Ecoindicators for the Future City: Assessing Sustainable Urban Planning Strategies
摘要
The growth of urban populations brings challenges such as urban expansion, resulting in dispersed or compact morphologies, each with benefits and issues. Urban areas, due to their morphology, are vulnerable to climate change, meaning that changing this aspect can potentially enhance resiliency and sustainability. Many parameters are affected by changing urban morphology, so a holistic approach is needed to evaluate those impacts. This study aims to develop an ecoindicator that assesses the sustainability of an urban area with a single value. Through the use of modelling tools, it integrates travel generation, road traffic emissions, meteorological, and air quality, to generate the parameters contributing to the ecoindicator’s overall assessment. A normalization process based on literature and policy benchmarks was adopted, to aggregate multiple parameters. The ecoindicator was applied to the region of Aveiro, Portugal, for two compact scenarios, and a disperse scenario. Results indicate that the compact scenarios, specifically the Independent City scenario, present the most sustainable option for future development, and the Disperse City scenario performs the worst. This underscores the importance of considering multiple parameters in urban air quality studies and prioritizing mobility policies. Findings support compact cities as a more sustainable, resilient alternative with better air quality.
Graphical AbstractThe graphical abstract illustrates an integrated framework for assessing the sustainability performance of urban morphology scenarios through the development and application of an ecoindicator-based modelling system. The process begins with a Baseline scenario, which is compared against Compact and Disperse urban configurations to evaluate alternative urban morphologies. These scenarios feed into a Modelling System that couples multiple simulation components, including a Traffic Generation Model (PTV-VISUM), Traffic Emissions Model (TREM), Meteorological Model (WRF), and Air Quality Model (CAMx). The outputs from this system provide key environmental and socio-economic variables required for Ecoindicator Development, encompassing five thematic dimensions: Temperature (urban heat island intensity, maximum daily temperature), Air Quality (NO2, PM10 concentrations), Health (population-weighted PM2.5 exposure, diurnal temperature range), Energy (Bowen ratio, CO2 emissions), and Mobility (passenger and freight transport). These indicators are subsequently integrated through Ecoindicator Calculation to yield a composite Sustainability Score normalized on a 0–1 scale, enabling direct comparison across scenarios. This framework provides a holistic, quantitative approach to assess urban form impacts on environmental quality, public health, and energy efficiency, supporting evidence-based decision-making for sustainable urban planning and policy development.