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Heavy air pollution attacked Beijing and its surrounding areas in January of 2013, which attracted large attentions from around the world. In this study, we conducted highly time-resolved measurements of inorganic ions associated with PM2.5 at an urban site in Beijing during this period. We applied the curve fitting method, the quantile regression model and the probability function model to evaluate the relationship between secondary inorganic ions (sulfate, nitrate and ammonium, SNA) and meteorological parameters (relative humidity (RH) and temperature). In our model results, RH was regarded as one of the key factors of high concentrations of SNA, and high level of RH would enhance the concentrations of SNA. In addition, the effect of temperature was also important and noticeable. We further constructed a probability function model to investigate the joint effects of RH and temperature. The model results showed higher RH and a temperature of approximately −5 °C (−4∼-6 °C for sulfate and nitrate; −5∼-7 °C for ammonium) would be the most suitable conditions for the high concentrations of SNA during the air pollution episodes in Beijing.

To evaluate the potential benefits of biomass use for air pollution control, this paper identified and quantified the emissions of major reactive organic compounds anticipated from biomass-fired industrial boilers. Wood pellets (WP) and straw pellets (SP) were burned to determine the volatile organic compound emission profiles for each biomass-boiler combination. More than 100 types of volatile organic compounds (VOCs) were measured from the two biomass boilers. The measured VOC species included alkanes, alkenes and acetylenes, aromatics, halocarbons and carbonyls. A single coal-fired boiler (CB) was also studied to provide a basis for comparison. Biomass boiler 1 (BB1) emitted relatively high proportions of alkanes (28.9%–38.1% by mass) and alkenes and acetylenes (23.4%–40.8%), while biomass boiler 2 (BB2) emitted relatively high proportions of aromatics (27.9%–29.2%) and oxygenated VOCs (33.0%–44.8%). The total VOC (TVOC) emission factors from BB1 (128.59–146.16 mg/kg) were higher than those from BB2 (41.26–85.29 mg/kg). The total ozone formation potential (OFP) ranged from 6.26 to 81.75 mg/m3 with an average of 33.66 mg/m3 for the two biomass boilers. The total secondary organic aerosol potential (SOAP) ranged from 61.56 to 211.67 mg/m3 with an average of 142.27 mg/m3 for the two biomass boilers. The emission factors (EFs) of TVOCs from biomass boilers in this study were similar to those for industrial coal-fired boilers with the same thermal power. These data can supplement existing VOC emission factors for biomass combustion and thus enrich the VOC emission inventory.

Modeling fine-scale spatial and temporal patterns of air pollutants can be challenging. Advanced spatio-temporal modeling methods were used to predict both long-term and short-term concentrations of six criteria air pollutants (particulate matter with aerodynamic diameter less than or equal to 10 and 2.5 μm [PM10 and PM2.5], SO2, NO2, ozone and carbon monoxide [CO]) in Beijing, China. Monitoring data for the six criteria pollutants from April 2014 through December 2017 were obtained from 23 administrative monitoring sites in Beijing. The dimensions of a large array of geographic covariates were reduced using partial least squares (PLS) regression. A land use regression (LUR) model in a universal kriging framework was used to estimate pollutant concentrations over space and time. Prediction ability of the models was determined using leave-one-out cross-validation (LOOCV). Prediction accuracy of the spatio-temporal two-week averages was excellent for all of the pollutants, with LOOCV mean squared error-based R2 (R2mse) of 0.86, 0.95, 0.90, 0.82, 0.94 and 0.95 for PM10, PM2.5, SO2, NO2, ozone and CO, respectively. These models find ready application in making fine-scale exposure predictions for members of cohort health studies and may reduce exposure measurement error relative to other modeling approaches.

Nitrate (NO3−) is a key component of secondary inorganic aerosols and PM2.5. However, the contributions of nitrogen oxides (NOx) emission sources to NO3− in PM2.5 remain poorly constrained. This study measured nitrogen (N) isotopes of NO3− (hereafter as δ15N-NO3-) in PM2.5 collected at Beijing in 2014. We observed that δ15N-NO3- values in PM2.5 (−2.3‰ − 19.7‰; 7.3 ± 5.4‰ annually) were significantly higher in winter (11.9 ± 4.4‰) than in summer (2.2 ± 2.5‰). The δ15N differences between source NOx and NO3− in PM2.5 (hereafter as Δ values) were estimated by a computation module as 7.8 ± 2.2‰ − 10.4 ± 1.6‰ (8.8 ± 2.4‰). Using the Δ values and δ15N values of NOx from major fossil (coal combustion, vehicle exhausts) and non-fossil sources (biomass burning, microbial N cycle), contributions of major NOx sources to NO3− in PM2.5 were further estimated by the SIAR model. We found that seasonal variations of δ15N-NO3- values in PM2.5 of Beijing were mainly caused by those of NOx contributions from coal combustion (38 ± 10% in winter, 20 ± 9% in summer). Annually, NOx from coal combustion, vehicle exhausts, biomass burning, and microbial N cycle contributed 28 ± 12%, 29 ± 17%, 27 ± 15%, and 16 ± 7% to NO3− in PM2.5, respectively, showing actually comparable contributions between non-fossil NOx (43 ± 16%) and fossil NOx (57 ± 21%). These results are useful for planning the reduction of NOx emissions in city environments and for elucidating relationships between regional NOx emissions and atmospheric NO3− pollution or deposition.

Background: Experimental research suggests that fine particulate matter (PM2.5) exposure might affect embryonic development. However, only few population-based studies have investigated the impact of maternal exposure to PM2.5 on the early pregnancy loss. Objectives: To estimate associations between clinically recognized early pregnancy loss (CREPL) and exposure to ambient PM2.5 at individual residences during peri-conception periods, with the aim to identify susceptible exposure time windows. Methods: CREPL cases and normal early pregnancy controls (of similar age and gravidity presenting within one week, a total of 364 pairs) were recruited between July 2017 and July 2018 among women residing in Tianjin, China. Average ambient PM2.5 concentrations of ten exposure windows (4 weeks, 2 weeks and 1 week before conception; the first, second, third and fourth single week, the first and second 2-week periods, and the entire 4-week period after conception) at the women's residential addresses were estimated using temporally-adjusted land use regression models. Associations between PM2.5 exposures at specific peri-conception time windows and CREPL were examined using conditional logistic regression models, adjusted for covariates. Results: Based on adjusted models, CREPL was significantly associated with a 10 μg/m3 increase in PM2.5 exposure during the second week after conception (OR = 1.15; 95% CI: 1.04, 1.27; p = 0.005), independent of effects at other time windows. There was also an association of CREPL with PM2.5 during the entire 4-week period after conception (OR = 1.22; 95% CI: 1.02, 1.46; p = 0.027). There was little evidence for associations with exposure during pre-conception exposure windows. Conclusions: Maternal exposures to ambient PM2.5 during a critical time window following conception are associated with CREPL, with the second week after conception possibly being the exposure window of most vulnerability. Future studies should focus on replicating these findings and on pathogenic mechanisms. Keywords: Adverse pregnancy outcomes, Air pollution, Land use regression models, Miscarriage, Particulate matter

Exposure to traffic-related air pollution (TRAP) may enhance the risk of cardiovascular disease. However, the short-term effects of TRAP components on the cardiovascular system are not well understood. We conducted a randomized, double-blinded, crossover intervention study in which 39 healthy university students spent 2 h next to a busy road. Participants wore a powered air-purifying respirator (PAPR) or an N95 mask. PAPRs were equipped with a filter for particulate matter (PM), a PM and volatile organic compounds (VOCs) filter or a sham filter. Participants were blinded to PAPR filter type and underwent randomized exposures four times, once for each intervention mode. Blood pressure (BP), heart rate (HR) and heart rate variability (HRV) were measured before, during and for 6 h after the roadside exposure. Linear mixed-effect models were used to evaluate the effects of the interventions relative to baseline controlling for other covariates. All HRV measures increased during and following exposure for all intervention modes. Some HRV measures (SDNN and rMSSD during exposure and SDNN after exposure) were marginally affected by PM filtration. Wearing the N95 mask affected VLF power and rMSSD responses to traffic exposure differently than the PAPR interventions. Both systolic and diastolic BP increased slightly during exposure, but then were generally lower than baseline after exposure for the sham and filter interventions. HR, which fell during exposure and mostly remained lower than baseline after exposure, was lower yet with all filter interventions compared to the sham mode following exposure. Therefore, short-term exposure to traffic acutely affects HRV, BP and HR, but N95 mask and PAPR interventions generally show little efficacy in reducing these effects. Removing the PM component of TRAP has some limited effects on HRV responses to exposure but exaggerates the traffic-related decrease in HR. HRV findings from N95 mask interventions need to be interpreted cautiously.

Background Evidence of maternal exposure to ambient air pollution on congenital heart defects (CHD) has been mixed and are still relatively limited in developing countries. We aimed to investigate the association between maternal exposure to air pollution and CHD in China. Method This longitudinal, population-based, case-control study consecutively recruited fetuses with CHD and healthy volunteers from 21 cities, Southern China, between January 2006 and December 2016. Residential address at delivery was linked to random forests models to estimate maternal exposure to particulate matter with an aerodynamic diameter of ≤ 1 µm (PM1), ≤2.5 µm, and ≤10 µm as well as nitrogen dioxides, in three trimesters. The CHD cases were evaluated by obstetrician, pediatrician, or cardiologist, and confirmed by cardia ultrasound. The CHD subtypes were coded using the International Classification Diseases. Adjusted logistic regression models were used to assess the associations between air pollutants and CHD and its subtypes. Results A total of 7055 isolated CHD and 6423 controls were included in the current analysis. Maternal air pollution exposures were consistently higher among cases than those among controls. Logistic regression analyses showed that maternal exposure to all air pollutants during the first trimester was associated with an increased odds of CHD (e.g., an interquartile range [13.3 µg/m3] increase in PM1 was associated with 1.09-fold ([95% confidence interval, 1.01–1.18]) greater odds of CHD). No significant associations were observed for maternal air pollution exposures during the second trimester and the third trimester. The pattern of the associations between air pollutants and different CHD subtypes was mixed. Conclusions Maternal exposure to greater levels of air pollutants during the pregnancy, especially the first trimester, is associated with higher odds of CHD in offspring. Further longitudinal well-designed studies are warranted to confirm our findings.

Air pollution is an increasing threat to human health in China. In this study, daily PM10 and PM2.5 samples were collected simultaneously at the Jinan Environmental Monitoring Station (EMS)in Jinan, China from 15 November 2016 to 15 March 2017. The aim of this work was to improve the understanding of the characteristics and sources of air particles and determine different levels of PM2.5 pollution and its constituent elements, water-soluble ions and carbonaceous species. Nitrate (NO3&minus, ), organic materials (OM) and sulfate (SO42&minus, ) were identified as the three main components of PM2.5 pollution. With increasing pollution level, the contributions of SO42&minus, NO3&minus, and NH4+ increased at greater rates, unlike that of OM. The proportion of SO42&minus, exceeded that of NO3&minus, and became predominant in severe PM2.5 pollution (SP, 250 &mu, g m&minus, 3 &le, PM2.5 &le, 500 &mu, 3). This work demonstrates that SO42&minus, has a dominant role in SP level and, consequently, requires greater research attention. It is demonstrated that relative humidity (RH) enhances the rate of sulfate formation more than that of nitrate. Therefore, under the current Chinese emergency response measures, it is necessary to further reduce emissions of SO2 and NO2. Four clusters of backward trajectories identified dominant pollution vectors originating from highly industrialized areas that exacerbate the poor air quality in Jinan. It is, therefore, necessary to undertake regional control measures to reduce pollutant emissions.

Effect estimates of prenatal exposure to ambient PM2.5 on change in grams (β) of birth weight among term births (≥37 weeks of gestation; term birth weight, TBW) vary widely across studies. We present the first systematic review and meta-analysis of evidence regarding these associations. Sixty-two studies met the eligibility criteria for this review, and 31 studies were included in the meta-analysis. Random-effects meta-analysis was used to assess the quantitative relationships. Subgroup analyses were performed to gain insight into heterogeneity derived from exposure assessment methods (grouped by land use regression [LUR]-models, aerosol optical depth [AOD]-based models, interpolation/dispersion/Bayesian models, and data from monitoring stations), study regions, and concentrations of PM2.5 exposure. The overall pooled estimate involving 23,925,941 newborns showed that TBW was negatively associated with PM2.5 exposure (per 10 μg/m3 increment) during the entire pregnancy (β = −16.54 g), but with high heterogeneity (I2 = 95.6%). The effect estimate in the LUR-models subgroup (β = −16.77 g) was the closest to the overall estimate and with less heterogeneity (I2 = 18.3%) than in the other subgroups of AOD-based models (β = −41.58 g; I2 = 95.6%), interpolation/dispersion models (β = −10.78 g; I2 = 86.6%), and data from monitoring stations (β = −11.53 g; I2 = 97.3%). Even PM2.5 exposure levels of lower than 10 μg/m3 (the WHO air quality guideline value) had adverse effects on TBW. The LUR-models subgroup was the only subgroup that obtained similar significant of negative associations during the three trimesters as the overall trimester-specific analyses. In conclusion, TBW was negatively associated with maternal PM2.5 exposures during the entire pregnancy and each trimester. More studies based on relatively standardized exposure assessment methods need to be conducted to further understand the precise susceptible exposure time windows and potential mechanisms.

This study sought to clarify the correlation of individual exposure measurements and PM2.5 measurements collected at regulatory monitoring sites in short-term panel study settings. To achieve this goal, 30 young, healthy adult participants were assigned to three groups with 4 samplers in each group to collect individual exposures during four weekends in March 2016. Participants also completed cardiopulmonary function tests during the same periods. For comparison, ambient air pollution data were obtained from the Air Pollution Surveillance Network in Guangzhou, China. The 8-h ambient pollutant averages and group sampler concentrations were used as separate indicators of air pollution exposure. Results showed that the 8-h mean concentration of personal PM2.5 exposure was 65.09 ± 22.18 μg/m3, which was 24.34 μg/m3 statistically higher than the ambient concentrations over the same period (p

The determination of background concentration of PM2.5 is important to understand the contribution of local emission sources to total PM2.5 concentration. The purpose of this study was to exam the performance of baseline separation techniques to estimate PM2.5 background concentration. Five separation methods, which included recursive digital filters (Lyne-Hollick, one-parameter algorithm, and Boughton two-parameter algorithm), sliding interval and smoothed minima, were applied to one-year PM2.5 time-series data in two heavily polluted cities, Tianjin and Jinan. To obtain the proper filter parameters and recession constants for the separation techniques, we conducted regression analysis at a background site during the emission reduction period enforced by the Government for the 2014 Asia-Pacific Economic Cooperation (APEC) meeting in Beijing. Background concentrations in Tianjin and Jinan were then estimated by applying the determined filter parameters and recession constants. The chemical mass balance (CMB) model was also applied to ascertain the effectiveness of the new approach. Our results showed that the contribution of background PM concentration to ambient pollution was at a comparable level to the contribution obtained from the previous study. The best performance was achieved using the Boughton two-parameter algorithm. The background concentrations were estimated at (27 ± 2) μg/m3 for the whole year, (34 ± 4) μg/m3 for the heating period (winter), (21 ± 2) μg/m3 for the non-heating period (summer), and (25 ± 2) μg/m3 for the sandstorm period in Tianjin. The corresponding values in Jinan were (30 ± 3) μg/m3, (40 ± 4) μg/m3, (24 ± 5) μg/m3, and (26 ± 2) μg/m3, respectively. The study revealed that these baseline separation techniques are valid for estimating levels of PM2.5 air pollution, and that our proposed method has great potential for estimating the background level of other air pollutants.

The role of precursors' concentrations and meteorological conditions on the emerging ozone pollution problem in China has received wide attention, especially after the releasing of the Air Pollution Prevention Control and Action Plan (APPC) since 2013. With the decreasing trend of PM2.5 nationwide, the effect of the strict control measures on increasing ozone variation has less been studied due to the challenge of complexity of nonlinear relationship among a number of factors on ozone formation. This paper evaluated the influence of both ozone precursors and meteorology on maximum daily average 8 h (MDA8) ozone at two urban sites and one rural site in Hebei province, China, from 2013 to 2017, by using a combined application of Kolmogorov-Zurbenko (KZ) filter and artificial neural network (ANN) model. Results showed that R2 was 0.80 between the measured and the simulated MDA8 ozone concentration when using meteorological factors and precursors' concentrations as input variables for ANN model. However, ANN model has limitation in estimating O3 concentration peaks. The values of threat score (TS), probability of detection (POD) and false alarm rate (FAR) for MDA8 ozone concentration were 39%, 44% and 21%, respectively, throughout three studied sites in Hebei province. The annual average percentage change of precursor-related ozone was 0.67% from 2014 to 2017. Temperature, atmospheric pressure and boundary layer height were shown to account for 64% of the variability in long-term ozone levels. Ozone variation in Hebei province was reproduced mainly by meteorological parameters, and the contribution from precursors’ concentration was smaller during the years when the APPC was implemented.

We investigated the association between respiratory health and particulate matter (PM) air pollution in elderly type 2 diabetes mellitus (T2DM) pre-, during, and post-the Chinese Lunar New Year (CLNY) holiday in Shanghai, China.We conducted repeated measurements of lung function and inflammation biomarker in a cohort consisted of 60 participants with T2DM.Decreased PM2.5 exposure had an effect on respiratory health by increasing in forced expiratory flow in 1 second (FEV1) and forced vital capacity (FVC). Positive associations between PM exposure and exhaled nitric oxide (eNO) were observed.Our observations indicated that PM air pollution exposure would exert adverse effect on respiratory health in elderly T2DM population.

In 2013, China issued "Air Pollution Prevention and Control Action Plan (Action Plan)" to improve air quality. To assess the benefits of this program in Beijing-Tianjin-Hebei (BTH) region, where the density of population and emissions vary greatly, we simulated the air quality benefit based on BenMAP to satisfy the Action Plan. In this study, we estimate PM2.5 concentration using Voronoi spatial interpolation method on a grid with a spatial resolution of 1×1km2. Combined with the exposure-response function between PM2.5 concentration and health endpoints, health effects of PM2.5 exposure are analyzed. The economic loss is assessed by using the willingness to pay (WTP) method and human capital (HC) method. When the PM2.5 concentration falls by 25% in BTH and reached 60μg/m3 in Beijing, the avoiding deaths will be in the range of 3175 to 14051 based on different functions each year. Of the estimated mortality attributable to all causes, 3117 annual deaths were due to lung cancer, 1924 - 6318 annual deaths were due to cardiovascular, and 343 - 1697 annual deaths were due to respiratory. Based on WTP, the estimated monetary values for the avoided cases of all cause mortality, cardiovascular mortality, respiratory mortality and lung cancer ranged from 1110 to 29632, 673 to 13325, 120 to 3579, 1091 to 6574 million yuan, respectively. Based on HC, the corresponding values for the avoided cases of these four mortalities were 267 to 1178, 161 to 529, 29 to 143 and 261 million yuan, respectively.

To assess the public health benefits of reducing PM2.5 in Tianjin, we created an annual air quality surface with a land use regression (LUR) model conducted at a high spatial resolution (1 km). The predictors included in the final model were population density, road length within a 1000 m buffer, industrial land area within a 2000m buffer and distance to the coast. The fitting R2 and the leave-one-out-cross-validation (LOOCV) R2 of the PM2.5 LUR models were 0.78 and 0.73, respectively, suggesting that the predicted PM2.5 concentrations fitted well with the measured values for the entire year. Daily air quality surfaces were established based on historic concentration data and interpolation method. We evaluated avoided cases of mortality and morbidity in Tianjin, assuming achievement of China's current air quality daily and annual standards (No. GB3095-2012). Reducing the daily average PM2.5 to the daily Class II standard (75 μg/m3), the avoided emergency department visits, the deaths for cardiovascular disease and the deaths for respiratory disease are 85,000 (95% confidence interval (CI), 17,000–150,000), 2000 (95% CI, 920–3100) and 280 (95% CI, 94–460) per year respectively, and the monetary values are 23–42 million yuan, 180–4800 million yuan and 25–670 million yuan per year in 2015 yuan year respectively. Reducing the annual average PM2.5 to the annual Class II standard (35 μg/m3), the avoided emergency department visits, the deaths for cardiovascular disease and the deaths for respiratory disease are 59,000 (95% CI, 12,000–110,000), 1400 (95% CI, 640–2100) and 200 (95% CI, 66–320) per year respectively, and the monetary values are 16–29 million yuan, 130 to 3400 million yuan and 18 to 480 million yuan per year in 2015 yuan year respectively.

Along with the rapid socioeconomic development, air pollution in China has become a severe problem. One component of air pollution, in particular, PM2.5 has aroused wide public concern because of its high concentration. In this study, data were collected from over 900 monitoring sites of the newly constructed PM2.5 monitoring network in China. The interpolation methods were used to simulate the PM2.5 exposure level of China especially in rural areas, thus reflecting the spatial variation of PM2.5 pollution. We calculated the health benefit caused by PM2.5 in China in 2014 based on Environmental Benefits Mapping and Analysis Program (BenMAP), assuming achievement of China National Ambient Air Quality Standard (No. GB3095-2012). By reducing the annual average concentration of PM2.5 to the annual Grade II standard (35 μg/m3), the avoided deaths for cardiovascular disease, respiratory disease and lung cancer could reach 89,000 (95% CI, 8000–170,000), 47,000 (95% CI, 3000–91,000) and 32,000 (95% CI, 6000–58,000) per year using long term health function, respectively. The attributable fractions of cardiovascular disease, respiratory disease and lung cancer to all cause were 42%, 22% and 15%, respectively. The total economic benefits for rolling back the concentration of PM2.5 to the level of 35 μg/m3 were estimated to be 260 (95%CI: (73, 440) billion RMB and 72 (95%CI: (45, 99) billion RMB using willingness to pay (WTP) and human capital (HC) methods, respectively, which account for 0.40% (95%CI: (0.11%, 0.69%) and 0.11% (95%CI: (0.07%, 0.15%) of the total annual Gross Domestic Product (GDP) of China in 2014.

In order to analyze the temporal-spatial distribution characteristics of PM2.5, PM10, SO2, NO2, CO and O3 in five cities and the potential sources of PM10 in southern Xinjiang during 2016, we collected one year officially released data for analysis. The average PM10, PM2.5, SO2, NO2, O3 and CO concentrations were 289 ± 363, 99 ± 106, 17 ± 9, 29 ± 11, 65 ± 25 μg m−3 and 1.3 ± 0.6 mg m−3 in southern Xinjiang in 2016, respectively. The air pollutants presented distinct seasonal and spatial distribution characteristics. During sandstorm process, the particulate matters (PM) concentrations increased abruptly, with the PM10 and PM2.5 maximum concentrations exceeding 1000 and 500 μg m−3 in each city. The backward trajectory results showed that the air masses in Akesu, Kurla, Hotan, Kashi and Atushi were mainly from the Bayingol Mongolian Autonomous Prefecture, Kyrgyzstan, Kizilesu Kirgiz Autonomous Prefecture and Taklimakan Desert (TD). In addition, TD was the main potential contributor to ambient PM10 in five cities during the dust season (DS), with a weighted potential source contribution function (WPSCF) > 0.9. While the trajectories of air masses from TD, Bayingol Mongolian Autonomous Prefecture, Urumqi-Changji Area and local emission were potential sources contributing to PM2.5 in these five cities during DS, with a WPSCF > 0.7. Moreover, the high weighted concentration weighted trajectory (WCWT) values were distributed in the Tarim basin, with PM10 > 700 μg m−3, however, the local emission and long distance transport contributed to the PM2.5 > 160 μg m−3 for five cities. This study comprehensively analyzes the pollution characteristics of air pollutants in five important cities in the southern margin of the Tarim Basin for the first time, and will provide an important reference basis for the prevention and control of air pollution in southern Xinjiang.

Particulate matter with an aerodynamic diameter of 2.5 μm or less (PM 2.5 ) is the main air pollutant in many countries. PM 2.5 levels vary substantially over time and short distances, which directly affects the interpretation of data collected from reference stations. Although such data are usually accurate for one location at a certain time, they cannot be extrapolated to carry out complete spatial and temporal PM 2.5 assessment. China’s varying geographies, climates and environment make it challenging to accurately measure ambient air PM 2.5 levels. This paper describes the current state of PM 2.5 pollution and standard/specifications of monitoring in China, reviews all available PM measurement techniques, highlights the advantages and limitations of the most widely used instruments, and discusses the related challenges. Based on our analysis of PM 2.5 measurements, we suggest some ways to improve this measurement in China. In particular, suitable instruments need to be developed to accommodate different environments, climates and pollution levels across China. However, it is important to note that monitoring is merely a way to measure pollution levels, and not the main purpose of our research. The final purpose we have is creating a healthy and comfortable living environment for China’s residents.

Cohort evidence that links long-term exposures to air pollution and mortality comes largely from the United States and European countries. We investigated the relationship between long-term exposures to particulate matter

Epidemiological studies have reported inconsistent and inconclusive associations between long-term exposure to ambient air pollution and lung function in children from Europe and America, where air pollution levels were typically low. The aim of the present study is to examine the relationship between air pollutants and lung function in children selected from heavily industrialized and polluted cities in northeastern China. During 2012, 6740 boys and girls aged 7–14 years were recruited in 24 districts of seven northeastern cities. Portable electronic spirometers were used to measure lung function. Four-year average concentrations of particulate matter with an aerodynamic diameter ≤10 μm (PM10), sulfur dioxide (SO2), nitrogen dioxide (NO2), and ozone (O3) were measured at monitoring stations in the 24 districts. Two-staged regression models were used in the data analysis, controlling for covariates. Overall, for all subjects, the increased odds of lung function impairment associated with exposure to air pollutants, ranged from 5% (adjusted odds ratio [aOR] = 1.05; 95% confidence interval [CI] = 1.01, 1.10) for FVC

Daily PM2.5 (particulate matter with an aerodynamic diameter of below 2.5 μm) mass concentrations were measured by gravimetric analysis in Chinese Research Academy of Environmental Sciences (CRAES), in the northern part of the Beijing urban area, from December 2013 to April 2015. Two pairs of Teflon (T1/T2) and Quartz (Q1/Q2) samples were obtained, for a total number of 1352 valid filters. Results showed elevated pollution in Beijing, with an annual mean PM2.5 mass concentration of 102 μg/m(3). According to the calculated PM2.5 mass concentration, 50% of our sampling days were acceptable (PM2.575 μg/m(3)), 30% had slight/medium pollution (75-150 μg/m(3)), and 7% had severe pollution (250 μg/m(3)). Sampling interruption occurred frequently for the Teflon filter group (75%) in severe pollution periods, resulting in important data being missing. Further analysis showed that high PM2.5 combined with high relative humidity (RH) gave rise to the interruptions. The seasonal variation of PM2.5 was presented, with higher monthly average mass concentrations in winter (peak value in February, 422 μg/m(3)), and lower in summer (7 μg/m(3) in June). From May to August, the typical summer period, least severe pollution events were observed, with high precipitation levels accelerating the process of wet deposition to remove PM2.5. The case of February presented the most serious pollution, with monthly averaged PM2.5 of 181 μg/m(3) and 32% of days with severe pollution. The abundance of PM2.5 in winter could be related to increased coal consumption for heating needs.

Evidence for effects of PM2.5 on systemic oxidative stress in pregnant women is limited, especially in early pregnancy. To estimate the associations between ambient PM2.5 exposures and biomarkers of lipid peroxidation and total antioxidant capacity (T-AOC) in women with normal early pregnancy (NEP) and women with clinically recognized early pregnancy loss (CREPL), 206 early pregnant women who had measurements of serum malondialdehyde (MDA) and T-AOC were recruited from a larger case-control study in Tianjin, China from December 2017 to July 2018. Ambient PM2.5 concentrations of eight single-day lags exposure time windows before blood collection at the women’s residential addresses were estimated using temporally-adjusted land use regression models. Effects of PM2.5 exposures on percentage change in the biomarkers were estimated using multivariable linear regression models adjusted for month, temperature, relative humidity, gestational age and other covariates. Unconstrained distributed lag models were used to estimate net cumulative effects. Increased serum MDA and T-AOC were significantly associated with increases in PM2.5 at several lag exposure time windows in both groups. The net effects of each interquartile range increase in PM2.5 over the preceding 8 days on MDA were significantly higher (p

In previous studies, inhalation cancer risk was estimated using conventional risk assessment method, which was normally based on compound-specific analysis, and cannot provide substantial data for source-specific particulate matter concentrations and pollution control. In the present study, we applied an integrated risk analysis method, which was a synthetic combination of source apportionment receptor model and risk assessment method, to estimate cancer risks associated to individual PAHs coming from specific sources. Personal exposure particulate matter samples referring to an elderly panel were collected in a community of Tianjin, Northern China, in 2009, and 12 PAH compounds were measured using GC-MS. Positive matrix factorization (PMF) was used to extract the potential sources and quantify the source contributions to the PAH mixture. Then, the lung cancer risk of each modeled source was estimated by summing up the cancer risks of all measured PAH species according to the extracted source profile. The final results indicated that the overall cancer risk was 1.12 × 10−5, with the largest contribution from gasoline vehicle emission (44.1%). Unlike other risk estimation studies, this study was successful in combining risk analysis and source apportionment approaches, which allow estimating the potential risk of all source types and provided suitable information to select prior control strategies and mitigate the main air pollution sources that contributing to health risks. This study was funded by the "National Basic Research Program of China" (Grant No. 2011CB503801).

As one of the biggest cities in North China, Jinan has been suffering heavy air pollution in recent decades. To better characterize the ambient particulate matter in Jinan during heavy pollution periods, we collected daily PM2.5 (particulate matter with aerodynamic diameters equal to or less than 2.5 &mu, m) filter samples from 15 October 2017 to 31 January 2018 and analyzed their chemical compositions (including inorganic water-soluble ions (WSIs), carbonaceous species, and inorganic elements). The daily average concentration of PM2.5 was 83.5 &mu, g/m3 during the sampling period. A meteorological analysis revealed that both low wind speed and high relative humidity facilitated the occurrence of high PM2.5 pollution episodes. A chemical analysis indicated that high concentrations of water-soluble ions, carbonaceous species, and elements were observed during heavy pollution days. The major constituents of PM2.5 in Jinan were secondary aerosol particles and organic matter based on the results of mass closure. Chemical Mass Balance (CMB) was used to track possible sources and identified that nitrate, sulfate, vehicle exhaust and coal fly ash were the main contributors to PM2.5 during heavy pollution days in Jinan, accounting for 25.4%, 18.6%, 18.2%, and 13.3%, respectively.

Overfitting is a concern with air pollution estimation models that rely on a limited number of monitoring sites. Here we develop spatio-temporal air pollution exposure prediction models using land use regression in a universal kriging framework with temporally rich but spatially poor monitoring data. Two-week average concentrations for six criteria pollutants (PM10, PM2.5, SO2, NO2, ozone and CO) from 2014 through 2017 were obtained from 23 administrative monitoring sites in the urban area in Beijing. A large array of geographic covariates (GC) was collected. Exposure prediction models for the air pollutants involved three steps: (1) deriving the smoothed temporal trends from a singular value decomposition; (2) reducing the dimensionality of the collected GC using partial least square regression (PLS); (3) developing spatio-temporal models based on the previous smoothed temporal trends and GC-related PLS scores. Leave-one-out cross validation (LOOCV) was used for prediction accuracy at each of the three s...

Cohort evidence linking long-term exposure to ambient air pollution and mortality has come largely from the United States and European countries. There is relatively little evidence from nationally...

No cohort studies in China on the health effects of long-term air pollution exposure have employed exposure estimates at the fine spatial scales desirable for cohort studies with individual-level health outcome data. Here we assess an array of modern air pollution exposure estimation approaches for assigning within-city exposure estimates in Beijing for individual pollutants and pollutant sources to individual members of a cohort. Issues considered in selecting specific monitoring data or new monitoring campaigns include: needed spatial resolution, exposure measurement error and its impact on health effect estimates, spatial alignment and compatibility with the cohort, and feasibility and expense. Sources of existing data largely include administrative monitoring data, predictions from air dispersion or chemical transport models and remote sensing (specifically satellite) data. New air monitoring campaigns include additional fixed site monitoring, snapshot monitoring, passive badge or micro-sensor saturation monitoring and mobile monitoring, as well as combinations of these. Each of these has relative advantages and disadvantages. It is concluded that a campaign in Beijing that at least includes a mobile monitoring component, when coupled with currently available spatio-temporal modeling methods, should be strongly considered. Such a campaign is economical and capable of providing the desired fine-scale spatial resolution for pollutants and sources.

We aimed to investigate if short-term exposure to reduced particulate matter (PM) air pollution would affect respiratory function in healthy adults. We followed a cohort of 42 healthy participants from a community afflicted with severe PM air pollution to a substantially less polluted area for nine days. We measured daily airborne PM [with an aerodynamic diameter of less than 2.5 μm (PM2.5) and 10 μm (PM10)] and PM2.5 carbon component concentrations. Five repeated respiratory function measurements and fractional exhaled nitric oxide test were made for each participant. Associations between respiratory health and PM exposure were assessed using linear mixed models. Each 10 μg/m3 decrease in same-day PM2.5 was associated with small but consistent increase in the forced expiratory volume in 1 s (FEV1) (9.00 mL) and forced vital capacity (14.35 mL). Our observations indicate that respiratory health benefits can be achieved even after a short-term reduction of exposure to PM. Our results provide strong...

A one-year-long aerosol characterization study was conducted from July 2002 through July 2003, in Beijing, China. Twenty-four hour PM2.5 and PM10 filter samples were collected, and about 50 aerosol samples of each type were obtained. Organic, elemental, and total carbon, levoglucosan and other organic compounds, and inorganic ionic species were measured. The overall mean PM mass concentrations were 99 and 175 mu g/m(3) for PM2.5 and PM10, respectively. Total carbon was the main component in both PM2.5 and PM10, with overall mean concentrations of 21 and 30 mu g/m(3), respectively. Of the organic compounds measured, levoglucosan exhibited the highest levels (overall mean of 0.31 mu g/m(3) in PM2.5 and of 0.40 ng/m(3) in PM10). Sulfate was the most prominent inorganic ionic species, with overall mean levels of 15.6 and 17.0 mu g/m(3) in PM2.5 and PM10, respectively. Most components measured were predominantly present in the PM2.5 size fraction; the overall mean PM2.5/PM10 ratio was typically in the range of 0.7-0.8, but this ratio was only 0.55 for the PM mass and for Ca2+ it was as low as 0.19. In PM2.5, total carbon exhibited relatively larger concentration levels (30 mu g/m(3)) in winter than in the other seasons. K+ also exhibited a relatively high concentration level in the winter season, with 2.3 mu g/m(3) in PM2.5. The contribution from biomass burning to K+ in PM2.5 was estimated on the basis of the levoglucosan data and the minimum K+/levoglucosan ratios obtained throughout the year; it was found that the contribution was largest in autumn, with 44%.

Measurements of gaseous pollutants – including ozone (O3), sulfur dioxide (SO2), nitrogen oxides (NOX = NO + NO2), carbon monoxide (CO), particle number concentrations (5.6–560 nm and 0.47–30 μm) – and meteorological parameters (T, RH, P) were conducted during the Campaigns of Air Quality Research in Beijing and Surrounding Regions in 2008 (CAREBeijing-2008), from 27 August through 13 October 2008. The data from a total 18 flights (70 h flight time) from near the surface to 2100 m altitude were obtained with a Yun-12 aircraft in the southern surrounding areas of Beijing (38–40° N, 114–118° E). The objectives of these measurements were to characterize the regional variation of air pollution during and after the Olympics of 2008, determine the importance of air mass trajectories and to evaluate of other factors that influence the pollution characteristics. The results suggest that there are primarily four distinct sources that influenced the magnitude and properties of the pollutants in the measured region based on back-trajectory analysis: (1) southerly transport of air masses from regions with high pollutant emissions, (2) northerly and northeasterly transport of less pollutant air from further away, (3) easterly transport from maritime sources where emissions of gaseous pollutant are less than from the south but still high in particle concentrations, and (4) the transport of air that is a mixture from different regions; that is, the air at all altitudes measured by the aircraft was not all from the same sources. The relatively long-lived CO concentration is shown to be a possible transport tracer of long-range transport from the northwesterly direction, especially at the higher altitudes. Three factors that influenced the size distribution of particles – i.e., air mass transport direction, ground source emissions and meteorological influences – are also discussed.

Epidemiologic studies have demonstrated that long-term exposure to relatively low levels of particulate air pollution is associated with adverse cardiovascular outcomes in Europe and North America. However, few studies have assessed the association with high level air pollutants. We aimed to assess the cardiovascular effects of long-term exposure to high level concentrations of inhalable particulate and to identify the characteristics of the Chinese population that are susceptible to the health effects. A retrospective cohort, containing 39,054 subjects from four cities in northern China, was followed for mortality of all cause and specific cardiovascular diseases from 1998 to 2009. Information on concentrations of PM10 (particulate matter

Assessment of human exposure to air pollution is a fundamental part of the more general process of health risk assessment. The measurement methods for exposure assessment now include personal exposure monitoring, indoor-outdoor sampling, mobile monitoring, and exposure assessment modeling (such as proximity models, interpolation model, air dispersion models, and land-use regression (LUR) models). Among these methods, personal exposure measurement is considered to be the most accurate method of pollutant exposure assessment until now, since it can better quantify observed differences and better reflect exposure among smaller groups of people at ground level. And since the great differences of geographical environment, source distribution, pollution characteristics, economic conditions, and living habits, there is a wide range of differences between indoor, outdoor, and individual air pollution exposure in different regions of China. In general, the indoor particles in most Chinese families comprise infiltrated outdoor particles, particles generated indoors, and a few secondary organic aerosol particles, and in most cases, outdoor particle pollution concentrations are a major contributor to indoor concentrations in China. Furthermore, since the time, energy, and expense are limited, it is difficult to measure the concentration of pollutants for each individual. In recent years, obtaining the concentration of air pollutants by using a variety of exposure assessment models is becoming a main method which could solve the problem of the increasing number of individuals in epidemiology studies.

Following the rapid development of China’s economy, air pollution has become more and more serious. Air pollution in China presents complex pollution characterized by high PM2.5 and O3 concentration. This study presents an overview of the status of air quality and emission in China and discusses the temporal and spatial distribution of major pollutants (PM10, PM2.5, SO2, NOX, and O3). The results show that the reduced emissions have improved the air quality in China. However, the Chinese National Ambient Air Quality Standard (CNAAQS) for PM10 and PM2.5 still be exceeded in many cities of China in 2015. A total of 77.5% (for PM2.5) and 65.4% (for PM10) of the monitoring cities were found to be exceeded CNAAQS. The average annual O3 concentration was increasing during 2013–2015, and 16% of the total cities in 2015 did not meet the CNAAQS, indicating that O3 pollution should be paid more attention. For NO2 and SO2, the exceedances of CNAAQS are rare. PM2.5, PM10, and SO2 concentrations are higher in northern than in southern regions. High NO2 occurred in Beijing-Tianjin-Hebei and Yangtze River delta region. Secondary particles formation and motor vehicle exhaust were the main sources of PM2.5 in megacities. Dust was the main source for PM10. The formation of O3 is VOC-limited in urban areas of China and NOX-limited in nonurban areas.

In order to investigate long-range transport of the air pollution in the East Asia, air pollutants, including SO2, NOx, CO, and O3, were observed by aircraft measurement over the coastal and offshore area of Yellow Sea of China in April 2011. NOx and SO2 seemed to become moderate in recent years, and the concentrations during the whole observations ranged from 0.49 to 9.57 ppb and from 0.10 to 16.02 ppb, respectively. The high concentrations of CO were measured with an average value of 0.98 ppm. The measured O3 average concentration was 76.25 ppb, which showed a higher level comparing with the results from some previous studies. Most of the results for the concentration values generally followed the typical characteristic of vertical and spatial distribution, which were “low altitude > high altitude” and “land/coastal > sea,” respectively. Transport of polluted air mass from the continent to the aircraft measurement area was confirmed in some days during the observation by the meteorological analysis, while the measurement results supposed to represent the background level of the pollutants in rest days. Additionally, some small-scale air pollution plumes were observed. Significant positive correlations between NOx and SO2 indicated that these two species originated from the same region. On the other hand, good positive correlations between NOx and O3 found during 2-day flight suggested that the O3 formation was probably under “NOx-limited” regime in these days.

A new air exchange rate (AER) monitoring method using continuous CO2 sensors was developed and validated through both laboratory experiments and field studies. Controlled laboratory simulation tests were conducted in a 1-m(3) environmental chamber at different AERs (0.1-10.0 hr(-1)). AERs were determined using the decay method based on box model assumptions. Field tests were conducted in classrooms, dormitories, meeting rooms and apartments during 2-5 weekdays using CO2 sensors coupled with data loggers. Indoor temperature, relative humidity (RH), and CO2 concentrations were continuously monitored while outdoor parameters combined with on-site climate conditions were recorded. Statistical results indicated that good laboratory performance was achieved: duplicate precision was within 10%, and the measured AERs were 90%-120% of the real AERs. Average AERs were 1.22, 1.37, 1.10, 1.91 and 0.73 hr(-1) in dormitories, air-conditioned classrooms, classrooms with an air circulation cooling system, reading rooms, and meeting rooms, respectively. In an elderly particulate matter exposure study, all the homes had AER values ranging from 0.29 to 3.46 hr(-1) in fall, and 0.12 to 1.39 hr(-1) in winter with a median AER of 1.15.

30 re-suspended dust samples were collected from building surfaces of an oilfield city, then re-suspended through PM2.5, PM10 and PM100 inlets and analyzed for 10 metals including V, Cr, Mn, Co, Ni, Cu, Zn, As, Cd and Pb by inductively coupled plasma-mass spectroscopy. Metals concentrations in different fractions and locations were studied. Metals sources were identified by cluster and primary component analysis. The potential risk to human health was assessed by human exposure model. Results showed that Zn, Mn, Pb and Cu were higher in all the three fractions. V, Cr, Mn and Co ranged close to the background values of Chinese soil indicating that they were mainly from crustal materials. Concentrations of Zn, Mn, Pb, V, Cr, Ni, Co and Cd were higher in old district than that in new district for the three fractions. The PM2.5/PM10, PM10/PM100 and PM2.5/PM100 ratios were higher for Zn, Cd, Cu, Pb, Ni, As and Cr (all higher than 1.0), and lower for Co, Mn and V (all less than or close to 1.0) which meant that anthropologic sources associated metals were more easily accumulated in finer particles than metals from crustal materials. Spatial variations indicated that the ten metals peaked at surroundings near railway station, gas stations, industrial boilers and machine manufacturing plant implying the influence of local vehicle emission, fossil fuel combustion and industrial activities as well as crustal materials which was verified by cluster analysis and primary component analysis results. Ingestion of dust particles appeared to be the main route of exposure to re-suspended dust. Hazard Indexes of As were both highest for children and adult which could be a potential threat to human health for non-cancer effect and it also exhibited the highest values for cancer effect as 1.01E-06, 7.04E-07 and 7.21E-07 for PM2.5, PM10 and PM100, respectively.

SO2, NO2, and PM10 are the major outdoor air pollutants in China, and most of the cities in China have regulatory monitoring sites for these three air pollutants. In this study, we developed a land use regression (LUR) model using regulatory monitoring data to predict the spatial distribution of air pollutant concentrations in Jinan, China. Traffic, land use and census data, and meteorological and physical conditions were included as candidate independent variables, and were tabulated for buffers of varying radii. SO2, NO2, and PM10 concentrations were most highly correlated with the area of industrial land within a buffer of 0.5 km (R2=0.34), the distance from an expressway (R2=0.45), and the area of residential land within a buffer of 1.5 km (R2=0.25), respectively. Three multiple linear regression (MLR) equations were established based on the most significant variables (p

Fourteen polycyclic aromatic hydrocarbons (PAHs) in PM(2.5) and PM(2.5-10) samples collected in five cities (Shenyang, Anshan, Jinzhou, Fushun and Dalian), Liaoning Province, China in 2004 and 2005 were analyzed by using a HPLC equipped with fluorescence and UV detectors. Results showed total PAHs concentrations in PM(2.5) and PM(2.5-10) were in the range of 75.32-1900.89 ng m(-3) and 16.74-303.24 ng m(-3), respectively. 90% of the total PAHs were in PM(2.5). PAHs in PM(2.5) had a winter to summer ratio varying from 6.5 to 125.8 while PAHs in PM(2.5-10) had a ratio ranging from 1.7 to 37.6. Total PAHs concentrations were most abundant at residential/commercial sites and were fewest at an industrial site for both PM(2.5) and PM(2.5-10). Urban background sites showed unexpected higher PAHs concentrations. Total BaP equivalent concentration (BaPeq) for PM(2.5) ranged from 7.80 to 88.42 ng m(-3) in different function zones. Similarities of PAHs profiles between sampling sites and between fine and coarse fractions were compared by coefficient of divergence which indicated that remarkable differences in PAHs compositions existed. Principal component analysis (PCA) associated with diagnostic ratios revealed coal combustion and vehicle emission were the major sources for PM(2.5) and PM(2.5-10) associated PAHs.

Land use regression (LUR) model was employed to predict the spatial concentration distribution of NO 2 and PM 10 in the Tianjin region based on the environmental air quality monitoring data. Four multiple linear regression (MLR) equations were established based on the most significant variables for NO 2 in heating season ( R 2 = 0.74), and non-heating season ( R 2 = 0.61) in the whole study area; and PM 10 in heating season ( R 2 = 0.72), and non-heating season ( R 2 = 0.49). Maps of spatial concentration distribution for NO 2 and PM 10 were obtained based on the MLR equations (resolution is 10 km). Intercepts of MLR equations were 0.050 (NO 2 , heating season), 0.035 (NO 2 , non-heating season), 0.068 (PM 10 , heating season), and 0.092 (PM 10 , non-heating season) in the whole study area. In the central area of Tianjin region, the intercepts were 0.042 (NO 2 , heating season), 0.043 (NO 2 , non-heating season), 0.087 (PM 10 , heating season), and 0.096 (PM 10 , non-heating season). These intercept values might imply an area's background concentrations. Predicted result derived from LUR model in the central area was better than that in the whole study area. R 2 values increased 0.09 (heating season) and 0.18 (non-heating season) for NO 2 , and 0.08 (heating season) and 0.04 (non-heating season) for PM 10 . In terms of R 2 , LUR model performed more effectively in heating season than non-heating season in the study area and gave a better result for NO 2 compared with PM 10 .

The concentrations of CH 4 , N 2 O and CO 2 at the sea level were observed from November 2007 to August 2008 in order to study the greenhouse gases in the Tianjin offshore area of Bohai Sea. CH 4 concentrations varied from 1.87 to 2.61 ppm with the highest value appearing in summer and the lowest in winter. The concentration range of N 2 O was 319.3 to 347.7 ppb, with the maximal value appearing in winter. CO 2 was higher in the heating season than in non-heating season in this area. Concentrations of the three greenhouse gases in the study area exceeded the 2005 global background values. Backward trajectory model was used to analyze the sources. All three gases were influenced evidently by continental sources in the inshore area during the sampling periods. Every gas was compared with each other by correlation analysis, showing that the correlation of CO 2 and N 2 O was more significant than to CH 4 and their relationship with meteorological factors was consistent. It can be concluded these three greenhouse gases may be influenced by some similar sources, especially for CO 2 and N 2 O.

To improve the photocatalytic application performances of TiO2, in this work, firstly CdS modified Degussa P25 TiO2 (CdS/TiO2) composites were prepared by two methods, sol–gel method and precipitation method. Next they, sol–gel-CdS/TiO2 (sg-CdS/TiO2) and precipitation-CdS/TiO2 (pp-CdS/TiO2), were loaded on activated carbon fibers (ACFs) by dip-coating method using the sodium carboxymethyl cellulose as adhesives. The composites were characterized by XRD, UV–vis absorbance spectra, SEM, EDS and BET. The photocatalytic activities under sunlight were investigated by the degradation of methylene blue. The results showed that CdS/TiO2 composites were mainly composed of anatase-TiO2 and little CdS cubic phases. The absorption wavelengths of sg-CdS/TiO2 and pp-CdS/TiO2 composites were extended to 590 nm and 740 nm, respectively. The absorption edge had a pronounced ‘red shift’. From EDS analysis, the elemental contents of CdS/TiO2 were mainly Ti and O and a small quantity of S and Cd. CdS/TiO2 loaded on ACFs were in the form of small clusters, but not very uniform; compared with the original ACFs, the surface area and pore volume of CdS/TiO2/ACFs decreased slightly, respectively, while the average pore diameter was not changed. The photodegradation rate of methylene blue under sunlight with CdS/TiO2/ACFs composites was markedly higher than that of P25-TiO2/ACFs, and the effect of pp-CdS/TiO2/ACFs composites was better than that of sg-CdS/TiO2/ACFs, when irradiated for 180 min, and the photodegradation rate of methylene blue reached to 90.1%. The photodegradation kinetics of the methylene blue fitted with the Langmuir–Hinshelwood equation. The apparent reaction rate constants of sg-CdS/TiO2/ACFs and pp-CdS/TiO2 were 0.0105 min−1 and 0.0146 min−1, respectively, which were about 1.3–1.7 times as large as that of P25-TiO2/ACFs.

Concentrations of organic carbon (OC) and elemental carbon (EC) in atmospheric particles were measured in Tianjin during January, April, July and October in 2008. The 24-h PM2.5 (particles with aerodynamic diameters less than 2.5 micrometer [�� m]) and PM10 (particles with aerodynamic diameters less than 10 micrometer [�� m]) samples were simultaneously collected every day during sampling periods. These samples were analyzed for OC/EC by thermal/optical reflectance (TOR) following the Interagency Monitoring of Protected Visual Environments (IMPROVE) protocol. The annual average concentration was 109.8 ± 48.5 �� g/m 3 in PM2.5, and 196.2 ± 86.1 �� g/m 3 in PM10, respectively. The average ratio of PM2.5/PM10 was 57.9%, indicating the PM2.5 had been one of the main contaminations affecting urban atmospheric environmental quality in Tianjin. The concentrations of OC and EC in PM2.5 and PM10 were all relatively higher in winter and fall and lower in summer and spring. This seasonal variation could be attributed to the cooperative effects of changes in emission rates and seasonal meteorological conditions. The annual average concentration of the estimated secondary organic carbon (SOC) was 14.9 �� g/m 3 and occupied 61.7% of the total OC in PM2.5, while those in PM10 were 23.4�� g/m 3 and 61.2%, respectively, indicating SOC had been an important contributor to organic aerosol in Tianjin. The distribution of eight carbon fractions (OC1, OC2, OC3, OC4, EC1, EC2, EC3 and OP) was also reported and found that the biomass burning, coal–combustion and motor-vehicle exhaust were all contributed to the carbonaceous particles in Tianjin.

A monitoring program of particulate matter was conducted at eight sampling sites in four highly industrialized cities (Shenyang, Anshan, Fushun, and Jinzhou) of Liaoning Province in Northeast China to identify the major potential sources of ambient PM2.5. A total of 814 PM2.5 and PM2.5–10 samples were collected between 2004 and 2005. All PM samples were collected simultaneously in four cities and analyzed gravimetrically for mass concentrations. A sum of 16 elemental species concentrations in the PM samples were determined using inductively coupled plasma atomic emission spectroscopy. Annual means of PM2.5 concentrations ranged from 65.0 to 222.0 μg m−3 in all the eight sampling sites, and the spatial and seasonal variations were discussed. Enrichment factors were calculated, and Cr, Cu, Zn, As, Cd, and Pb will be pollution-derived elements. Site-to-site comparisons of PM2.5 species in each city were examined using coefficient of divergence, revealing that the two sites in each city are similar in elemental species. Principle component analysis was used for preliminary source analysis of PM2.5. Three or four factors in each city were isolated, and similar sources (crustal source, coal combustion, vehicle exhaust, iron making, or some other metallurgical activities) were identified at four cities.

Considering the large amounts of PAHs emitted into the ambient air in China, it is urgent to take preliminary health risk assessment of citizens through inhalation exposure to PAHs in China. The incremental lifetime cancer risk (ILCR) model was used to get the risk level of Tianjin citizens as an example, and Monte Carlo simulation was adopted to deal with the uncertainty. Exposure analysis found that the average values of B[a]P equivalent (B[a]Peq) daily exposure doses for children in the indoor, traffic and outdoor settings were estimated to be 2,446.8, 478.4, and 321.6 ng day(-1), respectively. And those for adults were 3,344.1, 794.9, and 519.0 ng day(-1), respectively. Much attention must be paid to indoor exposure, as it contributes more than 70% of the B[a]Peq daily exposure dose. ILCR falls within the range of 10(-5)-10(-3), which is higher than the acceptable risk level of 10(-6), and lower than the priority risk level (10(-3)). So this risk should be compared with those of other public health issues in the purpose of risk management. Sensitivity analysis found that the two variables, indoor air PAHs concentration distribution and the cancer slope factor (CSF) of BaP, contribute about 89% of the total risk uncertainty. Thus they are considered as the two main factors influencing the accuracy of the PAHs health risk assessment.

TiO2 supported on active carbon fiber (TiO2/ACF), an absorbable photocatalyst, is a new kind of material applied in air purification. In this paper, the influence of environmental temperature (T) and relative humidity (RH) on the gas-solid adsorption of toluene and the photocatalytic oxidation (PCO) efficiency of adsorbed toluene on TiO2/ACF were studied, and then, the purification capability of TiO2/ACF was estimated. PCO results showed that although the PCO efficiency increased under high RH and T levels, the amount of adsorption of toluene decreased. Moreover, quantitative analysis results of intermediates indicated that more environmental risk emerged when PCO of toluene was carried out at higher environmental T and RH levels because more toxic intermediates would be accumulated on the TiO2/ACF. So, it is significant to control the environmental T and RH conditions in the application of the PCO technique. T = 25°C and RH530% is the optimal condition for purifying toluene in our experimental system.