Professor — Waste Management Engineer
Chen’s research and extension focus on value-added products from waste, mitigation of environmental impacts caused by waste, and dissemination of science-based information to help stakeholders make informed decisions, leading to positive changes.
- Ph.D., Iowa State University, 2008
- M.S., China Agricultural University, 1993
- B. S., China Agricultural University, 1989
- Advanced technologies for treating animal manure and other organic wastes
- Gas/odor/PM emissions monitoring
- Data acquisition and control system development
- Environmental control and ventilation systems for animal housing
- Development/improvement/application of various waste treatment technologies
- Wu, SX., L. Chen, J. Zhu, M. Walquist, D. Christian. 2018. Pre-digestion to enhance volatile fatty acids (VFAs) concentration as a carbon source for denitrification in treatment of liquid swine manure. Journal of Environmental Science and Health Part A, 53:10, 891-898, DOI: 10.1080/10934529.2018.1459072.
- Wu, S., J. Zhu, and L. Chen. 2017. Feeding schemes and C/N ratio of a laboratory-scale step-fed sequencing batch reactor for liquid swine manure treatment. Journal of Environmental Science and Health, Part A 52:8, 718-726. DOI: 10.1080/10934529.2017.1301748.
- Ni, J.Q., S. Liu, C.A. Diehl, T.T. Lin, B.W. Bogan, L. Chen, L. Chai, K. Wang, and A.J. Heber. 2017. Emission factors and characteristics of ammonia, hydrogen sulfide, carbon dioxide, and particulate matter at two high-rise layer hen houses. Atmospheric Environment (154) 260-273. DOI: 10.1016/j.atmosenv.2017.01.050.
- Kafle*, G. K., L. Chen, B. Glaze, and T. Tindall. 2016. Aerobic treatment of liquid swine manure using polymer: evaluation for ammonia gas emission reductions and nitrogen retention. Engineering in Agriculture, Environment and Food 9(3): 257-263. DOI: 10.1016/j.eaef.2016.01.005.
- Kafle*, G. K., L. Chen. 2016. Comparison on batch anaerobic digestion of five different livestock manures and prediction of biochemical methane potential (BMP) using different statistical models. Waste Management 48(2016) 492-502. DOI: 10.1016/j.wasman.2015.10.021.