ASAP-East Africa


About The Project

Project Partners:
University of Birmingham

Research Type:
Regional Research

Start Date:
Friday, September 1, 2017

End Date:
Tuesday, June 30, 2020

Urbanisation and Air Pollution

Project Target Countries:
Kenya, Ethiopia and Uganda


Project Description

The overarching objectives of this study are to:

  1. Study urbanisation trends and their impact on air quality

  2. Develop robust and cost appropriate approaches to monitoring air pollution

  3. Generate a holistic evidence base on the causes, consequences and levels of air pollution

  4. Identify and engage with locations and communities which are most vulnerable

  5. Identify social, environmental, policy and management measures to tackle air pollution

  6. Understand the dynamic political economies of focus cities and how these influence urban governance and air quality management

  7. Raise awareness of air pollution problems and impact policy uptake

Work Package Structure

Work Package Structure-01.png

The research programme is split into 7 complementary work packages (WPs), which employ a combination of innovative and multidisciplinary methodologies to study the East African cities as integrated systems. The linking structure of the 7 WPs is shown in below WP1-5 interact and exchange information, then collectively feed into WP6 which itself feeds in WP7. 

WP1- Diagnostic of the three cities and their sub-soft and hard infrastructure systems.

This WP identifies and analyses existing policy documents and datasets in study cities. To understand the different system and system components related to air pollution, a range of data will be collected and analysed. First, we will focus on city policies, and supporting documentation, related to urban infrastructure and air pollution. This will deliver a comparative analytical framework of city systems. Second, we will identify, collect and assess existing social, economic or environmental datasets. The intent is to identify and access the most pertinent public and private datasets as possible. Finally, geocoded data, where it is available, will be used to assemble a spatially integrated dataset consisting of variables drawn from across all datasets that will underpin the analysis in WP4. 

WP2 - Air pollution monitoring. 

Air quality will be measured in the study cities via three techniques: Calibrated low cost sensors, Visibility measurements, and Satellite measurements. The first two techniques will measure particulate matter concentration which has the greatest health impact of any air pollutant in East Africa. The satellite work will allow measurement of particulate matter and nitrogen dioxide another key air pollutant. The low cost sensor approach will measure particulate matter in the two size fractions that are epidemiologically important and subsequently have WHO guidelines: PM2.5 and PM10.[1]  Indoor air pollution will be measured in 30 different dwellings per city, each for 24 hours. The chosen dwellings will be representative of a range of social groups spread throughout the cities. Schools and hospitals in which the inhabitants (with characteristic age demographics) spend a high percentage of their time will also be monitored. Spatial maps and time series of pollutants will allow for analysis of exposure to air pollution to different sectors of society in WP5.

WP3 - Development of a mixed methods comparative framework

This WP will develop an integrated and inter-disciplinary understanding of challenges facing study cities. It will provide perspectives for more liveable environments, working for all regardless of gender, age and social status. Preliminary results from WP1 and WP2, will be assembled to explore the ‘who, what, when, where, why and how’ of soft and hard systems combined to components of air pollution. The focus is on identifying the interplay between different city systems that are involved in air pollution in each city and in determining the most important measures of these interrelationships. 

WP4 - Pollutant emissions modelling. 

Two different model types will be chosen to map pollution across study cities. These will be calibrated from air pollution measurement in WP2. One will be a land-use regression model to provide detailed city wide estimates of air pollutant concentrations on the basis of available variables such as the distance from polluting source. Such models have been shown to provide good estimates of air pollutant concentrations in developed world cities but their application in East Africa has yet to be tested. 

WP5 - A holistic understanding of the causes and effects of air pollution in East African.

Analysis of the data streams obtained from WP1-4 will be used to create a holistic understanding, or ‘city as systems’ approach, of the causes and effects of air pollution and reflect on what this means for the development of more liveable and sustainable urban environments. A principal components analysis (PCA) will be used to identify and understand variance in datasets and how different components relate to air pollution. This approach will enable the identification, for each city, of what can be termed an ‘urban nexus’. This will identify which systems (natural, economic, social, health, etc.) are important for understanding the challenges facing each city. A performance analysis will  be used to understand overall liveability and sustainability performance and how air pollution affects it. This will identify intra-urban and inter-urban differences. The primary sources of air pollution in each city and there locations will be identified and explored in relationship to the distribution of the population across the city. Finally, a first order estimate of the disease burden due to air pollutant exposure for the study cities will be generated. By incorporating information on population densities and use of concentration-response functions (HRAPIE, 2013), it will be feasible to calculate adverse human health outcomes for the mapped areas. This will include both short-term impacts such as daily mortality or hospital admissions and chronic impacts, e.g. premature mortality. 

WP6 - Informing and developing effective solutions to complex challenges.

WP6 acknowledges that it is through local, collective and multi-stakeholder action that the causes and consequences of air pollution can be addressed. The work package will engage local partners to co-design and undertake a programme of fact-finding and learning in the study cities (drawing on WP1-5). This will provide a better understanding of the interrelationship between air pollution, vulnerability and urban governance challenges. A rapid and action-oriented assessment of each study city will be undertaken to facilitate an urban profiling exercise. This will generate a social, economic and political profile of each city, focused on understanding factors contributing to air pollution in contexts of rapid urbanisation. Based on initial findings from urban profiling, alongside data collected in WP1-5, case studies (2 per city) will be developed that explore the spatial and demographic impact of air pollution, focusing on areas with local concentrates of high air pollution, or particularly vulnerable populations. Case studies will focus on the following subset of vulnerability issues: vulnerable areas/localities; vulnerable groups or vulnerable occupations.

WP7 -Co-creation and production of innovative solutions to East African air pollution. 

A series of detailed analytic reports and briefing notes based on multi-disciplinary cross-sectoral analysis will be generated. It will generate evidence based policy recommendations that balance national and city level demands for economic growth with interventions that produce positive results for current and future generations. A central aspect of WP7 is an acknowledgment that addressing air pollution requires the development of coalitions of urban stakeholders (government, private sector and civil society) that drive local solutions. This recognises people as assets; values an approach that works differently, promotes reciprocity across stakeholder groups involved and finally builds social networks that are based on trust and collaboration. The new knowledge generated will spur the development of these coalitions and furnish them with the information required to understand, regulate, monitor, and manage air pollution. To date, environmental protection has generally been a rich-country luxury, but living without chronic air pollution should be a fundamental right for all.