Investigation of the Best-case Scenario of Rice Husk/Briquette Combustion for Lower Particulate Matter Emission


Air pollution has been a major cause of diseases and deaths, especially in developing countries, due to their inability to afford cleaner sources of energy. Biomass such as agricultural residues is combusted, using inefficient combustion techniques, characterized by high emission of particulate matter (PM) and smoke, which have adverse effects on human health. This study investigated the best-case scenario of rice husk/briquette combustion that favors low PM2.5 emissions. Loosed rice husk and briquette samples of 3 g, were combusted in temperatures ranging from 600°C – 1000°C for a five-minute duration. The experimental set up comprises of a Yamato F100 fixed bed electric furnace attached with a fabricated tubular heat exchanger, and a dust track II aerosol analyzer. The dust track II instrument is a real-time single-channel PM counter and uses size selective cascade impactors. From the result, PM2.5 emission from the combustion of loosed rice husk increases from its minimum of 11.8 mg/m3 at 600°C to its maximum of 27.8 mg/m3 at 900°C. At 600°C, the combustion air was adequate for a low bulk density fuel, thus, clean combustion, however, as the temperature increases with constant combustion air, this leads to oxygen deficiency and consequently, higher emission. Contrastingly, PM2.5 emission from the combustion of rice husk briquette decreases from its peak of 57.9 mg/m3 to 29.8 mg/m3 as the temperature increases from 650°C to 950°C. The continuous increase of temperature leads to quick evolution from the smoldering phase into the burnt phase of a high bulk density fuel, consequently lower emission.

Author Information
Emmanuel Abah, University of Tsukuba, Japan
Ryozo Noguchi, University of Tsukuba, Japan

Paper Information
Conference: ECSEE2019
Stream: Energy: Renewable Energy and Environmental Solutions

This paper is part of the ECSEE2019 Conference Proceedings (View)
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Posted by James Alexander Gordon