Influence of urban resilience measures in the magnitude and behaviour of energy fluxes in the city of Porto (Portugal) under a climate change scenario

Are green roofs the path to clean air and low carbon cities?

Green roofs, as part of urban green structures, have been pointed out as the solution to pursuit the goal of healthy cities. This study aims to investigate the direct, focused on meteorological changes, and indirect, related to both meteorological and emissions changes, impacts of green roofs on air quality (PM10, NO₂ and O₃). For that, the numerical modelling system composed by the WRF-SLUCM-CHIMERE models was applied to a 1-year period (2017), having as case study the Porto urban area. The EnergyPlus model was also applied to estimate the green roofs impacts on the building's energy needs and related impacts on air quality and atmospheric emissions. The analysis of the direct impacts showed that green roofs promote a temperature increase during the autumn and winter seasons and a temperature decrease during the spring and summer seasons. Both negative - concentrations increase - and positive - concentrations decrease - impacts were obtained for the primary, PM10 and NO₂, and secondary, O₃, air pollutants, respectively, due to changes in the dynamical structure of the urban boundary layer. The indirect effects of green roofs showed their potential to enhance the buildings energy efficiency, reducing the cooling and heating needs. These changes in energy consumption promoted an overall decrease of the environmental and economic indicators. Regarding air quality, the impact was negligible. The obtained results highlight the need for a multipurpose evaluation of the impacts of green roofs, with the different effects having to be traded off against each other to better support the decision-making process.

Spatial–Temporal Evolution of Urban Resilience and Its Influencing Factors: Evidence from the Guanzhong Plain Urban Agglomeration

Rapid urbanization places great pressure on the ecological environment and the carrying capacity of cities. Improving urban resilience has become an inherent requirement for the sustainable development of modern cities and urban agglomerations. This study constructed a comprehensive system to evaluate urban resilience from four perspectives: The ecological environment, economic level, social environment, and infrastructure services. As a case study, the extreme entropy method and panel data from about 16 cities from 2009 to 2016 were used to calculate resilience levels in the Guanzhong plain urban agglomeration (GPUA) in China. The spatial and temporal evolution of urban resilience characteristics in the GPUA were analyzed using ArcGIS. The influencing factors were further explored using a grey correlation analysis. The results showed that the urban resilience of GPUA experienced geographical differentiation in the “East-Central-Western” area and a “circle type” evolution process. Most urban resilience levels were low. The resilience of the infrastructure and the ecological environment significantly impacted the city and became its development weaknesses. Economic considerations have become one of the main factors influencing fluctuations in urban resilience. In summary, this study explored the differences in resilience in the GPUA and provided a reference for improving the urban resilience of other cities located in underdeveloped regions. The study also provided a useful theoretical basis for sustainable urban development.

Quantification and mapping of urban fluxes under climate change: Application of WRF-SUEWS model to Greater Porto area (Portugal)

Climate change and the growth of urban populations are two of the main challenges facing Europe today. These issues are linked as climate change results in serious challenges for cities. Recent attention has focused on how urban surface-atmosphere exchanges of heat and water will be affected by climate change and the implications for urban planning and sustainability. In this study energy fluxes for Greater Porto area, Portugal, were estimated and the influence of the projected climate change evaluated. To accomplish this, the Weather Research and Forecasting Model (WRF) and the Surface Urban Energy and Water Balance Scheme (SUEWS) were applied for two climatological scenarios: a present (or reference, 1986-2005) scenario and a future scenario (2046-2065), in this case the Representative Concentration Pathway RCP8.5, which reflects the worst set of expectations (with the most onerous impacts). The results show that for the future climate conditions, the incoming shortwave radiation will increase by around 10%, the sensible heat flux around 40% and the net storage heat flux around 35%. In contrast, the latent heat flux will decrease about 20%. The changes in the magnitude of the different fluxes result in an increase of the net all-wave radiation by 15%. The implications of the changes of the energy balance on the meteorological variables are discussed, particularly in terms of temperature and precipitation.