Agent-based simulation for renewable energy incentive design

In this thesis, we propose a novel approach to model the diffusion of residential PV systems. For this purpose, we use an agent-based model where agents are the families living in the area of interest. The case study is the Emilia-Romagna Regional Energy plan, which aims to increase the produc- tion of electricity from renewable energy. So, we study the microdata from the Survey on Household Income and Wealth (SHIW) provided by Bank of Italy in order to obtain the characteristics of families living in Emilia-Romagna. These data have allowed us to artificial generate families and reproduce the socio-economic aspects of the region. The families generated by means of a software are placed on the virtual world by associating them with the buildings. These buildings are acquired by analysing the vector data of regional buildings made available by the region. Each year, the model determines the level of diffusion by simulating the installed capacity. The adoption behaviour is influenced by social interactions, household’s economic situation, the environmental benefits arising from the adoption and the payback period of the investment.

Assessing the Environmental Performance of New Mobility

This report has two main goals. First to improve methodologies of new mobility services .Second identify the solution to improve new mobility in urban transportation to decrease energy loss and decline climate change. This report also compares energy use and greenhouse gasses (GHG) emission impact for new mobility and all transportation modes. Having focus on central estimates and a range of possible alternatives to enhance the result to advance environmental effects. This analysis and research help to identify the possible solutions to make new mobility more sustainable

Light coloured and draining wearing courses for low-impact urban pavements

Urban health and well-being are becoming current issues of modern cities due to local climate change and environmental noise. The Urban Heat Island and the Urban Noise Island have a direct impact on the economic, social, and environmental aspects of urban life, negatively affecting the well-being of worldwide citizens. The present research is focused on the study of innovative materials employed in the production of wearing course mixtures aiming to mitigate these phenomena. In particular, a synthetic transparent binder substituting bitumen and recycled aggregates produced from construction and demolition waste. Four mixtures were analysed. Among them, Mix 1 and Mix 2 are conventional wearing courses. The first is exclusively made of natural aggregates, while the second is constituted of 45 % of recycled aggregates (RA). Mix 3 and Mix 4 are draining wearing courses and, in this case, Mix 4 was produced by using 55 % of RA. Laboratory tests were required to fully characterize all the produced samples, allowing a proper comparison of results. Overall, all the mixtures studied provide prominent results suggesting potential applications of these innovative wearing courses in cycle lanes, historical centres, plazas, and parking lots. Among the conventional mixtures, Mix 2 is the most likely to assure the best performance in terms of road safety, efficiency, and durability while as far as the draining mixtures are concerned, Mix 4 is preferable due to its high content of recycled aggregates.

Correlation between urban form and PM2.5 concentration — Evidence from the New York metropolitan Area and Shanghai city

With the development of the economy and society, air pollution has posed a huge threat to public health around the world, especially to people who live in urban areas. Typically, urban development patterns can be roughly divided into compact cities and urban sprawl. In recent years, the relationship between urban form and air quality (especially PM2.5) is gaining more and more attention from urban planners, environmentalists, and governments. This study is focusing on The New York metropolitan area and Shanghai city, which are both megacities but with different urban spatial forms. For both study areas,there are five main variables to measure the urban form metrics, naming Population Density, Artificial Land Area Per Ten Thousand People, Road Density, Green Land Area Ratio and Artificial Land Area Ratio. In addition, considering the impact of economic activities and public transportation, GDP per capita, Number of bus stop and Number of subway station are used as control variables. Based on the results of regression, a megacity like the New York metropolitan area with urban sprawl shows a low spatial correlation on PM2.5 concentration. Meanwhile, almost all the spatial form indicators effect on PM2.5 concentration is not significant. However, a compact megacity like Shanghai shows a diametrically opposite result. Urban form, especially population density, has a strong relationship with PM2.5 concentration. It can be predicted that a reduction in population density would lead to significant improvements on decrease the PM2.5 concentration in Shanghai. Meanwhile, increasing the ratio of green land and construction area per capita will get a positive influence on reducing PM2.5 concentration as well. Road density is not a significant factor for a megacity in both two urban forms. The way and type of energy used by vehicles on megacities maybe more critical.