Based on observed PM_2.5 concerntration data and atmospheric self-cleaning ability index (ASI) calculated by meteorological observation data, the change of pollutant emission rate per capita during two periods by applying urban atmospheric load index was analyzed. Meanwhile, the effects of meteorological condition and emission reduction on the change of air pollutant concentration during Sep. 2013 to Feb. 2019 were investigated. The emission reduction in autumn and winter was more obvious than that in spring and summer. The effect initially appeared in autumn and winter of 2014 due to emission reductions occurred in 74.5% cities, and on average emission reduction was 12.6% in this area. Emission reduced substantially in the autumn and winter of 2017 and 2018 in major cities of Beijing-Tianjin-Hebei and its surrounding areas, with emission reduction rate being 54.0% and 47.7% respectively relative to the baseline. Emission of autumn-winter in Changzhi during 2014~2017 was more than that in baseline, and started to decline in 2018. The change of emission rate in Shijiazhuang presented large fluctuation, and it in winter of 2016 was 68.2% more than that in 2014. Hence, special attention should be paid to these two cities. Urban atmospheric load index can objectively and quantitatively reflect the direction and magnitude of the change of emission rate in typical emission reduction periods, so it is an effective method to evaluate the effects of meteorological conditions and emission control measures on pollutant concentration change.

A numerical correction of the O₃ concentration forecasted by the Rapid refresh Multi-scale Analysis & Prediction System-CHEM (RMAPS-CHEM v1.0) was performed by using the Analog Ensemble (AnEn) method with 2a historical observations at 70 sites and forecast datasets in Beijing-Tianjin-Hebei region. The correction ability of the AnEn was evaluated against observed data from June to September 2018. The results showed that the performance of AnEn first increased and then decreased with the increase of ensemble member. The optimal performance was achieved when 14 members were used. The sensitivities of main forecast factors were different:the forecasted O₃ from the RMAPS-CHEM showed the greatest weight, followed by temperature at 2m, relative humidity at 2m, wind speed at 10m, and planetary boundary layer height. The predicted O₃ concentration from the RMAPS-CHEM was improved significantly using the AnEn method. The improvement was obvious for both the magnitude and spatiotemporal variation of predicted O₃ concentrations. The correlation coefficients between observed and AnEn-predicted O₃ concentrations were 68.6% larger than those between observed and RMAPS-CHEM-predicted concentrations. The root mean square errors after correction were 25% smaller. In addition, the performance of the AnEn method showed obvious spatial and diurnal variations in Beijing-Tianjin-Hebei region. In the daytime, the improvement was more evident in the eastern part of Beijing-Tianjin-Hebei region and in large cities, while at night, significant improvement mainly occured in urban areas. The performance of AnEn was generally better at night than in the daytime. Besides, the probability density distribution of O₃ modified by the AnEn method is closer to the observation than that of the RMAPS-CHEM, especially in areas with low (<35μg/m³) and high (>200μg/m³) O₃ concentrations. Evaluation at three cities during a typical O₃ pollution event indicated that the performance of the AnEn method was better in the forecast period of 0~48h than in 48~96h. The AnEn method performed best in Tianjin city, followed by Beijing and Shijiazhuang. Overall, the AnEn method showed better performance than RMAPS-CHEM in terms of the prediction of O₃ concentrations in Beijing-Tianjin-Hebei region, and thus could be applied more widely to the O₃ concentration forecast in North China.

Basing on the aerosol optical depth (AOD) and aerosol relative optical depth (AROD), retrieved from the Aerosol Robotic Network (AERONET) sites in China from 2006 to 2018, we classified the aerosol types and studied its spatiotemporal variations at the sites including Beijing, Taihu, Hong Kong and SACOL, representative of North China, East China, South China and Northwest China, respectively. The continental and urban industry aerosols were the dominant types of aerosols in the North, South and East China. The continental aerosols was the dominant aerosol type in Northwest China. The ratio of different aerosol types to the total aerosol existed distinct interannual variation in each region. Our results showed that the continental aerosols increased while sub-continental aerosols decreased during the past decade in North China, and especially in East China, where the clean continental aerosols' proportion rose at the rate of 2.78% per year, and the proportion of the urban industry aerosols dropped by 1.86% per year. On the other hand, the proportion of continental aerosol grew by 0.78% and urban industrial aerosol fell by 0.66% annually in South China. As the main source area of dust emission, the proportion of dust aerosols changed significantly in Northwest China, with an average annual increase of 0.51%. The seasonal variations of aerosol types were also found to be large in different areas. Dust aerosols occurred frequently during spring in North China, East China and Northwest China, and the percentage of dust in the latter was much higher than the other two regions (19%). The proportions of the urban industrial aerosols and continental aerosols in North China showed the highest values in summer and winter, respectively. The ratio of the urban industry aerosol in East China was substantial in summer and autumn, but the highest ratio of the urban industry aerosol in South China occurred in spring with the value of 57%. As for the Northwest China, the proportion of the continental aerosol was the highest in summer and autumn (83%).

Statistical characteristics of spring aerosol particle concentration and mass concentration over the Wutai mountain in Shanxi province based upon the particle concentration and mass concentration data observed by Grimm180 aerosol instrument over the Wutai mountain in Shanxi province. The Global Data Assimilation System (GDAS) data provided by the National Environmental Prediction Center (NCEP) from March to May 2018, cluster analysis and potential source contribution factor analysis (PSCF) were also utilized to reveal the main transmission path affecting the aerosol concentration variation, as well as the potential contribution source area. There were mainly 6 types of transmission routes affecting the aerosol concentration over the Wutai mountain in spring, of which the first, fourth, second and fifth were northwestern and westward, accounting for 62.5% of the total trajectory; while the third and sixth type were in the southern and eastern directions, accounting for 24.7% of the total trajectory. The statistical analysis of different transmission paths showed that the first and fourth types had the greatest influence on the concentration of PN₁₀, PN_>10 and PM₁₀, whose potential contribution source areas were mainly located in western Inner Mongolia and the Loess Plateau in northern Shaanxi Province, in which the PSCF values reached 0.6 or more; whereas the sixth and third type of routes had a larger impact on the PN_0.5, PN_1.0, and PM_1.0 concentration, of which the potential contribution source areas were mainly within the south-central and central Shaanxi Province, Beijing-Tianjin-Hebei region and northern Henan Province, in which the PSCF values were above 0.8. The high-value zone of fine particle PSCF was mainly located in the eastern and southern region around the Wutai mountain with the transmission height lowering than 2km. As the particle size increased, the high-value zone of PSCF became the northwestern and southeastern region, and the transmission height was within 2~4km of the free troposphere, through which the proportion of transportation at northwestern region increased gradually, and the high-value zone got farther and farther away from Wutai mountain station.

In order to analyze the characteristics of water-soluble ion pollution and its extinction contribution in the northern suburbs of Nanjing, PM_2.5 observation experiments were carried out from March 15 to April 15, July, and October in 2017, and the concentration characteristics of PM_2.5 and its components, the conversion characteristics of water-soluble ions and their precursors, and the optical characteristics of water-soluble ions in the three seasons of in Nanjing were analyzed. The results showed that the mass concentration of PM_2.5 during sampling is (93.8 ±40.3)μg/m³. Among them, 54.2% were water-soluble ions, and its total mass concentration was (50.9±25.6)μg/m³, and secondary water-soluble ions (SNA) accounted for 76.8% of water-soluble ions. The distribution of each water-soluble ion component was:NO₃^- > SO₄^2- > NH₄⁺ > Ca²⁺ > Cl^- > NO₂^- > K⁺ > F^- > Mg^{2 +} > Na⁺. In terms of seasonal changes, PM_2.5 and main water-soluble ions were high in spring and low in summer, but NO₃^- < SO₄^2- in summer. The average values ??of sulfur conversion rate (SOR) and nitrogen conversion rate (NOR) during the sampling period were 0.38 and 0.22, which indicated that Nanjing had a strong secondary conversion process. During the sampling period, the average[NO₃^-]/[SO₄^2-] The value of was 1, which indicated that water-soluble ions were mainly derived from emissions from mobile sources. The atmospheric extinction coefficient calculated by IMPROVE formula was lower than the actual value, but it can more accurately reflect the trend of Nanjing extinction coefficient. The extinction contribution of each component was (NH₄) ₂SO₄ (38.9%), NH₄NO₃ (36.7%), POM (13.6%), EC (9.3%), NO₂ (1.5%). Among them, the SNA extinction contribution accounted for more than 70%, the SNA extinction contribution was the largest in spring, and the smallest in summer.

Based on the real-time, on-line PM_2.5 monitoring data from 206 monitoring stations in Tangshan City, during three different periods, including heating period, heavy pollution period, and non-heating period, respectively, this research was to study the spatial distribution characteristics and spatial autocorrelation of air pollution so as to provide the basis to enhance air pollution control in Tangshan City, by using ArcGIS as the platform. All three periods had a certain spatial autocorrelation and the global spatial autocorrelation during heavy pollution period was the strongest. During heating and heavy pollution periods, the High-High cluster of PM_2.5 mainly occurred in the central areas of Tangshan, while the Low-Low cluster was mainly distributed in the northern mountain areas and a small portion in coastal areas. High-High cluster of non-heating period was mainly distributed in Fengrun District and Fengnan District, while Low-Low cluster occurred in the northern part of Zunhua. Through spatial interpolation, the PM_2.5 distribution of the whole city was simulated to result that the highest grid point value of PM_2.5 in Tangshan is 241μg/m³ during heavy pollution period, while the lowest value is only 37μg/m³ in non-heating period. Based on the characteristics of PM_2.5 concentration variation and spatial distribution, the 18 districts and counties of Tangshan were divided into 5 zones, and corresponding suggestions on PM_2.5 control measures for each zone were proposed.

We developed a coupling model combining the radial basis function (RBF) artificial neural network and the genetic algorithm to predict the average PM_2.5 concentrations in Beijing in the next 24hours. This model mainly used air pollutant concentration data obtained by air quality monitoring stations as inputs, and relied on the genetic algorithm to determine parameters such as the number of hidden layer neurons and the spread constant. The model had a good prediction performance (R-square up to 0.75) with less data inputs because it does not need meteorological or geographical information for its training process. Further improvements can be made by using multi-source data and increasing sample size in the training process to enhance the accuracy and robustness of the model for the prediction of air pollution in different situations.

In order to improve the forecasting ability of PM_2.5 concentration, especially the forecasting ability of PM_2.5 heavy pollution, this study was based on the mesoscale meteorological-chemical coupled modeling system (WRF-Chem) forecast data in combination with weather and PM_2.5 (fine particulate matter) observational data, a machine learning model of PM_2.5 prediction in Shanghai, China was established. The results showed that the machine learning algorithm combined with WRF-Chem prediction obviously corrected the deviation of model prediction due to the non-objectivity of the model, and improved the prediction effect. The linear regression method (Lasso) could not obtain a suitable optimization effect, and the deep learning sequence to sequence algorithm was selected to improve the model and verified by experiments. The overall correlation coefficient of the method for the PM_2.5 prediction increased from 0.51 to 0.79. The root mean square error was reduced from 25.9μg/m³ to 15.0μg/m³. The Seq2seq modified PM_2.5 forecasting model based on WRF-Chem can effectively improve the prediction accuracy. It took a useful application prospect in air quality forecast.

Experiments and theoretical analysis were conducted in a residential building in Changzhou to study particle penetration efficiency and deposition rate through establishing lumped parameter model of indoor PM_2.5 concentration. Meanwhile, the accuracy of those models were tested and verified by experiments using a dynamic model, and the collection time from March 2017 to January 2018. According to the experimental data, the result of PM_2.5 penetration efficiency was 0.78 to 0.97, while for deposition rate, it was 0.3 to 0.69h^-1 when air exchange rate ranged from 0.31 to 0.89h^-1. The models could be well applied to indoor particle prediction under different ventilation methods such as natural ventilation, mechanical ventilation, etc. The indoor PM_2.5 concentration ranged from 40 to 46μg/m³ by using fresh air system with 82% filtration efficiency, while outdoor PM_2.5 concentration was 135 to 150μg/m³.

The arid and semi-arid area in Northwest China is an important dust source region in the world. Compared with other major dust sources around the globe, this region is characterized by the complexity of its surrounding landform. In this paper, the WRF mesoscale weather forecast model coupled with the GOCART atmospheric chemical-aerosol radiation and transmission model was used to simulate a large-scale dust episode which originated from the dust source region in northwest China from April 27, 2011 to May 2, and verified by the MODIS remote sensing data, the airborne dust reservoir effect of Tarim Basin on dust aerosol distribution was found. In order to verify this effect and its impact on the air quality of downwind city, hourly mass concentration of water-soluble Ca²⁺ in PM₁₀ was monitored in Lanzhou during this period. Combined with CALIPSO vertical aerosol feature mask product and HYSPLIT air mass trajectory model, PSCF was used to analyze the 48-hour backward trajectories of air mass which arrived at Lanzhou during this dust episode. The simulation, remote sensing and site monitoring indicated that the effect of Airborne Dust Reservoir would constrain and accumulate the inbound dust aerosol. Meanwhile, if the wind direction changed, the suspended dust aerosol constrained by the basin could re-release as a secondary dust source, which would exacerbate the impact of the dust episode on the air quality of downwind city.

Based on the analysis of the spatial-temporal distribution of dust weather, the wind fields, and the AI(Aerosols Index) at 90 stations over the past 20 years, the occurrences and transport pathways of dust weather in this region are identified. Permanently dusty land was the source of most blowing sand weathers on the peninsula, beginning to expand in February and peaking in June. The distribution of floating dust was similar, but with another high-value center in the northern Hijaz Mountains, connecting with the high-value area of permanently dusty land in March, reaching its maximum area in June-July, after then shrinking and splitting into several small parts. The AI Index was distributed as a "down arrow" relatively high value center, with an evident unimodal distribution. The intensity and area of AI reached a peak in June. From October to April and from May to September, the wind direction in the peninsula respectively shifted clockwise and counterclockwise, driving dust transport downstream. Synoptic analysis showed that with the cold front invading the peninsula the cold air moved quickly from the north lifting the warm air, which was the main reason for the dust weather. The backward trajectory clustering analysis presented three transport routes over the peninsula, to the Sahara desert in the northwest direction, from Iraq or Iran by counter cyclone field, and the local transport.

The greenhouse gases inventory of central China was calculated according to IPCC guideline, and then a systematical analysis was conduct to reveal the status of animal husbandry in terms of total greenhouse gases emissions and emission intensity. In addition, a Logistic growth model, a Gompertz curve model and other non-linear time series models were used to simulate the livestock numbers and the corresponding greenhouse gases emissions of livestock in central China in 2030. In 2015, the total emissions of central China was 62.8909 million tCO₂-eq, with emissions per unit GDP about 11,300tCO₂-eq/billion yuan, or emissions per unit meat output about 3.73tCO₂-eq/t. In 2030, the total emissions range from 49.90 to 59.33million tCO₂-eq according to different model settings. Technical improvement in animal husbandry should be further optimized to promote the greenhouse gases emission efficiency. In addition, plans for keeping reasonable livestock with optimized structure is also essential to reduce the emissions of animal husbandry.

To explore the emission characteristics of carbonyl compounds (CCs) from boilers with different fuel types, the exhausts from the stacks of 14industrial boilers, whose fuel type included coal, biomass, petroleum coke and natural gas, and 2coal-fired utility boilers were sampled in the study. 21CCs were analyzed by a PFPH-derivatization-GC/MS method. The results showed that the composition of CCs in the exhausts varied significantly among different fuel types of boilers (One-way ANOVA, F=4.458, P=0.028<0.05). The total mass concentration of CCs (based on 9% oxygen content) was ranked as petroleum-coke-fired boilers > coal-fired utility boilers > coal-fired industrial boilers > gas-fired boilers > biomass-fired boilers, with the total mass concentrations of (6306.25±1335.35), (5745.96±2864.62),(5313.57±2959.36), (2461.38±1052.35), and (1341.18±616.46) μg/m³, respectively. Furthermore, among all types of boilers, low-molecular-mass-weight CCs, (e.g. formaldehyde, aldehyde, acetone and propanal) were the most important contributors to the total CCs of the exhaust, which occupied 87.56%, 91.36%, 92.94%, 78.70%, and 45.84% in the exhausts of petroleum-coke-fired, coal-fired utility, coal-fired industrial, gas-fired boilers and biomass-fired boilers, respectively. At last, ozone formation potential (OFP) was evaluated by maximum incremental reactivity (MIR) and total hydroxyl radical (OH) reactivity by CCs, respectively, revealing that formaldehyde, propionaldehyde, acetaldehyde are the key species with high OFP and (OH) reactivity.

A gaseous nitrous acid (HONO) prediction model based on Stacking ensemble learning was proposed. The concentrations of HONO in Beijing urban area were obtained using incoherent broadband cavity enhanced absorption spectroscopy (IBBCEAS). Combined with the HONO sources, O₃, CO, SO₂, NO, NO₂, NO_y, temperature (T), relative humidity (RH), wind speed (WS), j(HONO), j(NO₂), j(O¹D) were selected as characteristic data. By analyzing the average diurnal variation of HONO, the measurement time was converted into a new feature hour by hour. The base model was constructed by utilizing Extreme Gradient Boosting (XGBoost), Light Gradient Boosting Machine (LightGBM) and Random Forest (RF) algorithm. The training set was partitioned by 5-fold cross-validation method. The output of the base model was taken as a new feature set and as the input of second-level linear regression model. HONO prediction model was finally obtained via training the models in these two layers. Through the feature importance analysis and calculating the contribution of direct emission of vehicles at night, it showed that CO was an important impact factor in the prediction model, and that the direct emission of vehicles was a major source of HONO in the winter period at the region. The prediction performance of the base model and the Stacking ensemble model were evaluated by the test set respectively. The correlation coefficients between forecast results and measured values for the three base models were above 0.91. The performance of the Stacking ensemble model was the best, whose correlation coefficients reached 0.94. The average absolute error and root mean square error were 0.307×10^-9 and 0.453×10^-9, respectively. Explanability and applicability of the HONO prediction model based on Stacking ensemble learning.

Cu/SSZ-13catalysts with different Si/Al ratio were prepared by a solid-state ion exchange method, which were used for selective catalytic reduction of NO_x with NH₃ (NH₃-SCR) reaction. Various characterization methods, including X-ray diffraction (XRD), temperature programmed reduction with H₂ (H₂-TPR), temperature programmed desorption (TPD) of NO_x, temperature programmed desorption (TPD) of NH₃, and in situ diffuse reflectance FTIR spectroscopy (in situ DRIFTS), were used to elucidate the different catalytic performance over these Cu/SSZ-13catalysts. Compared with Cu/SSZ-13(25) and Cu/SSZ-13(5), Cu/SSZ-13(10) showed relatively superior SCR activity, with more than 80% NO conversion between 200 and 450℃. The XRD and H₂-TPR results suggested that Si/Al ratio could influence the dispersion of Cu species and redox property of Cu/SSZ-13 catalysts. The XRD and H₂-TPR results indicated that there were the most isolated Cu²⁺ ions existed in Cu/SSZ-13(10). Cu²⁺ ions could provide NO_x-adsorbed sites and Lewis acid sites over Cu/SSZ-13, which mainly account for its low-temperature SCR activity. However, the NO conversion of Cu/SSZ-13(25) decreased obviously in the whole temperature range, due to the significant loss of Lewis acid sites.

Volatile organic compounds (VOCs) have become one of the main atmospheric pollutants. Most of VOCs contain a large amount of water vapor, and the relative humidity (RH) is >60%. Therefore, it is crucial to developing hydrophobic adsorbents. In this contribution, tetraethyl orthosilicate (TEOS) was used as a hydrophobic agent to modify the surface of hydrophilic silica gel and prepare the hydrophobic silica gel through hydroxyl grafting reaction. The structure and stability of the adsorbent after grafting reaction was characterized by BET, FT-IR, XRD and TG-DTG. The performances of adsorption on various VOCs were investigated. The results shown that TEOS was successfully grafted on the surface of silica gel and hydrophobic silica gel was prepared. In addition, the mechanical strength has been increased to 66.85%, and stability of silica gel have been improved, the adsorbent after calcination in air at 550℃ is still hydrophobic and its adsorption capacity is twice than before. Last but the most important, higher adsorption capacity of VOCs as well as excellent thermal regeneration of this hydrophobic silica gel could be received under the conditions of high humidity and high concentration VOCs. The adsorption capacity of the hydrophobic silica gel at high concentration was 10 times than that at the low concentration and not affected by water vapor; the adsorption/desorption of the silica gel for 10 cycles was almost unchanged and the desorption rate of 90% was reached in 15-30min under certain conditions.

In-situ and on-line measurement of flue gas desulfurization reaction is critical for understanding mass transfer process during SO₂ absorption in a spray tower and improving desulfurization efficiency. The absorption process of SO₂ by Na₂CO₃ spray droplets was characterized. A Global Rainbow Technique (GRT) system was set up to measure the refractive indices of spray droplets. SO₂ was absorbed by Na₂CO₃ spray droplets, generating Na₂SO₃. Refractive indices of spray droplets gradually increased with the desulfurization reaction process. The linear relationship between the refractive indices of spray droplets and Na₂CO₃ consumption made it possible to evaluate the desulfurization reaction process quantitatively. The Na₂CO₃ consumption was about 62.1% and the absorption reaction rate was thus 8.8×10^-6kmol/(m²·s).

To reveal the relationship between the performance of upflow anaerobic sludge bed (UASB) reactor and syntrophic propionate-degrading consortia at startup, the operational characteristics during corn starch processing wastewater treatment in a UASB were investigated. The succession of syntrophic propionate-degrading consortia (propionate-oxidizing bacteria and methanogens) at startup was analyzed by quantitative real-time fluorescence polymerase chain reaction (qPCR). COD removal reached 91.9% after 38d operation under influent COD of 2000mg/L and hydraulic retention time (HRT) of 24h conditions. When HRT was shorten to 8h by stepwise, the specific methanogenic rate achieved 315LCH₄/(kg COD·d) and the granular sludge with good settling performance was formed. qPCR analysis showed that five identified species of propionate propionate-oxidizing bacteria existed in the UASB reactor. Pelotomaculum propionicum was the major propionate-oxidizing bacteria in inoculation sludge, accounting for 45.7% in detectable propionate-oxidizing bacteria. Its number was reduced as HRT shorting. However, the quantity of Syntrophobacter sulfatireducens and S. wolinii were increased as HRT decrease. The maximum with 1.3×10³ and 5.5×10³ 16S rDNA copies/ng DNA was reached in the end of startup, becoming the dominant propionate-oxidizing bacteria in the granular sludge. Methanobacterium and Methanosarcina were the dominant hydrogenotrophic and acetotrophic methanogens in the inoculation sludge. Their numbers were gradually reduced as HRT decrease. The quantity of Methanospirillum and Methanosaeta were increased, being the predominant methanogens in the granular sludge.

In order to address the denitrification problems of sewage plant effluent, type-A molecular sieve was synthesized by hydrothermal method with four different process schemes, using natural zeolite as a raw material that was collected from Gongyi, Henan Province. The synthesized product was examined for its adsorption performance on ammonia nitrogen, purity, crystal structure, morphology, porosity and other structural characteristics. The suitable process scheme for synthesizing high efficiency molecular sieve from natural zeolite was then explored. The alkali melting activation process was more effective than the direct alkali dissolution process in terms of the silicon source utilization from the raw material, while the product from silicon source purification synthesis scheme had a significantly improved ammonia nitrogen adsorption performance, with an equilibrium adsorption capacity of more than 20mg/g. It was associated with orderly crystal morphology, low impurity contents, and unobstructed pore channels, all of which were conducive to adsorption, diffusion and other mass transfer processes. By comprehensively considering the energy and materials consumption for synthesis and the adsorption properties of the synthesized product, the process scheme of alkali dissolution and silicon source purification was deemed as the suitable process plan to type A molecular sieve using natural zeolite.

The potential mechanisms for anaerobic phenol degradation and methanogenesis promotion by biochar addition were evaluated by batch experiments,and the effects of biochar derived at 300,500 and 700℃ on lag time,maximum methane production rate and microbial community structure were elucidated in this study. The results indicated a strong linear relationship between the electron exchange capacity of biochar and Rmax (R²=0.997). Furthermore, methanogenic lag time was notably shortened from 15.0days to 1.1~3.2days, and the maximum CH₄ production rate was increased from 4.0mL/d to 10.4~13.9mL/d by biochar addition (15g/L). Moreover, the methanogenesis of phenol was optimized by addition of biochar prepared at 500℃ because of the most abundance of electrochemically active quinones.In addition, microbial community analysis showed that the electroactive Geobacter and Methanosaeta microbial consortia were enriched by biochar addition. It was further demonstrated that biochar addition fueled the methane production rate of phenol by promoting interspecies electron transfer.

Aiming to solve the problems of decreased nitrogen removal efficiency of constructed wetland (CW) under the low temperature in winter, immobilization of the enriched cold resistant ammonia-oxidizing functional consortia was added into CW to explore its biological enhancement effect on nitrogen removal of CW under low temperature, as well as its microbial function mechanisms. Results showed that, at 5℃, the average ammonia removal rate of CW added with cold resistant ammonia-oxidizing functional consortia cultivated under gradient cooling (R1) and gradient cooling coupled selective inhibition (R2) were 84% and 88%, which were 24% and 28% higher than that in the control, respectively. High-throughput sequencing results revealed that Nitrospira sp., which belongs to complete ammonia oxidizing bacteria, was the dominant bacteria with the relative abundance up to 19.2%, and played the major role in the ammonia oxidation in CW. Analysis of microbial relative expression level showed that the expression abundance of ammonia oxidation gene amoA in the two groups of bio-enhanced constructed wetlands was 2.82×10⁸ and 8.22×10⁸copies/g matrix, which was significantly higher than that in the control, which was 2.50×10⁷copies/g matrix. Generally, the nitrogen removal efficiency of CW could be effectively improved by adding cold resistant ammonia-oxidizing functional consortia.

Three typical dyes, methylene blue, acid orange 7, and rhodamine B were treated by base catalysis of PMS in this study to investigate the optimal degradation conditions and the mechanism. Under the optimal condition (pH=10.8~11.5(methylene blue) or pH=10.0~10.8(acid orange 7 or rhodamine B), PMS dosage=100mg/L), the decolorization rate constants of methylene blue, acid orange 7 and rhodamine B were 0.097, 0.074, and 0.004min^-1, respectively, and the decolorization efficiency were 95.1%, 93.3%, and 30.1%, respectively. The scavenging tests indicated that singlet oxygen played a critical role in the treatment by PMS/base for all of the three dyes. Based on the results of UV-Vis spectra analysis, it could be speculated that the faster decolorization rates of methylene blue and acid orange 7 could be due to the more efficient oxidation of the thiazide chromophore group and the azo bond by singlet oxygen.

Zero-valent iron (Fe⁰) activated persulfate (PS) advance oxidation process was applied to degrade organic Eriochrome black T (EBT) dye in water. The effects of different system (PS oxidation alone, Fe⁰ and Fe⁰/PS, PS/Fe⁰ molar ratio, inorganic ions(NO₃^-, CO₃^2-, Cl^-), initial solution pH value, temperature and natural organic matter on the EBT degradation was investigated. The experiment result indicated EBT degradation followed well with the pseudo-first-order kinetic model (R²>0.87). Compared with the Fe⁰ and PS oxidation alone, EBT can be removed efficiently by Fe⁰/PS system, the removal percentage of EBT can be reached to 96. 21%. The optimum molar ratio of PS/Fe⁰ for EBT degradation was 1:1.5. Inorganic ions (NO₃^-, CO₃^2-) and natural organic matter had negative influence on degradation of EBT to a certain extent. The degradation rate of EBT decreased with the increase of initial solution pH. With the increase of temperature from 303K to 318K, the degradation rate increased at the beginning and then decreased slowly, meanwhile the reaction activation energy (Ea) was 43. 98kJ/mol. The removal efficiencies of EBT in real water still kept a high level. Based on the analysis result of GC-MS, ten intermediates were identified and the degradation pathway was proposed. The evaluation results of ECOSAR model showed that the ecotoxicity of small molecular organic matter from EBT degradation products was higher than that of macromolecular organic matter.

F-SnO₂/GAC particle electrode was prepared by sol-gel method using granular activated carbon (GAC) as substrate. Scanning electron microscopy (SEM), Energy dispersive spectrometer (EDS), X-ray diffraction (XRD), X-ray photoelectron spectroscopy (XPS) and Cyclic voltammetry curve(CV) were used to characterize the particle electrode. And it's electrocatalytic performance was investigated with Rhodamine B (RhB) as the target pollutant. The results showed that:F-SnO₂ nanoparticles are uniformly distributed on the inner and outer surfaces of the GAC, and the crystals are intact; the SnO₂ active components modified by F^- doping can increase the amount of transition charges in the reaction system and improve the electrocatalytic activity. When the mass concentration of RhB was 300mg/L, the initial pH 3, the voltage was 9V and reaction time 30minutes, the decolorization rate and COD removal rate of RhB by 10%F-SnO₂/GAC particle electrode calcined at 500℃ for 2h reached 97.6% and 89.0%. Electron spin resonance (ESR) technology has determined the electrocatalytic process mainly by indirect oxidation of hydroxyl radicals (·OH) to remove contaminants.

Sulfidated-nanoscale zerovalent iron (S-NZVI) was prepared by pre-sulfide synthesis and characterized. The S-NZVI reaction zone was established in sand columns to study the remediation efficiency of nitrobenzene contaminated groundwater. X-ray diffraction (XRD), X-ray photoelectron spectroscopy (XPS) and transmission electron microscopy (TEM) characterization tests showed that ferrous sulfide coating on the surface of Fe(0), which could inhibit the aggregation of S-NZVI particles, thus showed better dispersibility. Compared with NZVI, S-NZVI has higher degradation efficiency for NB, and the highest degradation efficiency was 99.65%. The degradation process of NB by S-NZVI conformed pseudo-first-order kinetics. It has stronger penetrating ability in sand column. The removal mechanism of S-NZVI on NB was that NB was quickly adsorbed on the surface and then further degraded by chemical reduction, so NB removal was faster and aniline formatioon was slower. The S-NZVI reaction zone had a large reduction of NB in the leakage zone. Increasing the single-well S-NZVI injection volume and adding injection well both improved the remediation efficiency. The cumulative removal efficiency of NB in the 7days was up to 87.43%, but the NB concentration in the first 2d was still high. The S-NZVI reaction zone showed better remediation effect in the transmission zone. Adding injection well showed better persistence and NB removal rate than increasing S-NZVI injection volume in the single well, and the cumulative removal efficiency of NB in the 7days was up to 99.90%.

Based on previous studies, we developed a method for rapid pre-treatment of water samples for three typical psychoactive substances (methamphetamine, amphetamine and ephedrine) under field conditions. The effects of the method parameters (pH and loading flow rate) on the recovery rate of the target substances were compared. The optimal parameters for the accelerated pre-treatment were using Oasis HLB, and the samples were loaded at a flow rate of 20mL/min under alkaline condition. Compared with the traditional method, the concentrations of the target substances measured using the accelerated pre-treatment method were slightly lower, but it still reflected the concentration level and variation characteristics of the target substances in domestic sewage. The field verifications in Beijing and Guangdong showed that the performance of this method was stable for both surface water and wastewater samples.

Biogas from chicken manure with anaerobic digestion has a high concentration of H₂S, which needs to be removed before further utilization such as power generation or purification to produce bio-natural gas. A batch experiment of chicken manure digestion was carried out in this study, and trace amount of air was introduced into the reactors to remove hydrogen sulfide by biological oxidation. The test was carried out by feeding the inoculum obtained from the effluent of chicken manure methane digestion reactor under mesophilic conditions, and introducing air at level of 7~50mL/g VS. Air introduction significantly reduces the H₂S concentration in the biogas. The experimental group with an air dosage of 30mL/g VS had the highest average desulfurization efficiency of 62%. At the same time, the cumulative methane production of the experimental group with an air dosage of 30mL/gVS reached 335mL/gVS, which was 78.6% higher than the control group. The biological desulfurization method with trace amount of oxygen has the application prospect of simple procedure and efficient removal of H₂S.

Geotextile clogging is a common issue in landfill. Two modified methods were applied to landfill geotextiles with graphene oxide (GO) to inhibit the geotextile bio-clogging in the early stage. Different chemical and microbial properties were analysed, including zeta potential, contact angle, antimicrobial activity and microbial community. The amount of EPS was tested to evaluate the bio-clogging. The geotextile was hydrophobic after modification, but the surface charge changes in some extent. The leachate consisted of bacteria Paraclostridium and archaea Methanoculleus. GO exhibited antibacterial activity in leachate. Compared to the blank group, the geotextile coated with GO and Nafion inhibited geotextile bio-clogging, resulting in 49% decreasing of EPS.

Laboratory free swell and hydraulic conductivity tests were conducted to assess the effect of wet-dry cycling concurrent with landfill leachate permeation on the swell index of bentonite and hydraulic performance of a geosynthetic clay liner (GCL). Wet-dry cycling concurrent with leachate permeation had a significantly detrimental effect on the swell index of bentonite and hydraulic performance of GCL. The swell index of bentonite decreased from 20mL/2g to 7.5mL/2g and the hydraulic conductivity of GCL increased from 1.65×10^-11m/s to 1.89×10^-7m/s. The decrease in the swell index of bentonite and the increase in hydraulic conductivity of GCL should be attributed to the loss of osmotic swell of bentonite. The GCL continuously permeated with municipal solid waste leachate maintained a low k during the entire study duration. Increasing the effective stress from 20 to 150kPa caused the hydraulic conductivity of GCL to decrease by almost 4orders of magnitude and lower than the maximum value (5.0×10^-11m/s) allowed for GCL used in municipal solid waste landfill.

In view of the problem that the portable X-ray fluorescence (pxrf) method is not accurate enough for the determination of heavy metals in soil, a general modeling method and process based on the relationship between the measured value of Pxrf and the characteristics of the site parameters are proposed, which is used to build a Pxrf correction model suitable for the characteristics of each site, so as to improve the measurement accuracy of Pxrf. Taking a typical mining area in Beijing as an example, By analyzing the correlation of potentially related factors (i.e., soil organic matter content, water content, and actual pollutant content) and different mathematical transformations of these factors (i.e., index, logarithm, and power function) with the measured values of Pxrf, we identified the influencing variables, influence degrees, and influence forms that significantly affect the measured values of Pxrf. Based on the identification of influencing factors, we established the mathematical model of Pxrf to achieve the purpose of correcting the measured value of pxrf and improving the accurate value. The results showed that the measured values of Pb, Cu and Zn were significantly correlated with the actual concentrations, and the correlation coefficients were 0.75~0.82; the correlation coefficients of Sr, Fe and Mn were 0.25~0.52, with slightly poor correlation. The influence of water content on the detection of Pxrf was in order of Sr, Mn, Cu, Pb, Zn, the correlation coefficient range was 0.1~0.7. The Pxrf of all heavy metals is weakly affected by the content of soil organic matter, and the correlation coefficient was lower than 0.5. After the model transformation, the correlation between the Pxrf of heavy metals Zn, Pb, Cu and the actual concentration increases (increased by 4%~13%); other heavy metals had no significant change. The model verification results showed that the correlation between the Pxrf of four heavy metals Pb, Zn, Cu, Mn Compared with the original Pxrf measurement, the relative error of the corrected Pxrf value in the model could be reduced from 32.4%~56.6% to 4%~29.9%.

Positive matrix factorization (PMF) model is one of widely used technologies in pollutant source apportionment, and its uncertain analysis have always been the frontier issue as well as hotspot. Three error estimation methods, including bootstrap (BS), displacement (DISP) and bootstrap enhanced by displacement (BS-DISP), were used to evaluate the uncertainties of source apportionment by PMF model, and heavy metals in soils in Dexing, China were carried out as a case study. Six-factor scenario was the best solution for PMF model run, except for Cr and Ti, the uncertainty intervals of DISP and BS were between 0.6 and 1.5 times the basic value of the identified element and the BS-DISP uncertainty interval was between 0.6 and 1.6 times the basic value in the source profiles under six-factor scenario, the uncertainty of the model results was more due to the uncertainty generated in the factor decomposition process. The three uncertainty analysis methods could obtain the random error and factor rotation error in the operation of PMF model. Among them, the results obtained by BS-DISP and BS can assist in determining whether the factor number was over-fitting and help understand the uncertainty of the source profile. While, DISP could be used to understand the uncertainty of rotation and be used as a method to evaluate the feasibility of rotation process. This study provides a good sample for evaluating the reliability of soil heavy metal source apportionment that calculated by PMF model.

In order to understand the source and distribution characteristics of dioxin and heavy metals in surface soils around the municipal solid waste incineration plant, three waste incineration plants in the Chengdu area were selected as research objects, 17kinds of Polychlorinated dibenzo-p-dioxins and dibenzofurans (PCDD/Fs) and 11heavy metals in the surrounding soil were monitored. The concentrations range of 0.25~0.75ng I-TEQ/kg for PCDD/Fs and 0.23~580.57mg/kg for heavy metals in the soil samples were determined, respectively. The contribution rate of toxic equivalent concentration of Polychlorinated dibenzofuran(PCDFs) in the soil around the three waste incineration plants was above Polychlorinated dibenzodioxins (PCDDs), the average contribution rate of PCDFs to toxic equivalent concentration reached 55%;Cd, Hg, Pb, Cu and Zn in soil samples had good correlations among each other. Hg, Pb and Zn had good correlations with some PCDFs. The correlation coefficients (r) were 0.792, 0.760 and 0.788, and the corresponding p values were 0.034, 0.047 and 0.035respectively. Therefore Hg, Pb and Zn were classified as the same cluster, which can be used as heavy metal tracers to characterize the source of PCDFs.

Neonicotinoids have occupied the largest market share of pesticides in the world, soil is the source for neonicotinoids to enter the environmental system. Understanding the environmental behaviors of neonicotinoids in the soil is significant for exploring the environmental fate and ecological evaluation. The environmental behaviors of neonicotinoids in the soil were summarized and discussed, including adsorption, desorption and degradation. The influence mechanisms of the environmental factors was mainly analyzed, including physicochemical properties of neonicotinoids, soil composition and types, pH, temperature and water content. Moreover, the mechanisms of biodegradation, photolysis and hydrolysis were also analyzed. In the end, the future emphasis and direction of research on neonicotinoids were provided.

In order to explore the effect of bacteria carried by manure on soil microorganisms, and to determine whether the history of manure application has affected the response of soil microorganisms to manure application. Taking the soil with long-term application of pig manure and long-term application of chemical fertilizer as the research objects, manure and sterilized manure were added to these soils. CFU number of the culturable bacteria, abundance of 16S-rRNA gene, bacterial community composition and microbial thermal metabolic activity were measured. When pig manure was applied as 9.0t/hm², the fecal bacteria and chemical nutrients carried by manure had no significant effect on the CFU number of culturable bacteria and 16S-rRNA copies in both soils. In addition, the soil indigenous microorganisms could significantly inhibit the colonization of exogenous bacteria carried by manure; if the indigenous microorganisms in these two soils had sterilized and pig manure was added, the average number of culturable bacteria would increase by 45 and 96 times respectively. Nutrients input from manure did not cause significant changes in soil bacterial community structure and abundance; while exogenous fecal bacteria imported from manure could colonize in the soil with long-term application of chemical fertilizer and affect the corresponding bacterial abundance. However, less fecal bacteria colonize in the soil with long-term application of pig manure, they were inhibited in the early stages of soil entry. Similarly, the addition of manure increased the microbial metabolic activity of the long-term chemical fertilizer application soil, but had no significant effect on the long-term manure application soil. In summary, manure has a greater impact on bacteria community in the soil with long-term application of chemical fertilizer, while the history of long-term application of manure reduces the "sensitivity" of the soil to manure, and enhances the inhibitory effect on the exogenous bacteria carried by manure.

Paddy soil was collected from Southern China and used as an inoculum in a microcosm experiment. The microcosm experiment was used to study the process of autotrophic nitrate reduction coupled with As(III) oxidation and its microbial community structure in the flooded paddy field. As(III) was completely oxidized in As(III)+NO₃^- treatment, while no As(III) oxidation was observed in the As(III) amendment and the sterilization treatment (Sterilized soil+As(III)+NO₃^-). Meanwhile, a small amount of NO₃^- reduction was observed in As(III)+NO₃^- amendment and no NO₃^- reduction was observed in NO₃^- amendment. 16S rRNA-based high-throughput sequencing was used to investigate the microbial community structure in Soil+As(III)+NO₃^- treatment. Diversity of soil bacterial community was decreased and its Shannon index was 8.19in Soil+As(III)+NO₃^- treatment. The dominant bacteria at the phyla level were Proteobacteria (33%), Chloroflexi (11%), and Planctomycetes (12%), and the dominant genus were Gemmatimonas (7.4%), with few Singulisphaera、Thermomonas、Bacillus in Soil+As(III)+NO₃^- treatment. In summary, the addition of NO₃^- can promote the autotrophic As(III) oxidation and influences the microbial community composition in flooded paddy soil.

In order to study the effect of microbial inoculants on improving the soil properties of Pisha sandstone soil, four single liquid microbial agents and one compound microbial agent CB were prepared from the plant growth-promoting bacteria Bacillus halotolerans P75, Sinorhizobium meliloti D10, Bacillus megaterium H3and Bacillus subtilis HB01, which were inoculated into Pisha sandstone soil at a volume-mass ratio of 5% respectively. The greenhouse pot experiments of planting Alfalfa (Medicogo sativa L.) and Caragana (Caragana korshinskii kom.) were conducted to evaluate the effects of the microbial agents on the Pisha sandstone soil quality and the growth of Alfalfa and Caragana. The results showed that the inoculated treatments could significantly increase Alfalfa biomass by 18.6%~45.6% and Caragana biomass by 24.1%~46.7% compared with the non-inoculated control group. Some bacterial treatments also could reduce soil pH, increase the contents of organic matter, ammonium nitrogen, nitrate nitrogen, available phosphorus and available potassium in soil, and improve water stability of soil aggregates. The compound bacterial agent could be more efficiently used for plant growth and the quality improvement of Pisha sandstone soil.

The heterogeneous soil layer was established by self-made three-dimensional plexiglass tank, and two leakage points in shallow and interior soil layer were set up to simulate the mobile phase crude oil migration and redistribution process under the condition of water level fluctuation in water-bearing soil layer. The corresponding resistivity response characteristics were revealed using self-made high density electrode arrays and electrometer. The results showed that the migration of crude oil in soil was affected by the leakage source location, the leakage volume and the soil layer structure. The transverse diffusion of the leakage point in the same soil layer was more obvious in the vertical direction, and oil around the shallow leakage point diffused around. The larger the leakage volume, the wider the pollution range. The higher the permeability of the soil layer, the deeper the pollution depth. There were two kinds of anomalies in high resistance and low resistance after crude oil leakage. When the soil layer structure was simple and the oil content was high, the high resistance anomaly was obvious. When the composition of soil layer was complex, especially the salt and clay mineral contents were high, or the water and oil contents were low, the low resistance anomaly was easy to occur. After the water level rose, the overall soil resistivity decreased and the crude oil was concentrated to the center of the polluted area. After the water level dropped, the resistivity increased, the crude oil dispersed around. From the above, the water level fluctuation caused the oil to diffuse further. Affected by the internal leakage point, the closer near the leakage point (0.08m), the more serious the pollution at the depth. In addition, the oil content in the lower part of the leakage point(0.15m) was higher than that in the upper part (0.04m), indicating that the downward migration of oil was more obvious than the upper one around the internal leakage point.

To understand changes in lake temperature in China and its response to climate change, MODIS temperature product (MOD11A1) from 2000 to 2015 and nine representative big lakes, all more than 250km² in surface area were chosen by us. These were Hulun Lake, Xingkai Lake, Hongze Lake, Taihu Lake, Fuxian Lake, Namco, Selinco, Qinghai Lake, and Bosten Lake, all distributed across different natural geographic regions within China. The Wavelet Transform method was used to study the seasonal and inter-annual variation characteristics of lake temperature and its response to climate change. All nine lakes had obvious seasonal variation in temperature. The annual difference in temperature of all nine lakes decreased from north to south across China as the latitude decreased. From 2000 to 2015, the inter-annual variation trend of lake temperature showed a rise and then a decline. The inflection point of inter-annual variation of Fuxian Lake, Selinco, and Bosten Lake is 2009, and the inflection point of the other six lakes occurred in 2010; lake temperature in all lakes showed a strong response to air temperature, and the variation trend of lake temperature and air temperature was basically the same. From 2000 to 2015, the onset date of icing in Selinco showed the most pronounced delaying trend, while the date of onset of icing in Namco showed the most pronounced advancing trend. The date of onset of ice melt in Hulun Lake showed the most pronounced advancing trend, while the most pronounced delaying trend of the onset of ice melt was observed in Namco. In this way, the icing period in Hulun Lake and Qinghai Lake became shorter, and that of Namco and Selinco became longer. The other lakes showed no significant change in the icing period.

In order to explore the environmental significance of the particulate organic as the source of stable isotopic carbon and nitrogen in suspended solids and sediments of the Lake in cold and arid regions, the contents of δ¹³C, δ¹⁵N and C/N ratio of suspended solids and surface sediments in Nanhai Lake during the ice-sealing period were determined in January 2019. The results showed that, δ¹³C, δ¹⁵N, C/N in the suspended organic matters varied in the range of -31.94‰~-27.87‰, 15.16‰~18.66‰, and 3.90~5.13, respectively, while in the sediments varied in the range of -25.39‰~-18.83‰, 7.04‰~13.66‰, and 7.66~12.23, respectively. The peak values of the δ¹³C and δ¹⁵N contents in the suspended organic substances appeared in the water entering area and the islands in the center of the lake, respectively, while in sediments, both the peak values appeard in the latter. The end-member mixing model showed, the suspended organic matter in the frozen period was mainly originated from the endogenous aquatic algae, which contributed 82.33% of the total suspended organic matters in the water conservation area, being consistent with the highest abundance of phytoplankton in the area. The main source of organic matters in the surface sediments was endogenous aquatic plants, which contributed 89.7% of the total organic matters in the water conservation area. Analyses showed that there was no significant correlation between suspended organic matter and δ¹³C, δ¹⁵N in the surface sediments during the freezing period. At low temperature, there exist significant negative correlation between the suspended δ¹⁵N and temperature (P<0.025) as well as nitrate nitrogen (P<0.019), positive correlation between the suspended δ¹⁵N and the nitrite nitrogen (P<0.034). These maybe due to the exogenous contribution rate and the isotopic effect of biological action. There was an extremely significant positive correlation between δ¹³C and COD in suspended matter (P<0.008), and a significant positive correlation between δ¹³C and salinity (P<0.046). The COD and suspended ¹³C are likely to have homology and have a certain environmental indication in the lake ice-sealing period.

Yulin river, a tributary of the Three Gorges reservoir area, was selected as the research object. The change of SWI oxygen flux under 5hydrodynamic conditions (average velocity 0.00, 0.03, 0.07, 0.12 and 0.20m/s) and the influence of hydrodynamic conditions on the generation mechanism of SWI oxygen flux were measured. As the average velocity increases, SWI oxygen flux increased from 1.197mmol/(m²·h) at 0.00m/s to 43.981mmol/(m²·h) at 0.20m/s. The penetration depth of dissolved oxygen also increased. Oxygen entered deeper sediments and got used by microorganisms and reducing substances thus the oxygen consumption increased. In addition, when the average velocity was low, the oxygen consumption of sediments was dominated by biological oxygen consumption. At 0.00m/s and 0.03m/s, the biological oxygen consumption accounted for 85.3% and 57.7% of the oxygen flux. While when the average velocity was high, the proportion of Chemical oxygen consumption and other oxygen consumption in the chemical process in oxygen flux gradually increased.

Through the maritime survey data from multiple cruises in the southern Yellow Sea in 2017,the variations and influencing factors of dissolved organic matter in the process of green tide (Ulva prolifera blooms) were analyzed. The high-value areas of dissolved organic carbon (DOC) were mainly located in the northwestern part of the southern Yellow Sea and that near the northern Jiangsu, indicating that the terrigenous input was one of the main resources of DOC to this area. The EEMs-Parallel factor analysis (EEMs-PARAFAC) method identified four fluorescent dissolved organic matter (FDOM) in the southern Yellow Sea:three terrestrial humic-like (C1, C2, C3) and one protein-like (C4) fluorescent components. The spatial distributions of the four fluorescent components were similar and had a significant negative correlation with salinity. As the green tide outbroke in the southern yellow sea, DOC and FDOM concentrations increased significantly, while dissolved organic nitrogen (DON) and dissolved organic phosphorus (DOP) concentrations were decreased. With the gradual disappearance of the green tide, the DOC concentration was going down but still slightly higher than that before the outbreak of green tide, instead the fluorescence intensities of C2 and C4 in surface waters were increased by 11.3% and 12.6%, respectively. During this period, DOP, DON and DON/DOC were also increased. The outbreak of the green tide in the South Yellow Sea had significant impacts on the spatiotemporal distribution of dissolved organic matter.

A grid-stirring turbulence generation device was applied with the grid rotation frequency of 0, 500, 1000and 1500Hz, corresponding to the turbulent energy dissipation rate ranged in 0~8.93×10^-3m²/s³, to investigate the effect of flow turbulence on the growth of Microcystis aeruginosa under high light intensity and phosphorus deficiency conditions. Under high light intensity (8000lx), the growth of Microcystis was significantly inhibited, and the algal concentration under the static condition was only 47.7% of that under normal light intensity. However, turbulence could alleviate the effect of high light environment to a certain extent. Among them, the algae concentration in the 1000Hz group was the highest, which was 1.8times higher compared to the static group. The Chl-a content in the high light intensity group was 1.52 to 1.78 times that of normal light conditions, which indicated that high light intensity might not promote the growth and division of algal cells, and the accumulation of Chl-a might be the defense response of Microcystis aeruginosa to the adverse conditions of high light intensity. In the absence of phosphorus, the algal biomass was only 1/6~1/4 of that in normal nutritional conditions. However, with the increase of turbulence intensity, the algae biomass increased slightly and the Chl-a concentration increased significantly from the initial concentration. Among them, the 1000Hz group was found to be with the best growth. Flow turbulence can alleviate the harsh environments such as high light intensity and phosphorus deficiency for algae growth and accumulation of Chl-a might be the defense response of algal cells to the adverse environment.

The suppressive effect of liverwort aqueous extract on chlorella growth was studied and a cheap, efficient and low-toxic algicide was selected. Thus, the difference in suppression effect of liverwort and extensive straw on chlorella growth was also compared and analyzed. The inhibition of chlorella growth reached 88.17% after culturing 120h in 0.5g/L liverwort aqueous extract, while, the inhibition of the straw aqueous extract only reached 66.28%. The inhibition of liverwort aqueous extract showed better efficacy than straw aqueous extract at the same conditions. The high concentration of liverwort aqueous extract (25g/L) could reduce the photosynthetic activity of chlorella, while low concentration of liverwort aqueous extract (1g/L) revealed insignificant effects on the photosynthetic activity of chlorella. Compared the suppressive effect of ethanol and deionized water extracts on chlorella, the organic allelopathic components of liverwort aqueous extract inhibited the growth of chlorella. Moreover, the algal inhibition effect of liverwort aqueous extract was similar to three single flavonoids, which were myricetin, parsley and lutein.

To explore the characteristics of community structure and species diversity of benthic invertebrates, three samplings of 6sites in marsh wetlands of the Sanjiang Plain were conducted in May, July and September, 2017. In total, 72 taxa of benthic invertebrates from 41families and 3phyla were recorded, mainly composed by aquatic insects and gastropoda. The average density of benthic invertebrates was (139.68±29.13)ind./m². Seasonally, the density of benthic invertebrates followed the order of autumn > spring > summer. The dominant species varied in different seasons, with the Valvata sibirica being the dominant species in three seasons. Indicator species analysis showed that Potamonectes sp. was the indicator species in spring, Lethocerus sp., Gyraulus centrifugus and Erpobdellidae sp. were the indicator species in summer, and Sgementina nitida was the indicator species in autumn. On the whole, Shannon-Wiener diversity index (H'), Pielou evenness index (J), and Margalef richness index (d_M) were all higher in spring than in summer and autumn. One-way ANOVA analysis showed that there were no significant differences in Shannon-Wiener diversity index (F=1.480, p=0.259), Margalef richness index (F=0.056, p=0.946), and Pielou evenness index (F=2.038, p=0.165) among the three seasons.

To explore whether temperature increase would lead to miniaturization of zooplankton in thermal discharge seawaters near the power plant, samples of zooplankton were collected by the type III net with mesh size of 77μm and data was analyzed. In total 75species (including pelagic larvae, eggs and fish larva) were identified with 18dominant species. The annual average abundance was up to 27690.0ind/m³. These communities were mainly composed of meso-and micro-copepods and pelagic larvae, meanwhile dominanted by meso-and micro-zooplankton with a body length <1000μm. Among them, microzooplankton with a length<500μm had the highest abundance in each month and section, its average accounted for over 58.2% of total abundance. The average of zooplankton with a body length of 500~1000μm accounted for over 34.8%. Zooplankton with a body length >1000μm only accounted for 7%. Analysis of similarity (ANOSIM) showed that community structures among seasons were significant different (P<0.05), while among sections were not significant different. Similarity percentage (SIMPER) analysis found the most important discriminating species causing seasonal differences were Oithona similis, Oikopleura dioica and Difflugia sp., etc. Besides, macrozooplankton (>2000μm) were all away from D02section driven by thermal seawater, major larval groups (copepod nauplii and Copepodites) were almost unaffected evenly distributed in the warming seawater. Moreover, a large number of microzooplankton, such as Difflugia sp., Oithona brevicornis and Oithona fallax gathered to the outfall, resulting in the highest abundance (35704.1ind/m³) at D02section. Diversity analysis showed that significant linear regression relationship existed between water temperature increment and the Shannon index (H'), Pielou evenness (J'), Simpson index (D') of zooplankton (P<0.05), however the relationship between water temperature increment and species number was not significant (P>0.05). Based on slope of regression equation, H' would decrease by 5.4%, J' by 5.0%, D' by 3.8% and S by 2.9% when increasing the temperature by 1℃.

A sampling program was conducted to determine the levels of benzothiazole and its five derivatives (BTs, including BT、2-NH₂-BT、2-OH-BT、MBT、MTBT) in PM_2.5 and PM₁₀ using UPLC-triple quadrupole MS. Three sampling points located at urban background and roadsides were selected. Pollution characteristics and exposure risks of target compounds were evaluated. The concentration of BT in PM_2.5 and PM₁₀ samples was the highest at all three points, accounting for 44.4%~55.2% of the total concentration. Concentration of BTs tended to be the highest at the roadside with high braking frequency, indicating that high braking frequency resulted in more tire wear particles in roadside air. There were good linear relationships between the concentration of BTs (except 2-NH₂-BT) in PM_2.5 and PM₁₀, which indicates that PM_2.5 and PM₁₀ of roadside air have the same source. The ratio of the concentration of BTs in PM_2.5 and PM₁₀(PM_2.5/PM₁₀) ranged from 0.41 to 0.95, indicating that BTs are more easily concentrated in fine particles or fine particles are the main fraction of tire wear emission. The results of exposure assessment showed that the daily inhalation exposure dose of roadside workers to BTs was greater than other people, which may cause a higher health risk. BT contributed the most to inhalation exposure dose among five compounds.

In order to investigate the effect of heavy metals on pulmonary surfactant (PS) membranes, the interaction between different types and concentrations of heavy metal ions and PS monolayer membranes were studied using Langmuir-Wilhelmy membrane balances. The six heavy metal ions of Cr³⁺, Cu²⁺, Hg²⁺, Pb²⁺, Cd²⁺ and Ni²⁺ all expanded the π-A isotherm G-LE phase transition phase of PS monolayer, while Fe³⁺ induced monolayer condensation. Subsequently, Cd²⁺, Cu²⁺, Hg²⁺and Fe³⁺ were selected to further investigate the effect of heavy metal concentration on the surface activity of PS monolayer films,the compressible modulus analysis was carried out, and the mechanism of action was explored by combining infrared spectroscopy (FTIR) and atomic force microscope (AFM). Cu²⁺, Fe³⁺ and Hg²⁺ all cooperated with the polar head of PS monolayer in a concentration-dependent manner to form a complex and change the stability of the membrane, while the effect of Cd²⁺ was obviously weaker than the other three metal ions, but it could also enhance the PS monolayer order.

In orderto investigate the enrichment of bisphenol F (BPF) and bisphenol S (BPS) in zebrafish and their combined neurotoxicity, single and combined exposure of 1, 10, 100, 1000μg/L BPF and BPS was conducted for 14days. The enrichment level of BPF and BPS in zebrafish tissues was positively correlated with the exposure concentration and time, and the enrichment capacity of BPF was higher than that of BPS. Combined exposure of BPF and BPS reduced the enrichment level of BPS in zebrafish, but had little effects on the enrichment of BPF. Toxicity studies on brain tissues showed that BPF induced levels of oxidative damage and inflammation indicators such as malondialdehyde (MDA), 8-hydroxy-2'-deoxyguanosine (8-OHdG), interleukin-1β(1L-1β) and tumor necrosis factor α (TNF-α), were higher than those of BPS. Moreover, combined exposure was found to have toxicity enhancement effects. However, the toxic effects of BPS on neurotoxic markers, such as cortisol (COR), epinephrine (EPI) and acetylcholinesterase (AChE), and genes related to neurological functions, such as Syn2a, MBP, Gfap, MAP2, NSE2 and S-100B, were higher than those of BPF. And, combined exposure reduced the effects on AChE, COR and EPI.

In this paper, spatial-temporal features of the air quality index (AQI) in Yangtze River economic belt were studied by the real-time monitoring data on air quality from 2015 to 2018, and emissions of air pollutants and meteorological factors were taken as two evaluating indicators to reveal the factors and their seasonal variation to the distribution of AQI in the target regions by geographical detector. The air quality of Yangtze River economic belt was improving from 2015 to 2018 with an average ratio of days beyond standard decreased to 16.2% from 19.8%, and the rest of monitoring indicators were decreasing more or less except a rising ratio of days beyond standard for O₃. In terms of the ratio of days beyond standard, PM₁₀ was overtook by O₃ and became the second most significant pollutant following PM_2.5 for Yangtze River economic belt since 2017. The monthly variation curve for AQI showed a "U" model, which was higher in winter and spring and lower in summer and autumn. The improving mentioned was particularly witnessed in winter and autumn. And the rising concentration of O₃ then led to a rising ratio of days beyond standard in summer, but a minus variation was seen in spring. AQI and ratio of days beyond standard presented a pattern of being higher in the east and north, and lower in the west and south. And the most polluted area covered Shanghai, Jiangsu, central and northern Anhui, and northern Zhejiang, then followed by central Hubei and Chengdu-Chongqing area, and the air quality was good in Yunnan, Guizhou, and western Sichuan. The variation of AQI in spring and summer was mainly presented when studied on east-west direction while it turned to south-north direction in autumn and winter. Factors to emissions of pollutants had a positive influence on the distribution of AQI in target areas, while there was a seasonal variation when it came to the direction of the influence by meteorological factors. The distribution of AQI in the whole year, spring, autumn and winter was mainly determined by the emission factors of air pollutants, while a more powerful influence was seen by meteorological factors in summer. Factors to emissions of pollutants had a positive influence on the distribution of AQI in target areas, while there was a seasonal variation when it came to the direction of the influence by meteorological factors. Whether for the whole year, spring, autumn or winter, the distribution of AQI was decided by the volume of air pollution pollutant, and a more powerful influence was seen by meteorological factors in summer.

Based on panel dataset of water pollutant emission and socio-economic development in Yangtze River Economic Belt (YREB) during the "Twelfth Five-Year Plan" period, the tempo-spatial evolution and pattern of water pollutants reduction was analyzed. Meanwhile, the spatial effects and driving forces of water pollutant emission reduction were quantitatively estimated by using spatial lag model and spatial error model. Water pollutant emissions reduction presented a significant agglomeration in the YREB, and the high emission-high emission reduction zones were mainly distributed in the Yangtze River Delta. However, the high emission-low emission reduction zones that were being threatened by environmental degradation as the rapid socioeconomic development, still exist, then it was urgent to accelerate the adjustment of industrial structure and the elimination of outdated production capacity, and fully implement the strict controls on emissions by existing standards. The geographical distribution of water pollutant emissions had a significant impact on its reduction in the YREB, namely, increase in water pollutants emission in a place would lead to nonsignificant reduction in water pollutants emission in adjacent areas. However, through exert the environmental control during the "Twelfth Five-Year Plan" period, the trend of coordinated emission reduction emerged since 2015. Population size, the percentage contribution of agriculture in GDP, and urbanization level were the major driving factors behind the variation of water pollutant emissions in the YREB. By 2015, the effects of former two factors worn off, while urbanization still had an increasing influence on the growth of water pollutants emissions. This finding reflected the ongoing urbanization in YREB should be given an urgent attention in the future. In addition, foreign direct investment and industrialization level played a positive role in the increases in chemical oxygen demand and ammonia nitrogen emissions, respectively. In this case, it was necessary to be alert to the rapid FDI inflows and industrialization that may increase the burden of reducing water pollutants emissions. Finally, main policy implications were presented as follows:it was crucial to jointly removing the spillover effect of distribution of water pollutants emissions, and promoting local and their adjacent regions to reach regulatory consensus on pollution standard and total scale. Moreover, establishing deep-level emission reduction models, such as environmental access mechanisms, pollution payment policies, and cross-border early-warning systems, should be constructed and promoted. Besides the implementation of project emission reductions laws and policies, the structural emission reductions should be reinforced. Aiming at the spatial coupling of driving factors and pollution emissions, we should shift the structures of industries, consumption, planting, and capital to the cleaner ones.

The Water Environment Bearing Capacity Assessment Index System and Model were constructed respectively from DPSIRM and SVR Model, then parameters of the SVR Model were optimized via cross-validation methodology to further improve the accuracy of the prediction. The evolution trend and spatial differences of water environment carrying capacity of Yangtze River Economic Zone from 2009~2018 were studied using the Model. Water Environment Bearing Capacity Grade of Yangtze River Economic Belt presents an upward trend in a whole, the bearing level of the city agglomeration of upstream and midstream of the River has been improved from level II (overload) to level IV (weakly loadable), while the level of the downstream area changed from Level I (heavy overload) to Level IV (weakly loadable). By comparing the evaluation results of the Model and entropy weight-TOPSIS method, the coincidence rate reaches 91.7%, the SVR model is feasible to evaluate the water environment carrying capacity and the results are reliable. The bearing capacity of six subsystems of the downstream region was analyzed, then the sensitivity analysis on evaluation indicators in each subsystem was performed based on Single Factor Alternate Method (OAT) so as to help decision makers identify the sensitivity of indicators.

The four-stage analysis framework of NSUSBM-SFA-NSUSBM-Tobit was constructed in this paper. Based on the panel data of 107 cities in the Yangtze River economic belt from 2007 to 2016, the global DEA technology was used to calculate the eco-efficiency of cities under the inseparable assumption. Then the three-stage DEA model was used to introduce natural factors. And combined with the new development concept, The Tobit model was used to analyze the influencing factors of urban eco-efficiency. Regardless of the environmental differences in the cities, the average comprehensive ecological efficiency in the Yangtze River economic zone increased from 0.288 to 0.617 in 2007~2016, with an increase of 114.24%. It had crossed the low-quality development stage of 0.4, but was still lower than the high-quality development standard of 0.8 in 2016. The ecological efficiency of Hunan Province grew fastest, with an increase of 213.85%. Considering the environmental differences, the average comprehensive ecological efficiency of the Yangtze River economic zone increased from 0.150 to 0.395 in 2007~2016, with an increase of 163.33%. Shanghai grew fastest, with an increase of 311.52%. Shanghai, Jiangsu and Zhejiang ranked the top three in most years, while Jiangxi, Guizhou and Yunnan ranked the bottom three. Innovation, urban-rural coordination, government environmental investment, foreign investment and urbanization all contributed to eco-efficiency.

Under the consideration of emission reduction efficiency and the purpose of maximizing the economic surplus in the carbon market, a two-stage dynamic game mechanism between the government and duopoly enterprises was constructed, and the effects of graded and progressive punishment mechanism on the power generation, profits of large and small enterprises and economic surplus were studied. The results showed that with the increase of penalty coefficient, if the large power enterprise was defaulted, the total power generation, total profit and economic surplus decreased by 7.47%, 15.34% and 5.88%; if the small power enterprise was defaulted, the total power generation decreased by 1.43%, the total profit decreased by 3.39% or increased by 0.03%, and the economic surplus increased by 0.13%; if the large power enterprise was not participated in carbon trading, the total profit decreased by 16.35%; if it was participated in carbon trading, the total profit decreased by 15.34%; if the small power enterprise was not participated in carbon trading, the total profit decreased by 3.39%; if it was participated in carbon trading, the total profit increased by 0.03%. Therefore, when designing a punishment mechanism for the power generation industry, we should increase the penalties and set up a graded and progressive punishment mechanism, according to the enterprise scale and carbon market participation, and an effective supervision system should be established.