Sub-national cooling risks

This report examines a more comprehensive methodology that evaluates key factors of the risks due to lack of access to cooling with the use of geo-spatial data and tools to more easily identify regions that experience persistent exposure to high temperatures. This level of information is helpful to identify specific pockets within sub-national regions, for example a town or district that are home to populations that could be at risk. Geographic information system (GIS) tools are proving to be efficient in identifying sub-national levels of access to cooling and provide an added advantage of rendering information, such as average temperature or average peak temperatures, [2] to visually identify zones that need additional attention or deeper analysis. GIS tools can also be used to portray economic and infrastructure-related data to better gauge the risks associated with cooling access gaps and opportunities to address them. However, the data for such analysis, particularly socioeconomic and infrastructure information, are very limited and typically not open source.

Chilling Prospects 2021 has put special emphasis on obtaining, utilizing, and analyzing open-source and internationally recognized data, so that the methodology can be easily replicated, including by countries and governments without access to extensive funding and/or expertise for the GIS tools. The resources used in these analyses are recognized globally as being derived from various projects funded by the UN, the World Bank and similar organizations. They include climate data, [3] population data and administrative boundaries [4]. Local data were used, where possible, to analyze the cooling access risks at sub-national level (Table 2.1).

Table 2.1: Indicators for assessing cooling risks at sub-national level

Accounting for the limited scope and time available for analysis of quantitative data across the different indicators, the methodology for Chilling Prospects 2021 uses GIS information specifically on temperature, visual rendering, and identification of administrative zones. Layering GIS data allows analysts to visually identify the locations that are exposed to high temperatures (above 35°C). If data are available then additional information, such as population, incomes, electricity access and electricity grid connections, can be layered on other GIS data to assess the risks associated with lack of cooling. Furthermore, information on passive cooling solutions that are relevant to local contexts such as building designs and nature-based solutions can be helpful for deeper evaluations for cooling access gaps. The 2021 sub-national cooling risk analysis uses a hybrid method, where the initial risk screening was carried out through a GIS tool [5] and subsequent risk assessment and regional cooling access disparities were analyzed with quantitative data (Figure 2.1). [6]

The key elements used in these analyses include temperature, GIS data, population density data, population data (quantitative national statistics), poverty data (quantitative national statistics or data adjusted to World Bank definitions), and tertiary data including for electricity access and appliance ownership where available. This model investigates cooling access gaps at sub-national levels mostly from a thermal comfort perspective with a limited assessment of food and nutrition security and healthcare and medical services. Further collection of cooling needs and sector-specific data, as identified in SEforALL's Cooling for All Needs Assessment, is needed for sub-national and national cooling assessments. 

Figure 2.1: Methodology to assess sub-national access to cooling risks