Policy Interactions and Underperforming Emission Trading Markets in

May 28, 2013 - Emission trading is considered to be cost-effective environmental economic instrument for pollution control. However, the ex post analy...
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Policy Interactions and Underperforming Emission Trading Markets in China Bing Zhang,†,‡ Hui Zhang,† Beibei Liu,† and Jun Bi†,* †

State Key Laboratory of Pollution Control and Resource Reuse, School of Environment, Nanjing University, Nanjing 210093, P.R. China ‡ Key Laboratory of Environmental Planning and Policy Simulation, Chinese Academy for Environmental Planning, Beijing 100012, P.R. China S Supporting Information *

ABSTRACT: Emission trading is considered to be costeffective environmental economic instrument for pollution control. However, the ex post analysis of emission trading program found that cost savings have been smaller and the trades fewer than might have been expected at the outset of the program. Besides policy design issues, pre-existing environmental regulations were considered to have a significant impact on the performance of the emission trading market in China. Taking the Jiangsu sulfur dioxide (SO2) market as a case study, this research examined the impact of policy interactions on the performance of the emission trading market. The results showed that cost savings associated with the Jiangsu SO2 emission trading market in the absence of any policy interactions were CNY 549 million or 12.5% of total pollution control costs. However, policy interactions generally had significant impacts on the emission trading system; the lone exception was current pollution levy system. When the model accounted for all four kinds of policy interactions, the total pollution control cost savings from the emission trading market fell to CNY 39.7 million or 1.36% of total pollution control costs. The impact of policy interactions would reduce 92.8% of cost savings brought by emission trading program.

1. INTRODUCTION China’s rapid industrialization has increased resource consumption, energy use and levels of pollution discharge.1 Growing criticism from the Chinese public and the international community has pressured the Chinese government to take actions toward reducing pollution to an acceptable level. Compared with the traditional administrative control approaches to pollution reduction, emission trading is considered a lower-cost alternative instrument.2 Early in the 1980s, China began discussing and piloting new projects for emission trading.3 In 1999, State Environmental Protection Agency (SEPA) and the U.S. EPA initiated cooperation on a study to assess the feasibility of introducing an SO2 cap and trade program in China. The project further explored the opportunities and obstacles to implementing an SO2 cap and trade program in the Chinese power sector; Benxi and Nanjing were chosen to be the locations for two pilots. The Asian Development Bank (ADB) also supported Taiyuan City in developing management methods for SO2 emission trading in Taiyuan in 2001. In 2002, SEPA began the “4 + 3+1” program, choosing Shandong, Jiangsu, Shanxi and Henan provinces; Shanghai and Tianjin municipalities; Liuzhou city and China Huaneng Group for pilots that would pursue total emissions control and emission trading. The 11th Five-Year Plan period © XXXX American Chemical Society

(2006−2010), which was contemporaneous with the shift of the National Environmental Protection Strategy from traditional administrative control approaches to the integrated use of administrative, legal, market and voluntary approaches. During this period, SEPA launched a pilot project of national environmental economic policies in 2007 to study and explore policies such as green credits, environmental insurance, green trade, environmental tax, ecological compensatio, and emission trading. Since 2007, the Ministry of Environmental Protection (MEP) and the Ministry of Finance have selected seven provinces to pilot emission trading programs in China.4 As was the case for many other emission trading programs, the ex post analysis of emission trading programs in China found that cost savings were smaller and the trades fewer than was expected at the outset of the programs.2,5,6 To date, there are limited cases of emission trading in those pilot programs.6,7 Dudek identified the flexibility of current emission trading policy, interference among different policies, and administrative interruption as the main barriers to the success of tradable Received: October 3, 2012 Revised: May 25, 2013 Accepted: May 28, 2013

A

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pollution markets in China.8 Researchers have noted that institutional arrangement or design of the emission trading policy has a decisive impact on cost-effectiveness based on ex ante and ex post analysis in other countries.9,10 These design issues include transaction costs,11,12 mechanisms for dealing with spatial and temporal relationships, initial allocations,13 market power, monitoring, and enforcement.2,14 In addition, most of the ex-ante analyses considered the emission trading system in isolation from the pre-existing system of environmental regulations. However, pre-existing distortions or regulations will also have impact on enterprises’ decision making, as well as emission trading.15 For example, in the case of the U.S. Acid Rain Program, all areas of the country must meet national health-based air quality standards that are distinct from the cap and trade program’s specific requirements. Thus, policy interactions are considered important barriers to introducing a new emission trading policy when poorly designed policy mixes resulting in undesirable overlaps.6,10,15−17 The emission trading policies would be operated in parallel with pre-existing regulations and to interact each other directly and indirectly.18 Policy interactions arise when enterprises in emission trading market directly affected by two policies overlap in some way or indirectly affected by one policy is also indirectly affected by another policy.19 Such policy overlap or double regulation usually entails some loss of flexibility on the part of firms in picking-up least-cost abatement options.19,20 Policy interactions and incompatibility issues between emission trading policy and other pre-existing environmental regulations, policies and instruments also appear to be important factors hindering successful policy innovation.19,21,22 Related factors or policies, such as environmental tax,15,18 electricity market19 and environmental quality standards19 et al., have been examined to investigate their impact on the performance of emission trading programs.19 In the case of water pollution trading programs, pre-existing water quality standards should be taken into consideration as a constraint for emission trading. Researchers provided different emission trading frameworks that meet preexisting water quality standards;23−25 this constraint will increase the transaction costs and reduce the cost savings. Thus, the introduction of emission trading requires capable of operating alongside existing policy instruments. However, there are obvious issues surrounding the compatibility and coordination of emission trading policy with pre-existing instruments.21,26 Since China’s regulatory system for pollution control is longestablished, some pre-existing policies will impact on the success of the new environmental policy instrument.6,16 Therefore, this research tried to examine whether the interactions between emission trading and pre-existing regulations will decline the effectiveness of emission trading programs. Taking the SO2 emission trading program in Jiangsu Province as a case study, this research tried to understand interactions between emission trading and other related polices in the next section. A basic simulation model of emission trading and investigate related policies that have an impact on emission trading are presented in Section 2. The simulation results of the SO2 emission trading program in Jiangsu Province are presented in Section 3, and a discussion of the impact of pre-existing policies on emission trading is presented in Section 4, as well as policy implications.

2. MATERIALS AND METHODS 2.1. Research Site. This research chose Jiangsu SO2 emission trading market as a case study. Jiangsu is the only province in China that has both an acid rain control zone and a sulfur dioxide control zone. In its 10th Five-Year Plan (2001− 2005), the annual average SO2 concentration of Jiangsu Province increased, as did the acid rain frequency. In 2005, the acid rain frequency reached 33.9%. In the 11th Five-Year Plan (2006−2010), the central government required Jiangsu Province to reduce SO2 emissions by 18% relative to 2005 levels. In the new 12th Five-Year Plan (2011−2015), Jiangsu province plans to reduce SO2 by 14.8% relative to 2010 levels. Emission trading is considered to be a feasible mechanism for achieving total pollution control target at a lower economic cost. A new SO2 emission trading measure will also be issued by the Jiangsu Environmental Protection Department in the near future. According to the Jiangsu emission trading program, every power plant will be issued a permit according to their SO2 discharge efficiency. Power plants should discharge no more SO2 than stipulated by the permit; however, the permits can also be traded between power plants. 2.2. Power Plants’ Decision Making in an Emission Trading Market. 2.2.1. Basic Model. A simple version of a cap and trade system can be explained as follows. A regulator determines the scope of the system (e.g., regions and sectors) and sets a limit, or cap, on the total emissions to be allowed. Economic agents are provided with emissions rights based on a certain standard, and each agent is required to hold the amount of rights corresponding to its emissions. If an economic agent does not hold enough emissions rights, it has to reduce its emissions or buy emissions rights from other agents who have a surplus. Power plants aim to abate SO2 emissions to levels below their emission rights and maximize profit. In contrast to traditional economic analysis, agents behave on the basis of local information. Each power plant considers the marginal profit (MP) function, SO2 emissions, emission rights, strategies, and pre-existing environmental regulations. Firms are free to trade permits at any time and may meet government standards by exercising pollution control or by possessing permits for their emissions. We assume that all power plants are profitmaximizing agents, there is no market power, and perfect monitoring and enforcement are available to the environmental regulator. We denote ei to be the unconstrained emissions in units per year, ri to be the pollution reduction in units per year by firm i, Ai to be the quantity of permits in units per year allocated to source i and xi to be the amount of emissions permits traded. Therefore, we have πi = gi(qi)pe − Ci(qi) − ci(ri) − pxi

(1)

Here, gi(qi) is the electricity production function and pe is the electricity price. The electricity production function is represented by gi(qi), which is assumed to be concave and twice differentiable everywhere.27 Ci(qi) is assumed to be the operation costs of power plant i. The emission abatement cost is ci(ri), for which ci′(ri) > 0 and ci″(ri) > 0. The total cost of emission control is ci(ri) + pxi. p denotes the price of emission permits. We assume that electricity generation is described by a homogeneous first-degree Cobb−Douglas production function, g(q) = Gqk, where G is a productivity parameter and k is a B

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emission rates to total emissions. Later, “two control zones” regions where acid rain and SO2 emissions are most severe were created to help improve management in these key areas. Finally, in April 2000, the People’s Congress adopted sweeping changes to the 1987 APPCL that incorporated the policies and measures developed during the 1990s and provide a stronger legal basis for policy implementation. These changes focus regulatory efforts on the most polluted areas, shift the emphasis of control from emission rates to total emission discharges, change the base of the pollution levy from excess emissions to total emissions, and establish emission permits as the vehicle by which national policy will be implemented at the local level. More recently, a number of additional environmental policies were adopted, including market-based instruments and technology and performance standards.29 (1). Total Pollution Control and Five-Year Plan. Until recently, China’s environmental governance system was largely based on a command-and-control regulatory approach that was well-suited to China’s planned economy and its hierarchical political system.30,31 The MEP and other agencies of the central government are primarily responsible for enacting policies, while enforcement is largely left to local governments.32 Thus, the top-down target responsibility system for pollution reduction goals has played an important role in environmental protection since the 10th FYP. During the 11th Five Year Plan period, the Chinese government emphasized the importance of environmental protection in its national development strategy by instituting goal-based pollution reduction, which included reducing SO2 and chemical oxygen demand by 10% from 2005 levels.33 According to China’s target-based pollution reduction program, the 10% SO2 reduction target was allocated across different provinces; the provincial governments subsequently allocate the reductions across different cities. To ensure that the overall target is met, the Central Committee of the Communist Party issued new rules regarding the promotion of local Communist Party officers and local officials.34 These new rules emphasize that environmental protection is an important criterion for promotion. If the failure to achieve these goals does not harm the leaders’ ranks, they face the risk of being removed from their original positions and placed in a more junior position. Conversely, achievement of the environmental protection goals could help promotion prospects.32 Thus, meeting the regional pollution reduction target becomes political task which ensures local governments work according to the agenda outlined by the central government. Thus, the total amount of emission discharge of all power plants in region j should be no more than the regional cap (RCj). Here, we set RCj equal to the total allocated permits of all power plants in region j.

constant determined by technology and power capacity for which 0 < k < 1. In addition, to make the model tractable, I assume that the operation costs (Ci) are continuous and linear in pc. Ci(qi) = φpc qi

(2)

Here,pc is the coal price and φ is the operation cost parameter. In addition, We also assume θi is the emission removal rate and α is the SO2 yield coefficient of coal. Thus

ri = eiθi = αiθiqi

(3)

ci is a function of θi and qi and is assumed to be concave and twice differentiable everywhere (ci′(θi) > 0, ci″(θi) > 0).

ci(ri) = ci(θi , qi)

(4)

The emission abatement costs are further assumed to be a function of the emission reduction and emission reduction rate:

ci = ϕα q θκ 1/1 − θi i i i i

(5)

Here, κ and φi are the parameters of the emission abatement cost function and θi is the emission abatement rate. All power plants are assumed to have the same value of κ but different values of φi. αiqiθi is the total emission reduction for power plant i. Finally, in most previous studies, the pollution levy is kept separate from the emission trading market. Firms do not need pay any tax or fee for emission discharge under the cap. However, there are also some countries, such as China, that have such a pollution levy system. According to China’s current environmental levy system, very firm i should pay the pollution levy ( fe), which is given by fe = αiqi(1 − θi) × pd

(6)

Here, pd is the pollution levy standard. Thus, in each period, a firm observes the electricity price (pe), permit price (p), pollution levy standard (pd), price of carbon fuel (pc), and allocated permits (Ai). A firm adopts a strategy in each period that is optimal from the firm’s perspective in that period. Thus, the firm’s strategy is a map from the Markov state ∧ = {P,A} to choice variables {qi, θi, xi}, where P is a price vector, i.e., P = {pe, p, pc, pd}. Here, θi is the emission removal rate and qi represents coal consumption. The set {qi, θi, xi} represents the three compliance strategies: abatement of emission, purchasing of allowances in addition to initial allocation, and adjustment of output levels. Let πi(P, Ai) denote the value of firm i. The maximization problem for the firm can be written as πi(P , Ai ) ≡ max[gi(qi)pe ‐φpc qi ‐ci(ri)‐pxi ‐pd αi(1‐θi)qi] θi , qi , xi

(7)

m

subject to

∑ αit(1‐θit )qit ≤ RCj

Ai + xi ‐αi(1‐θi)qi ≥ 0

(8)

0 ≤ θi ≤ 1

(9)

i=1

(10)

(2). Pollution Discharge Standard. In addition, the China government also regulates power plants by limiting emission concentrations. In 1991, China issued its first standard for power plants, the Emission Standard of Air Pollutants for CoalFired Power Plants (GB13223−1991). This standard set limits on SO2 emission rates according to the ‘‘effective stack height.’’.28,35 In 1996, the standards were revised by the MEP and the State Bureau of Quality and Technical Supervision (GB13223−1996) to focus on discharging concentration of SO2. For coal with a sulfur content less than 1%, the standard

2.2.2. Pre-Existing Regulation and Policy Interactions. Since the 1980s, China has been developing regulations, standards, and other various environmental policies to remedy its air pollution problem. Since 1995, the revised Air Pollution Prevention and Control Law (APPCL) placed an emphasis on reducing SO2 emitted by coal burning.28 The ninth Five-Year Plan (1996−2000) introduced the concept of Total Emissions Control, which shifted the focus of regulatory attention from C

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was 1200 mg/m3, while coal with a sulfur content greater than 1% had a limit of 2100 mg/m3. In addition, if the coal with a sulfur content greater than 1%, the power plant must be required added fuel gas desulfurization.36 In 2003, the urgency of air pollution problems made the MEP revise the emission standards again (GB13223−2003), establishing a limit of 1200 mg/m3 by 2010 for all power plants built before 1997. Those plants brought online in 1997 or later were required to meet a more stringent limit of 400 mg/m3.37 According to emission standards (GB13223−2003) and tighter requirements in Jiangsu Province, every power plant should abate more than 85% of SO2 emissions. In addition, during the 11th Five-Year Plan period, in order to increase the FGD’s operation rate, China began applying a price premium (0.015 RMB/kWh (0.0023 USD/kWh) for electricity generated at power plants with FGD technology.29 After that, Jiangsu’s operation rate reached of 97% in July 2007.38 Thus, we assume all of power plants in Jiangsu Province install FGD and meet the discharge standard. We have 0.85 ≤ θit ≤ 1

Ai + xi ‐αi(1‐θi)qi ≥ 0 m

∑ αit(1‐θit )qit ≤ RCj i=1

(15)

git (qit ) ≤ EGR i

(16)

0.85 ≤ θit ≤ 1

(17)

2.3. Market Simulation. To model the emission trading market, we designed a simple agent-based model. In the permit trading market, power plants make their trading decision based on their own information such as marginal profits, available permits, as well as other pre-existing environmental regulations. Power plants with the highest marginal profits are given priority to trade with the power plants with the lowest marginal profits. The model will stop when there is no feasible transfer remaining or none of the feasible transfers are profitable for the participants. The simulation program of the Jiangsu SO2 emission trading market is written using the NetLogo platform. 2.4. Data Collection and Parameters Initialization. Our research examines the SO2 emission trading market of power plants in Jiangsu Province. We chose 45 power plants in Jiangsu Province for the subsequent analysis. These 45 power plants accounted for 75.7% of the SO2 emission discharge of the electric power industry. Among those 45 power plants, two power plants (power plant 6 and 44) have plans to build new generating units. However, the new generating units must ask to buy permits from the emission trading market instead of having them allocated by the government. Data on initial allowances (A), electricity price (pe), coal consumption (qi), electricity generation and SO2 emission in 2006−2010 were collected from power plants and the Environmental Statistics System of Jiangsu. The pollution levy standard (pd) is set at 1.26 CNY/kg, in accordance with regulation in Jiangsu. The coal price (pc) is the average value of the commercial and power sector coal prices in China. The summary of variables pertaining to the Jiangsu SO2 emission trading market is listed in Supporting Information (SI) Table S1. Detail of the data and parameters initialization can be found in the SI.

(11)

(3). Electricity Generation Rights. In China, the SO2 and acid rain pollution control strategies interact with the Law on Coal, the Law on Electricity and the Law on Energy Conservation.39 Power plants in China are also restricted by electricity generation rights: power plants cannot generate more electricity than they are allocated.40 Before 2002, power plants had long-term contracts according to the Power Purchase Agreement with the electricity department. Since 2005, the electricity generation rights have been allocated and examined by government annually as an administrative permit. Power plants still cannot generate more electricity than their electricity generation rights allow. We set a plant’s electricity generation rights equal to its electricity generation in 2006. git (qit ) ≤ EGR i

(14)

(12)

Here, EGRi is the electricity generation rights of firm i. (4). Pollution Levy. Beyond traditional administrative control approaches, China is also applied pollution levy system to encourage power plants to reduce SO2 and other air pollutants. According to China’s Environmental Protection Law, all institutions and enterprises must pay the pollution levy according to their emissions volumes and concentration of discharged pollutants.41 In 1998, the State Council increased the SO2 discharge levy from 0.04 CNY/kg (0.006 USD/kg) to 0.21 CNY/kg (0.033 USD/kg). The pollution levy was also to be paid according to total SO2 emissions instead of only emissions above the standard. After several subsequent adjustments, the current SO2 discharge levy is 1.26 CNY/kg (pd = 1.26). Thus, China has a hybrid approach of pollution control, including price-based approach (pollution levy) and quantity-based approach (emission trading). The pollution levy will also impact on power plants’ pollution control strategies in emission trading market.42 To sum up, those existed policies will impact on power plants’ decision making on pollution control and emission trading. Thus, the maximization problem for the power plants can be revised as

3. RESULTS 3.1. Simulation Results of the Jiangsu SO2 Emission Trading Market in Isolation. To evaluate the proposed model of market and policy performance, we first examined the performance of a completely competitive emission trading market (Model-0 in Table 1) and compared it with the “command and control” scenario in which emission trading is not allowed. The equilibrium price in the Jiangsu SO2 emission Table 1. Summary of Emission Trading Models

πi(P , Ai ) ≡ max[gi(qi)pe ‐φpc qi ‐ci(ri)‐pxi ‐pd αi(1‐θi)qi] θi , qi , xi

(13)

subject to D

regional total pollution control policy

pollution discharge standard

electricity generation rights

pollution levy

policy conflict

∑mi = 1αit(1-θit)qit ≤ RCj

0.85 ≤ θit ≤ 1

git(qit) ≤ EGRi

pd = 1.26

Model-0 Model-1 Model-2 Model-3 Model-4 Model-5

√ √

√ √

√ √

√ √

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Figure 1. The market performance of Jiangsu emission trading market compared with the “command and control” scenario.

trading market is 5.46 CNY/kg, and the marginal control costs are equated across all agents. The total emission control costs decrease to CNY 3850 million when the market achieves equilibrium, thereby saving CNY 549 million in costs. The total emission control costs are 12.5% lower and profits are 1.2% higher compared with the “command and control” scenario (see Figure 1). 3.2. Simulation Results of the Jiangsu SO2 Emission Trading Market under Policy Interactions. A step-by-step analysis was carried out to examine the impact of policy interactions on emission trading market. We developed another five models (Model-1−Model-5) and compared the results to the results of Model-0, which did not take other pre-existing regulation into consideration (see Table 1). In Model-5, we incorporated all four pre-existing regulation into the emission trading model. Figure 2 presents the emission trading volume and permit price in the Jiangsu SO2 emission trading market. It is obvious that the policy interactions would prevent the market from achieving the global optimum, with the exception of the

pollution levy. Comparing the modeled four policy interaction scenarios, regional total pollution control target and pollution discharge standard would decline the total SO2 trading volume by 24.6% and 33.3%, respectively. On the other hand, the electricity generation right would increase the trading volume by 17.5%, while current pollution levy standard had no impact on the trading volume. When all of four policy interactions are modeled simultaneously, the emission trading volume is reduced to 5495 t of SO2, which is only 7.96% of the trading volume observed in Model-0. On the other hand, policy interactions also had significant impact on the permit price of Jiangsu SO2 emission trading market. The equilibrium price in Model-2, Model-3, and Model-4 were lower than price in Model-0. While in Model-1 and Model-5, different have different equilibrium price. For example, in the Model-2, the regional permit prices would different from each other (Figure 3). Liangyungang and Suqian had no price for no trading happened, while Taizhou had especially high price for including new generating units (power plant 44). Restricting emission trading will also reduce the cost savings of the Jiangsu SO2 emission trading market. Figure 4 presents the total emission control costs and cost savings of the Jiangsu

Figure 2. Emission trading volume and permit price of Jiangsu SO2 emission trading market.

Figure 3. Permit price in Model-2 while comparing to Model-0. E

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firm would meet the regulatory standard exactly and either sell excess permits or buy fewer than it would under cap-and-trade alone. The regulatory standard raises the firm’s cost of abating emissions without any resulting increase in overall abatement.” Recently, the MEP issued new emission standard of air pollutants for thermal power plants (GB 13223−2011), which set limits on SO2 emission 200 mg/m3. This will increase the compliance costs to meet the new standard, as well as the supply of permits. If the initial allowance is not adjusted, only the new built power plants (power plant 44) have transaction in Jiangsu SO2 emission trading market. 4.3. Electricity Generation Rights. In China’s planned electricity market, not only the electricity price, but also the electricity generation quota are decided by government. If power plants’ marginal profit of purchasing a permit is higher than the market price, they can increase electricity generation to obtain more profits. However, when electricity generation rights are taken into consideration, every power plant would be constrained such that they cannot generate more electricity than their generation rights allow. SI Figure S3 presents equilibrium electricity generation in Model-0 and Model-3; the EGR was also presented for comparison. The results showed that most power plants’ (42 of 45) final electricity generation in model-3 was lower than in model-0. The total electricity generation in Model-3 was only 65.6% of that in Model-0. The constraint on electricity generation also reduced demand for permits, which reduced the emission trading price to 3.43 CNY/kg. 4.4. Pollution Levy. Pollution levy (tax) is considered to be an alternative instrument for pollution control. Most research compared the cost-effectiveness between pollution levy (tax) and emission trading.44 While these two policies are existing simultaneously, it is considered to be policies overlap that similar emission sources are directly or indirectly covered by both tradable permits and a pollution levy.19 Ellerman (2002) pointed out that two instruments could coexist was depended on whether cap and trade is primary in pollution control.42 On the other hands, If the pollution levy is to be the primary instrument and set at a level high enough to bring the permit price down to zero, trade permits would be redundant.19,42 In the Jiangsu SO2 emission trading market, current pollution levy standard at a low level that would reduce the permit price. However, the pollution levy had no significant impact on emission trading system and cost savings. Thus, the pollution levy could coexist with emission trading system for other purpose.42 However, if we increased the pollution levy standard to a higher level, the pollution levy would reduce both the market price of a permit and the cost savings associated with the emission trading market (see SI Figure S4). As the pollution levy was increased, the permit price decreased; when the levy was set higher than 6.30 CNY/kg, the permit price was 0. In this case, permits would be traded to power plants 6 and 44; these plants have new units to build. 4.5. Policy Implications. The performance of an emission trading market will be determined by its design; however, interactions with pre-existing environmental regulations will also be very important. This research found that policy interactions generally had significant impacts on the emission trading system; the lone exception was the current pollution levy standard. When the model accounted for all four policy interactions, total pollution control cost savings from the emission trading market fell to CNY 39.7 million or 1.36% of total pollution control costs. The impact of policy interactions

Figure 4. Total pollution control costs and cost savings of the Jiangsu SO2 emission trading market.

SO2 emission trading market in each scenario. Both the pollution discharge standard and pollution levy increased the total pollution control costs, while electricity generation rights decreased the total pollution control costs and resulted in lower levels of SO2 emissions. The electricity generation rights mechanism had the most significant impact on the cost savings of the Jiangsu SO2 emission trading market; it reduced the cost savings by 56.6% relative to Model-0. When incorporating the effects of all four policy interactions, the cost savings were CNY 39.7 million, or 1.36% of total emission control costs.

4. DISCUSSION 4.1. Regional Total Pollution Control. Without a regional total pollution control constraint, power plants can trade across regions. SI Figure S1 presents the regional permit flows in the Jiangsu SO2 emission trading market. Yangzhou and Nanjing are two major cities which will purchase permits from other cities; Taizhou and Nantong will be net permit sellers. If cross-regional pollution trading is not allowed, the Jiangsu emission trading market will be divided into 13 regional emission trading markets. The local optima of the smaller emission trading markets cannot achieve the global (Jiangsu provincial) optimum; this fragmentation reduced cost savings by 24.6% relative to Model-0. Clearly, the market size is important for the success of an emission trading policy. Although the regional total pollution control target in Jiangsu is not based on environmental quality, such cross boundary regulation always ask policy-makers to make a trade-off between minimizing pollutant removal cost and avoiding “hot spots”.23,43 4.2. Pollution Discharge Standard. The hard constraints of the SO2 discharge standard will have an impact on power plants with high emission abatement costs because they cannot buy permits if their SO2 removal rate is lower than 85%. Of all power plants, 67% had an SO2 removal rate below 85% in Model-0 (SI Figure S2). When we impose the SO2 discharge standard on the emission trading model (Model-2), all power plants’ SO2 removal rate must be greater than or equal to 85%. The increased SO2 removal rate would increase the supply of SO2 permits, reduce demand for permits and lower the market price to 4.57 CNY/kg. Under these conditions, the Jiangsu SO2 emission trading market did not achieve the same equilibrium as in Model-0; total pollution control costs were 9.58% higher (see Figure 4). Levinson15 also point out that “if the permit price falls below the regulatory compliance costs for a firm, the F

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would reduce 92.8% of cost savings, which were brought by emission trading program. Thus, China should be careful in developing emission trading programs, including a potential carbon market. Designers of emission trading policy should also pay close attention to pre-existing environmental regulations, which were likely created without considering emission trading. There are some specific lessons learned from our analysis. First, because market size has a significant impact on the performance of emission trading market, a large-scale market should be designed in China. Given China’s pre-existing province-based total pollution control mechanism and regional pollution control strategies, the province level and regional level (such as the Yangtze River Delta) are potentially suitable scales for SO2 emission trading policy. Second, the electricity generation rights regulation would prevent power plants with a high marginal profit from buying SO2 permits from power plants with a low marginal profit. A generation right trading system for power plants is a possible instrument to help link emission trading and generation right trading.45 Third, the current pollution levy does not affect the emission trading amount and cost savings that the pollution levy and emission trading could coexist in China. But, pollution levy will impact on the allowance allocation and trading activities when it is set at a level high enough. Thus, it is also suggested that China’s carbon tax and carbon trading design should take policy interactions into consideration if China wants these two systems to be not mutually exclusive. Finally, this research did not examine the impact of emission trading on the other pre-existing regulations, further research should be focused on the aggressive performance of different policy mixes.

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ASSOCIATED CONTENT

S Supporting Information *

Additional information includes details on the data and parameters (SI-A and SI−B), as well as supplementary tables and figures. This material is available free via the Internet at http://pubs.acs.org.

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AUTHOR INFORMATION

Corresponding Author

*Phone/fax: 86-25-89680536; e-mail: [email protected]. Notes

The authors declare no competing financial interest.

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ACKNOWLEDGMENTS This paper is supported by the National Science Foundation of China (Grant No. 70903030) and Economy and Environmental Program for Southeast Asia (No. 106269).

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REFERENCES

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