Impacts of hydrologic variations on chemical weathering and solute sources in the Min River basin,Himalayan–Tibetan region

Environmental Science and Pollution Research - Feedback between hydrologic variations and chemical weathering is thought to play a crucial role in modulating global carbon cycling. The mechanisms...     

Occurrence,sources, and ecological risks of PBDEs,PCBs, OCPs,and PAHs in surface sediments of the Yangtze River Delta city cluster,China

Polybrominated diphenyl ethers (PBDEs), organochlorine pesticides (OCPs), polychlorinated biphenyls (PCBs), and polycyclic aromatic hydrocarbons (PAHs) in 25 surface sediments in three cities (Nantong, Wuxi, and Suzhou) in the Yangtze River Delta, eastern China were measured. The mean concentrations were 378, 45.8, 1.98, 4,002 ng/g for PBDEs, OCPs, PCBs, and PAHs, respectively. Their levels in the sediments in the three cities were generally consistent with the city industrialization. PBDEs and OCPs were markedly dominated by deca-BDE (>90 %) and DDTs (>70 %). A principle component analysis of the analytes identified three major factors suggesting different sources of the contaminants in the sediments. PBDEs and the organic carbon in the sediments have common sources from industrial activities; whereas OCPs and PCBs, correlated with the second factor, were mainly from historical sources. The third factor with loadings of PAHs is indicative of various combustion sources. Ecological risk assessment indicated that the potential highest risk is from DDTs, for which 22 sites exceed the effects range low (ERL) values and three sites exceed the effects range median (ERM) value.     

Prediction of half-life for adsorption kinetics in a batch reactor

Environmental Science and Pollution Research - Besides adsorption rate constant, the half-life was also a basic factor that described the characteristics of adsorption kinetics. However, the direct...     

石油化工催化剂生产过程中的职业病防治及应急处理

石化企业使用了大量的催化剂,催化剂开发、生产过程复杂,有许多原料和生产工艺,存在许多潜在的安全隐患和职业病危害因素。为预防催化剂生产过程中的事故,通过分析催化剂生产过程中的职业病危害分析,提出了相应的职业病防范及应急处置措施,加强催化剂生产过程中的职业病防治和应急处置能力,创造良好的经济、生态和社会效益,有效防止催化剂生产过程中发生安全事故和职业病。     

Pollination ecology of <Emphasis Type="Italic">Eomecon chionantha</Emphasis> Hance (Papaveraceae), an endemic species in China

Eomecon chionantha Hance, the only species in the genus Eomecon, is an angiosperm species endemic to China. Here we investigated the pollination syndrome, pollinator generalization of E. chionantha. Our results showed that the individual flower longevity of E. chionantha was 3–5 days. The flowering phenology of E. chionantha can be divided into five phases. We found significant differences in the pollination efficiency of the different insects visiting E. chionantha with bees and flies being the most efficient pollinators. This, in addition to floral morphology and phenology, suggests that E. chionantha is generalized on bees and flies and possesses an outcrossing, partially self-compatible and pollinator-dependent breeding system.     

Structural regulation of electroplating sludge by a metal–organic framework synthesis method for an enhanced denitrification activity

Journal of Material Cycles and Waste Management - Electroplating sludge contained multi-metals and organics. In previous reports, electroplating sludges were usually recycled by direct calcination...     

Deep learning architecture for air quality predictions

With the rapid development of urbanization and industrialization, many developing countries are suffering from heavy air pollution. Governments and citizens have expressed increasing concern regarding air pollution because it affects human health and sustainable development worldwide. Current air quality prediction methods mainly use shallow models; however, these methods produce unsatisfactory results, which inspired us to investigate methods of predicting air quality based on deep architecture models. In this paper, a novel spatiotemporal deep learning (STDL)-based air quality prediction method that inherently considers spatial and temporal correlations is proposed. A stacked autoencoder (SAE) model is used to extract inherent air quality features, and it is trained in a greedy layer-wise manner. Compared with traditional time series prediction models, our model can predict the air quality of all stations simultaneously and shows the temporal stability in all seasons. Moreover, a comparison with the spatiotemporal artificial neural network (STANN), auto regression moving average (ARMA), and support vector regression (SVR) models demonstrates that the proposed method of performing air quality predictions has a superior performance.     

Improving artificial forest biomass estimates using afforestation age information from time series Landsat stacks

China maintains the largest artificial forest area in the world. Studying the dynamic variation of forest biomass and carbon stock is important to the sustainable use of forest resources and understanding of the artificial forest carbon budget in China. In this study, we investigated the potential of Landsat time series stacks for aboveground biomass (AGB) estimation in Yulin District, a key region of the Three-North Shelter region of China. Firstly, the afforestation age was successfully retrieved from the Landsat time series stacks in the last 40 years (from 1974 to 2013) and shown to be consistent with the surveyed tree ages, with a root-mean-square error (RMSE) value of 4.32 years and a determination coefficient (R ²) of 0.824. Then, the AGB regression models were successfully developed by integrating vegetation indices and tree age. The simple ratio vegetation index (SR) is the best candidate of the commonly used vegetation indices for estimating forest AGB, and the forest AGB model was significantly improved using the combination of SR and tree age, with R ² values from 0.50 to 0.727. Finally, the forest AGB images were mapped at eight epochs from 1985 to 2013 using SR and afforestation age. The total forest AGB in seven counties of Yulin District increased by 20.8 G kg, from 5.8 G kg in 1986 to 26.6 G kg in 2013, a total increase of 360 %. For the persistent forest area since 1974, the forest AGB density increased from 15.72 t/ha in 1986 to 44.53 t/ha in 2013, with an annual rate of about 0.98 t/ha. For the artificial forest planted after 1974, the AGB density increased about 1.03 t/ha a year from 1974 to 2013. The results present a noticeable carbon increment for the planted artificial forest in Yulin District over the last four decades.     

Optimization of bio-drying of kitchen waste: inoculation,initial moisture content and bulking agents

Journal of Material Cycles and Waste Management - Bio-drying has been proved to be a promising method for treatment of MSW (municipal solid waste) and sewage sludge due to its high energy...     

阿维菌素对中华绒螯蟹肝胰腺氧化胁迫效应和组织结构的影响

采用半静态染毒法,研究不同浓度(1.6、8.0、16.0μg·L-1)阿维菌素在胁迫中华绒螯蟹12、24、48、96 h时肝胰腺超氧化物歧化酶(SOD)、过氧化氢酶(CAT)活性和丙二醛(MDA)积累量等氧化胁迫相关指标的变化;并在胁迫60 d时,记录各实验组和对照组中华绒螯蟹肝胰腺颜色的变化并进行组织病理观察。3个阿维菌素浓度组为实验组,空白组和溶剂组为对照组。结果表明在整个实验过程中空白组和溶剂组各个时间点各项指标之间无显著差异(P>0.05);低浓度(1.6μg·L-1)组SOD和CAT活力变化不显著(P>0.05);中浓度(8.0μg·L-1)组SOD和CAT活力变化趋势一致,持续被诱导,SOD活力在24 h以后显著高于空白组(P<0.01),CAT活力在48 h以后显著高于空白组(P<0.01);高浓度(16.0μg·L-1)组SOD和CAT活力在12 h~24 h之间变化趋势一致,表现为显著升高(P<0.05),但是在48 h之后,SOD活力显著下降(P<0.05);96 h时,高浓度组SOD活力显著低于空白组(P<0.01),而CAT活力显著高于空白组(P<0.01);在整个实验过程中各实验组MDA积累量逐渐增加,高浓度组氧化胁迫指标的变化幅度大于低浓度组。胁迫60 d时,取样观察可见对照组中华绒螯蟹肝胰腺正常,各实验组中华绒螯蟹肝胰腺发生了不同程度的病变,肝胰腺颜色由最开始的橘黄色变成了淡黄色、黄白色甚至白色,高、中、低各浓度组肝胰腺白化所占的比例分别是66.6%、57.1%和25.0%。组织病理分析显示,淡黄色肝胰腺的病理变化主要是B细胞数量减少,肝胰腺上皮细胞部分肿大并出现空泡;黄白肝病理观察可见肝胰腺上皮细胞中空泡数量增多,体积增大,且空泡内出现内容物,细胞核固缩;白肝的病理表现主要是基膜增厚,上皮细胞大量脱落,散落在管腔中,空泡数量进一步增多,肝胰腺的生理功能受损。由此得出,阿维菌素会对中华绒螯蟹肝胰腺造成氧化胁迫和组织损伤,且阿维菌素和对肝胰腺的氧化胁迫效应和组织结构损伤程度有一定的剂量-效应关系。