Ambient Concentrations Of PM2 Research Articles

Health Risk of Ambient PM10-bound PAHs at Bus Stops in Spring and Autumn in Tianjin, China

ABSTRACT A study was conducted to measure ambient concentrations of PM10 and PM10-bound PAHs to estimate health risks due to exposure to PAHs during wait times at bus stops in September 2012 and March 2014. Samples were collected by personal exposure monitors at Balitai and Haiguangsi bus stops in Tianjin, China. The equivalent concentration of benzo[a]pyrene (BaPeq) was used to estimate the health risks of PAHs in PM10 inhaled by passengers waiting at these bus stops. The results showed the average PM10 level was higher in autumn (non-heating season) compared to spring (heating season) (307 ± 67 µg m–3 vs. 226 ± 100 µg m–3). When averaged over the two bus stops, concentrations of total PAHs in PM10 were much higher during spring compared to autumn (417 vs. 193 ng m–3), while BaPeq was slightly lower during spring (29.7 vs. 32.8 ng m–3). The incremental lifetime cancer risks (ILCR) at the two bus stops, Balitai and Haiguangsi, in spring were 9.0 × 10–8 and 4.5 × 10–8, and in autumn were 1.1 × 10–7 and 7.7 × 10–8, respectively. All these risk values were lower than the acceptable risk range of 10–6–10–4 approved by US Environmental Protection Agency.

Temporal Variation of Ambient PM10 Concentration within an Urban-Industrial Environment

PM10 concentration in the ambient air has been reported to be the main pollutant affecting human health, particularly in the urban areas. This research is conducted to study the variation of PM10 concentration at the three urban-industrial areas in Malaysia, namely Shah Alam, Kuala Terengganu and Melaka. In addition, the association and correlation between PM10 concentration and other air pollutants will be distinguished. Five years interval dataset (2008-2012) consisting of PM10, SOX, NOX and O3 concentrations and other weather parameters such as wind speed, humidity and temperature were obtained from Department of Environment, Malaysia. Shah Alam shows the highest average of PM10 concentration with the value of 62.76 μg/m3 in June, whereas for Kuala Terengganu was 59.29 μg/m3 in February and 46.61 μg/m3 in August for Melaka. Two peaks were observed from the time series plot using the averaged monthly PM10 concentration. First peak occurs when PM10 concentration rises from January to February and the second peak is reached in June and remain high for the next two consecutive months for Shah Alam and Kuala Terengganu. Meanwhile the second peak for Melaka is only achieved in August as a result of the transboundary of smoke from forest fires in the Sumatra region during dry season from May to September. Both of the pollutants can be sourced from rapid industrial activities at Shah Alam. PM10 concentration is strongly correlated with carbon monoxide concentration in Kuala Terengganu and Melaka with value of r2 = 0.1725 and 0.2744 respectively. High carbon monoxide and PM10 concentration are associated with burning of fossil fuel from increased number of vehicles at these areas.

Acute respiratory symptoms associated with short term fluctuations in ambient pollutants among schoolchildren in Durban, South Africa.

Ambient air pollution has been associated with adverse respiratory outcomes, especially among children with asthma. This study reports on associations between daily ambient air pollutant concentrations and the respiratory symptoms of schoolchildren living in Durban, South Africa. This city is Africa's busiest port and a key hub for imported crude oil and exported refined petroleum and petrochemical products, and it experiences a mixture of air pollutants that reflects emissions from industry, traffic and biomass burning. Children in four communities in the highly industrialized southern portion of the city were compared to children of similar socio-economic profiles living in the north of the city. One school was selected in each community. A total of 423 children were recruited. Symptom logs were completed every 1.5-2h over 3-week period in each of four seasons. Ambient concentrations of NO2, NO, SO2, CO, O3, PM2.5 and PM10 were measured throughout the study. Generalized estimating equation (GEE) models were used to estimate odds ratios (ORs) and assess lag effects (1-5 days) using single pollutant (single lags or distributed lags) models. Concentrations of SO2 and NOx were markedly higher in the south, while PM10 did not vary. Significant increase in the odds ratios of cough were identified for the various lags analyzed. The OR of symptoms was further increased among those living in the south compared to the north. In conclusion, in this analysis of over 70,000 observations, we provide further evidence that exposure to PM10, SO2, NO2 and NO is associated with significantly increased occurrence of respiratory symptoms among children. This was evident for cough, shortness of breath, and chest tightness, across the four pollutants and for different lags of exposure. This is the first study describing these changes in sub-Saharan Africa.

Assessment of the potential respiratory hazard of volcanic ash from future Icelandic eruptions: a study of archived basaltic to rhyolitic ash samples

BackgroundThe eruptions of Eyjafjallajökull (2010) and Grímsvötn (2011), Iceland, triggered immediate, international consideration of the respiratory health hazard of inhaling volcanic ash, and prompted the need to estimate the potential hazard posed by future eruptions of Iceland’s volcanoes to Icelandic and Northern European populations.MethodsA physicochemical characterization and toxicological assessment was conducted on a suite of archived ash samples spanning the spectrum of past eruptions (basaltic to rhyolitic magmatic composition) of Icelandic volcanoes following a protocol specifically designed by the International Volcanic Health Hazard Network.ResultsIcelandic ash can be of a respirable size (up to 11.3 vol.% < 4 μm), but the samples did not display physicochemical characteristics of pathogenic particulate in terms of composition or morphology. Ash particles were generally angular, being composed of fragmented glass and crystals. Few fiber-like particles were observed, but those present comprised glass or sodium oxides, and are not related to pathogenic natural fibers, like asbestos or fibrous zeolites, thereby limiting concern of associated respiratory diseases. None of the samples contained cristobalite or tridymite, and only one sample contained quartz, minerals of interest due to the potential to cause silicosis. Sample surface areas are low, ranging from 0.4 to 1.6 m2 g−1, which aligns with analyses on ash from other eruptions worldwide. All samples generated a low level of hydroxyl radicals (HO•), a measure of surface reactivity, through the iron-catalyzed Fenton reaction compared to concurrently analyzed comparative samples. However, radical generation increased after ‘refreshing’ sample surfaces, indicating that newly erupted samples may display higher reactivity. A composition-dependent range of available surface iron was measured after a 7-day incubation, from 22.5 to 315.7 μmol m−2, with mafic samples releasing more iron than silicic samples. All samples were non-reactive in a test of red blood cell-membrane damage.ConclusionsThe primary particle-specific concern is the potential for future eruptions of Iceland’s volcanoes to generate fine, respirable material and, thus, to increase ambient PM concentrations. This particularly applies to highly explosive silicic eruptions, but can also hold true for explosive basaltic eruptions or discrete events associated with basaltic fissure eruptions.

Maternal exposure to ambient air pollution and fetal growth in North-East Scotland: A population-based study using routine ultrasound scans

BackgroundMaternal ambient air pollution exposure is associated with reduced birthweight. Few studies have examined the effect on growth in utero and none have examined the effect of exposure to particulates less than 2.5µm (PM2.5) and possible effect modification by smoking status. ObjectivesExamine the effect of maternal exposure to ambient concentrations of PM10, PM2.5 and nitrogen dioxide (NO2) for in utero fetal growth, size at birth and effect modification by smoking status. MethodsAdministratively acquired second and third trimester fetal measurements (bi-parietal diameter, femur length and abdominal circumference), birth outcomes (weight, crown heel length and occipito-frontal circumference) and maternal details were obtained from routine fetal ultrasound scans and maternity records (period 1994–2009). These were modelled against residential annual pollution concentrations (calendar year mean) adjusting for covariates and stratifying by smoking status. ResultsIn the whole sample (n=13,775 pregnancies), exposure to PM10, PM2.5 and NO2 was associated with reductions in measurements at birth and biparietal diameter from late second trimester onwards. Among mothers who did not smoke at all during pregnancy (n=11,075), associations between biparietal diameter and pollution exposure remained significant but were insignificant among those who did smoke (n=2700). Femur length and abdominal circumference were not significantly associated with pollution exposure. ConclusionsFetal growth is strongly associated with particulates exposure from later in second trimester onwards but the effect appears to be subsumed by smoking. Typical ambient exposures in this study were relatively low compared to other studies and given these results, it may be necessary to consider reducing recommended “safe” ambient air exposures.

A GIS Model for PM10 Exposure from Biomass Burning in the North of Thailand

Human exposure to particulate matter with an aerodynamic diameter below 10 μm (PM10) is found to be associated with biomass burning in Thailand. Recent investigations confirm that primary sources of PM10 are natural forest fires and agricultural waste burning. Incidence of atmospheric haze increases significantly during the dry season from January to April. PM10 exposure in eight provinces in Northern Thailand were determined using GIS through spatial interpolation. Daily average ambient PM10 concentrations from 10 monitoring stations were used as the input data for the GIS model. Three interpolation techniques: Inverse Distance Weighted (IDW), Kriging and Spline, were compared. The predicted PM10concentrations were verified with field measurements. GIS-based maps illustrated the variability of PM10 distribution and high-risk locations, which were found to be associated with wind direction and forest fire frequencies. Mae Hong Son, Chiang Rai and Phrae were found to be at highest risk of PM10 exposure during the dry season.

Ensemble classification for identifying neighbourhood sources of fugitive dust and associations with observed PM10

In urban areas the deterioration of air quality as a result of fugitive dust receives less attention than the more prominent traffic and industrial emissions. We assessed whether fugitive dust emission sources in the neighbourhood of an air quality monitor are predictors of ambient PM10 concentrations on days characterized by strong local winds. An ensemble maximum likelihood method is developed for land cover mapping in the vicinity of an air quality station using SPOT 6 multi-spectral images. The ensemble maximum likelihood classifier is developed through multiple training iterations for improved accuracy of the bare soil class. Five primary land cover classes are considered, namely built-up areas, vegetation, bare soil, water and ‘mixed bare soil’ which denotes areas where soil is mixed with either vegetation or synthetic materials. Preliminary validation of the ensemble classifier for the bare soil class results in an accuracy range of 65–98%. Final validation of all classes results in an overall accuracy of 78%. Next, cluster analysis and a varying intercepts regression model are used to assess the statistical association between land cover, a fugitive dust emissions proxy and observed PM10. We found that land cover patterns in the neighbourhood of an air quality station are significant predictors of observed average PM10 concentrations on days when wind speeds are conducive for dust emissions. This study concludes that in the absence of an emissions inventory for ambient particulate matter, PM10 emitted from dust reservoirs can be statistically accounted for by land cover characteristics. This supports the use of land cover data for improved prediction of PM10 at locations without air quality monitoring stations.

Spatial Analysis of Ambient PM2.5 Exposure and Bladder Cancer Mortality in Taiwan.

Fine particulate matter (PM2.5) is an air pollutant that is receiving intense regulatory attention in Taiwan. In previous studies, the effect of air pollution on bladder cancer has been explored. This study was conducted to elucidate the effect of atmospheric PM2.5 and other local risk factors on bladder cancer mortality based on available 13-year mortality data. Geographically weighted regression (GWR) was applied to estimate and interpret the spatial variability of the relationships between bladder cancer mortality and ambient PM2.5 concentrations, and other variables were covariates used to adjust for the effect of PM2.5. After applying a GWR model, the concentration of ambient PM2.5 showed a positive correlation with bladder cancer mortality in males in northern Taiwan and females in most of the townships in Taiwan. This is the first time PM2.5 has been identified as a risk factor for bladder cancer based on the statistical evidence provided by GWR analysis.

Is short-term exposure to ambient fine particles associated with measles incidence in China? A multi-city study

BackgroundChina's rapid economic development has resulted in severe particulate matter (PM) air pollution and the control and prevention of infectious disease is an ongoing priority. This study examined the relationships between short-term exposure to ambient particles with aerodynamic diameter ≤2.5µm (PM2.5) and measles incidence in China. MethodsData on daily numbers of new measles cases and concentrations of ambient PM2.5 were collected from 21 cities in China during Oct 2013 and Dec 2014. Poisson regression was used to examine city-specific associations of PM2.5 and measles, with a constrained distributed lag model, after adjusting for seasonality, day of the week, and weather conditions. Then, the effects at the national scale were pooled with a random-effect meta-analysis. ResultsA 10µg/m3 increase in PM2.5 at lag 1day, lag 2day and lag 3day was significantly associated with increased measles incidence [relative risk (RR) and 95% confidence interval (CI) were 1.010 (1.003, 1.018), 1.010 (1.003, 1.016) and 1.006 (1.000, 1.012), respectively]. The cumulative relative risk of measles associated with PM2.5 at lag 1–3 days was 1.029 (95% CI: 1.010, 1.048). Stratified analyses by meteorological factors showed that the PM2.5 and measles associations were stronger on days with high temperature, low humidity, and high wind speed. ConclusionsWe provide new evidence that measles incidence is associated with exposure to ambient PM2.5 in China. Effective policies to reduce air pollution may also reduce measles incidence.

Dust deposition and ambient PM&amp;lt;sub&amp;gt;10&amp;lt;/sub&amp;gt; concentration in northwest China: spatial and temporal variability

Abstract. Eolian dust transport and deposition are important geophysical processes which influence global bio-geochemical cycles. Currently, reliable deposition data are scarce in central and east Asia. Located at the boundary of central and east Asia, Xinjiang Province of northwestern China has long played a strategic role in cultural and economic trade between Asia and Europe. In this paper, we investigated the spatial distribution and temporal variation in dust deposition and ambient PM10 (particulate matter in aerodynamic diameter ≤ 10 µm) concentration from 2000 to 2013 in Xinjiang Province. This variation was assessed using environmental monitoring records from 14 stations in the province. Over the 14 years, annual average dust deposition across stations in the province ranged from 255.7 to 421.4 t km−2. Annual dust deposition was greater in southern Xinjiang (663.6 t km−2) than northern (147.8 t km−2) and eastern Xinjiang (194.9 t km−2). Annual average PM10 concentration across stations in the province varied from 100 to 196 µg m−3 and was 70, 115 and 239 µg m−3 in northern, eastern and southern Xinjiang, respectively. The highest annual dust deposition (1394.1 t km−2) and ambient PM10 concentration (352 µg m−3) were observed in Hotan, which is located in southern Xinjiang and at the southern boundary of the Taklamakan Desert. Dust deposition was more intense during the spring and summer than other seasons. PM10 was the main air pollutant that significantly influenced regional air quality. Annual average dust deposition increased logarithmically with ambient PM10 concentration (R2 ≥ 0.81). While the annual average dust storm frequency remained unchanged from 2000 to 2013, there was a positive relationship between dust storm days and dust deposition and PM10 concentration across stations. This study suggests that sand storms are a major factor affecting the temporal variability and spatial distribution of dust deposition in northwest China.

Source apportionment of ambient fine and coarse particulate matter at the Fort McKay community site, in the Athabasca Oil Sands Region, Alberta, Canada.

An ambient air particulate matter sampling study was conducted at the Wood Buffalo Environmental Association (WBEA) AMS-1 Fort McKay monitoring station in the Athabasca Oil Sand Region (AOSR) in Alberta, Canada from February 2010 to July 2011. Daily 24h integrated fine (PM2.5) and coarse (PM10-2.5) particulate matter was collected using a sequential dichotomous sampler. Over the duration of the study, 392 valid daily dichotomous PM2.5 and PM10-2.5 sample pairs were collected with concentrations of 6.8±12.9μgm-3 (mean±standard deviation) and 6.9±5.9μgm-3, respectively. A subset of 100 filter pairs was selected for element analysis by energy dispersive X-ray fluorescence and dynamic reaction cell inductively coupled plasma mass spectrometry. Application of the U.S. EPA positive matrix factorization (PMF) receptor model to the study data matrix resolved five PM2.5 sources explaining 96% of the mass including oil sands upgrading (32%), fugitive dust (26%), biomass combustion (25%), long-range Asian transport lead source (9%), and winter road salt (4%). An analysis of historical PM2.5 data at this site shows that the impact of smoke from wildland fires was particularly high during the summer of 2011. PMF resolved six PM10-2.5 sources explaining 99% of the mass including fugitive haul road dust (40%), fugitive oil sand (27%), a mixed source fugitive dust (16%), biomass combustion (12%), mobile source (3%), and a local copper factor (1%). Results support the conclusion of a previous epiphytic lichen biomonitor study that near-field atmospheric deposition in the AOSR is dominated by coarse fraction fugitive dust from bitumen mining and upgrading operations, and suggest that fugitive dust abatement strategies targeting the three major sources of PM10-2.5 (e.g., oil sand mining, haul roads, bulk material stockpiles) would significantly reduce near-field atmospheric deposition gradients in the AOSR and reduce ambient PM concentrations in the Fort McKay community.

Relationships between Outdoor and Personal Exposure of Carbonaceous Species and Polycyclic Aromatic Hydrocarbons (PAHs) in Fine Particulate Matter (PM2.5) at Hong Kong

ABSTRACTPersonal and ambient fine particulate matter (PM2.5) samples were simultaneously collected at Hong Kong during winter in 2014. Mass concentration, organic carbon (OC), elemental carbon (EC), and polycyclic aromatic hydrocarbons (PAHs) relationships were analyzed. The correlations of personal and ambient concentrations of PM2.5, OC, and EC indicated the ambient concentrations were the factors showing influences on the personal exposures. Personal to ambient (P/A) ratios in PM2.5, OC, and EC were all > 1, suggesting influences between indoor sources and/or personal activities. Significant higher ambient ΣPAHs concentrations with P/A ratios were nevertheless < 1. The Σ15 U.S. EPA priority PAHs accounted for 50.6% and 70.8% of ΣPAHs in personal and ambient samples, respectively. The ratios of indicator compounds confirmed the origin of PAHs in personal PM2.5, which were found to be associated predominantly with traffic emissions and the influence by the indoor sources.

Assessment and prediction of the impact of road transport on ambient concentrations of particulate matter PM10

The main challenge facing the air quality management authorities in most cities is meeting the air quality limits and objectives in areas where road traffic is high. The difficulty and uncertainties associated with the estimation and prediction of the road traffic contribution to the overall air quality levels is the major contributing factor. In this paper, particulate matter (PM10) data from 10 monitoring sites in London was investigated with a view to estimating and developing Artificial Neural Network models (ANN) for predicting the impact of the road traffic on the levels of PM10 concentration in London. Twin studies in conjunction with bivariate polar plots were used to identify and estimate the contribution of road traffic and other sources of PM10 at the monitoring sites. The road traffic was found to have contributed between 24% and 62% of the hourly average roadside PM10 concentrations. The ANN models performed well in predicting the road contributions with their R-values ranging between 0.6 and 0.9, FAC2 between 0.6 and 0.95, and the normalised mean bias between 0.01 and 0.11. The hourly emission rates of the vehicles were found to be the most contributing input variables to the outputs of the ANN models followed by background PM10, gaseous pollutants and meteorological variables respectively.

Source Proximity and Meteorological Effects on Residential Ambient Concentrations of PM2.5, Organic Carbon, Elemental Carbon, and p-PAHs in Houston and Los Angeles, USA

Source Proximity and Meteorological Effects on Residential Ambient Concentrations of PM2.5, Organic Carbon, Elemental Carbon, and p-PAHs in Houston and Los Angeles, USA

Influence of tree crown characteristics on the local PM10 distribution inside an urban street canyon in Antwerp (Belgium): A model and experimental approach

Apart from influencing the amount of leaf-deposited particles, tree crown morphology will influence the local distribution of atmospheric particles. Nevertheless, tree crowns are often represented very rudimentary in three-dimensional air quality models. Therefore, the influence of tree crown representation on the local ambient PM10 concentration and resulting leaf-deposited PM10 mass was evaluated, using the three-dimensional computational fluid dynamics (CFD) model ENVI-met® and ground-based LiDAR imaging. The modelled leaf-deposited PM10 mass was compared to gravimetric results within three different particle size fractions (0.2–3, 3–10 and >10μm), obtained at 20 locations within the tree crown. Modelling of the LiDAR-derived tree crown resulted in altered atmospheric PM10 concentrations in the vicinity of the tree crown. Although this model study was limited to a single tree and model configuration, our results demonstrate that improving tree crown characteristics (shape, dimensions and LAD) affects the resulting local PM10 distribution in ENVI-met. An accurate tree crown representation seems, therefore, of great importance when aiming at modelling the local PM distribution.

Major heat waves of 2003 and 2006 and health outcomes in Prague

We have investigated the association between heat waves and mortality and hospital admissions for Prague inhabitants for the summer heat waves of August 2003 and July 2006. The effect of heat waves was investigated using negative binomial regression in a generalized additive model. We used a linear model on a logarithmic scale, having 1-day lagged temperature differences from the long-term average, 1-day lagged ambient O3 and PM10 concentration, relative humidity, simple “heat wave” indicator, and smooth seasonal effect as explanatory variables. We found a small increase in daily mortality for the examined period. This increase can be attributed to PM10 concentrations in most cases, and in fewer instances, to air temperature and O3 concentrations. The “heat wave” indicator did not significantly increase the relative risk; the same held for the relative humidity. For the general unstratified population, the highest increase in relative risk of 1.072 (95% CI 1.001–1.147) was observed for cardiovascular mortality and was associated with an increase in temperature of 10 °C, followed by an increase in relative risk of 1.056 (95% CI 1.025–1.087) for respiratory mortality associated with an increase in O3 concentrations by 10 μg.m−3. A higher risk in most cases was found for women. A significant increase of relative risk of 1.013 (95 % CI 1.002–1.024) due to PM10 was found for hospital admissions for cardiovascular causes. This issue should be studied further in view of the anticipated increase in meteorological extremes, including heat waves, in the future, to prepare prevention plans for eliminating their negative effects as far as possible.

Estimating acute cardiovascular effects of ambient PM2.5 water-soluble metals

Introduction. Health effects of fine particulate matter (PM2.5) are thought to differ by chemical composition. Among PM components, transition metals may be biologically-relevant due to their potential of inducing oxidative stress. Few studies have estimated associations between individual metals and health outcomes, particularly the more bioavailable water-soluble metal fractions. Methods. Ambient concentrations of PM2.5 water-soluble vanadium (V), chromium, manganese, iron (Fe), nickel, and copper were measured daily during 1998-2008 and 1-in-3 days during 2009-2013 at a central site in Atlanta. PM2.5 mass, PM2.5 major components, and criteria gases were also measured. We estimated associations between daily counts of cardiovascular emergency department (ED) visits and daily pollutant levels in a time-series framework using Poisson regression. Analyses were conducted separately in earlier (1998-2008) and later (2008-2013) periods to account for changes in lab protocols. Results. In the earlier period, all metals except for Fe were below detection on over 50% of days. During this period, Fe and V were associated with cardiovascular ED visits [rate ratios (95% CIs) of 1.012 (1.005, 1.018) and 1.010 (1.002, 1.019) per interquartile range increase]. The Fe association had little change when controlling for PM2.5 mass, major components, or criteria gases one at a time in two-pollutant models. V was not sufficiently detected during 1998-2008 and thus not included in two-pollutant analyses. In the later period, detection for metals was improved with changes to lab protocols, the measured concentrations were generally lower for all pollutants, and associations for most pollutants were weaker. Conclusions. Ambient PM2.5 water-soluble metals are not routinely measured and their health effects are not well understood. We found water-soluble Fe and V associated with cardiovascular outcomes. More studies are needed to understand if they are health-relevant components of PM2.5.

Ambient Air Pollution Exposures and Risk of Parkinson Disease.

Background:Few epidemiologic studies have evaluated the effects of air pollution on the risk of Parkinson disease (PD).Objective:We investigated the associations of long-term residential concentrations of ambient particulate matter (PM) < 10 μm in diameter (PM10) and < 2.5 μm in diameter (PM2.5) and nitrogen dioxide (NO2) in relation to PD risk.Methods:Our nested case–control analysis included 1,556 self-reported physician-diagnosed PD cases identified between 1995 and 2006 and 3,313 controls frequency-matched on age, sex, and race. We geocoded home addresses reported in 1995–1996 and estimated the average ambient concentrations of PM10, PM2.5, and NO2 using a national fine-scale geostatistical model incorporating roadway information and other geographic covariates. Air pollutant exposures were analyzed as both quintiles and continuous variables, adjusting for matching variables and potential confounders.Results:We observed no statistically significant overall association between PM or NO2 exposures and PD risk. However, in preplanned subgroup analyses, a higher risk of PD was associated with higher exposure to PM10 (ORQ5 vs. Q1 = 1.65; 95% CI: 1.11, 2.45; p-trend = 0.02) among women, and with higher exposure to PM2.5 (ORQ5 vs. Q1 = 1.29; 95% CI: 0.94, 1.76; p-trend = 0.04) among never smokers. In post hoc analyses among female never smokers, both PM2.5 (ORQ5 vs. Q1 = 1.79; 95% CI: 1.01, 3.17; p-trend = 0.05) and PM10 (ORQ5 vs. Q1 = 2.34; 95% CI: 1.29, 4.26; p-trend = 0.01) showed positive associations with PD risk. Analyses based on continuous exposure variables generally showed similar but nonsignificant associations.Conclusions:Overall, we found limited evidence for an association between exposures to ambient PM10, PM2.5, or NO2 and PD risk. The suggestive evidence that exposures to PM2.5 and PM10 may increase PD risk among female never smokers warrants further investigation.Citation:Liu R, Young MT, Chen JC, Kaufman JD, Chen H. 2016. Ambient air pollution exposures and risk of Parkinson disease. Environ Health Perspect 124:1759–1765; http://dx.doi.org/10.1289/EHP135

Study of relationship between content of fine particulate matter in atmospheric and the number of emergency room visits with acute coronary syndrome

Objective To explore the relationship between content of fine particulate matter (PM2.5) in atmospheric and the number of emergency room(ER) visits with acute coronary syndrome(ACS). Methods Daily data of ER visits to Peking University Third Hospital for ACS was collected from December 1st, 2013 to November 30th, 2014. All patients were resident population of Haidian District, Beijing. The daily meteorological data and contents of air pollutants in Beijing were also collected in the same time period. Generalized Additive Model(GAM)was fitted to estimate the association between the ambient PM2.5 and the ER visits for ACS, under controlling for time trends, holiday effect, day of week effect and weather conditions. Results The annual average amount of PM2.5 was 85.44 μg/m3 over the study period. There were 619 cases with ACS as ER visits. PM2.5 was positive related with PM10, NO2 and SO2. The corresponding correlation coefficients were 0.87, 0.48 and 0.67, respectively (P<0.05). But PM2.5 was negative related with mean temperature (r=-0.04, P<0.05). In the polluted model, there was positive association between PM2.5 and ER visits with ACS. When each increament in PM2.5 with 10 μg/m3 , the relative risk strength of ER visits with ACS was 1.019 (95%CI: 1.000-1.038). PM2.5 concentrations had a delayed effect on the onset of ACS occurred on the next day. This lagged 1 day phenomenon showed the most significant influence of PM2.5 on ER visits for ACS. Conclusions The ambient concentrations of PM2.5 are positively associated with ER visits for ACS. And there is a lag effect. Key words: Acute coronary syndrome; Fine particulate matter; Emergency room visits; Generalized additive model; Air pollution; Lag effect

Observations of ambient trace gas and PM10 concentrations at Patna, Central Ganga Basin during 2013–2014: The influence of meteorological variables on atmospheric pollutants

Atmospheric pollutants including ozone (O3), sulfur dioxide (SO2), oxides of nitrogen (NOx), carbon monoxide (CO), and inhalable particulate matter (PM10) were measured in the central Indo-Gangetic Basin (IGB) at Patna, India, from 1st March 2013 to 31st December 2014, and significant variability was observed in the temporal patterns of these pollutant concentrations. The mean O3, SO2, NO, NO2, CO (trace gases: TG), and PM10 (PM) concentrations were 14.5±4.8, 5.9±4.8, 23.1±22, 20.6±14.6ppb, 1.5±0.7ppm, and 192.0±132.8μg/m3, respectively, over the study period. The highest concentrations of these species were during the post-monsoon and winter seasons except O3 and SO2 that showed the highest concentrations during the pre-monsoon. The lowest concentrations of TG and PM were observed during the monsoon season as a result of scavenging by rain. NO and NO2 along with PM concentrations decreased by ~76, 19, and 63% when the wind speed (WS) was >0.5m/s. However, for O3, an opposite trend was observed with ~14% higher concentrations. The WS was negatively correlated with PM during the winter (−0.48) and post-monsoon (− 0.32) seasons. In order to investigate the source region of TG and PM, 5-day air mass back trajectories were computed. The dominance of the air masses (92, 53, and 49%) were from the IGB is highly polluted during the winter, pre-monsoon, and post-monsoon, respectively. The TG and PM were observed much higher during these periods. During the biomass burning period (post-monsoon), the trajectory analysis showed that the TG and PM concentrations were around three-fold higher (flow from the IGB ) than the other seasons. To improve air quality over IGB, the mitigation measures should be designed to reduce emissions from both local and regional sources.