Exposure,epidemiology, and mechanism of the environmental toxicant manganese

It has become increasingly apparent that global manganese (Mn) pollution to air and water is a significant threat to human health. Despite this recognition, research is only beginning to comprehend the detrimental effects of exposure. Mn, while essential, is particularly harmful to the central nervous system, and overexposure is symptomatic of several neurological disorders. At-risk populations have been identified, but it is still unclear whether typical exposure levels have any long-term consequences. Those at an elevated risk have diminished intellectual function, learning and memory, and mental development. While the overall mechanism of toxicity is undetermined, Mn has been found to induce oxidative stress, exacerbate mitochondrial dysfunction, dysregulate autophagy, and promote apoptosis, ultimately enhancing neurodegeneration. Extrapolation of this in vitro and in vivo data to humans is difficult. There is a definite need to correlate epidemiological studies with causative effects. It is imperative that research efforts endure, so threats are appropriately identified and exposure properly regulated.     

The fractionation and geochemical characteristics of rare earth elements measured in ambient size-resolved PM in an integrated iron and steelmaking industry zone

Environmental Science and Pollution Research - Improved understanding of the fractionation and geochemical characteristic of rare earth elements (REEs) from steel plant emissions is important due...     

Decoupling of nonferrous metal consumption from economic growth in China

Nonferrous metal is an important basis material for the development of the national economy, and its consumption directly affects economic development. It has great significance in the effective utilization of nonferrous metals, development of an environment-friendly society, and investigation of the decoupling of nonferrous metal consumption and GDP growth. The decoupling indicators for nonferrous metal consumption and GDP growth (D _r) in China from 1995 to 2010 were calculated in this study, and the results were analyzed. A productive model based on BP neural network was established. Then, the decoupling indicators for nonferrous metal consumption and GDP growth in China for the period of 2011–2020 were predicted. For the period of 1995–2010, the annual average decoupling indicators were <1 for copper, aluminum, zinc, lead, and nickel, except for tin, which was 0.21. The analysis showed that the decoupling of nonferrous metal consumption and GDP growth is in a less optimistic situation to copper, aluminum, zinc, lead, and nickel in China from 1995 to 2010. The annual average decoupling indicator for tin was 0.21, which indicates relative decoupling. For the period of 2011–2020, the predicted decoupling indicators for copper, aluminum, zinc, lead, nickel, and tin were between 0 and 1. This finding indicates the implementation of relative decoupling. However, the total consumption of nonferrous metals did not decouple from GDP growth.     

Rebound effect and its decomposition – an analysis based on energy types in China

Rebound effect derived from energy efficiency improvement has been widely invested. However, most of studies focus on the rebound effect of the energy composite level and neither distinguish nor compare different energy types. We compare the differences in energy saving and energy rebound between primary and secondary energy sources, and further decompose the rebound effect into production rebound part and final demand component. To do so, we add a module for rebound into a comparative state China-CGE model. We design and test two simulation scenarios using the model. In Scenario 1, all production sectors’ energy efficiency of using primary energy increases by 5%. In Scenario 2, all production sectors’ energy efficiency of using secondary energy increases by 5%. The results show that Scenario 2 leads to more GDP growth and more energy saving. Our scenarios show rebound effects range between 9.6% and 27.9%, and in general are higher when energy efficiency of using primary energy sources is improved. Our decomposition analysis shows that improving energy efficiency in production sectors would stimulates energy use of final demand. Indeed, the consumption side has significant contribution to rebound in secondary energy use, especially in crude oil and gas. This study reveals that improving efficiency of using secondary energy is better than improving that of primary energy, both in terms of economic impact and energy rebound. And complementary policies that prevent energy services prices from falling too much can be adopted to reduce rebound. Controlling residential energy use could also be effective in reducing rebound, this has particular implication to economies in which residential energy consumption are far from saturation.     

江苏省沿江开发区空间分工、制造业集聚与转移

基于新经济地理学相关理论,针对江苏省沿江开发战略实施以后,制造业空间可能存在的变动,在整理和分析调查问卷资料的基础上,选择专业化指数和基尼系数2种方法来定量分析江苏省21个沿江省级以上开发区空间分工、制造业集聚和转移态势。结果表明：（1）2002~2006年江南沿江开发区通过向江北沿江开发区转移部分传统产业,逐渐形成了江南沿江技术/资本密集型制造业“中心”和江北沿江劳动密集型制造业“外围”的空间分工格局;（2）江南沿江开发区内部、江北沿江开发区内部尚未形成良好的分工关系;（3）受开发区发展阶段、区域产业政策、本地化资源供给和市场需求等因素影响,并未发现理论预期的普遍存在的产业集聚现象,仅纺织服装、石化、电力、塑料橡胶等产业呈现集中趋势.     

大坝拦截对河流水溶解组分化学组成的影响分析——以夏季乌江渡水库为例

以乌江渡水库为主要研究对象,揭示了大坝拦截条件下的夏季水化学特征：阴离子以HCO-3,SO2-4为主,阳离子以Ca2+,Mg2+为主,其余离子含量低于10%,说明了碳酸盐岩的风化对水体化学组成起到了主要控制作用,蒸发盐岩石的风化对水体化学组成影响较小。水库水体存在温度分层现象,形成了不同层位的水体有着不同的水化学组成,即水化学分层。水化学的分层形成了溶解组分在水库垂直深度上的规律分布,比如受藻类的影响,Si和叶绿素随深度成相反的变化特征;HCO-3受光合作用和有机质降解的影响,30 m 以上随着水深的增加而递增,30 m 以下呈现相反趋势;水库泄水方式明显改变了水化学各种参数和离子在水体中的分配。乌江水库两主要支流（息烽河和偏岩河）分别对乌江渡坝前水体中的Ca2+,SO2-4,HCO-3,Mg2+和K+,Na+,Cl-有贡献。网箱养鱼、生活污水、农业施肥、酸性矿山废水以及酸雨沉降都会对水体造成不同程度的污染。     

绵阳市代表性点位土壤多环芳烃剖面分布特征

通过挑选绵阳市有代表性的点位土壤柱,应用GC MS分析土壤柱垂直剖面中多环芳烃的含量水平,得出其垂直剖面分布特征。结果表明：5~20 cm深度中的PAHs含量最高,40 cm以下则含量锐减。由于表层（0～5 cm）土壤与大气之间的土气交换频繁,PAHs含量相对较低,而5~20 cm处土壤受到表层土壤的遮盖,PAHs富集较高,含量达到整个土壤柱最高值。多环芳烃总体垂直剖面分布特征表现出随深度增加含量减少的趋势。PAHs总含量以江油市点位(33024 ng/g)最高,其次是三台县点位(29989 ng/g),最低是游仙区点位(11274 ng/g)。研究区主要污染物为Nap、Phe和Chr/y。其中不同的土质、种植物都能影响PAHs的富集和迁移速率,导致含量在不同深度上产生变化。此外,参照有关环境质量标准,发现PAHs总量上江油市点位与三台县点位属于轻微污染、游仙区点位则属于无污染。     

负载TiO2浮石对污水处理厂二沉池出水的矿化与灭菌研究

城市污水处理厂第二沉淀池出水的污染物浓度较低,经过矿化及灭菌等深度处理后可以回用,从而减轻对淡水资源的需求。本实验采用溶胶-凝胶法制备了负载TiO2的浮石光催化剂,对城市污水处理厂第二沉淀池出水进行了矿化及灭菌处理研究。采用低压汞灯对处理水样照射2h,有机物降解率可以达到50％,灭菌效率达到100％。处理后的水可以作为农作物灌溉、城市绿化和娱乐用水。负载在浮石表面的TiO2薄膜经过10次的光催化循环实验后,没有明显破损,可以再次循环使用。TiO2浮石具有质轻、机械性能好和价格低等优点,该方法处理废水的适用浓度低,可以广泛应用于微污染水和城市污水处理厂出水的深度处理。     

Characterization of on-road vehicle emission factors and microenvironmental air quality in Beijing,China

In this paper, we report the results and analysis of a recent field campaign in August 2007 investigating the impacts of emissions from transportation on air quality and community concentrations in Beijing, China. We conducted measurements in three different environments, on-road, roadside and ambient. The carbon monoxide, black carbon and ultrafine particle number emission factors for on-road light-duty vehicles are derived to be 95 g kg^?1-fuel, 0.3 g kg^?1-fuel and 1.8 × 10¹⁵ particles kg^?1-fuel, respectively. The emission factors for on-road heavy-duty vehicles are 50 g kg^?1-fuel, 1.3 g kg^?1-fuel and 1.1 × 10¹⁶ particles kg^?1-fuel, respectively. The carbon monoxide emission factors from this study agree with those derived from remote sensing and on-board vehicle emission testing systems in China. The on-road black carbon and particle number emission factors for Chinese vehicles are reported for the first time in the literature. Strong traffic impacts can be observed from the concentrations measured in these different environments. Most clear is a reflection of diesel truck traffic activity in black carbon concentrations. The comparison of the particle size distributions measured at the three environments suggests that the traffic is a major source of ultrafine particles. A four-day traffic control experiment conducted by the Beijing Government as a pilot to test the effectiveness of proposed controls was found to be effective in reducing extreme concentrations that occurred at both on-road and ambient environments.     

Simulation of global warming potential (GWP) from rice fields in the Tai-Lake region,China by coupling 1:50,000 soil database with DNDC model

Quantifying greenhouse gas (GHG) emissions from wetland ecosystems is a relatively new issue in global climate change studies. China has approximately 22% of the world's rice paddies and 38% of the world's rice production, which are crucial to accurately estimate the global warming potential (GWP) at regional scale. This paper reports an application of a biogeochemical model (DeNitrification and DeComposition or DNDC) for quantifying GWP from rice fields in the Tai-Lake region of China. For this application, DNDC is linked to a 1:50,000 soil database, which was derived from 1107 paddy soil profiles compiled during the Second National Soil Survey of China in the 1980–1990s. The simulated results show that the 2.34 Mha of paddy soil cultivated in rice–wheat rotation in the Tai-Lake region emitted about ?1.48 Tg C, 0.84 Tg N and 5.67 Tg C as CO₂, N₂O, and CH₄ respectively, with a cumulative GWP of 565 Tg CO₂ equivalent from 1982 to 2000. As for soil subgroups, the highest GWP (26,900 kg CO₂ equivalent ha^?1 yr^?1) was linked to gleyed paddy soils accounting for about 4.4% of the total area of paddy soils. The lowest GWP (5370 kg CO₂ equivalent ha^?1 yr^?1) was associated with submergenic paddy soils accounting for about 0.32% of the total area of paddy soils. The most common soil in the area was hydromorphic paddy soils, which accounted for about 53% of the total area of paddy soils with a GWP of 12,300 kg CO₂ equivalent ha^?1 yr^?1. On a regional basis, the annual averaged GWP in the polder, Tai-Lake plain, and alluvial plain soil regions was distinctly higher than that in the low mountainous and Hilly soil regions. As for administrative areas, the average annual GWP of counties in Shanghai city was high. Conversely, the average annual GWP of counties in Jiangsu province was low. The high variability in soil properties throughout the Tai-Lake region is important and affects the net greenhouse gas emissions. Therefore, the use of detailed soil data sets with high-resolution digital soil maps is essential to improve the accuracy of GWP estimates with process-based models at regional and national scales.