Mapping the urban heat island

Professor Yuan Chao discusses the potential of computer modelling in understanding the urban heat island phenomenon, and in mitigating its negative repercussions, through a scientific approach to design and planning.

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Professor Yuan Chao is Director of Research at NUS Cities, and Founder and Principal Investigator of the Urban Climate Design Lab at NUS

Climate Change Projections and Climate-Sensitive Planning and Design

The Intergovernmental Panel on Climate Change (IPCC) AR6 climate change 2021 report has clearly indicated that anthropogenic influence has increased greenhouse gas (GHG) emissions, which has been warming the global climate at an unprecedented rate [1].

However, according to data from the World Bank, since the first IPCC assessment report in 1990, when the world first became widely aware of the magnitude of the environmental crisis, the annual global GHG emissions, including the GHG emission in Singapore, have not decreased.
The climate risks, such as heatwaves in cities, have been shown to have increased in both frequency and intensity, posing serious threats to human health and the social economy [1].

Cities are responsible for more than 60% of global GHG emissions, and the urban environment is more vulnerable to climate risk than the rural environment due to high-density living and urbanisation [2].

Since rapid urbanisation from the mid-1970s, Singapore has warmed notably at a rate of 0.25 degrees Celsius per decade, according to the Meteorological Service Singapore. This rate is higher than the global average rate of 0.17 degrees Celsius per decade since 1970, a number based on data from IPCC [1][3].

Figure 1a: Projection of the future local impact of climate change on air temperature in Singapore [4].

If the current urban development approach remains unchanged, local warming will lead to a rise in electricity demand for cooling, and a higher risk that residents will suffer from heat stress.

As shown in Figures 1a and 1b, the coupling effect of urbanisation and climate change on the future air temperature is expected to be significant [4].

Figure 1b: Impact of future urbanisation on air temperature in Singapore [4].

Overarching Research Methods

To mitigate, and adapt to, future climate risks in the  urban environment, both immediate and pre-emptive actions in urban planning and design are urgently needed.

However, the impact of climate and relevant research on city and building performance has been very low, even though the idea of developing a climate-sensitive method for designing and operating cities and buildings has been understood for some time.

This issue is caused by the fact that urban planners, architects, meteorologists, and policymakers have been working separately instead of together to address this long-discussed issue, as well as the broader need to balance the human desire for development with the urban carrying capacity.

As architect-environmentalists, my research team at the Urban Climate Design Lab (UCDL), Department of Architecture, National University of Singapore, wears the hats of both a designer and urban climate scientist to achieve the above objectives. Our research at UCDL is precisely multidisciplinary, cross cutting across the fields of architecture design, urban planning, and urban climate science.

Our research approaches include Internet of Things (IoT) urban climate sensing, multi-physics numerical simulation, and Geographic Information System (GIS) modelling-mapping, which have been conducted using consistent and unique approaches.

This can contribute to and aid in a more systematic implementation of urban climate information into urban planning and design practice. Our research ambition is to convert this long-discussed research into actionable solutions that mitigate, and adapt to, potential urban heat risks and other climate issues.

Here, I mainly introduced the development of new GIS climate modelling-planning tools, which are based on urban climate physics and analytics, and are developed from urban planning indices such as the site coverage ratio and plot ratio.
Therefore, rather than using numerical simulations and wind/water tunnel experiments, urban planners can evaluate the impact of new developments on the microclimate in their planning practice, using GIS tools, and so, can avoid complicated fluid dynamic calculations [5].

Both numerical simulation and wind/water tunnels, especially for modelling work at the urban scale, are time-consuming, and thus the modelling results from these tools cannot keep pace with the rapid urban planning and design process.

As a result, the impact of urban climate technicalities on practical urban planning remains low, and the issues regarding the outdoor thermal environment and air quality have not been addressed in practice, despite the growing number of academic journal papers in this field.

Using the above as motivation, the UCDL research team developed GIS climate modelling-mapping tools based on the analytics of momentum/mass/heat transfer at the urban canopy layer and the urban boundary layer to tackle these challenges, as in the four models, as follows.

Urban wind environment model
Fine-scale wind environment model
Urban tree-airflow model
Anthropogenic heat dispersion model

Urban wind environment model

This GIS-based tool makes wind information more accessible to urban planners and designers, enabling them to readily understand urban permeability for outdoor natural ventilation by calculating the familiar planning index, i.e., ground coverage ratio and frontal area density, rather than performing complicated fluid mechanics calculations.

Both the GIS-based tool and the scientific understanding resulting from this study have become an important part of the Sustainable Planning Guidelines in mega cities such as, e.g., Hong Kong and Wuhan, China [6][7].

A similar method has been applied in Singapore. As shown in Figure 2, both potential and existing air paths were identified based on the distribution of frontal area density. This modelling and mapping work provide crucial information to support the high- density development at the Eastern part  of Singapore [3].

Figure 2. Potential and existing air paths identification in the Eastern part of Singapore [3].

Fine-scale wind environment model

Based on the modelling method introduced in the urban wind environment in Section 3.1, I developed a novel approach for modelling high-resolution pedestrian-level wind speed with point-based (as opposed to the usual area-based) metrics [8].

Modeling high-resolution wind at the pedestrian level in heterogenous urban areas without using Computational Fluid Dynamics (CFD) is extremely challenging but critical to supporting district planning and urban design.

The tool, which combines GIS mapping and urban fluid dynamics, can be used in district-scale urban modeling. The UCDL research team integrated this modelling tool into the open-access microclimate digital platform, to facilitate the knowledge and technology transfer, as shown in Figure 3.

Figure 3. Neighborhood scale wind permeability [8].

Urban tree-airflow model

Urban trees and greenery are crucial to the tropical cities, where urban trees and greenery provide a significant nature-based cooling effect throughby shading and evapotranspiration. But, at the same time, urban trees could also have a negative impact on outdoor natural ventilation.

Therefore, it is important to choose the appropriate planting locations and tree species, and modelling work is needed to support this decision-making. However, it is usually very expensive to apply numerical simulation to estimate the drag force of trees on air flow.

This GIS-based tool estimates  the impact of urban trees on  airflow based on the balance between the total drag force of  both buildings and trees on the airflow and vertical flux of horizontal momentum [9].

This modelling tool correlates tree geometries with wind speed in the street canyon, thereby enabling landscape planners to make crucial evidence-based decisions regarding tree species and  planting locations using their  in-house data.

With such a new and innovative practical tool, landscape planning can introduce more trees into urban areas and, meanwhile, minimise the negative effects  of trees on the outdoor  natural ventilation.

Figure 4. Modelling of the drag force of urban trees on air flow, and suggestions on tree species to minimise the negative effect of trees on air flow [9].

Anthropogenic heat dispersion model

Our research on anthropogenic heat dispersion was supported by Singapore’s National Research Foundation.

Anthropogenic heat is an important factor for street air warming, especially in residential areas and at night, therefore, it is important in terms of public health and energy consumption for cooling. Compared with airflow and pollutant dispersion, the challenge of heat dispersion modelling is the buoyancy effect.

The UCDL research team developed an innovative analytical method for including the buoyancy effect into the modelling by introducing a buoyancy coefficient that is estimated based on advanced computational fluid dynamics (CFD) simulation results.

Using the buoyancy coefficient, a GIS-based tool was developed to estimate the impact of anthropogenic heat on air temperature.

With this GIS tool, both the transient and time-averaged air temperature increment can be easily modelled at the urban scale, e.g., the entirety of Singapore, as shown in Figure 5.

Figure 5. Impact of anthropogenic heat emission at residential areas on air temperature [10].

Future Studies

The above-mentioned GIS  modelling-mapping tools have  drawn attention to the rising importance of systematic  climate-sensitive planning tools/guidelines and platforms.

First, the above-mentioned models have been applied in several key policy-level research and design projects commissioned by the  Hong Kong, Wuhan, Macau, and Singapore governments.

Second, the above-mentioned  models have been integrated into an open-access digital platform, the UCDL Microclimate Digital Platform, to facilitate the knowledge and technology transfer.

We have been developing an open-access Microclimate Digital Platform (MDP) to support climate-sensitive urban planning/design practices and training, and to promote climate situation awareness and research collaboration (data, models, design, etc., sharing and exchange).

The primary goals of this platform are to facilitate knowledge and technology transfer, and to empower stakeholders to make evidence-based decisions to build up urban climate sustainability and resilience. MDP is the first platform to integrate multi-scale-physics climate modelling and visualisation through a set of GIS-based modelling tools and a digital platform.

This integration will enable stakeholders (such as urban planners, engineers, health practitioners, environmental engineers and residents) to easily obtain climate information, especially regarding the coupling impacts of climate change and urbanisation on urban climate. We aim to include more climate models into the MDP in the future.

References

[1] Lee H., et al., 2023, Synthesis Report of the IPCC sixth assessment report (AR6), Longer Report, available at: https://report.ipcc.ch/ar6syr/pdf/IPCC_AR6_SYR_LongerReport.pdf.
[2] Hoornweg D., Sugar L., Gomez C., et al., 2020. Cities and Greenhouse Gas Emissions: Moving Forward, 5(1).
[3] Zhang L.Q., Yuan C., 2023, Multi-scale climate-sensitive planning framework to mitigate urban heat island effect: A case study in Singapore, Urban Climate, Urbanisation, 49, 101451.
[4] He W.H., Zhang L.Q., Yuan C., 2022. Future Air Temperature Projection in High-Density Tropical Cities Based on Global Climate Change and Urbanization --- A Study in Singapore, Urban Climate, 42, 101115.
[5] Yuan C., 2018. Urban Wind Environment--Integrated Climate-Sensitive Planning and Design, Edition 1, Springer, Singapore.
[6] Ng E., Yuan C., Chen L., Ren C., Fung J.C.H., 2011. Improving the wind environment in high-density cities by understanding urban morphology and surface roughness: A study in Hong Kong, Landscape and Urban Planning. 101 (1), pp. 59-74.
[7] Yuan C.*, Ren C., and Ng E., 2014. GIS-based surface roughness evaluation in the urban planning system to improve the wind environment -- A study in Wuhan, China, Urban Climate. 10, pp. 585–593.
[8] Yuan C., Norford L.K., Britter R., Ng E., 2016. A Modelling-Mapping Approach for Fine-Scale Assessment of Pedestrian-level Wind in High-Density Cities, Building and Environment. 97, pp. 152-165.
[9] Yuan C.*, Norford L.K., Ng E., 2017. A Semi-Empirical Model for the Effect of Trees on the Urban Wind Environment, Landscape and Urban Planning, 168, pp 84-93.
[10] Yuan C., Adelia A.S., Mei S.J., He W.H., Li X.X., Norford L., 2020. Mitigating intensity of urban heat island by better understanding on urban morphology and anthropogenic heat dispersion, Building and Environment, 176, pp 106876.