Development and field validation of an indicator to assess the relative mobility and risk of pesticides in the Lourens River catchment,South Africa

A GIS based pesticide risk indicator that integrates exposure variables (i.e. pesticide application, geographic, physicochemical and crop data) and toxicity endpoints (using species sensitivity distributions) was developed to estimate the Predicted Relative Exposure (PREX) and Predicted Relative Risk (PRRI) of applied pesticides to aquatic ecosystem health in the Lourens River catchment, Western Cape, South Africa. Samples were collected weekly at five sites from the beginning of the spraying season (October) till the beginning of the rainy season (April) and were semi quantitatively analysed for relevant pesticides applied according to the local farmers spraying programme. Monitoring data indicate that physicochemical data obtained from international databases are reliable indicators of pesticide behaviour in the Western Cape of South Africa. Sensitivity analysis identified K_OC as the most important parameter influencing predictions of pesticide loading derived from runoff. A comparison to monitoring data showed that the PREX successfully identified hotspot sites, gave a reasonable estimation of the relative contamination potential of different pesticides at a site and identified important routes of exposure (i.e. runoff or spray drift) of different pesticides at different sites. All pesticides detected during a monitored runoff event, were indicated as being more associated with runoff than spray drift by the PREX. The PRRI identified azinphos-methyl and chlorpyrifos as high risk pesticides towards the aquatic ecosystem. These results contribute to providing increased confidence in the use of risk indicator applications and, in particular, could lead to improved utilisation of limited resources for monitoring and management in resource constrained countries.     

Artificial neural network based carbon monoxide persistence models for episodic urban air quality management

This paper describes the development of artificial neural network (ANN) based carbon monoxide (CO) persistence (ANNCOP) models to forecast 8-h average CO concentration using 1-h maximum predicted CO data for the critical (winter) period (November–March). The models have been developed for three 8-h groupings of 10 p.m. to 6 a.m., 6 a.m. to 2 p.m. and 2–10 p.m., at two air quality control regions (AQCRs) in Delhi city, representing an urban intersection and an arterial road consisting heterogeneous traffic flows. The result indicates that time grouping of 2–10 pm is dominantly affected by inversion conditions and peak traffic flow. The ANNCOP model corresponding to this grouping predicts the 8-h average CO concentrations within the accuracy range of 68–71%. The CO persistence values derived from ANNCOP model are comparable with the persistence values as suggested by the Environmental Protection Agency (EPA), USA. This work demonstrates that ANN based model is capable of describing winter period CO persistence phenomena.     

SAMPLING FRAME FOR IMPROVING PEBBLE COUNT ACCURACY IN COARSE GRAVEL‐BED STREAMS1

ABSTRACT: Improved sampling techniques are needed to increase the accuracy of pebble‐count particle‐size distributions used for stream studies in gravel‐bed streams. However, pebble counts are prone to operator errors introduced through subjective particle selection, serial correlation, and inaccurate particle‐size measurements. Errors in particle‐size measurements can be minimized by using a gravel template. Operator influence on particle selection can be minimized by using a sampling frame, 60 by 60 cm, in which sampling points are identified by the cross points of thin elastic bands. Serial correlation can be minimized by adjusting the spacing between the cross points and setting it equal to the dominant large particle size (=D₉₅). In a field test in a cobble‐bed stream, the sampling frame developed in this study produced slightly coarser size distributions, particularly in the cobble range, than the traditional heel‐to‐toe walk that selects particles with a blind touch at the tip of the boot. The sampling frame produced more similar sampling results between two operators than heel‐to‐toe walks. The difference between the two sampling methods is attributed to an unbiased selection of fine and coarse particles when using the sampling frame.     

Utilization of Photographs for Determining Impact Indicators for Trail Management

Indicators are a key component of resource management, but selecting them can be difficult and controversial. This study explores different methods for selecting impact indicators for management of trail conditions by comparing photo survey methods (PSM) with written survey methods (WSM). A total of 661 subjects participated in interviews conducted within Mudeung- Mountain Provincial Park in Kwang-ju, Korea. PSM explained variation in acceptability better than WSM. Six major photo components (in order of importance: area of large rocks on trail, area of wood steps, area of bare roots, area of bare soil, area of small stones, and area of stone steps) explained 84.7% of the variation in acceptability of trail management conditions. This study suggests that PSM can be a useful tool for selecting impact indicators. Supported by the grant of Post-Doctoral Program, Chonbuk National University (2001)     

基于结构方程的旅游环境承载系统耦合关联与作用机理

构建旅游环境承载力评价体系,运用耦合度指数和结构方程模型揭示山东半岛蓝色经济区旅游环境承载系统的耦合演化规律和动态关联特征.研究表明,半岛蓝色经济区7市各子系统的承载指数均呈增长态势,各承载子系统之间存在耦合作用,协调发展水平均稳步上升,生态承载子系统对经济承载子系统产生正影响,社会承载子系统可通过生态承载子系统对经济承载子系统产生正向影响力.     

Exergetic Sustainability Indicators as a Tool in Commercial Aircraft: A Case Study for a Turbofan Engine

This paper focuses on the exergetic sustainability indicators of a medium-range commercial aircraft engine for constant reference environment and ground running conditions. First, a detailed exergy analysis of turbofan engine have been performed based on engine test cell parameters. Starting from the sustainability considerations and the second law of the thermodynamics, the paper presents six exergy-based sustainability indicators. The indicators of the turbofan engine developed here in conjunction with exergetic analysis and sustainable development are exergy efficiency, waste exergy ratio, exergy destruction factor, recoverable exergy rate, environmental effect factor, and exergetic sustainability index. The investigated sustainable indicators have been calculated by using exergy analysis outputs for aircraft ground running condition. Results from this study show that values of exergy efficiency, waste exergy ratio, exergy destruction factor, recoverable exergy rate, environmental effect factor, and exergetic sustainability index of investigated turbofan engine are found to be 0.315, 0.685, 0.408, 0, 2.174, and 0.460, respectively. These parameters are expected to quantify how the turbofan engine and aircraft become more environmentally benign and sustainable.     

安徽省省内人口流动空间选择研究

安徽省省内流动人口空间选择主要体现为省会优先、邻近区域优先和高工资区域优先的特征。省内形成以首府合肥为第一层次,以芜湖和淮南为第二层次,以蚌埠、淮北、安庆、马鞍山和铜陵为第三层次,其余城市为第四层次的空间选择格局。合肥是省内人口流入最大的辐合场,淮南、芜湖是次级辐合场,淮北、淮南、六安、巢湖等城市是对流场,流入人口规模与流出人口规模大体相当。     

炼化废水絮凝剂筛选实验

中国石油大连石化公司的生产废水不仅具有炼化废水的复杂性,而且其中含有大量的氯离子,给絮凝药剂的筛选带来一定的困难。通过对715、728两种絮凝药剂的现场应用实验,找出了不同水质情况下的最佳投药量。实验结果表明,当污水中含油量大于100mg/L时,715药剂加入量控制在150～180mg/L,728的加入量为4mg/L,此时油、SS、COD、浊度的去除率分别为92%、41%、41%和82%。当污水含油量在30mg/L以下时,715药剂加入量为90～120mg/L,728加入量为2.7～3.3mg/L,此时油、SS、COD、浊度的去除率分别为74%、71%、38%和89%。经实验筛选出的这两种药剂可以利用现有的加药系统设备加入污水,加药处理后能提高出水的水质。     

PROCEDURES FOR THE EVALUATION OF ENGINEERING ALTERNATIVES1

ABSTRACT: This paper describes a method of analyzing the nonquantifiable parameters which should be considered in the evaluation of engineering alternatives. The nonquantifiable parameters can include environmental impact, feasibility of implementation, and performance. The method considers rating all the alternatives on the basis of a set of criteria which reflect these parameters. A procedure is discussed for obtaining review and guidance in the evaluation of engineering alternatives from the local elected officials or governing bodies and for obtaining the views and desires of the local communities. This is achieved through the formation of project review committees and an evaluation procedure which allows for the technical rating of alternatives by the engineer and the weighing of the evaluation criteria by the political and social groups. With the growing environmental concern and the high cost of engineering projects, the involvement of the public during the evaluation of engineering projects is becoming increasingly important to the final success of the project.     

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.