Ming Hu

Dr. Ming Hu

University of Maryland College Park
orcid

Research Focus & Metrics

Academic Career Length

24Years (2003-Present)

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

Representative Publications

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19 October 2022 in Chemical Reviews
Verified
Journal Article
Closed access
YDYu Ding
Yu Ding
ZPZhenqian Pang
Zhenqian Pang
KLKai Lan
Kai Lan
YYYuan Yao
Yuan Yao
Guido PanzarasaGuido Panzarasa
Guido Panzarasa
LHLiangbing Hu
Liangbing Hu

3 March 2023 in Urban Climate
Verified
Journal Article
Closed access
Ming HuMing Hu
Ming Hu
KZKai Zhang
Kai Zhang
QNQuynh Nguyen
Quynh Nguyen
TTTolga Tasdizen
Tolga Tasdizen

1 February 2021 in Sustainable Cities and Society
Verified
Journal Article
Closed access
Ming HuMing Hu
Ming Hu
JRJennifer D. Roberts
Jennifer D. Roberts
GAGesine Pryor Azevedo
Gesine Pryor Azevedo
DMDavid Milner
David Milner

1 February 2019 in Resources, Conservation and Recycling
Verified
Journal Article
Closed access
JLJing Liang
Jing Liang
YQYueming Qiu
Yueming Qiu
Ming HuMing Hu
Ming Hu

29 May 2024 in Sustainability
Verified
Journal Article
Open access
PDF file
SGSiavash Ghorbany
Siavash Ghorbany
Ming HuMing Hu
Ming Hu
SYSiyuan Yao
Siyuan Yao
CWChaoli Wang
Chaoli Wang
The urban heat island (UHI) is a crucial factor in developing sustainable cities and societies. Appropriate data collection, analysis, and prediction are essential first steps in studying the effects of the UHI. This research systematically reviewed the papers related to the UHI that have used on-site data collection in the United States and Canada and the papers related to predicting and analyzing this effect in these regions. To achieve this goal, this study extracted 330 articles from Scopus and Web of Science and, after selecting the papers, reviewed 30 papers in detail from 1998 to 2023. The findings of this paper indicated a methodological shift from traditional sensors and data loggers towards more innovative and customized technologies. Concurrently, this research reveals a growing trend in using machine learning, moving from supportive to direct predictive roles and using techniques like neural networks and Bayesian networks. Despite the maturation of UHI research due to these developments, they also present challenges in technology complexity and data integration. The review emphasizes the need for future research to focus on accessible, accurate technologies. Moreover, interdisciplinary approaches are crucial for addressing UHI challenges in an era of climate change.

30 June 2023 in Science Advances
Verified
Journal Article
Open access
KKKyeezu Kim
Kyeezu Kim
BJBrian Joyce
Brian Joyce
DNDrew R. Nannini
Drew R. Nannini
YZYinan Zheng
Yinan Zheng
PGPenny Gordon-Larsen
Penny Gordon-Larsen
LHLifang Hou
Lifang Hou
Slower epigenetic aging is associated with exposure to green space (greenness); however, the longitudinal relationship has not been well studied, particularly in minority groups. We investigated the association between 20-year exposure to greenness [Normalized Difference Vegetation Index (NDVI)] and epigenetic aging in a large, biracial (Black/white), U.S. urban cohort. Using generalized estimating equations adjusted for individual and neighborhood socioeconomic characteristics, greater greenness was associated with slower epigenetic aging. Black participants had less surrounding greenness and an attenuated association between greenness and epigenetic aging [β NDVI5km : −0.80, 95% confidence interval (CI): −4.75, 3.13 versus β NDVI5km : −3.03, 95% CI: −5.63, −0.43 in white participants]. Participants in disadvantaged neighborhoods showed a stronger association between greenness and epigenetic aging (β NDVI5km : −3.36, 95% CI: −6.65, −0.08 versus β NDVI5km : −1.57, 95% CI: −4.12, 0.96 in less disadvantaged). In conclusion, we found a relationship between greenness and slower epigenetic aging, and different associations by social determinants of health such as race and neighborhood socioeconomic status.