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This study investigates the association between remittances, FDI, energy use, and CO₂ emissions for a sample of the top six Asian nations receiving remittances, namely, China, India, the Philippines, Pakistan, Bangladesh, and Sri Lanka, during the 1982–2014 period. The results of employing an autoregressive distributed lag (ARDL)-bound technique signify that there is a stable long-run association among the stated variables. The empirical findings indicate that CO₂ increases significantly with a rise in energy use in all sample nations in both the long and short-runs. Conversely, the association between CO₂ emissions and remittances is found to be significantly positive for Sri Lanka, Pakistan, the Philippines, and Bangladesh in the long-run, positive for Pakistan, the Philippines, and Sri Lanka only in the short-term, and non-significant for India and China in both the long and short-runs. Furthermore, the empirical results illustrate that the inflow of FDI significantly increases CO₂ emissions in the cases of China, Sri Lanka, and India in both the long and short-runs. While FDI inflow has no significant effect on CO₂ emissions for the Philippines and Pakistan, it has a significant negative effect for Bangladesh in both the long and short-runs. Thus, the connection between remittances, FDI, and CO₂ emissions varies significantly across the countries considered in our study.

Energy use and greenhouse gas (GHG) emissions associated with life cycle stages of road infrastructure are currently rarely assessed during road infrastructure planning. This study examines the road infrastructure planning process, with emphasis on its use of Environmental Assessments (EA), and identifies when and how Life Cycle Assessment (LCA) can be integrated in the early planning stages for supporting decisions such as choice of road corridor. Road infrastructure planning processes are compared for four European countries (Sweden, Norway, Denmark, and the Netherlands).

The results show that only Norway has a formalised way of using LCA during choice of road corridor. Only the Netherlands has a requirement for using LCA in the later procurement stage. It is concluded that during the early stages of planning, LCA could be integrated as part of an EA, as a separate process or as part of a Cost-Benefit Analysis.

A city’s economic structure and energy mix would change when the city is developed to accommodate more residents, visitors, and activities. This paper reviews Macao’s economic growth, energy use, and greenhouse gases (GHG) emission from 1985 to 2020. Specifically, Macao’s gross domestic product (GDP), energy use, and GHG emission have surged after the gaming industry was liberalized in 2002. The official data show that Macao’s GDP was MOP 11 billion in 1985, increased by four-fold to MOP 54 billion in 2000, and then surged rapidly to MOP 445 billion in 2019. Additionally, Macao’s total energy use increased from 8,840TJ in 1985 to 48,330TJ in 2019 while Macao’s GHG emission increased from 0.70Mt of CO₂-equivalent in 1985 to 6.13Mt of CO₂-equivalent in 2019. Macao’s GHG emission from all local sources per capita and GDP per capita exhibit an inverted U-shaped relationship, showing an environmental Kuznets curve. Due to the negative impact of COVID-19 pandemic, Macao’s GDP dropped by 56% to MOP 194 billion while its total energy use and GHG emission dropped by 33% and 17% to 32,198TJ and 5.06Mt of CO₂-equivalent, respectively, in 2020.

One of the main aspects that has to be carefully accounted and controlled in sustainable buildings is energy use, which is directly related to greenhouse-gas (GHG) emissions. During a building life cycle, the operation is the most energy intensive stage due to the presence of technical systems, equipment, occupants, etc. In green buildings (GB), design teams predict the expected energy performance of a building at the design stage, by means of a building energy simulation model, and study the most sustainable solutions in order to minimize the use of energy before the construction process occurs, so as to reduce the impacts that the operation stage will have in the environment. Meanwhile, researchers by comparing real energy performance results with the predicted ones have identified significant differences between them. These differences can be related to low maintenance, inefficiencies and occupants. Nevertheless, the way occupants behave in terms of energy use is the most impacting factor to the performance of a building (Norford et al., 1994). Therefore, this chapter presents the influence occupants have in the energy use of a building using a simulation model that analyzes occupant interaction with different building systems, having as baseline the Australian National Construction Building Code (ABCB, 2016) requirements for office buildings. The model has been developed using the simulation tools DesignBuilder and EnergyPlus in order to determine the annual energy performance of a typical Australian office building in Sydney and consequent GHG emissions. By varying certain parameters it is possible to estimate the impact occupants will have in the energy use of a building as a whole and which system will be most affected by their action.