Sustainable Energy & Environment
Description
No matching items found.
People
Publications
- ● Urea-doped corn cob biochar for CO2 capture; Ketwalee Kositkanawuth, Jooladit Janda, Siriwipha Sirirat, et al.; 2024; Conference proceedings article
- ● USE OF BIOCHAR IMPREGNATED WITH IRON AND CHITOSAN FOR HEAVY METAL REMOVAL: SORPTION PERFORMANCES; Nattakarn Kruatong, Soydoa Vinitnantharat, Anawat Pinisakul, et al.; 2021; Conference proceedings article
- ● USING A MULTI-CRITERIA DECISION MAKING APPROACH IN CONJUNCTION WITH A DELPHI STUDY TO IDENTIFY FACTORS INFLUENCING POLLUTANT EMISSIONS; Walailak Atthirawong, Kanogkan Leerojanaprapa, Tuanjai Somboonwiwat, et al.; 2023; Conference proceedings article
- ● Using proteomic approaches to predict particulate matter stress response of ornamental plant; Arnon Setsungnern, Chairat Treesubsuntorn, Waleeporn Pongkua, et al.; 2024; Journal article
- ● Using stacked pot connection of wetland microbial fuel cells to charge the battery: Potential and effecting factor; Muhammad Nashafi, Azizuddin; Thiravetyan, Paitip; Dolphen, et al.; 2024; Journal article
Projects
- ● Absolute environmental sustainability assessment of hydrogen production from organic waste in Thailand; SHABBIR H. GHEEWALA - The Joint Graduate School of Energy and Environment
- ● “A feasibility study on the replacement of current diesel vehicles by electric, CNG, and EURO 6 exhaust emission standard vehicles in the Bangkok Metropolitan Region for ambient PM2.5 concentration reduction”.; YOSSAPONG LAOONUAL - Department of Mechanical Engineering
- ● A Greenhouse Rainwater Catchment System for Vegetable Cultivation in the Non-Irrigated Area; ANUSORN RATTANATHANAOPAT - Royal Project Foundation and King'S Recommended Project Supporting Center
- ● Air Pollution Assessment using Satellite Data: A Case Study of Greater Bangkok; KASEMSAN MANOMAIPIBOON - The Joint Graduate School of Energy and Environment
- ● An Accurate Description of Pre-Bias Space-Charge-Limited Current Measurements in Perovskite Thin Films for Accurate Charge Transport Properties: A New Machine Learning-Based Experimental-Computational Study; NON THONGPRONG - Office of the Dean












