Analysis of drivers to increasing travel demand and emissions pre- and post-pandemic using ARDL and spatial LMDI

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ID: 286910
2021
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Abstract
The Republic of the Philippines is an archipelagic country, accommodating 108.12 million people. With increasing population, there is a growing demand for transport leading to huge congestion in several regions of the country. These are as a result of poor transportation framework and infrastructural planning in the country. As transport becomes essential in our daily lives, there is a need to address several driving factors leading to the huge traffic flow with a rise in transport emissions. For decades, human activities and energy consumption have been linked to climate change, which has caused many worries. The transportation sector, in particular, contributes significantly to global emissions. This is owing to a growing reliance on private vehicles and a shoddy transportation system. This has substantial environmental and sustainability consequences in addition to economic effects. Transitioning from a product-based to a service-based approach, i.e., lowering private vehicle ownership and use, is one way to use circular economy ideas in transportation. This is evident in recent innovations in numerous countries, ranging from ridesharing, bike-sharing, and car-sharing programs. However, studies show that as income levels improve, private vehicle ownership will continue to outpace public transportation use in emerging countries over the next decade. Recent vehicle ownership statistics in the Philippines support this. Using an exemplary case study in the Philippines, this work provides an approach for analyzing drivers of energy use, traffic flow, and CO2 emissions in regions using spatial Logarithmic Mean Divisia Index (LMDI). Regional disparities in traffic flow are evaluated using plausible explanatory factors such as population, economic activity, travel intensity, and mode structure. Similar patterns emerge for drivers in terms of traffic flow and transportation emissions, yielding some intriguing results. In terms of the impact, the findings demonstrated that increased economic activity generally reduces traffic intensity and switching to cleaner energy is not a guarantee of lower carbon emissions. As the pandemic came into place, the study carried out an extensive review on how to address the spread of the virus in public transport, address supply and demand issues and lastly improve contact tracing in the country. In addition, as the pandemic skewed up recent findings with huge reduction of carbon emission in the country, the researcher further extended the study to cover the energy reduction during this event using LMDI analysis pre- and post-pandemic and the drivers were also revealed. Furthermore, Autoregressive Distributive Lag (ARDL) and Cointegration Analysis addressed the relationship
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Authors Nnadiri, Geoffrey Udoka
Journal Malay Journal
Year 2021
DOI
DOI not found
URL
https://animorepository.dlsu.edu.ph/etdd_mecheng/1
Keywords Keywords not found

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