Qiao Xing

Dr. Qiao Xing


Research Focus & Metrics

Academic Career Length

4Years (2023-Present)

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

Representative Publications

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12 March 2025 in Toxics
Verified
Journal Article
Open access
PDF file
文魏文超 魏
文超 魏
YZYun Zhang
Yun Zhang
LWLicheng Wang
Licheng Wang
QXQiao Xing
Qiao Xing
JXJun Xiang
Jun Xiang
LMLing Mo
Ling Mo
China is facing increasing marine microplastic pollution. Despite the fact that the South China Sea is the largest marine area in China, the ecological danger and present state of microplastic contamination in this region have not been systematically and comprehensively investigated. This study analyzed the abundance, distribution, and characteristics of microplastics in different environmental media and biological samples from the Xisha Islands in the South China Sea, and then the ecological risk assessment of microplastic pollution in this area was conducted. The findings indicated that the quantities of sediments, soil, water, fish, and birds were 41.56 ± 19.12 items/kg, 92.94 ± 111.05 items/kg, 2.89 ± 1.92 items/L, 2.57 ± 2.12 items/ind, and 1.702 ± 1.50 items/ind, respectively. By evaluating the pollution load index (PLI), polymer hazard index (PHI), and potential ecological risk index (PERI), the PLI of the Xisha Islands in the South China Sea as a whole indicated that the hazard level was slightly polluted, the PHI was at a high-risk level, and the PERI samples were at no risk, except for the soil and seawater, which were at a medium-risk level.

15 July 2023 in Science of The Total Environment
Verified
Journal Article
Closed access
HTHuadong Tan
Huadong Tan
LWLicheng Wang
Licheng Wang
LMLing Mo
Ling Mo
CWChunyuan Wu
Chunyuan Wu
QXQiao Xing
Qiao Xing
QLQinfen Li
Qinfen Li

22 May 2026 in Atmosphere
Verified
Journal Article
Open access
PDF file
RXRongfu Xie
Rongfu Xie
YFYuzhen Fu
Yuzhen Fu
ZYZHaohui YANG
ZHaohui YANG
YSYating Song
Yating Song
XWXiaochen Wang
Xiaochen Wang
QXQiao Xing
Qiao Xing
Vehicle emission inventories are highly sensitive to vehicle activity data, yet annual vehicle kilometers traveled (VKT) is still commonly represented using generalized default values whose representativeness at the city scale remains uncertain. In this study, large-scale vehicle inspection data from Haikou, China, were used to derive inspection-based VKT estimates and to quantify how activity assumptions affect urban vehicle emission inventories and policy evaluation. By holding vehicle population and emission factors constant across scenarios, we explicitly isolated the effect of activity representation on emission estimates. An inspection-based, age-sensitive VKT framework was further developed to capture within-fleet heterogeneity. The results showed that inspection-derived VKT accounted for only 36–75% of guideline-recommended values across major vehicle categories, with the largest discrepancies observed for diesel freight vehicles. As a result, the use of guideline-based VKT produced higher emission estimates by 34–39% for carbon monoxide (CO) and volatile organic compounds (VOCs) and by approximately 66–67% for nitrogen oxides (NOx) and particulate matter (PM). The influence of activity representation was also evident in policy assessment. In a case study of old diesel vehicle retirement, guideline-based VKT produced estimated emission reduction benefits that were more than 120% higher for most pollutants and nearly 200% higher for NOx than those derived from inspection-based VKT. These findings demonstrate that generalized activity assumptions can substantially affect both emission inventory estimates and policy-oriented assessments. Rather than merely refining a local mileage parameter, this study highlights a potential representativeness limitation of generalized activity assumptions when they are applied to city-specific emission inventories, particularly in medium-sized or geographically constrained urban systems. The inspection-based, age-sensitive approach proposed here provides a practical pathway for improving activity representation in data-rich urban environments, while its transferability should be evaluated according to local fleet structure and transport conditions.