Evaluation of the efficiency of a Venturi scrubber in particulate matter collection smaller than 2.5 µm emitted by biomass burning

评估文丘里洗涤器收集生物质燃烧排放的小于 2.5 µm 颗粒物的效率

阅读:19

Abstract

Energy demand has increased worldwide, and biomass burning is one of the solutions most used by industries, especially in countries that have a great potential in agriculture, such as Brazil. However, these energy sources generate pollutants, consisting of particulate matter (PM) with a complex chemical composition, such as sugarcane bagasse (SB) burning. Controlling these emissions is necessary; therefore, the aim was to evaluate PM collection using a rectangular Venturi scrubber (RVS), and its effects on the composition of the PM emitted. Considering the appropriate use of biomass as an industrial fuel and the emerging need for a technique capable of efficiently removing pollutants from biomass burning, this study shows the control of emissions as an innovation in a situation such as the industrial one with the use of a Venturi scrubber in fine particle collection, in addition to using portable and representative isokinetic sampling equipment of these particles. The pilot-scale simulation of the biomass burning process, the representative sampling of fine particles and obtaining parameters to control pollutant emissions for a Venturi scrubber, meets the current situation of concern about air quality. The average collection efficiency values were 96.6% for PM> 2.5, 85.5% for PM1.0-2.5, and 66.9% for PM< 1.0. The ionic analysis for PM< 1.0 filters showed potassium, chloride, nitrate, and nitrite at concentrations ranging from 20.12 to 36.5 μg/m3. As the ethanol and sugar plants will continue to generate electricity with sugarcane bagasse burning, emission control technologies and cost-effective and efficient portable samplers are needed to monitor particulate materials and improve current gas cleaning equipment projects.

特别声明

1、本页面内容包含部分的内容是基于公开信息的合理引用;引用内容仅为补充信息,不代表本站立场。

2、若认为本页面引用内容涉及侵权,请及时与本站联系,我们将第一时间处理。

3、其他媒体/个人如需使用本页面原创内容,需注明“来源:[生知库]”并获得授权;使用引用内容的,需自行联系原作者获得许可。

4、投稿及合作请联系:info@biocloudy.com。