Teja Dharmasanam Ravi, Gupta Suyog, Yadav Brahmdeo, Gupta Sunil Kumar
Department of Environmental Science and Engineering, Indian Institute of Technology (Indian School of Mines), Dhanbad, 826004, India.
Department of Civil Engineering, Birsa Institute of Technology Sindri, Dhanbad, 828123, India.
Environ Sci Pollut Res Int. 2023 Jan;30(2):4949-4958. doi: 10.1007/s11356-022-22556-1. Epub 2022 Aug 17.
The fuzzy leachate pollution index (FLPI) was established to classify the landfill sites on the basis of their leachate pollution potential by considering the limitations of traditional methods. The FLPI was developed adopting 9 critical input parameters, i.e., TDS, pH, Cl, Cu, Pb, Cr, Zn, BOD, and COD, from 22 major landfill sites across India. Using these critical parameters, 3 groups, i.e., inorganic leachate strength (INLS), organic leachate strength (ORLS), and heavy metal leachate strength (HMLS), were generated to estimate the FLPI. The regression analysis, ANOVA, and sensitivity analysis were also performed to determine the significance and uncertainty of the index. The results showed that among all MFs, the triangular with overlapping open ends (TOO) MF was best fitted (R = 0.90) for FLPI estimation. Accordingly, 41% of the landfill sites showed less treatment while the others (59%) required moderate degree of treatment. The regression (R = 0.92) and ANOVA (F value = 15.003, p = 0.000031) analyses described that the developed tool was significant (p < 0.05). The sensitivity analysis showed that Zn (R = 0.99) was the most influencing factor followed by BOD > COD > pH > Cr > Cu > Cl > Pb > TDS. The study provides an important tool that can also be used by researchers and scientists for investigating and evaluating various environmental problems.
考虑到传统方法的局限性，建立了模糊渗滤液污染指数（FLPI），以便根据垃圾填埋场的渗滤液污染潜力对其进行分类。FLPI是采用印度22个主要垃圾填埋场的9个关键输入参数（即总溶解固体（TDS）、pH值、氯离子（Cl）、铜（Cu）、铅（Pb）、铬（Cr）、锌（Zn）、生化需氧量（BOD）和化学需氧量（COD））开发的。利用这些关键参数，生成了3组数据，即无机渗滤液强度（INLS）、有机渗滤液强度（ORLS）和重金属渗滤液强度（HMLS），以估算FLPI。还进行了回归分析、方差分析和敏感性分析，以确定该指数的显著性和不确定性。结果表明，在所有隶属函数中，具有重叠开口端的三角形（TOO）隶属函数最适合FLPI估算（R = 0.90）。因此，41%的垃圾填埋场显示处理程度较低，而其他垃圾填埋场（59%）需要中等程度的处理。回归分析（R = 0.92）和方差分析（F值 = 15.003，p = 0.000031）表明，所开发的工具具有显著性（p < 0.05）。敏感性分析表明，锌（R = 0.99）是最具影响的因素，其次是生化需氧量 > 化学需氧量 > pH值 > 铬 > 铜 > 氯离子 > 铅 > 总溶解固体。该研究提供了一个重要工具，研究人员和科学家也可利用它来调查和评估各种环境问题。
