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Aug 13, 2014 - ABSTRACT: Although ambient PM2.5 has been linked to adverse health effects, the chemical constituents that cause harm are largely uncle...
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PM2.5 Constituents and Hospital Emergency-Room Visits in Shanghai, China Liping Qiao,†,§ Jing Cai,‡,§ Hongli Wang,*,† Weibing Wang,‡ Min Zhou,† Shengrong Lou,† Renjie Chen,‡ Haixia Dai,† Changhong Chen,† and Haidong Kan*,‡ †

State Environmental Protection Key Laboratory of the Formation and Prevention of Urban Air Pollution Complex, Shanghai Academy of Environmental Sciences, Shanghai, China ‡ School of Public Health, Key Lab of Public Health Safety of the Ministry of Education, and Key Lab of Health Technology Assessment of the Ministry of Health, Fudan University, Shanghai, China S Supporting Information *

ABSTRACT: Although ambient PM2.5 has been linked to adverse health effects, the chemical constituents that cause harm are largely unclear. Few prior studies in a developing country have reported the health impacts of PM2.5 constituents. In this study, we examined the short-term association between PM2.5 constituents and emergency room visits in Shanghai, China. We measured daily concentrations of PM2.5, organic carbon (OC), elemental carbon (EC), and eight water-soluble ions between January 1, 2011 and December 31, 2012. We analyzed the data using overdispersed generalized linear Poisson models. During our study period, the mean daily average concentration of PM2.5 in Shanghai was 55 μg/m3. Major contributors to PM2.5 mass included OC, EC, sulfate, nitrate, and ammonium. For a 1-day lag, an interquartile range increment in PM2.5 mass (36.47 μg/m3) corresponded to 0.57% [95% confidence interval (CI): 0.13%, 1.01%] increase of emergency room visits. In all the three models used, we found significant positive associations of emergency room visits with OC and EC. Our findings suggest that PM2.5 constituents from the combustion of fossil fuel (e.g., OC and EC) may have an appreciable influence on the health impact attributable to PM2.5.

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INTRODUCTION Epidemiological studies have reported that short- and longterm exposure to fine particulate matter (PM2.5, defined as particle less than 2.5 μm in aerodynamic diameter) contributes to increased cardiopulmonary mortality and morbidity.1 The health impact of PM2.5 varies regionally, which might be explained by heterogeneity in particles’ chemical composition and sources.2 In North America and Europe, several studies have been conducted to link certain PM2.5 constituents and sources with adverse health outcomes.2−5 Understanding of the local health effects of PM2.5 constituents is important in setting air pollution control policy from a public health viewpoint. As the largest developing country, China may have the highest PM2.5 level in the world.6 According to the 2010 Global Burden of Disease (GBD 2010) study, PM2.5 contributes to over 1.2 million deaths and 24 million healthy years of life lost in China, ranking at number 4 among all risk factors contributing to the health burden.7 There have been no published PM2.5 cohort studies in China, though the relationship between PM2.5 mass and daily mortality has been examined in several Chinese cities, including Beijing,8 Chongqing,9 Shanghai,10 and Shenyang.11 Few studies in the country have investigated the adverse health impact of PM2.5 © 2014 American Chemical Society

constituents due to lack of monitoring data. To our knowledge, only one published study in China has investigated the health impacts of PM2.5 constituents on daily mortality.12 Moreover, few Chinese cities have established city-wide morbidity reporting systems, and consequently, data about the association between PM2.5 and morbidity outcomes are quite limited. In this study, we examine short-term associations between PM2.5 constituents and emergency-room visits in Shanghai, China.

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MATERIALS AND METHODS Data. Health Data. Our study area included nine urban districts in Shanghai (Supporting Information (SI) Figure S1). Approximately seven million permanent residents live in the study area, which has an area of 279 km2. We obtained the numbers of daily hospital emergency-room visits for all diagnoses combined for the residents living in the nine urban districts between January 1, 2011 and December 31, 2012 (731 Received: Revised: Accepted: Published: 10406

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Automatic Stations of Ambient Air Quality in Shanghai based on the national specification HJ/T193-2005, which was developed following the technical guidance established by the U.S. EPA.18 In addition, external standard solution calibration for MARGA and sucrose solution calibration for OC/EC analyzer were carried out quarterly. To control for the effect of gaseous pollutants and weather on emergency room visits, we obtained daily mean concentrations of sulfur dioxide (SO2) and nitrogen dioxide (NO2) from the Shanghai Environmental Monitoring Center, and daily mean temperature and relative humidity (RH) from Shanghai Meteorological Bureau. The gaseous pollutant concentrations were averaged from the available monitoring results across six stations in our study area (SI Figure S1-b). For the calculation of daily concentrations of SO2 and NO2, at least 75% of the 1 h values must be available on that particular day. If a station had more than 25% of the values missing for the whole period of analysis, the entire station was excluded. Statistical Methods. We examined the associations between daily emergency room visits and PM2.5 constituents with time-series analyses.19 Specifically, we employed overdispersed generalized linear Poisson models (quasi-likelihood) with natural spline (ns) smoothers to analyze daily emergency room visits, PM2.5 constituents, and covariate data. We used ns functions of time to control for long-term and seasonal trends of emergency room visits.20 We used partial autocorrelation function (PACF) to guide the selection of degrees of freedom (df) for the time trend until the absolute values of the sum of PACF of the residuals for lags up to 30 reached a minimal value.21 Residuals were examined to check whether there were discernible patterns and autocorrelation by means of residual plots and PACF plots. As the result, 7 df per year for time trend was used for emergency room visits. We included day of the week (DOW) as a dummy variable, and used ns functions with 3 df for temperature and RH during the whole study period.22 We then included the pollutant concentrations in the model. We used three models to estimate associations of PM2.5 constituents with emergency room visits:23 (1) constituent concentration without adjustment for PM2.5 mass; (2) constituent concentration adjusting for PM2.5 mass; and (3) PM2.5-adjusted constituent residuals which were obtained by constructing a linear regression model with constituent concentration as the dependent variable and PM2.5 mass as the independent variable. We examined the effect of PM2.5 constituents with different lag structures from lag 0 to lag 3, given that previous epidemiologic studies of PM2.5 in China found little evidence of significant associations with a lag over 3 days.10 A lag of day 0 (lag 0) refers to the current-day PM2.5 constituents, and a lag of day 1 (lag 1) corresponds to the previous-day PM2.5 constituents. We also used the spline with 3 df to graphically describe the relationship of PM2.5 constituents with emergency room visits; to compare the linear and spline models, we computed the difference between the deviances of the two fitted models. We conducted several sensitivity analyses to examine the robustness of our findings. First, we examined the effect of PM2.5 constituents with extended lag structures until 1 week (7 days). Second, we tested the impact of alternative df selection on the regression results. Third, we compared the effects of PM2.5 constituents before and after adjustment for SO2 and NO2. Fourth, because previous study has shown that PM2.5 mixture may modify the health effects of PM2.5 mass,24 we

days) from the Shanghai Health Insurance Bureau (SHIB). The SHIB is the government agency that administers the Shanghai Health Insurance System. The Shanghai Health Insurance System, which provides compulsory universal health insurance, covers most of the permanent residents in Shanghai (the coverage rate was 95% in 2008). In Shanghai, all hospitals are under contract with the SHIB. Computerized records of hospital emergency-room visits are maintained at each contracted hospital and then sent to the SHIB through an internal computer network. Pollutant and Meteorological Data. The ambient monitoring site was located on the rooftop of a five-story building about 15 m high above the ground at Shanghai Academy of Environmental Sciences (SAES, 31.17° N, 121.43° E) in the southwest of the central urban area of Shanghai.13 The site was mostly surrounded by commercial properties and residential dwellings. The mass concentration of PM2.5 was measured by an online particulate monitor (FH 62 C14 series, Thermo Fisher Scientific Inc.) using beta attenuation techniques equipped with a verified PM2.5 cyclone. The instrument collected ambient PM onto a quartz filter tape through a vertically mounted stainless steel tube and measured the attenuation of the C14 source beta rays continuously which was proportional to the filter loading. The sample flow rate was 16.7 L/min and the sample tube was heated to 45 °C. The carbonaceous concentrations in PM2.5 were measured by a semicontinuous OC/EC analyzer (model RT-4, Sunset Laboratory Inc.) equipped with a PM2.5 cyclone and an upstream parallel-plate organic denuder (Sunset Laboratory Inc.). Ambient particulate was sampled on a quartz filter in the oven at a flow rate of 8.0 L/min, and analyzed by the thermaloptical transmittance method (TOT) with a two-stage thermal procedure (600−840 °C in a He atmosphere and 550−650− 870 °C in an oxidizing atmosphere of 2% O2 with He as diluent gas). The time resolution was 1 h for each sample with 45 min of sampling and 15 min of analysis. The concentrations of eight major water-soluble inorganic ions in PM2.5 (Cl−, NO3−, SO42−, Na+, NH4+, K+, Mg2+, Ca2+) were measured by a commercial instrument for online monitoring of aerosols and gases (MARGA, model ADI 2080, Applikon Analytical B.V.). The principle and operation of this instrument has been described in detail elsewhere.14−17 Briefly, ambient air was drawn at the flow rate of 16.7 L/min through a PM2.5 cyclone. The sample air was first drawn through a wet rotating annular denuder (WRD) where watersoluble gases diffused to the absorption solution (0.0035% H2O2), then particles were collected in a stream-jet aerosol collector (SJAC). The absorption solutions were drawn from the WRD and the SJAC to syringes and subsequently injected to ion chromatographs (IC, conductivity detector, Metrosep C4-100/4.0 column and 3.2 mmol/L CH3SO3H eluent for cation, Metrosep A Supp 10-75/4.0 column and 7.0 mmol/L Na 2 CO 3 + 8.0 mmol/L NaHCO 3 eluent with H 3 PO 4 suppressor for anion) with an internal standard (LiBr) for components analysis for every hour. The detection limits of all components were 0.10 μg/m3 or better, except for K+ (0.16 μg/ m3), Mg2+ (0.12 μg/m3), and Ca2+ (0.21 μg/m3).16 The routine quality assurance (QA) and quality control (QC) procedures, including instrument maintenance and cleaning, air flow rate calibration, mass foil calibration, and temperature/pressure sensor calibration for PM2.5 monitor, etc. were conducted according to the Technical Guideline of 10407

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Table 1. Distribution of Daily Data on Emergency-Room Visits and Weather Conditions in Shanghai, China (2011−2012) mean ± SD 13,608 ± 2,342 16.9 ± 9.3 69.1 ± 12.7

emergency-room visits temperature (°C) relative humidity (%)

P(25) 12,188 8.3 61

min 9,249 −1.7 30

P(50) 13,169 18.3 70

P(75) 14,497 24.7 79

max 25,984 33.6 95

Table 2. Descriptive Statistics for Air Pollutants in Shanghai, China (2011−2012)

a

pollutant

observation number

mean ± SD (μg/m3)

min

max

IQRa (μg/m3)

percent PM2.5 mass (%)

PM2.5 SO2 NO2 OC EC Na+ NH4+ K+ Mg2+ Ca2+ SO42− NO3− Cl−

680 731 731 662 662 474 671 671 670 664 671 671 671

54.94 ± 37.04 31.30 ± 17.60 59.13 ± 20.02 9.21 ± 4.95 2.10 ± 1.21 0.40 ± 0.19 5.65 ± 4.46 1.37 ± 1.40 0.16 ± 0.14 0.85 ± 0.73 9.92 ± 6.27 8.73 ± 7.81 2.01 ± 1.82

10.84 6.00 16.00 2.75 0.38 0.06 0.05 0.00 0.00 0.03 1.29 0.26 0.05

262.70 112.00 131.20 38.39 7.94 2.22 33.27 21.96 1.98 6.25 44.47 58.36 16.87

36.47 24.00 28.80 5.52 1.39 0.19 4.85 0.62 0.13 0.65 6.89 7.98 2.17

16.75 3.82 0.72 10.29 2.49 0.29 1.54 18.05 15.88 3.67

IQR: interquartile range.

Table 3. Correlations among PM2.5 Mass and Constituents in Shanghai, China (2011−2012) PM2.5 OC EC SO42− NO3− Na+ NH4+ K+ Mg2+ Ca2+ Cl−

PM2.5 1 0.86 0.74 0.80 0.85 0.11 0.82 0.53 0.21 0.19 0.68

OC

EC

SO42−

NO3−

Na+

NH4+

K+

Mg2+

Ca2+

Cl−

1 0.85 0.73 0.81 0.15 0.79 0.48 0.08 0.15 0.59

1 0.63 0.70 0.19 0.72 0.29 −0.05 0.18 0.50

1 0.78 0.11 0.91 0.47 0.08 −0.04 0.53

1 0.13 0.91 0.43 0.12 0.13 0.63

1 0.14 0.17 0.26 0.01 0.12

1 0.42 0.01 −0.07 0.58

1 0.49 −0.11 0.65

1 0.43 0.31

1 0.07

1

3.82% of the total PM2.5 mass, respectively (Table 2). Other large contributors to PM2.5 were SO42− (18.05%), NO3− (15.88%), NH4+ (10.29%), and Cl− (3.67%). Generally, moderate to high correlations (r = 0.53−0.86) were observed for PM2.5 with OC, EC, SO42−, NO3−, NH4+, K+, Cl−, and Mg2+ (Table 3). PM2.5 was weakly correlated with Na+ (r = 0.11) and Ca2+ (r = 0.19). Figure 1 presents the quantitative regression results for lags 0−3 of PM2.5 mass and various constituents (without adjustment for PM2.5). PM2.5 mass (lag 0 and 1) was significantly associated with emergency room visits; for a 1day lag, an IQR increment in PM2.5 mass (36.47 μg/m3) corresponded to 0.57% (95% confidence interval (CI): 0.13%, 1.01%) increase of emergency room visits. Consistent with previous studies,12,25 the effect estimates of PM2.5 constituents varied by lag structures. Half of the associations assessed were positive and statistically significant for OC (lag 0 and 1), EC (lag 0 and 1), NO3− (lag 0 and 1), Cl− (lag 2 and 3), and Na+ (lag 2 and 3). At least one positive significant association was observed for NH4+ (lag 0), SO42− (lag 0), Ca2+ (lag 2), K+ (lag 2), and Mg2+ (lag 2). Figure 2 shows the effect estimates of PM2.5 constituents after further adjustment for PM2.5 mass. We observed significant associations of emergency room visits with OC

examined the effects of PM2.5 stratified by relative proportion of SO42−, NO3−, NH4+, elemental carbon (EC), and organic carbon (OC). We conducted all analyses in R 2.15.1 with the MGCV package. The results are presented as the percent change in daily emergency room visits per interquartile range (IQR) increase of pollutant concentrations. We defined statistical significance as p < 0.05.

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RESULTS From 2011 to 2012, a total of 9 948 065 emergency room visits were recorded in our study population. On average, there were 13 608 emergency room visits per day (Table 1). The average temperature and RH were 16.9 °C and 69.1%, respectively, reflecting the subtropical climate in Shanghai. The mean daily average concentration of PM2.5 was 54.94 μg/m3 in Shanghai during 2011−2012 (Table 2), which was 5 times higher than the Global Guidelines set by the World Health Organization (WHO) (annual average: 10 μg/m3). Meanwhile, the mean daily average concentrations of SO2 and NO2 were 31.30 and 59.30 μg/m3. There were 662 observations of OC and EC during the 2 years (731 days); the averaged concentrations were 9.21 μg/m3 for OC and 2.10 μg/m3 for EC, accounting for 16.75% and 10408

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Figure 2. Estimated percent increase (mean (95% CI)) in emergency room visits per IQR increase in PM2.5 constituent concentrations on the current day (lag 0) or the previous 1−3 days (lag 1, 2, and 3), adjusted for PM2.5 mass, temporal trend, day of the week, temperature, relative humidity, and SO2 and NO2 concentrations. Figure 1. Estimated percent increase (mean (95% CI)) in emergency room visits per IQR increase in PM 2.5 and its constituent concentrations on the current day (lag 0) or the previous 1−3 days (lag 1, 2, and 3), adjusted for temporal trend, day of the week, temperature, relative humidity, and SO2 and NO2 concentrations.

SO42−, K+, and Mg2+ were no longer positively and statistically significantly associated with emergency room visits, and some of the adjusted associations even became negative (e.g., SO42−). Figure 3 shows the results for PM2.5-adjusted constituent residuals. Among various constituents, only OC (lag 0 and 1) and EC (lag 0 and 1) remained significantly associated with emergency room visits. For example, an IQR increase in 1-day

(lag 0 and 1), EC (lag 0 and 1), NO3− (lag 0 and 1), Ca2+ (lag 2), Cl− (lag 2 and 3), and Na+ (lag 2 and 3). However, NH4+, 10409

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room visits. We did not observe evidence of obvious threshold concentrations below which these pollutants had no health effects. The differences in the deviance between the linear and spline models were statistically insignificant. In the sensitivity analyses, we generally did not observe statistically significant associations with extended lag structures (4−7 days) (SI Figure S2). Alternative df/year options for time trend and adjustment for gaseous pollutants (SO2 and NO2) did not substantially affect the estimated effects of pollutants (SI Figures S3−S4). We did not find a clear pattern whether the PM2.5 effects would be enhanced when particles were enriched in secondary constituents (e.g., SO42−, NO3−, or NH4+) (SI Table S1).

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DISCUSSION This study showed that PM2.5 mass and several constituents (e.g., OC and EC) were associated with increased risk of emergency room visit in Shanghai. The observed levels of PM2.5 and its constituents in our study were much higher than those in developed countries. The constituents (OC and EC) that were associated with emergency room visit are related with the combustion of fossil fuel (e.g., coal and oil) in Shanghai.26 We did not observe evidence of threshold concentrations below which PM2.5 and its constituents were not associated with emergency room visits. To our knowledge, this is the first study of its kind in a developing country to investigate the impact of PM2.5 constituents on hospital visits. Among PM2.5 constituents, only OC and EC were significantly associated with emergency-room visits in all the three models we examined. Cardiovascular and respiratory diseases are the major causes of emergency room visits in China. In Beijing, for example, cardiovascular and respiratory disease accounted for 58.5% and 12.7% of total emergency room visits, respectively.27 Our positive finding of OC is consistent with previous studies that exposure to OC increases the risk of cardiopulmonary diseases. For example, Vedal and colleagues found strong evidence for associations of OC with subclinical and clinical cardiovascular outcomes in the MultiEthnic Study of Atherosclerosis and Women’s Health Initiative.4 Exposure to OC was also associated with increased nitric oxide in exhaled breath, a marker of airway inflammation.28 Moreover, an intervention study during the Beijing Olympics in 2008 showed that reduced ambient level of OC was associated with improved cardiopulmonary outcomes.29 Consistent with a meta-analysis of the acute effects of EC,30 our analysis indicates positive associations of emergency room visits with EC even after adjustment for PM2.5 mass. Several previous studies support the biological plausibility of a link between exposure to EC and exacerbations of cardiopulmonary diseases. In 24 Boston residents 61−88 years of age, short-term exposure to EC was associated with ST-segment depression, possibly representing myocardial ischemia or inflammation.31 In three European cities, Lanki et al. examined the associations of five PM2.5 components (Si, S, Ni, Cl, and EC) with occurrence of ST-segment depression, and found only EC had significant effect in multipollutant models.32 EC and black carbon (BC) are operationally defined according to the measurement method that is applied, and the terms are often used interchangeably.30 Given the accumulating evidence of its independent health effects, BC was recommended to be incorporated into the WHO air quality guidelines.33 In Beijing, recent exposure to BC was associated with acute respiratory inflammation in schoolchildren.34 The major sources of EC are

Figure 3. Estimated percent increase (mean (95% CI)) in emergency room visits per IQR increase in PM2.5-adjusted constituent residuals on the current day (lag 0) or the previous 1−3 days (lag 1, 2, and 3), adjusted for temporal trend, day of the week, temperature, relative humidity, and SO2 and NO2 concentrations.

lagged OC and EC was associated with 0.99% (95% CI: 0.06%, 1.92%) and 1.05% (95% CI: 0.26%, 1.84%) increase in emergency room visits, respectively. Figure 4 graphically shows the exposure−response relationships for PM2.5 mass and selected constituents (OC and EC) because they show the strongest associations with emergency 10410

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Figure 4. Smoothing plots of PM2.5, OC, and EC concentrations against emergency room visits (df = 3), adjusted for temporal trend, day of the week, temperature, relative humidity, and SO2 and NO2 concentrations. X-axis is the pollutant concentrations (μg/m3). Y-axis is the estimated percent change in emergency room visits (%). The solid lines indicate the estimated mean percent change (%) in daily emergency room visits using the lowest pollutant concentration as the reference level, and the dotted lines represent the 95% CI.

motorized vehicles, coal burning, shipping emissions, and industrial sources in Shanghai;26 therefore, EC might serve as an indicator for the larger category of primary combustion particles in the city. It is possible that we observed a more robust association for EC because it more closely resembles the harmful components in air pollution mixtures than it resembles general PM.33 We did not find significant associations for NO3− or SO42− in the model using PM2.5-adjusted constituent residuals. NO3− is acidic in nature. There has been no convincing toxicological evidence of NO3− effects at typical ambient levels. Current epidemiologic evidence on the health risks of NO3− has been conflicting. For example, one study in Hong Kong found significant associations of NO3− with cardiovascular hospitalization after controlling for copollutants,35 while several others did not report significant associations.25,36 More studies are needed to investigate the health effects of NO3−. Also, our negative findings of SO42− were consistent with previous epidemiologic studies in other Chinese cities.12,35 SO42− at typical environmental concentrations generally did not show evidence of toxic effects on the cardiopulmonary system. For example, controlled exposure studies of healthy adults have shown no consistent effects on pulmonary function or respiratory symptoms following acute exposures to SO42− at concentrations >1000 μg/m3, even with exercise.37

The shape of exposure−response relationships is crucial for public health assessment and there has been growing demand for providing the relevant curves. Consistent with previous multicity studies in the U.S. and Europe,1 our study generally supported linear associations without threshold for PM2.5 and its constituents (Figure 4). However, our analysis of exposure− response relationships is limited by the use of data from a single city. Future multicity analysis in China should address this limitation and further explore the role of effect modifiers in explaining the heterogeneity in the shape of the exposure− response relationships. Quantitative knowledge about the relationship between PM2.5 and health outcomes is crucial to assessing the disease burden of air pollution. In our analysis, a 10-μg/m3 increment in the 1-day lagged PM2.5 concentrations was associated with 0.16% increases in emergency-room visits. Our effect estimate per unit increase in PM2.5 was relatively lower compared with studies of PM2.5 and emergency-room visit in developed countries where PM2.5 levels are much lower.38−41 For instance, in Atlanta, a 10-μg/m3 increase of PM2.5 was associated with 3.3% increases in emergency department visits for cardiovascular disease38 and 1.6% increases for respiratory disease.39 In Doña Ana County, New Mexico, 10-μg/m3 increase of PM2.5 was associated with 3.0% increases in emergency-room visits for cardiovascular disease and 4.5% increases for respiratory disease.41 In Graz and Linz, Austria, cardiorespiratory 10411

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ambulance transports increased with PM2.5 by 6.1% per 10 μg/ m3 on the same day.40 Our findings generally support prior evidence suggesting smaller effect estimates of unit increase in air pollution in China than in developed countries.42 Characteristics of the study sites, such as sensitivity of local residents to PM2.5 (e.g., socio-economic status, age, smoking rate), transport of pollutants from outdoor air to indoor, and PM2.5 levels, may affect the magnitudes of exposure−response relationships. Our result was also consistent with recent finding on the integrated exposure response (IER) function suggesting that the relationship between PM2.5 levels and health risk is likely to be nonlinear and tend to become flat at the higher end.43 Our study has limitations. First, we examined associations of multiple constituents and lags, and some significant associations therefore may have been detected by chance. Second, we did not measure elements, especially transition metals such as nickel (Ni), selenium (Se), and vanadium (V), though these elements have been reported to be associated with adverse health outcomes.3 Third, we used the monitoring results from one fixed station as a proxy measure for population exposures to PM2.5 constituents. The difference between ambient concentrations and true exposures is an inherent and unavoidable type of measurement error. Moreover, the extent of exposure misclassification may vary among individual constituents, and may influence associations. Fourth, we had no access to the patients’ individual characteristics, such as their age, sex, socioeconomic status, or disease classification, limiting our ability to link potentially sensitive subpopulations and specific diseases to PM2.5 constituents. Thus, we have probably underestimated the effect of PM2.5 constituents on emergencyroom visits because we accounted for the total emergency-room visits only. Previous studies in China have examined the possible biological mechanisms and plausible disease categories associated with PM2.5 exposure.44,45 Finally, we did not conduct source apportionment of PM2.5 constituents, and therefore cannot identify the sources responsible for the adverse health effects. Conclusively, our findings provide evidence linking daily emergency room visits with PM2.5 constituents from fossil fuel combustion, such as OC and EC. Our results lend support to the growing body of literature concerning PM2.5-related health effects in China, and suggest that combustion-related particles are particularly important.

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ACKNOWLEDGMENTS The study was supported by the National Basic Research Program (973 program) of China (2011CB503802), China Medical Board Collaborating Program (13-152), National Natural Science Foundation of China (81222036), and National Environmental Public Welfare Research Program of Ministry of Environmental Protection of China (201409008, 201209008, 201209007, 201209001).

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ASSOCIATED CONTENT

S Supporting Information *

A map of the study area and detailed results for sensitivity analyses. This material is available free of charge via the Internet at http://pubs.acs.org/.

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AUTHOR INFORMATION

Corresponding Authors

*(H.K.) Telephone/fax: +86 21 54237908; e-mail: [email protected]; mail: 130 Dong-An Road, Shanghai 200032, China. *(H.W.) Telephone/fax: +86 21 64085119; e-mail: wanghl@ saes.sh.cn; mail: 508 Qin-Zhou Road, Shanghai 200233, China. Author Contributions §

L.Q. and J.C. contributed equally to this work.

Notes

The authors declare no competing financial interest. 10412

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