Decomposition of Net CO 2 Emission in the Wuhan Metropolitan Area of Central China

Policy-makers have been sharing growing concerns that climate change has significant impacts on human society and economic activates. Knowledge of the influencing factors of CO2 emission is the crucial step to reduce it. In this paper, both CO2 emission and CO2 sink on a city-level of the nine cities in Wuhan Metropolitan Area are calculated using the Intergovernmental Panel on Climate Change approach. Moreover, the logarithmic mean Divisia index (LMDI) model was employed to decompose the net CO2 emission from 2001 to 2009. Results showed that (1) the largest amount of CO2 emission comes from energy while the largest amount CO2 sink comes from cropland; (2) economic level (S) was the largest positive driving factor for net CO2 emission growth in the Wuhan Metropolitan Area, population (P) also played a positive driving role, but with very weak contribution; and as negative inhibiting factors, energy structure (E) and energy efficiency (C) significantly reduced the net CO2 emission.


Introduction
Policy-makers have been sharing growing concerns that climate change has significant impacts on human society [1].Increasing greenhouse gas (GHGs) emission, driven by economic growth, makes government create sustainable economic schemes which decouple GHG emission and development, and knowledge of its influencing factors is of crucial importance for CO 2 emission reduction [2].Approaches that are popularly used for CO 2 emission decomposition are mainly the Divisia index and Lyspeyres index.Despite being more complicated, the logarithmic mean Divisia index (LMDI) model is a preferred method than the other six index decomposition methods for its sound theoretical foundation and obvious improvement in achieving a more scientific result in the 1990s [3].Decomposition index analysis originated from the early 1970s after the world oil crisis [4]; since then it has triggered the interests of researchers and analysts.
The above researched have done excellent work to decompose CO 2 emission, however, limitations still exits: (1) Most decomposition work was done to decompose CO 2 emission from one sector, rather than total CO 2 emissions from all aspects of human society and economic activities.The main advantage of a society-wide approach over a sector-wide approach is its ability to provide a fuller account of a region's carbon footprint and to identify relative potentials (e.g., sinks), as well as challenges (e.g., emissions).Recent decomposition CO 2 emission from one sector (energy/transport/manufacture, etc.) of Beijing, Shanghai, Chongqing, and Guangzhou have been well documented in previous studies [25,31], and have provided useful information for policy aiming to mitigate sector-wide emissions.In this study, we take a society-wide approach to assist carbon policy-making in a broader context; (2) though national studies are well-document by the need for cooperation among nations to solve this global environmental problem, they are not specific enough to conduct carbon trading at present [32].Carbon reduction action happening on the local level will lead to more impractical effects when a carbon emissions trading system is imposed.Specifically, in-depth local knowledge on CO 2 emission, rather than aggregated information at the national level, is what is needed most when designing and implementing a pilot carbon trading market in pilot cities, including Wuhan; and (3) for the several analyses conducted on the city level, their work decomposed the total CO 2 emissions rather than net CO 2 emissions, which neglected CO 2 sinks and made the decomposition work inaccurate.To our knowledge, little attention has been paid to decomposition net CO 2 emission at the city level in China.
Therefore, in this paper, (1) both CO 2 emissions and CO 2 sinks will be taken into account by containing four sectors and 27 subsets of main CO 2 sources, and four sectors and 13 subsets of main CO 2 sinks; (2) the composition work will be done at the city level, which will include the nine cities of the Wuhan Metropolitan Area; and (3) the net CO 2 emissions from 2001 to 2009 will be used for decomposition.
The Wuhan Metropolitan Area is composed of Wuhan and eight other cities within 100 km; they are Huangshi, Ezhou, Huanggang, Xiaogan, Xianning, Xiantao, Tianmen, and Qianjiang (Figure 1, obtained from the official website of Hubei Provincial People's Government: http://www.hubei.gov.cn/).The whole area is 58.1 ˆ10 3 km 2 , with a population of 30.24 ˆ10 6 .Its GDP exceeded 1000 ˆ10 9 Yuan in 2013.It was launched as the first nationwide pilot area of resource-saving and environment-friendly society by China's government since 2008.Moreover, Wuhan also became the seventh carbon emission trading center in China, following Beijing, Shanghai, Guangzhou, Shenzhen, Tianjin, and Chongqing in 2013.Another feature about the Wuhan Metropolitan Area case is that it is a so large a developing metropolitan entity that belongs to one province (Hubei) in China, thus the findings from this paper will deliver many more significant policy implications given the province-oriented governance scheme in environmental regulation.The national government's goal is to cut the carbon emission intensity by 40%-45% according to the 50th session of Copenhagen Accord in 2009 [33], and a low-carbon development strategy of Wuhan aimed to reduce carbon emission by 56% in 2020 compared with that in 2002 by the reported from Reuters China in 2013.Moreover, more than 40% of its economy results from energy-intensive industries with high carbon emissions, which implies an impossible task.Hence, a deliberate investigation and a sound understanding on drivers behind CO 2 emission would facilitate effective policy-making to achieve the target.

Net CO2 Emissions
In this paper, net CO2 emission (NCE) equals total CO2 emission, deducting total CO2 sinks.The model can be written as follows: where  i CE (i = 1 … 4) is the sum of CO2 emissions,  i CS (i = 1, 4) is the sum of CO2 sinks.

CO2 Emissions
For CO2 emission, i CE (i = 1 … 4) represents the CO2 emission from energy, industry processes and product use, agriculture, forest, and other land use, waste [34].They are calculated by the following methods: (1) CO2 emissions from energy can be calculated through Equation (2): (2) CO2 emission from Industry Processes and Product Use could be estimated through Equation (3): where industry CE is the CO2 emission from industry processes and product use.iq Ton is the amount of products from the industry sector and can be drawn from The Statistical Yearbook of Hubei Province.iq  is the CO2 emission parameter, which is drawn from IPCC [34].
(3) CO2 emissions from agricultural, forest and other land use change are more complicate and could be estimated through Equation ( 4):

Net CO 2 Emissions
In this paper, net CO 2 emission (NCE) equals total CO 2 emission, deducting total CO 2 sinks.The model can be written as follows: where ř CE i (i = 1 . . .4) is the sum of CO 2 emissions, ř CS i (i = 1, 4) is the sum of CO 2 sinks.

CO 2 Emissions
For CO 2 emission, CE i (i = 1 . . .4) represents the CO 2 emission from energy, industry processes and product use, agriculture, forest, and other land use, waste [34].They are calculated by the following methods: (1) CO 2 emissions from energy can be calculated through Equation (2): where CE energy is the CO 2 emission from the department of energy.
where CE agriculture is the sum of two parts, ř CE am ("a" refers to agriculture and m = 1, 2) and ř CE an ("a" refers to agriculture and n = 1, 2, 3, 4).ř CE am contains CO 2 emissions from agricultural immigration and agricultural land plowing, it is the sum of the area of item m ( ř Area am ) multiplied by their corresponding parameters (α am ).
ř CE an is the sum of CO 2 emissions from the consumption of chemical fertilizer, pesticides, plastic membrane, and diesel fuel, and it equals to the multiplication of the weight of item "n" (Ton an ) multiplied by their corresponding parameters (β an ).The area of agricultural immigration and agricultural land plowing ( ř Area am ) are derived from The Rural Statistical Yearbook of Hubei Province, which are the same for the consumption amounts of chemical fertilizer, pesticides, plastic membrane, and diesel fuel (Ton an ).α am and β an are drawn from those of Zhao et al. [30].
(4) CO 2 emission from waste department could be estimated through Equation ( 5): where CE waste is the CO 2 emission from the production from waste, ř CE w (w = 1, 2, 3) is the CO 2 emission from incineration of waste, open burning of waste, and incineration of fossil liquid waste.Ton wj is the weight or volume of the above three aspects, j is the component of every aspects, which were derived from The Statistical Yearbook of Hubei Province and The Rural Statistical Yearbook of Hubei Province.α wj is the CO 2 emission parameter of the j-th component of sector , which can be drawn from IPCC [34].

CO 2 Sinks
(1) CO 2 sinks include the CO 2 sink from cropland, forest, grassland, and the change of land use types.CO 2 sink from cropland could be estimated through the following method: where C i is the CO 2 sink of the crop i during its growth period; C f is the rate of CO 2 absorption; Y w is economic yield; r is the water content rate; H i is economic parameter.The economic yield (Y w ) is drawn from The Rural Statistical Yearbook of Hubei Province.The CO 2 absorption rate (C f ), water content rate (r) and economic coefficient (H i ) of China's main crops are derived from IPCC [34] and Li et al. [35].
(2) The CO 2 sink from forest could be estimated through Equation (7): where CS f orest is the CO 2 sink of forest.Area f orest is the area of forest, and it is derived from The Second National Land Survey.β f orest is the CO 2 sink parameter, which can be derived from Li et al. [35].
(3) The CO 2 sink from grassland could be estimated through Equation ( 8): where CS grassland is the CO 2 sink of grassland.Area grassland is the area of grassland, and it is derived from The Second National Land Survey.β grassland is the CO 2 emission parameter, which can be derived from Zhao et al. [30].
(4) The CO 2 sink from land use change occurring in China are the cultivated land that was used for construction purposes and reforestation of marginal arable land; their CO 2 sink could be estimated through the following Equation ( 9): where CS change is the CO 2 sink from changing of land use types.Area re f orest is the area of the reforestation of marginal arable land, Area construction is the area of cultivated land that was used for construction purpose, and they can be derived from The Second National Land Survey.
β f orest´f armland is the difference between the CO 2 sink parameters of forest and farmland, β f armland is the parameter of the CO 2 sink from farmland, which were derived from IPCC [34].

Decomposition Analysis of Net CO 2 Emission
In order to find out the factors that influence the change of net CO 2 emission, both additive and multiplicative forms of the LMDI can be employed to reach this goal.According to Ang [35], there exists a simple relationship between multiplicative decomposition and additive decomposition, which makes a separate decomposition using the multiplicative and additive schemes unnecessary.However, compared with multiplicative decomposition, additive decomposition decomposes the difference rather than ratio, which can fully reflect the direction of the factors' effect.We have, thus, chosen the additive form in this analysis.
Therefore, we can define NCE as the sum of net CO 2 emission for the whole Metro area, nce i is the net CO 2 emission at the city level such that i is the nine cities of the Wuhan Metropolitan Area, e is the amount of fossil energy consumption, g is GDP, and P is the population; then the net CO 2 emission decomposition equation can be established according to the additive form of the LMDI model as follows: NCE " nce e ˆe g ˆg P ˆP When we assume that nce e " E (CO 2 emission per unit of fossil energy consumption), e g " C (fossil energy consumption per unit of GDP), g P " S (GDP per capital), which can be named as energy structure, energy efficiency, economic level respectively.Then the index decomposition analysis equation can be expressed as: From year 0 (T 0 ) and year t (T t ), the changes of net CO 2 emission can be expressed as the following equation: The decomposition analysis of net CO 2 emission now can be expressed as follows: Finally, the changes of net CO 2 emission can be expressed as the following equation:

Results
According to the IPCC list, both CO 2 emissions and sinks of each city during the past decade are covered in this study, in an attempt to achieve a more precise result of the CO 2 emissions in the Wuhan Metropolitan Area.To be more specific, energy contributed the largest amount to CO 2 emission, followed by the industry processes and product use, and then the CO 2 emission from agriculture, forest, and other land use.The smallest amount of CO 2 emission comes from waste.
Table 1 also indicates that total CO 2 sinks of the Wuhan Metropolitan Area increased by 13.71% from 2001 to 2009, with the annual increasing rate of 1.52%.Specifically, cropland contributed the largest amount of CO 2 sinks during this period, followed by CO 2 sinks from forest.CO 2 sinks from grassland were the smallest and showed a decreasing trend.Surprisingly, CO 2 sinks coming from land use change is negative, which means land use change creates CO 2 emissions during the period from 2001 to 2009.This is mainly due to the rapid process of urbanization and sprawling of cities. Area of farmland that was converted for construction use is much larger than that of reforestation of marginal arable land.
As explained above, by Equation ( 5), an accurate calculation of net CO 2 emissions between 2001 and 2009 are calculated in this study.Generally, it shows a slightly increasing trend, net CO 2 emissions in 2009 increased by 84.97% compared with that of 2001.However, the change of total CO 2 emissions and sinks follow similar trends and are the same order of magnitude, so the net CO 2 emissions during this period did not fluctuate significantly (see Figure 2).The net CO 2 emissions remain unchanged due to the same changing trend of total CO 2 emissions and total CO 2 sinks from 2001-2009.
The annual increasing rate of net CO 2 emission in the Wuhan Metropolitan Area was 9.55% from 2001 to 2009, higher than Chongqing (9.20%), Tianjin (7.74%), Shanghai (4.43%), and Beijing (1.87%) during the same period.In particular, the increasing rate of CO 2 emission of most provinces and cities in China were much lower than their GDP increasing rate; this may explained as the lag effect.Despite the net CO 2 sink from 2001 to 2009 of the Wuhan Metropolitan Area not fluctuating significantly, there was a slightly higher increasing rate during 2003 to 2004 and this can be explained as the implementation of NO. 1 Document of Chinese Central Government, in which the national government began to provide agricultural subsidies to farmers who preserve their farmland.This policy promoted the farmers' enthusiasm of grain planting greatly, so the CO 2 sink from cropland increased rapidly in this year.
The changing trend of total CO 2 emission and net CO 2 emission of the Wuhan Metropolitan Area from 2001 to 2009 showed similar changing trends due to the relatively stable net CO 2 sink from 2001 to 2009.From 2001 to 2002, both the total CO 2 emission and net CO 2 emission decreased, which can be explained by the decrease of CO 2 emission from energy and agriculture departments.From 2003 to 2009, they both increased slightly, because rapid urbanization processes need large amounts of energy consumption and also areas of farmland were converted into construction land.

Spatial Distribution of Net CO 2 Emission in the Wuhan Metropolitan Area in 2009
Period-wise analysis of the Wuhan Metropolitan Area could show the changing trend of CO 2 emissions/sinks and net CO 2 emissions from 2001 to 2009, however, cross-sectional results presented on a city-scale could help local governments understand the distance to their own CO 2 emission reducing targets, which will also make the comparison among cities more convenient and intuitive, then promote the CO 2 emission trading in each city.Results of cross-sectional data of CO 2 emissions of the nine cities in the Wuhan Metropolitan Area in 2009 are calculated and listed in Table 2.According to Table 2, for the total CO 2 emission in the Wuhan Metropolitan Area, energy contributed the largest amount of CO 2 emission in 2009 (43.43 ˆ10 6 ton), followed by industrial processes and product use (25.54 ˆ10 6 ton), followed by CO 2 emissions from agriculture, forest, and other land use (2.01 ˆ10 6 ton).The smallest amount of CO 2 emission comes from waste (0.92 ˆ10 6 ton).
Among the nine cities of the Wuhan Metropolitan Area in 2009, each department followed the same rank order of CO 2 emission as above, except Wuhan, Huangshi, and Tianmen.For Wuhan, CO 2 emission from water deposing (0.53 ˆ10 6 ton) was higher than that from the agricultural sector (0.40 ˆ10 6 ton).As for the latter two cities, CO 2 emissions from industrial processes and product use (9.75 ˆ10 6 ton, 0.86 ˆ10 6 ton) were higher than those from the energy sector (4.60 ˆ10 6 ton, 0.72 ˆ10 6 ton), respectively.Most of the heavy industries of the Wuhan Metropolitan Area were distributed in those two cities.Compared to CO 2 emissions from light industries, heavy industries, such as the petrochemical industry, iron and steel industry, and power generation, are all industries with high CO 2 emissions.
Table 2 also indicates that, in the Wuhan Metropolitan Area, cropland contributed the largest amount of CO 2 sinks (13.14 ˆ10 6 ton) during this period, followed by CO 2 sinks from forests (7.56 ˆ10 6 ton).CO 2 sinks from grassland (1400 ton) were the smallest and showed a decreasing trend.Surprisingly, CO 2 sinks coming from land use change sector (´0.28 ˆ10 6 ton) is negative; in other words, it is CO 2 emitter.This is also true for the total CO 2 sinks of the eight cities, except Huanggang, whose forests contribute the largest amount of CO 2 sinks (3.49ˆ10 6 ton).This can be explained by the forest covering rate achieving 56% in Huanggang, much higher than the average forest covering rate of the Wuhan Metropolitan Area.Forest has the highest ability to absorb CO 2 .
Particularly, the net CO 2 emission in the Wuhan Metropolitan Area in 2009 achieved as much as 53.03 ˆ10 6 tons, only Huanggang' total CO 2 emission was lower than its total CO 2 sink, the other eight cities behaved in the opposite way.
The spatial distribution of CO 2 emission of the Wuhan Metropolitan Area in 2009 was unbalanced, which can be shown in Figure 3. Wuhan contributed the highest amount of CO 2 emission in the Wuhan Metropolitan Area, followed by Huangshi and Xiaogan.The CO 2 emission of the above three cities accounted for 72.24% of the total CO 2 emission in Wuhan Metropolitan Area.While the three cities with the least CO 2 emission were Xitantao, Qianjing, and Tianmen, the CO 2 emission of these three cities only accounted for 8.51% of the total CO 2 emission of the Wuhan Metropolitan Area.More surprisingly, the CO 2 emission of Wuhan was nearly 20 times higher that of Tianmen.For CO 2 sinks of the Wuhan Metropolitan Area in 2009, Huanggang contributed the highest amount of CO 2 sinks, followed by Xiaogan and Xianning.The CO 2 sinks of the above three cities account for 69.24% of the total CO 2 sinks of the Wuhan Metropolitan Area.While the three cities with the least CO 2 sinks were Tianmen, Qianjiang, and Ezhou, the CO 2 sinks of these three cities only account for 10.41% of the total CO 2 sinks of the Wuhan Metropolitan Area.More surprisingly, the CO 2 emission of Huanggang was nearly 20 times higher that of Ezhou.This is to say, the spatial distribution of CO 2 sinks of the Wuhan Metropolitan Area was unbalanced, but less than for CO 2 emission.Different cities should adopt different policies to increase their CO 2 sinks by taking their own CO 2 emission reduction pressure into consideration.
Compared to CO 2 emissions and CO 2 sinks, the spatial intensity distribution of net CO 2 emission of a city (net CO 2 emission divided by its land area) can be used for different cities to make comparisons of their CO 2 emission [31].Figure 3 indicates that among the nine cities of the Wuhan Metropolitan Area, Wuhan contributed the highest amount of net CO 2 emission, followed by Huangshi and Xiaogan.The net CO 2 emission of the above three cities accounted for 86.61% of the total CO 2 sinks of the Wuhan Metropolitan Area in 2009.While the three cities with the least CO 2 sink were Qianjiang, Xiantao, and Tianmen, the net CO 2 emission of these three cities only accounted for 5.64% of the net CO 2 emission of the Wuhan Metropolitan Area.Particularly, the CO 2 emission of Wuhan was nearly 25 times higher than that of Tianmen.Moreover, there was a special city (Huangang), whose net CO 2 emission was negative (´1.36 ˆ10 6 ton), it indicated that its total CO 2 emission was lower than its total CO 2 sink.

Decomposition and Analysis of Net CO 2 Emission in the Wuhan Metropolitan Area
Estimation of CO 2 emission, CO 2 sink, and net CO 2 emission can only provide the public with a general and quantity description of the CO 2 emission in the Wuhan Metropolitan Area.More specific analysis is needed if the authors want to explore the driving factors behind the increasing CO 2 emission trend.Generally, decomposition analysis is helpful for the public to understand those driving factors and the nature of CO 2 emissions changes over a specific time which can provide the basis for the authorities to design more pertinent policies on CO 2 emission deducing and trading.

Decomposition for Net CO 2 Emission in the Wuhan Metropolitan Area
Period-wise decomposition analysis of net CO 2 emission in the Wuhan Metropolitan Area from 2001 to 2009 was presented in Table 3.The driving factors were decomposed into the energy structure effect, the energy efficiency effect, the economic development effect, and the population effect through the LMDI model.The annual and accumulative explanatory effects were calculated and listed below.It should be noted that only the net CO 2 emission was analyzed through the LMDI model in this study.According to the decomposition result of the net CO 2 emission in the Wuhan Metropolitan Area from 2001 to 2009, the total effect was always negative, except that of 2006-2007 and 2007-2008.Factors of energy structure and energy efficiency are restricting factors of net CO 2 emission, while the economic level and population, the main drivers of net CO 2 emission, increase.Especially, the economic level and energy structure had significant effects on the net CO 2 emission, while the effects of energy efficiency and population were not as significant.
To be more specific, for the two restricting factors of net CO 2 emission, the energy structure effect showed a fluctuating trend from 2001 to 2009 while the energy efficiency effect showed a clear increasing trend from 2001 to 2003, and began to decrease from 2004 to 2009.For the two promoting effects, the economic level effect was also unstable, while the population presented a relatively stable trend during this period.
As shown in Figure 4, period-wise analysis of the total effect of CO 2 emissions from 2001 to 2009 can be divided into two stages.From 2001 to 2005, the gap between the restriction effect and the prompting effect became smaller, which led to the net CO 2 emission reduction during this period.After 2005, this gap became larger as time went by, so the net CO 2 emission kept increasing since then.All of these can be reflected in the total effect during 2001 to 2009.

Decomposition Analysis
Table 3 and Figure 4 show that factors that contribute to the rapid increase of net CO 2 emission from 2000 to 2009 in the Wuhan Metropolitan Area were economic level and population.The economic level was the most important prompting factor with an accumulative contribution of 4380.39 ˆ10 4 ton, much higher than that of population (173.26ˆ10 4 ton).
This indicated that, without restricting the function of other factors, the increment of the total CO 2 footprint of the Wuhan Metropolitan Area will be much higher by the influence of economic development.Especially during the period of 2004-2005, the drastic increase of economic level led to its increasing contribution to net CO 2 emission in the Wuhan Metropolitan Area.The population factor was also a promoting factor, but its contribution value was much less than that of the economic development factor, whose contribution value was only about 1/25 times as much as that of the economic level.The effect of population experienced a peak in 2004-2005, then returned to the normal status.Generally, the effect of population was so insignificant that it can be neglected.
The main restricting factors were the energy structure effect and the energy efficiency effect, in which the restricting effect of the energy structure was the highest, on the whole.Generally, the restricting effect of the energy structure presented a fluctuating trend from 2001 to 2009.The total contribution value was huge.However, the restricting effect of energy efficiency was not only as significant as the energy structure, but also showed a clear decreasing trend effect.After all of the factors which could affect the CO 2 emission were decomposed by reasonable conversion of the LMDI model, the results show that factors of the energy structure and energy efficiency can restrain net CO 2 emission.Conversely, economic development and the population scale increase the net CO 2 emission.

Conclusions
This study established a city-scale CO 2 emission/sink accounting system that covers all sectors of economic activities in the Wuhan Metropolitan Area according to reference [34].Results indicated that total CO 2 emissions kept increasing from 2001 to 2009, energy (43.43 ˆ10 6 ton) was the highest proportion, followed by the industry (25.54 ˆ10 6 ton) and agriculture (2.01 ˆ10 6 ton), and the smallest amount of CO 2 emission comes from the waste (0.92 ˆ10 6 ton).CO 2 sinks showed a fluctuating trend during 2001 to 2009, cropland contributed the largest (13.14 ˆ10 6 ton), followed by forest (7.56 ˆ10 6 ton), and then grass (0.14 ˆ10 4 ton).CO 2 sinks from land use change is negative (´0.28 ˆ10 6 ton, actually it was CO 2 emission).Moreover, the net CO 2 emission and its influencing factors during 2001 to 2009 were analyzed through the LMDI model.It could be concluded that energy intensity effect and economy development were identified as the dominant contributors to the decline and increase in net CO 2 emissions respectively.Energy efficiency effect contributed less to reduce the net CO 2 emission, and population effects are found to contribute little to the increase in the net CO 2 emission in the Wuhan Metropolitan Area.A comparison with the previous work was also made as follows: First, CO 2 emission of the Wuhan Metropolitan Area shows an increasing trend from 2001 to 2009, with energy making the greatest contribution, followed by industry, agriculture, and waste.This is generally consistent with the broader literature (e.g., Chong et al. [21], Li et al. [35]) that energy and industry are often the largest contributors to CO 2 emissions.Moreover, CO 2 sinks fluctuate during this period, with cropland contributing the most, followed by forest and grass.Land use change actually increases CO 2 emission rather than act as a sink over this period.The magnitudes of CO 2 sinks from forest and grassland are also consistent with Zhao et al. [30].There has been very limited literature incorporating CO 2 sinks in decomposition analysis.
The boarder decomposition literature has generally found that energy efficiency effect (energy intensity effect or technological effect) is the dominant contributor to decreased gross CO 2 emission, while scale effect (including income effect and scale effect) contributes the most to increased CO 2 emissions, which is consistent with the conclusion of Karmellos et al. [5] and Zhang et al. [31].These results turn out to be relatively robust even if one uses net rather than gross emissions.However, the role of emission intensity effect becomes significantly greater in the change of net emissions compared to gross emissions.
Third, this study has several limitations.As we are conducting decomposition analysis at a disaggregated city level, data becomes less available as we introduce more factors into the decomposition.This has constrained us from performing a finer analysis.Although LMDI has become popular in the decomposition literature, it cannot handle zero values [36].Lastly, given that decomposition models are descriptive rather than inferential, potential inter-region endogenous effects are hard to identify.
Finally, improvements of this study can be made from the following aspects: (1) CO 2 emission from waste should be more specific, since different ways of dealing with different kinds of waste will produce different amounts of CO 2 emission, more specific CO 2 emission coefficients, and relevant statistics should be taken into consideration for further research; (2) the research period was 2001-2009 in this paper due to the unavailability of the latest data; calculation and decomposition work of the following years should be added in the following study; (3) CO 2 sinks from chemical or biological treatments should be included into the estimation of carbon sinks despite its scale being quite small in the Wuhan Metropolitan Area at the present.

Implications
Our results show that emission intensity played a key role in CO 2 emission reduction.Given that coal is the dominant energy consumed in the Wuhan Metropolitan Area, developing clean energy technologies is of great potential.Another approach to emission mitigation is to reduce energy intensity or improve energy efficiency.As the economy in the Wuhan Metropolitan Area relies heavily upon the energy-consuming petrochemical industry, iron and steel industry, and power generation, the reduction in economy-wide energy intensity can be achieved by improving energy efficiency, as well as adjusting the industrial structure.As Wuhan is one of the seven pilot markets for carbon trading-a market-based instrument to mitigate carbon emission-it is interesting to see how such a policy experiment could help develop cleaner technologies and facilitate a transition towards a low-carbon economy.
On the other hand, CO 2 sinks play a vital role in reducing net CO 2 emission, which mainly relies on agriculture and forest.Despite various policy initiatives to protect agricultural and forest land, we still observe 0.9% of the remaining agricultural land converted into urban land due to the rapid urbanization in the Wuhan Metropolitan Area every year.Policies with compensation incentives for agricultural and forest land protection are urgently called for.Immediate questions include what the level and terms of compensation should be and how regional heterogeneity could be incorporated, etc.

Figure 1 .
Figure 1.Administrative division of Wuhan Metropolitan Area.
emission from the department of energy. ep Ton is the final consumption (double accounting can be avoided in this way) of energy( ep Ton )and comes from The Statistical Yearbook of Hubei Province.ep  is the CO2 emission parameter, which can be drawn from the Intergovernmental Panel on Climate Change reference approach IPCC [34].

Figure 1 .
Figure 1.Administrative division of Wuhan Metropolitan Area.

Figure 2 .
Figure 2. Total CO 2 emission/sink and net CO 2 emission of the Wuhan Metropolitan Area from 2001 to 2009.

Figure 3 .
Figure 3. CO 2 emission/sink and net CO 2 emission of the nine cities in the Wuhan Metropolitan Area in 2009 (unti: 10 6 ton).

Figure 4 .
Figure 4.The decomposition of net CO 2 emissions in the Wuhan Metropolitan Area from 2001 to 2009 (unit: 10 4 ton).
Ton ep is the final consumption (double accounting can be avoided in this way) of energy(Ton ep ) and comes from The Statistical Yearbook of Hubei Province.α ep is the CO 2 emission parameter, which can be drawn from the

Table 1 .
3.1.Net CO 2 Emission in Wuhan Metropolitan Area from 2001 to 2009 According to the above methods and data, precise estimates of net CO 2 emissions of the nine cities in the Wuhan Metropolitan Area from 2001 to 2009 were calculated.Table 1 summarizes the empirical results of the four sectors that contributed to CO 2 emissions and four sectors that contribute to CO 2 sinks from 2001 to 2009.The net CO 2 emissions during this period are listed in Table 1.CO 2 emission/sink and net CO 2 emission from 2001 to 2009 in the Wuhan Metropolitan Area (unti: 10 6 ton).According to the results of Table 1, total CO 2 emission of the Wuhan Metropolitan Area in 2001, total CO 2 emission increase in 2009 increased by 58.89%, with the annual increasing rate of 6.54%.Table 1 also shows changes in CO 2 emissions in each city from 2001 to 2009.CO 2 emissions gradually increased in all cities, to differing extents, due to the rapid development of the Chinese economy.

Table 2 .
CO 2 emissions/sinks and net CO 2 emissions in the nine cities in the Wuhan Metropolitan Area in 2009 (unti: 10 6 ton).

Table 3 .
Explanatory effects of CO 2 emissions in the Wuhan Metropolitan Area from 2001 to 2009 (unit: 10 4 ton).