关于室内装修有害气体烘焙排风稀释技术数值研究

依据实测数据,应用数值计算手法,对烘焙排风稀释技术不同工况下总挥发性有机化合物的排除量、烘焙排风稀释阶段室内空气中总挥发性有机化合物的浓度变化进行计算并讨论烘焙温度、换气次数对去除效果的影响。     

《燃煤二氧化硫排放污染防治技术政策》绩效定量评估

基于全国46个城市(其中38个城市位于"两控区")1996~2005年的面板数据,运用difference-in-differ-ences(DID)模型对《燃煤二氧化硫排放污染防治技术政策》的绩效进行了定量评估。结果表明,该政策的实施对于降低工业二氧化硫排放量起到积极作用,使"两控区"城市年工业二氧化硫的排放量平均降低了19.3%。     

环境约束下大都市城郊土地利用结构评价——基于信息熵和非期望产出模型分析

土地利用过程中会产生期望和非期望产出,针对以往土地利用结构评价中忽略环境产生的非期望产出而影响土地利用结构效率真实性问题,以大都市城郊的上海青浦区为例,宏观上,运用信息熵模型对该区2005~2014年土地利用结构有序性进行评价;微观上,运用非期望产出模型测算青浦区研究期间土地利用结构效率,为寻求区域土地利用结构效率损失的原因及改善途径提供参考。结果表明:(1)2005~2014年青浦区土地利用结构信息熵值时序上呈现"M"形变化趋势,空间上由中部向东西两翼递减;(2)2005~2014年青浦区土地利用结构效率变化趋势在时间序列上呈现"W"形变化趋势,空间上由中部的中心城区向东西两翼递减格局;(3)将环境的负产出纳入非期望产出模型进行土地利用结构效率评价,能更加准确的反映土地利用结构效率的真实性;(4)影响青浦区土地利用结构效率水平变化的主要因素为纯技术效率的变化,资源过度消耗和环境污染物排放过量是制约青浦区土地利用结构效率提升的主要原因。针对土地利用结构效率损失的原因及区域差异提出效率提升途径。研究结果可为青浦区土地利用结构优化和可持续发展提供科学借鉴。     

A new approach to quantify the degradation kinetics of linuron with UV, ozonation and UV/O3 processes

The degradation of linuron, one of phenylurea herbicides, was investigated for its reaction kinetics by different treatment processes including ultraviolet irradiation (UV), ozonation (O₃), and UV/O₃. The decay rate of linuron by UV/O₃ process was found to be around 3.5 times and 2.5 times faster than sole-UV and ozone-alone, respectively. Experimental results also indicate overall rate constants increased exponentially with pH above 9.0 while the increase of rate constants with pH below 9 is insignificant in O₃ system. All dominant parameters involved in the three processes were determined in the assistant of proposed linear models in this study. The approach was found useful in predicting the process performances through the quantification of quantum yield (rate constant for the formation of free radical HOO⁻ from ozone decomposition at high pH), rate constant of linuron with ozone (k_O3,LNR), rate constant of linuron with hydroxyl radical (k_OH,LNR), and α (the ratio of the production rate of OH and the decay rate of ozone in UV/O₃ system).     

Neural network forecasting of air pollutants hourly concentrations using optimised temporal averages of meteorological variables and pollutant concentrations

The new method for the forecasting hourly concentrations of air pollutants is presented in the paper. The method was developed for a site in urban residential area in city of Zagreb, Croatia, for four air pollutants (NO₂, O₃, CO and PM₁₀). Meteorological variables and concentrations of the respective pollutant were taken as predictors. A novel approach, based on families of univariate regression models, was employed in selecting the averaging intervals for input variables. For each variable and each averaging period between 1 and 97 h, a separate model was built. By inspecting values of the coefficient of correlation between measured and modelled concentrations, optimal averaging periods for each variable were selected. A new dataset for building the forecasting model was then calculated as temporal moving averages (running means) of former variables. A multi-layer perceptron type of neural networks is used as the forecasting model. Index of agreement, calculated for the entire dataset including the data for model building, ranged from 0.91 to 0.97 for the respective pollutants. As suggested by the analysis of the relative importance of the input variables, different agreements for different pollutants are likely due to different sources and production mechanisms of investigated pollutants. A comparison of the new method with more traditional method, which takes hourly averages of the forecast hour as input variables, showed similar or better performance. The model was developed for the purpose of public-health-oriented air quality forecasting, aiming to use a numerical weather forecast model for the prediction of the part of input data yet unknown at the forecasting time. It is to expect that longer term averages used as inputs in the proposed method will contribute to smaller input errors and the greater accuracy of the model.     

A review and test of predictive models for the bioaccumulation of radiostrontium in fish

Empirical relations between the ⁹⁰Sr concentration factor (CF) and the calcium concentration in freshwater aquatic systems have previously been determined in studies based on data obtained prior to the Chernobyl accident. The purpose of the present research is to review and compare these models, and to test them against a database of post-Chernobyl measurements from rivers and lakes in Ukraine, Russia, Belarus and Finland. It was found that two independently developed models, based on pre-Chernobyl empirical data, are in close agreement with each other, and with empirical data. Testing of both models against new data obtained after the Chernobyl accident confirms the models’ predictive ability. An investigation of the influence of fish size on ⁹⁰Sr accumulation showed no significant relationship, though the data set was somewhat limited.     

A Sensitivity Analysis of an Integrated Modelling Approach to Assess the Risk of Wind-borne Spread of Foot-and-mouth Disease Virus from Infected Premises

The sensitivity of an integrated model to assess the potential for wind-borne spread of foot-and-mouth disease (FMD) to variations in key parameters controlling different physical and biological processes was evaluated. The estimated number of farms at risk is sensitive to the virus strain used and the accompanying effective contact rate. The C Noville strain increased the estimated number of exposed farms ranked as high and medium risk of being infected by a factor of 5, compared to the baseline, based on the O UKG 2001 strain. The inclusion of a model for biological ageing of the virus can also have a significant effect on the concentration patterns arising from transport and dispersion of the virus. Its inclusion has the practical advantage of markedly reducing the time required for the calculations. The estimated number of farms affected by exposure to high and medium virus concentrations is not grossly sensitive to attenuation caused by temperature or relative humidity effects. Changes in susceptibility to infection, as determined by the parameter θ in the exposure-risk model, does not change the configuration of the virus plumes, but it does change the distribution of farms at risk by risk category. These findings suggest that a good understanding of characteristics (excretion rates from infected animals, susceptibility of different species to infection, virus survival, etc.) of the virus strain involved in an FMD outbreak is necessary to provide a reliable assessment of the risk of wind-borne spread. In the event of an incursion of FMD, provision for laboratory studies on the virus will be an essential component of the disease response and should be factored into contingency plans.

Toluene removal biofilter modeling: Optimization and case study

Based on the model proposed by De Visscher and Van Cleemput for methane oxidation in landfill cover soils, a simulation model for biofiltration of toluene-contaminated air has been developed for biofilters with substrate inhibition. A convenient way to optimize biofilter performance was developed assuming Haldane kinetics. It was calculated that for a typical oilsands operation emitting 200 ton of toluene annually, 90% of the toluene can be removed by a 740 m³ biofilter, if the waste gas sent to the biofilter has a toluene concentration of 2.25 g m⁻³. The optimal initial concentration increases with increasing target efficiency.     

Comparison of models of simazine transport and fate in the subsurface environment in a citrus farm

Contamination of groundwater by agrochemicals is now widely recognized as an extremely important environmental problem. Modern agricultural practices involve the combined use of irrigation with the application of large amounts of agrochemicals to maximize crop yield. Due to flood irrigation and natural runoff, agricultural activities might generate soil, surface water and groundwater contamination problems and leaching of pesticides. Modeling of the transport and fate of pesticides, such as simazine, may help understand the long-term potential risk to the subsurface environment. This paper illustrates a comparative study via the use of three different pesticide transport simulation models and the applicability of those models in determining the groundwater vulnerability to pesticides contamination in a citrus orchard located at the Lower Rio Grande Valley (LRGV). The three models used in the study are the pesticide root zone model-3 (PRZM-3), the pesticide analytical model (PESTAN) and integrated pesticide transport modeling (IPTM). The concentration values obtained from all three models are in agreement, and they show a decreasing trend from the surface through the vadose zone. The problem is how to use this information and, specifically, how to combine the testimony of a number of experts into a single useful judgment. With the aid of the fuzzy multiattribute decision making method, PRZM-3 is deemed as the most promising one for such precision farming applications.