Bio

Zhenlin (Richard) Chen is a Ph.D. candidate at Stanford's Adam Brandt lab, focuses on greenhouse gas emissions from oil and gas. His work primarily revolves around evaluating ground sensor technologies for methane detection and quantification ability. His methodological approach blends engineering principles, field data collection, and applied statistics. Chen is exploring AI-driven frameworks, particularly large language models, to refine energy data extraction and enhance the OPGEE model through private data fine-tuning and reinforcement learning. His emphasis remains on domain-specific tasks, aiming for efficiency in terms of latency and cost. He pursued his undergraduate studies in environmental science at Cornell University and holds a master's in Atmosphere and Energy Engineering from Stanford.

Education & Certifications

  • Master of Engineering, Stanford University, Atmosphere and Energy
  • Master of Science, Cornell University, Information and Data Science
  • Bachelor of Science, Cornell University, Environmental Science

Contact

  • Academic
    zhenlinc@stanford.edu
    University - Student Department: Department of Energy Science and Engineering Position: Graduate

Additional Info

All Publications

  • Technological Maturity of Aircraft-Based Methane Sensing for Greenhouse Gas Mitigation. Environmental science & technology El Abbadi, S. H., Chen, Z., Burdeau, P. M., Rutherford, J. S., Chen, Y., Zhang, Z., Sherwin, E. D., Brandt, A. R. 2024

    Abstract

    Methane is a major contributor to anthropogenic greenhouse gas emissions. Identifying large sources of methane, particularly from the oil and gas sectors, will be essential for mitigating climate change. Aircraft-based methane sensing platforms can rapidly detect and quantify methane point-source emissions across large geographic regions, and play an increasingly important role in industrial methane management and greenhouse gas inventory. We independently evaluate the performance of five major methane-sensing aircraft platforms: Carbon Mapper, GHGSat-AV, Insight M, MethaneAIR, and Scientific Aviation. Over a 6 week period, we released metered gas for over 700 single-blind measurements across all five platforms to evaluate their ability to detect and quantify emissions that range from 1 to over 1,500 kg(CH4)/h. Aircraft consistently quantified releases above 10 kg(CH4)/h, and GHGSat-AV and Insight M detected emissions below 5 kg(CH4)/h. Fully blinded quantification estimates for platforms using downward-facing imaging spectrometers have parity slopes ranging from 0.76 to 1.13, with R2 values of 0.61 to 0.93; the platform using continuous air sampling has a parity slope of 0.5 (R2 = 0.93). Results demonstrate that aircraft-based methane sensing has matured since previous studies and is ready for an increasingly important role in environmental policy and regulation.

    View details for DOI 10.1021/acs.est.4c02439

    View details for PubMedID 38759639

  • Evaluating the Sustainable Development Goals within Spatial Planning for Decision-Making: A Major Function-Oriented Zone Planning Strategy in China LAND Fu, H., Liu, J., Dong, X., Chen, Z., He, M. 2024; 13 (3)

    View details for DOI 10.3390/land13030390

    View details for Web of Science ID 001192824300001

https://orcid.org/0000-0003-3295-6958