Faced with a growing population, the Dutch government is promoting development plans to increase built density and accommodate the demand of new homes within existing urban areas. However, high-density developments are widely considered to exacerbate heat risks, causing health risks for vulnerable populations. Despite the known heat-related impacts on urban livability, effective methods are currently lacking at the municipal level for adopting heat-sensitive densification strategies while the high computational cost of existing simulation tools makes rapid assessment of multiple planning scenarios difficult. To address these challenges, the study addresses a densification case in Rotterdam and develops an AI-based methodology to quantify the thermal impact of increasing density within an existing urban area. The U-Net approach is used to estimate Tmrt and PET at a resolution of 1 m based on SOLWEIG-calculated data. This model reaches very high levels of precision (R2 ≈ 0.95). It also allows rapid assessment of different scenarios while maintaining high resolution.

Nine densification scenarios with different floor space index and morphological configurations were tested through the U-Net model, showing that it can generate high speed prediction with high accuracy. The modelling results show that the morphological characteristics of the new buildings and street canyons, and the distribution of building masses lead to different levels of diurnal and nocturnal increase of temperature and thermal stress. On wider streets, densification through horizontal development contributes to higher Tmrt and PET compared to vertical development, as high-rise buildings cast more shade especially during the day. Besides, vertical development also exhibits less heat retention and foster better ventilation than horizontal development. In narrow streets, horizontal development has better shading and ventilation performance compared to vertical development. Although horizontal development slightly increases heat retention, the effect is minimal and can be reduced by the guiding airflow movements.
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Only 1% of the surface water in the Netherlands has been classified as ‘good’, making it the EU member state with the worst quality of surface water (Didde, 2022). Polluted rivers cause problems such as worsened human health, reduced biodiversity, and poor soil fertility. To comply with the Water Framework Directive, there is an urgent need to transform water management in the Netherlands. This report adopts a research-by-design approach to address the issue of water pollution on a pilot project scale, specifically the river Eem in the Netherlands. The policies and interventions implemented in the river Eem area are categorised according to their transferability to different programming areas, namely urban, industry, or agriculture, creating a toolbox that can be used to upscale the same approach in various parts of the Eurodelta. The report answers the following research question: How can the transformation of the Eem Valley turn the river Eem into the healthiest river in Europe as a pilot for the Eurodelta? It catalyses rethinking pollution flows from human activities, industries, and agricultural practices. The goal is to develop sustainable practices for the land surrounding the river and create a synergy between improved soil and water quality. Finally, the report concludes with a toolbox of interventions and policies that contribute to improving river water quality. The toolbox forms the basis for implementing this small-scale approach on a larger scale ... Read more