Energy-Saving Methods for Urban Travel and Public Transportation in Smart Cities

In many countries, energy-saving and emissions mitigation for urban travel and public transportation are important for smart city developments. It is essential to understand the impact of smart transportation (ST) in public transportation in the context of energy savings in smart cities. The general strategy and significant ideas in developing ST for smart cities, focusing on deep learning technologies, simulation experiments, and simultaneous formulation, are in progress. This study hence presents simultaneous transportation monitoring and management frameworks (STMF ). STMF has the potential to be extended to the next generation of smart transportation infrastructure. The proposed framework consists of community signal and community traffic, ST platforms and applications, agent-based traffic control, and transportation expertise augmentation. Experimental outcomes exhibit better quality metrics of the proposed STMF technique in energy saving and emissions mitigation for urban travel and public transportation than other conventional approaches. The deployed system improves the accuracy, consistency, and F-1 measure by 27.50%, 28.81%, and 31.12%. It minimizes the error rate by 75.35%.

ASSESSMENT OF ROAD LIGHTING PERFORMANCE FOR TRAFFIC INTENSITY AND TRAFFIC DETECTION BASED LIGHTING ADAPTATION

Amongst many road lighting design criteria, energy performance plays an important role as it has a direct link to operational costs, potential reduction of carbon dioxide emissions, mitigation of obtrusive light, and its impact on the night-time environment in urban and con-urban settlements. The energy energy performance of road lighting is conveniently described by the pair of normative numerical indicators PDI and AECI established in European standards. This paper aims to present typical values of the AECI (Annual Energy Consumption Indicator) for different combinations of road arrangements, road widths, lighting classes and light source technologies to illustrate what benchmarks can be expected using this assessment system. Essential part of this paper is focusing on assessment of the performance for traffic intensity and traffic detection based lighting adaptation.

Breaking down barriers on PV trade will facilitate global carbon mitigation

The global trade of solar photovoltaic (PV) products substantially contributes to increases in solar power generation and carbon emissions reductions. This paper depicts global PV product trade patterns, explores emissions reduction potential, and evaluates the impeding effect of tariff barriers on global PV product trade and emissions reductions. Solar power generation will result in a reduction of emissions in a range of 50–180 gigatons of carbon dioxide equivalent (GtCO2e) between 2017 and 2060 in a business as usual (BAU) scenario. Compared with BAU, during 2017–2060, global total solar cell and module production and installation will increase by roughly 750 gigawatts (GW) if half of the status quo trade barrier are removed, while it will decrease by 160–370 GW under tensioned trade barrier scenarios. Trade barrier reduction by half from the 2017 status quo level will increase the net carbon emissions mitigation potential by 4–12 GtCO2e by 2060, while extra trade barrier imposition will result in global net carbon emissions mitigation potential decreasing by up to 3–4 GtCO2e by 2060. Well-coordinated policy and institutional reforms are recommended to facilitate PV product trade and to deliver the related global environmental benefits.