Volume 24, Issue 3 (Autumn 2019)
JPBUD 2019, 24(3): 87-110 |
Back to browse issues page
Download citation:
BibTeX | RIS | EndNote | Medlars | ProCite | Reference Manager | RefWorks
Send citation to:
BibTeX | RIS | EndNote | Medlars | ProCite | Reference Manager | RefWorks
Send citation to:
Sadeghi Z, Jalaei A, Movahedi M. (2019). Natural Gas Pricing Based On Social Costs of Carbon: A Case Study of Kerman Province. JPBUD. 24(3), 87-110. doi:10.29252/jpbud.24.3.87
URL: http://jpbud.ir/article-1-1868-en.html
URL: http://jpbud.ir/article-1-1868-en.html
1- Shahid Bahonar University of Kerman, Kerman, Iran , z_sadeghi@uk.ac.ir
2- Shahid Bahonar University of Kerman, Kerman, Iran.
2- Shahid Bahonar University of Kerman, Kerman, Iran.
Abstract: (4262 Views)
Due to the increasing demand for natural gas and its benefit of producing less carbon compared to other fossil fuels, pricing the natural gas based on the social expenses is becoming necessary more than ever. Accordingly, presenting models that enable us to find coordination between natural gas pricing and the final cost of carbon reduction is of high importance. This study aims to find the relationship between natural gas pricing, carbon rent, and the degree of pollution caused by natural gas. To this end, the final cost of CO2 reduction for two carriers of natural gas and gas oil in Kerman province has been calculated; Then the measures of social costs based on carbon expenses for natural gas and gas oil in 3 sections of the power plant, industry and houses is conducted. This study presents the evaluation of the final cost of carbon caused by natural gas and gas oil for the three mentioned sectors. The results indicate that the final costs of carbon caused by natural gas are always lower than the final costs of carbon caused by gas oil. This is the major reason as to why the social costs of natural gas are lower than of gas oil in the three sectors. Moreover, the results show that there is not a significant difference
between the rates of the final cost of natural gas and the price of natural gas delivery to the end-users in 2013-2016. This is due to the little amount of pollution natural gas produces and the relatively low cost of its pollution. However, the rate of delivery cost to the power plant is 8 percent of social costs and 9 percent of the final costs of natural gas.
between the rates of the final cost of natural gas and the price of natural gas delivery to the end-users in 2013-2016. This is due to the little amount of pollution natural gas produces and the relatively low cost of its pollution. However, the rate of delivery cost to the power plant is 8 percent of social costs and 9 percent of the final costs of natural gas.
Keywords: Abatement Cost of Carbon Dioxide, Natural Gas Pricing, Shadow Price, Distance Function, Data Envelopment Analysis.
Type of Study: Research |
Received: Jan 27 2020 | Accepted: May 24 2020 | ePublished: Sep 15 2020
Received: Jan 27 2020 | Accepted: May 24 2020 | ePublished: Sep 15 2020
References
1. Aguilera, R. F. (2014). The Role of Natural Gas in a Low Carbon Asia Pacific. Applied Energy, 113(1), 1795-1800. [DOI:10.1016/j.apenergy.2013.07.048]
2. Bacon, R. W., & Bhattacharya, S. (2007). Growth and CO2 Emissions: How Do Different Countries Fare? The World Bank Environmental Department, Environmental Department Papers, 113-120.
3. Boyd, G., Molburg, J., & Prince, R. (1996). Alternative Methods of Marginal Abatement Cost Estimation: Non-Parametric Distance Functions. (No. ANL/DIS/CP-90838; CONF-9610179-3). Argonne National Lab., IL (United States). Decision and Information Sciences Div.
4. BP (2018). BP Statistical Review of World Energy. BP Statistical Review, London, UK, Accessed Aug, 6, 2018.
5. Choi, Y., Zhang, N., & Zhou, P. (2012). Efficiency and Abatement Costs of Energy-Related CO2 Emissions in China: A Slacks-Based Efficiency Measure. Applied Energy, 98(1), 198-208. [DOI:10.1016/j.apenergy.2012.03.024]
6. Chung, Y. H., Färe, R., & Grosskopf, S. (1997). Productivity and Undesirable Outputs: A Directional Distance Function Approach. Journal of Environmental Management, 51(3), 229-240. [DOI:10.1006/jema.1997.0146]
7. Du, L., Hanley, A., & Wei, C. (2015). Estimating the Marginal Abatement Cost Curve of CO2 Emissions in China: Provincial Panel Data Analysis. Energy Economics, 48(1), 217-229. [DOI:10.1016/j.eneco.2015.01.007]
8. Duan, Y., Li, N., Mu, H., & Li, L. (2017). Research on Provincial Shadow Price of Carbon Dioxide in China's Iron and Steel Industry. Energy Procedia, 142(1), 2335-2340. [DOI:10.1016/j.egypro.2017.12.163]
9. Energy Information Administration (EIA), U. S. (2017). Annual Energy Outlook 2015: With Projections to 2040.
10. Färe, R., & Grosskopf, S. (2000). Theory and Application of Directional Distance Functions. Journal of Productivity Analysis, 13(2), 93-103. [DOI:10.1023/A:1007844628920]
11. Färe, R., Grosskopf, S., Noh, D.-W., & Weber, W. (2005). Characteristics of a Polluting Technology: Theory and Practice. Journal of Econometrics, 126(2), 469-492. [DOI:10.1016/j.jeconom.2004.05.010]
12. Gallaher, M., Delhotal, C., & Petrusa, J. (2005). Region-Specific Marginal Abatement Costs for Methane from Coal, Natural Gas, and Landfills through. 2030 Greenhouse Gas Control Technologies 7 (pp. 851-859): Elsevier. [DOI:10.1016/B978-008044704-9/50086-0]
13. Hailu, A., & Veeman, T. S. (2000). Environmentally Sensitive Productivity Analysis of the Canadian Pulp and Paper Industry, 1959-1994: An Input Distance Function Approach. Journal of Environmental Economics and Management, 40(3), 251-274. [DOI:10.1006/jeem.2000.1124]
14. Hailu, A., & Veeman, T. S. (2001). Non-Parametric Productivity Analysis with Undesirable Outputs: An Application to the Canadian Pulp and Paper Industry. American Journal of Agricultural Economics, 83(3), 605-616. [DOI:10.1111/0002-9092.00181]
15. Hamilton, C., & Turton, H. (2002). Determinants of Emissions Growth in OECD Countries. Energy Policy, 30(1), 63-71. [DOI:10.1016/S0301-4215(01)00060-X]
16. Lee, C.-Y., & Zhou, P. (2015). Directional Shadow Price Estimation of CO2, SO2 and NOx in the United States Coal Power Industry 1990-2010. Energy Economics, 51(1), 493-502. [DOI:10.1016/j.eneco.2015.08.010]
17. Lise, W. (2006). Decomposition of CO2 Emissions Over 1980-2003 in Turkey. Energy Policy, 34(14), 1841-1852. [DOI:10.1016/j.enpol.2004.12.021]
18. Wang, Q., Cui, Q., Zhou, D., & Wang, S. (2011). Marginal Abatement Costs of Carbon Dioxide in China: A Nonparametric Analysis. Energy Procedia, 5(1), 2316-2320. [DOI:10.1016/j.egypro.2011.03.398]
19. Yang, X., Li, H., Wallin, F., Yu, Z., & Wang, Z. (2017). Impacts of Emission Reduction and External Cost on Natural Gas Distribution. Applied Energy, 207(1), 553-561. [DOI:10.1016/j.apenergy.2017.06.005]
20. Zhang, M., Mu, H., Ning, Y., & Song, Y. (2009). Decomposition of Energy-Related CO2 Emission Over 1991-2006 in China. Ecological Economics, 68(7), 2122-2128. [DOI:10.1016/j.ecolecon.2009.02.005]
21. Zhou, P., Zhou, X., & Fan, L. (2014). On Estimating Shadow Prices of Undesirable Outputs With Efficiency Models: A Literature Review. Applied Energy, 130(1), 799-806. [DOI:10.1016/j.apenergy.2014.02.049]
22. Zhou, X., Fan, L., & Zhou, P. (2015). Marginal CO2 Abatement Costs: Findings from Alternative Shadow Price Estimates for Shanghai Industrial Sectors. Energy Policy, 77(1), 109-117. [DOI:10.1016/j.enpol.2014.12.009]
| Rights and permissions | |
.jpg) |
This work is licensed under a Creative Commons Attribution 4.0 International License. |
