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.

The silicon active sites driven by oxygen vacancies in iron silicate for activating peroxymonosulfate.

Most metal sites and some non-metallic sites such as carbon and nitrogen are usually considered to be traditional active sites during peroxymonosulfate (PMS) activation. However, as an important non-metallic element, the actual role of silicon (Si) in PMS activation still remains unclear. In this work, taking iron silicate (FeSi) as an example, the role of the Si region in PMS activation was clearly revealed. The experiments and density functional theory (DFT) calculation results showed that besides the traditional Fe sites, the Si also played a non-negligible role during PMS activation. In FeSi containing oxygen vacancies (Ovac), Fe-Si was the active site instead of Fe-Fe. The Bard charge results implied that the presence of Ovac tuned the electronic properties of FeSi, making the Si participate in PMS activation. This work deepened understanding of the role of Si in silicates for PMS activation and provided a theoretical basis for the development of excellent Si-based catalysts.

Retracted: Long-term copper toxicity in apple trees (Malus pumila Mill) and bioaccumulation in fruits.

The following article from Environmental Toxicology, 'Long-term Copper Toxicity in Apple Trees (Malus pumila Mill) and Bioaccumulation in Fruits' by Bai-Ye Sun, Shi- Hong Kan, Yan-Zong Zhang, Jun Wu, Shi-Huai Deng, Chun-Sheng Liu and Gang Yang, published online on January 15, 2010 in Wiley InterScience (www.interscience.wiley.com; DOI: 10.1002/tox.20565), has been retracted by agreement between the authors, the journal Editor in Chief, Dr. Paul Tchounwou, and Wiley Periodicals, Inc. The retraction has been agreed at the request of the authors due to overlap with 'Copper Toxicity and Bioaccumulation in Chinese Cabbage (Brassica pekinensis Rupr.)' by Zhi-Ting Xiong and Hai Wang, published in Environmental Toxicology, Volume 20, pages 188-194, 2005.

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.

Investigation of carbon dioxide emission in China by primary component analysis.

Principal component analysis (PCA) is employed to investigate the relationship between CO2 emissions (COEs) stemming from fossil fuel burning and cement manufacturing and their affecting factors. Eight affecting factors, namely, Population (P), Urban Population (UP); the Output Values of Primary Industry (PIOV), Secondary Industry (SIOV), and Tertiary Industry (TIOV); and the Proportions of Primary Industry's Output Value (PPIOV), Secondary Industry's Output Value (PSIOV), and Tertiary Industry's Output Value (PTIOV), are chosen. PCA is employed to eliminate the multicollinearity of the affecting factors. Two principal components, which can explain 92.86% of the variance of the eight affecting factors, are chosen as variables in the regression analysis. Ordinary least square regression is used to estimate multiple linear regression models, in which COEs and the principal components serve as dependent and independent variables, respectively. The results are given in the following. (1) Theoretically, the carbon intensities of PIOV, SIOV, and TIOV are 2573.4693, 552.7036, and 606.0791 kt per one billion $, respectively. The incomplete statistical data, the different statistical standards, and the ideology of self sufficiency and peasantry appear to show that the carbon intensity of PIOV is higher than those of SIOV and TIOV in China. (2) PPIOV, PSIOV, and PTIOV influence the fluctuations of COE. The parameters of PPIOV, PSIOV, and PTIOV are -2706946.7564, 2557300.5450, and 3924767.9807 kt, respectively. As the economic structure of China is strongly tied to technology level, the period when PIOV plays the leading position is characterized by lagging technology and economic developing. Thus, the influence of PPIOV has a negative value. As the increase of PSIOV and PTIOV is always followed by technological innovation and economic development, PSIOV and PTIOV have the opposite influence. (3) The carbon intensities of P and UP are 1.1029 and 1.7862 kt per thousand people, respectively. The carbon intensity of the rural population can be inferred to be lower than 1.1029 kt per thousand people. The characteristics of poverty and the use of bio-energy in rural areas result in a carbon intensity of the rural population that is lower than that of P.

[Environmental impacts of sewage treatment system based on emergy analysis].

"Integrated sewage treatment system" (ISTS) consists of sewage treatment plant system and their products (treated water and dewatered sludge) disposal facilities, which gives a holistic view of the whole sewage treatment process. During its construction and operation, ISTS has two main impacts on the environment, i.e., the consumption of resources and the damage of discharged pollutants on the environment, while the latter was usually ignored by the previous researchers when they assessed the impacts of wastewater treatment system. In order to more comprehensively understanding the impacts of sewage treatment on the environment, an analysis was made on the ISTS based on the theories of emergy analysis, and, in combining with ecological footprint theory, the sustainability of the ISTS was also analyzed. The results showed that the emergy of the impacts of water pollutants on the environment was far larger than that of the impacts of air pollutants, and NH3-N was the main responsible cause. The emergy consumption of ISTS mainly came from the emergy of wastewater and of local renewable resources. The "sewage treatment plant system + landfill system" had the highest emergy utilization efficiency, while the "sewage treatment plant system + reclaimed water reuse system + incineration system" had the lowest one. From the aspect of environmental sustainability, the "sewage treatment plant system + reclaimed water reuse system + landfill system" was the best ISTS, while the "sewage treatment plant system + incineration system" was the worst one.

[Secondary organic tracers in summer PM2.5 aerosols from Baima Spring Scenic Area, Yaan, Sichuan Province].

Integrated PM2.5 aerosol samples were collected at Baima Spring Scenic Area, a forest site of Yaan, Sichuan Province, during the summer of 2010. Organic speciation including isoprene oxidation products (2-methyltetrols, C5-alkene trols, 2-methylyceric acid), alpha-/beta-pinene oxidation products (norpinic acid, 3-hydroxyglutaric acid, 3-methy-1,2,3-butanetricarboxylic acid), and small molecular carboxylic acid (malic acid, 2-hydroxyglutaric acid) were analyzed. The generation mechanisms of SOA as well as their influencing factors were particularly discussed. Results show that average concentrations of 2-methyltetrols, C5-alkene triols, 2-methyglyceric acid, norpinic acid, 3-hydroxyglutaric acid and 3-methy-1,2,3-butanetricarboxylic acid are 63.3, 45.0, 4.4, 4.1, 5.0, 5.3 ng x m(-3) respectively, of 24-hour lapse samples. SOA compounds are consistent with higher concentrations in the day than during the night only except for norpinic acid. Relatively high level of biogenic SOA at the study area is concerned with many environmental factors, i. e. local abundant vegetations, warm and humid climate, sunken valley topography, the atmospheric pollution state, etc.

Certain antioxidant enzymes and lipid peroxidation of radish (Raphanus sativus L.) as early warning biomarkers of soil copper exposure.

Copper (Cu) is a major heavy metal contaminant with various anthropogenic and natural sources. Recently, using biomarkers to monitor the effects of pollutants has attracted increased interest. Pot culture experiments using radish (Raphanus sativus L.) was performed to investigate Cu phytotoxic effects on antioxidant enzymes and other early warning biomarkers of soil Cu exposure. Under low dose Cu stress (lower than the EC10, Cu concentration reducing root length by 10%), activity and isozyme expression of superoxide dismutase (SOD), catalase (CAT), and peroxidases (POD) increased significantly; no significant variations in chlorophyll, carotenoid, and malondialdehyde (MDA) content in leaves and toxic symptoms were observed. Under a slightly higher Cu stress (close to the EC10), activity and isozyme expression of SOD and MDA content were enhanced significantly; those of CAT and POD decreased due to an inverted U-shape dose response. Chlorophyll content remained unchanged. Thus, antioxidant enzymes and MDA content are more sensitive to Cu stress, showing significant variations ahead of chlorophyll and toxic symptoms under Cu stress (lower than about 200 mg kg(-1) soil). Thus, the joint monitoring of antioxidant enzymes and MDA content of R. sativus can be used as biomarkers of soil Cu contamination.