Heatwave Vulnerability in Hounslow


Sponsor: London Borough Of Hounslow Contingency Planning Unit teamPhoto
Sponsor Liaison: Twm Palmer, Head of Contingency Planning and Resilience.
Student Team: Nick Benoit, Jerish Brown, Benjamin Mattiuzzi, Connor Murphy

The purpose of this project was to aid the London Borough of Hounslow in improving their heatwave emergency plans and to assist in an experimental project that aims to determine if heatwave models can be used for emergency planning. We accomplished these tasks by first reviewing previously developed models in order to build an operational definition of vulnerability. We then began a large-scale review of data available in the borough that could be used for heat wave modeling and emergency planning. Finally, we created a set of recommendations for the borough and highlighted areas we found to be most at risk to heatwaves based on the data we identified. We also pinpointed key areas of our project that future projects may want to expand upon.


Final Report:  Hounslow IQP Final Submission

Final Presentation: Final IQP Presentation

Executive Summary

Recent heatwave events, such as the European heatwave of 2003 that resulted in seventy thousand deaths across the European Union (Robine et. al., 2008), show that emergency planners need to be increasingly prepared for these situations in order to respond effectively. Understanding where vulnerable populations are located is important for emergency planners in mitigating the risk and damage of these events. To better understand which populations are vulnerable and where they reside, researchers have developed models that can determine the vulnerability of individual dwellings and the people who reside in them.

These models have been evaluated at the national and city-wide level, but not at smaller scales such as at the borough level. A group of researchers at the Greater London Authority, University College London, Meteorological Office, Public Health England, London Climate Change Partnership, and the University of Westminster are attempting to evaluate if heatwave models can be used to help emergency planning at the borough-level by piloting the study in the London Borough of Hounslow. Researchers need to know what data is available within the London Borough of Hounslow and what the use of that data is when compared to more widely available public data in order to complete the pilot study.

Our project’s main objectives were to create an operational definition of vulnerability, work within the borough to identify data that can be used to further heatwave emergency planning efforts, and analyze the data found for its usefulness. We reviewed definitions of vulnerability within multiple heatwave models. This allowed us to understand what kinds of data may be useful. We then identified many sources of data within the borough by interviewing borough employees from various departments. Finally, we developed recommendations for the borough based on findings about the available data.

Developing an Operational Definition of Vulnerability

In order to develop an operational definition of vulnerability, our team researched four heatwave models. The LUCID project is the basis of many studies that have simulated urban heat islands and used localized weather data to analyze the indoor temperature of buildings within the Urban Heat Island (Kolokotroni, 2007). The Triple Heat Jeopardy Framework used age as a proxy for vulnerability, combined with location within the Urban Heat Island and indoor heating modelled using building characteristics, to model mortality. AWESOME examined how air quality combined with indoor temperature affects health. Finally, the Development of a Heatwave Vulnerability Index for London is a study that assigned a vulnerability rating for each Lower Super Output Area based on 10 risk factors.

During our review of the literature, we found definitions of vulnerability are all characterized by a combination of internal and external factors, sensitivity and exposure. We defined vulnerability as a function of local exposure to heat and the sensitivity of individuals. By comparing similar vulnerability factors found within each project, our team identified a number of factors to be most prevalent to heatwave vulnerability: Regional climate, UHI location, indoor heat exposure, high population density, green space, proximity to industry, age, sex, medical condition, socioeconomic and demographic status, social isolation, minority status, and airborne pollutants.

Identification of Vulnerability Data

To identify available data sets on the discussed proxies, our team began by reaching out to interview staff in the London Borough of Hounslow that were recommended by our sponsor, and individuals outside the borough recommended by the Steering Group. The Steering Group is comprised of members of multiple organizations within the Greater London Area who have a stake in heatwave vulnerability planning. Members include our sponsor, the London Borough of Hounslow Contingency Planning Unit, researchers and heatwave vulnerability experts from University College London Institute for Environmental Design and Engineering, health and vulnerability experts from Public Health England, and policy makers from the Greater London Authority and the Mayor’s Office.

We identified multiple sources of data within the London Borough of Hounslow and without; including the London Borough of Hounslow Social Housing databases, multiple layers of the London Borough of Hounslow GIS, a weekly Vulnerable Clients list sent to the Contingency Planning Unit, the public Energy Performance Certificates database, and the United Kingdom Census. From the EPC database, through collaboration with Jonathon Taylor at UCL, we were able to create a new data set that models indoor temperature for buildings in the London Borough of Hounslow at different outdoor temperatures.

Assessment of Datasets

In order to effectively evaluate the data sets identified, we created a set of standard criteria that could be used to assess the various different types of data we encountered. These suitability criteria would allow us to give a qualitative measure of their usefulness. The criteria we chose are accessibility, age, reliability, resolution, pertinence, and completeness of the data set. We chose these criteria based on the factors identified to us by our sponsor and the Steering Group as most important in the data we were discovering. We used these criteria to evaluate data from the United Kingdom Census, the Energy Performance Certificate database, the London Borough of Hounslow Social Housing database, the London Borough of Hounslow Geographic Information System database, and Indoor Temperature Model data provided by Jonathon Taylor at UCL.

Conclusions and Recommendations

Throughout our project, we were faced with challenges that made it difficult to collect and analyze important data, but despite these challenges we have been able to discover and analyze multiple data sets related to heatwave vulnerability.

Vulnerability Analysis

  • An assessment of the effectiveness of complex vulnerability analysis and indices reliant on composite measures of vulnerability will need to be pursued by emergency planning officials within the London Borough of Hounslow and researchers from the Hounslow Heatwave Steering Group.
  • We believe targeting vulnerable areas with additional information prior to and during heatwave events will help reduce the risk of increased morbidity and mortality during a heatwave. Using MOSAIC data available on the Hounslow GIS, targeted information can be broadcast to the residents of these areas using the most effective means of communication for the prevalent demographics.

Vulnerability Factors and the Indoor Overheating Model

When analyzing the layers from the GIS, there were areas that became clearly identifiable as vulnerable to a variety of proxies our team had identified. Though we were not qualified to identify the weights of comparative proxies within the layers, our team conducted a count of recorded areas and the prevalent proxies that were found for each.

  • We recommend emergency planners use high indoor heat exposure trends to place cooling centers and allocate resources more effectively. Additionally, this can allow targeted warning and informing procedures for neighborhoods most likely to be adversely affected in the days leading up to a heatwave.
  • We recommend targeting neighborhoods that show trends of overheating for improvement projects that mitigate the effects of heatwaves can target dwellings identified as most likely to overheat.


Housing Data

We found that the borough does not hold data on the privately owned housing within the borough. The indoor overheating model could be improved by having access to highly accurate data on all housing within the borough.

  • We recommend that the borough carries out the CROHM assessment on privately owned housing stock in order to have a complete housing characteristics data set.
    • This data can be used by researchers to model indoor temperature exposure at the address level.
    • The data can be mapped in order to spatially analyze trends of high heat exposure. This has implications for emergency planning and long-term development and regeneration within the borough.


Future Projects

  • We recommend that future projects look further into the data identified in this report by having thorough discussions with the teams and individuals identified as owners of the data. In particular, the borough’s Health and Wellbeing and General Practitioners or Clinical Commissioning Groups that work with the borough. Collaboration may provide Emergency Planners with more information about vulnerable people within the London Borough of Hounslow than they currently have access to.
  • We recommend that future projects complete the Privacy Impact Assessment (PIA), a document that is required in order to access data that the borough holds, early on in their project timeline. The PIA was a major roadblock in our project and we anticipate that it will also be a challenge for future projects.

The London Borough of Hounslow has the opportunity to save lives, more effectively allocate resources, and improve the wellbeing of its most deprived citizens through improved heatwave response and emergency planning. Our recommendations can be implemented provisionally and assessed in by qualified researchers and emergency planners in order to test their effectiveness. If shown to be effective, these measures could be integrated into the London Borough of Hounslow’s heatwave plan.