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Urban heat island (UHI) is a zone that is significantly warmer than its surrounding rural zones as a result of human activities and rapid and dense urbanization. Excessive air temperature due to the UHI phenomenon affects the energy performance of buildings and human health and contributes to global warming. Knowing that most of the building energy is consumed by residential buildings, therefore, developing a framework to mitigate the impact of the UHI on residential building energy performance is vital. This study develops an integrated framework that combines hybrid micro-climate and building energy performance simulations and multi-criteria decision-making techniques. As a case study, an urban area is analyzed under the Urban GreenUP project funded by the European Union’s Horizon 2020 Programme. Four different strategies to mitigate the UHI effect, including the current situation, changing the low-albedo materials with high-albedo ones, nature-based solutions, and changing building façade materials, are investigated with a micro-climatic simulation tool. Then, the output of the strategies, which is potential air temperature, is used in a dynamic building energy simulation software to obtain energy consumption and thermal comfort data of the residential buildings in the case area. Finally, a multi-criteria decision-making model, using real-life criteria, such as total energy consumption, thermal comfort, capital cost, lifetime and installation flexibility, is used to make a decision for decreasing the UHI effect on residential energy performance of buildings. The results showed that applying NBSs, such as green roofs and changing existing trees with high leaf area density ones, have the highest ranking among all mitigation strategies. The output of this study may help urban planners, architects, and engineers in the decision-making processes during the design phase of urban planning.

Fifty-four percent of the world's population lives in big cities and it is projected to increase to nearly 70% by 2050s. Rapid and dense urbanization leads to smart cities which improve the quality of lives of the citizens. Therefore, development of smart cities is becoming vital. The quality of the citizens is affected by many factors including poor air quality, increased pollutants and microclimates called urban heat islands. The URBAN GreenUP project, initiated in June 2017, is a project funded under the European Union's Horizon 2020 programme. The main objective of the project is the development, application and replication of re-naturing Urban Plans in a number of European cities. In this study, measurement of nature-based solutions for mitigation of urban heat island effect and improvement of air quality for Urban GreenUP project in Izmir, will be introduced.

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Air pollution is a substantial menace, especially in industrialized urban zones, which affects the balance of the environment, life of vital organisms and human health. Besides the main causes of air pollution such as dense urbanization, poor quality fuels and vehicle emissions, physical environment characteristics play an important role on air quality. Therefore, it is vital to understand the relationship between the characteristics of the natural environment and air quality. This study examines the correlations between the PM10 pollutant data and meteorological parameters such as temperature (Tair), relative humidity (RH), and wind speed (WS) and direction (WD) under the European Union’s Horizon 2020 project. Two different zones (Vilayetler Evi as an urban zone and Sasalı Natural Life Park as a rural zone) of Izmir Province in Türkiye are used as a case study and the PM10 data is evaluated between 1 January 2017 and 31 December 2021. A one-tailed t-test is used in order to statistically determine the relationships between the PM10 pollutant data and meteorological parameters. As a further study, practical significance of the parameters is investigated via the effect size method and the results show that the RH is found to be the most influencing parameter on the PM10 for both zones, while Tair is found to be statistically non-significant.