基于模糊理论的重金属浸出行为研究及潜在风险评价

发布时间：2018-06-29 23:20

本文选题：城市生活垃圾焚烧(MSWI) + 重金属　；参考：《河北工程大学》2015年硕士论文

【摘要】：随着世界经济的高速发展,人们生活水平快速提高,生活垃圾逐日累增。垃圾焚烧以其占地面积小、减量化显著、无害化彻底以及其能量可再利用等优点,已成为生活垃圾减量化、无害化、资源化的有效处理方式。但垃圾焚烧所产生的灰渣中,残留并富集绝大部分的重金属。重金属会通过生态环境和生物累积双重作用下迁移转化,最终通过各个途径进入人体内,而且重金属对人体的危害极大。研究重金属在浸出过程中的行为,并对环境的潜在生态风险评价,具有重要的意义。灰渣中的重金属在填埋场内发生迁移转化会受多种因素综合作用,其溶解和释放过程非常缓慢,且所得实测样本数据非常有限。当样本为小样本时,直接利用样本数据进行预测或求解指标值会增大误差,降低精度,导致结果的模糊和不确定,而模糊理论在解决具有模糊不确定性的问题方面有着较为明显的优势。本文详细介绍了模糊理论,在分析小样本问题的基础上。采用模糊C均值聚类算法,结合线性方程组对小样本数据进行扩充。在经数据处理后对新样本模糊处理,将隶属度作为拟合重金属浸出行为趋势线的权重值。该方法仿真结果与Visual MINTEQ模型计算的结果及实测数据拟合结果进行比较,说明该方法具有更好的诠释作用,可靠性更高。由于重金属难以降解,重金属的浸出行为,会导致地下水水体、空气,以及周边土壤的重金属污染,从而对人类、动植物等产生持续的潜在风险。对重金属污染风险准确评价有助于灰渣的安全处置和再利用,也为制定合理的土壤修复计划和防止控制填埋场污染奠定基础。本文将模糊专家系统引入潜在生态风险评价中,将重金属的富集系数作为输入,重金属对环境的潜在风险作为输出。在专家系统的基础之上对系统的知识库和推理机制进行了模糊算法的处理,应用模糊规则的方法来实现重金属对环境危害快速、不确定信息的准确推理。结果验证该方法能够更快速、准确地做出适当的决定,为重金属对环境的潜在生态风险作出评价。
[Abstract]:With the rapid development of the world economy, people's living standard improves rapidly. MSW incineration has become an effective disposal method for MSW with its advantages of small occupation area, remarkable reduction, complete innocuity and reutilization of energy, and so on. However, most of the heavy metals are left and enriched in the ash produced by MSW incineration. Heavy metals can be transported and transformed through ecological environment and bioaccumulation, and eventually enter into human body through various ways, and the harm of heavy metals to human body is great. It is of great significance to study the behavior of heavy metals in leaching process and to evaluate the potential ecological risk of the environment. The migration and transformation of heavy metals in the ash in the landfill site will be affected by a variety of factors, the dissolution and release process is very slow, and the measured sample data are very limited. When the sample is a small sample, using the sample data directly to predict or solve the index value will increase the error, reduce the precision, and lead to the ambiguity and uncertainty of the result. The fuzzy theory has obvious advantages in solving the problem with fuzzy uncertainty. This paper introduces the fuzzy theory in detail, on the basis of analyzing the small sample problem. The fuzzy C-means clustering algorithm is used to extend the small sample data with linear equations. After the data processing, the membership degree is taken as the weight value to fit the trend line of heavy metal leaching. The simulation results of this method are compared with the results of Visual MINTEQ model and the fitting results of measured data. It shows that the method has better interpretation function and higher reliability. Because heavy metals are difficult to degrade, heavy metal leaching will lead to heavy metal pollution in groundwater, air and surrounding soil, which will cause persistent potential risks to human beings, animals and plants and so on. The accurate assessment of heavy metal pollution risk is not only helpful to the safe disposal and reuse of ash, but also to the establishment of a reasonable soil remediation plan and the prevention and control of landfill pollution. In this paper, the fuzzy expert system is introduced into the potential ecological risk assessment. The enrichment coefficient of heavy metals is taken as the input and the potential risk of heavy metals to the environment is taken as the output. On the basis of expert system, the knowledge base and reasoning mechanism of the system are processed by fuzzy algorithm. The method of fuzzy rules is applied to realize the accurate reasoning of heavy metals' harm to the environment and uncertain information. The results show that this method can make appropriate decisions more quickly and accurately and evaluate the potential ecological risk of heavy metals to the environment.
【学位授予单位】：河北工程大学
【学位级别】：硕士
【学位授予年份】：2015
【分类号】：X508;X820.4

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