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To explore the characteristics and sources of PM 2.5 pollution in winter of Handan City in the past five years, PM 2.5 samples were collected in winter of 2016 to 2020, and eight types of water-soluble inorganic ions were analyzed. The principal component analysis(PCA) model was used to analyze the types of pollution sources, and the backward trajectory and potential source contribution factor(PSCF) were used to simulate the transport trajectory and pollution sources. The results showed that the PM 2.5 concentration in winter of 2018 was the highest, increasing by 60.44%, 25.46%, 91.43%, and 21.53% compared with that in 2016, 2017, 2019, and 2020, respectively. In the winter of 2020, the concentration of water-soluble inorganic ions(WSIIs) decreased by 18.86% compared with that in 2016, and WSIIs/PM 2.5 decreased to 26.69%. The PM 2.5 concentration(110.20-209.65 μg·m -3 ) at night was higher than that in the daytime(95.21-193.00 μg·m -3 ). The concentration of NO 3 - and NH 4 + increased more at night. On the contrary, the concentration and proportion of Cl - decreased annually. In the winter of 2020, the daytime concentrations of K + , Ca 2+ , Na + , and Mg 2+ decreased by 69.72%, 97.10%, 90.91%, and 74.51% compared with that of 2018, and the night concentrations decreased by 66.67%, 95.38%, 91.67%, and 77.78%, respectively. In 2020, the concentrations of NO 3 - , SO 4 2- , and NH 4 + on polluted days were 4.90, 5.80, and 5.20 times those on non-polluted days, with the largest increase in five years. PCA results showed that the main sources of pollution were secondary sources, coal sources, biomass combustion sources, and road and building dust. The backward trajectory and PSCF analysis results showed that pollution transport continued to exist between south-central Mongolia and central Inner Mongolia in winter and was influenced by the transport between northern Henan and Handan and central Hebei and Handan in winter of 2016 and 2017, whereas the latter had a greater impact in winter of 2018-2020.

Based on the air quality data and conventional meteorological data of the Nanjing Region from January 2015 to December 2016, to analyze the characteristics of O 3 concentration changes in the Nanjing Region, a light gradient boosting machine (LightGBM) model was established to predict O 3 concentration. The model was compared with three machine learning methods that are commonly used in air quality prediction, including support vector machine, recurrent neural network, and random forest methods, to verify its effectiveness and feasibility. Finally, the performance of the prediction model was analyzed under different meteorological conditions. The results showed that the variation in O 3 concentration in Nanjing had significant seasonal differences and was affected by a combination of its pre-concentration, meteorological factors, and other air pollutant concentrations. The LightGBM model predicted the ground-level O 3 concentration in the Nanjing area more precisely to a large extent ( R 2 =0.92), and the model outperformed other models in prediction accuracy and computational efficiency. In particular, the model showed a significantly higher prediction accuracy and stability than that of other models under a high-temperature condition that was more likely prone to ozone pollution. The LightGBM model was characterized by its high prediction accuracy, good stability, satisfactory generalization ability, and short operation time, which broaden its application prospect in O 3 concentration prediction.

AMA GC5000BTX was used to monitor the mixing ratio of benzene, toluene, ethylbenzene, m,p -xylene, o -xylene, and styrene (BTESX) in the atmosphere of the northern suburb of Nanjing from January 2014 to December 2016. The temporal variation characteristics of BTESX and the influence of meteorological elements on it were analyzed, and the characteristic ratio method (T/B) was used to qualitatively analyze the source of BTESX. Finally, the human exposure analysis and evaluation method of EPA was used to evaluate the health risk of BTESX. The results showed that during the observation period, the average mixing ratio of BTESX was (7.28±6.63)×10 -9 , and the mixing ratio of benzene was the highest at (2.45±3.91)×10 -9 . The mixing ratio of other species from large to small was toluene>ethylbenzene> m,p -xylene> o -xylene>styrene, which were (2.41±2.61)×10 -9 , (1.37±1.28)×10 -9 , (0.51±0.48)×10 -9 , (0.3±0.36)×10 -9 , and (0.22±0.42)×10 -9 , respectively. Due to the existence of stable aromatic sources, the monthly and seasonal variation in BTESX mixing ratio was not as obvious as that of other species (NO x , CO, SO 2 , PM 2.5 , etc.). The weekend effect of BTESX and other pollutants was not significant. The mixing ratio of BTESX was largely affected by the short distance transportation of chemical enterprises and traffic trunk roads in the northeast, resulting in a large mixing ratio of BTESX in the northeast. The mixing ratio of BTESX was jointly affected by relative humidity and temperature, and its high value area was mainly located in the range of 30%-70% relative humidity. In this range of relative humidity, the high value range of BTESX volume fraction increased with the elevation of temperature. The HI (hazard index) of BTESX in different seasons was within the safety range recognized by EPA, whereas the R (carcinogenic risk of benzene) value was higher than the safety threshold specified by EPA. At the same time, the HI and R values were higher in summer, to which great attention should be paid.

In order to explore the chemical composition and source profiles of atmospheric particulate matter in winter in the northern area of Handan, a heavily polluted city in the southern part of North China, PM 1 and PM 2.5 samples were collected and analyzed from November 23 to December 12, 2020. During the observation period, the daily average ρ (PM 1 )and ρ (PM 2.5 ) were 114.53 μg·m -3 and 124.25 μg·m -3 , respectively, and the ratio of PM 1 /PM 2.5 was 83.3%-95.3%, which was significantly higher than those of other cities in the Beijing-Tianjin-Hebei region, indicating that air pollution of fine particulate matter, especially sub-micron particulate matter, was more serious in Handan. Compared with that during clean days, SNA (SO 4 2- , NO 3 - , and NH 4 + ) in PM 1 increased by 14.5% during heavy pollution, and SNA in PM 2.5 increased by 15.2%; the nitrogen oxidation rate (NOR) in particular increased by three times on heavy pollution days. With the deepening of pollution, the proportion of secondary organic carbon (SOC) in PM 1 and PM 2.5 increased by 22.0% and 12.5%, respectively. SOC tended to accumulate in small particles, whereas the proportion of primary organic carbon (POC) and elemental carbon (EC) in PM 1 decreased by 15.4% and 6.6%, and the POC and EC in PM 2.5 decreased by 8.2% and 4.3%, respectively. The above results indicated that secondary formation played an important role in the heavy pollution of particulate matter. With the aggravation of air pollution, the liquid water content of the particles increased, and both the sulfur oxidation ratio (SOR) and nitrogen oxidation ratio (NOR) increased, indicating that the aqueous phase chemical reaction made an important contribution to the formation of secondary inorganics. With the deepening of pollution, inorganic elements were on the rise; Se, As, Pb, and Zn were highly enriched in inorganic elements. The results of principal component analysis (PCA) showed that secondary formation, industrial emissions, vehicle exhaust, and biomass burning emissions were the main sources of particulate pollutants. The results of potential source contribution factor analysis (PSCF) showed that the high value areas of SO 4 2- , NO 3 - , EC, OC, and inorganic elements were mainly from the north and southwest directions of the observation area.

Sediment samples were collected from nine sites of three sections, in the intertidal zone of Haizhou bay in July 2018. The abundance and characteristics of microplastics in the sediments (and ragworms within the sediments) were then determined to identify the source of microplastics in ragworms, and to explore the effects of ragworms on microplastics in sediment. The average abundance of microplastics in tidal flat sediments was (0.49±0.17) n·g -1 , which was at a high level in domestic offshore environmental studies. Among all the microplastics detected, the most common form and color were fiber and black-gray, respectively, and the materials were mainly polyethylene (PE), polyester (PET), and polystyrene (PS). The detection rate of microplastics in ragworm was 77.78%-86.67%, with an average abundance of (6.68±2.21) n·ind -1 ; the abundance was significantly correlated with individual mass ( r =0.42, P =0.002). The microplastic abundance was significantly higher in ragworms with individual mass over 1.5 g than in those with a mass of<0.5 g or 0.5-1 g ( F 3 =141.029, P =0.000). In ragworms, microplastics were dominated by small black or blue fibers, and the main materials were PE and PET. By analyzing the various characteristics of microplastics with a particle size of 0-3 mm, it was found that the abundance of microplastics in sediments was strongly correlated with that in ragworms ( r =0.79, P =0.01); the main form ( r =0.90, P =0.035) and the material composition ( r =0.73, P =0.024) also showed significant correlation between sediments and ragworms. This indicates that ragworms ingest microplastics in the sedimentary environment and exchange the microplastics with the sediments. Therefore, ragworms can be used as an indicator species of microplastic pollution in sediments.

Ozone pollution has recently become a severe air quality issue in the Beijing-Tianjin-Hebei region. Due to the lack of a precursor emission inventory and complexity of physical and chemical mechanism of ozone generation, numerical modeling still exhibits significant deviations in ozone forecasting. Owing to its simplicity and low calculation costs, the time series analysis model can be effectively applied for ozone pollution forecasting. We conducted a time series analysis of ozone concentration at Shangdianzi, Baoding, and Tianjin sites. Both seasonal and dynamic ARIMA models were established to perform mid- and long-term ozone forecasting. The correlation coefficient R between the predicted and observed value can reach 0.951, and the RMSE is only 10.2 μg·m -3 for the monthly average ozone prediction by the seasonal ARIMA model. The correlation coefficient R between the predicted and observed value increased from 0.296-0.455 to 0.670-0.748, and RMSE was effectively reduced for the 8-hour ozone average predicted by the dynamic ARIMA model.

An investigation the optical properties and spatial distribution of dissolved organic matter (DOM) in an ecological purification system and the primary factors that affect the optical properties of the DOM was conducted. Taking the Yanlong Lake ecological purification system as an example, data from spring 2017 and 2018 were compared. The results show that the concentrations of total phosphorus and total nitrogen and the permanganate index in Yanlong Lake were 0.05-0.25, 1.25-2.75, and 3.99-7.17 mg·L -1 , respectively. In addition, the dissolved oxygen in the effluent of Yanlong Lake increased to (11.93±1.31) mg·L -1 , and the turbidity decreased to (13.23±2.24) NTU, while the change in the permanganate index was not significant. Principal component analysis (PCA) showed that the water quality of the Yanlong Lake raw water and water in the pre-treatment area was closely related to the inflow of exogenous sources, while the water quality in submerged plant areas and deep purification areas was dependent on endogenous effects. According to the fluorescence index, humification index, and biological source index analysis, it was found that there are new spontaneous sources of DOM in this body of water, the degree of humification is lower, and endogenous biological DOM is dominant. The PARAFAC model can be used to classify DOM into UV-fulvic acid-like components (239 nm, 304 nm/407 nm), visible light fulvic acid-like components (256 nm, 352 nm/439 nm), tryptophan-like protein (276 nm/327 nm) and humic acid (292 nm, 395 nm/491 nm). The UV absorption index indicates that the spectral intensity of DOM in the raw water, pretreatment unit, and emergent water plant area of Yanlong Lake fluctuates greatly, and the DOM spectral intensity of the submerged plant area and deep purification area is relatively stable. The factors affecting the optical properties of the DOM in terms of water quality parameters are mainly transparency, dissolved oxygen, conductivity, total nitrogen, and algae cell number.

Meteorological conditions have important impact on the diffusion and transport of air pollutants, thus separating and quantifying the impact of meteorological factors is a prerequisite for evaluation of air pollution control measures. Using observation data on SO 2 , NO, NO 2 , NO x , CO, PM 2.5 , PM 1 , and PM 10 as well as meteorological factors at the Chaoyang site, an urban site in Beijing, we evaluated the impact of meteorological conditions and control measures on air quality in Beijing during APEC 2014 (from 15 October to 30 November, 2014) by the multiple linear regression method. The simulation performance of a multivariate linear regression model based on the parameters of meteorological factors for predicting pollutant concentration assuming constant emission conditions were ideal, produced a range of determination coefficient ( R 2 ) of 0.494-0.783. Our results suggested that air pollution control measures reduced the concentration of SO 2 , NO, NO 2 , NO x , CO, PM 2.5 , PM 1 , and PM 10 by 48.3%, 53.5%, 18.7%, 40.6%, 3.6%, 34.8%, 28.8%, and 40.6%, while meteorological conditions reduced the concentration of SO 2 , NO, NO 2 , NO x , CO, PM 2.5 , PM 1 , and PM 10 by 1.7%, -2.8%, 18.7%, 4.5%, 18.6%, 27.5%, 30.6%, and 35.6%. The combination of meteorological factors and control measures has significantly improved the air quality in Beijing during the APEC period. Control measures played a leading role in the reduction of SO 2 and nitrogen oxides, and meteorological factors played a leading role in the reduction of CO. Meteorological factors and control measures made roughly equal contributions to the reduction of particulate matter. We also used the relative weight method to study the contribution of meteorological factors to the pollutant concentration. The results showed that the decisive meteorological factors on the concentrations of different pollutants were different.

Sewage water, the influent of the secondary sedimentation tanks, the final effluent, sludge from biological pools, and dewatered excess sludge samples from eight wastewater treatment plants (WWPTs) in Suzhou, including those from seven A 2 /O processes and one oxidation ditch process, were collected in 2017 to study the pollution characteristics of organophosphorus flame retardants (OPFRs) in WWPTs. Accelerated solvent extraction (ASE) combined with a solid-phase extraction method was used to detect the concentration of 10 organic phosphorus flame retardant (OPFRs). The removal efficiency of OPFRs was compared and final daily emissions were estimated. The results showed seven kinds of OPFRs were detected in the influent, final effluent, and sludge. The total content of OPFRs in the influent ranged from 0.74 to 222.65 μg ·L -1 (average 65.56 μg ·L -1 ), while the content in the final effluent was between 0.46 and 175.41 μg ·L -1 (average 22.99 μg ·L -1 ). The concentration in the effluent of the secondary sedimentation tank was between 0.48 and 178.14 μg ·L -1 (average 43.14 μg ·L -1 ). The daily emission of OPFRs in final effluent was 36.69-2177.12 g ·d -1 . The content in the dewatered excess sludge was between 89.32 and 596.24 μg ·g -1 dw (average 249.35 μg ·g -1 dw), the minimum daily emission was 3.57-7.15 kg ·d -1 , and the maximum was 47.70-95.40 kg ·d -1 . The oxidation ditch process has a good removal rate of OPFRs, at 92%, while the A 2 /O process removal rate covered a large range from 11%-99%. Three chlorinated OPFRs, TCEP, TCPP, and TDCPP, were the main components in the influent and final effluent, mainly because of the large consumption of OPFRs and also because the removal rate by the traditional wastewater treatment technology was low.

Eight polybrominated diphenyl ether (PBDE) congeners in indoor and outdoor air particles were collected using higher-volume active sampling techniques from different functional areas, including an industrial workplace, office, domestic area, and scenic area in an industrial zone, in Suzhou city, and the samples were analyzed by GC-MS. The total concentration of PBDEs ranged from 9.22-64.15 pg·m -3 (average 20.93 pg·m -3 ), and 1.06-8.44 pg·m -3 (average 5.11 pg·m -3 )in indoor and outdoor air, respectively. The results showed that the concentrations of PBDEs in indoor PM 10 was significantly higher than that in the outdoor PM 10 . The average concentrations of PBDEs in the air of the different sampling areas were in the order:industrial workplace-1 by the workers in the workplace, workers in office, and toddlers, respectively. Results showed that inhalation exposure to PBDEs did not cause potential health risks in the local residents of Suzhou.

This study aimed to investigate the occurrence and spatio-temporal distribution of 4- tert -octylphenol (4- t -OP), 4-nonylphenol (4-NP), triclosan (TCS), estrone (E1), 17 β -estradiol (E2), and bisphenol-A (BPA) as endocrine disrupting chemicals (EDCs) in the water of the Liuxi River and to evaluate the risks for estrogenic activity. The results showed that EDCs had been detected at the 14 monitoring sites and the total concentration ranged from 26.07 ng·L -1 to 7109.5 ng·L -1 , with the highest contribution rate coming from 4-NP (78.62%), followed by BPA (11.91%), and the other four EDCs (≤ 4.92%). On a spatial and temporal scale, the EDC contents increased longitudinally from upstream to downstream, especially in the heavily-polluted Baiyun section where the water quality was lower than level Ⅴ. The EDC contents in the tributaries were much higher than those in the main channels. Influenced by the monsoon precipitation, the contents of 4-NP, 4- t -OP, and total EDCs in the rainy season were significantly ( P <0.05) higher than those in the dry season, while the seasonal changes of E1 and E2 followed the opposite tendency. A Pearson correlation analysis showed that DO was significantly negatively correlated with all the EDCs, suggesting that the EDCs and reductive organic pollutants might coexist. As TN, TP, NH 4 + -N, permanganate index, and EC were significantly positively correlated with E1, E2, BPA, and TCS but not obviously correlated with 4-NP ( P >0.05), we presumed that the pollution source of E1, E2, BPA, and TCS might be the same with nitrogen and phosphorus nutrition, originating from the point source emission of the domestic sewage, industrial, and agricultural wastewater. In contrast, 4-NP and 4- t -OP more likely originated from the non-point source pollution from agriculture. RDA results showed that the variation of the EDCs contents by season was more obvious than that in space (RDA1 56.14%>RDA2 14.20%), which was much more influenced by 4-NP in the rainy season and by BPA in the dry season. As E1, E2, and TCS were positively correlated with the Cu, Zn, cyanide, and fecal coliform, these three target compounds could be used to indicate the multiple pollution components for water quality. Compared with the worldwide reported EDC contents in waters, 4-NP, BPA, and TCS contents in the middle and lower reaches of the Liuxi River were at higher levels, while E1, E2, and 4- t -OP were at the middle and lower levels. The risk assessment for estrogenic activity showed that the RQ values in the middle and lower reaches of the Liuxi River were all greater than 1, indicating that the downstream river sections were under high risk for estrogenic activity. As a result, appropriate precautions are needed to improve environmental management.

Ambient volatile organic compounds (VOCs) were continuously measured during the high ozone (O 3 ) periods from May 1 to May 31 and June 1 to July 16, 2015 at an industrial area in the north suburb of Nanjing. A positive matrix factorization (PMF) model and an observation-based model (OBM) were combined for the first time to investigate the contributions of VOC sources and species to local photochemical O 3 formation. The average VOC concentrations in 2014 and 2015 were (36.47±33.44)×10 -9 and (34.69±34.08)×10 -9 , respectively. The VOC sources identified by the PMF model for 2014 and 2015 belonged to 7 source categories, including vehicular emissions, liquefied petroleum gas usage, biogenic emissions, furniture manufacturing industry, chemical industry, chemical coating industry, and chemical materials industry emission sources. The OBM was modified to assess the O 3 precursors' relationships. Generally, photochemical O 3 production was VOC limited, with positive relative incremental reactivity (RIR) values for VOC species and a negative RIR value for NO. It can be seen that alkenes (1.20-1.79) and aromatics (1.42-1.48) presented higher RIR values and controlling O 3 would be the most effective when the VOC emissions from alkenes were reduced by 80%. Vehicle emissions (1.01-1.11), LPG (0.74-0.82), biogenic emissions (0.34-0.42), and furniture manufacturing industry (0.32-0.49) sources were the top four VOC sources making significant contributions to photochemical O 3 formation, which suggests that controlling vehicle emissions, biogenic emissions, LPG, and furniture manufacturing industry sources should be the most effective strategy to reduce photochemical O 3 formation.

The contamination levels and distribution characteristics of four organophosphate flame retardants (OPFRs) in 25 outdoor dust samples collected in Suzhou were quantitatively analyzed by gas chromatography-mass spectrometry (GC-MS). The exposure to OPFRs via ingestion and inhalation of dust were also estimated for adults, children, and professional street sweepers. Four types of OPFRs were detected in all dust samples at different levels; the total OPFRs concentrations ranged from non-detected (ND) to 8901.66 ng·g -1 , with a median of 1039.21 ng·g -1 . The concentrations of TCPP, TBEP, TDCPP, and TCEP were in the range of 0-6931.46, 0-2021.15, 0-788.44, and 0-62.16 ng·g -1 , respectively. The daily intake of ∑OPEs under a high dust ingestion scenario was 125.68, 915.78, and 6314.16 pg·kg -1 for adults, children, and professional street sweepers, respectively. The estimated exposure of children to ∑OPEs was six times higher than that of adults. However, the daily intake of OPFRs via dust inhalation was 3.07E-02, 1.89E-02, and 1.54E-01 pg·kg -1 for adults, children, and professional street sweepers, respectively. These findings indicated that the occurrence of OPFRs in the dust poses a significant risk to children and professional street sweepers.

The data of ozone (O 3 ) and its precursors (NO x , CO, VOCs) observed at northern suburb of Nanjing from December 01, 2013 to November 30, 2014 were used to analyze the difference of pollutant concentrations on weekends and weekdays, and its causes. The results showed that there was an obvious "Weekend Effect" in northern suburb of Nanjing. The mass concentrations of O 3 on weekdays were higher than those on weekends, whereas mass concentrations of its precursors were higher on the weekends; The average mass concentrations of O 3 were 19.84 μg·m -3 , 53.45 μg·m -3 , 57.17 μg·m -3 , and 40.43 μg·m -3 in winter, spring, summer, and autumn respectively. Compared with other seasons, "Weekend Effect " was more distinct in spring. The value of NO 2 /NO was 4.81% higher on weekdays (3.63) than on weekends (3.46). The longer cumulative time and higher accumulation rate of O 3 , and the stronger atmospheric oxidation capacity on weekdays were responsible for the higher O 3 mass concentrations on weekdays. The correlation coefficients of the mass concentrations of O 3 with VOCs, NO x , NO, and NO 2 were higher on weekdays than on weekends.

The particles number concentrations were determined by Wide-range Particle Spectrometer (WPS) in northern suburb of Nanjing in January and April 2015. The information of size distributions was applied in the multiple-path particle dosimetry model (MPPD) v.3.04 to quantify deposition fractions (DF) and number concentration (NC) depositions of fine particles in different regions of human airway, at different air quality levels, at rest and exercise. DF of nucleation mode and Aitken mode at rest and exercise were similar, while DF of accumulation mode at exercise was 2.49 times of that at rest. DF of nucleation mode and Aitken mode in pulmonary (PUL) was the highest, about 48.17% of total deposition fractions (TDF) at rest and 54.23% of TDF at exercise. DF of accumulation mode in head was the highest, about 41.23% of TDF at rest and 80.47% of TDF at exercise. The particle NC deposition in human airway in winter was lower than that in spring, and the total NC deposition in 3 regions was in the order of PUL > tracheobronchial(TB) > head. Compared with resting, nucleation mode deposition in PUL and accumulation mode deposition in TB and head increased at exercise. The worse the air quality, the higher the deposition growth rate of exercising to resting in head. DF difference among regions was mainly due to the different physiological parameters, while NC deposition difference was mainly due to the different particle NC in the local environment.

BTEX concentrations were determined by GC5000 online gas chromatography in the atmosphere of the north suburb of Nanjing in March 2013 to February 2014, using the EPA human exposure analysis evaluation method for benzene series compounds of volatile organic compounds (VOCs) in health risk assessment. The results showed that the total amount of BTEX showed the variation characteristics of spring > winter > autumn > summer. BTEX concentration was higher in the periods of 07:00-10:00 and 17:00-20:00, and the lowest was detected between 13:00-15:00; At the weekend, the concentration of BTEX was higher than on the working day. The sources of BTEX included traffic sources, industrial sources and solvent evaporation. The HQ of BTEX in all four seasons showed the order of benzene > xylene > ethylbenzene > toluene, and the HQ risk values were within the safety range in all analysis periods. The distribution of R value was winter > autumn > spring > summer, and R was higher than the safety threshold for all the analyses, indicating the existence of carcinogenic risk.

Volatile organic compounds (VOCs) in the atmosphere of the north suburb of Nanjing in December 2015 were determined by GC5000 online gas chromatography,and the main composition and characteristics of VOCs were analyzed by using the PMF receptor model sources of VOCs parsing.The United States Environmental Protection Agency (EPA) human exposure analysis and evaluation method in the United States were used to evaluate Human health risk of benzene series.The results showed that there were 6 sources in the PMF mode.Natural gas leakage accounted for 32.05%,automobile exhaust accounted for 18.99%,solvent use 13.67%,industrial emissions 2 13.20%,gasoline volatile 11.72%,and industrial emissions 1(chemical type)10.36%.The high value areas of the emission source were in accordance with the location of pollution sources surrounding the observation point.The B/T ratio was 0.74,which was at a relatively high level.The noncarcinogenic risk hazard quotient value HQ at 06:00 reached the highest value.HQ risk values were within the safe range specified by EPA.HQ of each source was as follows:automobile exhaust emissions 20.67×10 -2 ,solvent use 6.97×10 -2 ,natural gas leakage 6.34×10 -2 .In the carcinogenic risk of benzene,automobile exhaust emissions was 4.11×10 -6 ,and natural gas leakage was 1.09×10 -6 ,both were higher than the EPA specified safety threshold.

To study the variation characteristics of water soluble ions during youth Olympic Games, PM 2.5 and water soluble ions were observed by using the beta dust instrument, Anderson 9th sampler and IC type ion chromatography analyzer from August 6 to September 4, 2014. The observations were divided into three types of weather, sunny, rainy and cloudy. The average concentrations of PM 2.5 under different weather conditions were sunny > cloudy > rainy days. The concentrations of water soluble ions in PM 1.1 , PM 1.1-2.1 and PM 2.1-10 were also sunny > cloudy > rainy days, and the obliterate of fine particles by precipitation process was more obvious. The spectra of Ca 2+ and Mg 2+ were bimodal. The scavenging effects of SO 4 2- and NH 4 + in range of 0.65-1.1 μm were stronger. The ratio of NO 3 - /SO 4 2- under different weather conditions was less than 1, and the ratio of NO 3 - /SO 4 2- in rainy and cloudy days was higher than that in sunny days. The values of SOR and NOR in the three kinds of weather conditions were more than 0.1, SO 2 and NO 2 had different degrees of transformation, there was more secondary pollutant in the atmosphere.

The concentration and distribution of PBDEs in liver, heart, brain, egg and muscle tissues of market farmed fish and wild river fish (crucian carp) from Taizhou, which is a large e-waste recycling site in China, were quantitatively measured using gas chromatography -negative chemical ion tandem mass spectrometry (GC-NCI-MS). The dietary intake of PBDEs via the consumption of fish by the population of this region was also estimated. The results showed that the concentrations of PBDEs in the muscle of river fish samples near the e-waste recycling site were significantly higher than those in the market farmed fish without obviously polluted sources of PBDEs. The distribution of PBDEs in various tissues was not even, and the highest and lowest mean concentrations of total PBDEs ( sigma PBDEs) were 18.82 ng x g(-1) and 1.97 ng x g(-1) (wet weight), in heart and egg tissues, respectively. A similar PBDE congener profiles in different tissues of farmed fish were found. Among PBDE congeners, BDE-47 was predominant in various tissues accounting for above 50% of the total PBDEs, and followed by BDE-183 (about 20%), BDE-99 and BDE-153. While different profiles of PBDEs in muscle tissues between wild fish in river and market farmed fish were observed, that BDE-47, -153 and -99 were dominant for the former type. These facts suggested primitive e-waste recycling behavior to be a pollution source of high levels of PBDEs in wild fish. The average estimated daily intake of PBDEs via river fish consumption by local residents near the e-waste recycling site in Taizhou was approximately 29.0 ng, slightly higher than that in other regions.

Using two vehicles fuelled with pure gasoline, M15, M30 and pure gasoline, E10, E20 separately, 25 degrees C normal temperature type I emission test, -7 degrees C low temperature type VI emission test and type IV evaporation emission test were carried out. FTIR, HPLC and GC-MS methods were utilized to measure alcohols, aldehydes, aromatic hydrocarbons and olefins emissions. The test results indicate that at the low as well as normal ambient temperature, as the alcohols proportion increasing in the fuel, unburned methanol, formaldehyde, acetaldehyde increase proportionally, benzene, toluene, ethylene, propylene, 1,3-butadiene and isobutene decrease slightly. The unregulated emissions at the low ambient temperature are significantly higher than those at the normal ambient temperature. The difference of HC emissions in the entire process of evaporative emission tests of E10, gasoline and M15 fuels is slight. There is a small difference of unregulated emissions in the diurnal test of three fuels.

With the purpose of establishing diesel fuel standard for China National 4th Emission Standard, as one part of Beijing "Auto-Oil" programme, engine performance test has been done on a typical Euro IV diesel engine using eight diesel fuels with different fuel properties. Test results show that, fuel properties has little effect on power, fuel consumption, and in-cylinder combustion process of tested Euro IV diesel engine; sulfate in PM and gaseous SO2 emissions increase linearly with diesel sulfur content increase; cetane number increase cause BSFC and PM reduce and NOx increase; T90 decrease cause NOx reduce while PM shows trend of reduce. Prediction equations of tested Euro IV diesel engine's ESC cycle NOx and PM emissions before SCR response to diesel fuel sulfur content, cetane number, T90 and aromatics have been obtained using linear regression method on the base of test results.

Life Cycle Assessment (LCA) was used to compare energy consumption and pollutant emissions of two oxygen biofuels, ethanol and methyl ester, which were mixed with gasoline and diesel oil at levels of 10% and 30% of the biofuel. The future of oxygen-containing biofuels was analyzed and forecasted. The results show that the mixture of biofuels and petroleum products can reduce crude oil consumption, but only methyl ester alternative fuel can reduce fossil fuel consumption. Use of methyl ester mixtures would reduce NOx by 50% compared to gasoline or diesel on a life cycle basis; however, NOx would increase using ethanol. Each alternative fuel mixture reduced PM10 emissions from the vehicle and methyl ester decreased VOCs. The SO2 emissions from the fuel production processes, which account for about 80% of SO2 life cycle emissions, must be strictly controlled.

Catalytic properties of Ag/Al2O3, In/Al2O3, Sn/Al2O3, Co/Al2O3, Pt/Al2O3 and a two-stage catalyst composed of Ag/Al2O3 and Pt/Al2O3 were investigated for the selective reduction of NO by C3H6 or C2H5OH in excess oxygen. The Ag/Al2O3 showed the highest NO reduction activity among the catalysts studied. A substantial amount of CO was formed over alumina-based transient metal oxides. HC and CO oxidations over Pt/Al2O3 occurred in relatively low temperatures, compared with the other catalysts. The sequential use of Ag/Al2O3 and Pt/Al2O3 was effective to broaden the temperature window for the reduction of NO, to improve oxidation of HC and CO and to inhibit the formation of N2O and CH3CHO.

Six water samples were collected, and twenty-one compounds of organochlorine pesticides (OCPs) in surface water from the Pearl River Artery estuary were analyzed quantitatively, based on USEPA 8000 series methods and under quality assurance and quality control (QA/QC). The total (particulate plus dissolved phase) concentration of OCPs in surface water from the Pearl River Artery estuary in both high flow season and low flow season were 9.7 ng/L-26.3 ng/L and 41.7 ng/L-122.5 ng/L respectively. The concentration of total HCHs and total other OCPs was much higher than that of DDTs. The seasonality of the concentration of OCPs was significantly, and the level of OCPs in low flow season was higher than that of OCPs in high flow season. The spatial and temporal distribution of OCPs suggested that there were significant differences of OCPs between the East River (Dongjiang) network and Guangzhou channel and the nonpoint-source pollution of OCPs was found in the Pearl River Artery estuary, particularly in high flow season.