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Environmental Modeling
The Role of Industrial Parks in Mitigating Greenhouse Gas Emissions from China Yang Guo, Jinping Tian, Na Zang, Yang Gao, and Lujun Chen Environ. Sci. Technol., Just Accepted Manuscript • DOI: 10.1021/acs.est.8b00537 • Publication Date (Web): 14 Jun 2018 Downloaded from http://pubs.acs.org on June 16, 2018
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Environmental Science & Technology
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The
Role
of
Industrial
Parks
in
2
Greenhouse Gas Emissions from China
Mitigating
3 4
Yang Guo 1, Jinping Tian 1, *, Na Zang 1, Yang Gao 1, Lujun Chen 1, 2
5
1
School of Environment, Tsinghua University, Beijing 100084, China
6
2
Zhejiang Provincial Key Laboratory of Water Science and Technology, Department
7
of Environment, Yangtze Delta Region Institute of Tsinghua University, Zhejiang,
8
Jiaxing 314006, China
9
Abstract
10
This study uncovered the direct and indirect energy-related GHG emissions of 213 Chinese
11
national-level industrial parks, providing 11% of China’s GDP, from a life-cycle perspective.
12
Direct emissions are sourced from fuel combustion, and indirect emissions are embodied in energy
13
production. The results indicated that in 2015, the direct and indirect GHG emissions of the parks
14
were 1042 and 181 million tonne CO2 eq., respectively, totally accounting for 11% of national
15
GHG emissions. The total energy consumption of the parks accounted for 10% of national energy
16
consumption. Coal constituted 74% of total energy consumption in these parks. Baseline and
17
low-carbon scenarios are established for 2030, and five GHG mitigation measures targeting
18
energy consumption are modeled. The GHG mitigation potential for these parks in 2030 is
19
quantified as 116 million tonne, equivalent to 9.5% of the parks’ total emission in 2015. The
20
measures that increase the share of natural gas consumption, reduce the GHG emission factor of
21
electricity grid, and improve the average efficiency of industrial coal-fired boilers, will totally
22
contribute 94% and 98% in direct and indirect GHG emissions reductions, respectively. These
23
findings will provide a solid foundation for the low-carbon development of Chinese industrial
24
parks.
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1 Introduction
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China is the largest carbon emitter, and it generated 9,084 million tonne of energy-related
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CO2 emissions in 2014.1 To address climate change issues, China promised to reach the CO2
29
emission peak around 2030.2 China has more than 2500 national and provincial industrial parks,3
30
which are the most important carriers of industrial sectors and contribute more than half of
31
national industrial output.4 As early as 2011, the Chinese central government started to attach great
32
importance to low-carbon development of industrial parks.5 The Ministry of Industry and
33
Information Technology and National Development and Reform Commission jointly facilitated
34
the low-carbon pilot industrial parks program since 2013.6,
35
establishing 150 low carbon pilot industrial parks was proposed in the national strategies on
36
addressing climate change by 2020.8 Moreover, in the grand plan of green development issued in
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2016, the low-carbon transition of industrial parks was emphasized once more, and in particular, a
38
number of parks were requested to reach the CO2 emission peak first.9 Thus, uncovering the
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features of the greenhouse gas (GHG) emissions of Chinese industrial parks will be critical to
40
identifying the role of industrial parks in addressing carbon emissions reductions. Doing so will
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provide a robust foundation for decision making regarding the low-carbon transformation of
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industrial parks and the green development of industrial sectors in China.
7
In 2014, an ambitious target of
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The GHG emissions of several industrial park cases in China have been examined in previous
44
studies,10-12 and the GHG emission accounting methods of those parks mainly followed
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consumption-based principles13 and employed the guideline issued by World Resources Institute.14
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In this guideline, GHG emissions are classified into Scopes 1, 2 and 3. For an industrial park,
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Scope 1 emissions refer to all direct GHG emissions within the park boundary, such as emissions
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from fuel combustion and industrial processes; Scope 2 emissions refer to indirect GHG emissions
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embodied in outsourced electricity and heat, which is consumed inside the park but produced
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outside the park; and Scope 3 emissions are other life-cycle emissions excluded those in Scopes 1
51
and 2, such as emissions from raw materials production outside the park. In the case study of
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Suzhou industrial park, Scopes 1 and 2 emissions are considered,10, 11 while in Beijing industrial
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park, Scopes 1 and 2 emissions and some important Scope 3 emissions (from solid waste disposal)
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are considered.12 Ban et al. estimated the Scope 1 GHG emissions of 41 eco-industrial park cases 2
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in Korea to assess the emissions reduction performance of those parks.15 In summary, the studies
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mentioned above did not adequately analyze the indirect GHG emissions of industrial parks.
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Further, there are some studies on GHG emission accounting for industrial parks from a
58
life-cycle perspective. Chen et al. developed a GHG inventory of a high-end industrial park,
59
including the construction, operation, and demolition stages of the park.16 Dong et al. developed a
60
hybrid life-cycle assessment (LCA) method to assess the carbon footprint of a Chinese industrial
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park by considering upstream, on-site, and downstream GHG emissions. Meanwhile, the
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embodied GHG emissions of material consumption were estimated by employing an input-output
63
analysis.17
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To assess the GHG emissions of numerous industrial parks in China, the system boundary of
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GHG emission accounting needs to be consistent. There is still a gap in accounting life-cycle
66
GHG emissions of industrial parks across China. Generally, energy consumption is the major
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source of GHG emissions, accounting for approximately 60% of global GHG emissions.18 Related
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studies have showed that energy use is the key component of carbon metabolism of industrial
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parks.19, 20 Energy-related GHG emissions include those from fuel combustion, fuel production
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and transportation, and embodied in outsourced electricity and heat. In the three cases mentioned
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above, energy-related GHG emissions account for 97%, 94% and 62% of the total emission in
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Beijing, Suzhou and Shenyang parks, respectively.11, 12, 17 Another study also stressed the fact that
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energy-related GHG emissions play a crucial role in total GHG emission.21 The above results
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indicated that energy-related GHG emissions constitute the majority of the total emission of
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industrial parks. Other GHG emissions in industrial parks, especially those from industrial
76
processes and embodied in material consumption, are too complex and time-consuming to collect
77
necessary data. Therefore, to account comparable GHG emissions for numerous industrial parks
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by consistent accounting boundary, energy-related GHG emissions could be the main
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consideration.
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This study aims to answer the following question: Could industrial parks be accountable for
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mitigating GHG emissions from China? To determine the answer, the life-cycle energy-related
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GHG emissions of 213 Chinese national industrial parks are carefully studied, including their
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emissions from fuel production, transportation and combustion, and embodied in outsourced
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electricity and heat. The considered cases cover 57% of national economic-technical development 3
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zones and national high-tech industrial development zones in China.3 Then, the GHG mitigation
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potential by targeting energy consumption in the 213 parks was quantified based on scenario
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analysis for 2030.
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2 Materials and Methods
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2.1 Data collection
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China has more than 2500 national-level and provincial-level parks.3 However, there is no
91
official statistical data on these parks. Thus, data availability is a big challenge for studying the
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industrial parks. The 213 parks considered in this study are all national-level parks, which are
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well-developed and have a large economic output. These 213 parks have a total GDP of 7,591
94
billion CNY in 2015, accounting for 11% of China’s GDP.22 Meanwhile, their data availability and
95
reliability are generally better than those on provincial-level parks.
96
This study collected the detailed data on each category of energy consumption, GDP,
97
population, land area, and geographic coordinates of 213 national industrial parks, through on-site
98
investigation and questionnaires (see Table S1 in Supporting Information). The energy
99
consumption of an industrial park covers that for energy conversion, industrial processes, waste
100
treatment and other on-site activities, while the energy consumption of transportation sector is not
101
considered in the study. The data on energy consumption includes primary energy (such as coal,
102
natural gas, and petroleum) and secondary energy (such as coal products, petroleum products,
103
electricity, and heat). Some companies in the park convert primary energy to secondary energy,
104
e.g., coal to electricity and steam, and raw petroleum to petroleum products. The secondary energy
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converted by these companies was excluded from net energy consumption of the park, whether it
106
was consumed by other companies in the park or exported outside. Thus, the net energy
107
consumption of an industrial park can be calculated by equation 1. A diagram illustrating energy
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flows of an industrial park is presented in Figure S1 of Supporting Information.
109
= −
110
(1)
111
From the regional perspective, 45.5% of the parks are located in East China, while the shares 4
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for Northwest, Central, Northeast, North, Southwest, and South China are 10.8%, 9.9%, 9.9%,
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9.4%, 9.4%, and 5.2%, respectively. Specifically, the 213 parks are located in 31 provincial-level
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administrative regions (see Figure 1). The Jiangsu and Zhejiang Provinces have 26 and 21 parks
115
respectively, while Shandong, Anhui, Fujian, and Jiangxi host 13, 12, 10, and 10 parks,
116
respectively. Each of the other 25 provinces has fewer than 10 parks (see detailed data in the
117
Supporting Information). We employ a life-cycle accounting method for energy-related GHG
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emissions of the parks, by integrating the foreground data in 2015 (collected from on-site
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investigations) and background data (cited from a professional LCA database, the Chinese Life
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Cycle Database (CLCD)). The CLCD is a localized database for China and has been increasingly
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employed in the studies related to Chinese issues.23, 24
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123 124
Figure 1 The 213 industrial parks with available data and the other industrial parks in China
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Note: In the newly released catalog (2018), there are more than 2500 national-level and
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provincial-level industrial parks in China.3 This study collected all the geographic coordinates of
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more than 1500 parks in the previous version of catalog (released in 2007)25, therefore, some parks
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are not marked in the map. The Chinese map is drawn by importing geographic data released in
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public by Ministry of Natural Resources of China (http://www.webmap.cn/main.do?method=index) 5
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into ArcGIS software.
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2.2 Accounting for energy-related GHG emissions of the 213 Chinese
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industrial parks
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Inventory analysis, input-output analysis, and ecological network analysis are widely used for
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GHG emission accounting.26 In particular, the embodied carbon flows in energy, material and
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trade has been carefully examined in recent studies.27-29 This study employed a process-based LCA
136
to calculate the GHG emissions from fuel production and transportation, and the emissions
137
embodied in outsourced electricity and heat (see Figure 2). GHG emissions considered include
138
CO2, CH4 and N2O, which are converted to CO2 equivalents according to the 100-year global
139
warming potentials (see Table S1 in the Supporting Information). The definitions of the variables
140
and parameters for accounting for the life-cycle energy-related emissions are presented in Table 1.
141 142
Figure 2 Framework of energy-related GHG emission accounting in industrial parks
143 144
Table 1 Definitions of variables and parameters Variable/Parameter
Definition
/
Direct or indirect GHG emissions of the ith park
! / " !
Total energy consumption or output of energy conversion of the jth fuel in the ith park 6
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/"
Total electricity consumption or production in the ith park
/"
Total heat consumption or production in the ith park
( ! )
GHG emission factor for the combustion of the jth fuel
( ! )
GHG emission factor for the production of the jth fuel GHG emission factor for electricity generation and
(, )
transmission in the regional power grid where the ith park is located
()
GHG emission factor for heat generation and transmission
145
Direct GHG emission considered all kinds of fuels with a non-zero GHG emission factor
146
during combustion. These fuels and their GHG emission factors are listed in Table S1 of the
147
Supporting Information. Thus, direct GHG emissions from total energy consumption can be
148
derived as equation 2. Additionally, the sections of coal for coking and raw petroleum for refinery
149
are excluded when accounting direct GHG emissions.
150
= ∑!( ! × ( ! )) (2)
151
The indirect energy-related GHG emissions are formulated as equation 3, by considering all
152
the energy categories listed in Table S2 of the Supporting Information. Only the indirect GHG
153
emissions associated with net outsourced portion of energy are included. When the total
154
consumption of a kind of energy is less than the output of energy conversion, the park is
155
considered as energy self-sufficient and will export the surplus part. As a result, this will decrease
156
the GHG emissions that the park should be responsible for. Furthermore, the life-cycle GHG
157
emission factor of outsourced electricity is sensitive to the regional electricity grid where the park
158
is located. The life-cycle GHG emission factors of electricity imported are cited from the CLCD,
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as shown in Table S2 of the Supporting Information. In particular, the GHG emissions embodied
160
in exported electricity are accounted by also using the emission factors of regional electricity grid.
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This factor preference will favor the low-carbon energy production within industrial parks.21 For
162
example, when the GHG emission factor of electricity generation in the park is less than that of
163
regional grid, such selection will offset more GHG emissions of the park.
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= ∑!(( ! − " ! ) × ( ! )) + ( −
165
" ) × (, ) + ( − " ) × ()
166
(3)
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2.3 GHG mitigation potential in the 213 Chinese industrial parks by
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targeting energy consumption
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Based on tailored national strategies of industrial and energy development,30-33 we
170
established baseline and low-carbon scenarios, as shown in Table 2, to explore the GHG
171
mitigation potential of the 213 Chinese parks. The base year is 2015, and the target year is 2030.
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The total energy consumption of the parks is targeted to increase by 39.5%, according to the
173
national strategies listed in Table 2. Thus, incremental energy consumption will be anticipated in
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both scenarios. In the baseline scenario, the energy structure of the 213 parks will remain the same
175
in 2030 as that in 2015. In the low-carbon scenario, five measures of GHG mitigation will be
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applied by targeting energy consumption.
177
Among the five GHG mitigation measures, M1-M3 will directly change the energy structure
178
by increasing the shares of natural gas (NG), municipal solid waste (MSW), and biomass to
179
decrease the coal share. M4 is to reduce the GHG emission factors of regional electricity grids.
180
M5 is to improve the average efficiency of industrial coal-fired boilers to cut down coal
181
consumption. The parameters of these measures are set by referencing the targets for the whole
182
country in the grand strategies listed in Table 2, and more information is presented in Table S3 of
183
Supporting Information. Thus, the GHG mitigation potential can be quantified by comparing the
184
GHG emissions in 2030 under the low-carbon scenario with that under the baseline scenario. The
185
details and equations of modeling GHG mitigation potential of the 213 parks can be found in the
186
Supporting Information.
187 188
Table 2 Scenario setup for the 213 Chinese industrial parks in 2030 Parameter
2015
Total energy consumption of the 213 parks (million tce)
389
Improving energy structure
Coal and products
78.3%
NG
8.20%
2030 (Baseline scenario)
2030 (Low-carbon scenario)
Increased by 39.5%
Unchanged
Policy reference Refs 30 and 31
Decreased accordingly
Ref 30
Increased by 83% (M1)
Refs 30 and 31
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MSW
0.42%
Increased by 60% (M2)
Ref 32
Biomass
0.49%
Increased by 32% (M3)
Ref 32
Reducing GHG emission factor of electricity grid
-
Decreased by 20% (M4)
Ref 33
Improving average efficiency of industrial coal-fired boilers
-
The average increased from 70% to 75% (M5)
Ref 33
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3 Results and Discussion
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3.1 Energy structure of the 213 Chinese industrial parks
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Figure 3 presents the structure of net energy consumption (see equation 1) of the 213 Chinese
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national industrial parks in 2015. The net energy consumption of each category was converted to
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tonne of standard coal equivalent (tce), based on the lower calorific value (see Table S4 in the
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Supporting Information). The total energy consumption of the 213 parks in 2015 was 389 million
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tce, accounting for 9.7% of national energy consumption in 2015.34
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From the perspective of energy category, coal and coal products played a dominant role,
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accounting for 78.3% of net energy consumption, which is much higher than the share of coal
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consumption in Chinese industrial sector in 2015, 56%.34 Raw petroleum ranked second, taking
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35.5%, and NG had a share of 8.2%. Meanwhile, non-conventional energy, such as waste heat
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recovery, biomass, MSW, coal gangue, and industrial waste, accounted for 2% in total. Electricity
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generated by energy infrastructure in the parks must be uploaded to power grid; meanwhile, the
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parks buy electricity from local power grid for their use. The net outsourced electricity of the 213
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parks was only 2.8% of net energy consumption. Twenty of the 213 parks have petroleum refinery
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facilities, and their downstream product outputs to market, e.g., a chemical park in Shanghai as
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reported.35 Thus, petroleum products had a negative net consumption, accounting for -25.9% of
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net energy consumption. There are 72 parks supplying surplus heat to local community; thus, they
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also had a negative net heat consumption.
208
From the perspective of geographic location, the parks could be classified into seven regions,
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as shown in Figure 3. The parks in East China consumed the largest share in almost every category
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of energy, e.g., 40% of coal, 53% of raw petroleum, and 40% of NG. Meanwhile, the parks in East 9
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and South China exported most of petroleum products with shares of 53% and 36%, respectively.
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For electricity consumption, the parks in North, East, Northeast, Northwest, and Southwest China
213
accounted for 43%, 30%, 17%, 22%, and 33%, respectively. The parks in South and Northeast
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China exported more electricity than that bought from local grid. In addition, the parks in
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Northeast China also supplied a great deal of heat to local community due to district heating
216
demand in the winter.
217
218 219
Figure 3 Energy structure of the 213 Chinese industrial parks
220
3.2 Life-cycle energy-related GHG emissions from the 213 Chinese
221
industrial parks
222
The direct and indirect GHG emissions of the 213 Chinese industrial parks were 1,042 and
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181 million tonne, respectively, as presented in Figure 4. The most recently released figure for
224
China’s total GHG emission was 11.32 billion tonne in 2012.36 The life-cycle energy-related GHG
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emission of the 213 parks was 10.8% of total national emission. The direct GHG emissions
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constituted a major part of the 9.2% of national GHG emission, and accounted for 85% of the total
227
emission of the 213 parks. The parks in East China were the largest emitter with 41% of direct
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emission and 40% of indirect GHG emission, respectively. This is partly due to the leading role of
229
the parks in East China with regard to the number of parks (97 of the 213 parks) and their 10
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economic volume (53% of the total GDP). The statistical information of the 213 parks by different
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regions is presented in Table S5 of Supporting Information.
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233 234
Figure 4 Direct and indirect GHG emissions of the 213 Chinese industrial parks by geographic
235
region
236 237
Figure 5 shows the direct and indirect GHG emissions of the 213 parks. The annual GHG
238
emissions of the parks varied within the range of [-1.0, 80.3] million tonne. There were 210 parks
239
with a positive total GHG emission, while the remaining parks had a negative value. A negative
240
value of total GHG emission for a park means that the park has a better than average performance
241
with regard to its emissions intensity in energy conversion. For instance, if an industrial park is
242
less carbon-intensive in electricity generation (GHG emission per kWh) than the emission factor
243
of regional power grid, then the indirect emissions embodied in electricity uploaded to grid will
244
offset direct emissions in the park, as indicated in equation 3. There were 167 parks with a positive
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value for indirect GHG emission, while the remaining 46 parks had a negative value. A negative
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value for indirect GHG emission indicates the park exports electricity or heat. Forty eight percent
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of the 213 parks had a share of indirect GHG emission that was greater than 50%, implying more
248
outsourced energy consumption.
249 11
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250 251
Figure 5 Direct and indirect GHG emissions of the 213 Chinese industrial parks by geographic
252
location
253
Note: Each pie represents total GHG emission of a park, and the area is proportional to the total
254
emission. The blue and yellow sectors refer to the direct and indirect GHG emissions, respectively.
255
If the indirect emission are negative, the direct emission will be directly offset, and the pie will
256
only be blue. The Chinese map is drawn by importing geographic data released in public by
257
Ministry of Natural Resources of China (http://www.webmap.cn/main.do?method=index) into
258
ArcGIS software.
259 260
To further identify the main drivers of the GHG emissions of the parks, the direct and indirect
261
GHG emissions are disaggregated by both geographical region and energy category, as shown in
262
Figure 6. The coal and products consumption of the parks generated 896 million tonne CO2 eq. of
263
direct GHG emissions, accounting for 86% of total direct emission. Meanwhile, the outsourced
264
electricity consumption was responsible for 89 million tonne CO2 eq., accounting for 49% of total
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indirect GHG emission. Some regions have a negative contribution to indirect GHG emissions due
266
to net energy export.
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Figure 6 Direct and indirect GHG emissions of the 213 Chinese industrial parks disaggregated by
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geographic region and energy category
271 272
There is a significant difference in GHG emission intensity among the parks in the range of
273
-40,333 ~ 673,231 tonne/km2, -78 ~ 5,206 tonne/million CNY of GDP, and -62 ~ 1,862
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tonne/capita. The GHG emission, GDP, land area and population of each park can be found in the
275
Supporting Information. The average intensities of the energy-related GHG emissions of the parks
276
are presented in Table 3.
277
The average intensities were calculated by dividing the sum of the GHG emissions with the
278
sum of land area, GDP, or population, respectively. Overall, from the perspective of GHG
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emission per land area, the 213 national parks are much more carbon-intensive than average
280
national level, 1,214 tonne/km2.22 Generally, the parks in East, Central, and South China
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outperformed the parks in other areas in the three metrics. The parks in North and Northwest
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China have large gaps compared with other parks, which indicates that these parks host more
283
energy-intensive industries.
284
Furthermore, the average of GDP, land area, and population for the parks in different regions
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are listed in Table S5 of Supporting information. Among all the parks, those in Northwest China,
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averagely, have the smallest GDP (16,959 million CNY) and population (42,345 capita), and the
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second smallest land area (92 km2), however, they have the largest GHG emission (10 million
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tonne CO2 eq.). This leads to the largest GHG intensities for the parks in the Northwest China.
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Meanwhile, the parks in the North China have the smallest average land area (84 km2) and the
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second largest average GHG emission (9.8 million tonne CO2 eq.). Thus, the parks with relatively
291
large intensities of GHG emission, such as the parks in the North and Northwest China, could be
292
regarded as the prior candidates of facilitating GHG mitigation measures.
293 294
Table 3 Average GHG emission intensities of the 213 Chinese industrial parks
North East Central South Northeast Northwest Southwest All
GHG emission per area of land (tonne/km2)
GHG emission per GDP (tonne/million CNY)
GHG emission per capita (tonne/capita)
115,704 41,363 21,208 19,641 28,311 109,493 42,470 45,293
261 124 76 122 170 593 132 161
126 48 37 62 78 238 70 68
295
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3.3 GHG mitigation potential in the 213 Chinese industrial parks by
297
targeting energy consumption
298
Figure 7 presents the increment and mitigation potential of GHG emissions in the 213
299
Chinese industrial parks for 2030. According to the national strategies listed in Table 2, the total
300
net energy consumption (including primary and secondary energy) of the 213 parks is projected to
301
increase by 39.5% during 2015-2030. This growth will result in 412 and 71 million tonne more
302
direct and indirect GHG emissions, respectively, as shown in Figure 7. Thus, in the baseline
303
scenario, the direct and indirect GHG emissions will reach 1,455 and 252 million tonne,
304
respectively.
305
In the low-carbon scenario, by implementing the five measures, the direct and indirect GHG
306
emissions of the 213 parks will be decreased by 83.2 and 32.4 million tonne in total, respectively.
307
The total emission reduction, 116 million tonne, equals 9.5% of the total emission in 2015. In 14
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general, M1 (increasing the share of NG), M4 (reducing the GHG emission factor of electricity
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grid), and M5 (improving the average efficiency of industrial coal-fired boilers) have the most
310
significant GHG mitigation potentials, while M2 (increasing the share of MSW) and M3
311
(increasing the share of biomass) contributed insignificantly to GHG emission reduction.
312
Therefore, the reduction of direct GHG emissions will be leveraged mainly by M1 (-47 million
313
tonne) and M5 (-31 million tonne). Meanwhile, the mitigation of indirect GHG emissions will be
314
accomplished primarily by M1 (-3.7 million tonne), M4 (-25 million tonne), and M5 (-3.2 million
315
tonne). However, the GHG mitigation potential cannot totally offset the increment of GHG
316
emissions driven by energy consumption growth since it only accounts for 20% of the direct
317
emission increment and 45% of the indirect emission increment, respectively. The targets set in the
318
low-carbon scenario are in line with the grand plan of low-carbon development of the whole
319
country. The 213 national industrial parks could achieve more ambitious GHG mitigation goals.
320
Therefore, given the target of achieving carbon emissions peak for industrial parks around 2030,
321
more effort can be made to reduce coal dependence and improve energy efficiency of energy
322
infrastructure in industrial parks, such as using more renewable energy to replace coal, and
323
upgrading technology and capacity of facilities.
324
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Figure 7 GHG mitigation potential of the 213 Chinese industrial parks in 2030 by targeting energy
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consumption
328 329
In China, industrial parks are important bearers of economic development and play the roles
330
of both trouble-maker and trouble shooter for environmental issues. This study, to the best of our
331
knowledge, provides the features of direct and indirect energy-related GHG emissions from a large
332
number of Chinese industrial parks for the first time. The national industrial parks outperformed
333
all the parks, however, in reaching the carbon emissions peak first, more efforts are still needed to
334
decouple their economic development and GHG emissions. This study uncovers the GHG
335
emissions and mitigation potentials of industrial parks from the perspective of energy
336
consumption. The GHG emissions from industrial processes and waste treatment are not
337
considered at this stage. It will be also helpful for decision making to expand the factors like
338
industrial products and energy efficiency those behind energy consumption. Especially, energy
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infrastructure in Chinese industrial parks has been proved to act as the dominant role of both GHG
340
emission and mitigation.37, 38 In our forthcoming work, the GHG emission mitigation potential of 16
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~1600 Chinese industrial parks will be examined from the perspective of energy infrastructure,
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based on a high-resolution inventory and a delicate vintage-stock model. The high-resolution
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inventory will cover the park-level, plant-level, and unit-level data on energy infrastructure in
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Chinese industrial parks and be embedded in Geographic Information System. An updated version
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of vintage-stock model based on our previous work,38 will be employed to quantify the GHG
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mitigation potential, cost and co-benefits of energy infrastructure from the perspective of
347
serviceable lifetime.
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Supporting Information
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Supporting Information includes an Excel sheet and a Word file. The Excel sheet lists the basic
350
information and detailed GHG emissions of the 213 Chinese national industrial parks. The Word
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file includes: illustrative diagram of energy flows in an industrial park, GHG emission factors for
352
fuel
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transportation/transmission, detailed information for the parameters of GHG mitigation measures
354
proposed in scenario analysis, lower calorific value of each energy category, statistical
355
information of the 213 parks by different regions in China, and the model of GHG mitigation
356
potential.
357
Author Information
358
Corresponding Author
359
*Phone: +86-10-62785573; Fax: +86-10-62785573; E-mail:
[email protected].
360
Acknowledgments
361
The authors acknowledge the National Natural Science Foundation in China for its financial
362
support through projects 41471468 and 41671530. The authors acknowledge the Key Laboratory
363
for Solid Waste Management and Environment Safety (Tsinghua University), Ministry of
364
Education of China. The Ministry of Education of China is also acknowledged for their financial
combustion,
life
cycle
GHG
emission
factors
17
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for
energy
production
and
Environmental Science & Technology
365
support through R&D project (20130002110025). The authors are grateful to local governments of
366
the industrial parks for their assistance with interviews and data collection.
367
References
368
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213 Chinese Industrial Parks GHG Emission in 2015 1,100
1,042 Mtonne CO2 eq.
GHG Mitigation in 2030 100
Coal and products
M1 - Increasing share of natural gas
Natural gas
83 Mtonne CO2 eq.
Petroleum and products 900 80
Coal gangue
M2 - Increasing share of municipal solid waste M3 - Increasing share of biomass
Municipal solid waste M4 - Reducing GHG emission factor of electricity grid
Industrial waste
700
Biomass
60
M5 - Improving average efficiency of industrial coal-fired boilers
Electricity 500
Heat 40
32 Mtonne CO2 eq. 300
181 Mtonne CO2 eq. 20 100
0
Direct -100
Indirect
0 ACS Paragon Plus Environment
Direct
Indirect