Estimating the remaining atmospheric environmental capacity using a single-box model in a high pollution risk suburb of Chengdu, China.

The atmospheric pollution has been the public attention in recent years. In order to better coordinate economic development and atmospheric environmental management, China introduced the concept of atmospheric environmental capacity (AEC). The remaining atmospheric environmental capacity (RAEC) calculated by existing atmospheric pollution sources and AEC is an important basis for regional development and environmental protection. The RAEC of the high-pollution risk suburb of Chengdu in 2015 was estimated by the single-box model and analyzed on multiple time scales. The results show that the RAEC of SO2 and NO2 in this region is 3299 t/a and 2849 t/a, respectively under the annual time scale. However, in the daily time scale, the RAEC of NO2 is negative for 3 days, that is, there are 3 days with serious air pollution. Therefore, it is not appropriate to plan the industrial area only by relying on annual RAEC. Especially, RAEC displays inter-seasonal and monthly variability. On the one hand, in plain areas with low wind speed and little change in wind direction, achieving the prediction of atmospheric mixing layer height could give early warning of atmospheric pollution events. On the other hand, different management measures are taken on different time scales. On a long timescale, the regional energy structure should be optimized. On seasonal and monthly time scales, the production plans should be adapted to RAEC. On the daily time scale, it mainly deals with the serious atmospheric pollution accident timely.

Mechanism-based structure-activity relationship (SAR) analysis of aromatic amines and nitroaromatics carcinogenicity via statistical analyses based on CPDB.

Cancer is a leading cause of human mortality around the globe. In this study, mechanism-based SAR (Structure-Activity Relationship) was employed to investigate the carcinogenicity of aromatic amines and nitroaromatics based on CPDB. Principal component analysis and cluster analysis were used to construct the SAR model. Principle component analysis generated three principal components from 12 mechanism-based descriptors. The extracted principal components were later used for cluster analysis, which divided the selected 55 chemicals into six clusters. The three principal components were proposed to describe the "transport", "reactivity" and "electrophilicity" properties of the chemicals. Cluster analysis indicated that the relevant "transport" properties positively correlated with the carcinogenic potential and were contributing factors in determining the carcinogenicity of the studied chemicals. The mechanism-based SAR analysis suggested the electron donating groups, electron withdrawing groups and planarity are significant factors in determining the carcinogenic potency for studied aromatic compounds. The present study may provide insights into the relationship between the three proposed properties and the carcinogenesis of aromatic amines and nitroaromatics.

[Flux Characteristics of CO2, CH4, and N2 O and their Influencing Factors in Different Types of Ditches on the Chengdu Plain].

In order to study the flux characteristics of CH4, CO2 and N2O in different ditches and their influencing factors, three types of ditches (an agricultural ditch, agricultural-living compound ditch, and living ditch) were monitored once a month from March 2014 to February 2015 using static floating chambers in the Chengdu Plain. The results showed that:① Affected by human activities, CO2, CH4, and N2O fluxes were high in ditches and ranged from -2.26-1504.40 mg·(m2·h)-1, 0.69-40.00 mg·(m2·h)-1, and -2.27-70.35 µg·(m2·h)-1,respectively. All are higher in summer compared to autumn and spring, and are lowest in winter. ② The flux of CO2 in agricultural-living compound ditches was significantly higher than that in agricultural ditches and living ditches (P<0.05), and the fluxes of CH4 and N2O in living ditches were significantly higher than those in agricultural ditches and agricultural-living compound ditches (P<0.05). ③ Water temperature and rainfall were the main environmental factors affecting CO2, CH4, and N2O fluxes, and DO (dissolved oxygen) and TN (total nitrogen) were the main environmental factors affecting CO2 and N2O fluxes. NH4+-N (ammonium nitrogen) and DO were the main water quality parameters affecting the CH4 flux.

[Nitrogen non-point source pollution identification based on ArcSWAT in Changle River].

The ArcSWAT (Soil and Water Assessment Tool) model was adopted for Non-point source (NPS) nitrogen pollution modeling and nitrogen source apportionment for the Changle River watershed, a typical agricultural watershed in Southeast China. Water quality and hydrological parameters were monitored, and the watershed natural conditions (including soil, climate, land use, etc) and pollution sources information were also investigated and collected for SWAT database. The ArcSWAT model was established in the Changle River after the calibrating and validating procedures of the model parameters. Based on the validated SWAT model, the contributions of different nitrogen sources to river TN loading were quantified, and spatial-temporal distributions of NPS nitrogen export to rivers were addressed. The results showed that in the Changle River watershed, Nitrogen fertilizer, nitrogen air deposition and nitrogen soil pool were the prominent pollution sources, which contributed 35%, 32% and 25% to the river TN loading, respectively. There were spatial-temporal variations in the critical sources for NPS TN export to the river. Natural sources, such as soil nitrogen pool and atmospheric nitrogen deposition, should be targeted as the critical sources for river TN pollution during the rainy seasons. Chemical nitrogen fertilizer application should be targeted as the critical sources for river TN pollution during the crop growing season. Chemical nitrogen fertilizer application, soil nitrogen pool and atmospheric nitrogen deposition were the main sources for TN exported from the garden plot, forest and residential land, respectively. However, they were the main sources for TN exported both from the upland and paddy field. These results revealed that NPS pollution controlling rules should focus on the spatio-temporal distribution of NPS pollution sources.