International Journal of Environment and Pollution Research (IJEPR)

EA Journals

Characterization and Modelling Of Air Pollutants Transport from Panteka Market, Jimeta-Yola, Nigeria

Abstract

The primary motivation of the current research was to apply Land GEM model to predict gaseous pollutant mobility by means of pollutant concentrations, annual waste mass received, and dumpsite open year from the research area. Land GEM model is believed to have wide application on emission rates from landfills/dumpsites using both site specific and default model parameters. Emission concentration levels were achieved through field and laboratory experimental work from vegetable waste dumpsites using scientific calibrated instruments. Data obtained were applied on Land GEM computer based software; version 3.02 in order to predict air-pollutant transport from the market environment and her surroundings. The model was tested to ascertain its validity where the measured and simulated values indicated good match with an error of 3.8% .The closure year of the case study dumpsite A was predicted to be in 2074 having reached hazardous level in 2024 while control dumpsite B predicted a closure year of 2023 and hazardous level in 2019 with modeling efficiency of 64%. Understanding the types of gases emitted from decomposing vegetable waste dumpsites (CH4, CO2, NMOC, H2S) and their transport pattern could go a long way to ensuring control measures of these pollutions there by having a sustainable zero wastes market to boost economic activities under pleasant environment; hence healthy environment is a prerequisite of healthy life, and fighting pollution is definitely the best way of healthy life.

Keywords: Air pollutants, Dumpsites, Land GEM, Model, Transport

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This work by European American Journals is licensed under a Creative Commons Attribution-NonCommercial-NoDerivs 4.0 Unported License

 

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Email ID: editor.ijepr@ea-journals.org
Impact Factor: 7.01
Print ISSN: 2056-7537
Online ISSN: 2056-7545
DOI: https://doi.org/10.37745/ijepr.13

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