**5. Conclusions**

In this study, we investigated the effect of additional housing in constructed zones on heat stress, worked out using different urban planning strategies for the current and future climates for the city of The Hague (the Netherlands). The heat stress is expressed based on the frequency of tropical nights, where minimum temperatures are above 20 ◦C, and on the 95th percentile of the maximum daily urban heat island, UHImax. The proposed additional housing was added near the city center and in a residential area in The Hague. The urban planning strategies were applied in delineated urban neighborhoods and differed in replacing low- and mid-rise buildings with high-rise buildings, or constructing buildings on vegetated areas. The temperature projection was computed using a validated diagnostic equation which combined weather data and urban morphological characteristics. The vegetation fraction appeared to be a more critical parameter than the sky-view factor, which was reduced by the tall buildings for the vast majority of urban configurations. This means that the combination of mid-rise and high-rise buildings with a preservation of vegetated areas was the best strategy. There is, however, an empirically determined optimum between vegetation fraction and sky-view factor. The most favorable green strategy mitigated the heat stress by 42% and 20% for the two urban districts tested.

In general, climate change will cause a larger increase in heat stress than the extra heat stress caused by the imposed urbanization. Only the largest imposed building assignments could compete with the colder climate scenarios. The most urbanized area of the city has on average 4.5 tropical nights per year. For this area, we found a range of 6.5–16 tropical nights per year for the coldest and warmest climate scenarios. For the warmest summer in the data series (year 2006), the number of tropical nights would increase from 14 in the current climate to 32 in the warmest climate scenario. The results were verified with a selection of high-quality citizen weather stations. The model results were in good agreement with observations and showed only a slight cold bias. The prescribed method based on a diagnostic equation is a fast and efficient way of determining climatologies in minimum temperatures, and it is directly applicable for other cities across northwestern Europe.

**Supplementary Materials:** The following are available online at http://www.mdpi.com/2073-4433/9/9/353/s1, Figure S1: Modelled number of tropical nights per year for the year 2006, Figure S2: Modelled number of tropical nights per year for year 2006 transformed to the four KNMI'14 scenarios, Figure S3: Modelled average number of nights per year above 20 ◦C for The Hague Southwest for the current climate, Figure S4: Modelled average number of nights per year above 20 ◦C for The Hague Southwest for the GL climate scenario, Figure S5: Modelled average number of nights per year above 20 ◦C for The Hague Southwest for the GH climate scenario, Figure S6: Modelled average number of nights per year above 20 ◦C for The Hague Southwest for the WL climate scenario, Figure S7: Modelled number of nights above 20 ◦C per year for the CID for the GL climate scenario, Figure S8: Modelled number of nights above 20 ◦C per year for the CID for the GH climate scenario, Figure S9: Modelled number of nights above 20 ◦C per year for the CID for the WH climate scenario, Table S1: Transformation table GL climate scenario from current climate to future climate in 2050, Table S2: Transformation table GH climate scenario from current climate to future climate in 2050, Table S3: Transformation table WL climate scenario from current climate to future climate in 2050, Table S4: Transformation table WH-scenario from current climate to future climate in 2050.

**Author Contributions:** Data curation, S.K.; Formal analysis, S.K.; Funding acquisition, R.R., G.-J.S. and A.M.G. K.T.; Investigation, S.K. and R.R.; Methodology, S.K., R.R. and A.M.G.K.T.; Project administration, G.-J.S.; Software, S.K.; Supervision, G.-J.S.; Validation, S.K.; Visualization, S.K.; Writing—original draft, S.K.; Writing—review & editing, S.K., R.R., G.-J.S., A.A.M.H. and A.M.G.K.T.

**Funding:** This study was funded by the Ministry of Infrastructure and Environment.

**Acknowledgments:** The authors acknowledge feedback from Jan Willem Notenboom, Raymond Sluiter (KNMI Datalab), Rien Bout and Nieske Bisschop (Ministry of Infrastructure and Environment), Erik de Haan (Province of South Holland), and Arno Lammers (Municipality of The Hague). In addition, the authors acknowledge Andrea Pagani (KNMI Datalab) for the provision and feedback of the sky-view factor data. The authors acknowledge Weather Underground® for making the weather data available, which were used for verification, and acknowledge the weather enthusiasts for sharing their data to the platform of Weather Underground®. We acknowledge Robin Palmer for language editing.

**Conflicts of Interest:** The authors declare no conflict of interest.
