Climate Modelling Methods Applied to China

Academics focussing on China and other experts in this area have been reviewed by Teng et al., (2007). They have used a number of IAM methodologies that have been

applied to assess the impacts of climate change, mitigation and adaptation policies in China. General Equilibrium models are preferred in China, as well as Simulation and Cost Minimisation models (Table 3.2). A more detailed survey of Chinese IAM features can be found in Appendix 8.

Table 3.2: Classifications of Chinese IAM methodologies (Teng et al., 2007) General Equilibrium Simulation Input-Output Cost Minimisation

HE YE MARKAL

PRCGEM Liang LEAP

TEDCGE AIM

CNAGE 3E

Surprisingly hybrid IAMs (welfare maximisation and cost minimisation) has not seen a widespread use. This section discusses the different types of IAMs already applied in China and explores the possibility of using hybrid IAMs in China.

3.2.1. General Equilibrium Analysis

General Equilibrium analysis is widely applied amongst Chinese IAM researchers.

The most common are HE, PRCGEM, TEDCGE and CNAGE.

HE

HE is a static General Equilibrium model used to analyse the impacts of carbon tax on the national economy. The model includes detailed assumptions for capital, labour, coal, oil and gas. These factors of production can be substituted against each other.

HE divides the national economy into nine sectors including three energy sectors and six non-energy sectors. The nine sectors are coal mining, oil and natural gas production, agriculture, electricity, manufacturing, construction, transportation and communication, commercial, and service.

An application of HE has been used to assess the impacts of carbon tax on the emission reduction and national economy. HE has also been used to evaluate the impact of the Clean Development Mechanism (CDM) in China. Four factors that help reduce emission are considered. These are economic structure adjustment, technical progress, energy structure adjustment and energy efficiency (He and Shen, 2002).

PRCGEM

PRCGEM is a static large-scale General Equilibrium model, composed of 118 sectors across 30 regions. The model’s main objective is to simulate and analyse trade liberalisation energy policy. When the user considers the substitution amongst energy factors and emission equations, PRCGEM also can be used to determine the impacts of environmental policy and CO2 reduction on the national economy.

The application of PRCGEM by the Institute of the Chinese Social Science academy and Monash University of Australia evaluated the cost of CO2 abatement under different abatement objectives. Under short-term assumptions the wage (cost of production for labour) is fixed and capital is limited within the same sector, therefore no equilibrium exists. Under the long term, the wage is variable and capital flows freely among sectors so that all factor markets are clear.

The limitation is that PRCGEM only considers the emissions caused by fossil fuel combustion, while the emissions in industrial processes and non-industrial sources are excluded. The carbon tax theme in PRCGEM is a unit tax on the carbon content in fossil fuel instead of CO2 emissions (Zheng and Fan, 1999).

TEDCGE

TEDCGE is a dynamic General Equilibrium model used to understand the impact of carbon tax. The national economy is divided into 10 productive sectors: agriculture, heavy industry, light industry, transportation, construction, services, coal, oil, natural gas and electricity. The production function is the nested constant elasticity of the production function with capital, labour and energy (coal, oil, and natural gas).

The application of TEDCGE has remained focused on analysing the impacts of carbon taxes on the market clearing prices of carbon. At different abatement levels, TEDCGE is used to calculate different additional investments for technology and estimate the marginal abatement cost function in China. TEDCGE is also useful in assessing the potential of the Clean Development Mechanism (CDM) in China (Wang et al., 2009).

CNAGE

CNAGE is a static General Equilibrium model. The production function is a constant return to scale Cobb-Douglas production function with the aggregation of labour, capital and energy to calculate GDP. The energy factor includes 19 commercial energies with 5 types suitable for final consumption. In this case, the investment structure is not adjusted according to different carbon tax levels. All carbon tax is assumed to be reinvested. Generation technology is assumed to be both independent to the energy cost, and energy consumption structure, and fixed within each sector.

This results in an identical growth rate for the consumption of different energy products in the same sector.

CNAGE is applied to analyse the short-term and long-term impacts of different carbon tax levels on the national economy and on different end-use sectors (Glomsrød, 1998).

3.2.2. Simulation and Input-Output Analysis

The second commonly applied classification of Chinese IAM research is Simulation modelling. Two commonly used models are YE (Michelsen et al., 2008) and Liang (Liang et al., 2007).

YE

The YE model is a dynamic input-output model and is based on the input-output table.

The input-output table is used in the analysis of industrial and economic structures, as well as in making economic forecasts. The table is a collection to account for what inputs of labour, capital and other factors of production are needed for a set of output and offers an economic snapshot of the country’ productivity. The input-output approach provides a useful framework for tracing energy use and other activities such as environmental pollution associated with inter-industry activity as specific inputs for labour and capital will also indicate the levels of GHG emission outputs. YE simulates various abatement scenarios and the impact this has on GDP levels and growth. Using input-output tables, YE projects the best reduction path under cumulative emissions control and the corresponding industrial structure adjustment and technical choice (Michelsen et al., 2008).

Liang

The Liang model performs input-output analysis with a built in function to evaluate difference scenarios. The model developed by the Energy & Environmental Policy Research (CEEP) accounts for the impact of different social economic factors on energy demand and energy intensity on climate change and the macroeconomy. Final energy demand is a function of average consumption per capita. Liang applied his model to run scenarios based different growth rates of population, urbanisation and average incomes (Liang et al., 2007).

3.2.3. Cost Minimisation and Detailed Energy-Sector Analysis

The third commonly applied IAM classification that has been specifically applied to understand China is cost minimisation. Four commonly used models which could aid Chinese energy policy makers are MARKAL, LEAP, AIM and 3E.

MARKAL

The MARKAL Model is a highly complex and detailed multi-period linear programming model of energy systems. MARKAL is a non-country-specific and flexible analytical model which can be adapted to different energy systems at national, provincial and local level. The Model assesses the overall energy system costs resultant of different energy policy stances. In other words, it is designed to determine the lowest cost method of satisfying energy demand. The objective function covers R&D investment costs. The cost function consists of energy exploitation costs, import and export costs, capital costs, operation costs, distribution costs of electricity, and transmission costs of heating.

Chinese institutions that have applied MARKAL include the Institute of Nuclear and New Energy Technology, Tsinghua University and Shanghai Environment Science Research Institute. One often cited adaptation of MARKAL was constructed by the Shanghai Environment Science Research Institute to estimate the repercussions of an adjustment in energy structures. These repercussion scenarios include changes in energy efficiency, generation and end-use (Chen, 2005).

LEAP

The LEAP model is a scenario-based energy-environment modelling methodology.

The model’s scenarios are based on a detailed accounting of energy consumption, which in turn drives energy generation under a range of assumptions on population, economic growth, technology and price. LEAP’s flexible data structure allows for an analysis with as rich technological specification and end-use detail as the user chooses.

LEAP has been applied by the Energy Research Institute, the Institute of Nuclear and New Energy Technology (INET), Tsinghua University, and Shanghai Environment Science Research Institute. In 1999, the Energy Research Institute adopted the LEAP Model for research on the sustainable development scenarios in China. In 2003, the Energy Research Institute (ERI) finished the research which generated three sustainable development energy demand scenarios (Zhou et al., 2003). More recently, the Shanghai Environment Science Research Institute adopted the LEAP Model to better understand low carbon emission development in Shanghai to reduce energy demand and air pollution. The model was used to make energy policy suggestions relating to health and pollution issues (Heaps, 2009). More recently, Imperial College London’s Grantham Institute for Climate Change also used the LEAP model with update inputs to study China. The research focussed on policy-relevant evidence to inform governmental decision making on avoiding dangerous climate change brought on by greenhouse gas emissions (Gambhir et al., 2011).

AIM

AIM, or the Asian Pacific derivative coined APAC-AIM, is an energy technology model which contains detailed accounts of generation technologies. The model evaluates technology and emissions policies. Carbon taxes and subsidies change the generation costs of different technologies. Since stakeholders adopt a minimum cost approach, the action to reduce costs for the end-user changes the preferences of energy use. The resulting reduction in energy use also reduces GHG emissions.

The ERI applies this methodology across the residential and commercial sectors. In these sectors, the Institute optimises the selection the effective technology combination selection based on generation costs (Jiang and Hu, 2003).

3E

The 3E model is a cost minimisation model, with the aim of reducing GHG emissions.

3E links emissions with the macroeconomy through an energy demand forecasting framework, with the objective function to minimise energy generation costs. The model is broken down into three components, namely the macroeconomic modules (MEM), end-use forecasting modules (EDFM), and energy system optimising modules (ESOM). MEM is a macro module used to estimate Chinese economic long-term development plans. EDFM is energy demand, or end-use energy forecasting module. It estimates demand according to energy intensity and substitutability between different forms of energy use. ESOM is a multi-period linear programme module based on an energy flow system.

Tsinghua University’s Institute of Nuclear applied this methodology. The Institute analyses the marginal costs, branch marginal costs, upfront expenses, upfront investment, and temporal distribution of expenses of CO2 emissions. They further analyse the energy structure shift and technical options open to different methods of CO2 abatement, and abatement costs under different energy development strategies (Michelsen et al., 2008).

In reviewing the existing types of IAMs specifically used to study China, there has been a preference towards general equilibrium, simulation and cost minimisation models. There are limited applications via welfare maximisation or Hybrid methodology that combined welfare maximisation and cost minimisation. This research explores the role of Hybrid IAMs as alternative tool for providing an additional modelling perspective to aid Chinese policy makers made informed energy decisions.