Tokyo Institute of Technology · Engineering
Professor Fumitake Takahashi's research lab focuses on environmental health and sustainable energy systems, with a strong emphasis on understanding the impact of pollutants—particularly mercury—on human health and ecosystems. The lab investigates atmospheric emissions from waste combustion, especially speciated mercury, and develops advanced monitoring and modeling techniques to reduce uncertainty in emission estimates. Additionally, the lab explores biomass resources such as crop residues and animal dung for bioenergy potential, using probabilistic modeling to quantify availability and energy yield under uncertainty. These interdisciplinary efforts bridge environmental science, public health, and renewable energy technologies.
Figures are computed from collected data and may differ slightly.
Patients with idiopathic ulcerative colitis (UC) have a colon- bound antibody (CCA-IgG) that reacts with colon tissue extracts. We have partially characterized a colonic protein that is specifically recognized by CCA-IgG. CCA-IgG was eluted from operative colon specimens from 10 patients with UC. A colon tissue-bound IgG was similarly eluted from six patients with Crohn's colitis, two with ischemic colitis, and one with diver- ticulitis. Purified serum IgG from patients with Crohn's disease, fro
Atmospheric mercury emissions have attracted great attention owing to adverse impact of mercury on human health and the ecosystem. Although waste combustion is one of major anthropogenic sources, estimated emission might have large uncertainty due to great heterogeneity of wastes. This study investigated atmospheric emissions of speciated mercury from the combustions of municipal solid wastes (MSW), sewage treatment sludge (STS), STS with waste plastics, industrial waste mixtures (IWM), waste pl
Crop residues and animal dung can contribute a significant portion to the biomass available for conversion to biofuels in Zimbabwe. This paper will extend a quantitative methodology involving the use of probability distributions to rigorously address uncertainty in the quantification of this biomass. The results of 100 000 Monte Carlo simulations using Palisade’s @Risk tool indicates the following at a 90% confidence interval: 2.55-5.50 million Mg/yr. of crop residue and 2.99-4.99 million Mg/yr.
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