تحلیل خط مشی‌های اقلیمی اتحادیه اروپا جهت کاهش انتشار کربن در افق زمانی 2021 تا 2030 و تأثیرات آن در سیاست های راهبردی زیست محیطی ایران با رویکرد پویایی سیستم ها

نوع مقاله : مقاله پژوهشی

نویسندگان

1 استادیار دانشکده مهندسی صنایع، دانشگاه صنعتی خواجه نصیرالدین طوسی، تهران، ایران

2 دانشجوی دکتری دانشکده مهندسی صنایع، دانشگاه صنعتی خواجه نصیرالدین طوسی، تهران، ایران

3 دانشجوی کارشناسی ارشد، دانشکده مهندسی صنایع، دانشگاه صنعتی خواجه نصیرالدین طوسی، تهران، ایران.

چکیده

هدف: تغییرات اقلیمی ناشی از انتشار گازهای گلخانه ای بخصوص کربن دی اکسید، پیامدهای خطرناکی را به دنبال دارد که گرمایش زمین مهم­ترین آن­هاست. اتحادیه اروپا به عنوان جلودار در مسیر کاهش میزان انتشار کربن، اقدامات اساسی زیادی انجام داده و خط‌ مشی­‌ها و سیاست های مختلفی را وضع کرده است.تحلیل اقدامات و خط مشی­های اتخاذ شده توسط این اتحادیه می تواند در تعیین استراتژی صحیح جهت حفاظت از محیط زیست در داخل کشورمان مفید باشد.
روش: این پژوهش با استفاده از رویکرد پویا یی سیستم­ها و در ‌نظرگیری حلقه‌های بازخوردی تعدیل کننده انتشار کربن ناشی از اعمال خط مشی‌های اقلیمی، یک مدل شبیه‌سازی برای تحلیل اثربخشی سیاست‌های اتحادیه اروپا برای دستیابی به اهداف مرتبط تا سال 2030 به منظور کاهش انتشار کربن ارائه می‌کند.
یافته­ها:نتایج حاصله نشان می‌دهد که اتخاذ یک خط مشی به تنهایی نمی‌تواند اثربخشی مطلوبی در کاهش میزان انتشار داشته باشد. همچنین نتایج بدست آمده نشان می‌دهد، سیستم مدیریت انتشار  EU ETS به تنهایی، کمترین عملکرد را در کاهش میزان انتشار کربن دارد.
نتیجه­گیری:سناریویی که اتخاذ خط مشی‌های سه گانه اقلیمی اتحادیه اروپا را نشان می‌دهد، بهترین اثرگذاری را در کاهش میزان انتشار تا سال 2030 نشان می دهد. از میان حلقه‌های بازخوردی تعدیل کننده در کاهش انتشار کربن، و بنا بر ترکیب خط مشی‌های اقلیمی اتحادیه اروپا، انجام اقدامات در حوزه کارایی انرژی و سیستم مدیریت انتشارEU ETS بایستی بیشتر مورد توجه قرار گیرد.

کلیدواژه‌ها

عنوان مقاله [English]

Analyzing the Effectiveness of EU Climate Policies by Simulating Scenarios to Reduce Carbon Emissions from 2021 to 2030 and Its Impacts on Iranian Environmental Strategic Policies Using a System Dynamics Approach

نویسندگان [English]

  • nasser safaie 1
  • sajad Hedayati 2
  • SEYED AMIR NASRI 3
  • majid mirzaie 1
1 Assistant Professor of Industrial Engineering, K. N. Toosi University of Technology, Tehran, Iran
2 Ph.D. Student in Industrial Engineering, K. N. Toosi University of Technology, Tehran, Iran
3 M.A. Student in Industrial Engineering, K. N. Toosi University of Technology, Tehran, Iran
چکیده [English]

Objective: Climate change due to greenhouse gas emissions, especially carbon dioxide, has dangerous consequences, the most important of which is global warming. The European Union, as a leader in reducing carbon emissions, has taken a number of key steps and set various policies and guidelines. Analyzing the actions and policies adopted by this union could help determine the correct strategy for environmental protection in our country.
Method: This study presents a simulation model to analyze the effectiveness of EU policies to achieve related aims by 2030 to reduce carbon emissions, using a system dynamic approach to reduce carbon emissions.
Findings: The results show that the adoption of a policy alone cannot have the desired effect in reducing emissions. The results also indicate that the EU ETS emission management system alone has the lowest performance in reducing carbon emissions.
Conclusion: The scenario showing the adoption of the EU's three climate policies showed the best impact on reducing emissions by 2030. Among the moderating feedback loops on reducing carbon emissions, and in line with the EU's climate policy, action on energy efficiency and the EU ETS emission management system should be given more attention.

کلیدواژه‌ها [English]

  • EU Climate Policies
  • Carbon Emissions
  • System Dynamics
  • Iranian Environmental Strategic Policies
  • Environmental Protection Organization

مراجع

Capros, P., De Vita, A., Höglund Isaksson, L., Winiwarter, W., Purohit, P., Bottcher, H., ... & Witzke, H. P. (2013). EU energy, transport and GHG emissions trends to 2050-Reference scenario 2013. European Commission.
Wang, Y.F., Liang, S., (2013). Carbon dioxide mitigation target of China in 2020 andkey economic sectors. Energy Policy 58, 90e96.
Zhang, X.H., Han, J., Zhao, H., (2012). Evaluating the interplays among economicgrowth and energy consumption and CO2 emission of China during 1990e2007.Renew. Sustain. Energy Rev. 16, 65e72.
Choi, J.-K., Bakshi, B.R., Haab, T., (2010). Effects of a CO2 price in the U.S. on economicsectors, resource use, and emissions: an input–output approach. Energy Policy38, 3527–3536.
Ghosh, S., (2010). Examining CO2 emissions economic growth nexus for India:a multivariate co-integration approach. Energy Policy 38, 3008–3014.
Ross Morrow, W., Gallagher, K.S., Collantes, G., Lee, H., (2010). Analysis of policies toreduce oil consumption and greenhouse-gas emissions from the US transportation sector. Energy Policy 38, 1305–1320.
Peters, M., Fudge, S., Sinclair, P., (2010). Mobilising community action towards alow-CO2 future: opportunities and challenges for local government in the UK.Energy Policy 38, 7596–7603.
Chicco, G., Stephenson, P.M., (2011). Effectiveness of setting cumulative CO2 dioxideemissions reduction targets. Energy.
Ang, B.W., Zhang, F.Q., Choi, K.H., (1998). Factorizing changes in energy and environmental indicators through decomposition. Energy 23 (6), 489e495.
Wang, C., Chen, J., Zou, J., (2005). Decomposition of energy-related CO2 emission in China: 1957e2000. Energy 30 (1), 73e83.
Fan, Y., Liu, L.C., Wu, G., Tsai, H.T., Wei, Y.M., (2007). Changes in carbon intensity in China: empirical findings from 1980e2003. Ecol. Econ. 62 (3e4), 683e691.
Ipek, T.G., Serap, T.A., Akbostanci, (2009) E. A decomposition analysis of CO2 emissions from energy use: Turkish case. Energy Policy , ,37 (11), 4689e4699.
Paul, S., Bhattacharya,(2004) R.N. CO2 emission from energy use in India: a decomposition analysis. Energy Policy,, 32 (5), 585e593.
Li, Fujia, et al. "The improvement of CO2 emission reduction policies based on system dynamics method in traditional industrial region with large CO2 emission." Energy Policy 51: 683-695.
Sims, R.E.H., Rogner, H.H., Ken, G. (2003) Carbon emission and mitigation cost comparisons between fossil fuel, nuclear and renewable energy resources for electricity generation. Energy Policy, 31, 1315e1326.
Van den Broek, M., Faaij, Andre, Turkenburg, Wim, (2008). Planning for an electricity sector with carbon capture and storage: case of the Netherlands. Int. J. Greenh. Gas Control 2,105e129.
Mondal, M.A.H., Mathur, J., Denich, M. (2011) Impacts of CO2 emission constraints on technology selection and energy resources for power generation in Bangladesh. Energy Policy , 39, 2043e2050.
Chen, W.Y., Wu, Z.X., He, J.K., Gao, P.F., Xu, S.F. (2007) Carbon emission control strategies for China: a comparative study with partial and general equilibrium versions of the China MARKAL model. Energy ,32 (1), 59e72.
Endo, E., Ichinohe, M. (2006) Analysis on market deployment of photovoltaics in Japan by using energy system model MARKAL. Sol. Energy Mater. Sol. Cells, ,90 (18e19), 3061e3067.
Sarica, K., Tyner, W.E., (2013). Analysis of US renewable fuels policies using a modified MARKAL model. Renew. Energy 50 (0), 701e709.
Strachan, N., Kannan, R. (2008) Hybrid modelling of long-term carbon reduction scenarios for the UK. Energy Econ, 30 (6), 2947e2963.
Sue, W.I., (2004). Computable General Equilibrium Models and Their Use in Economy-Wide Policy Analysis: Everything You Ever Wanted to Know (but Were Afraid to Ask). Technical note no. 6. MIT Joint Program on the Science and Policy of Global Change. Cambridge, MA.
Liang, Q.M., Fan, Y., Wei, Y.M. (2007) Carbon taxation policy in China: how to protect energy- and trade-intensive sectors? J. Policy Model, 29 (2), 311e333.
Hassan, Q.U., Baek, S.S. (2010) How to do structural validity of a system dynamics type simulation model: the case of an energy policy model. Energy Policy, , 38, 2216e2224.
Chi, K.C., Nuttall, W.J., Reiner, D.M. (2009) Dynamics of the UK natural gas industry: system dynamics modelling and long-term energy policy analysis. Technol. Forecast. Soc. Change , 76, 339e357.
Ansari, N., Seifi, A. (2012) A system dynamics analysis of energy consumption and corrective policies in Iranian iron and steel industry. Energy,43, 334e343.
Dong, X., Li, C., Li, J., Huang, W., Wang, J., Liao, R. (2012) Application of a system dynamics approach for assessment of the impact of regulations on cleaner production in the electroplating industry in China. J., Clean. Prod,20 (1), 72e81.
Fong, W.K., Matsumoto, H., Lun, Y.F. (2009) Application of system dynamics model asdecision making tool in urban planning process toward stabilizing carbon dioxide emissions from cities. Build. Environ, 44, 1528e1537.
Kunsch, P., Springael, J.(2008) Simulation with system dynamics and fuzzyreasoning of a tax policy to reduce CO2 emissions in the residential sector. Eur. J.Oper. Res, 185, 1285e1299.
Feng, Y.Y., Chen, S.Q., Zhang, L.X. (2013) System dynamics modeling for urban energyconsumption and CO2 emissions: a case study of Beijing, China. Ecol. Model,252, 44e52.
Nastaran, A., Abbas, S. (2013)A system dynamics model for analyzing energy consumption and CO2 emission in Iranian cement industry under various production and export scenarios. Energy Policy, 58, 75e89.
Nuri, C.O., Gokhan, E., Omer, T. (2014) Towards greening the U.S. residential buildingstock: a system dynamics approach. Build. Environ., 78, 68e80.
Khadivar A, javaheri S. (2015) System Dynamics simulation for Developing and intenerating knowledge management and Knowledge strategy. IQBQ. 19 (1):117-146.
Haji Gholam Saryazdi A, rajabzadeh Ghatari A, Mashayekhi A N, Hasanzadeh (2017) A. The Dilemma of the Dynamic Problems: Provide a Framework for the Process of Problem Definition. IQBQ. 21 (2):1-26.
Heydarpour, vahid and Zandieh, Mostafa and Farsijani, Hassan and Rabieh, Masoud, (2017) Proposing a Model for Forecasting Port Container Terminal Performance; System Dynamics Approach, Modern Research in Decision Making ,2(2), 109-132.
Sterman, John D. (2000) "Business Dynamics"-Systems Thinking and Modeling for a Complex World,McGraw-Hill.
Javadian nikbakhsh, Khani M.,Mahdavi I., (2012) Identifying effective factors on supply chain performance and improving them by using system dynamics techniques, Case study in Darugar Company Case study in darugar company. IQBQ. 16 (3) :39-58.
Mohaghar A, Sharif Abadi A M.)2006( Modeling Just in Time Production Using System Dynamics Approach. IQBQ. 10 (20) :269-292.
Al-Najjar, Wareef. System dynamics simulation model for forecasting energy demand in Pueblo county, )2013(, A. Diss. Colorado State University-Pueblo. Library.

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