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20 NOV 2023 (MON) 10:00-10:45 | 11:15-12:00 | 14:30-15:15 | 15:45-16:30

Departmental Research Seminars Series

Land System Science

Date: 20 NOV 2023 (Monday)

Time: 10:00-10:45 | 11:15-12:00 | 14:30-15:15 | 15:45-16:30 (HKT)

Mode: Hybrid Mode

Venue: CLL, Department of Geography, 10F, The Jockey Club Tower, Centennial Campus, HKU

Zoom: Zoom link will be provided upon successful registration


[ 10:00-10:45 ]


Efficient Land Use and Management as Climate Solutions for Rising Food and Wood Demand

The rising global population and income levels are expected to increase the demand for food and wood by over 50%. Current agricultural systems face enormous pressure to supply adequate, nutritious food while reducing their impacts on climate, land, and biodiversity. Similarly, forestry activities significantly reduce carbon storage in vegetation and soil, further intensifying land competition and climate impacts. Conversely, climate change has a profound influence on food production and forest ecosystems by altering water availability. My overarching research goal is to advance our understanding of the interactions between land use and climate. My work has ranged from examining the climate’s impact on agriculture and water cycles to mitigating land use emissions and promoting sustainable forestry and agriculture practices. Integrating ground observations with satellite data, I have developed long-term meteorological and evapotranspiration datasets crucial for agricultural drought analysis. Applying the GlobAgri model and carbon opportunity cost approach, I quantify emissions from agricultural production and land use change at scales ranging from country to global. To estimate the carbon costs associated with wood harvests, I developed a new global forestry carbon accounting model, CHARM, by synthesizing a variety of data sources. My research on wood production indicates that global wood harvests could account for significant annual emissions by 2050, highlighting a previously overlooked factor in climate change. My research on agricultural emissions presents robust mitigation potentials through technical pathways such as improved crop yields and livestock feeding efficiency. The findings deepen our understanding of the future climate and land use challenges posed by rising demand. They help redirect agriculture and forestry practices towards efficient production and consumption as solutions for climate mitigation.


Dr. Liqing PENG

Food & Agriculture Modeler, Food Program, World Resources Institute, United States

Dr. Peng earned her Ph.D. in Environmental Engineering from Princeton University in 2019. She also holds dual bachelor degrees in Geosciences and Philosophy from Peking University. Currently, Dr. Peng is a research scientist at the Food Program of the World Resources Institute, where she primarily focuses on carbon emissions and land use in food and wood production across various scales. She recently developed a new global forestry carbon and land-use accounting model, CHARM, where she oversees its development, data synthesis, and the critical analysis of global climate impacts tied to future wood demand. She also supports the development of the GlobAgri model to understand agriculture's greenhouse gas impacts under future scenarios. She is currently evaluating different pathways towards low-carbon agriculture in regions like Sub-Saharan Africa and China. Previously, Dr. Peng conducted research in the field of water resources and agriculture, and has developed meteorological datasets and evaporative demand models for agricultural drought monitoring. She has published more than 15 peer-reviewed publications, including high impact journals like Nature and Global Change Biology.


[ 11:15-12:00 ]


Moving Toward the Next-Generation Land Surface Modeling

The land system sequesters about 25% of human-emitted CO2, helping mitigate the changing climate. However, the future land carbon sink predicted by climate models is highly uncertain, making it difficult for policymaking. The primary reasons for this uncertainty include the lack of representation of the biological and biophysical processes, divergence in model parameterization schemes, and inadequate model calibration using regional and global scale data. Recent advances in vegetation models, soil and plant trait databases, and remote sensing data have allowed for dealing with these challenges. Embracing the latest model developments and growing data, we are developing the next-generation land surface model within the Climate Modeling Alliance. Our new model, CliMA Land, is process-based (with increasing implementations of surface processes), traitbased (better accounting for spatial and temporal variations of the land system), and hyperspectral (using satellite data for monitoring and calibration). We envision the move to next-generation land surface modeling will help improve the climate models’ predictive skills and explore nature-based solutions to climate change with increasing confidence.


Dr. Yujie WANG

Research Scientist, California Institute of Technology, California, United States

Yujie graduated from the University of Science and Technology of China in 2011 and 2013 for the bachelor and master degrees in Biology. Yujie obtained his PhD in plant biology from the University of Utah in 2020, and started his first postdoc at California Institute of Technology afterward. He is currently a staff scientist at California Institute of Technology, and his research focuses on vegetation and land surface modeling, particularly in how plants respond and acclimate to the changing climate. There at the Climate Modeling Alliance (CliMA), he leads the development of a next-generation land surface model CliMA Land from scratch. The research aims are to improve the Earth system models’ predictive skills in tracking global carbon, water, and energy fluxes using the increasing number of remote sensing data. To date, Dr. Wang has published more than 20 papers in the professional journals like Journal of Advances in Modeling Earth Systems and New Phytologist.


[ 14:30-15:15 ]


The Hydroxyl Radical: A Key to Air Quality and Climate

The hydroxyl radical (OH) lies at the nexus of climate and air quality as the primary oxidant for both reactive greenhouse gases and many hazardous air pollutants. Lacking direct observations, interannual trends of OH either in urban areas or at continental-to-global scale are not well understood due to the short lifetime and high spatial heterogeneity of OH. This talk will describe two examples from my research predicting OH using the synthesis of chemistry/climate model, satellite observations and machine learning. I will present the OH predictions in 49 North American cities between 2005 and 2014 and show how these OH predictions can be used to inform the best control strategy of ozone pollution in each city. As the main loss pathway of methane is the reaction with OH, I also present a novel approach to probe the OH trends at continental-to-global scale and utilize them to interpret the observed methane trends. I will also provide an overview of my current and future research in the context of addressing the interplay between air quality and climate change.


Dr. Qindan ZHU

NOAA Climate & Global Change Postdoctoral Fellow, Massachusetts Institute of Technology, United States

Qindan did her undergrad at Peking University with double majors in environmental science and mathematics. After getting her bachelor's degree in 2017, She pursued her PhD in Earth and Planetary Science at University of California at Berkeley, working with Prof. Ron Cohen. Her research topics include satellite observations of air pollutants, airborne flux measurements and urban OH chemistry. She is now a 2nd year NOAA Climate & Global Change Postdoc Fellow working with Prof. Arlene Fiore at MIT with the research on fully coupled chemistry-climate model and chemistry-climate interaction. She is the recipient of the CEE rising star in 2022 and the ACCESS (Atmospheric Chemistry Colloquium for Emerging Senior Scientists) in 2023. So far, she has published first-author papers in prestigious journals, including PNAS, ES&T, and ACP.


[ 15:45-16:30 ]


Towards Carbon Neutrality Under Climate Risk

Achieving carbon neutrality is the solution to combating climate change and ensuring sustainable development. On the side of carbon sink, land ecosystem has mitigated about 32% of the total anthropogenic CO2 emissions in the past six decades, but there is no consensus on how long land ecosystem may continue to be sustained under climate change. In this seminar, I will present how we combine ground observations, satellite measurements, and model simulations to improve the understanding of land carbon-climate interactions, with a focus on the critical drought-carbon feedback and underlying processes. On the side of carbon source, a fundamental transition from fossil fuel to green solar and wind energy is critical. In this seminar, I will present how we combine climate data, energy modeling, and geographic information system (GIS) analysis to provide an upto- date assessment of China’s wind and solar energy resources and propose a clear and actionable development strategy. Beyond China, I will also discuss how we identify climate change impacts on the energy security of wind and solar energy systems on a global scale. These synergistic studies on both sink and source support and accelerate carbon neutrality under climate risk.


Dr. Laibao LIU

Postdoctoral Research Scientist, ETH Zurich, Switzerland

Dr. Laibao Liu is a Postdoctoral Research Scientist at ETH Zurich, Switzerland. Prior to joining ETH Zurich, he received his Ph.D. in Physical Geography from Peking University. His research interests are land and climate systems, land-atmosphere interactions, land carbon cycle, and renewable energy, and his vision is to achieve a climate resilient and sustainable development by advancing carbon neutrality. He combines data science, climate and energy model, and geographic information system (GIS) analysis in research ranging from the local scale to the global scale, based on ground observations, satellite measurements and model simulations. He has published more than 20 peer-reviewed articles. His leading research outcomes are published in high-impact journals, such as Nature, Nature Energy and Nature Communications, and received several awards for his research, including 2022 Best Paper (“Research Article”) in Resources, Recycling & Reservation, Top 50 Nature Communications Earth and planetary sciences articles published in 2020, and two Highly Cited Papers by Clarivate since 2021 and 2023, respectively. In the last three years, he has been actively involved in two European Commission Horizon-funded research and innovation projects on climate change and carbon neutrality.



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