عنوان مقاله [English]
Environmental risk assessment is one of the most important parts of the environmental management system and plays a significant role in improving the quality indices and environmental performance. The cost of damage (direct, indirect, and intangible), and the consequences of pollution and environmental accidents are very high, causing significant damage to organizations and countries every year. Therefore, it is necessary that risk management, which involves identifying, assessing and controlling risk, is implemented at the level of companies that have the potential capacity for such events. In this research, the environmental quality assessment of the Pars Special Economic Region from 2011 to 2014 has been investigated using fuzzy logic. Fuzzy logic is a multi-valued logic that allows the grading of values to work with the user's values in a system.
Acosta H, Wu D, Forrest BM, “Fuzzy experts on recreational vessels, a risk modeling approach for marine invasions”, Ecological Modelling, 2010, 221, 850-863.
Azimi Y, Osanloo M, Aakbarpour-Shirazi M, Bazzazi AA, “Prediction of the blastability designation of rock masses using fuzzy sets. International”, Journal of Rock Mechanics and Mining Sciences, 2010, 47, 1126-1140.
Azimi Y, “Prediction of Seismic Wave Intensity Generated by Bench Blasting Using Intelligence Committee Machines”, IJE TRANSACTIONS A: Basics, 2019, 32 (4), 617-627.
Bagheri M, Shabakhty N, “Calculation of Fuzzy Structural Reliability Index Using α-level Optimization Technique”, Journal of Civil and Environmental Engineering, 2014, 43 (4), 73, 1-12.
Cabanillas J, Ginebreda A, Guillén D, Martínez E, Barceló D, Moragas L, Robusté J, Darbra RM, “Fuzzy logic based risk assessment of effluents from waste-water treatment plants”, Science of the Total Environment, 2010, 439, 202-221.
CCME, “Canadian water quality guidelinesfor the protection of aquatic life: CCME Water Quality Index 1.0, User’s manual. In: Canadian Environmental quality guidelines, 1999”, Canadian Council of Ministers of the Environment, Winnipeg, Manitoba 2001, http://www.ccme.ca/assets/pdf/wqi_usermanualfctsht_e.pdf).
CCME, “Canadian Environmental Sustainability Indicators. Freshwater QualityIndicator: Data Sources and Methods”, 2005, Catalogue no. 16-256-XIE, http://www.statcan.ca/bsolc/english/bsolc?catno=16-256-XIENumberformatdisp.
Cieszynska M, Wesolowski M, Bartoszewicz M, Michalska M, Nowacki J, “Application of physicochemical data for water-quality assessment of watercourses in the Gdansk Municipality (South Baltic coast)”, Environmental Monitoring and Assessment, 2012, 184, 2017-2029.
Dahiya S, Singh B, Gaur S, Garg VK, Kushwaha HS, “Analysis of groundwater qualityusing fuzzy synthetic evaluation”, Journal of Hazardous Materials, 2007, 147, 938-946.
Diriba D, Till S, Feyera S, Steven VP, Azadi H, “Environmental and health impacts of effluents from textile industries in Ethiopia: the case of Gelan and Dukem, Oromia Regional State”, Environmental Monitoring and Assessment, 2017, 189, 11.
Esty DC, Levy MA, Srebotnjak T, de Sherbinin A, Kim CH, Anderson B, Pilot “Environmental Performance Index. New Haven”, Yale Center for Environmental Law & Policy, 2006.
Gharibi H, Mahvi AH, Nabizadeh R, Arabalibeik H, Yunesian M, Sowlat MH, “A novel approach in water quality assessment based on fuzzy logic”, Journal of Environmental Management, 2012, 112, 87-95.
Ghaysari P, Bayatvarkeshi M, “Application of fuzzy logic and wavelet transform in estimation of ground water level using ENSO indexes”, Articles in Press, Accepted Manuscript, Journal of Civil and Environmental Engineering. Available Online from 17 November 2018.
Hosseini-Moghari SM, Ebrahimi K, Azarnivand A, “Groundwater quality assessment with respect to fuzzy water quality index (FWQI): an application of expert systems in environmental monitoring”, Environmental Earth Sciences, 2015, 74, 7229.
Hernández JJC, Fernández LPS, Ochoa JAC, Trinidad JFM, “Assessment and prediction of air quality using fuzzy logic and autoregressive models”, Atmospheric Environment, 2012, 60, 37-50.
Kamrani S, Rezaei M, Amiri V, Sabernia “AInvestigating the efficiency of information entropy and fuzzy theories to classification of groundwatersamples for drinking purposes: Lenjanat Plain, Central Iran’’, Environmental Earth Sciences, 2016, 75, 1370.
Liou S, Lo S, Wang S, “A generalized water quality index for Taiwan”, Environmental Monitoring and Assessment, 2004, 96, 35-52.
Liou SM, Lo SL, Hu CY, “Application of two-stage fuzzy set theory to river quality evaluation in Taiwan”, Water Research, 2003, 37, 1406-1416.
Lourenço RW, Silva DCC, Martins ACG, “Use of fuzzy systems in the elaboration of an anthropic pressureindicator to evaluate the remaining forest fragments’’, Environmental Earth Sciences, 2015, 74, 2481.
McKone TE, Deshpande AW, “Can fuzzy logic bring complex environmental problemsinto focus?”, Environmental Science & Technology, 2005, 39, 42A-47A.
Mo-Yuen C, “Methodologies of Using Neural Network and Fuzzy Logic Technologiesfor Motor Incipient Fault Detection’, World Scientific, Singapore, 1997.
Nasiri F, Maqsood I, Huang G, Fuller N, “Water quality index: a fuzzy riverpollution decision support expert system”, Journal of Water Resources Planning and Management. 2007, 133, 95-105.
Ocampo- Duque W, Ferré- Huguet N, Domingo JL, Schuhmacher M, “Assessing waterquality in rivers with fuzzy inference systems: a case study”, Environment International, 2006, 32, 733-742.
Peche R, Rodrı´guez E, “Environmental impact assessment bymeans of a procedure based on fuzzy logic: a practical application”, Environ Impact Assessment Review, 2011, 31 (2), 87-96.
Pesce SF, Wunderlin DA, “Use of water quality indices to verify the impact of Cordoba City (Argentina) on Suquia River”, Water Research34: 2000, 2915-2926.
Sarkheil H, Rahbari Sh, Nazari B, Tavakoli J, “Evaluate and compare the environmental assessment and environmental risk assessment; the history, methods and application to look to the companions of the northern oil field”, National Disaster Management and HSE Conference in vital arteries, Industry and Urban Management, Tehran University, 1393 (In Persian).
Sarkheil H, Rahbari Sh, “HSE Key Performance Indicators in HSE-MS Establishment and Sustainability: A Case of South Pars Gas Complex, Iran”, International Journal of Occupational Hygiene, 2016, 8 (1), 45-53.
Sarkheil H, Azimi Y, Rahbari Sh, “Fuzzy Wastewater Quality Index (FWWQI) Determination for Environmental Quality Assessment under Uncertain and Vagueness Conditions” IJE TRANSACTIONS B: Applications, 2018, 31 (8), 1196-1204.
Sarkheil H, Rahbari Sh, “Development of Case Historical Logical Air Quality Indices via Fuzzy Mathematics (Mamdani and Takagi-Sugeno Systems), A case Study for Shahre Rey Town”, Environmental Earth Sciences, 2016, 75, 1319.
Sarkheil H, Azimi Y, Rahbari Sh, “Modeling environmental air quality assessment using fuzzy logic in the Pars Special Economic Energy Zone (Case study: Assaluyeh, Bidkhon and Shirino regions)”, Journal of Environmental Science and Technology, 20 (4), 2019.
Sarkheil H, Rahbari Sh, “Environmental Performance Assessment and Management of the South Pars Gas Complex, Comparing Refineries: 1 and 9-10”, Journal of Environmental Science and Technology, 2017.
Sarkheil H, Rahbari Sh, “RRR (Reclamation, Remediation and Recovery): Green Phases of Mining and Drilling Lifecycle Influence on and/or Influenced by Sustainable Development”, European Online Journal of Natural and Social Sciences, 2015, 4 (4).
Sarkheil H, Azimi Y, Rahbari Sh, Tavakoli J, Shayanfard P, “Evolving Principle Based Fuzzy Inherently Safer Design Index (FISDI) for ISD Assessment, Case Study for Acetic Acid Production Plant”, International Journal of Occupational Hygiene, 2018, 10 (1), 18-23.
Shirmohammadi H, Hadadi F, “Prediction and Control of Vehicular Emissions and Fuel consumption at Urban Intersections by Fuzzy logic Inference Intelligent System”, Journal of Civil and Environmental Engineering, Articles in Press, Accepted Manuscript, Available Online from 24 April 2019.