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Frontiers of Environmental Science & Engineering

ISSN 2095-2201

ISSN 2095-221X(Online)

CN 10-1013/X

邮发代号 80-973

2018 Impact Factor: 3.883

Frontiers of Environmental Science & Engineering  2014, Vol. 8 Issue (1): 79-88   https://doi.org/10.1007/s11783-013-0516-1
  RESEARCH ARTICLE 本期目录
Neighborhood form and CO2 emission: evidence from 23 neighborhoods in Jinan, China
Neighborhood form and CO2 emission: evidence from 23 neighborhoods in Jinan, China
Jiaxing GUO1, Huan LIU1(), Yang JIANG2,3, Dongquan HE2, Qidong WANG1, Fei MENG2, Kebin HE1()
1. State Key Joint Laboratory of Environment Simulation and Pollution Control, School of ?Environment, Tsinghua University, Beijing 100084, China; 2. The Energy Foundation, Beijing 100004, China; 3. School of Architecture, Tsinghua University, Beijing 100084, China
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Abstract

To understand the household CO2 emission level in China, as well as how much the neighborhoods’ socio-economic or design factors could influence the CO2 emission, 23 neighborhoods in Jinan were investigated in 2009 and 2010. These neighborhoods fall into four different types: superblock, enclave, grid and traditional. The household CO2 emission includes sources of both in-home energy use and passenger transportation. The average CO2 emission per household is 7.66 t·a-1, including 6.87 t in-home operational emission and 792 kg transportation emission. The household CO2 emission by neighborhood categories is 10.97, 5.65, 6.49, 5.40 t·household-1·a-1 for superblock, enclave, grid and traditional respectively. Superblock has the highest average emission and also the highest percent (more than 25%) of transportation emission among four different types of neighborhoods. The residential CO2 emission of superblock neighborhoods in Jinan has already reached the level in developed countries nearly ten years ago. It is predictable that more superblock neighborhoods would be built in China with the fast urbanization. How to avoid the rapid household CO2 emission growth in the future would be a systematic issue. The study also found that in addition to income and apartment area, household density, land use mix and accessibility to public transportation are three primary factors which have significant impacts on CO2 emission. High density, mixed land use and convenient accessibility to public transportation tend to reduce household CO2 emission.

Key wordsCO2 emission    neighborhood type    transportation    household energy    China
收稿日期: 2012-09-17      出版日期: 2014-02-01
Corresponding Author(s): LIU Huan,Email:liu_env@tsinghua.edu.cn; HE Kebin,Email:hekb@tsinghua.edu.cn   
 引用本文:   
. Neighborhood form and CO2 emission: evidence from 23 neighborhoods in Jinan, China[J]. Frontiers of Environmental Science & Engineering, 2014, 8(1): 79-88.
Jiaxing GUO, Huan LIU, Yang JIANG, Dongquan HE, Qidong WANG, Fei MENG, Kebin HE. Neighborhood form and CO2 emission: evidence from 23 neighborhoods in Jinan, China. Front Envir Sci Eng, 2014, 8(1): 79-88.
 链接本文:  
https://academic.hep.com.cn/fese/CN/10.1007/s11783-013-0516-1
https://academic.hep.com.cn/fese/CN/Y2014/V8/I1/79
typologyneighborhood namenear BRT (yes or no)distance to city center /kmneighborhood population /personsample number /household
traditional1. Zhang Villageyes3.011190309
2. Dikouno5.0778992
3. Furongno0.77594125
grid4. Commercial Districtno3.611720296
5. Commercial Southno2.48439117
6. Commercial Northyes2.75526122
enclave7. Wuyingtanyes4.616130305
8. Yanzishanno3.521000304
9. Dongcangyes2.35600296
10. Foshanyuanno0.85300281
11. Gannanyes1.69205123
12. Kuangshanyes6.317977172
13. Taoyuanno8.76541110
superblock14. Shanghai Gardenno7.36400305
15. Sunshine 100no4.819000303
16. Lvjingjiayuanyes2.82500230
17. Mingshiyes6.1604988
18. Quancheng Gardenyes7.211147188
19. Weidongyes4.94759108
20. Jixiangyuanno4.3412792
21. Digital Bayno3.5154649
22. Feicuijunyes4.21440081
23. New Worldno4.3307273
Tab.1  
Fig.1  
itemcarbustaximotorcyclee-bike
energy typegasolinedieselgasolinegasolineelectricity
EIm /(MJ?km-1)2.96210.6802.6730.6120.076
CO2 EFfuel /(t?TJ–1)69.374.169.369.3
FUm /(L?km-1) a)0.0920.3b)0.0830.0190.021c)
Tab.2  
fuelbituminous coalanthracitecoalnatural gasliquefied petroleum gas (LPG)coal gasdieselgasoline
IPCC categoryenergy industriesresidentialresidentialresidentialResidentialtransportationtransportation
associated HH energy sourceelectricity centralized heatinghousehold coalgasgasGastransitcar/motor
CO2EFfuel /(t·TJ-1)94.698.356.163.144.474.169.3
Tab.3  
item of surveysample numbermeanstandard deviationmaxmin
operational /(CNY·month-1)electricity2400122929003
gas1000453550010
goal445413140010
heating1633549230215050
transportationfrequency /(trips·week-1)car26278.345.17400.125
taxi2475.614.54281.000
motor2418.275.35301.000
e-bike12529.735.89601.000
bus36187.845.21400.125
length /(km·trip-1)car256612.3811.14900.250
taxi2239.017.54401.000
motor2417.006.17400.425
e-bike12087.186.89600.200
bus348410.228.683000.100
occupancy /(occupancy·trip-1)car27131.530.7571.000
taxi2611.520.7741.000
motor2411.150.3521.000
e-bike12751.190.4341.000
bus-30a)---
Tab.4  
Fig.2  
Fig.3  
income /(10,000 CNY·a-1)
(0, 1](1, 3](3, 6](6, 9](9, 12](12,20](20,30](30,)
area /(m2)CO2 emission /(kg·HH-1·a-1)
(0, 20]522921262369182135373548
(20, 50]35093952437351524262473976084554
(50, 80]48344280508257285982604698259197
(80, 100]953557367637077676312307123078423
(100, 150]55158643789482709410100261138610005
(150, )368512632113331143912328138071663411455
Tab.5  
Fig.4  
Fig.5  
Fig.6  
Fig.7  
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