Fuzzy Assessment of Heavy Metal Pollution
محورهای موضوعی : مجله بین المللی ریاضیات صنعتی
Gh. Hesamian
1
(Department of Statistics, Payame Noor University, Tehran, Iran.)
M. G. Akbari
2
(Department of Mathematical Sciences, University of Birjand, Birjand, Iran.)
M. Shams
3
(Department of Statistics, Faculty of Mathematical Sciences, University of Kashan, Kashan, Iran.)
کلید واژه: Fuzzy contamination, Triangular fuzzy number, Degree of belonging, Fuzzy pollution criterion,
چکیده مقاله :
The present work is aimed to extend the common pollution indices into the fuzzy environment. For this purpose, a method was developed for converting the heavy metal contamination in soil by fuzzy numbers. Then, the most commonly used pollution indices are defined as fuzzy numbers by applying the alpha-cuts approach. To evaluate the degree of heavy metal contamination in a specific level, a degree of belonging was also suggested.
هدف این مقاله تعمیم شاخصهای آلودگی و تفسیر آنها به محیط فازی است. برای این منظور، ابتدا میزان فلزات سنگین در خاک توسط اعداد فازی اندازه گیری شدند. سپس، رایجترین شاخصهای آلودگی را با استفاده از روش آلفا-برش‌ها توسط اعداد فازی تعریف شدند. برای ارزیابی میزان آلودگی فلزات سنگین در یک سطح خاص، درجهای از تعلق نیز پیشنهاد شد. در نهایت، روش پیشنهادی با یک مثال کاربردی مورد بررسی و تحلیل قرار گرفت.
[1] G. M. S. Abrahim, Holocene sediments of Tamaki Estuary: Characterization and impact of recent human activity on an urban estuary in Auckland,New Zealand, PhD Thesis University of Auckland, Auckland (New Zealand), (2005).
[2] A. S. Ayangbenro, O. O. Babalola, A new strategy for heavy metal polluted environments: A review of microbial biosorbents, International Journal of Environmental Research and Public Health 14 (2017) 97-109.
[3] Z. Bien, K. C. Min, Fuzzy logic and its applications to engineering, information sciences, and intelligent systems, Kluwer Academic Publishers, Norwell, MA, USA, (1995).
[4] M. Brown, C. Harris, Neurofuzzy adaptive modelling and control, Prentice Hall, New York, (1994).
[5] A. Buccolieri, G. Buccolieri, N. Cardellicchio, Heavy metals in marine sediments of Taranto gulf (Ionian sea, southern italy), Marine Chemistry 99 (2006) 227-235.
[6] J. J. Buckley, Fuzzy Statistics, Studies in fuzziness and soft computing, SpringerVerlag, Berlin, (2006).
[7] E. I. B. Chopin, B. J. Alloway, Distribution and mobility of trace elements in soils and vegetation around the mining and smelting areas of Tharsis, Rotinto and Huelva, Iberian Pyrite Belt, SW Spain, Water, Air, and Soil Pollution 182 (2007) 245-261.
[8] R. Dixit, D. Malaviya, K. Pandiyan, U. B. Singh, A. Sahu, R. Shukla, B. P. Singh, J. P. Rai, P. K. Sharma, H. Lade, Bioremediation of heavy metals from soil and aquatic environment: An overview of principles and criteria of fundamental processes, Sustainability 7 (2015) 2189-2212.
[9] D. Dubois, Fuzzy sets and systems: Theory and applications, Academic Press, Inc., Orlando, FL, USA, (1997).
[10] N. Gaur, G. Flora, M. Yadav, A. Tiwari, A review with recent advancements on bioremediation-based abolition of heavy metals, Environment Science Process Impacts 16 (2014) 180-193.
[11] W. Grzebisz, L. Ciesla, J. Komisarek, J. Potarzycki, Geochemical assessment of the heavy metals pollution of urban soils, Polish Journal of Environmental Studies 11 (2002) 493-500.
[12] Y. G. Gu, X. N. Wang, Q. Lin, F. Y. Du, J. J. Ning, L. G. Wang, Y. F. Li, Fuzzy comprehensive assessment of heavy metals and Pb isotopic signature in surface sediments from a bay under serious anthropogenic influences: Daya Bay, China, Ecotoxicology and Environmental Safety 126 (2016) 38-44.
[13] J. Jantzen, Foundations of fuzzy control: A practical approach (2nd ed.), Wiley Publishing, (2013).
[14] M. C. Jung, I. Thornton, Heavy metal contamination of soils and plants in the vicinity of a lead zinc mine, Korean Journal of Applied Geochemistry 11 (1996) 53-59.
[15] C. Kahraman, I. U. Sari, Intelligence systems in environmental management: Theory and applications (1st ed.), Springer Publishing Company, Incorporated, (2016).
[16] C. Kahraman, U. Kaymak, A. Yazici, Fuzzy logic in its 50th year: New developments, directions and challenges (1st ed.), Springer Publishing Company, Incorporated, (2016).
[17] M. Z. H. Khan, M. R. Hasan, M. Khan, S. Aktar, K. Fatema, Distribution of heavy metals in surface sediments of the Bay of Bengal coast, Journal of Toxicology 20 (2017) 132-145.
[18] K. H. Lee, First course on fuzzy theory and applications, Springer-Verlag, Berlin, (2005).
[19] G. L. Liao, D. X . Liao, Q. M. Li, Heavy metals contamination characteristics in soil of different mining activity zone Trans, Transactions of Nonferrous Metals Society of China 18 (2008) 207-211.
[20] M. Li, The fuzzy comprehensive assessment on heavy metal pollution of farmland soil in Linzi, 2011 International Conference on New Technology of Agricultural, Zibo, 26 (2011) 486-491.
[21] F. Li, J. Zhang, W. Liu, J. Liu, J. Huang, L. Zeng, An exploration of an integrated stochastic-fuzzy pollution assessment for heavy metals in urban topsoil based on metal enrichment and bio accessibility, Science of The Total Environment 644 (2018) 649-660.
[22] G. Mller, Index of geoaccumulation in sediments of the Rhine river, Geojournal 2 (1969) 108-118.
[23] K. Naresh Sinha, M. Madan Gupta, Soft computing and intelligent systems-theory and application, Academic Press, (2000).
[24] W. Pedrycz, F. Gomide, Fuzzy systems engineering: Toward human-centric computing, Wiley-IEEE Press, (2007).[25] S. Rajasekaran, G. A. Vijayalaksmi Pai, Neural network, fuzzy logic, and genetic algorithms-synthesis and applications, Prentice Hall, (2005).
[26] S. N. M. Ripin, S. Hasan, M. L. Kamal, N. M. Hashim, Analysis and pollution assessment of heavy metal in soil, Perlis, The Malaysian Journal of Analytical Sciences 18 (2014) 155-161.
[27] G. Shen, Y. Lu, M. Wang, Y. Sun, Status and fuzzy comprehensive assessment of combined heavy metal and organo-chlorine pesticide pollution in the Taihu Lake region of China, Journal of Environmental Management 76 (2005) 355-362.
[28] R. A. Sutherland, C. A. Tolosa, F. M. G. Tack, M. G. Verloo, Characterization of selected element concentration and enrichment ratios in background and anthropogenically impacted roadside areas, Archives of Environmental Contamination and Toxicology 38 (2000) 428-438.
[29] H. I. Tak, F. Ahmad, O. O. Babalola, Advances in the application of plant growthpromoting rhizobacteria in phytoremediation of heavy metals, In Reviews of Environmental Contamination and Toxicology; Springer: New York, NY, USA, (2013).
[30] D. L. Tomlinson, J. G. Wilson, C. R. Harris, D. W. Jeffrey, Problem in the assessment of heavy metals levels in estuaries and the formation of a pollution index, Helgolnder Meeresuntersuchungen 33 (1980 ) 566-575.
[31] R. Viertl, Statistical Methods for Fuzzy Data, John Wiley & Sons, Chichester, Ltd, (2011).
[32] Y. Yang, Z. Zhengchao, B. A. I. Yanying, C. A. I. Yimin, Chen, W. Risk assessment of heavy metal pollution in sediments of the Fenghe River by the fuzzy synthetic evaluation model and multivariate statistical methods, Pedosphere 26 (2016) 326-334.
[33] L. A. Zadeh, Fuzzy sets, Information and Control 8 (1965) 338-353.
[34] L. P. Zhang, X. Ye, H. Feng, Y. Jing, T. Ouyang, X. Yu, R. Liang, C. Gao, W. Chen, Heavy metal contamination in western Xiamen Bay sediments and its vicinity, Marine Pollution Bulletin 54 (2007) 974-982.
[35] H. J. Zimmermann, Fuzzy set theory and mdash and its applications (3rd Ed.), Kluwer Academic Publishers, Norwell, MA, USA, (1996).
