Shule Liu

Dr. Shule Liu


Research Focus & Metrics

Academic Career Length

3Years (2024-Present)

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

Representative Publications

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27 September 2024 in Agriculture
Verified
Journal Article
Open access
PDF file
YWYurong Wang
Yurong Wang
SLShule Liu
Shule Liu
Qiuju XieQiuju Xie
Qiuju Xie
ZMZhanyun Ma
Zhanyun Ma
Dairy farming is one of the most important sources of greenhouse gas (GHG) emissions in the livestock sector. In order to identify the key emission links and the best emission-reduction strategies for combined dairy farms, this study selected a typical large-scale combined dairy farm in northeast China, constructed a carbon emission model based on the lifecycle assessment concept, and set up different emission reduction scenarios to explore the zero-carbon pathway for combined dairy farms. The results showed that: (1) enteric fermentation and manure management of cows are important sources of carbon emissions from the seeding-integrated dairy farms, accounting for 38.2% and 29.4% of the total, respectively; (2) the seeding-integrated system showed a 10.6% reduction in carbon footprint compared with the non-seeding-integrated system; and (3) scenarios 1–4 reduced carbon emissions by 9%, 20%, 42%, and 61% compared with the baseline scenario, respectively. Therefore, the integrated-farming model is important for the green development of animal husbandry, and as the “net-zero” goal cannot be achieved at present, integrated-farming dairy farms have the potential for further emission reduction. The results of this study provide a theoretical basis for low-carbon milk production.

21 April 2026 in Atmosphere
Verified
Journal Article
Open access
PDF file
DYDeng Yinhe
Deng Yinhe
YSYun Shu
Yun Shu
HSHong Sun
Hong Sun
SLShule Liu
Shule Liu
ZMZhanyun Ma
Zhanyun Ma
QGQingxian Gao
Qingxian Gao
This study estimates China’s methane (CH4) emissions from 43 specific emission sources in 2020 and projects future trends through 2050 under two scenarios: Current Legislation (CLE) and Maximum Technically Feasible Reduction (MFR). The analysis utilises the Greenhouse gas and Air pollution Interactions and Synergies (GAINS) model methane framework, incorporating updated province-level activity data to capture the pronounced regional heterogeneity inherent in emission profiles and mitigation capacities. The results reveal a national CH4 budget of 1114 MtCO2e in 2020, with the energy sector (59%) and agriculture (28%) emerging as the primary contributors. A substantial technical mitigation potential is identified; by 2050, emissions could be curtailed by up to 48% relative to the CLE scenario, representing a 46% reduction from 2020 levels. The energy and waste sectors emerge as the primary contributors to this potential. Specifically, coal mining CH4 abatement constitutes 58% of the energy sector’s total reduction potential, while enhanced solid waste management accounts for 97% of the mitigation within the waste sector. Key measures include ventilation air methane (VAM) oxidation and pre-mining degasification, as well as anaerobic digestion and recovery and utilization for energy use. Owing to regional disparities in hydrothermal conditions (representing the combined influence of temperature and moisture), demographic status, economic development, the most effective mitigation strategies vary across provinces. For example, pre-mining degasification and VAM oxidation are most impactful in major coal-producing regions such as Shanxi, Inner Mongolia, and Shaanxi. In contrast, anaerobic digestion, recovery and utilization, and waste incineration play a dominant role in more economically developed and densely populated provinces such as Jiangsu, Shandong and Zhejiang. By delineating region-specific technological priorities, this study quantifies the maximum technical mitigation potential for China and offers guidance for other nations facing similar mitigation challenges.

1 July 2026 in Journal of Environmental Management
Verified
Journal Article
Closed access
JHJie Hu
Jie Hu
SLShule Liu
Shule Liu
Wenkang GaoWenkang Gao
Wenkang Gao
bo hubo hu
bo hu
HLHuasheng Li
Huasheng Li
ZMZhanyun Ma
Zhanyun Ma