HONG KONG ENERGY POLICY SIMULATOR: METHODS, DATA, AND SCENARIO RESULTS FOR 2050

The report details the creation of the Hong Kong Energy Policy Simulator (EPS), an open-source system-dynamics model used to project energy-related CO2 emissions and evaluate policy combinations through 2050. It compares a 'Current Policy Scenario' with a 'Decarbonization Scenario,' demonstrating that while current trends project emissions to drop from 36 million tonnes in 2017 to 22.5 million tonnes by 2050, a targeted decarbonization strategy could reduce them to approximately 5 million tonnes. Key levers for this reduction include carbon capture and storage (CCS), electric vehicle mandates, and increased imports of renewable energy from Mainland China.

• Under the Current Policy Scenario, Hong Kong's total energy-related CO2 emissions are projected to decrease from 36 million tonnes in 2017 to 22.5 million tonnes by 2050.
• The Decarbonization Scenario suggests that emissions could be reduced to approximately 5 million tonnes by 2050 through a combination of aggressive policy interventions.
• In the Current Policy Scenario, natural gas is projected to become the dominant electricity source, contributing about 69 percent of generation by 2050, while coal is phased out by 2038.
• To achieve net-zero emissions by 2050, the study proposes increasing renewable energy use to 38 percent, with 35 percent imported from Mainland China and 3 percent generated locally.
• The Decarbonization Scenario relies on carbon capture and storage (CCS) to capture 99 percent of emissions from the power and industry sectors starting in 2030.
• The model identifies several high-impact policies for deep decarbonization, including an electric vehicle (EV) sales mandate, building energy-efficiency standards, and increased retrofitting.
• The EPS uses a 'system dynamics' approach, treating energy use and the economy as an open, non-equilibrium system and utilizing 'stock variables' to track quantities that change gradually over time.
• The simulator's data is prioritized by importance: very high and high importance variables use Hong Kong government data, medium importance variables use Hong Kong or adapted China/U.S. data, and low importance variables use unchanged global data.

APA

Jiang, X., Ge, M., Orvis, R., Rissman, J., Iu, L., & Henning, R. (2019). HONG KONG ENERGY POLICY SIMULATOR: METHODS, DATA, AND SCENARIO RESULTS FOR 2050. Energy Innovation. https://energyinnovation.org/wp-content/uploads/Hong-Kong-EPS_Final20191220.pdf

Chicago

Jiang, Xiaoqian, Mengpin Ge, Robbie Orvis, Jeffrey Rissman, Lawrence Iu, and Roman Henning. HONG KONG ENERGY POLICY SIMULATOR: METHODS, DATA, AND SCENARIO RESULTS FOR 2050. Energy Innovation, 2019. https://energyinnovation.org/wp-content/uploads/Hong-Kong-EPS_Final20191220.pdf.

Wikipedia

{{cite report |last1=Jiang |first1=Xiaoqian |last2=Ge |first2=Mengpin |last3=Orvis |first3=Robbie |last4=Rissman |first4=Jeffrey |last5=Iu |first5=Lawrence |last6=Henning |first6=Roman |title=HONG KONG ENERGY POLICY SIMULATOR: METHODS, DATA, AND SCENARIO RESULTS FOR 2050 |publisher=Energy Innovation |date=December 2019 |url=https://energyinnovation.org/wp-content/uploads/Hong-Kong-EPS_Final20191220.pdf |access-date=23 October 2026 |via=Climate Insights Directory}}

BibTeX

@techreport{jiang2019hong, author = {Jiang, Xiaoqian and Ge, Mengpin and Orvis, Robbie and Rissman, Jeffrey and Iu, Lawrence and Henning, Roman}, title = {{HONG KONG ENERGY POLICY SIMULATOR: METHODS, DATA, AND SCENARIO RESULTS FOR 2050}}, institution = {Energy Innovation}, year = {2019}, month = dec, url = {https://energyinnovation.org/wp-content/uploads/Hong-Kong-EPS_Final20191220.pdf}, urldate = {2026-10-23}, note = {Indexed by Climate Insights Directory} }