kangmin Wu

kangmin Wu

orcid

Research Focus & Metrics

Academic Career Length

11Years (2016-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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1 February 2017 in Applied Geography
Verified
Journal Article
Closed access
Yang WangYang Wang
Yang Wang
Shaojian WangShaojian Wang
Shaojian Wang
GLGuangdong Li
Guangdong Li
HZHongou Zhang
Hongou Zhang
LJLixia Jin
Lixia Jin
KWkangmin Wu
kangmin Wu

22 December 2017 in Sustainability
Verified
Journal Article
Open access
PDF file
YYYuyao Ye
Yuyao Ye
CWChangjian Wang
Changjian Wang
YZYuling Zhang
Yuling Zhang
KWkangmin Wu
kangmin Wu
Qitao WUQitao WU
Qitao WU
YSYongxian Su
Yongxian Su
Optimising the spatial structure of cities to promote low-carbon travel is a primary goal of urban planning and construction innovation in the low-carbon era. There is a need for basic research on the structural characteristics that help to reduce motor traffic, thereby promoting energy conservation. We first review the existing literature on the influence of urban spatial structure on transport carbon dioxide emissions and summarise the influence mechanisms. We then present two low-carbon transportation oriented patterns of urban spatial structure including the traditional walking city and the modern transit metropolis, illustrated by case studies. Furthermore, we propose an improved model Green Transportation System Oriented Development (GTOD), which is an extension of traditional transit-oriented development (TOD) and includes the additional features of a walking city and an emphasis on the integration of land use with a green transportation system, consisting of the public transportation and non-auto travel system. A compact urban form, effective mix of land use and appropriate scale of block are the basic structural features of a low-carbon transportation city. However, these features are only effective at promoting low-carbon transportation when integrated with the green traffic systems. Proper integration of the urban structural system with the green space system is also required. The optimal land use/transportation integration strategy is to divide traffic corridors with wedge-shaped green spaces and limit development along the transit corridors. This strategy forms the basis of the proposed urban structural model to promote low-carbon transportation and sustainable urban growth management.

1 May 2019 in Applied Geography
Verified
Journal Article
Closed access
YYYuyao Ye
Yuyao Ye
KWkangmin Wu
kangmin Wu
Yichun XieYichun Xie
Yichun Xie
GHGengzhi Huang
Gengzhi Huang
CWChangjian Wang
Changjian Wang
JCJun Chen
Jun Chen

14 August 2023 in Sustainable Cities and Society
Verified
Journal Article
Closed access
KWkangmin Wu
kangmin Wu
YYYe Yuyao
Ye Yuyao
WXWang Xiangyu
Wang Xiangyu
LZLiu Zhengqian
Liu Zhengqian
ZHZhang Hong'OU
Zhang Hong'OU

31 July 2021 in Applied Spatial Analysis and Policy
Verified
Journal Article
Closed access
PDF file
Yang WangYang Wang
Yang Wang
KWkangmin Wu
kangmin Wu
YZYabo Zhao
Yabo Zhao
CWChangjian Wang
Changjian Wang
HZHong’oU Zhang
Hong’oU Zhang

11 February 2019 in PLOS ONE
Verified
Journal Article
Open access
PDF file
CWChangjian Wang
Changjian Wang
KWkangmin Wu
kangmin Wu
XZXinlin Zhang
Xinlin Zhang
FWFei Wang
Fei Wang
HZHongou Zhang
Hongou Zhang
BWBin Wen
Bin Wen
Based on the apparent energy consumption data, a systematic and comprehensive city-level total carbon accounting approach was established and applied in Guangzhou, China. A newly extended LMDI method based on the Kaya identity was adopted to examine the main drivers for the carbon emissions increments both at the industrial sector and the residential sector. Research results are listed as follow: (1) Carbon emissions embodied in the imported electricity played a significant important role in emissions mitigation in Guangzhou. (2) The influences and impacts of various driving factors on industrial and residential carbon emissions are different in the three different development periods, namely, the 10th five-year plan period (2003–2005), the 11th five-year plan period (2005–2010), and the 12th five-year plan period (2010–2013). The main reasons underlying these influencing mechanisms were different policy measures announced by the central and local government during the different five-year plan periods. (3) The affluence effect (g-effect) was the dominant positive effect in driving emissions increase, while the energy intensity effect of production (e-effect-Production), the economic structure effect (s-effect) and the carbon intensity effect of production (f-effect-Production) were the main contributing factors suppressing emissions growth at the industrial sector. (4) The affluence effect of urban (g-effect-AUI) was the most dominant positive driving factor on emissions increment, while the energy intensity effect of urban (e-effect-Urban) played the most important role in curbing emissions growth at the residential sector.