Feng, Chenxi
Member Profile
School of Integrative Plant Science
Cornell University
110 Arboretum Rd
Ithaca, NY 14853
Email: cf545@cornell.edu
Website: https://sites.google.com/view/chenxi-fengs-website
EDUCATION
08/2024-present, Ph.D. in Soil and Crop Science, Cornell University
09/2020-06/2024, B.S. in Atmospheric Science, Nanjing University Nanjing, China
PUBLICATIONS
• Chenxi Feng, Sihe Chen, Zhao-Cheng Zeng, Yangcheng Luo, et al. (2024) Aerosol-Calibrated Matched Filter applied on retrievals of methane point source emissions over Los Angeles Basin, Earth & Space Science, doi:10.1029/2024EA003519
• Fei Li, Shiwei Sun, Yongguang Zhang, Chenxi Feng, et al. (2023) Mapping methane super-emitters in China and United States with GF5-02 hyperspectral imaging spectrometer, National Remote Sensing Bulletin, doi:10.11834/jrs.20232453
RESEARCH EXPERIENCE
Quantification of aerosol’s impact on methane retrieval, California Institute of Technology, Pasadena, USA (Project leader, supervised by Prof. Yuk Yung, 06/2023-01/2024)
• Used the two-stream-exact-single-scattering (2S-ESS) RT model to simulate synthetic radiance spectra with different aerosol properties, which are used to analyze aerosols’ effect on methane concentration estimation.
• Innovatively designed and developed an aerosol-calibrated matched filter method for methane retrieval to correct the aerosol-induced bias based on the model study. Optimized the algorithm's computational efficiency and performance to ensure its feasibility in practical applications.
• Performed algorithm performance assessments using end-to-end simulation and compare them with existing methane retrieval methods. Analyze the strengths and limitations of different methods under different aerosol scenarios.
• Utilized the developed algorithm for a case study on typical methane point sources in the Los Angeles basin using airborne (e.g., AVIRIS) remote sensing data. Evaluate the underestimation of methane point source emissions caused by aerosols and propose improvement strategies.
Methane inversion and point source identification, Nanjing University, Nanjing, China (Project leader, supervised by Prof. Yongguang Zhang, 02/2022 – 07/2024)
• Conducted research to enhance the performance of methane retrieval methods, explored new technologies which combine retrieval results in methane’s weak (1600-1900nm) and strong (2100-2400nm) absorption bands to improve the precision and efficiency of retrieval and collaborated with team members to collectively identify best practices and methods.
• Conducted end-to-end simulations to assess the overall performance of methane retrieval methods and validate the accuracy and credibility of inversion results using ground truth testing data.
• Used remote sensing data from China satellites (e.g., GF5, GF5B, ZY1E, etc.) and improved retrieval method, conducted methane column concentration retrieval work, performed data and image processing to obtain spatial distribution maps of methane concentration.
• Analyzed inversion results in potential methane emission areas, confirmed methane plumes within key regions, and located methane leakage from oil and gas industries in the US and the Middle East.
• Based on inversion results and the characteristics of methane plumes, estimated methane emission rates.
In-situ detection of methane and carbon dioxide, Nanjing University, Nanjing, China (Research assistant, supervised by Prof. Huilin Chen, 12/2022-12/2023)
• Collaborated with the team to design an unmanned aircraft methane and carbon dioxide monitoring system using Axetris AG and K96 sensors, ensuring that the system meets project requirements and technical specifications.
• Planned, designed, and conducted laboratory experiments to assess sensor performance, including sensitivity, accuracy, and response time to standardized methane and carbon dioxide gases, among other key parameters, and recorded and analyzed experimental data.
• Assisted in planning and preparing the necessary equipment and resources for field observation experiments over two methane emitters in Nanjing, China. Ensuring the proper functioning of the monitoring system and effective data collection.
• Extract crucial monitoring data from the experiments, analyzing methane plumes using Gaussian plume model, as well as providing recommendations on data interpretation and future improvement directions to support the successful implementation of the project.
AWARDS
2024, Chenxue Scholarship for Overseas Study, Nanjing University
2023, Scholarship of Academic Excellence (The First Prize, Top 5%), Nanjing University
2022, Zhenggang Fellowship for Oversea Studies of Nanjing University (Top 5%), Nanjing University
2022, Scholarship of Academic Excellence (The Second Prize, Top 10%), Nanjing University
2022, Outstanding Student for Theory and Methods of Land Surface Remote Sensing Inversion Summer School 2022 of Beijing Normal University
2021, Scholarship of Academic Excellence (The Second Prize, Top 10%), Nanjing University
TECHNICAL SKILLS
Proficient in using Python, MATLAB, and Fortran
