Greenhouse gas emissions estimation and ways to mitigate emissions in the Yellow River Delta High-efficient Eco-economic Zone, China

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Journal of Cleaner Production 81 (2014) 89e102

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Journal of Cleaner Production

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Greenhouse gas emissions estimation and ways to mitigate emissionsin the Yellow River Delta High-efficient Eco-economic Zone, China

Mingxing Sun a, Yi Yuan a, Junying Zhang a, Renqing Wang a, Yutao Wang a, b, *

a Institute of Ecology and Biodiversity, School of Life Sciences, Shandong University, Jinan 250100, Chinab Key Laboratory of Carrying Capacity Assessment for Resource and Environment, Ministry of Land and Resources, Beijing 101149, China

a r t i c l e i n f o

Article history:Received 18 April 2014Received in revised form27 May 2014Accepted 10 June 2014Available online 17 June 2014

Keywords:GHG emissionsRegional scaleGovernment planYellow River Delta

* Corresponding author. Institute of Ecology and Biences, Shandong University, Jinan 250100, China. Tel.

E-mail addresses: [email protected], yutao

http://dx.doi.org/10.1016/j.jclepro.2014.06.0320959-6526/© 2014 Elsevier Ltd. All rights reserved.

a b s t r a c t

Rapid economic development and urbanization has led to a tremendous carbon emissions increase. Thedevelopment of the Yellow River Delta High-efficient Eco-economic Zone (YRDHEZ), according to itsplan, would be accompanied by a sharp economic increase and new pattern of urbanization. This paper,based on IPCC guidelines, explored the carbon emissions trajectory in YRDHEZ from 2005 to 2011 from 6sectors (industrial energy consumption, fugitive emissions, transportation, industrial processes, livestockemissions, and waste), and predicted its carbon emissions in 2015 and 2020 based on the developmentplan. The results showed that total carbon emissions substantially increased from 2005 to 2011 and itwould still increase in 2015 and 2020, with the largest emissions sector coming from industrial energyconsumption. The carbon emissions intensity decreased from 2005 to 2011, and would decrease in 2015and 2020. The carbon emissions intensity reduction rate would fail to meet the national target of 40e45%reduction in 2020 compared to the level in 2005 if no further mitigation methods were adopted. Toincrease the mitigation of carbon emissions, universal and unique methods were proposed in YRDHEZ:industrial structure adjustment, energy efficiency improvement, and adoption of renewable energy;transformation of reserve land into eco-land; and the employment of carbon capture and storagetechnology in the future. These results and implications would provide valuable suggestions for devel-opment of YRDHEZ.

© 2014 Elsevier Ltd. All rights reserved.

1. Introduction

In recent years, GHG emissions have attracted more and moreattention because of global warming and consequent significantdamages (Dhakal, 2008; Kennedy et al., 2009). Cities, whichoccupy less than 1% of the earth surface and concentrate over 50%of the population, emit about 80% of the world's GHG emissions(Feng et al., 2014). Therefore, more studies are concentrated onGHG emissions at the city level (Dhakal, 2009; Li et al., 2010). Atthe city level, most of the studies focused on geographical andadministrative boundaries due to data availability and compari-sons among cities. The literature addressed GHG emission sourcesdifferently, some only covered CO2 emissions (Tian et al., 2013),others focused on CH4, N2O, and other greenhouse gases (Bi et al.,2011). The sectors the literature focused on also differed (Shao

odiversity, School of Life Sci-/fax: þ86 531 [email protected] (Y. Wang).

et al., 2014; Liu et al., 2012). Mega cities, such as capitals, hadpriority in carbon emission calculations at the city level. Thestudies mainly explored carbon emission trajectories and driversand inhibiting factors of certain cities (Liu et al., 2012; Wang et al.,2012; Xi et al., 2011). Some inquired into the carbon emissions inthe coming years under different development scenarios (Lin et al.,2010; Liu et al., 2009). Generally, across cities, great variations arewitnessed in the scale of total emissions, carbon emission density,and the per capital emissions. The variations mainly came fromthe nature of emission sources, industrial structures, and energymixes (Dhakal, 2008).

Two sources of standards and protocols were mainly used in thecalculation of carbon emissions at the city level: the technical re-ports and methodology guidelines of the International Panel onClimate Change (IPCC) and the Greenhouse Gas Protocol (GHGprotocol) (IPCC, 2006) of the World Resource Institute (WRI) andthe World Business Council on Sustainable Development (WBCSD)(WBCSD, 2004). The IPCCmethod, which focuses on local emissionsand has an important impact on the local situation and arguably

M. Sun et al. / Journal of Cleaner Production 81 (2014) 89e10290

should be thought of as themost important object for accounting, iscontroversial because it excludes any indirect emissions and doesnot give a comprehensive picture of carbon emissions of a city(Hoornweg et al., 2011; Jacobson, 2010). The GHG protocol is alsodisputed because it regards GHG emissions outside of thegeographical boundaries as indirect emissions. Because of theabove reasons, the concept “scope ” was used to delineate directand indirect emissions and avoid double accounting (ICLEI, 2009).Scope 1 includes all direct GHG emissions within the geographicalboundary which contains fossil fuel consumption, waste emission,industrial processes and product use, agriculture, forestry, andother land uses (AFOLU). Scope 2 includes the indirect GHG emis-sions of purchased electricity, steam, and heating. Scope 3 includesother life-cycle emissions excluded from scope 1 and 2, such asembodied emission from food and materials consumed (Kennedyet al., 2010). The ideal scope of GHG emissions should includeScope 1e3 (Xi et al., 2011). Due to data availability and multiplecounting problems, most of the studies only included Scope 1 and2. A new standard, which aims at carbon emissions at city ormunicipal levels, was developed by the Local Governments forSustainability (ICLEI) and has been popular since over 1000 localgovernments worldwide have taken part in its initiatives. However,the ICLEI approach cannot be applied to Chinese circumstancessince the statistics in China cannot meet the ICLEI statistical re-quirements (Feng et al., 2014). By far, most of the studies are basedon the standards and protocols of IPCC guidelines and GHGprotocols.

Carbon emissions studies were also conducted at the nationallevel to reveal national level emissions and find mitigating solu-tions from a holistic perspective. Carbon trade is another reason forcalculation at the national level. IPCC guidelines, inputeoutputmodels, and the stochastic frontier model have been employed toestimate the carbon emissions at the national level (Chen and Chen,2010; Dong et al., 2013; Zhang et al., 2011). Previous literaturemainly focused on the following aspects: total carbon emissions inthe whole economy or in specific sectors, carbon emissions indifferent regions in the country and influencing factors, theconvergence analyses of different regions, and the spillover ofdifferent regions (Huang and Meng, 2013; Meng et al., 2013; Zhanget al., 2011). The results of those studies provided a database forcarbon emissions in the nation and put forward feasible carbonmitigation methods at the national level.

Compared to studies at city and national levels, research at theregional level was much less. This might be because regionsconsist of multiple counties from different cities and the incon-sistence of development policies and strategies complicate theanalysis. Also, the lack of carbon trade among different regionswithin the country might slow down the process of carbonemission calculation at the regional level. As one of three deltas(Yangze River Delta, Pearl River Delta and Yellow River Delta) inChina, the Yellow River Delta is facing great development op-portunities and challenges. Unlike the Yangze River Delta andPearl River Delta which are characterized by great economicvolume, all-scale export-oriented economy, and a large popula-tion, the Yellow River Delta is still in the early stage of economicdevelopment. With the endorsement of Yellow River Delta High-efficient Eco-economic Zone (YRDHEZ) by the central govern-ment, the development plan in this region will be more consis-tent. A high speed booming economy, a new pattern ofurbanization, and highly-efficient eco-industrial system are ex-pected to happen, which might bring about large quantities ofcarbon emissions. Therefore, it is essential to explore the carbonemission trajectory in the past years and predict the carbonemissions in the future in YRDHEZ and put forward effective andefficient methods to mitigate carbon emissions. The research can

not only provide information and insights for the development ofYRDHEZ, but be of great reference value for integrative devel-opment zones in China and of the world.

In this study, following the IPCC guidelines, carbon emissions inYRDHEZ were investigated and calculated from retrospective andprospective aspects. In this paper, we want to answer the following2 questions: (1) what is the trajectory of carbon emissions inYRDHEZ and (2) will carbon emission intensity in 2020 meet thenational target of 40e45% reduction compared to the level in 2005?In addition, we also tried to provide ways to reduce carbon emis-sions in YRDHEZ.

2. Methodology

2.1. Study area and data collection

YRDHEZ was endorsed by China's government in 2009 and islocated along the Yellow River estuary in Shandong Province. Itconsists of 196 counties in 6 cities(Dongying City; Binzhou City;Hanting County, Shouguang County and Changyi County inWeifang City; Qingyun County and Laoling County in DezhouCity; Laizhou County in Yantai City; and Gaoqing County in ZiboCity) with an area of 26.5 thousand square kilometers (Fig. 1).The total population was 9.88 million and the GDP was 456.4billion RMB in 2008 (NDRC, 2009). YRDHEZ is characterized witha large amount of reserve land and this reserve land is increasingbecause of the Yellow River alluvia. The oil and natural gasstorage is 5 billion tons and 230 billion cubic meters respectivelywhich make it an energy base for the whole country. It is alsothe largest salt chemical engineering base in China and a bigreservoir for wind energy, geothermal energy, and marine re-sources. YRDHEZ has been a heavy industrial zone since 1960safter oil was discovered. Secondary industry accounted for 69.3%in 2006, of which 87% of the industrial added value came fromtextile, building materials, energy, machinery, and chemical en-gineering industries (Gu and Yang, 2011). The development ofindustries has resulted in a large amount of GHG emissions andenergy consumption. According to the plan, the GDP of YRDHEZwill double that of 2008 in 2015 and be over 3 times in 2020,which will be mainly achieved by the secondary industrydevelopment. The energy demand and carbon emission will betremendous.

Data used in this paper come from city statistical documents andpublished reports and literature. Data on industrial energy con-sumption, industrial processes and products use, fugitive emission,ground transportation, and annual breading stock of livestock wereobtained from the Statistical Yearbook of Dongying (DMSB,2006e2012b), Statistical Yearbook of Binzhou(BMSB,2006e2012), Statistical Yearbook of Weifang (WMSB,2006e2012), Statistical Yearbook of Yantai (YMSB, 2006e2012),Statistical Yearbook of Dezhou(DMSB, 2006e2012a), and StatisticalYearbook of Zibo (ZMSB, 2006e2012). Data on waste and trans-portation prediction were obtained from the literature (He et al.,2005; Mou et al., 2009; Qu and Yang, 2011).

2.2. Scope of research

Determining the boundary of the study area's carbon emission isof great importance since the study area as an open system ofteninvolving intensive energy and materials exchanges with the sur-roundings. The World Resource Institute/World Business Councilfor Sustainable Development defined GHG emissions related to thespatial boundary at a city scale. To reflect the real emissions in thegeographical boundary, we only considered Scope 1 for the emis-sions because Scope 2 reflects the real emissions in power plants

Fig. 1. Geographical location of the study area.

M. Sun et al. / Journal of Cleaner Production 81 (2014) 89e102 91

rather than in the study area. In the study, six sectors included inthe GHG emissions in YRDHEZ were industrial energy consump-tion, industrial processes, fugitive emissions, transportation, live-stock emissions, and solid waste.

2.3. Calculation methods for different sectors

2.3.1. Industrial energy consumptionPrimary sources of energy were considered in the industrial

energy consumption in YRDHEZ. The primary sources of energyinclude crude coal, washed coal, other washed coal, briquette, coke,coking products, coke oven gas, blast furnace gas, natural gas, LNG,crude oil, gas, kerosene, diesel, fuel oil, LPG, refinery dry gas, andother petroleum products. According to the IPCC Guidelines for

National Greenhouse Gases Inventories, carbon emissions from theindustrial sector were calculated as follows:

Ei ¼Xi

ECi � EFi (1)

where Ei is carbon emission from the industrial energy consump-tion sector, t- CO2e; i is the type of energy consumed; ECi is theterminal-type consumption of energy i, unit (ton, m3); and EFi isthe carbon emission factor of energy type i (CO2e per unit). The dataof energy consumption of different sources were obtained from theStatistic Yearbooks of different cities (2007e2012). CO2e emissionfactors were calculated according to IPCC recommend method andthe net calorific value came from the China Energy StatisticalYearbook (NSB, 2009), while the carbon content and oxidation rate

M. Sun et al. / Journal of Cleaner Production 81 (2014) 89e10292

came from Guidelines for Provincial GHGs List in China (NDRC,2011).

2.3.2. Fugitive emissionSince YRDHEZ is a big energy source base and petroleum pro-

cessing base for the country, fugitive emissions which mainly comefrom energy source exploitation and processing were included inthe study. Coal and petroleum mining and petroleum processingwere considered. The calculation methods were as follows:

EF ¼Xi

EPi � EFi (2)

where EF is the carbon emissions from the fugitive emissions sector,t- CO2e; i is the type of energy produced or processed; EPi is theenergy production or processing in type i which can be obtainedfrom the Statistical Yearbooks of different cities, t; and EFi is thecarbon emission factor of type i, t- CO2e per unit. The carbonemission factors came from the Guidelines for Provincial GHGs Listin China (NDRC, 2011).

2.3.3. TransportationAccording to previous studies, ground transportation accounts

for over 70% of the total carbon emission in the transportationsector in China (He et al., 2005). Due to data availability, onlyground transportation was calculated in this study. Kennedy et al.(2010) summarized three methods to calculate the carbon emis-sion of ground transportation at the city level. The first one is to uselocal fuel sale data where data are available. The second method isto use vehicle kilometers traveled (VKT) within cities to estimatefuel consumption. The third method is to estimate the fuel con-sumption based on the scale of the regional data. It turned out thatthe three approaches produce reasonable close estimates if the VKTcalculations are appropriate. Therefore, the second method wasemployed in the calculation due to data availability. Each vehiclefleet was calculated for its fuel consumption and carbon emission,which includes trucks (heavy, medium, light, and micro), buses(heavy, medium, light, and micro), cars, and motorcycles. Thecalculation methods are as follows:

ET ¼Xi

hVPi � VMTi � FEi � EFg=d

i� 10�3 (3)

where ET is the carbon emissions from the ground transportationsector, t- CO2e; VPi is the number of vehicles of type I; VMTi is theaverage number of kilometers traveled by vehicle type i, kilome-ters/vehicle/year; FEi is the fuel economy of the vehicle type i, L/Km; and EFg/d is the carbon emission factor for gasoline or diesel,Kg- CO2e/L.

The vehicle numbers were obtained from the Statistical Year-book of the cities and VMT and FE were obtained from He et al.(2005). EF was calculated based on the carbon content, carbonoxidation, and net calorific data from Guidelines for ProvincialGHGs List in China (NDRC, 2011) and the Chinese Energy StatisticalYearbook (NSB, 2009).

2.3.4. Industrial processesCarbon emissions in industrial processes mainly refer to GHG

emissions from industrial processes which exclude emissions fromcombustion for the industrial energy supply. Considering dataavailability, we only included three major industrial processes:mining, chemical, and metal industries. The production data andemission factors were derived from the Statistical Yearbooks ofcities and Guidelines for Provincial GHGs List in China (NDRC,2011).

Mining industry: according to IPCC, cement, lime, and glassproduction are the dominant industrial sectors in carbon emissionin the mining industry, especially for cement production whoseemissions account for 5% of total global carbon emissions. Thecarbon emission calculation for the cement production process is asfollows:

Ec ¼ ½M � C� � EF (4)

where Ec is the carbon emission from cement production process, t-CO2e; M is the production of cement, ton; C is the ratio of cementclinker (default value is 65%); and EF is the emission factor ofclinker, t- CO2e/t-clinker (default value is 0.538).

Chemical industry: The carbon emissions in the chemical in-dustry were mainly from the following processes: ammonia pro-duction, nitric acid production, and sodium carbonate production.The production of the chemicals came from Statistical Yearbooks ofcities and emission factors came from Guidelines for ProvincialGHGs List in China (NDRC, 2011).

Metal industry: The metal industries which generate GHGemissions include production of steel, crude steel, pig iron, andaluminum. The production data came from Statistical Yearbooks ofcities and emission factors came from Guidelines for ProvincialGHGs List in China (NDRC, 2011).

2.3.5. Livestock emissionsThe carbon sources of AFOLU were calculated. Enteric fermen-

tation and manure management were taken into consideration.Direct and indirect N2O emissions were excluded from this studysince there are no available data. The method used to calculatelivestock emissions is summarized as follows:

EL ¼Xi

Li � EFi (5)

where EL is the carbon emission from livestock, Li is the number oflivestock in type i, and EFi is the emission factor of entericfermentation or manure management.

2.3.6. Solid wasteThe IPCC report (IPCC, 2006) shows that about 3%e4% of

anthropogenic GHG emissions were caused by CH4 emissionsgenerated from solid waste disposal sites. It also shows that about97% of the municipal solid waste is disposed of by landfill in China.So, the landfill was considered as solid waste. The IPCC stronglyrecommends the use of the First Order Decay Model to calculatecarbon emission from landfill waste, which needs at least 50 yearsof landfill waste data. Due to data availability, we applied the solidwaste emissions of China which were calculated by Qu and Yang(2011) to the study area based on GDP.

2.4. Total carbon emissions in YRDHEZ

The overall carbon emissions in YRDHEZ include emissions fromfossil fuels combustion, industrial process, fugitive emissions fromenergy resources exploitation and processing, transportation,livestock emissions, and waste management. We did not includethe carbon emission embodied in imported electricity, heat, andsteam, nor exclude the exported ones. What the study focused onwas the real emission within the boundary.

2.5. Prediction of carbon emissions in 2015 and 2020

According to the Plan for YRDHEZ (NDRC, 2009), the energyconsumption intensity per GDP in 2015 will be reduced by 22%

Table

1GHG

emission

sof

differentcities

andtheirratio.

Cities

2005

2006

2007

2008

2009

2010

2011

GHG

emission

s10

4tCO2e

Share

GHGem

ission

s10

4tCO2e

Share

GHGem

ission

s10

4tCO2e

Share

GHG

emission

s10

4tCO2e

Share

GHG

emission

s10

4tCO2e

Share

GHG

emission

s10

4tCO2e

Share

GHG

emission

s10

4tCO2e

Share

Don

gying

4008

.188

46.72%

4609

.19

40.46%

5450

.66

40.90%

5658

.68

41.83%

6128

.64

41.87%

7503

.02

45.73%

8173

.49

46.32%

Binzh

ou23

62.752

27.54%

4030

.21

35.38%

4874

.19

36.57%

4911

.60

36.30%

5188

.03

35.44%

5332

.05

32.50%

5583

.57

31.64%

Han

ting,

Shou

guan

g,Chan

gyi

1198

.935

13.97%

1486

.42

13.05%

1636

.89

12.28%

1502

.67

11.11%

1921

.94

13.13%

1995

.02

12.16%

2142

.56

12.14%

Laizhou

347.64

574.05

%41

3.19

3.63

%43

7.66

3.28

%41

8.14

3.09

%41

8.55

2.86

%43

0.17

2.62

%44

4.11

2.52

%Qingy

un,L

aolin

g40

6.51

094.74

%45

4.64

3.99

%48

6.34

3.65

%59

8.32

4.42

%52

2.99

3.57

%60

1.78

3.67

%56

1.92

3.18

%Gao

qing

255.28

082.98

%39

8.93

3.50

%44

2.30

3.32

%43

9.62

3.25

%45

8.24

3.13

%54

3.75

3.31

%74

1.73

4.20

%To

tal

8579

.312

100.00

%11

392.77

100.00

%13

328.23

100.00

%13

529.23

100.00

%14

638.60

100.00

%16

405.99

100.00

%17

647.57

100.00

%

M. Sun et al. / Journal of Cleaner Production 81 (2014) 89e102 93

compared to that in 2008 and in 2020 by 15% compared to that in2015. Therefore, the energy consumptions in 2015 and 2020 werepredicted.

The number of vehicles in ground transportation in ShandongProvince was expected to reach 36.34 million in 2020 (Mou et al.,2009). YRDHEZ, which accounts for 12.52% of the vehicles inShandong Province in 2008, was expected to have 2.87 millionand 4.55 million ground vehicles in 2015 and 2020 respectivelyassuming that vehicle share of YRDHEZ is the same as that in2008. According to He et al. (2005), numbers of different types ofvehicles were predicted and fuel consumptions and carbonemissions in this sector were calculated.

Industrial energy consumption and transportation are the onlytwo sectors that consume energy. Therefore, the energy con-sumptions in the industrial energy consumption sector in 2015and 2020 were calculated and allocated to different energy sour-ces according to the ratios of different types of energy sources in2008. Then the carbon emissions in industrial energy consump-tion sector were predicted for 2015 and 2020.

In the fugitive emission sector and industrial process sector, itwas assumed that the increase rates of industrial products andenergy production were in accordance with the increase rate ofsecondary industry which would share 50% and 53% of theeconomy in 2015 and 2020 respectively (Gu and Yang, 2011).

According to the increase rate of livestock in recently years, thenumbers of livestock and corresponding carbon emissions tend tobe stable as shown in the results. Therefore, it was assumed thatthe number of the livestock would be the same as that of 2008. Forthe solid waste sector, it was assumed that it would proportionallyincrease with the national increase.

3. Results

3.1. Sectoral carbon emissions

3.1.1. Industrial energy consumptionCarbon emissions for different cities (counties) and their ratios

in industrial energy consumption sector were calculated andaggregated into total emissions in YRDHEZ. The results are shownin Table 1. The carbon emission from the industrial energy con-sumption sector dramatically increased with an average increaserate of 11% per year, reaching 135.29 Mt CO2e in 2008 and 176.48Mt CO2e in 2011. Dongying City and Binzhou City, as the maincities in the study area, contributed the most to the carbonemissions. The increment of emissions of different types of energyshowed that carbon emissions mainly came from six types ofenergy fuels, crude coal, washed coal, coke, crude oil, fuel oil, andother petroleum products, which covered about 98% of the totalemissions in this sector. (Fig. 2) Though still the dominant fueltypes, the carbon emissions proportions of crude coal and crudeoil substantially decreased, while the proportions of washed coaland fuel oil increased.

3.1.2. Fugitive emission sectorFugitive emissions mostly come from coal, oil, and natural gas

exploitation, and their processing. As is shown in Fig. 3, the carbonemissions in this sector were steady at between 800 and 900thousand tons CO2e from 2005 to 2011. Dongying City, accountedfor over 95% of the carbon emissions, while the rest of the cities intotal supplied less that 5% of the carbon emissions in this sector.

3.1.3. TransportationCarbon emissions in the transportation sector and the numbers

of different types of vehicles are shown in Fig 4. It can be seen thatthe carbon emission in this sector substantially increased. The

Fig. 2. Proportion of different types of energy in the industrial energy consumption sector.

M. Sun et al. / Journal of Cleaner Production 81 (2014) 89e10294

carbon emission in this sector reached 1.23 Mt CO2e in 2010, almost1.8 times of that in 2006. The carbon emissions in 2011 wereslightly less than that in 2010. The number of cars and trucksdramatically increased, as did their carbon emissions whichincreased 109.3% and 121.0% respectively from 2005 to 2011. Whilecarbon emissions from buses steadily increased, there was somedecrease in the carbon emissions from motorcycles.

3.1.4. Industrial processesCarbon emissions from the industrial processes sector have

dramatically increased in the past few years. The carbon emissions

Fig. 3. Carbon emissions in the fugitive

in this sector reached 15.32 Mt CO2e in 2011 and were over 3 timesof that in 2005 with an average 33.71% annual increase. (Fig. 5)Though its proportion decreased from 62.72% in 2005 to 31.84% in2011, cement production was still the largest contributor to carbonemission in the industrial processes sector, followed by the pig ironproduction process which was about one quarter of the carbonemissions. Crude steel and primary aluminum (except for 2009)emissions largely increased, and the share of carbon emissionsfrom the crude steel process increased from 2.20% in 2005 to24.24% in 2011. Cement emissions steadily increased (except for2010).

sector and ratio of Dongying City.

Fig. 4. Carbon emissions from the transportation sector and numbers of main types of vehicles.

M. Sun et al. / Journal of Cleaner Production 81 (2014) 89e102 95

3.1.5. Live stock emissionsThe carbon emissions in the livestock emissions sector were

calculated. The results showed that the carbon emissions in thissector reached about 3.30 Mt CO2e and there was no obvious trendin the carbon emissions increase. (Fig. 6) Most of the carbonemissions came from cows which made up about three-quarters ofthe total emissions in this sector. Pigs and sheep contributed anextensive proportion of carbon emissions. Other large animals andpoultry supplied a very small percentage of carbon emissions.

Fig. 5. Carbon emissions in each industry and tota

3.1.6. Solid wasteCarbon emissions in this sector reached 1.46 Mt CO2e in 2011.

There was no obvious trend in carbon emissions from solid waste.

3.2. Total carbon emission in YRDHEZ

Theoverall carbonemissions sharply increased from2005to2011.The total emissions reached 209.44Mt CO2e in 2011 with an average16.45% annual increase rate (Fig. 7). According to Fig. 8, carbon

l emissions in the industrial processes sector.

Fig. 6. Carbon emissions in the livestock sector and share of different types of livestock.

M. Sun et al. / Journal of Cleaner Production 81 (2014) 89e10296

emissions related to industrial energy consumption accounted formost of the emissions, with the percentage varying from 81.38%(2005) to 86.69% (2007). The share of carbon emissions related totransportationand industrialprocesseswas steadywithapercentagevarying from 4.50% to 8.00%, while the share of carbon emissions forlivestock emissions, fugitive emissions and solidwaste declinedwitha percentage less than 3%. The increase rate of total carbon emissionsvaried with the smallest increase rate 3.07% in 2008. The industrialenergy consumption sector was the largest carbon emissions sourceand the increase rate fluctuated from 1.51% to 32.79%. Carbon

Fig. 7. Total carbon em

emissions for the industrial processes sector steadily increased withan annual increase rate varying from6.53% to 23.44% except for somedecline in 2006. Carbon emissions for transportation had a stableincrease rate which peaked at 21.54% in 2009 (Fig.9).

3.3. Carbon emission intensity

The carbon emissions per GDP and per capital in YRDHEZ andeach city are summarized in Table 2. Carbon emission intensityreached 3.28 in 2011. However, the carbon emission density varied

issions in YRDHEZ.

Fig. 8. Proportion of different sectors.

M. Sun et al. / Journal of Cleaner Production 81 (2014) 89e102 97

among different cities. Using 2011 as an example, the largest in-tensity came from Gaoqing in Zibo City with an intensity of 6.28,and the smallest intensity came from Laizhou in Yantai City whoseintensity was 1.19, less than one fifth of the former and about 36% ofthe overall intensity in YRDHEZ. Carbon emission intensitydecreased during 2006e2011, but it increased from 2005 to 2006.The overall carbon intensity increased from 3.72 in 2005 to 4.16 in2006 and then decreased to 3.28 in 2011 with an overall 11.76%decrease rate. The decrease rate also varied from city to city. The

Fig. 9. Increase rate of total carbon

largest decrease was from Laizhou in Yantai City (47.17%) and therewas some increase in the carbon density in Dongying City.

The carbon emission per capital (CO2e per capital) dramaticallyincreased. As shown in Table 3, the overall emission factor reached21.03 in 2011. The emission factors also varied from city to city. Thelargest came from Dongying City with a factor of 47, and thesmallest came from Laizhou, Yantai City with a factor of 7.29. Theincrease rate analysis of carbon emission per capital from 2005 to2011 showed that the overall increase rate was 95.56%, and the

emissions and different sectors.

Table 2Carbon emission intensities in YRDHEZ and in different cities (t- CO2e/104 Yuan).

Cities 2005 2006 2007 2008 2009 2010 2011

Dongying 3.20 3.48 3.58 2.96 3.22 3.42 3.27Binzhou 4.43 5.59 4.24 4.67 4.55 4.21 3.82Hanting, Shouguang,

Changyi4.19 4.24 3.83 3.23 3.61 3.22 3.03

Laizhou 2.25 2.00 1.73 1.56 1.49 1.31 1.19Qingyun, Laoling 5.26 4.84 4.29 4.23 4.18 3.68 3.26Gaoqing 9.96 9.10 8.34 6.73 5.85 6.27 6.28Overall 3.72 4.16 3.77 3.47 3.61 3.50 3.28

M. Sun et al. / Journal of Cleaner Production 81 (2014) 89e10298

largest increase rate came fromGaoqing, Zibo City, and the smallestcame from Laizhou, Yantai City.

3.4. Carbon emissions in 2015 and 2020

The carbon emissions in 2015 and 2020 were predicted andsummarized. As shown in Fig. 10, the carbon emissions in 2015 willbe 246.60 Mt CO2e which will be 1.56 times that in 2008, and in2020 the number will be 341.34Mt CO2e and 2.15 times that in2008. The proportion analysis showed that industrial energy con-sumption will still be the largest contributor to total carbon emis-sion, though its share will substantially decrease. The share ofcarbon emissions related to transportation and industrial processessectors will significantly increase. The actual carbon emissions intransportation and industrial processes sectors in 2015 will be 5.39and 3.29 times that in 2008 respectively. There will be a slight in-crease of the share of fugitive emissions, but the share of livestockemissions and solid waste sectors will decline. All three sectors willproduce less than 1% of the total emissions in 2020. The carbonemissions intensity will be 2.65 and 2.28 in 2015 and 2020respectively.

4. Discussion

4.1. The dynamics of sectoral emissions

As the largest contributor to carbon emissions in YRDHEZ, car-bon emissions in industrial energy consumption significantlyincreased from 2005 to 2011. This was mainly because (1) YRDHEZis a heavy-industry region with a large quantity of high energy andcarbon emission intensive industries, such as construction mate-rials and chemical engineering industries (Gu and Yang, 2011). (2)YRDHEZ is still in the developing stagewhich needs a fast economicincrease, resulting in rapid growth of secondary industry and cor-responding carbon emissions. (3) The energy mix showed that themain energy sources were crude coal and oil, and the share of

Table 3GHG emissions from study area and other cities.

Cities Per capital emissions (t-CO2e/cap)

Washington D. C.a 18.1Study areab 17.6Chicagoa 13.4Sydneya 11.7Nanjinga 9.8Singaporea 9.5Hongkonga 6.7Londona 6.2Tokyoa 5.1Madrida 4.9Stockholma 3.4

a Source: Bi et al. (2011).b Source: Results of this paper.

cleaner energy sources was very low. (4) Electricity, heating, andsteam production carbon emissions are included in this sector sinceall these are produced in secondary industries. The variation ofshares of different cities in this sector mainly came from economicdifferences. The share of carbon emissions of Dongying City in thissector was still dramatically increasing, mainly because of its higheconomic increase.

Fugitive emissions were included in the study because YRDHEZhas been an important energy source base and energy processingbase for China. The fugitive emissions were very small compared toother sectors. Most of the emissions in this sector came fromDongying City which is the home to one of the largest oil field inChina, Shengli Oilfield and numerous petroleum refining industries(Gu and Yang, 2011).

The carbon emissions increase in the transportation sectormainly came from cars and trucks. Different from other studies (Biet al., 2011; He et al., 2005), the largest increase and increase ratecame from trucks rather than cars. The high ratio of industrieswhich needed cargo transportation might explain the high increaseof carbon emissions from trucks. The slight decrease of carbonemission in the transportation sector in 2011 came from the factthat the carbon emissions from motorcycles were not included inthe study in 2011 since the Statistical Yearbooks stopped reportingthe number of motorcycles in 2011. Carbon emissions from carswere still the largest emission source in the transportation sectorwhich showed the same increasing trend as other studies. Carbonemissions from the transportation sector are a big contributor tototal carbon emissions in global cities, with a percentage of 20e50%(Kennedy et al., 2010). However, in this study, the share of carbonemissions in transportation varied from 4.0% to 6.3%, much lowerthan global cities, and lower than that in cities in China (Bi et al.,2011).

Cement, pig iron, and crude steel were the three largest com-ponents in carbon emissions in the industrial processes sector andaccounted for over 80% of the total emissions in this sector. Theresults were in accordance with the situation in YRDHEZ thatconstruction materials and machinery were the dominant in-dustries (Gu and Yang, 2011). It should be noted that the carbonemissions calculated here were a little less than the actual emis-sions in the industrial processes sectors since we only considered afew industries.

4.2. High carbon emissions and emissions intensity in YRDHEZ

Positively correlated to GDP, carbon emissions in YRDHEZsharply increased from 2005 to 2011 except for 2007e2008 whenthere was a global recession and the increase rate was 1.51%. In-dustrial energy consumption, transportation, and industrial pro-cesseswere three largest components for carbon emissions. As seenin Table 3, the carbon emission density analyses showed that thecarbon emission intensity and carbon emissions per capital weremuch higher than in the literature (Bi et al., 2011; Kennedy et al.,2009; Xi et al., 2011). They were also higher than the averagelevels of Shandong Province and China (Fig. 11). This could beexplained as follows. First, industrial structures and characteristicsin YRDHEZ contribute to the high emissions. The secondary in-dustries accounted for 69% of the industry in YRDHEZ in 2009 (Guand Yang, 2011), which was much higher than that of ShandongProvince and the national average. Heavy industries with a shortindustrial chain, low added economic value, high energy, and car-bon emission intensity make up most of the secondary industries.According to statistics, 87% of the industrial added value came fromfive major industries in 2006 (Gu and Yang, 2011), textile, buildingmaterials, energy, machinery, and chemical engineering industries.Second, the comparatively low energy efficiency in the study area

Fig. 10. Total carbon emissions and carbon emissions intensity in 2015 and 2020.

M. Sun et al. / Journal of Cleaner Production 81 (2014) 89e102 99

might be another important factor responsible for high carbonemissions. Third, most of the previous studies focused on big cities,which are service-oriented and heavily dependent on other re-gions. Although embodied emissions from imported energy, heat-ing, and steam were included (in some case not included) in thetotal emissions, the embodied emissions from other products andservices were not calculated, such as imported food and materials.

Fig. 11. Carbon emissions intensity of YRDHEZ

The study areawas YRDHEZ which is an industry-oriented area andproduces energy and products for other areas. The embodied en-ergy and carbon emissions of the products and materials exportedto other regions were included and calculated. So carbon emissionswithin the geographical boundary of YRDHEZ were high.

The carbon emission intensity in 2006 and 2007 was higherthan that in 2005. This was mainly because 2006 was the first year

, China, and Shandong Province in 2009.

M. Sun et al. / Journal of Cleaner Production 81 (2014) 89e102100

of 11th Five-Year-Plan, and the construction of “resource-conser-vative and environment-friendly” society was beginning, and thusenergy efficiency was still low. However, from 2007 the carbonintensity substantially decreased which was in accordance with the11th Five-Year-Plan.

The variance of carbon emission density of different cities wascaused by different industrial structures and the economic devel-opment level. The high carbon emission per GDP in Gaoqing, ZiboCity was mainly caused by the large quantity of chemical engi-neering industries. The high carbon emissions per capita in Don-gying City were mainly caused by high increases of industries andthe economy.

4.3. Carbon emissions in the future

Urbanization is thought to be one of the main drivers for eco-nomic growth and carbon emissions increase in China (Liu et al.,2012). In the study area, the urbanization rate was 42.5% in 2008,lower than the national average level (45.68%). With the imple-mentation of “Urbanization Development Outline for ShandongProvince” and “The Yellow River Delta High-efficient Eco-economicZone Development Plan”, the urbanization rate will be 54% in 2015and 60% in 2020 respectively. This implies a great deal of carbonemission growth in YRDHEZ. The largest increase would come fromthe industrial energy consumption sector, while the largest in-crease rate would come from the transportation sector.

According to the plans, YRDHEZ will still be the national energybase and salt and chemical engineering demonstration bases(NDRC, 2009). Also, textile and manufacture industries will have alarge development potential in the coming years. The rapiddevelopment of the economy and secondary industries will beaccompanied by an increased carbon emission potential. As theeconomy and urbanization rate increase, the transportation willdramatically increase, as will the carbon emissions from thetransportation sector. All these factors will contribute to the sharpincrease of carbon emissions.

Carbon emissions in 2015 and 2020 will largely increase, whilecarbon emission intensity (CO2e per GDP) will decrease. The na-tional target of reducing the intensity of carbon dioxide emissionper GDP in 2020 is 40e45% reduction compared to that in 2005. Theanalysis showed that the reduction rate in 2020 will be 34.46%compared to 2008 and 38.86% compared to 2005 which will notmeet the national target if no further carbon emissions reductionpolicies and methods are employed. More efforts are needed forcarbon emission control in YRDHEZ. Carbon emission per capitawill also increase, which will be 23.87 CO2e per capital and 31.87CO2e per capital in 2015 and 2020 respectively. The prevailingincreasing trend seems to be inevitable with the high increasingrate of urbanization and a booming economy.

4.4. Uncertainties

Uncertainties exist in carbon emissions calculation processes.Some are common to all kinds of calculationmethods such as errorsin emission factors caused by emission variability in different re-gions. Some are unique to certain studies due to data availabilityand study areas differences. The uncertainties in this study mainlycame from the following aspects. First, non-point GHG emissionsfrom household biomass, coal, and natural gas burning for cookingor heating were not included in the study since no data wereavailable. Second, some emissions, such as emissions from solidwaste, were calculated according to national data and then allo-cated to the local area, which may be different from the actualsituation in the local areas. Third, in the industrial processes sector,we only consideredmining, chemical, andmetal productions due to

data availability, which underestimated the actual carbon emis-sions in industrial processes. Fourth, in the transportation sector,VKT and FE were based on data from other literature and trans-portation numbers in 2015 and 2020 were predicted based onother's results. All the above will affect the results of carbonemissions. Quantitative analysis of the above uncertainties isneeded for further studies when more basic information on carbonemissions is released.

4.5. Ways for carbon emission reduction

With the construction of a low-carbon society, carbon emissionreduction will deserve special attention and be an important issuein national and local construction processes. As shown in aboveanalyses, the industrial energy consumption sector will still be themain emission sector and have the greatest potential for emissionsreduction. Besides improving energy efficiency, industry upgrade,technology, and management innovation mentioned by otherstudies, there are some unique methods in YRDHEZ to countercarbon emission increase.

First, substitutions for fossil fuels would be a goodway to reducefossil fuels combustion and carbon emissions. In addition to richmineral resources and fossil fuels, wind power energy is anotherrich energy resource in YRDHEZ. There are more than 10 middle orlarge scalewind power plants in this area and another 10 large scaleplants will be built in near future which will be mainly in Laizhou,Yantai City and Wudi, Binzhou City (Gu and Yang, 2011). Anotherimportant energy source is geothermal resources. According toinvestigations, the storage of geothermal energy in YRDHEZ couldbe 130 Mtce (Gu and Yang, 2011), the utilization of which wouldsubstantially reduce the fossil fuel consumption. Solar energy isalso a potential energy source for carbon emission reduction sinceit would greatly reduce the carbon emissions compared to tradi-tional energy sources (Sims et al., 2003). However, the utilization ofbiomass needs more consideration since the carbon emissionreduction effects are not certain (Righelato and Spracklen, 2007).

Second, the most typical advantage of YRDHEZ is its largeamount of and growing reserve land, much of which is salt marshand a source of emissions for GHGs (Chen et al., 2013). The con-version of salt marsh to eco-land would transform the carbonsource to a carbon sink in this area, such as forests, wetlands, andgrasslands. Therefore, ecological restorations to turn salt marshreserve land to land use types that have carbon sink functions areneeded in the study area. Land use types, such as forests, wetlands,and grasslands, also have other ecosystem services, such as waterand soil conservation and air purification.

4.6. Policy implications

To construct a high-efficient and eco-economic zone and meetthe national target of carbon emissions intensity reduction, carbonemissions reduction is urgently needed in YRDHEZ.

In the development plan, there is no certain and explicit targetsand methods for carbon emissions reduction. Since policy targetscould significantly offset the carbon emissions (Wang and Chen,2010), an explicit and vigorous carbon emissions target should beproposed for YRDHEZ from a holistic perspective. The unbalancedindustrial structure, dominated by secondary industry which ishigh carbon intensive, calls for adjustment in YRDHEZ. More ter-tiary industry is greatly needed. New energy sources or green en-ergy sources are a significant substitution for fossil energy. Theabundances of wind energy, solar energy, and geothermal energy inthe study area make it possible to employ new types of energy forindustrial and living purposes. Policies on renewable energyexploitation should be developed.

M. Sun et al. / Journal of Cleaner Production 81 (2014) 89e102 101

Green plants which have the ability to absorb carbon dioxideand give off oxygen play a vital role in carbon emissions reduction.The decay and decomposition of dead plant body are sources forGHG emissions. Many reserve lands in YRDHEZ serve as a carbonsource rather than a carbon sink (Chen et al., 2013), which increasescarbon emissions. Therefore, it is essential to convert large amountsof reserve land from a carbon source into a carbon sink with thehelp of appropriate technologies and ecological engineering. Pol-icies giving impetus to ecological restoration in YRDHEZ should bemade and implemented. According to International Energy Agency,energy efficiency and renewable energy will not achieve the goal of50%e80% CO2 emissions by 2050 (Stangeland, 2007). However,carbon capture and storage (CCS) allows the coexistence of fossilenergy consumption and GHG emissions reduction by capturing,transporting, and safely storing the CO2 arising from fossil fuelcombustion into an underground geological formation. The utili-zation of CCS that will substantially reduce carbon emissionsthough technologies is still in the process of development(Stangeland, 2007). Therefore, CSC should be a crucial measure forcarbon emission reduction in YRDHEZ where the main energysources are coal and oil. Policies addressing the above aspects areurgently needed to reduce carbon emissions in YRDHEZ.

The development pattern of YRDHEZ could provide valuablereferences for development of other similar areas. Integrativedevelopment is a typical characteristic for YRDHEZ. Integrativedevelopment of different regions has been proposedmany times bythe government to stimulate economy and sustainable develop-ment. The accompanying carbon emissions change should also bestressed in integrative development regions. Integrative policies oncarbon emissions reduction targets and methodologies thoseYRDHEZ could provide insight and references in other integrativedevelopment zones. As a main energy base and important heavyindustry base in China, YRDHEZwill continue providing energy andsources in China. The carbon emissions reduction in YRDHEZ couldalso be of great significance for areas that serve as energy and re-sources bases.

5. Conclusions

Carbon emissions in YRDHEZwere calculated from 2005 to 2011for 6 sectors, including industrial energy consumption, fugitiveemissions, transportation, industrial processes, livestock emissions,and solid waste. The carbon emissions in 2015 and 2020 were alsopredicted according to the plan. Carbon emissions sharplyincreased in YRDHEZ from 2005 to 2011 and should still substan-tially increase in 2015 and 2020. Industrial energy consumption isand will still be the largest sector of carbon emissions which pro-duces 79.46%e86.69% of the total carbon emissions in YRDHEZ. Theshare of transportation and industrial processes is increasingthough their share is still low.

The carbon emissions intensity and carbon emissions percapital analysis showed that overall carbon emissions intensitywas decreasing and will still decrease in 2015 and 2020, whilecarbon emissions per capital was increasing and will increase in2015 and 2020. However, carbon emissions intensity and carbonemissions per capital were much higher than other cities, whichmight be explained by an irrational industrial structure, low effi-ciency, and embodied carbon emissions for other areas in YRDHEZ.The carbon emissions in 2015 and 2020 will be sharply reduced,but the rate of reduction will fail to meet the national target of40e45% carbon emissions reduction compared to the level in2005.

Therefore, the high carbon emissions call for multiple measuresto reduce carbon emissions. Carbon emission reduction that targetsestablishments, industrial structure adjustment, renewable energy

usage, land use conversion, and CCS were proposed to reduce car-bon emissions in YRDHEZ. The implementation of those policyimplications could help reduce carbon emissions and transit to alow-carbon society in YRDHEZ. The research could also provideinsights for regional integrated development for areas similar toYRDHEZ.

Acknowledgments

This work was supported by China Postdoctoral Science Foun-dation funded project (2013T60656), Open Foundation of MLRLAB(CCA2013.09), and National Natural Science Foundation(41301640). Thanks to Dr. Edward C. Mignot, Shandong University,for linguistic advice.

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