China has been implementing stronger and integrated measures in an effort to reduce its Greenhouse gas (GHG) emissions since it became the largest CO2
emitter in the world in 2007 [1
]. Additionally, air pollution has become a major problem in many cities across the country. Cities are now facing serious environmental threats, including acidification, bioaccumulation of toxic metals, and contamination of water streams [2
]. One of the main challenges that China faces with regard to reducing its GHG and air pollution emissions is that it relies heavily on coal to meet energy demands. Coal usage accounts for 69% of the total energy consumption [4
]. Electricity generation, being primarily coal-based, is the main contributor to GHG emissions, accounting for 44% of the total CO2
]. Coal-fired power generation has also been associated with air pollution and a negative impact on health [3
]. Thus, the main contributor of both types of emissions is the electric power sector.
In collaboration with the USA, China has announced its most significant international commitments regarding climate change efforts, in which it has committed to peak its CO2
emissions and coal consumption by 2030 and 2020, respectively. China has also committed to decrease its CO2
emissions per unit of GDP by 40–45% by 2020, as compared to data collected for 2005. Additionally, the government has introduced specific measures with regard to GHGs and air pollution, which has resulted in some progress thus far. With respect to GHG emission reductions, the target goal set by the government was a reduction in energy intensity by 20% in the 11th Five Year Plan (FYP), which will be achieved by shutting down small and inefficient coal power plants [6
]. A reduction of carbon intensity by 17% between 2010 and 2015 was the target set by the government outlined in the 12th FYP [7
]. Similarly, specific targets have also been set by the government aimed at reducing environmental pollution. With regard to SO2
emissions, the target goal set by the government in the 11th FYP was a reduction in SO2
emissions by 10%, as compared to 2005 [8
]. The government expected to achieve these targets through the introduction of flue gas desulfurization devices and shutting down of small coal power plants. In the 12th FYP, the government set specific reduction targets for ambient concentrations of SO2
, and NOx
, of 10%, 10% and 8%, respectively, by 2015 as compared to the levels measured in 2010 [9
]. While many of these targets have been met, there are still difficult challenges ahead. For example, in the 11th FYP the energy intensity target was nearly achieved, reaching 19.1% [10
]. However, primary energy production grew by 31% and CO2
emissions increased by 34% [11
]. In the case of air pollutants, while reduction targets have been achieved, the current level of pollution is still higher than in other developed nations [12
Effective environmental policies can drive technology innovation, which in turn play a key role in achieving specific targets [13
]. In an effort to improve energy efficiency and reduce air pollution, the link between policies and innovation in energy-intensive sectors has been the focus of a few published studies. Most of these studies are based on bottom-up models. Balash et al. [15
] analyzed the impact of the potential command and control and market regulations on future electricity mix and generation, as well as CO2
and air pollution emission levels in the USA by using the market allocation (MARKAL) model. The results of the study illustrate that different regions have their own environmental regulation policy preference. The impact of CO2
emission targets and carbon tax on technology selection and demand in the power sector in Bangladesh was analyzed by Mondal et al. using the MARKAL model [16
]. The results of this study suggest that the application of such measures will favor the adoption of cleaner fossil fuels and renewables in the near future [16
]. In the case of China, there is extensive research that has focused on the impact of technology innovation on energy resource consumption and air emissions of the industrial sectors. For example, Zhang et al. [17
] analyzed the potential co-benefits of energy efficiency and emission mitigation in the iron and steel industries in China. Through the use of greenhouse gas and air pollution interactions and synergies model (GAINS) [17
], the study found that the introduction of end-of-pipe control options and the implementation of best available energy efficiency measures can help reduce GHG emissions and air pollutants. Cai et al. [18
] forecasted fuel consumption and associated it with CO2
mitigation in China’s thermal electricity sector from 2000 to 2030 using the “long-range energy alternative planning system” (LEAP) model. The results of this study indicated that if structural adjustments and technical mitigation measures in China’s electricity sector are not implemented, energy consumption and CO2
emissions in this sector will rise rapidly [18
]. Zhang et al. [19
] estimated the potential amount of CO2
emissions and air pollutants from the electricity sector in China in 2030 based on government regulations and external costs associated with emissions from coal power plants using the LEAP model. This study indicated that the application of such measures will promote advanced coal technologies and help reduce emissions [19
]. Yu et al. [20
] designed a technology-based bottom-up model in order to estimate the performance of China’s coal-fired electricity industry on energy resource consumption and environmental emissions and found that technology innovation is the determining factor in decreasing resource use and environmental impacts from electricity production. The majority of published studies have only considered the impact of specific measures on individual sectors but neglected to analyze the interactions of different industrial sectors in the entire economy. Additionally, these studies were conducted at the national level and utilized a bottom-up approach.
Other studies have focused on the co-benefits of GHG emission and air pollution mitigation policies. Tang et al. [21
] evaluated the potential co-benefits of CO2
mitigation policies on dust, NOx
emissions in China’s cement industry. The results of the study suggest that co-benefits could be achieved when the CO2
reduction target is set between 2.3% and 5.5% [21
]. Li et al. [22
] used historical data to analyze the aggregate effect of actual air pollution regulation on CO2
mitigation in the manufacturing industry in China. Their findings showed that SO2
regulations would reduce the price of carbon permits. Zheng et al. [23
] conducted an analysis of the air pollution reduction and climate change mitigation in the industry sector of the Yangtze River using the GAINS-China model. The results of this study showed that SO2
emissions would be under control by 2030 but NOx
emission would continue growing, while PM2.5
showed different trends for the three study regions. Liu et al. [24
] quantitatively evaluated and compared two categories of emission reduction instruments, carbon tax, and the mandatory application of end-of-pipe emission control measures, in China’s iron and steel sectors for CO2
, and NOx
using two soft-linked models. The results indicated that carbon tax can bring co-benefit for multi-pollutants to a certain level because the emission reduction rates are affected by the tax rates. However, their comparison was inconsistent because the technology was introduced in the iron and steel sector using the technology-based model but the carbon tax was applied in all of the sectors using the top-down Computable General Equilibrium Model (CGE) model. Zhou et al. [25
] developed an integrated top-down model which incorporated new technology as a new industry and a carbon tax in the thermal power sector. This paper builds on the study by Zhou et al. [25
] by incorporating different levels of a carbon tax rate and a technology reduction cost in the thermal power sector alone.
The purpose of this paper is to explore how carbon taxes, subsidies, and technology innovation promotion, both in isolation and combination, will impact the electricity mix, energy, environment, and economy under government environmental regulations. To address this question, we used a regional-dynamic input–output (I-O) model with detailed classified technologies in the thermal power sector to perform a policy comparative analysis.
The main advantage of the dynamic I-O model is that the data requirement is less than CGE [26
]. Additional data requirement of CGE increases the uncertainty of simulation result, especially for research at a regional level. The I-O model can help us track the consequence of external shock better than CGE because the substitution relationship within different commodity and production factors leads to complicated response of the CGE model system to external shocks.
Additionally, GHG emission by energy sectors has basically technical aspects, namely, energy efficiency in terms of GHG emissions and air pollutants. Economically, the model developed in this paper allows us to simulate and analyze the substitution among alternative technologies available currently and in near future. In contrary to traditional I-O and CGE models, in our simulation model, several constraints on resources (e.g., a GHG upper limit, air pollutant upper limit, etc.) are built and it is possible for substitution to happen in the market if alternative technology exists and/or the economic situation changes.
In this study, our dynamic regional I-O model combined the advantages of top-down and bottom-up models. The model incorporated detailed high efficient technologies and highlighted the potential and prosperous new industries in electricity sector in the near future, which is the advantage of bottom-up model. This method could eliminate possible inconsistencies by coupling top-down and bottom-up models via a simulation that clarifies both technology selection and assessment of such prosperous technology in the near future in terms of index of GRP, which clarifies the significance of new technology for stakeholders in monetary terms.
The wide gaps among regions in terms of technology development and environmental regulations contribute to the significance of the studies at the regional level. Thus, we chose the municipality Chongqing as a case study because it has been identified as a strategically important city, acting as a gateway for the development of Western China. Chongqing is the only central municipality (the other three are Beijing, Shanghai, and Tianjin), and it is also the most populated Chinese municipality. It is also a major economic, financial, and manufacturing center as well as a transport hub in southwestern China. Rapid economic development, coupled with the use of traditional, inefficient, thermal power generation will have an environmental as well as a socio-economic impact on the city. This makes identifying the optimal policy measures at the economic–environmental–technological level for Chongqing an urgent and important matter.
The rest of the paper is organized as follows: climate change and pollution mitigation challenges are introduced in Section 2
. The methodology is described in Section 3
. The results and discussion are presented in Section 4
. Finally, the conclusions drawn and the policy implications are highlighted in Section 5