An Interval-Parameter Waste-Load-Allocation Model for River Water Quality Management Under Uncertainty

A simulation-based interval quadratic waste load allocation (IQWLA) model was developed for supporting river water quality management. A multi-segment simulation model was developed to generate water-quality transformation matrices and vectors under steady-state river flow conditions. The established matrices and vectors were then used to establish the water-quality constraints that were included in a water quality management model. Uncertainties associated with water quality parameters, cost functions, and environmental guidelines were described as intervals. The cost functions of wastewater treatment units were expressed in quadratic forms. A water-quality planning problem in the Changsha section of Xiangjiang River in China was used as a study case to demonstrate applicability of the proposed method. The study results demonstrated that IQWLA model could effectively communicate the interval-format uncertainties into optimization process, and generate inexact solutions that contain a spectrum of potential wastewater treatment options. Decision alternatives can be generated by adjusting different combinations of the decision variables within their solution intervals. The results are valuable for supporting local decision makers in generating cost-effective water quality management strategies.     

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 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).     

Process design optimization and risk analysis

Hazard identification and risk assessment are key aspects in process plant design. They are often applied in the final stages of the process at whatever the cost, unless financial constraints are imposed. However, a much better solution would be to introduce risk analysis earlier by including it in earlier stages of the design process, such as when the cost of a plant and the cost of any accidents that may occur are estimated. In this paper, an optimization methodology is proposed, in which both cost and risk (with a deterministic approach) are taken into account, to improve on the current situation. If a decision variable is chosen, an objective function will be established that makes it possible to analyze variations in overall costs, including the cost of the investment and the cost of accidents. This leads to an optimum situation in which costs are kept to a minimum. Of course, this optimization is subject to constraints, the greatest of which is the fact that risk must not exceed tolerated threshold levels. The procedure is explained and two examples, one involving a toxic release and the other a BLEVE/fireball, are used to illustrate it.     

中国工业碳排放达峰的情景预测与减排潜力评估

实现2030年碳排放达峰不仅是中国为应对全球气候变化向国际社会做出的郑重承诺,也是中国未来经济结构转型与可持续发展的必然选择。基于中国实现2030年碳排放达到峰值的宏观目标为背景,本文以中国碳排放的主要行业工业为研究对象,首先运用拓展的STIRPAT模型对工业及其9个细分行业的碳排放达峰进行了情景预测,然后基于公平和效率的双重视角对工业细分行业的减排潜力进行评估。研究表明:(1)仅有低碳情景和抑制排放情景2可以实现中国碳排放2030年达峰,低碳情景是实现中国工业碳排放达峰的最佳发展模式,达峰时间最早(2030年),峰值最低(140.43亿t)。激进排放情景则是最差的发展模式,达峰时间最晚(2036年),峰值也最高(150.09亿t)。(2)工业内部各细分行业碳排放的最优达峰情景差别较大。建材和纺织制造业能够实现提前达峰,可以在这类行业率先实施达峰管理措施,使其带动其他行业陆续达峰。(3)最具减排潜力的行业是石油制造业,其次是电力行业,这些减排潜力较大的行业应该成为国家节能减排的重点对象。(4)基于工业各细分行业在减排公平性和效率性上的差异将工业9个细分行业分为四类。其中,石油、钢铁制造业和电力行业属于"高效高公平行业";化工、建材制造业属于"低效高公平行业";采掘业属于"高效不公平行业";纺织、轻工和机电制造业属于"低效不公平行业"。中国应针对不同类型的行业制定出相应的减排战略,将减排重点放在各行业最具潜力的方面。最后,文章对实现中国工业碳排放达峰管理提出了几点政策建议。     

秦皇岛市“创模”对策研究及效益分析

介绍了秦皇岛市创建国家环境保护模范城市的意义,重点阐述了完成创模任务的主要对策,包括:构建以旅游业为中心、特色产业互融互促的现代产业体系;加快城乡一体化建设;提升城镇发展质量和水平;加强重大基础设施建设;积极推广清洁能源,深入开展工程节能;积极推进循环经济发展等。秦皇岛市创建国家环境保护模范城市,将会在环境、经济和社会三方面产生明显的综合效益。     

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.     

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.     

B—P网络逐步聚类法在环境测点优选中的应用

将Ｂ－Ｐ网络原理与逐步聚类分析思想相结合,用于环境测点聚类优选。该方法用于水清河几个监测断面的优选结果是符合客观实际的。     

IFTCIP: An Integrated Optimization Model for Environmental Management under Uncertainty

In this study, an interval-fuzzy two-stage chance-constrained integer programming (IFTCIP) method is developed for supporting environmental management under uncertainty. The IFTCIP improves upon the existing interval, fuzzy, and two-stage programming approaches by allowing uncertainties expressed as probability distributions, fuzzy sets, and discrete intervals to be directly incorporated within a general mixed integer linear programming framework. It has advantages in uncertainty reflection, policy investigation, risk assessment, and capacity-expansion analysis in comparison to the other optimization methods. Moreover, it can help examine the risk of violating system constraints and the associated consequences. The developed method is applied to the planning for facility expansion and waste-flow allocation within a municipal solid waste management system. Violations of capacity constraints are allowed under a range of significance levels, which reflects tradeoffs between the system cost and the constraint-violation risk. The results indicate that reasonable solutions for both binary and continuous variables have been generated under different risk levels. They are useful for generating desired decision alternatives with minimized system cost and constraint-violation risk under various environmental, economic, and system-reliability conditions. Generally, willingness to take a higher risk of constraint violation will guarantee a lower system cost; a strong desire to acquire a lower risk will run into a higher system cost.