底栖动物对富营养化水体的影响研究

通过室内试验探讨中华圆田螺营养盐释放的温度影响因子对氮磷营养盐循环、水体悬浮物以及摄入量和排泄量的影响等生态特性。研究发现,温度对中华圆田螺营养盐的释放有显著影响。TN和TDN随温度升高呈小幅度增加,TP和TDP则随温度升高呈明显增高,当温度分别由8℃升高至15℃和35℃时,TN则分别增加了5.71%和23.43%,TDN增加6.76%和17.57%;TP则增加92.60%和208.35%,TDP增加2.25%和110.17%。当温度分别由8℃升高至15℃和35℃时,NH4+-N分别增加了1.89%和26.55%,PO4--P增加了14.27%和225.96%,NO3--N则不受温度影响。另外,温度对SS的影响不明显(p>0.05),即使在8℃条件下仍有较高的去除率,为69.50%;试验各个温度下,螺对SS摄食量都大于排泄量,随着时间延长,螺对SS的摄入量有所降低,但仍高于其排泄量。由此可见,底栖软体动物对富营养化水体具有明显的净化作用,为湖泊富营养化控制提供了可供参考的依据。     

应用模糊数学方法评价水环境质量

模糊综合评价就是根据给出的评价标准和实测值,经过模糊变换,对待评价对象给出总的评价的一种方法。在水质评价中,确定评价因子集、评价集、隶属函数,然后通过计算确定水质级别。本文采用模糊综合评价方法,对锦州市大凌河3个断面进行模糊综合评价。     

哈尔滨大气中PAHs污染特征

多环芳烃(PAHs)是大气中广泛存在的一种有毒污染物,因其具有"三致"毒性,已成为关注的焦点。本文通过在哈尔滨市区设置大气采样点,利用大流量主动采样器进行为期一年的大气样品采集,对大气中PAHs的浓度、污染特征进行了研究,并深入探讨了PAHs的污染源和贡献率,结果表明,哈尔滨大气中∑16PAHs浓度范围为6.3～340 ng/m3,平均浓度为100±94 ng/m3,主要以低分子量的PAHs为主。与国内外的研究相比,哈尔滨大气中PAHs的污染处于中等污染水平。PAHs具有明显的季节差异,低温气象条件和排放源的增强是导致冬季PAHs污染加重的主要原因。     

滇池流域城市面源污染控制区划研究

滇池流域点源污染已逐步得到控制,面源污染成为水污染治理的重点。随着流域内城市迅速发展,城市面源污染控制将成为水环境改善的重要瓶颈。结合滇池流域城市发展规划,依据城市下垫面特征,降雨径流污染程度和距离入滇河道远近,将流域内城区划分为重点防控区、中等防控区和一般防控区,其面积百分比分别是17.9%、39.1%和43.0%;重点控制区为昆明市主城区,其次是呈贡新区,并在此基础上提出相应的防治措施。城市面源污染控制区划,对滇池流域面源污染治理具有重要意义。     

潜流人工湿地去除效果研究

在连续运行条件下,采用水平潜流人工湿地净化低浓度的生活污水,考察了其净化效果。结果表明,该系统能够有效的降低生活污水中的COD、TN、TP,适合于城镇生活污水的处理。在0.1、0.2 m3/(m2.d)的水力负荷条件下,系统较容易出现死水区;当0.3 m3/(m2·d)的水力负荷条件下,水流呈推流状态,有效容积和水力效率得到提高,去除率分别为90.3%、86.6%和96.7%。试验表明,适当增加水力负荷,有利于污染物的去除。     

A land use regression model incorporating data on industrial point source pollution

Advancing the understanding of the spatial aspects of air pollution in the city regional environment is an area where improved methods can be of great benefit to exposure assessment and policy support. We created land use regression (LUR) models for SO₂, NO₂ and PM₁₀ for Tianjin, China. Traffic volumes, road networks, land use data, population density, meteorological conditions, physical conditions and satellite-derived greenness, brightness and wetness were used for predicting SO₂, NO₂ and PM₁₀ concentrations. We incorporated data on industrial point sources to improve LUR model performance. In order to consider the impact of different sources, we calculated the PSIndex, LSIndex and area of different land use types (agricultural land, industrial land, commercial land, residential land, green space and water area) within different buffer radii (1 to 20 km). This method makes up for the lack of consideration of source impact based on the LUR model. Remote sensing-derived variables were significantly correlated with gaseous pollutant concentrations such as SO₂ and NO₂. R² values of the multiple linear regression equations for SO₂, NO₂ and PM₁₀ were 0.78, 0.89 and 0.84, respectively, and the RMSE values were 0.32, 0.18 and 0.21, respectively. Model predictions at validation monitoring sites went well with predictions generally within 15% of measured values. Compared to the relationship between dependent variables and simple variables (such as traffic variables or meteorological condition variables), the relationship between dependent variables and integrated variables was more consistent with a linear relationship. Such integration has a discernable influence on both the overall model prediction and health effects assessment on the spatial distribution of air pollution in the city region.     

Experimental study of photooxidation products of ethylbenzene

Smog chamber experiments were performed to investigate the composition of products formed from photooxidation of aromatic hydrocarbon ethylbenzene. Vacuum ultraviolet photoionization mass spectrometer and aerosol time-of-flight mass spectrometer were used to measure the products in the gas and particle phases in real-time. Experimental results demonstrated that ethylphenol, methylglyoxal, phenol, benzaldehyde, and 2-ethylfurane were the predominant photooxidation products in both the gas and particle phases. However, there were some di erences between detected gas phase products and those of particle phase, for example, 2-ethylfurane, ethylglyoxylic acid, nitroethylbenzene, 3,4-dioxopentanal and ethyl-nitrophenol were only existing in the particle-phase. The possible reaction mechanisms leading to these products were also discussed and proposed.     

A land use regression for predicting NO2 and PM10 concentrations in di erent seasons in Tianjin region, China

Land use regression (LUR) model was employed to predict the spatial concentration distribution of NO2 and PM10 in the Tianjin region based on the environmental air quality monitoring data. Four multiple linear regression (MLR) equations were established based on the most significant variables for NO2 in heating season (R2 = 0.74), and non-heating season (R2 = 0.61) in the whole study area; and PM10 in heating season (R2 = 0.72), and non-heating season (R2 = 0.49). Maps of spatial concentration distribution for NO2 and PM10 were obtained based on the MLR equations (resolution is 10 km). Intercepts of MLR equations were 0.050 (NO2, heating season), 0.035 (NO2, non-heating season), 0.068 (PM10, heating season), and 0.092 (PM10, non-heating season) in the whole study area. In the central area of Tianjin region, the intercepts were 0.042 (NO2, heating season), 0.043 (NO2, non-heating season), 0.087 (PM10, heating season), and 0.096 (PM10, non-heating season). These intercept values might imply an area’s background concentrations. Predicted result derived from LUR model in the central area was better than that in the whole study area. R2 values increased 0.09 (heating season) and 0.18 (non-heating season) for NO2, and 0.08 (heating season) and 0.04 (non-heating season) for PM10. In terms of R2, LUR model performed more e ectively in heating season than non-heating season in the study area and gave a better result for NO2 compared with PM10.     

Characterization of personal exposure concentration of fine particles for adults and children exposed to high ambient concentrations in Beijing, China

In China, the health risk from overexposure to particles is becoming an important public health concern. To investigate daily exposure characteristics to PM 2.5 with high ambient concentration in urban area, a personal exposure study was conducted for school children, and office workers in Beijing, China. For all participants (N = 114), the mean personal 24-hr exposure concentration was 102.5, 14.7, 0.093, 0.528, 0.934, 0.174 and 0.703 μg/m 3 for PM 2.5 , black carbon, Mn, Al, Ca, Pb, and Fe. Children's exposure concentrations of PM 2.5 were 4-5 times higher than those in related studies. The ambient concentration of PM 2.5 (128.5 μg/m 3 ) was significantly higher than the personal exposure concentration (P 0.05), and exceed the reference concentration (25 μg/m 3 ) of WHO air quality guideline. Good correlation relationships and significant differences were identified between ambient concentration and personal exposure concentration. The relationships indicate that the ambient concentration is the main factor influencing personal exposure concentration, but is not a good indicator of personal exposure concentration. Outdoor activities (commute mode, exposure to heating, workday or weekend travel) influenced personal exposure concentrations significantly, but the magnitude of the influence from indoor activities (exposure to cooking) was masked by the high ambient concentrations.     

生态修复水生植物根际氨氧化细菌的研究

为研究水生植被恢复对底泥氨氧化细菌(ammonia-oxidizing bacteria,AOB)种群的影响,选取在生态修复中广泛使用的4种水生植物,芦苇(Phragmites communis)、窄叶香蒲(Typha angustifolia L.)、菹草(Potamogeton crispus L.)和荇菜(Limnanthemun nymphoides),采用最大可能数法(most pmbable number,MPN)计数AOB的数量,巢式聚合酶链式反应-变性梯度凝胶电泳(nested polymerase chain reaction-denaturing gradienl gel electmphoresis,nested PCR-DGGE)及条带回收测序的方法分析AOB的主要种类.结果显示,水生植物根际AOB密度显著高于无水生植物的表层底泥,而芦苇(2.8×105cells/g)和菖蒲(4.3×10'celts/g)又明显高于菹草(9.3 x 104cells/g)和荇菜(7.7×104 cells/g).水生植物根际呈氧化环境,而NH 4的浓度低于无水生植物的对照区.DNA测序结果显示尽管不同植物根际AOB主要种类有所区别,但基本属于亚硝化单胞菌属(Nitrosomonas).此类微生物群落在水生植物根际的聚集对促进生态修复中N元素的循环具有重要作用.