Using Climate-Sensitive 3D City Modeling to Analyze Outdoor Thermal Comfort in Urban Areas

Abstract

With increasing urbanization, climate change poses an unprecedented threat, and climate-sensitive urban management is highly demanded. Mitigating climate change undoubtedly requires smarter urban design tools and techniques than ever before. With the continuous evolution of geospatial technologies and an added benefit of analyzing and virtually visualizing our world in three dimensions, the focus is now shifting from a traditional 2D to a more complicated 3D spatial design and assessment with increasing potential of supporting climate-responsive urban decisions. This paper focuses on using 3D city models to calculate the mean radiant temperature (Tmrt) as an outdoor thermal comfort indicator in terms of assessing the spatiotemporal distribution of heat stress on the district scale. The analysis is done to evaluate planning scenarios for a district transformation in Montreal/Canada. The research identifies a systematic workflow to assess and upgrade the outdoor thermal comfort using the contribution of ArcGIS CityEngine for 3D city modeling and the open-source model of solar longwave environmental irradiance geometry (SOLWEIG) as the climate assessment model. A statistically downscaled weather profile for the warmest year predicted before 2050 (2047) is used for climate data. The outcome shows the workflow capacity for the structured recognition of area under heat stress alongside supporting the efficient intervention, the tree placement as a passive strategy of heat mitigation. The adaptability of workflow with the various urban scale makes it an effective response to the technical challenges of urban designers for decision-making and action planning. However, the discovered technical issues in data conversion and wall surface albedo processing call for the climate assessment model improvement as future demand.

Findings from a field study of urban microclimate in Korea using mobile meteorological measurements

“…Figure 6b shows the same correlations measured on September 13 and 30, using fixed weather stations. The parameter T mrt is an indicator that is widely used to assess the effects of urban form on outdoor thermal comfort in urban environments, which is mainly affected by the exposure to sunlight and material properties of the surface (HosseiniHaghighi et al. , 2020).…”

“…Figure 6b shows the same correlations measured on September 13 and 30, using fixed weather stations. The parameter T mrt is an indicator that is widely used to assess the effects of urban form on outdoor thermal comfort in urban Effects of urban canyons on air temperature environments, which is mainly affected by the exposure to sunlight and material properties of the surface (HosseiniHaghighi et al, 2020). For example, the differences in T mrt between shaded and sunlit areas were measured at up to 20 8C in Freiburg, Germany, while the variations in air temperature were only 1-2 8C (Mayer et al, 2008) Effects of urban canyons on air temperature (shaded area) and 28 (sunlit area) on September 13 and 30 ranged from 24.1 to 43.7 8C (see Figure 6b).…”

City‐scale assessment of the material and environmental footprint of buildings using an advanced building information model: A case study from Canberra, Australia

“…Several building stock models focus on assessing energy consumption to promote efficient use of energy in buildings (Evans et al, 2017;Guo et al, 2019;Heisel et al, 2022;Österbring et al, 2016). Other applications focus on informing planning urban resources (Padsala et al, 2021); assessing urban water demand (Bao et al, 2020); forecasting the growth of employment and population retention and transport and land use planning (The Mid-Region Council of Government, 2022;UrbanSim Inc., n.d.); analyzing outdoor thermal comfort (Hosseinihaghighi et al, 2020); and assessing global urban settlements and agglomeration by generating a global 3D map of buildings (Esch et al, 2022).…”

Impacts of Urban Morphology on Seasonal Land Surface Temperatures: Comparing Grid- and Block-Based Approaches

“…Converting natural land cover into urbanized impervious surfaces significantly increases LST in warm seasons, primarily because of the removal of evapotranspiration cooling by vegetation and water bodies and the increase in low-albedo materials such as buildings and roads [21][22][23]. Surface albedo significantly influences LST by altering solar radiation absorption [24,25]. Low-albedo urban features absorb and retain a significant amount of solar radiation, instead of reflecting it, and release the heat slowly, exacerbating the urban heat island effect [13,22].…”