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.     

Variation of soil fertility and carbon sequestration by planting Hevea brasiliensis in Hainan Island, China

The development of rubber industry depends on the sustainable management of rubber plantation. To evaluate the environmental effects of planting Hevea brasiliensis on a subsystem of tropical forest ecosystem, the variation of soil fertility and carbon sequestration under rubber plantation within 30-year life period were investigated in Hainan Island. Results showed that （1） with the increase of stand age of rubber plantation, soil fertility decreased all along. From 1954 to 1995, soil organic matter, total N, available K and available P decreased by 48.2%, 54.1%, 56.7% and 64.1%, respectively. （2） If the complete return of litters was considered without additional fertilizer application to the soil of the rubber plantations, the consumption periods for P, N, K, Mg were only 825 years, 329 years, 94 years and 65 years, respectively~ To improve soil fertility is essential for rubber plantation development. （3） The C sequestration of rubber trees per hectare accounts for 272.08 t within 30-year life period and 57.91% of them was fixed in litters. In comparison with C sequestration by rain forest （234.305 t/hm^2） and by secondary rain forest （150.203 t/hm^2）, rubber forest has more potentials for C fixation. On the base of above results, the following measures would benefit the maintenance of soil fertility and the development of rubber industry, including applying fertilizer to maintain the balance of soil nutrients, intercropping leguminous plant to improve soil fertility, reducing the collection of litters, optimizing soil properties to improve element P availability such as applying CaCO3. The information gathered from the study can be used as baseline data for the sustainable management of rubber plantation elsewhere.     

企业风险管理与经营效率：来自中国保险业的经验证据

本文从风险管理的视角对企业效率评估的数据包络分析技术进行了改进,探讨了风险管理与经营效率的内在关联,并以中国保险业为例,对1999年以来企业真实的经营效率水平进行了评估。结果表明：企业内部的风险管理能力对其经营效率水平的提升具有明显的影响,而且这种影响力正在逐渐加强。不考虑企业内部的风险管理水平将直接导致其经营效率的测算结果出现低估,2002年以后这种低估的程度越发明显,这可归因于同期保险企业开始逐渐重视提高自身的风险管理能力。以上结论也为企业如何在管控风险的同时提升经营效率水平提供了有价值的指导。     

污水处理厂数据采集系统的设计与应用

以贵州某污水处理厂数据采集系统为例．介绍vXPLC和C≠≠为核心的数据采集系统的构成,通信网络的选型和总体设计思路,以及PLC和C#在该污水处理厂中的成功应用。     

VBA在环境监测数据统计中的应用

VBA是Office系列软件内嵌的通用编程语言,用于定制和扩展Office的功能。将VBA应用在环境监测数据统计中,并以功能区噪声等效声级日期筛选为例,通过编制宏代码,方便快捷地实现功能区噪声数据的自动筛选。     

加速腐蚀环境下LD2CS铝合金腐蚀损伤分析方法

目的研究LD2CS铝合金腐蚀损伤数据的分析方法。方法针对LD2CS铝合金腐蚀坑深度值,采用最小二乘支持向量机、BP人工神经网络和求和自回归移动平均等3种模型进行回归和预测分析。对比总结各种模型在小样本递增时间序列下的应用特点。结果对于LD2CS铝合金腐蚀坑深度值预测,最小二乘支持向量机在回归和预测上都有较高的精度。结论最小二乘支持向量机模型最适合LD2CS铝合金的腐蚀坑深度值预测。