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Purpose: Multiutility tunnel (MUT) has been recognised as a more sustainable method to place underground utilities than the traditional directly buried (DB) method. However, the implementation of MUT is hindered because of high initial construction costs and the difficulty to demonstrate its benefits, especially social benefits that are hard to be quantified. To address the limitation, this paper aims to quantify and compare both economic costs and traveller loss (i.e. an important part of social costs) of the MUT and DB method. Design/methodology/approach: An agent-based model (ABM) is developed, which considers attributes and actions of vehicles, interactions between vehicles and interactions between vehicles and the road network. The ABM is used to estimate traveller loss by comparing traveller time when the MUT and DB method is adopted, respectively. The traveller loss is combined with economic costs to estimate and compare the LCC of the MUT and DB method. To verify the ABM-based approach, it is implemented in an MUT project in Shanghai, China. Findings: Results of the study indicate: (1) When the DB method is adopted, periodic E&Rs cause severe traffic congestion and substantial traveller loss. (2) When traveller loss is not included in the LCC estimation, the DB method has a lower LCC in most scenarios. (3) When traveller loss is included, the relative LCC of MUT and the time it takes to cover the LCC of the MUT and DB method is largely reduced. Thus, when social costs are considered, MUT will bring more benefits than the DB method. Originality/value: Previous studies on comparing the MUT and DB method focus on investigating economic costs, while other costs, e.g. social costs, are not well addressed quantitatively. Besides, current studies of traveller loss estimation lack consideration of factors such as unique attributes, actions and interactions of vehicles and the network. Hence, this paper applies an ABM-based approach to involve these factors and produce more reliable estimation of traveller loss than existing approaches. Moreover, by integrating traveller loss into LCC analysis, this paper helps to understand the benefits of MUT thus assisting decision-making in selecting utilities placement methods. [ABSTRACT FROM AUTHOR]

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This article presents a flood risk assessment for Shanghai, which provides an indication of what buildings (including residential, commercial, office, and industrial) will be exposed to flooding and its damage. Specifically, this assessment provides a risk assessment that buildings may face after construction. To achieve the flood risk assessment on buildings, we developed an integrated flood model and collected data on building shape and number of floors, land use, and construction costs for different building types in Shanghai. The extreme compound flood scenarios (1/200 -, 1/500 -, 1/1000 -, and 1/5000 -year floods) and building metadata were aggregated using a risk analysis chain. According to the damage for different flood scenarios, the average annual loss (AAL) can be calculated and is referred to as building flood risk. The AAL of residential, commercial, office, and industrial buildings is USD 12.3, 2.5, 3.7, and 3.4 million, respectively. Among the 15 (non-island) districts in Shanghai, Pudong has the highest AAL. The risk analysis chain developed in this study can be reproduced for other megacities. The results provide a clear picture for future building flood risks which links directly to disaster risk management, which implies the extent of flood risk in building types, sub-districts, and districts related to the Shanghai Master Plan. This assessment takes into consideration future climate change scenarios, information for scenario-based decision making, and a cost–benefit analysis for extreme flood risk management in Shanghai. We also discussed different potential adaptation options for flood risk management. [ABSTRACT FROM AUTHOR]

Nowadays, it is noticed that more than a third of the carbon dioxide (CO2) emitted in the atmosphere comes from the construction sector. This CO2 concentration has a significant effect on climate change. In the new cities, tall buildings multiply as mushrooms. Some specialists believe that they can be one of the solutions to reduce the carbon content in the atmosphere. The main aim of this study is to simulate, analyze and compare the embodied carbon and operational carbon of the two tallest buildings located in the United States and China, by using Design Builder and Pleiades software: the One World Trade Center in USA and the Shanghai Tower in China. Even if the embodied carbon of these super tall buildings is very high, the operational carbon remains the most important source of carbon emissions on their whole life cycle. Future carbon emissions of these two buildings were estimated in three periods (2030, 2050 and 2080) following the A2 scenario from the Intergovernmental Panel on Climate Change (IPCC). The results show that the operational carbon will increase by 10.6% at One World Trade Center (1WTC, USA) and 7.8% at Shanghai Tower (ST, China) in 2050. In addition, this study analyzed the impacts of the electricity mix and photovoltaic panels on their carbon dioxide emissions. Replacing energy production based on coal by renewable energy sources in the electricity mix of these countries could induce a reduction of 47.5% and 65.6% of total operational carbon emitted by the 1WTC and ST, respectively, by 2050. Finally, 46% of the building construction cost of these skyscrapers is related to their structure and superstructure. [ABSTRACT FROM AUTHOR]

This paper proposes a new prediction method incorporating a set of measuring models applicable to the financing efficiency of China's carbon market to quantify such market's maturity, trading risk coefficient, and financing income. Our theoretical analysis indicates that the price of carbon emission quota essentially affects the financing efficiency of carbon market. While a robust safeguard measure to obtain a respectable income from carbon market financing is the long-term average quota price exceeding the initial quota price. Empirical findings derived from China's emissions trading scheme pilots reveal that these pilots can be divided into the growth-oriented market (i.e. Guangdong whose financing capacity is always significant), the balance-oriented market (i.e. Shanghai and Hubei whose quota pricing mechanisms and the financing level of carbon markets both maturely develop), and the risk-oriented market (i.e. Beijing whose quota price runs at a high-level with an intense financing income volatility). It is therefore achieved that carbon market's maturity level and quota price volatility are both robustly explicable for different financing effects among these pilots. Our key findings show that expanding the coverage of quota trading parties, stabilizing carbon price, and promoting carbon asset management help to improve the financing efficiency of carbon market. • The financing mechanism is analyzed with clarifying its main influence factors. • A stochastic process is used to build a price simulation equation that meets the operation law of China's carbon market. • An income model is built and thus evaluate market financing effect based on price expression and financing mechanism. • The financing effect of China's 8 pilot markets is measured, and thus 3 kinds of development modes are proposed. [ABSTRACT FROM AUTHOR]