青海省洪水变化情况的研究

为了研究青海省洪水变化情况,搜集了青海省内43个水文站的相关数据,其中选取具有长期观测资料的32个水文站资料,采用P-Ⅲ曲线作为其理论频率曲线,并与各站自建站-1974年和建站-2008年的水文计算成果进行比较,结果表明青海省水情发生了较大的变化,且在各水文分区的变化也不相同。     

基于超低电容特性的微尘在线监测技术研究

为了更有效地测量工业烟尘排放浓度,研究了一种电容特性的微尘在线监测技术,利用电容传感器输出电压来反映粉尘质量。介绍了电容法测量粉尘量的原理、测量系统组成等,研究了粉尘质量与电容传感器输出电压的关系。对5种不同粉尘的测量结果进行分析表明,粉尘质量与电容传感器输出电压之间存在着一定的比例关系,其相关系数高达0.99。同时进行了微尘在线测量的研究,并采用电容特性曲线对测量系统进行了标定,从而验证了电容法在线微尘监测的可行性。     

论环境监测过程中的质量保证工作

介绍了环境监测工作中常用的质量控制方法。认为应通过质量控制工作,使监测数据符合五性：代表性、准确性、精密性、可比性、完整性。     

环保企业应收账款和信用管理浅析

针对环境保护企业财务管理中的应收账款和信用管理现状,重点分析了环保企业应收账款的管理方式,通过对模型流程的建立,采用数据挖掘处理技术来有效解决环保企业应收账款信用的分析判断,提高环保企业应收账款财务的整体管理水平。对于提高环保行业的整体良性发展具有借鉴意义。     

基于熵权的改进密切值法在地面水水质评价中的应用

为了简化传统密切值法运算,更能全面客观地反映出各样本的优劣情况,尝试采用目标差值率法进行初始矩阵的规范化处理,引入熵权法确定各评价指标的权重,对传统密切值法进行了改进.通过将两种不同密切值法对某区域水体水质的评价结果进行对比表明: 两种密切值法评价水质得出了一致的水质优劣排序,但改进后的密切值法可以有效地消除各评价指标在量纲、数量级及指标优劣等方面的差异,计算更简便; 改进后的密切值法利用熵权法确定各评价指标的权重,更客观; 改进后的密切值法评价结果中各样本的差异性放大了,对比更为明显.     

Spatial distribution of aerosol pollution based on MODIS data over Beijing, China

With the help of regression analysis,the relationships were detected between aerosol's contribution to apparent reflectance(ACR) derived from Moderate Resolution Imaging Spectroradiometer(MODIS)on board Terra and hourly PM_(10)mass concentration measured at 30 ground-based locations in Beijing for the August of 2003 and 2004.It was shown that there was a good correlation between the ACR and PM_(10)(linear correlation coefficient,R=0.56).On the basis of this relationship,spatial distribution and possible sources of PM_(10)derived from MODIS were analyzed and two frequently heavily-polluted regions were found,namely downtown of the city and the district near Xishan Mountain.These two regions coincidently are also urban heat island centers.The foundings of this paper will be greatly useful for environmental monitoring and urban planning for Beijing,especially for the 2008 Olympic game to be held in Beijing.     

Artificial neural network model for identifying taxi gross emitter from remote sensing data of vehicle emission

Vehicle emission has been the major source of air pollution in urban areas in the past two decades. This article proposes an artificial neural network model for identifying the taxi gross emitters based on the remote sensing data. After carrying out the field test in Guangzhou and analyzing various factors from the emission data, the artificial neural network modeling was proved to be an advisable method of identifying the gross emitters. On the basis of the principal component analysis and the selection of algorithm and architecture, the Back-Propagation neural network model with 8-17-1 architecture was established as the optimal approach for this purpose. It gave a percentage of hits of 93%. Our previous research result and the result from aggression analysis were compared, and they provided respectively the percentage of hits of 81.63% and 75%. This comparison demonstrates the potentiality and validity of the proposed method in the identification of taxi gross emitters.     

Residual dynamics of thiacloprid in medical herbs marjoram, thyme, and camomile and in soil

Thiacloprid is a new insecticide of the chloronicotinyl family. To assess its risk after application, residual characteristics of thiacloprid in marjoram, thyme, and camomile and in soil were studied under field conditions. The active ingredient was extracted from the plant material using a mixture of acetone-water. After filtration, the extract was concentrated to the aqueous phase, diluted with water, and portioned against ethyl acetate on a matrix solid phase dispersion column. Thiacloprid was extracted from soil using a mixture of methanol-water, filtered, and re.extracted （clean up） with dichloromethane. The residues were quantified using HPLC-MS-MS. The methods were validated by recovery experiments. Thiacloprid residues in marjoram, thyme, and camomile and in soil persisted beyond 10, 14, 14, and 21 d but no residues were detected after 14, 21, 21, and 28 d, respectively. The data obtained in this study indicated that the biexponential model is more suitable than the first-order function to describe the decline of thiacloprid in fresh marjoram, fresh thyme, and dried camomile flowers with half-life （t1/2） of 1.1, 0.7, and 1.2 d, respectively. However, both the first-order function and biexponential model were found to be applicable for dissipation of thiacloprid in soil with almost the same t1/2 values of 3.5 and 3.6 d. The results indicated that thiacloprid dissipates rapidly and does not accumulate in the tested herbs and in soil.     

Heavy metal availability and impact on activity of soil microorganisms along a Cu/Zn contamination gradient

All the regulations that define a maximum concentration of metals in the receiving soil are based on total soil metal concentration. However, the potential toxicity of a heavy metal in the soil depends on its speciation and availability. We studied the effects of heavy metal speciation and availability on soil microorganism activities along a Cu/Zn contamination gradient. Microbial biomass and enzyme activity of soil contaminated with both Cu and Zn were investigated. The results showed that microbial biomass was negatively affected by the elevated metal levels. The microbial biomass-C （Cmic）/organic C （Corg） ratio was closely correlated to heavy metal stress. There were negative correlations between soil microbial biomass, phosphatase activity and NH4NO3 extractable heavy metals. The soil microorganism activity could be predicted using empirical models with the availability of Cu and Zn. We observed that 72% of the variation in phosphatase activity could be explained by the NH4NO3-extractable and total heavy metal concentration. By considering different monitoring approaches and different viewpoints, this set of methods applied in this study seemed sensitive to site differences and contributed to a better understanding of the effects of heavy metals on the size and activity of microorganisms in soils. The data presented demonstrate the relationship between heavy metals availability and heavy metal toxicity to soil microorganism along a contamination gradient.     

Anaerobic tapered fluidized bed reactor for starch wastewater treatment and modeling using multilayer perceptron neural network

Anaerobic treatability of synthetic sago wastewater was investigated in a laboratory anaerobic tapered fluidized bed reactor(ATFBR) with a mesoporous granular activated carbon(GAC)as a support material.The experimental protocol was defined to examine the effect of the maximum organic loading rate(OLR),hydraulic retention time(HRT),the efficiency of the reactor and to report on its steady- state performance.The reactor was subjected to a steady-state operation over a range of OLR up to 85.44 kg COD/(m~3.d).The COD removal efficiency was found to be 92% in the reactor while the biogas produced in the digester reached 25.38 m~3/(m~3·d) of the reactor. With the increase of OLR from 83.7 kg COD/(m~3.d),the COD removal efficiency decreased.Also an artificial neural network(ANN) model using multilayer perceptron(MLP)has been developed for a system of two input variable and five output dependent variables. For the training of the input-output data,the experimental values obtained have been used.The output parameters predicted have been found to be much closer to the corresponding experimental ones and the model was validated for 30% of the untrained data.The mean square error(MSE)was found to be only 0.0146.