基于EFDC的长江常州段污水排江浓度场数值模拟

长江感潮河段水流与污染排放引起的浓度场复杂多变,基于EFDC(Environmental Fluid Dynamic Code)模型,采用正交曲线网格拟合自然河道边界,建立了长江常州段的水动力和水质模型。采用现场同步实测资料,与计算结果比对,证明该模型在水动力和水质两个方面都与实测数据吻合较好,满足了实际工程的需要;同时由于长江水流运动较快,一阶降解动力学已经满足了化学需氧量(COD)、氨氮(NH3-N)和总磷(TP)浓度计算要求,可以不考虑它们复杂的生化反应过程。     

浅谈滨海湿地生态环境退化监测与评价

指出了滨海湿地面临的主要环境问题。简述了美国、欧洲、澳大利亚等滨海湿地现状及监测评价方法。对我国滨海湿地管理与研究进展进行了分析探索。     

美国地表水环境监测管理体系及对我国的启示

简述了美国地表水监测管理体系,指出其健全的环境监测体系、完善的标准体系以及充分的信息公开和数据共享是保障水环境质量的基石、关键和枢纽。结合我国水环境监测管理的现状,提出,应加强水环境质量监测的立法工作,进一步完善水污染物排污许可证制度,建立以水环境质量为目标的水环境管理制度体系,进一步加大监测信息公开和数据共享力度,修订更适合我国的水环境质量监测指标。     

Diversity of crude oil-degrading bacteria and alkane hydroxylase (<Emphasis Type="Italic">alkB</Emphasis>) genes from the Qinghai-Tibet Plateau

The aim of this study was to survey the response of the microbial community to crude oil and the diversity of alkane hydroxylase (alkB) genes in soil samples from the Qinghai-Tibet Plateau (QTP). The enrichment cultures and clone libraries were used. Finally, 53 isolates and 94 alkB sequences were obtained from 10 pristine soil samples after enrichment at 10 °C with crude oil as sole carbon source. The isolates fell into the phyla Proteobacteria, Actinobacteria, and Bacteroidetes, with the dominance of Pseudomonas and Acinetobacter. The composition of degraders was different from polar habitats where Acinetobacter sp. is not a predominant responder of alkane degradative microbial communities. Phylogenetic analysis showed that the alkB genes from isolates and enrichment communities formed eight clusters and mainly related with alkB genes of Pseudomonas, Rhodococcus, and Acinetobacter. The alkB gene diversity in the QTP was lower than marine environments and polar soil samples. In particular, a total of 10 isolates exhibiting vigorous growth with crude oil could detect no crude oil degradation-related gene sequences, such as alkB, P450, almA, ndoB, and xylE genes. The Shannon-Wiener index of the alkB clone libraries from the QTP ranged from 1.00 to 2.24 which is similar with polar pristine soil samples but lower than that of contaminated soils. These results indicated that the Pseudomonas, Acinetobacter, and Rhodococcus genera are the candidate for in situ bioremediation, and the environment of QTP may be still relatively uncontaminated by crude oil.     

Fluctuating asymmetry rather than oxidative stress in <Emphasis Type="Italic">Bufo raddei</Emphasis> can be an accurate indicator of environmental pollution induced by heavy metals

Oxidative stress (OS) and fluctuating asymmetry (FA) as risk markers for environmental stress are widely used to predict changes in the health and fitness of many animals exposed to pollutants. However, from the perspective of protecting declining amphibians, it remains to be verified which one would be a reliable indicator for amphibians exposed to long-term heavy metal pollution under natural conditions. In this study, the OS and FA of Bufo raddei exposed to natural heavy metal pollution were analyzed to determine which marker is more accurate for indicating heavy metal-induced stress. Three years of data were collected during the breeding season of B. raddei from Baiyin (BY), which has been mainly contaminated with Cu, Zn, Pb, and Cd compounds for a long period, and from Liujiaxia (LJX), which is a relatively unpolluted area. Unexpectedly, although significant accumulation of the four heavy metals was found in the kidney and liver of B. raddei from BY, the levels of superoxide dismutase, glutathione peroxidase, and malondialdehyde in these two organs were found to be irregular, with low repeatability in both BY and LJX. However, significant differences in the levels of FA were observed in B. raddei populations from these two areas over the past 3 years (P < 0.01). The degrees of FA in B. raddei populations from BY and LJX were assessed as degree 4 and 1, respectively. In short, this study suggested that FA was a more reliable and effective indicator than OS to monitor and predict long-term environmental stress on anuran amphibians.     

Spatial succession modeling of biological communities: a multi-model approach

Strong spatial correlation may exist in the spatial succession of biological communities, and the spatial succession can be mathematically described. It was confirmed by our study on spatial succession of both plant and arthropod communities along a linear transect of natural grassland. Both auto-correlation and cross-correlation analyses revealed that the succession of plant and arthropod communities exhibited a significant spatial correlation, and the spatial correlation for plant community succession was stronger than arthropod community succession. Theoretically it should be reasonable to infer a site's community composition from the last site in the linear transect. An artificial neural network for state space modeling (ANNSSM) was developed in present study. An algorithm (i.e., Importance Detection Method (IDM)) for determining the relative importance of input variables was proposed. The relative importance for plant families Gramineae, Compositae and Leguminosae, and arthropod orders Homoptera, Diptera and Orthoptera, were detected and analyzed using IDM. ANNSSM performed better than multivariate linear regression and ordinary differential equation, while ordinary differential equation exhibited the worst performance in the simulation and prediction of spatial succession of biological communities. A state transition probability model (STPM) was proposed to simulate the state transition process of biological communities. STPM performed better than multinomial logistic regression in the state transition modeling. We suggested a novel multi-model framework, i.e., the joint use of ANNSSM and STPM, to predict the spatial succession of biological communities. In this framework, ANNSSM and STPM can be separately used to simulate the continuous and discrete dynamics.     

Spatial variability of soil heavy metals in the three gorges area: multivariate and geostatistical analyses

There is a growing concern about environmental contamination in the three gorges area. The objectives of this study were to investigate the spatial variability and the possible influence factors of seven heavy metals (As, Cd, Cr, Cu, Hg, Pb, and Zn) in the center of this area based on multivariate and geostatistical approaches. All analyzed heavy metals were below their background levels, except Cd. The average concentrations of the analyzed elements in topsoil (0-20 cm) were 5.83 mg As kg(-1), 0.21 mg Cd kg(-1), 78.79 mg Cr kg(-1), 21.53 mg Cu kg (-1), 0.049 mg Hg kg(-1), 24.12 mg Pb kg(-1), and 68.5 mg Zn kg(-1). The concentration of As was mostly due to parent materials, whereas the source of Pb was mainly due to vehicle exhaust. The high concentration of Cd was resulted from agricultural practices and parent materials. The concentrations of Cr, Cu, Hg, and Zn were associated with parent materials and human activities.     

Risk assessment and distribution of soil Pb in Guangdong, China

In this study, the spatial distributions of soil lead (Pb) concentration in three horizontal soils in Guangdong, China, were surveyed and analyzed using geostatistics and geography information systems (GIS). Findings indicated that the Pb geometric mean concentration of 23.3 mg/kg in surface soils was found to be higher than those in global soils, which ranged from 2.3–235 mg/kg. In addition, the Pb geometric mean concentrations from A- to C-horizon were found to be 23.3, 27.2, and 28.6 mg/kg, respectively. The classification of a soil Pb environmental risk in an area was likewise presented based on the different levels of environmental quality of Pb and was done by GIS technology. Accordingly, there is a higher local concentration of Pb in the surrounding areas of Guangzhou where there is higher population density and in the north of Guangdong, which is a historic mining area. The results obtained by the environmental risk assessment reveal that about 46% of total surveyed area was above the background value, that is, 2.7% of the total area was at risk of pollution.     

Identification of sources of elevated concentrations of polycyclic aromatic hydrocarbons in an industrial area in Tianjin, China

The concentrations of 16 polycyclic aromatic hydrocarbons (PAHs) were determined by gas chromatography equipped with a mass spectrometry detector in 105 topsoil samples from an industrial area around Bohai Bay, Tianjin in the North of China. Results demonstrated that concentrations of PAHs in 104 soil samples from this area ranged from 68.7 to 5,590 ng g^???1 dry weight with a mean of ∑16PAHs 814 ± 813 ng g^???1, which suggests that there exists mid to high levels of PAH contamination. The concentration of ∑16PAHs in one soil sample from Tianjin Port was exceptionally high (48,700 ng g^???1). Ninety-three of the 105 soil samples were considered to be contaminated with PAHs (>200 ng g^???1), and 25 were heavily polluted (>1,000 ng g^???1). The sites with high PAHs concentration are mainly distributed around chemical industry parks and near highways. Two low molecular weight PAHs, naphthalene and phenanthrene, were the dominant components in the soil samples, which accounted for 22.1% and 10.7% of the ∑16PAHs concentration, respectively. According to the observed molecular indices, house heating in winter, straw stalk combustion in open areas after harvest, and petroleum input were common sources of PAHs in this area, while factory discharge and vehicle exhaust were the major sources around chemical industrial parks and near highways. Biological processes were probably another main source of low molecular weight PAHs.