燃煤型砷中毒的最低有效累积暴露剂量初探

以陕南燃煤型砷中毒病区的5个自然村为调查采样点,通过现场流行病学调查和环境样品的分析测定,分析砷暴露人群的砷暴露途径,估算各暴露途径(呼吸、饮水和食物)的暴露剂量及对总暴露的贡献率,探讨引发燃煤型地方性砷中毒发病的最低有效暴露剂量。研究结果表明,除对照村外,采暖季各村的烤火间和卧室空气砷含量均有不同程度的超标,水和粮食未受燃煤砷污染。在采暖季,高砷煤燃烧污染的空气是人群砷暴露的主要来源;在非采暖季消化道砷暴露是各村的主要摄砷途径;提示消化道暴露对累积砷暴露的贡献不容忽视。结合问卷调查和流行病学调查结果,估算陕南病区引发燃煤型砷中毒的最低累积暴露剂量在1 712 mg左右。     

石化销售企业工程建设施工安全监管应用研究

分析了石化销售企业施工现场安全管理的现状以及产生的原因,针对上述问题提出了加强工程施工安全监管的建议和相关管理措施。     

一元有机酸的络合萃取研究

本文考察了不同稀释剂中磷酸三丁酯（ＴＢＰ）和甲基异丁基酮（ＭＩＢＫ）的甲酸，乙酸，丙酸，丁酸及氯乙酸，二氯乙酸和三氯乙酸等一元有机酸的萃取，萃取反应属中性络合萃取机理，有机相中生成１：１的萃合物，同时，探讨了各因素（有机酸种类、稀释剂性质、温度和无机盐）对萃取的影响，得到了萃取反应的平衡常数，热力学函数和萃取性能与有机酸性质间的关系方程等。     

邯钢炼铁系统粉尘污染防治技术分析

重点介绍了邯钢新建2000m^3高炉（7^#高炉）出铁场和槽下上料系统粉尘污染治理方面的成功经验，并对应用电除尘器处理粉尘的技术进行了简要分析。     

Potential health risk of arsenic and cadmium in groundwater near Xiangjiang River, China: a case study for risk assessment and management of toxic substances

As part of our efforts to find effective methods to the drinking water risk management, the health risk assessment of arsenic and cadmium in groundwater near Xiangjiang River was analyzed. The results suggest that although the arsenic and cadmium concentrations in 97% of groundwater sources are less than the requirement of Water Quality Standards for Drinking Water (GB5749-2006) in China, the residents served by almost all of the investigated centralized drinking water sources have a significant potential health risk by consumption, especially cancer risk. It is justified through analyses that risk assessment is an effective tool for risk management, and the maximum permissible concentration of arsenic and cadmium in drinking water (0.01 and 0.005?mg L^-1, respectively) is suitable for China at present, considering the current economic status of China. Risk managers develop cleanup standards designed to protect against all possible adverse effects, which should take into account highly exposed individuals, effects of mixtures of toxic substances, attendant uncertainties, and other factors such as site-specific (or generic) criteria, technical feasibility, cost?Cbenefit analyses, and sociopolitical concerns.     

Characteristics of environmental factors and their effects on CH4 and CO2 emissions from a closed landfill: An ecological case study of Shanghai

To elucidate the influence of landfill gas (LFG) emission on environmental factors, an ecological investigation that was primarily concerned with the characteristics of vegetation, cover soil, and solid waste in the landfill was carried out. Temporal and spatial variations in vegetation diversity and coverage and their effects on reducing the emission of methane in the landfill were investigated. The results showed that both vegetation coverage and diversity increased with elapsed landfill closure time. The transition trend of the vegetation species was from perennial plant (Phragmites australis) to annual plants. Perennial vegetation was the dominant type of vegetation during the early closure period, and annual vegetation coverage increased with closure time. Vegetation preferentially appeared in areas of comparatively high depth of cover soil, which was characterized by high moisture retentiveness that enabled vegetation growth. The concentrations of methane and carbon dioxide in the cover soil significantly decreased with increasing closure time. The concentrations of methane and carbon dioxide from bare cover soil were higher than those from vegetated cover soil whereas the CO₂ flux of bare cover soil was less than that of vegetated cover soil.     

The electrochemical selective reduction of NO using CoSe2@CNTs hybrid

Converting the NO from gaseous pollutant into NH₄ ⁺ through electrocatalytical reduction using cost-effective materials holds great promise for pollutant purifying and resources recycling. In this work, we developed a highly selective and stable catalyst CoSe₂ nanoparticle hybridized with carbon nanotubes (CoSe₂@CNTs). The CoSe₂@CNTs hybrid catalysts performed an extraordinary high selectivity for NH₄ ⁺ formation in NO electroreduction with minimal N₂O production and H₂ evolution. The specific spatial structure of CoSe₂ is conductive to the predominant formation of N-H bond between the N from adsorbed NO and H and inhibition of N-N formation from adjacent adsorbed NO. It was also the first time to convert the coordinated NO into NH₄ ⁺ using non-noble metal catalysis. Moreover, the original concept of employing CoSe₂ as eletrocatalyst for NO hydrogenation presented in this work can broaden horizons and provide new dimensions in the design of new highly efficient catalysts for NH₄ ⁺ synthesis in aqueous solution.

     

Oasis land-use change and its effects on the oasis eco-environment in Keriya Oasis,China

Land-use change in oases of arid zones play a significant role in the sustainable development and stability of oases. This paper presents a typical case of successful efforts to mitigate land-use change, its drivers and effects on the oasis eco-environment at Keriya Oasis in the western arid zone of China using remotely-sensed data, official statistics, and data collected by field investigation. Mathematical models were developed to quantify important elements related to land-use change, including net change and total change. The results indicate that: (1) approximately 17% of land-use types of Keriya Oasis changed between 1991 and 2002; (2) socioeconomic development, climate change, and economic polices contributed to land-use change in the oasis; (3) inappropriate human activities were the main cause of land-use change and eco-environmental degradation in the oasis; and (4) the stability of the oasis is threatened by land-use change and unexpected eco-environmental changes in the oasis and oasis–desert ecotone. The study suggests irrational human activity in arid zones, and that caution should be exercised to maintain stability and sustainable development of oases.     

Forecasting energy demand of China using Bayesian Combination model

To analyze the impact of the related economic factors on China's energy demand, Path analysis is used to analyze the major factors and their direct and indirect effects on energy demand. This study showed that the main factors that affect the energy demand are the economic growth, the total population, and the primary energy structure, the economic growth is the main determining factor, and the primary energy structure is the major restrictive factor. On this basis and considering the multicollinearity and the validity of the forecast, we established a partial least-square (PLS) and the trend extrapolation prediction model, and then we sum up all the information to found a PLS—trend extrapolation combination forecasting model based on the optimized combining forecast theory. Finally, we obtain the probability distribution of the error using the Bayesian statistic theory and find the confidence interval of combining forecasting result. The results indicate that the outcome of combining forecasting will be more precise after using the Bayesian error correction approach.