The Development of a CO2 Emission Coefficient for Medium- and Heavy-Duty Vehicles with Different Road Slope Conditions Using Multiple Linear Regression, and Considering the Health Effects

Greenhouse gas emissions trends and drivers insights from the domestic aviation in Thailand

Domestic aviation is a swiftly expanding contributor to global greenhouse gas (GHG) emissions. Presently, economic volatility and the Coronavirus disease (COVID-19) crisis have resulted in the decline of domestic aviation, but domestic aviation is rapidly recovering in many countries. However, from a GHG emissions viewpoint, the domestic aviation sector is largely unenforced even though the International Civil Aviation Organization's (ICAO) Carbon Offsetting and Reduction Scheme for International Aviation (CORSIA) provision for international aviation is currently in place. Accordingly, the knowledge base on emissions and their drivers from domestic aviation is weak, especially in developing countries, thus hindering an evidence-based policy debate. In this context, we have estimated and analyzed the pre-COVID-19 GHG emissions and their trends from commercial domestic aviation in Thailand; and provided insights on the role of key drivers that influence GHG emissions that are expected to be useful not only for Thailand but also for other developing countries. Emissions are estimated following Intergovernmental Panel on Climate Change (IPCC) Tier-II. Specifically, activity-based landing/take-off (LTO) cycle and cruise. This is compared to the Tier-I method, and key drivers were analyzed using an index decomposition method. The total annual average GHG emissions for all LTO cycles and cruises of commercial domestic aviation for 2015-2020 was 2254 Th. tonnes of CO2-eq. During the LTO cycle of the aircraft, GHG emissions were at an average of 983 Th. tonnes of CO2-eq. Additionally, during the cruise stage, emissions averaged 1270 Th. tonnes of CO2-eq. The choice of accounting methods (i.e., IPCC Tier II vs. Tier I) seems to have had only nominal implications. Our analysis showed that, in the 2008-2020 period, the aviation activity effect and economic growth were the key decisive factors in this sector's GHG emissions growth. It was followed by the fuel energy intensity levels and the population effect in descending order of impact. These findings have significant ramifications for present and future policies aimed at decreasing GHG emissions, aiding Thailand in achieving its climate targets by 2050, and enhancing energy efficiency as the domestic aviation market adapts.

The Dynamic Evaluation Model of Health Sustainability under MCDM Benchmarking Health Indicator Standards

The coronavirus pandemic causing millions of deaths around the world has raised awareness of the importance of healthcare in a city, especially its efficiency in the city's system. Although the health dimension is found to have critical effects on sustainable development in addition to the existing three dimensions, the majority of sustainability assessments that are developed based on the UN's Sustainable Development Goals (SDGs) do not define standards for each indicator. On the contrary, an effective assessment model should be dynamic and suitable to the context of each city by referring to standardized criteria, such as those in a health indicator standard (HIS), instead of comparing with other cities. Hence, this research presents a new sustainability assessment model that integrates the health dimension (HEDm) with the other three dimensions generally used in studies of sustainable development (STD) and develops an assessment method to evaluate real data with references to the HIS from reliable organizations, such as the World Health Organization (WHO) and the United Nations (UN), for the SDGs. By using the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) with the framework obtained from literature reviews, ISO Standards (ISO37120, ISO37122, ISO37123) and U4SSC, the researchers formed indicators in four dimensions with a total of 15 elements and 45 indicators. Afterwards, the weight of each indicator was determined with the Analytic Hierarchy Process (AHP) conducted in each dimension and element, resulting in a four-dimensional sustainability assessment model based on HIS value that limits the need to compare with other cities. The results from Khon Kaen province have shown the weaknesses and strengths of the target city that policymakers can reference to formulate a policy and strategy to improve HIS values in each dimension to meet standards, elevate city capacity and raise quality of life for the people living in the area.