Dong Xu

Dr. Dong Xu

orcid

Research Focus & Metrics

Academic Career Length

6Years (2021-Present)

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

Representative Publications

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1 October 2021 in Journal of Cleaner Production
Verified
Journal Article
Closed access
DXDong Xu
Dong Xu
FYFeng Yang
Feng Yang
LYLe Yu
Le Yu
Yuyu ZhouYuyu Zhou
Yuyu Zhou
HLHaixing Li
Haixing Li
Jie ChengJie Cheng
Jie Cheng

29 June 2023 in Journal of Environmental Management
Verified
Journal Article
Closed access
TBTingting Bai
Tingting Bai
YQYong Qi
Yong Qi
ZLZihao Li
Zihao Li
DXDong Xu
Dong Xu

19 February 2023 in Journal of Cleaner Production
Verified
Journal Article
Closed access
TBTingting Bai
Tingting Bai
Jie ChengJie Cheng
Jie Cheng
ZZZihao Zheng
Zihao Zheng
QZQifei Zhang
Qifei Zhang
ZLZihao Li
Zihao Li
DXDong Xu
Dong Xu

30 December 2023 in Oeconomia Copernicana
Verified
Journal Article
Open access
PDF file
TBTingting Bai
Tingting Bai
DXDong Xu
Dong Xu
QYQianyi Yang
Qianyi Yang
VPVargáné Dudás Piroska
Vargáné Dudás Piroska
LDLóránt Dávid
Lóránt Dávid
KZKai Zhu
Kai Zhu
Research background: To achieve the targets for carbon peak and air quality improvement, local governments should propose environmental targets and develop realization paths that are tailored to their unique local conditions. They then promote low-carbon development through the implementation of multiple measures. Purpose of the article: As the government performance appraisal system im-proves, the question arises as to whether governments take the initiative to com-bine environmental policies with government target constraints to reduce carbon emissions. Methods: The announcement of environmental target constraints by local governments in government work reports is considered a quasi-natural experiment. This study examines the effect of government environmental target constraints (GETC) on carbon emissions (CEs) using differences-in-differences (DID), propensity score matching-DID (PSM-DID), and spatial-DID (SDID) with data from 241 Chinese cities from 2003 to 2019. Findings & value added: The results demonstrate that GETC can effectively reduce local CEs, with the inhibitory effect being most effective in the first two years after setting environmental targets, but diminishing in the third year. GETC can reduce local CEs through three paths: reducing energy consumption, promoting industrial structure optimization, and encouraging green technology innovation. Spatial spillover effects show that GETC reduces local CEs while exacerbating CEs in neighboring cities, indicating a beggar-thy-neighbor effect in conventional environmental regulation policy. This effect is observed mainly in the geographic matrix and the economic-geographic matrix, but not in the economic matrix. According to heterogeneity analysis, GETC in the eastern and central cities can significantly reduce CEs. The inhibitory effect of GETC on local CEs is stronger in cities where secretaries and mayors have longer tenures and higher levels of education. The paper's theoretical value lies in exploring the reduction of CEs through the combination of government self-restraint and environmental policies, providing a new solution for local governments to achieve CEs reduction. Furthermore, it offers practical insights into the improvement of the Chinese government assessment system.

2 January 2022 in Remote Sensing
Verified
Journal Article
Open access
PDF file
DXDong Xu
Dong Xu
Jie ChengJie Cheng
Jie Cheng
XSXu Shen
Xu Shen
JGJing Geng
Jing Geng
FYFeng Yang
Feng Yang
HLHaixing Li
Haixing Li
The rapid development of urbanization and population growth in China has posed a major threat to the green sustainable development of the ecological environment. However, the impact of urbanization on the eco-environmental quality (EEQ) in China remains to be developed. Understanding their interactive coupling mechanism is of great significance to achieve the urban sustainable development goals. By using multi-source remote sensing data and the coupling coordination degree model (CCDM), we intended to answer the question “What are the temporal and spatial characteristics of urbanization and EEQ in China on the pixel scale during 2000–2013, and what is the coupling mechanism between the urbanization and the EEQ?”. To answer these questions, we explored the coupling mechanism between urbanization and the EEQ in China with a combined mathematical and graphics model. The results show that the urbanization and the coupling coordination degree (CCD) of the whole region continually increased from 2000 to 2013, especially in the three major urban agglomerations, with a spatial distribution pattern that was “high in the east and low in the west”. Most importantly, from 2000 to 2013, the CCD type of cities in China gradually evolved from uncoordinated cities to coordinated cities. Additionally, the decisive factor affecting the CCD from 2000 to 2013 was the development of urbanization, and the degree at which urbanization had an impact on CCD was about 8.4 times larger than that of the EEQ. At the same time, the rapid urbanization that has occurred in some areas has led to a significant decline in the EEQ, thus indicating that China needs to increase its protection of the ecological environment while pursuing social and economic development in the future. This study makes up for the deficiencies in the existing literature and investigates the long-term coupling of the EEQ and urbanization in China, thereby providing a new research perspective for the sustainable development of China and even the world in the future.

3 February 2023 in Journal of Environmental Management
Verified
Journal Article
Closed access
JSJian Sun
Jian Sun
YHYang Hu
Yang Hu
YLYang Li
Yang Li
LWLingfei Weng
Lingfei Weng
HBHaonan Bai
Haonan Bai
SLSha Lu
Sha Lu