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

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 infrastructura...

Full description

Saved in:
Bibliographic Details
Main Author: Nnadiri, Geoffrey Udoka
Format: text
Language:English
Published: Animo Repository 2021
Subjects:
Online Access:https://animorepository.dlsu.edu.ph/etdd_mecheng/1
https://animorepository.dlsu.edu.ph/cgi/viewcontent.cgi?article=1001&context=etdd_mecheng
Tags: Add Tag
No Tags, Be the first to tag this record!
Institution: De La Salle University
Language: English
id oai:animorepository.dlsu.edu.ph:etdd_mecheng-1001
record_format eprints
institution De La Salle University
building De La Salle University Library
continent Asia
country Philippines
Philippines
content_provider De La Salle University Library
collection DLSU Institutional Repository
language English
topic Automobiles—Philippines--Fuel consumption
Traffic congestion--Philippines
Atmospheric carbon dioxide--Philippines
Transportation--Philippines
Energy Systems
Mechanical Engineering
spellingShingle Automobiles—Philippines--Fuel consumption
Traffic congestion--Philippines
Atmospheric carbon dioxide--Philippines
Transportation--Philippines
Energy Systems
Mechanical Engineering
Nnadiri, Geoffrey Udoka
Analysis of drivers to increasing travel demand and emissions pre- and post-pandemic using ARDL and spatial LMDI
description 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 between population, gross domestic product (GDP) and carbon emission, revealing there exists long term relationship between emissions of previous year and if these are not addressed, emissions will start to rebound until it catches up with us 4 years later. GDP on the other hand showed slight significance on the current year’s carbon emission but not in a long run. The novelty of this study is the introduction of an ARDL-modified Spatial LMDI to ensure that correlated previous-year data are also considered. The researcher provided a way forward towards the end of the study, which include the need to develop a roadmap to reduce the overall transport demand, equity on the appropriation of transport infrastructure projects, quality improvement of public transport services, promoting mixed-use development, and providing fiscal and non-fiscal incentive to companies adapting to telecommuting. This study further supports the Sustainable Development Goals (SDGs) of industry, innovation and infrastructure (SDG 9), sustainable cities and commodities (SDG 11), and climate action (SDG 13). Keywords: Spatial LMDI; LMDI; Traffic flow; Emissions; ARDL; COVID-19; Transport; ARDL-modified Spatial LMDI; Philippines
format text
author Nnadiri, Geoffrey Udoka
author_facet Nnadiri, Geoffrey Udoka
author_sort Nnadiri, Geoffrey Udoka
title Analysis of drivers to increasing travel demand and emissions pre- and post-pandemic using ARDL and spatial LMDI
title_short Analysis of drivers to increasing travel demand and emissions pre- and post-pandemic using ARDL and spatial LMDI
title_full Analysis of drivers to increasing travel demand and emissions pre- and post-pandemic using ARDL and spatial LMDI
title_fullStr Analysis of drivers to increasing travel demand and emissions pre- and post-pandemic using ARDL and spatial LMDI
title_full_unstemmed Analysis of drivers to increasing travel demand and emissions pre- and post-pandemic using ARDL and spatial LMDI
title_sort analysis of drivers to increasing travel demand and emissions pre- and post-pandemic using ardl and spatial lmdi
publisher Animo Repository
publishDate 2021
url https://animorepository.dlsu.edu.ph/etdd_mecheng/1
https://animorepository.dlsu.edu.ph/cgi/viewcontent.cgi?article=1001&context=etdd_mecheng
_version_ 1712576775202013184
spelling oai:animorepository.dlsu.edu.ph:etdd_mecheng-10012021-09-17T00:40:23Z Analysis of drivers to increasing travel demand and emissions pre- and post-pandemic using ARDL and spatial LMDI Nnadiri, Geoffrey Udoka 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 between population, gross domestic product (GDP) and carbon emission, revealing there exists long term relationship between emissions of previous year and if these are not addressed, emissions will start to rebound until it catches up with us 4 years later. GDP on the other hand showed slight significance on the current year’s carbon emission but not in a long run. The novelty of this study is the introduction of an ARDL-modified Spatial LMDI to ensure that correlated previous-year data are also considered. The researcher provided a way forward towards the end of the study, which include the need to develop a roadmap to reduce the overall transport demand, equity on the appropriation of transport infrastructure projects, quality improvement of public transport services, promoting mixed-use development, and providing fiscal and non-fiscal incentive to companies adapting to telecommuting. This study further supports the Sustainable Development Goals (SDGs) of industry, innovation and infrastructure (SDG 9), sustainable cities and commodities (SDG 11), and climate action (SDG 13). Keywords: Spatial LMDI; LMDI; Traffic flow; Emissions; ARDL; COVID-19; Transport; ARDL-modified Spatial LMDI; Philippines 2021-09-03T07:00:00Z text application/pdf https://animorepository.dlsu.edu.ph/etdd_mecheng/1 https://animorepository.dlsu.edu.ph/cgi/viewcontent.cgi?article=1001&context=etdd_mecheng Mechanical Engineering Dissertations English Animo Repository Automobiles—Philippines--Fuel consumption Traffic congestion--Philippines Atmospheric carbon dioxide--Philippines Transportation--Philippines Energy Systems Mechanical Engineering