Multiobjective optimization and marginal pollution abatement cost in the electricity sector – An Israeli case study

2002 ◽  
Vol 140 (3) ◽  
pp. 571-583 ◽  
Author(s):  
David Soloveitchik ◽  
Nissim Ben-Aderet ◽  
Mira Grinman ◽  
Alexander Lotov
Keyword(s):  
Multiobjective Optimization ◽  
Pollution Abatement ◽  
Abatement Cost ◽  
Electricity Sector ◽  
Pollution Abatement Cost

Water pollution abatement cost function: methodological issues and an application to small-scale factories in an industrial estate in India

2001 ◽  
Vol 6 (1) ◽  
pp. 103-122 ◽  
Author(s):  
BISHWANATH GOLDAR ◽  
SMITA MISRA ◽  
BADAL MUKHERJI
Keyword(s):  
Water Pollution ◽  
Cost Function ◽  
Pollution Abatement ◽  
Abatement Cost ◽  
Policy Formulation ◽  
Primary Data ◽  
Small Scale ◽  
Industrial Estate ◽  
Pollution Abatement Cost ◽  
The Cost

Formulation and estimation of a correctly specified abatement cost function would be central to policy formulation regarding imposing taxes or user-fees as well as of sharing social cost in the presence of environmental pollution. Often in research, the output of an abatement activity for water pollution appears to us not to have been clearly specified. This activity is very distinct from whatever is the actual product of the plant. We propose in this paper that the output is only and exclusively the reduction in the level of the pollutant in the outflow from the plant and illustrate this with primary data for small-scale factories in Nandesari Industrial Estate in Gujarat, India. The cost function estimates provide evidence of significant scale economies and high marginal abatement cost in wastewater treatment by small-scale factories.

scholarly journals Modelling environmental technical efficiency and phosphorus pollution abatement cost in dairy farms

2020 ◽  
Vol 714 ◽  
pp. 136690 ◽  
Author(s):  
Adewale Henry Adenuga ◽  
John Davis ◽  
George Hutchinson ◽  
Myles Patton ◽  
Trevor Donnellan
Keyword(s):  
Technical Efficiency ◽  
Pollution Abatement ◽  
Dairy Farms ◽  
Abatement Cost ◽  
Phosphorus Pollution ◽  
Pollution Abatement Cost

A bottom-up method to develop pollution abatement cost curves for coal-fired utility boilers

Energy Policy ◽  
2010 ◽  
Vol 38 (5) ◽  
pp. 2255-2261 ◽  
Author(s):  
Samudra Vijay ◽  
Joseph F. DeCarolis ◽  
Ravi K. Srivastava
Keyword(s):  
Pollution Abatement ◽  
Abatement Cost ◽  
Bottom Up ◽  
Cost Curves ◽  
Utility Boilers ◽  
Pollution Abatement Cost

A Cooperative Approach to Reduce Water Pollution Abatement Cost in an Interjurisdictional Lake Basin

2013 ◽  
Vol 50 (3) ◽  
pp. 777-790 ◽  
Author(s):  
Laijun Zhao ◽  
Wei Huang ◽  
H. Oliver Gao ◽  
Jian Xue ◽  
Changmin Li ◽  
...  
Keyword(s):  
Water Pollution ◽  
Pollution Abatement ◽  
Abatement Cost ◽  
Lake Basin ◽  
Cooperative Approach ◽  
Pollution Abatement Cost

Pollution abatement cost savings and FDI inflows to polluting sectors in China

2007 ◽  
Vol 12 (6) ◽  
pp. 775-798 ◽  
Author(s):  
WENHUA DI
Keyword(s):  
Local Governments ◽  
Bargaining Power ◽  
Pollution Abatement ◽  
Cost Savings ◽  
Abatement Cost ◽  
Nested Logit ◽  
Fdi Inflows ◽  
Pollution Abatement Cost ◽  
Potential Pollution ◽  
Polluting Firms

ABSTRACTThis paper uses a nested logit model to examine whether potential pollution abatement cost savings adjusted by institutional and socio-economic conditions influence the location choices of Foreign Direct Investment (FDI) among Chinese provinces. It incorporates individual polluting firms’ characteristics instead of looking only at location attributes. The results show that (i) FDI firms in polluting industries tend to locate in provinces with higher potential abatement costs savings adjusted for local environmental regulation; (ii) relatively dirtier firms are more likely to locate in less developed provinces or provinces with fewer similar polluting industries; (iii) firms in pollution-intensive industries are more sensitive to regulation and development status than firms in non-polluting industries; and (iv) firms tend to locate in provinces where they have more bargaining power with local governments. These findings suggest the existence of domestic pollution havens in China.

scholarly journals Portfolio optimization of power plants by using renewable energy in Iran

2020 ◽  
Author(s):  
Seyedeh Asra Ahmadi ◽  
Seyed Mojtaba Mirlohi ◽  
Mohammad Hossein Ahmadi ◽  
Majid Ameri
Keyword(s):  
Renewable Energy ◽  
Portfolio Optimization ◽  
Energy Supply ◽  
Power Plants ◽  
Renewable Energy Sources ◽  
Modern Society ◽  
Sustainable Growth ◽  
Electricity Sector ◽  
Capital Costs

Abstract Lack of investment in the electricity sector has created a huge bottleneck in the continuous flow of energy in the market, and this will create many problems for the sustainable growth and development of modern society. The main reason for this lack of investment is the investment risk in the electricity sector. One way to reduce portfolio risk is to diversify it. This study applies the concept of portfolio optimization to demonstrate the potential for greater use of renewable energy, which reduces the risk of investing in the electricity sector. Besides, it shows that investing in renewable energies can offset the risk associated with the total input costs. These costs stem from the volatility of associated prices, including fossil fuel, capital costs, maintenance, operation and environmental costs. This case study shows that Iran can theoretically supply ~33% of its electricity demand from renewable energy sources compared to its current 15% share. This case study confirms this finding and predicts that Iran, while reducing the risk of investing in electricity supply, can achieve a renewable energy supply of ~9% with an average increase in supply costs. Sensitivity analysis further shows that with a 10% change in input cost factors, the percentage of renewable energy supply is only partially affected, but basket costs change according to the scenario of 5–32%. Finally, suggestions are made that minimize risk rather than cost, which will bring about an increase in renewable energy supply.

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