Comprehensive Analysis of the Environmental Benefits of Introducing Technology Innovation in the Energy Sector: Case Study in Chongqing City, China

Because of the serious damage caused by acid rain, Chongqing city was designated as an Acid Rain Control Zone by the Chinese Central Government. The main factor responsible for the acid rain is the ever-increasing emission of sulfur dioxide (SO2) due to utilization of coal as the primary energy source to meet increasing energy demand. Simultaneously, CO2 emission has dramatically increased with coal utilization. In order to transform the current energy structure, alternative renewable energy technologies must be identified and proved feasible and effective. This research aims to comprehensively analyze the benefits of small-scale hydropower and wind power technologies to reduce SO2 and Greenhouse gases (GHG). For this purpose, we constructed a dynamic comprehensive evaluation model based on an Input-Output (I/O) analysis for the period 2010-2020. The simulation results indicate that the introduction of small scale hydropower and wind power technologies have a positive impact on Chongqing’s socio-economic, environmental and energy development in the first half of the study period. However, the results also show that the scarcity of renewable energy technologies to meet the increasing energy demand as well as the stricter emission constrains affect both economic growth and SO2 and GHG reduction efforts from the latter half of the study period. To address this weakness, the study suggests that additional advanced renewable energy technologies are necessary as well as specific regulations to meet air pollution reduction targets. Last but not least, some feasible policies are proposed by analyzing the potential economic benefit of reducing air pollution and GHG emissions in terms of improved quality of life and environmental conservation. We argue that these benefits could offset the lower GRP growth obtained by the proposed policy.


Introduction
The access to a stable energy supply is a very important condition to achieve sustainable development.China has largely relied on the utilization of fossil fuels, especially coal, as a primary energy source to meet increasing demand for economic development.This situation has led to an inappropriate energy consumption structure.Furthermore, environmental degradation including acid rain associated with this unsustainable energy structure is becoming more prominent, with the rapid economic development.Renewable energy, an effective tool in reducing SO 2 and GHG emissions and in providing energy supply, has attracted increasing attention worldwide as clean energy resource (Dincer, 2000;Menegaki, 2008;Zheng, Zhang, Yu, & Lin, 2011).Chongqing is a typical area in this respect; almost all of its energy comes from fossil fuels particularly coal.The proportion of coal to the total energy utilization was 70 % in 2010 (Chongqing Municipal Bureau of Statistics, 2011).The reliance on coal for energy supply has caused environmental problems including acid rain and air pollution in addition to the rapid increase in GHG emissions.It is significant for Chongqing to introduce renewable energy technologies to improve the local energy structure while achieving the SO 2 and GHG emission targets set by the Chinese Central Government.Chongqing is located in Southwest China, where the distribution rate of economically exploitable hydro resources in China is 58.9 % (Huang & Yang, 2009).This means hydropower will be an important potential renewable energy contributing to energy structure transformation.Additionally in the "12 th Five Year Plan", the Chongqing government plans to introduce wind power technologies to promote the wind power industry.In this process, evaluation of candidate renewable technologies is a significant step for government policy-makers to decide budget allocation, mitigation plans, energy and economic development.Consequently, the specific objectives of this study are to comprehensively analyze the impact of small-scale hydropower and wind power technologies to explore renewable energy potential in Chongqing and the feasibility of introducing these technologies.We chose the "Chongqing Siyangping 49.3 MW Wind Power Project" and the "9.6 MW Xiaohe Small Hydropower Project, China", registered CDM projects as reference for the potential of renewable energy introduction."Renewable technologies" refers to these two kinds of technology projects in this paper.
Recently, many studies employing Input-Output models have been undertaken to comprehensively evaluate policies which act as a motivation to make optimal balance between economic development and environmental protection.Mizunoya and Higano (1999) simulated an optimal tax-subsidy to reduce air pollutant (CO 2 , SO 2, NO x ) emissions in Japan.Li et al. (2012) analyzed the impact of a recycling tax on metal recycling and GHG emission.Sakurai et al. (2003) proposed an environmental tax rate to maximize GDP under restriction of GHG emission based on an I/O model.Li and Higano (2004) simulated the best environmental tax rate for policies to introduce renewable energies for emission reduction in China.Wang et al. (2012) investigated an environmental tax to develop biomass power technologies for GHG mitigation.
However, limited research has been undertaken to comprehensively evaluate the benefits of renewable energy technologies via a simulation model and later identify the feasibility of introducing them.In this study, we propose an integrated environmental management policy using a computer simulation that includes the introduction of renewable energy technologies to improve the air quality in Chongqing and minimize GHG emissions while achieving optimal economic development.Three sub-models (material flow balance model, socio-economic model and energy balance model) and one objective function, gross regional product (GRP), were included in the simulation.The paper also describes the methodology of the Input-Output model and puts forwards a comprehensively initial policy analysis.

Method
This paper focused on building a comprehensive simulation model system to forecast environmental improvement potential based on input-output table and balances simulating social, economic and environmental developments.The simulation model considered significant factors, such as GRP growth, energy consumption and the existing individual sub-sectorial policy targets.
This study utilized an optimization simulation model, comprising dynamic linear LINGO programming, to evaluate the impact of the renewable energy technologies on gas emission reduction along with optimized economic development in the research area.The comprehensive simulation model can precisely estimate the benefits that may result from social, economic, and environment policy decisions.

Scheme of the Simulation Model
The simulation model is composed of 3 sub-models (socio-economic model, air emission model and energy demand-supply model) and one objective function (Figure 1).Chongqing's social and economic activities provide the simulation base and reflect real social and economic development.Three economic agents (industry, household, government) were assumed in this research.Figure 2 shows the commodity, SO 2 and GHG flow between economic agents.Based on the relationship between economic agents, we design the comprehensive evaluation model.As shown in Table 1, there are four big industries in the model.Each industry contains several sectors.We calculated the input coefficients between economic agents based on "2010 Input-Output table of Chongqing".

New energy substitution
Energy demandsupply balance model

Social-economic Model
Max GRP

Industry Consumption
Wind energy industry

High energy consumption and high emission industry
GHG and SO 2

Design of the Simulation Model
In the simulation model, the variables are divided into endogenous (en) and exogenous (ex).The exogenous parameters are calculated based on current data; the endogenous variables will be determined by the model structure.The research period is 11 years, from 2010 to 2020.The selection of the research period was based on the availability of specific government targets for both SO 2 and GHG emissions.The objective function of this simulation is to maximize GRP of the study area and it can be formulated as: Where, GRP (t) is the gross regional product in term t (en), X i (t) is the production of each industry i in term t (en) and  is the social discount rate.V i is the value-added rate of industry i (ex).The objective function is subject to the following constraints.

Balance of the Material Flows
In Formula 3, the left side represents the supply and the right side represents the demand.Usually, the supply is not lower than the demand.The input coefficient of production is calculated based on the 2010 input-output table of Chongqing.: export of each sector in industry i (ex, column vector)   i M t : import of commodity of each sector in industry i (en, column vector)

Energy Flow Balance
The energy supply in left side is not lower than the energy demand from industries, household consumption, export and import.
Where ( ) e X t is energy supply and ei A is input coefficient

Value Balance
The left side of the formula is the income and the right side includes expenses.The income of each industry is equal to the expenses.
(5)   i P t : price rates of each sector in industry i (en, row vector) h i Y (t) : national income of each sector in industry i (en, row vector) i δ : depreciation rate of each sector in industry i (ex, row vector ) i τ : indirect tax rate of each sector in industry i (ex, row vector)

Air Emission Balance
Gases are emitted by industrial activities, household and government consumption.

Case Setting
In this paper we adopted SO 2 and GHG (Table 2) as the environment control index in simulation and used it in the case setting.We proposed four different cases ranging from business as usual (BAU) to emission constrains and the introduction of renewable technologies as shown in Table 3.
We set Case 0-∞ as the BAU scenario without renewable technology introduction and gas emission constraints; that is, the case based on forecasting and analyzing the economic trends in Chongqing during the period 2010-2020.Specifically, in order to demonstrate the contribution of renewable technologies to local development, emission restrictions compared with the base year are proposed in the alternative models as shown in Case 0-200 %, Case 1-200 % and Case 1-150 %.For instance, Case 0-200 % means the amount of gas emission each year is not larger than twice the amount emitted in 2010.In case setting, we selected 2 and 1.5 times the emission amount in 2010 as the emission upper boundary.We did this selection based on the fact that lower emission constraints would result in extremely low GRP growth.
In this paper air emissions are divided into air pollutant gas and GHG.In case setting, "Yes" does not necessarily mean that the renewable technology is adopted.After the technology assessment through the simulation, if the technology has advantage, it will be adopted.

Results and Discussion
Four scenarios are established to evaluate the environmental and economic benefits of introducing renewable energy technologies.The simulation provides an effective approach to estimate gas emission, economic and energy utilization trends through the comprehensive system.Compared with the actual social-economic and environment development, the simulation system is proved as an effective tool in technologies and policies assessment.

Air Emission Trends
The simulation results indicate that along with high economic growth rate (17.7 % in 2010), the air pollution and GHG emissions will inevitably increase.As shown in Figure 3, the CO 2 -e amount and emission trends are increasing with a high growth rate in BAU scenario and reach 1.42 billion tons in 2020, which is more than 7 times the amount in 2010.To put in perspective, the total CO 2 -e emission amount in Chongqing city under BAU conditions will be more than the current GHG emissions in Japan that reached 1.261 billion tons in 2011.In addition, SO 2 emissions also increase with a high growth rate reaching 5,073,510 tons in 2020 in the BAU scenario (see Figure 4).However, in the alternative scenarios the emission trends keep a low growth rate with the emission constraints as shown in Figure 3 and 4. By comparing the emission amount of BAU and case 1-200 % the total reduction could reach 5.64 Billion Ton CO 2 -e and 16,323,223 Ton SO 2 in the research period (2010-2020).To have a clearer idea about the amount of emission savings we can state that these emissions are equivalent to 55 % of the total CO 2 -e emissions and 59 % of the total SO 2 emissions in China in 2010 (Zhao, Zhang, & Nielsen, 2012).
Many factors that contribute to the emission trends were shown in Figure 3 and 4. Firstly, from model perspective, we maximize total products added-value in each industry (Equation ( 1) and ( 2)) in the study period as the objective function and the gas emissions amount are decided (Equation ( 6)-( 11)) by the emission intensity and product in each industry.The gas emission intensity of each industry is constant and calculated on IPCC Guidelines for National Greenhouse Gas Inventories (2006) (Eggleston, Buendia, & Miwa, 2006) and Chongqing energy consumption statistic in Yearbook 2011.Therefore, the gas emission amount is mainly decided by the product value in each industry if there is no emission constraint (Figure 3, 4 and 6: BAU emission trend).On the contrary, the gas emission constraints will have an impact on economic development (see Figure 8).Secondly, the energy technology introduction in this research pushes the renewable energy industry development which not only contributes to both SO 2 and GHG emission reduction (Figure 3 and 4) but also to moderate economic development (Figure 8 and 9).
Simultaneously, introducing technology innovation in the energy sector creates multiple benefits.Firstly, although many researches have been undertaken to measure the economic cost of climate change and air pollution (Haines et al., 2007;Matus et al., 2012), some benefits and costs do not have monetary values, such as quality of life, extended life span, good health, etc. From an environmental and health perspective, the CO 2 -e emission reduction potential of 5.64 Billion Ton (see Figure 3) in the research period (2010-2020), compared with BAU and case 1-200%, contribute a lot to climate change mitigation.Climate change may be considered as a key factor for environmental change, exposure to health risks and pathogens (Pascal, Viso, Medina, Delmas, & Beaudeau, 2012).China's rapid development has come at the cost of severe environmental degradation: outdoor air pollution is associated with more than 300,000 deaths, 20 million cases of respiratory illness, and a health cost of more than 500 Billion CNY (more than 3% of gross domestic product) annually (Millman, Tang, & Perera, 2008).Chongqing air quality is worse than China's average level; the health loss would be much more serious than whole country average level (Andrew, 2012).
In addition, the introduction of renewable energy sources will not only reduce the emission of SO 2 but also other pollutants associated with fossil fuel consumption such as Hg, TSP, PM, etc.This will further contribute to improving quality of life and the environment.
Secondly, fossil fuels are non-renewable that will eventually become scarce and will become too expensive or too environmentally damaging to retrieve (Menegaki, 2008).Renewable energy utilization can increase fuel diversity and energy independence and could be an effective solution to mitigate the impacts of price fluctuation brought by economic or political instabilities.
Thirdly, from the economic development perspective, gas emission constrains and the introduction of renewable energy technology will push the high emission intensity sectors to adopt advanced technologies to improve production efficiency.In the long run, it promotes cleaner production -high value-added industries development and realize the development of the whole society.Figure 4 shows SO 2 mitigation potential 16,323,223 Ton contributed by gas emission constrains and energy technology introduction.

Reduction Rate of GHG Emission Intensity and SO 2 Emission Amount
The Chinese government set the target to reduce the total amount of SO 2 emissions by 8 % in the year 2015 compared with 2010 (KPMG China, 2011).The Government also set the goal to improve the GHG intensity by 17 % in 2015 compared to 2010 and between 40-45 % by 2020 compared to 2005.
In this study, we take the GHG emission intensity and SO 2 emission amount reduction rate by 2015 clarified in the "12 th Five-Year Plan" as specific short-term targets.Comparing the reduction rate by 2015 of the proposed scenarios with the target, we can identify the policy strengths and weaknesses in each scenario.This is an effective way to evaluate the policies and help improve them, which is the necessary process to achieve the 2020 climate objective which China committed to at the Copenhagen Conference in 2009.

Figure 5. GHG emission intensity reduction and deviation from target in four scenarios
Figure 5 shows the GHG emission intensity reduction rate from 2010 and 2005 and their target by 2015 and 2020 in the four scenarios.Except for the BAU scenario, all proposed scenarios achieve the government target clarified in "12 th Five Years Plan".In addition, the reduction rates in technologies introduction scenarios are much higher.This result suggests that the introduction of renewable technologies is necessary in pursuing sustainable development.GHG intensity reduction rate (%) Figure 6.SO 2 emission reduction rate and deviation from target in four scenarios Figure 6 shows the SO 2 emission rates reached by 2015 in the four scenarios and government target by 2015.Compared with government target (more than 8 % reduction) clarified in "12 th Five Years Plan", the simulation result shows that no scenario will achieve the government target.However, the BAU scenario has a much wider gap with the government target; the total SO 2 emissions will almost triple compared with case 1-200 %.This poses an almost impossible challenge to overcome for Chongqing.While the other scenarios also show an increase in the SO 2 emissions, it would be much easier to improve the situation with the gas emissions constrain and technologies introduction.Based on the experience of other countries, it is possible to reduce the SO 2 emission amount significantly by the installation of SO 2 trapping technologies such as the flue-gas desulfurization devices (FGD) and introduction of monitoring regulation which guarantee that these devices operate efficiently based on Case 1-200 % or Case 1-150 % (Xu, Williams, & Socolow, 2009).The introduction of alternative renewable technologies (such as biomass technologies) as well as specific regulations to address air pollution (such as FGD for SO 2 and selective catalytic reduction for NO 2 in coal power plants) is expected to eliminate the gap gradually.
Case 1-200 % can be seen as the optimal proposed scenarios since the simulation result shows that its total GRP is the largest one under the same gas emission constraints, and the reduction cost is the lowest.Therefore we will analyze the economic-environmental benefit and energy conservation for Case 1-200 % to prove the feasibility of achieving the local government plan.In this case, gas emission control and the amount of renewable energy utilization can be used as guidelines in achieving optimal development.
The environmental and social benefits of introducing emission constraints and renewable technology will greatly benefit Chongqing in the long run offsetting the economic loss caused by lower GRP growth rate (see Figure 8).Compared with BAU, average GRP loss in case 1-200 % is 2.29 % annually (see Figure 7), which could be lower than the potential economic benefit associated with the reduction of 5.64 Billion Ton CO 2 -e and 16,323,223 Ton SO 2 .Dones et al. (2005) estimated the external cost of CO 2 -e and SO 2 per ton in the Year 2000 in EU as 19 € 2000 /ton CO 2 -e and 2939 € 2000 /ton SO 2 .Based on their research we can calculate that the saving cost from both CO 2 -e and SO 2 emission would be 1,223.96Billion CNY.In the long run, if we include the impacts of other pollutants associated with coal power generation such as NO x , Hg, PM2.5, etc; the external cost could be much higher in BAU scenario.In fact Andrew (2012) estimated that the annual cost of pollution amounts to 3% of the total GDP in China and the quality of life is a very important factor that must be taken into consideration.

Economic Development Trend
Under the SO 2 and GHG emission constraints, GRP in Chongqing showed steady improvement since 2010.It is clearly shown in Figure 7 that the total GRP amount is much higher in BAU than other cases.This means the introduction of SO 2 and GHG emission constraints will affect economic growth.However, as we mentioned in discussion before, the decrease in economic growth can be more than compensated with the benefits of much better quality of life in terms of human and environmental health at the local level as well as climate change mitigation at the global level.
Case 0-200 % and case 1-200 % are cases with the same SO 2 and emission constraints.The difference between them is that the latter has renewable technology introduction; there is a GRP increase from case 0-200 % to case 1-200 %; the contribution of renewable technologies to economic development is significant.The gap between them is 993 Billion CNY.From case 1-200 % to case 1-150 %, although the gas emissions are reduced, the total GRP amount and increase rate declined.The reason is that along with stricter limitations on gas emission, economic benefits are sacrificed for environment conservation.Although the renewable technology's contribution can achieve dual targets of economic development and environment protection (Figure 7: case 1-200 %), as it has stricter limits for gasses, it cannot be effective (Figure 7: case 1-150 %).
Figure 7.Total GRP amount with air emission reduction from 2010 to 2020 From the GRP trends (Figure 8) in case 0-200 %, case 1-200 % and case 1-150 %, we can see the overall rate of increase in the GRP is higher during the former half (2011)(2012)(2013)(2014)(2015) than the latter half (2016-2020).There are 3 key drivers that contribute to that result.The first one is industries adjustment between high emission intensity sectors and low emission intensity ones; the second one is the introduction of renewable energy technologies and the third one is GHG, air pollutants emission constraints implemented through "12 th Five Years Plan" of Chinese Central and local governments.The simulation result shows that in the first 5 years two scenarios (case 1-200 % and case 1-150%) achieved government GHG emission intensity reduction rate mitigation target clarified in "12 th Five Years Plan" with a high economic development trend (see Figure 8) which is similar with BAU's.Simultaneously, while SO 2 emissions increase in the proposed scenarios, these increases are much lower than under BAU situation.In addition, they can also contribute to climate change mitigation caused by GHG emission, human health protection and air pollution reduction.The proposed policies in case 1-200 % and case 1-150 % are significant to realize both environmental and economic benefit in Chongqing.
In the first 5 years, the 3 key drivers mentioned above act as the different important roles to mitigate GHG and SO 2 emission (see Figure 3 and 4) and promote economic development with a high growth rate.The main benefit comes from the industry structure adjustment between high emission intensity sectors (such as: high energy consumption and high emission industries, traditional energy sector) and low emissions intensity departments (such as: manufacture of communication equipment, computers and other electronic equipment sector).In other words, the technology introduction will not only benefit by keeping economic growth with a high rate, but will also help reduce GHG and SO 2 emission compared to BAU as shown in Figure 3 and 4.
From the economic development trend in Figure 8, we can find the GRP gaps compared with BAU mainly happen in the period 2016-2020.This gap can be explained by two main reasons.First of all, GHG and SO 2 emission constrains affect economic development if there is no technologies innovation in any sector.Secondly, the potential small-scale hydropower and wind power capacity is limited.However, the policies contribute to GHG and SO 2 emissions reduction, which benefit to mitigate climate change and improve quality of life.
Therefore, from 2016, we need to consider other renewable energy sources such as biomass energy, and cleaner power generation technologies (IGCC) or cleaner fuels such as natural gas in addition to pollution control devices.

Renewable Energy Utilization Trend in Electricity Power Sector
We ran the simulation to find the renewable energy utilization potential from 2010 to 2020.With economic development and financial support in research areas, as shown in Figure 9 the total renewable energy usage amount is growing for the first 4 years.From 2014 the amount of renewable energy reached the upper boundary of local renewable energy capacity.The simulation results indicate that along with economic development, much more thermal power is necessary to support social economic development.That's why the rate of the constant renewable energy to total energy consumed decreases from 2013 to 2016.However, the thermal power industry which has a high gas emission coefficient cannot produce power according to demand as the gas emission constraints and industry structure adjustment acts as an effective tool to realize dual target from 2016 to 2020, which contribute to the rate of renewable energy power to total energy power increasing from 2016 to 2020.However, the absolute amount of renewable energy does not change from 2014.This simulation result shows that current technology will not be adequate to support a continued increase in energy demand in the latter years.This result calls for technological innovation to provide multiple scenarios for local development, such as the introduction of cleaner energy technologies to improve the efficiency of fossil fuel utilization.Rate of windpower to total energy power Rate of hydropower to total energy power

Conclusion
In this paper, we used a comprehensive simulation model to find out the impact of introducing renewable technology to reduce GHG and SO 2 emissions and explore renewable energy resources.This study demonstrated that Chongqing can effectively address climate change and air pollution challenges by adopting an effective policy that combines emission restrictions and the introduction of renewable energy technologies.However, the environmental and health benefits were achieved at the expense of lower GRP growth.
From the scenario analysis, case 1-200 % provides benefits in terms of decreasing air pollution and increasing renewable energy utilization.The renewable energy can contribute to economic growth indicated by the simulation result.When the amount of gas emissions each year is not larger than twice of that in 2010, moderate economic development can be achieved; total GRP is 19,884 billion CNY, 993 billion Yuan more than case 0-200 % without renewable technology introduction.The simulation result found that the limitation of wind power and hydropower supply capacity will not be able to meet the energy demand in the study area affecting the economic growth of the region (less than 4 % growth) from the year 2017.
A rapid and effective solution to drastically reduce SO 2 emissions could be possible by introducing SO 2 trapping-technologies in the current coal power plants or by using clean coal.In the long term, renewable energy technologies introduction to explore renewable energy source could help achieve environmental objectives.This approach could not only benefit in terms of GHG and air pollutant mitigation, but also improve economic development and promote technological innovation.Emissions reduction will result in direct and immediate health benefits, especially for children.The benefits will accrue over their entire lifetime.Further research is necessary to analyze the economic benefit of improving the environmental and health quality in terms of reducing costs in health provision and improving the quality of life and determine if this benefit could balance the lower GRP obtained with the alternative scenarios.
This research has some limitations that call for follow-up research.Hydropower and wind power are not constant, which are affected by the climate and seasons.Electricity produced by them can be variable.Energy storage will be another urgent problem.Hydrogen and fuel cell technologies could offer solution to tackle the energy storage problem.Further studies will consider about introducing hydrogen and fuel cell technologies.In addition, we must also include NO 2 emissions that have increased very rapidly due to motorization.

Figure
Figure 3. GHG Emission from 2010 to 2020

Figure 8 .
Figure 8. GRP trends with SO 2 and GHG reduction from 2010 to 2020

Figure 9 .
Figure 9. Trend of renewable energy utilization rate from 2010 to 2020

Table 1 .
Classification of industries in the model

SO 2 and GHG emission flow model
Constraints on the Amount of SO 2 and GHG Emission 10) 2 CO i IE : CO 2 emission coefficient of industry i (ex, row vector) 4 CH i IE : CH 4 emission coefficient of industry i (ex, row vector) 2 N O i IE : N 2 O emission coefficient of industry i (ex, row vector) 2 4 SO IE : SO 2 emission coefficient of renewable energy industry i (ex, row vector) 2 CO CE : CO 2 emission coefficient of consumption subject (ex, scalar)   2 CO W t : total amount of CO 2 emission (en, scalar)   4 CH W t : total amount of CH 4 emission (en, scalar)   2 N O W t : total amount of N 2 O emission (en, scalar)   GHG W t : total amount of GHG emission (en, scalar) 2.2.5 b: the upper bound emission (ex, column vector) 2.2.6 Government Income and Expenses In the formula 12, the right side represents the government revenue.It consists of direct taxes and indirect taxes.The government expenses include consumption, saving and capital depreciation.

Table 2 .
Types of air pollutants