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Abstract

Climate change and air pollution are two major environmental issues linked in several ways. Air pollutants reduction would benefit from the Greenhouse gas (GHG) emissions mitigation policy. China is facing a serious air pollution and GHG emissions. Effective and low cost strategies to solve these problems have been discussed by a number of researchers. Previous studies typically evaluated near-term and direct co-benefits, neglecting the socio-economic impacts on CO2 and PM2.5 emission. In this paper, production-based and consumption-based emissions are quantified to compare the differences. Input-output analysis (IOA) is adopted to investigate the consumption-based CO2 and PM2.5 emissions that result from the current monetary flows and energy structure. The correlations of CO2 and PM2.5 emissions from both consumption-based and production-based perspectives are assessed to see the extent to which these co-benefits are valued in integrated assessment models. We distribute the indirect emissions to original sector and identify the correlations of CO2 reductions for air quality in Beijing, which provide a new point of view on formulating impartial and effective polices of alleviating the air pollution and reducing CO2 emissions.
1876-6102 © 2016 The Authors. Published by Elsevier Ltd. This is an open access article under the CC BY-NC-ND license
(http://creativecommons.org/licenses/by-nc-nd/4.0/).
Peer-review under responsibility of the scientific committee of the Applied Energy Symposium and Forum, CUE2016: Low carbon cities
and urban energy systems.
doi: 10.1016/j.egypro.2016.12.017
Energy Procedia 104 ( 2016 ) 92 97
ScienceDirect
CUE2016-Applied Energy Symposium and Forum 2016: Low carbon cities & urban
energy systems
Co-benefits of CO2 and PM2.5 emission reduction
Siyuan Yang, Bin Chen
*
, Sergio Ulgiati
School Of Environment, Beijing Normal University, Beijing100875, P.R. China
Abstract
Climate change and air pollution are two major environmental issues linked in several ways. Air
pollutants reduction would benefit from the Greenhouse gas (GHG) emissions mitigation policy. China is
facing a serious air pollution and GHG emissions. Effective and low cost strategies to solve these problems
have been discussed by a number of researchers. Previous studies typically evaluated near-term and direct
co-benefits, neglecting the socio-economic impacts on CO2 and PM2.5 emission. In this paper, production-
based and consumption-based emissions are quantified to compare the differences. Input-output analysis
(IOA) is adopted to investigate the consumption-based CO2 and PM2.5 emissions that result from the current
monetary flows and energy structure. The correlations of CO2 and PM2.5 emissions from both consumption-
based and production-based perspectives are assessed to see the extent to which these co-benefits are valued
in integrated assessment models. We distribute the indirect emissions to original sector and identify the
correlations of CO2 reductions for air quality in Beijing, which provide a new point of view on formulating
impartial and effective polices of alleviating the air pollution and reducing CO2 emissions.
© 2016 The Authors. Published by Elsevier Ltd.
Selection and/or peer-review under responsibility of CUE
Keywords: CO2; PM2.5; Input-output analysis; China
1. Introduction
China, with an annual economic growth rate of over 8% for years, largely through the energy-intensive
construction of infrastructure, is facing big challenges to meet air quality regulation and Greenhouse gases
* Corresponding author. Tel.: +86-10-58807368; fax: +86-10-58807368
E-mail address: chenb@bnu.edu.cn
Available online at www.sciencedirect.com
© 2016 The Authors. Published by Elsevier Ltd. This is an open access article under the CC BY-NC-ND license
(http://creativecommons.org/licenses/by-nc-nd/4.0/).
Peer-review under responsibility of the scientific committee of the Applied Energy Symposium and Forum, CUE2016: Low carbon
cities and urban energy systems.
Siyuan Yang et al. / Energy Procedia 104 ( 2016 ) 92 – 97 93
emissions (GHG) emission mitigation [1]. Previous studies have been proved that fossil fuels combustion
emits a number of pollutants apart from CO2 [2-4]. Barker [2] has calculated that this source is responsible
for over 99% of SO2 and NO2, 91% of particulate matter, 48% of methane and 38% of VOC (volatile organic
compounds) emissions in the United Kingdom. GHG mitigation policies can also have favourable effect on
local air quality, which lower the net costs of emission reductions and thereby may strengthen the incentives
to participate in climate change mitigation agreement [5-7]. A lot of synergy between climate change and
air quality is a result of changes in the energy system from a production-based perspective (e.g., efficiency
improvement, energy switching and structural adjustment) [8]. However, consumption-based accounting,
where all emissions occurring along the supply chains and distribution are assigned to the final consumer
of products, is seen as providing supplementary information for policy and decision makers [9]. This
approach can be used to trace the physical emissions back to the initial cause through the economic activities
and make consumers realize their life-style and consumption choices would trigger adverse impacts on the
environment. Likewise, it also raises awareness of indirect emissions caused by governments and businesses
[10, 11]. The aim of this paper is to examine the effect of socioeconomic activities on CO2 and PM2.5
emissions in Beijing, identifying the common contributors of PM2.5 and CO2 emissions to largely reduce
the costs of meeting air pollution and GHG reduction targets.
The research objectives are to: i) calculate the production-based CO2 and PM2.5 emissions according to
the emission factor and energy consumption, ii) quantify the consumption-based CO2 and PM2.5 emissions
which are embodied in goods or services transported through interconnected economic sectors by using
input output analysis (IOA), iii) assess the correlations of CO2 and PM2.5 emissions from both consumption-
based and production-based perspectives.
Nomenclature
Abbreviation
PM2.5 Particulate Matter 2.5
IOA Input Output Analysis
Symbols
x Sectoral output
I Identity matrix
A Coefficient matrix
(I-A)-1 Leontief inverse matrix
y Final demand
k CO2 or PM2.5 emission coefficient
DEM Direct emissions
IEM Indirect emissions
Subscript
i i-th sector in row
j j-th sector in column
94 Siyuan Yang et al. / Energy Procedia 104 ( 2016 ) 92 – 97
2. Material and methods
2.1. Study site
Beijing as the capital of China is the center of policy and economy. It is located in the northern part of
the North China Plain, with 62% of its area being mountainous and the remaining 38% being plain. Its
special terrain makes it difficult to disperse the air pollution. In addition, the regional meteorological
conditions also have a general effect on air quality. Although the supply of electricity and heat has largely
substituted for coal combustion in urban areas, residential cooking and space heating in both the rural area
and suburban area (92 percent of total area) of Beijing still relied largely on coal combustion [12].
2.2. Data source
Energy consumption from each sector is abstracted from China Statistical Yearbook [12]. Direct CO2
emissions from each sector are calculated by multiplying the energy consumption with their corresponding
emissions factors which are obtained from Guidelines for National Greenhouse Gas Inventories [13]. The
data for PM2.5 emission factor is derived from the greenhouse gasair pollution interactions and synergies
(GAINS) model that is developed by the International Institute for Applied Systems Analysis (IIASA). The
input-output table for 42 economic sectors in Beijing is provided by Beijing Municipal Bureau of Statistics
[14]. To highlight the sectors with high emissions, 42 economic sectors are aggregated into 15 sectors.
2.3. Theory/calculation
Input-output analysis (IOA) is an analytical approach first developed by Leontief [15, 16]. After
applying to evaluate the environmental impacts or resources, it has been widely used to identify the hidden
drivers and indirect causes of environmental changes on different scales [11, 17]. It is a top-down method
to illustrate emissions or energy consumptions required to produce a unit of economic output (goods and
services) driven by final demand in a consistent framework [18-19]. This method can be used to distinguish
the direct and indirect emissions embodied in trade and distribute all the CO2 and PM2.5 emissions triggered
by final demand into each sector to reflect the embodied emission flow across sectors [20]. Some
assumptions are made in this paper, i) the study is conducted within the administrative boundary of Beijing;
ii) burning same type of fuel from different sectors are assumed to have the same CO2 and PM2.5 emission
coefficient; iii) emission factor of CO2 and PM2.5 from those goods and services imported from other regions
or countries are considered to be the same as the local products.
The specific derivation of the formula has been described by many researchers in detail [21-23]. Here
only the main equations are listed:
ݔσܺ௜௝
௝ୀଵ ൅ݕ
 (1)
The technical coefficient matrix A is calculated as:
ܣൌܺ
௜௝ ݔ
Τ (2)
Combining Eqs. (1) and (2), we can get
ݔൌܫെܣ
ିଵݕ (3)
CO2 and PM2.5 emission intensity from each sector can be calculated by:
݇ൌܧ
ݔ
Τ (4)
Siyuan Yang et al. / Energy Procedia 104 ( 2016 ) 92 – 97 95
To convert the monetary flow into emissions flow, the equation (3) and (4) should be combined:
ܧൌ݇
ܫെܣ
ିଵݕ (5)
Then, the direct and indirect CO2 and PM2.5 emissions can be calculated as:
ܦாெ ൌ ݇ሺܫ ൅ ܣሻݕ (7)
ܫாெ ൌ݇ܫെܣ
ିଵݕെܦ
ாெ (8)
3. Results
Fig.1. Left (a) shows production-based CO2 and PM2.5 emissions from 15 aggregated sectors. Right (b)
shows consumption-based CO2 and PM2.5 emissions from 15 sectors.
It can be found in Fig.1 (a) that production-based CO2 and PM2.5 emissions have positive correlations
with correlation coefficient bigger than 0.6. The “supply and production of electricity” sector and
“transportation” sector with 22.36 Mt and 18.15 Mt CO2 emissions rank first and second as the two biggest
source of CO2. The “supply and production of electricity” sector with 46.05 kt of PM2.5 emissions becomes
the dominant emitter, followed by “smelting and pressing of metals” sector with 36.79 kt. From Fig.1 (b),
it is obvious that there is a significant relevance between CO2 and PM2.5 emissions from 15 aggregated
sectors based on consumption-based perspective. The “residential service” sector with 45.10 kt PM2.5
emissions and 21.25 Mt CO2 emissions becomes the main contributor to air pollution and climate change
in Beijing.
4. Discussion and conclusions
This study shows that CO2 and PM2.5 emissions have positive correlations from both production-based
and consumption-based perspective. The “supply and production of electricity” sector, due to the fuel
combustion, is the main cause for the direct emission of CO2 and PM2.5. In that sector, CO2 and PM2.5
emissions to a large extent stem from the same sources. Energy switching and efficiency improvement are
the promising solutions to reduce the emissions. The “residential service” sector, which consists of residents
relying on consuming the goods or services from other sectors, is the major contributor to consumption-
based CO2 and PM2.5 emissions. In this condition, government should create incentives for people to
purchase goods with low intensity of carbon emissions or air pollutants and encourage residents to develop
a more conservation-minded lifestyle.
96 Siyuan Yang et al. / Energy Procedia 104 ( 2016 ) 92 – 97
Acknowledgement
This work was supported by the National Key Research & Development Program (2016YFA0602304),
National Natural Science Foundation of China (No. 71573021, 71628301), Specialized Research Fund for
the Doctoral Program of Higher Education of China (No. 20130003110027), and China-EU Joint Project
from Ministry of Science and Technology of China (No. SQ2013ZOA000022).
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Biography
Bin Chen is a professor of energy science at Beijing Normal University. Dr. Chen has published over 200
peer-reviewed papers in prestigious international journals. He is also serving as subject editor of Applied
Energy and editorial board member of more than ten journals.
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The following values have no corresponding Zotero field: ID - 52
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