Xiaoying Qian

Dr. Xiaoying Qian


Research Focus & Metrics

Academic Career Length

9Years (2018-Present)

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

Representative Publications

View All Publications
21 January 2022 in Materials Science and Engineering: A
Verified
Journal Article
Closed access
CHChao He
Chao He
YMYuan Ming
Yuan Ming
BJBin Jiang
Bin Jiang
SBShengwen Bai
Shengwen Bai
BLBin Lei
Bin Lei
FPFusheng Pan
Fusheng Pan

1 November 2018 in Ecological Economics
Verified
Journal Article
Closed access
WZWei Zhen
Wei Zhen
Quande  QinQuande Qin
Quande Qin
XQXiaoying Qian
Xiaoying Qian
YWYi-Ming Wei
Yi-Ming Wei

20 February 2024 in Applied Geography
Verified
Journal Article
Closed access
Yu YangYu Yang
Yu Yang
JXJiashun Xue
Jiashun Xue
JQJunxi Qian
Junxi Qian
XQXiaoying Qian
Xiaoying Qian

21 August 2025 in Nature Sustainability
Verified
Journal Article
Closed access
PDF file
Yu YangYu Yang
Yu Yang
YCYan Cheng
Yan Cheng
JPJessie P. H. Poon
Jessie P. H. Poon
ZYZhou Yannan
Zhou Yannan
XQXiaoying Qian
Xiaoying Qian
HZHaiping Zhang
Haiping Zhang

SXSiyou Xia
Siyou Xia
Yu YangYu Yang
Yu Yang
XQXiaoying Qian
Xiaoying Qian
XXXin Xu
Xin Xu
This study investigated the energy poverty spatiotemporal interaction characteristics and socioeconomic determinants in rural China from 2000 to 2015 using exploratory time–space data analysis and a geographical detector model. We obtained the following results. (1) The overall trend of energy poverty in China’s rural areas was “rising first and then declining”, and the evolution trend of energy poverty in the three regions formed a “central–west–east” stepwise decreasing pattern. (2) There was a dynamic local spatial dependence and unstable spatial evolution process, and the spatial agglomeration of rural energy poverty in China had a relatively higher path dependence and locked spatial characteristics. (3) The provinces with negative connections were mainly concentrated in the central and western regions. Anhui and Henan, Inner Mongolia and Jilin, Jilin and Heilongjiang, Hebei and Shanxi, and Liaoning and Jilin constituted a strong synergistic growth period. (4) From a long-term perspective, the disposable income of rural residents had the greatest determinant power on rural energy poverty, followed by per capita GDP, rural labor education level, regulatory agencies, and energy investment. In addition, our findings showed that the selected driving factors all had enhanced effects on rural energy poverty in China through interaction effects.

24 October 2025 in Energies
Verified
Journal Article
Open access
PDF file
QLQiqi Liu
Qiqi Liu
Yu YangYu Yang
Yu Yang
YLYi Liu
Yi Liu
XQXiaoying Qian
Xiaoying Qian
Embodied energy flows link production systems with the energy sector, reflecting dependencies and structural risks under globalization and regional coordination. Guangdong, China’s most manufacturing-intensive, open, and energy-consuming province, is a central hub in both global value chains and domestic production networks, playing a pivotal role in national energy security. Understanding Guangdong’s embodied energy flows is essential for revealing the transmission of energy across multi-level spatial systems and the resilience of China’s energy infrastructure. This study integrates international (EXIOBASE) and Chinese inter-provincial input–output data to build a province-level nested global MRIO model, combined with Structural Path Analysis (SPA), to characterize Guangdong’s manufacturing embodied energy flows in domestic and international dual circulation from 2002 to 2017. Our findings confirm Guangdong’s pivotal bridging role in embodied energy transfers. First, flows are dual-directional and dominated by international transfers. Second, energy efficiency has improved, narrowing the intensity gap between export- and domestic-oriented industries. Third, flows have diversified spatially from concentration in developed regions toward developing regions, with domestic inter-provincial flows more dispersed. Finally, embodied energy remains highly concentrated across sectors, with leading industries shifting from labor- and capital-intensive to capital- and technology-intensive sectors. This research offers vital empirical evidence and policy reference for enhancing national energy security and optimizing spatial energy allocation.