the rural area., Implications: Of the eight potential influential variables, PM2.5 showed the greatest effects on reduced visibility. Compared with other type of episodes, the aerosols tend to be fine size during the episodes of stagnant weather. This is the main reason why the poorest visibility occurred during the SW episodes. Good correlations between visibility and secondary inorganic salts (NH4+, NO3-, and SO4(2-)) suggested that secondary inorganic salts did contribute significantly to the degradation of visibility. Among the three inorganic salts, nitrates played a leading role for visibility degradation in urban areas in central Taiwan.

Understanding temporal coherence in particulate matter (PM) pollution across East Asian outflow regions is crucial for collaborative efforts in addressing air pollution challenges. In this study, we analyze daily PM exceedance patterns using ground-based measurements over the past two decades, focusing on the influence of El Niño-Southern Oscillation (ENSO) and Asian dust activity. ENSO-related coherent PM exceedance shows lower occurrence during El Niño compared to La Niña in spring, due to weakened continental outflows and increased precipitation. Temporal distribution of dust-related coherent PM exceedance closely mirrors springtime dust activity in source regions, indicating significant dust emission impact on outflow regions. Our findings have implications for climate variability and the assessment of multi-decade model simulations. [ABSTRACT FROM AUTHOR]

The Indochina biomass burning (BB) season in springtime has a substantial environmental impact on the surrounding areas in Asia. In this study, we evaluated the environmental impact of a major long-range BB transport event on 19 March 2018 (a flight of the High Altitude and Long Range Research Aircraft (HALO; https://www.halo-spp.de , last access: 14 February 2023) research aircraft, flight F0319) preceded by a minor event on 17 March 2018 (flight F0317). Aircraft data obtained during the campaign in Asia of the Effect of Megacities on the transport and transformation of pollutants on the Regional to Global scales (EMeRGe) were available between 12 March and 7 April 2018. In F0319, results of 1 min mean carbon monoxide (CO), ozone (O 3) , acetone (ACE), acetonitrile (ACN), organic aerosol (OA), and black carbon aerosol (BC) concentrations were up to 312.0, 79.0, 3.0, and 0.6 ppb and 6.4 and 2.5 µ g m -3 , respectively, during the flight, which passed through the BB plume transport layer (BPTL) between the elevation of 2000–4000 m over the East China Sea (ECS). During F0319, the CO, O 3 , ACE, ACN, OA, and BC maximum of the 1 min average concentrations were higher in the BPTL by 109.0, 8.0, 1.0, and 0.3 ppb and 3.0 and 1.3 µ g m -3 compared to flight F0317, respectively. Sulfate aerosol, rather than OA, showed the highest concentration at low altitudes (<1000 m) in both flights F0317 and F0319 resulting from the continental outflow in the ECS. The transport of BB aerosols from Indochina and its impacts on the downstream area were evaluated using a Weather Research Forecasting with Chemistry (WRF-Chem) model. The modeling results tended to overestimate the concentration of the species, with examples being CO (64 ppb), OA (0.3 µ g m -3) , BC (0.2 µ g m -3) , and O 3 (12.5 ppb) in the BPTL. Over the ECS, the simulated BB contribution demonstrated an increasing trend from the lowest values on 17 March 2018 to the highest values on 18 and 19 March 2018 for CO, fine particulate matter (PM 2.5) , OA, BC, hydroxyl radicals (OH), nitrogen oxides (NO x) , total reactive nitrogen (NO y) , and O 3 ; by contrast, the variation of J(O1D) decreased as the BB plume's contribution increased over the ECS. In the lower boundary layer (<1000 m), the BB plume's contribution to most species in the remote downstream areas was <20 %. However, at the BPTL, the contribution of the long-range transported BB plume was as high as 30 %–80 % for most of the species (NO y , NO x , PM 2.5 , BC, OH, O 3 , and CO) over southern China (SC), Taiwan, and the ECS. BB aerosols were identified as a potential source of cloud condensation nuclei, and the simulation results indicated that the transported BB plume had an effect on cloud water formation over SC and the ECS on 19 March 2018. The combination of BB aerosol enhancement with cloud water resulted in a reduction of incoming shortwave radiation at the surface in SC and the ECS by 5 %–7 % and 2 %–4 %, respectively, which potentially has significant regional climate implications. [ABSTRACT FROM AUTHOR]

In addition to the Taiwan Strait, the geographical channel effect (GCE) has been observed in the Taipei Basin during winters. This study explored the potential links amongst GCE phenomena in the basin, fine particulate matter (PM2.5) events, and position of the continental high-pressure system (CHPS). Principal component analysis was applied to classify the CHPS distribution patterns influencing PM2.5 concentrations and meteorological parameters in the Taipei metropolis. In addition, non-parametric Kruskal–Wallis and Dwass–Steel–Critchlow–Fligner tests were applied to compare the parameters amongst distinct groups. Moreover, track analysis was utilised to trace the trajectories of air masses. The merged Dark Target Aerosol Angstrom Exponent (Ocean), Deep Blue Aerosol Angstrom Exponent (Land), and Aerosol Optical Depth (AOD) 3 km (Land and Ocean) of Terra/MODIS and Aqua/MODIS were used to confirm the connection of long-range PM2.5 transport. Two features in the atmospheric environment induce double GCEs: (1) wind direction below 90° in most of the upwind area of the Taisumi and Xindian River Basins; (2) CHPS centres moved across 110° E. Double GCEs can reduce the magnitude of PM2.5 air pollution and shape the distribution of PM2.5; however, they cannot prevent PM2.5 events. [ABSTRACT FROM AUTHOR]

Particulate lead (Pb) is a primary air pollutant that affects society because of its health impacts. This study investigates the source sectors of Pb associated with ambient fine particulate matter (PM2.5) over central-western Taiwan (CWT) with new constraints on the Pb-isotopic composition. We demonstrate that the contribution of coal-fired facilities is overwhelming, which is estimated to reach 35 ± 16% in the summertime and is enhanced to 57 ± 24% during the winter monsoon seasons. Moreover, fossil-fuel vehicles remain a major source of atmospheric Pb, which accounts for 12 ± 5%, despite the current absence of a leaded gasoline supply. Significant seasonal and geographical variations in the Pb-isotopic composition are revealed, which suggest that the impact of East Asian (EA) pollution outflows is important in north CWT and drastically declines toward the south. We estimate the average contribution of EA outflows as accounting for 35 ± 15% (3.6 ± 1.5 ng/m3) of the atmospheric Pb loading in CWT during the winter monsoon seasons. [ABSTRACT FROM AUTHOR]

This study compares the performance of 12 regional chemical transport models (CTMs) from the third phase of the Model Inter-Comparison Study for Asia (MICS-Asia III) on simulating the particulate matter (PM) over East Asia (EA) in 2010. The participating models include the Weather Research and Forecasting model coupled with Community Multiscale Air Quality (WRF-CMAQ; v4.7.1 and v5.0.2), the Regional Atmospheric Modeling System coupled with CMAQ (RAMS-CMAQ; v4.7.1 and v5.0.2), the Weather Research and Forecasting model coupled with chemistry (WRF-Chem; v3.6.1 and v3.7.1), Goddard Earth Observing System coupled with chemistry (GEOS-Chem), a non-hydrostatic model coupled with chemistry (NHM-Chem), the Nested Air Quality Prediction Modeling System (NAQPMS) and the NASA-Unified WRF (NU-WRF). This study investigates three model processes as the possible reasons for different model performances on PM. (1) Models perform very differently in the gas–particle conversion of sulfur (S) and oxidized nitrogen (N). The model differences in sulfur oxidation ratio (50 %) are of the same magnitude as that in SO42- concentrations. The gas–particle conversion is one of the main reasons for different model performances on fine mode PM. (2) Models without dust emission modules can perform well on PM 10 at non-dust-affected sites but largely underestimate (up to 50 %) the PM 10 concentrations at dust sites. The implementation of dust emission modules in the models has largely improved the model accuracies at dust sites (reduce model bias to -20 %). However, both the magnitude and distribution of dust pollution are not fully captured. (3) The amounts of modeled depositions vary among models by 75 %, 39 %, 21 % and 38 % for S wet, S dry, N wet and N dry depositions, respectively. Large inter-model differences are found in the washout ratios of wet deposition (at most 170 % in India) and dry deposition velocities (generally 0.3–2 cm s -1 differences over inland regions). [ABSTRACT FROM AUTHOR]

Daily and hourly average data from nine air-quality monitoring stations distributed across central Taiwan, which include ten items (i.e., PM, PM, wind direction, wind speed, temperature, relative humidity, SO, NO, NO, and CO), were collected from 2005 to 2009. Four episode types: long-range transport with dust storms (DS), long-range transport with frontal pollution (FP), river dust (RD), and stagnant weather (SW), and one mixed type of episode were identified. Of these four episode types, the SW was the dominant type, averaging about 70 %. The mean ratio of PM/PM was the lowest during the RD episodes (0.42), while the mean ratio of PM/PM was the highest during the SW episodes (0.64). Fine aerosol (PM) and coarse aerosol (PM) samples were collected by high-volume samplers for chemical composition analysis, from only three stations (Douliou, Lunbei, and Siansi) during the days of SW, RD, DS, and FP. The concentrations of PM and three ionic species (NH, NO, and SO) all showed significant differences among the four episode types. The highest levels of NO (12.1 μg/m) and SO (20.5 μg/m) were found during the SW and FP episodes, respectively. A comparison on the spatial similarity of aerosol compositions among the episodes and/or non-episodes (control) was characterized by the coefficient of divergence (CD). The results showed higher CD values in PM than in PM, and the CD values between RD episodes and the other three episodes were higher than those between two types of episode for the other three episodes. The ratios of SOR (sulfur oxidation ratio), SO/EC (elemental carbon), NOR (nitrogen oxidation ratio), and NO/EC showed that sulfate formation was most rapid during the FP, while nitrate formation was most rapid during the SW. [ABSTRACT FROM AUTHOR]

Abstract: Surface ozone (O3) and carbon monoxide (CO) mixing ratios were measured at Mei-Feng (24.05 °N, 120.10 °E, 2269 m above sea level) remote mountain site between March 2009 and September 2010 to investigate the impact of regional pollution on O3 and CO. The results showed that the maximum values of both O3 and CO were found in the springtime. Backward trajectory analysis, combined with MODIS fire spots suggested that the enhanced O3 and CO in springtime could be attributed to biomass burning (BB) activities over Southeast (SE) Asia. Thirteen BB events were identified by backward trajectory analysis, MODIS fires, NCEP weather data sets and CO concentrations. Good correlation between O3 and CO was found during the BB plumes. Using the linear regression, the slope (ΔO3/ΔCO) was calculated to be 0.18 ± 0.08 (mean ± 1σ). This value was in agreement with that of 0.2 observed over the west Pacific region during the TRACE-P campaign, but was higher than those (0.11–0.14) of Canadian and Siberian fires. Moreover, significant enhanced O3 productivity was also found in aged BB plumes and that mixed with urban emissions from SE coastal China. To assess the net influence of SE Asian BB, the air masses from SE Asia and SE China were divided in two groups: those that passed over the fire regions (PF) and those that did not (NP). The result showed that the maximum differences between PF and NP were estimated in March with 8 ppb for O3 and 45 ppb for CO, respectively, accounting for 23% of both CO and O3 levels at Mei-Feng. Although uncertainties existed in the estimations, the significant discrepancies of O3 and CO in the two air groups suggested the air pollutants emitted by SE Asian BB could be transported and influence the air quality over subtropical Taiwan in springtime. [Copyright &y& Elsevier]

Autism spectrum disorder (ASD) is a group of neurodevelopmental disorders, and its incidence is increasing over time. Although several environmental factors have been suspected to be risk factors for ASD, studies on the effects of airborne heavy metals on newly developed ASD are still limited. We conducted a large birth cohort study of 168,062 live term births in Taichung during 2004–2011 to assess the association of heavy metals in particulate matter with an aerodynamic diameter less than 2.5 μm (PM 2.5) with ASD, and identify sensitive time windows during prenatal and postnatal periods. Heavy metals, including arsenic (As), cadmium (Cd), mercury (Hg), and lead (Pb) in PM 2.5 , were estimated using the Weather Research and Forecasting/Chem (WRF/Chem), inserted from the top 75 emission sources for the module. The association between childhood ASD and 4 metals were analyzed from pregnancy to 9 months after birth. The Cox proportional hazard model with a distributed lag nonlinear model (DLNM) was used to estimate the association between heavy metals in PM 2.5 and ASD. We identified 666 incident ASD cases in 168,062 participants. A positive association between Hg and ASD was found at 9 months after birth (Hazard Ratio: 1.63; 95% CI: 1.13–2.36). According to the DLNM, there was an increased risk of exposure to Hg during 10–25 weeks after birth, and decreased risk of exposure to Hg during gestational weeks 4–6. Exposure to As and Hg on the risk of ASD were significantly stronger in low birth weight infants (<2500 g) than in those of birth weight ≥2500 g during postnatal period. Postnatal exposure to Hg in PM 2.5 may associate with increased ASD incidence. Infants with low birth weight and exposure to As and Hg in PM 2.5 are more likely to develop ASD. • Exposure to Hg during the postnatal period will increase the risk of childhood ASD. • The sensitive time window of exposure to Hg was found in 10–25 weeks after birth. • Infants with low birth weight and exposure to As and Hg are more likely to develop ASD. [ABSTRACT FROM AUTHOR]

Abstract This study investigated isotopic signatures of carbon (C), lead (Pb) and strontium (Sr) in PM 2.5 samples collected from two paired sites (urban vs. rural/background) in northern Taiwan during the summer of 2015 and the spring of 2016, respectively. Significant seasonality was revealed in the isotopic signatures of C and Pb, whereas no seasonal difference was observed in 87Sr/86Sr ratio. The values of δ13C, 206Pb/207Pb, and 208Pb/207Pb were more diverse and exhibited local features in summer. However, during the episodes of continental pollution outbreaks in springtime, the δ13C and Pb isotope ratios of PM 2.5 shifted and converged consistently toward the documented characteristics of particulate matters in northern China. Moreover, the results showed that the differences in the Pb and Sr isotopic characteristics between the paired urban and rural sites were statistically insignificant, whereas marginally lower δ13C values were observed at the urban site. It was inferred accordingly that a substantial amount of gaseous hydrocarbons emitted in local urban areas could have been converted to secondary organic aerosols with lower δ13C. On the contrary, the consistency in the spatial and temporal variations of mass concentration and isotope ratios of Pb at the two sites suggested that East-Asian continental pollution outbreak was the major source of Pb-containing particles in the northern Taiwan during springtime. It is noteworthy that there was neither seasonal nor spatial differences in the 87Sr/86Sr ratio observed in this study, which suggested that the Sr-containing particles collected in this study could be originating from a common mixture of sources, including not only natural dust but also the anthropogenic emissions, coal-combustion for instance. This investigation upon the C-Pb-Sr isotopic features evidenced the substantial impacts of the continental pollution outbreaks on the aerosol composition and air quality in the downwind areas of the East-Asian winter monsoons. Graphical abstract Unlabelled Image Highlights • Seasonal and temporal variations of C-Pb-Sr isotopes of PM 2.5 were investigated. • C and Pb in PM 2.5 exhibited significant seasonal isotope signatures. • Isotopic evidences for the impacts of Asian outflows on air quality were revealed. • Consistent Sr isotope ratios were observed from local and distant sources. [ABSTRACT FROM AUTHOR]

This paper explores the spatio-temporal patterns of particulate matter (PM) in Taiwan based on a series of methods. Using fuzzy c-means clustering first, the spatial heterogeneity (six clusters) in the PM data collected between 2005 and 2009 in Taiwan are identified and the industrial and urban areas of Taiwan (southwestern, west central, northwestern, and northern Taiwan) are found to have high PM concentrations. The PM10-PM2.5 relationship is then modeled with global ordinary least squares regression, geographically weighted regression (GWR), and geographically and temporally weighted regression (GTWR). The GTWR and GWR produce consistent results; however, GTWR provides more detailed information of spatio-temporal variations of the PM10-PM2.5 relationship. The results also show that GTWR provides a relatively high goodness of fit and sufficient space-time explanatory power. In particular, the PM2.5 or PM10 varies with time and space, depending on weather conditions and the spatial distribution of land use and emission patterns in local areas. Such information can be used to determine patterns of spatio-temporal heterogeneity in PM that will allow the control of pollutants and the reduction of public exposure. [ABSTRACT FROM AUTHOR]

Particulate lead (Pb) is a primary air pollutant that affects society because of its health impacts. This study investigates the source sectors of Pb associated with ambient fine particulate matter (PM2.5) over central-western Taiwan (CWT) with new constraints on the Pb-isotopic composition. We demonstrate that the contribution of coal-fired facilities is overwhelming, which is estimated to reach 35 ± 16% in the summertime and is enhanced to 57 ± 24% during the winter monsoon seasons. Moreover, fossil-fuel vehicles remain a major source of atmospheric Pb, which accounts for 12 ± 5%, despite the current absence of a leaded gasoline supply. Significant seasonal and geographical variations in the Pb-isotopic composition are revealed, which suggest that the impact of East Asian (EA) pollution outflows is important in north CWT and drastically declines toward the south. We estimate the average contribution of EA outflows as accounting for 35 ± 15% (3.6 ± 1.5 ng/m3) of the atmospheric Pb loading in CWT during the winter monsoon seasons. [ABSTRACT FROM AUTHOR]

Abstract: Intensive measurements of aerosol (PM10) and associated water-soluble ionic and carbonaceous species were conducted in Guangzhou, a mega city of China, during summer 2006. Elevated levels of most chemical species were observed especially at nighttime during two episodes, characterized by dramatic build-up of the biomass burning tracers levoglucosan and non-sea-salt potassium, when the prevailing wind direction had changed due to two approaching tropical cyclones. High-resolution air mass back trajectories based on the MM5 model revealed that air masses with high concentrations of levoglucosan (43–473 ng m−3) and non-sea-salt potassium (0.83–3.2 μg m−3) had passed over rural regions of the Pearl River Delta and Guangdong Province, where agricultural activities and field burning of crop residues are common practices. The relative contributions of biomass burning smoke to organic carbon in PM10 were estimated from levoglucosan data to be on average 7.0 and 14% at daytime and nighttime, respectively, with maxima of 9.7 and 32% during the episodic transport events, indicating that biomass and biofuel burning activities in the rural parts of the Pearl River Delta and neighboring regions could have a significant impact on ambient urban aerosol levels. [Copyright &y& Elsevier]

Abstract: We identify the directionality of sources contributing to observed pollutant concentrations at a rural site through the use of the analysis methods of Conditional Probability Function (CPF) and the Source Direction Probability (SDP). Input data consists of hourly averaged PM2.5 mass, Organic Mass (OM) from Organic Carbon (OC), optical Elemental Carbon (optical EC), SO2, CO, NOy, O3 concentrations and metrological data from Pinnacle State Park site in rural New York State for the period of Dec 2004 to Dec 2008. These measured pollutants are coupled with on-site wind data to identify the directionality of the sources; which are then compared to known stationary source locations from the EPA Air Data web site. Although the CPF plot of the O3 showed no distinct directionality source area, the Pinnacle State Park site was frequently impacted by plumes of relatively high PM2.5 mass, SO2, CO, NOy, optical EC and OM concentrations. Further analysis of the enhanced pollution occurrence frequency from the eastern sector revealed two peaks in the time-of-day distribution of elevated CO, NOy, and optical EC, which provides additional information on the sources. This contrasts with the enhanced pollution occurrence frequency from the south for CO, OM, and optical EC, which shows a single morning peak in its time-of-day distribution and indicates a somewhat more distant, but common source for these carbon-containing pollutants. PM2.5 mass corresponds to the source areas related to emission facilities listed in the EPA Emissions Inventory, which is further confirmed by correlation and analysis of aerosol optical depth (AOD) data from Moderate-resolution Imaging Spectrometer (MODIS) on board Terra and Aqua satellites. We present evidence that most of the high pollution episodes likely arise from emission sources located several hundred kilometers from the site, indicating mid-long range transport of pollutants to this location. [Copyright &y& Elsevier]