Qianjun Mao

Prof. Dr. Qianjun Mao


Research Focus & Metrics

Academic Career Length

14Years (2013-Present)

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

Representative Publications

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1 June 2020 in Renewable Energy
Verified
Journal Article
Closed access
Qianjun MaoQianjun Mao
Qianjun Mao
YZYamei Zhang
Yamei Zhang

1 June 2016 in Renewable and Sustainable Energy Reviews
Verified
Journal Article
Closed access
Qianjun MaoQianjun Mao
Qianjun Mao

1 January 2018 in Advances in Materials Science and Engineering
Verified
Journal Article
Open access
PDF file
Qianjun MaoQianjun Mao
Qianjun Mao
NLNing Liu
Ning Liu
LPLi Peng
Li Peng
Solar thermal energy storage (TES) is an efficient way to solve the conflict between unsteady input energy and steady output energy in concentrating solar power plant. The latent heat thermal energy storage (LHTES) system is a main method of storing thermal energy using phase change materials (PCMs). Thermal properties, that is, melting points and latent heat, are the key parameters of PCMs for the TES system. In this paper, the PCMs are classified into inorganic and organic by the chemical composition, and according to the melting point, the inorganic PCMs can be divided into three contributions: low‐temperature heat storage (less than 120°C), medium‐temperature heat storage (120–300°C), and high‐temperature heat storage (more than 300°C). The present article focuses mainly on the recent investigations on the melting point and latent heat of PCMs via DSC setup in the solar TES systems. The results can provide a good reference for the selection and utilization of PCMs in the solar TES systems.

1 December 2019 in Atmospheric Environment
Verified
Journal Article
Closed access
Qianjun MaoQianjun Mao
Qianjun Mao
CHChunlin Huang
Chunlin Huang
QCQixiang Chen
Qixiang Chen
HZHengxing Zhang
Hengxing Zhang
YYYuan Yuan
Yuan Yuan

29 September 2023 in Energy and Buildings
Verified
Journal Article
Closed access
Tao LiTao Li
Tao Li
QLQingxia Liu
Qingxia Liu
YGYanfeng Gong
Yanfeng Gong
JXJingtao Xia
Jingtao Xia
LSLei Shi
Lei Shi
Qianjun MaoQianjun Mao
Qianjun Mao

6 August 2021 in Remote Sensing
Verified
Journal Article
Open access
PDF file
CHChunlin Huang
Chunlin Huang
JLJunzhang Li
Junzhang Li
WSWeiwei Sun
Weiwei Sun
QCQixiang Chen
Qixiang Chen
Qianjun MaoQianjun Mao
Qianjun Mao
YYYuan Yuan
Yuan Yuan
Long-term (2000–2019) assessment of aerosol loads and dominant aerosol types at spatiotemporal scales using multi-source datasets can provide a strong impetus to the investigation of aerosol loads and to the targeted prevention control of atmospheric pollution in densely populated regions with frequent anthropogenic activities and heavy aerosol emissions. This study uses multi-source aerosol datasets, including Modern-Era Retrospective Analysis for Research and Applications version 2 (MERRA-2), Moderate Resolution Imaging Spectroradiometer (MODIS), and Aerosol Robotic Network (AERONET), to conduct a long-term variation assessment of aerosol load, high aerosol load frequency, and dominant aerosol types over Asia. The results indicate that regional aerosol type information with adequate spatial resolution can be combined with aerosol optical depth (AOD) values and heavy aerosol load frequency characterization results to explore the key contributors to air pollution. During the study period, the aerosol load over the North China Plain, Central China, Yangtze River Delta, Red River Delta, Sichuan Basin, and Pearl River Delta exhibited an increasing trend from 2000–2009 due to a sharp rise in aerosol emissions with economic development and a declining trend from 2010–2019 under stricter energy conservation controls and emissions reductions. The growth of urban/industrial (UI) type and biomass burning (BB) type aerosol emissions hindered the improvement of the atmospheric environment. Therefore, in future pollution mitigation efforts, focus should be on the control of UI-type and BB-type aerosol emissions. The Indus–Ganges River Plain, Deccan Plateau, and Eastern Ghats show a continuously increasing trend; however, the aerosol load growth rate of the last decade was lower than that of the first decade, which was mainly due to the decrease in the proportion of the mixed type aerosols.