Emissions trading in Hong Kong and the Pearl River Delta region-A modeling approach to trade decisions in Hong Kong's electricity industry

Research output: Journal Publications and Reviews (RGC: 21, 22, 62)21_Publication in refereed journal

8 Scopus Citations
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Author(s)

Detail(s)

Original languageEnglish
Pages (from-to)1-12
Journal / PublicationEnvironmental Science and Policy
Volume31
Publication statusPublished - Aug 2013

Abstract

In 2002, the Hong Kong government and the Guangdong provincial government agreed to reduce emissions of sulfur dioxide, nitrogen oxides, respirable suspended particulates, and volatile organic compounds by 40%, 20%, 55%, and 55%, respectively. There was strong public demand for the power stations in Hong Kong to reduce emissions. Emission caps were introduced, with allowances for the trading of emission credits. However, local power stations were using equipment built in the 1980s and 1990s, making it difficult for them to meet the new emissions requirements. The situation presented a new challenge, which involved a choice of either improving the existing equipment, or using emissions trading to meet the emission caps. This study reviews the background on emissions in Hong Kong and the surrounding regions, the "cap and trade" system, and the technologies used for power generation and emission reduction. A modeling approach is adopted to simulate the equipment, the electricity dispatching requirements, and the costs of either reducing emissions or trading emission credits. Data from a power station in Hong Kong was chosen for the simulation. Different options were simulated in the model to identify the optimal strategy. The results were then compared with the plan for emission reduction. This study demonstrates that a modeling approach using linear programming can analyze the complicated options involving emission reduction and investments to achieve an optimized business solution. © 2013 Elsevier Ltd.

Research Area(s)

  • Air pollution, Emission control, Modeling, Regional emissions trading