Findings on Modelling Carbon Dioxide Concentration Scenarios in the Nairobi Metropolitan Region before and during COVID-19

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dc.contributor.author Okwaro, John Okanda
dc.date.accessioned 2024-08-14T14:32:45Z
dc.date.available 2024-08-14T14:32:45Z
dc.date.issued 2024-08-14
dc.identifier.citation OkwaroJO2021 en_US
dc.identifier.uri http://localhost/xmlui/handle/123456789/6455
dc.description Proceedings of the Sustainable Research and Innovation Conference JKUAT Main Campus, Kenya 6 - 7 October, 2021 en_US
dc.description.abstract The increasing concentration of GHG in the atmosphere has been verified as the most important cause of global warming. Carbon (IV) oxide (CO2) is the most important of them all and is the greatest contributor to global warming. CO2 is emitted majorly from fossil fuel combustion and industrial production. The sources, of interest, of CO2 in the study area are mining activities, transport system, and industrial processes. This study is aimed at building models that will help in monitoring the emissions within the study area. A statistical modelling approach was applied. The Orbiting Carbon Observatory-2 (OCO-2) and the Orbiting Carbon Observatory-3 (OCO-3) secondary data were used. Three scenarios were discussed, namely: pessimistic scenario; business-as-usual scenario; and the optimistic scenario. The result showed that there was a reduction in CO2 concentration by about 50.3 ppm between March 2020 and January 2021 inclusive. From the models, the pessimistic, business-as- usual, and the optimistic scenarios gives CO2 concentration of about 545.9 ppm, 415.0 ppm, and 360.1 ppm respectively on December 31st 2021. Also, the CO2 concentration trend follows the business-as-usual scenario (BAU) path. This research helps paint the picture, to the policy makers, of the relationship between energy sources and CO2 emissions. This research recommends investment in solar energy by energy-intensive companies, equipment and machine maintenance, investment in electric vehicles, and doubling tree planting efforts to achieve the 10% cover. Keywords – economic recovery, forecasting, greenhouse gas, green energy, energy-intensive en_US
dc.description.sponsorship John Okanda Okwaro en_US
dc.language.iso en en_US
dc.publisher JKUAT-COETEC en_US
dc.subject Economic recovery en_US
dc.subject Forecasting en_US
dc.subject Greenhouse gas en_US
dc.subject Green energy en_US
dc.subject Energy-intensive en_US
dc.title Findings on Modelling Carbon Dioxide Concentration Scenarios in the Nairobi Metropolitan Region before and during COVID-19 en_US
dc.type Article en_US


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