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The current regulatory site investigation employs the J&E model to predict vapor intrusion risk. However, the J&E model assumes that the source concentration is constant for a given exposure period, which is not consistent with the actual site source under depletion. In this study, we compared the differences between the J&E model (constant source), SD source depletion model, and RBCA source depletion model for predicting indoor concentration variation as well as the risk levels during the exposure period with a case study in Beijing. The results showed that the source and indoor air concentrations predicted by the SD and RBCA models showed exponential decreases, whereas those predicted by the J&E model maintained high concentrations throughout the exposure period, which greatly overestimated the risk. The RBCA predicted source depletion at the fastest rate, but the predicted indoor air concentrations were still lower than those of the SD model, which was related to the fact that the RBCA did not consider the effect of buildings on source depletion and did not follow mass conservation. Further, the sensitivity analysis showed that the pressure difference (dP) had the greatest influence on the source concentration in the SD model. For the calculated carcinogenic risk and hazard quotients, the J&E constant source model, the SD source depletion model, and the RBCA source depletion model were ranked in descending order. The results indicated that in general the J&E model was too conservative, the RBCA model may have underestimated risk, and the SD model was more suitable for quantifying vapor intrusion risk in reality.

Vehicle emissions are an important source of anthropogenic volatile organic compound (VOCs) emissions in urban areas and are commonly quantified using vehicle emission inventories. However, most previous studies on vehicle emission inventories have incomplete emission factors and emission processes or insufficient consideration of meteorological parameters. Based on the localized full-process emission factors attained from tested data and previous studies, a method to develop a monthly vehicular VOC emission inventory of full process for the long-term was established, which covered exhaust and evaporative emissions (including running loss, diurnal breathing loss, hot soak loss, and refueling emission). Then, the method was used to develop a full-process vehicular VOC emission inventory in Tianjin from 2000 to 2020. The results showed that the total vehicular VOC emissions in Tianjin rose slowly and then gradually decreased. In 2020, the total emissions were 21400 tons. The light-duty passenger vehicles were the dominant contributors and covered 75.00% of the total emissions. Unlike the continuous decline in exhaust emissions, evaporative emissions showed an inverted U-shaped trend with an increasing contribution to total emissions yearly, accounting for 31.69% in 2020. Monthly emissions were affected by both vehicle activity and emission factors. VOC emissions were high in autumn and winter and low in spring and summer. During the COVID-19 epidemic in 2020, vehicle activity was limited by closure and control, making VOC emissions significantly lower than those during the same period in previous years. The method and data in this study can provide technical reference and a decision-making basis for air pollution prevention and control.

In the summer of 2019, field measurements of ozone (O 3 ) and its precursors[volatile organic compounds (VOCs) and nitrogen oxides (NO x )] were carried out at an urban site in Ji'nan. We found that the daily maximum 8-hour averages φ (O 3 ) were (103.0±14.5)×10 -9 . The average φ (NO x ) and φ (VOCs), which are ozone precursors, were (16.7±11.3)×10 -9 and (22.4±9.4)×10 -9 , respectively. The ·OH reactivity of VOCs was determined (9.6±3.8) s -1 . Ji'nan suffered from serious O 3 pollution. An observation-constrained chemical box model was deployed to evaluate in situ photochemical O 3 production, which indicated that chemical reactions made positive contributions to O 3 production rates between 07:00 and 19:00 LT, with the average hourly O 3 production rate of 35.6×10 -9 h -1 . To evaluate the effectiveness of various ozone precursor control strategies in reducing ozone pollution, we combined the observation-based model (OBM) with the relative incremental reactivity (RIR) method. The key indicators that affect the local ozone production rate were identified. Ji'nan was under VOC-limited conditions and the key VOC precursors were alkenes. The O 3 formation mechanism changed from the VOC-limited regime in the morning to the transitional regime in the afternoon. Correspondingly, the simulated local O 3 production rate was increased from 18.3×10 -9 h -1 to 29.6×10 -9 h -1 . To further explore the role of anthropogenic emissions in ozone pollution, we used the positive matrix factorization (PMF) model to identify the major sources contributing to VOCs. The major sources in Ji'nan were vehicular exhaust and gasoline evaporation, accounting for more than 50% of the observed VOCs. Therefore, constraints on vehicular emissions is the most effective strategy to control O 3 pollution in Ji'nan.

In this study, 130 surface soil samples were collected at an industrial pollution site in Beijing and the contents of As, Be, Cd, Cu, Cr, Hg, Ni, Pb, Sb, Ti, Zn, and 16 PAHs were determined. The positive matrix factorization (PMF) model was used to analyze the sources of heavy metals and PAHs, and the contributions of these sources to carcinogenic risk and hazard index in the study area were calculated. The results showed that the contents of Cd, Cu, Pb, Hg, As, Zn, and Cr in the soil exceeded the background values in different degrees; Cd, Hg, Pb, Zn, and Cu exceeded the background values by>50%. Low molecular weight PAHs (two and three rings) and high molecular weight PAHs (four to six rings) accounted for 39.6% and 60.4% of the total content of 16 PAHs. The PAH content at 77% of the sampling points at the target site was more than 1000 μg ·kg -1 , which suggests severe PAH pollution at the site. Heavy metals Be, Ti, As, and Ni mainly originated from natural sources. There are three major sources of 7 heavy metals and 16 PAHs at the site: coal combustion (Hg and ∑16PAHs), smelting (Cu, Cr, Pb, and Zn), and traffic (Sb and Cd). The contribution rates of these sources to the total average contents of seven heavy metals and sixteen PAHs at 130 sampling sites were 8.46% (coal combustion), 90.61% (smelting), and 0.94% (traffic). Human health risk assessment results showed that the carcinogenic risk of seven heavy metals and ∑16PAHs ranged from 4.17×10 -6 to 39.38×10 -4 , and the hazard index ranged from 0 to 32.23. The maximum carcinogenic risk and hazard index values were calculated near the coking plant. Benzo[α]pyrene was the PAH that posed the highest carcinogenic risk and Zn was the heavy metal that had the highest hazard index value. The average carcinogenic risk of coal combustion was 2.16×10 -4 , accounting for 50.26% of the total average carcinogenic risk. The average hazard index of smelting was 0.834, accounting for 56.43% of the total average non-carcinogenic risk. These two pollution sources are responsible for the high levels of heavy metals and PAHs in the soil of the steel smelting sites that pose the most severe health risks. The results of this study can provide reference for soil remediation and process optimization at other heavily polluted industrial sites.

During 8th-14th Jan., 2013, severe particulate matter (PM) pollution episodes happened in Beijing. These air pollution events lead to high risks for public health. In addition to various PM chemical compositions, biological components in the air may also impose threaten. Little is known about airborne microbial community in such severe air pollution conditions. PM2.5 and PM10 samples were collected during that 7-day pollution period. The 16S rRNA gene V3 amplification and the MiSeq sequencing were performed for analyzing these samples. It is found that there is no significant difference at phylum level for PM2.5 bacterial communities during that 7-day pollution period both at phylum and at genus level. At genus level, Arthrobacter and Frankia are the major airborne microbes presented in Beijing winter.samples. At genus level, there are 39 common genera (combined by first 50 genera bacterial of the two analysis) between the 16S rRNA gene analysis and those are found by Metagenomic analysis on the same PM samples. Frankia and Paracoccus are relatively more abundant in 16S rRNA gene data, while Kocuria and Geodermatophilus are relatively more abundant in Meta-data. PM10 bacterial communities are similar to those of PM2.5 with some noticeable differences, i.e., at phylum level, more Firmicutes and less Actinobacteria present in PM10 samples than in PM2.5 samples, while at genus level, more Clostridium presents in PM10 samples. The findings in Beijing were compared with three 16S rRNA gene studies in other countries. Although the sampling locations and times are different from each other, compositions of bacterial community are similar for those sampled at the ground atmosphere. Airborne microbial communities near the ground surface are different from those sampled in the upper troposphere.

The abandoned mineral samples were collected in an acid mine drainage area in Anhui Province. Molecular ecological methods were used to construct 18S rDNA clone libraries after analyzing the main physicochemical parameters, and then the microeukaryotic diversity and community structure in the acid mine drainage area were studied. The results showed that the region was strongly acidic (pH <3), and the concentrations of Fe, SO2-(4), P, NO-(3) -N showed the same trend, all higher in the bare waste ore samples PD and 1 M than in the vegetation covered samples LW and XC. Four eukaryotic phyla were detected in the abandoned mineral samples: Ascomycota, Basidiomycota, Glomeromycota and Arthropoda. Glomeromycota can form an absolute symbiotic relationship with the plant, and it was a key factor for early plant to adapt the terrestrial environment. The biodiversity of the vegetation covered samples LW and XC, which contained Glomeromycota, was much higher than that of the bare abandoned rock samples PD and 1 M. Moreover, many sequences in the libraries were closely related to some isolated strains, which are tolerant to low pH and heavy metals, such as Penicillium purpurogenum, Chaetothyriales sp. and Staninwardia suttonii.

Site investigation was carried out on an area to be redeveloped as a subway station, which is right downstream of the groundwater of a former chemical plant. The results indicate the subsurface soil and groundwater in the area are both polluted heavily by 1,2-dichloroethane, which was caused by the chemical plant upstream with the highest concentration was 104.08 mg.kg-1 for soil sample at 8.6 m below ground and the highest concentration was 18500 microg.L-1 for groundwater. Further, a site-specific contamination conceptual model, giving consideration to the specific structure configuration of the station, was developed, and the corresponding risk calculation equation was derived. The carcinogenic risks calculated with models developed on the generic site conceptual model and derived herein on the site-specific conceptual model were compared. Both models indicate that the carcinogenic risk is significantly higher than the acceptable level which is 1 x 10(-6). The comparison result reveals that the risk calculated with the former models for soil and groundwater are higher than the one calculated with the latter models by 2 times and 1.5 times, respectively. The finding in this paper indicates that the generic risk assessment model may underestimate the risk if specific site conditions and structure configuration are not considered.

The carcinogenic risk originated from benzene in contaminated groundwater of a large-scale coke plant in Beijing was analyzed and assessed for different land use zones according to the site redevelopment plan. The results revealed that indoor vapor inhalation was the key exposure pathway for all the three zones. The carcinogenic risk in zone A as commercial area was 6.37 x 10(-8), below the maximum allowable level (1.0 x 10(-6)), but was 2.20 x 10(-4) in zone B as industrial park and 7.49 x 10(-5) in zone C as residential/commercial area, both beyond the acceptable level. Further, the remediation target for benzene was calculated at 118 microg x L(-1) and the corresponding remediation area was contoured to be 165 000 m2. Given the high permeability of the aquifer and the excellent volatility of benzene, air-sparging with a combination of engineering control measure was recommended to mitigate the risk of the groundwater contamination.

The influence of BSA on adsorption equilibrium of Ni2+ onto delta-MnO2 had been investigated using a batch method. It was showed that the adsorption-pH curves of Ni2+ onto delta-MnO2 were "S-shape" at [BSA] = 10 mg x L(-1), and the leaping range of adsorption would move to high value of pH in the presence of BSA. The extent of effect had relation to the adding order and the concentration of BSA, and the trend was IV (BSA added first) > III (Ni2+ and BSA added simultaneously) approximately II (Ni2+ added first). The adsorption percentage decreased with increasing BSA concentration at the same value of pH. The Langmuir adsorption model fit the experimental date reasonably in the presence of BSA. The maximum adsorption capacity related to the BSA adding order was I (without BSA) > II approximately III > IV. In addition, the adsorption of Ni2+ onto delta-MnO2 increased with the rise of temperature. It was found that the adsorption was irreversible at pH = 4.0 and pH = 7.0. BSA had no effect on the reversibility of Ni2+ adsorption onto delta-MnO2.