APEx: An Air Pollution Exposure model to integrate protection of vulnerable groups into the UK Clean Air Programme

Lead Research Organisation: King's College London
Department Name: Analytical & Environmental Sciences

Abstract

Poor air quality is a public health crisis, with approximately 40,000 deaths per year attributable to outdoor air pollution and costing the UK £20 billion per year in illness, deaths, health service and business costs (RCP, 2016). Poor indoor air quality further adds to this risk and is often overlooked despite the majority of the UK population spending more than 90% of its time indoors. The risk to health of poor air quality and its impacts being disproportionally suffered by vulnerable groups, such as children, the elderly and those with underlying health problems. This risk is heightened by the impact of poor-quality buildings and other unavoidable socio-economic vulnerabilities. Despite this crisis and acknowledgement of the risks for individuals, current methods for assessing the impact of clean air policies are entirely based on outdoor air quality, without considering human behaviours or susceptibility. This study will place people at the centre of the problem by creating an exposure model that more accurately reflects the air that people breathe as they interact with the city, incorporating the indoor and outdoor environment, transport and behaviour patterns.

Bringing together experts from a range of disciplines, this study will create a tool that will inform the implementation of the UK Government's Clean Air Strategy. This tool, called APEx, will be used to instigate new solutions to protect the health of vulnerable groups, allow the refinement of existing solutions to increase impact and reduce unintended consequences. It will achieve this by merging three existing advanced urban models of air pollution, buildings and urban form and a human behaviour (agent-based) model that will, in combination, be capable of estimating how much air pollution people are exposed to as they move around a city. APEx will be evaluated using an extensive database of world leading and unique personal exposure measurements gathered from several research campaigns carried out in recent years. Choice surveys will be carried out to ensure that human behaviour is correctly reflected in the model, including how citizens might react to the introduction of proposed clean air policies.

The tool will first be developed for London, where the most input data are available, then expanded to cover the city of Birmingham. A protocol will be developed describing how further cities could be incorporated in the future to assist in protective person-centred air quality management across the UK. As cities design, implement and evaluate air pollution policies and controls, they need tools and guides that take into account how people experience air pollution and make choices that affect their exposure.

Once complete, APEx will be used to quantify the impact of current Clean Air Zone policies on the levels of air pollution citizens breathe. These results will be used to formulate new or augmented policy scenarios incorporating human choice and behaviour to reduce atmospheric emissions and protect targeted vulnerable groups. Throughout the study, we will engage with public representatives and stakeholders through workshops and online user groups. This co-production of knowledge will maximise the relevance of outputs, including model design, policy formulation and public health advice.

RCP (2016). 'Every breath we take: the lifelong impact of air pollution'. https://www.rcplondon.ac.uk/projects/outputs/every-breath-we-take-lifelong-impact-air-pollution

Planned Impact

Due to its connection with daily activities and recognisable human behaviour, evidence and knowledge based personal exposure to air pollution can have greater public impact than fixed ambient measurements. Furthermore, the APEx study's focus on evidence and actions to identify and protect vulnerable groups has the potential to deliver significant and rapid impact, as such information has not previously been available.

We will work with stakeholders and media outlets to create engaging materials illustrating APEx study outputs with the aim of increasing public understanding, thereby closing the knowledge gap between perception and evidence.

The introduction of human activities and behaviour into the air quality management process creates great opportunities for impact, but also considerable challenges. For this reason, the APEx study will closely and frequently engage with a range of stakeholders with representation from relevant NGOs (e.g. British Heart Foundation, British Lung Foundation, Age Concern etc.), policy makers (e.g. Greater London Authority, Public Health England, Birmingham City Council) and members of the public (e.g. school governors, community group leaders). This method of co-production of knowledge will ensure that messages developed during the study will be rapidly and widely disseminated via the stakeholders.

Engagement with policy makers in development of the APEx model will result in the formulation of new and augmented policy options. Of particular interest will be policies based on behavioural change based on public information campaigns, rather than new legislation or restrictions. We will present information to stakeholders via a series of demonstration case studies highlighting the impact of behaviour and choice on policy design and outcomes

By creating a protocol for the deployment of the APEx model, or similar modelling frameworks, in other cities and countries will allow the translation of APEx science into other regions. Each region will be capable of testing policy scenarios tailored to their own population behaviour and vulnerable groups.

We envisage that the data obtained from the APEx study will provide novel information that will be significant and interesting to researchers active in numerous areas and disciplines. For example, research into urban and transport planning, building design, social justice and behavioural change. The integration of human behaviour into physical and environmental models has the potential to be applied in other domains where populations interact with urban landscapes, such as climate change. In addition, the APEx model will be applicable to future epidemiological, cohort, panel or toxicological studies linking health outcomes to the pollutants modelled. More accurate representation of exposure should allow stronger associations with fewer confounders.

Several features of our study will maximise the translation of APEx science to other research fields; (i) it is a multidisciplinary collaborative study across six universities, (ii) Investigators are drawn from four Centres of Excellence representing each of the four Research Councils and (iii) APEx will integrate and other studies within the Clean Air Programme studies. We will exploit each of these opportunities via regular cross-institution invited seminars, presentation at Centre conferences, future joint applications and collaborative programme meetings.

Publications

10 25 50

Related Projects

Project Reference Relationship Related To Start End Award Value
NE/T001887/1 13/02/2019 29/06/2020 £1,356,617
NE/T001887/2 Transfer NE/T001887/1 30/06/2020 12/02/2023 £1,024,736
 
Description (urbisphere) - urbisphere - coupling dynamic cities and climate
Amount € 12,720,904 (EUR)
Funding ID 855005 
Organisation European Commission 
Sector Public
Country European Union (EU)
Start 03/2020 
End 03/2026
 
Description ASSURE: Across-Scale processeS in URban Environments
Amount £624,437 (GBP)
Funding ID NE/W002965/1 
Organisation Natural Environment Research Council 
Sector Public
Country United Kingdom
Start 12/2021 
End 11/2025
 
Description Investigating the consequences of measurement error of gradually more sophisticated long-term personal exposure models in assessing health effects: The London Study
Amount $809,000 (USD)
Organisation Health Effects Institute (HEI) 
Sector Charity/Non Profit
Country United States
Start 06/2020 
End 06/2023
 
Description West London Healthy Home and Environment Study (WellHome)
Amount £2,900,363 (GBP)
Funding ID NE/W002116/1 
Organisation Natural Environment Research Council 
Sector Public
Country United Kingdom
Start 07/2021 
End 07/2025
 
Title Dynamic Anthropogenic activitieS impacting Heat emissions (DASH v1.0): Development and evaluation 
Description Dynamic Anthropogenic activitieS impacting Heat emissions (DASH v1.0): Development and evaluation DASH - is undergoing significantly development (e.g. being made more generic, more efficient, more capabilities). Currently, results are benchmarked to this version. Please contact c.s.grimmond@reading.ac.uk to find out about the most appropriate source of code Funding Acknowledgement: UK-China Research & Innovation Partnership Fund through the Met Office Climate Science for Service Partnership (CSSP) China as part of the Newton Fund EPSRC (Reading) NERC APEx:10.13039/501100000690::NE/T001887/1 ERC-2019-SyG: 855005 urbisphere Overview Source code and input data for v1.0 of the Dynamic Anthropogenic activitieS impacting Heat emissions model. DASH considers both urban form and function in simulating QF by use of an agent-based structure that includes behavioural characteristics of city populations. This allows social practices to drive the calculation of QF as occupants move, varying by day type, demographic, location, activity, socio-economic factors and in response to environmental conditions. DASH has simple transport and building energy models to allow simulation of dynamic vehicle use, occupancy and heating/cooling demand, with subsequent release of energy to the outdoor environment through the building fabric. The entire model comprises two parts: 1. Agent interaction (under 2.movementtravel) 2. Agent reaction (under.energyQfcalcs README files can be found in each folder with quick start guides for each. 1.dataprocessing Currently in python 3.7 ## what does this code do? Various scripts transform elements of raw data to input data readable by DASH ## what does this folder include? Input Data Processed Data - source-code # scripts for creating input data from raw data ## how to run this code? 1. Different elements are currently run separately. # 2.movementtravel ## what does this code do? 1. Determines the travel and movement behaviours. 2. Distributes people across the city. 3. Provides occupancy and transport levels across the study area. ## What does this folder include? run `tree . -d -L 1` to show the following (may vary over time) Data # input data +-- Runs # runs with cfg and output +-- py2-backup.tgz # backup of py2 files before 2to3 conversion +-- gen-traveltime-py2 # script to generate travel functions in py2 +-- source-code # source code ## How to run this module Before run this code, 2to3 was executed to convert all code into py3. the py2 version is secured into `py2-backup.tgz` archive QUICK START Run the code: 1. entry point: `source_code/Main.py`: `python3 Main.py`# 3.energyQfcalcs## what does this code do? 1. To determine the occupancy levels in buildings 2. To determine distribution of traffic on transport network 2. To calculate energy use - giving Qf (B, T, and M)## what does this folder include? run tree . -d -L 1 to show the following (may vary over time) +-- Data # input data +-- Runs # runs with cfg and output +-- py2-backup.tar # backup of py2 files before 2to3 conversion +-- source-code # source code## how to run this code? 1. create and install the C code extension in directory `STEBBS`, run: to install the C extension. 2. main file: `Main.py` switch the same folder of this `README.md` file, run the following: python3 source_code/Main.py # 4.visualisation ## what does this code do? 1. Produces graphs of results from 2.movementtravel and 3.energyQfcalcs ## what does this folder include? run `tree . -d -L 1` to show the following (may vary over time) +-- source-code # scripts for creating plots from results ## how to run this code?. Different elements are currently run separately. 
Type Of Technology Software 
Year Produced 2020 
Open Source License? Yes  
URL https://zenodo.org/record/3745524
 
Title Dynamic Anthropogenic activitieS impacting Heat emissions (DASH v1.0): Development and evaluation 
Description Dynamic Anthropogenic activitieS impacting Heat emissions (DASH v1.0): Development and evaluation DASH - is undergoing significantly development (e.g. being made more generic, more efficient, more capabilities). Currently, results are benchmarked to this version. Please contact c.s.grimmond@reading.ac.uk to find out about the most appropriate source of code Funding Acknowledgement: UK-China Research & Innovation Partnership Fund through the Met Office Climate Science for Service Partnership (CSSP) China as part of the Newton Fund EPSRC (Reading) NERC APEx:10.13039/501100000690::NE/T001887/1 ERC-2019-SyG: 855005 urbisphere Overview Source code and input data for v1.0 of the Dynamic Anthropogenic activitieS impacting Heat emissions model. DASH considers both urban form and function in simulating QF by use of an agent-based structure that includes behavioural characteristics of city populations. This allows social practices to drive the calculation of QF as occupants move, varying by day type, demographic, location, activity, socio-economic factors and in response to environmental conditions. DASH has simple transport and building energy models to allow simulation of dynamic vehicle use, occupancy and heating/cooling demand, with subsequent release of energy to the outdoor environment through the building fabric. The entire model comprises two parts: 1. Agent interaction (under 2.movementtravel) 2. Agent reaction (under.energyQfcalcs README files can be found in each folder with quick start guides for each. 1.dataprocessing Currently in python 3.7 ## what does this code do? Various scripts transform elements of raw data to input data readable by DASH ## what does this folder include? Input Data Processed Data - source-code # scripts for creating input data from raw data ## how to run this code? 1. Different elements are currently run separately. # 2.movementtravel ## what does this code do? 1. Determines the travel and movement behaviours. 2. Distributes people across the city. 3. Provides occupancy and transport levels across the study area. ## What does this folder include? run `tree . -d -L 1` to show the following (may vary over time) Data # input data +-- Runs # runs with cfg and output +-- py2-backup.tgz # backup of py2 files before 2to3 conversion +-- gen-traveltime-py2 # script to generate travel functions in py2 +-- source-code # source code ## How to run this module Before run this code, 2to3 was executed to convert all code into py3. the py2 version is secured into `py2-backup.tgz` archive QUICK START Run the code: 1. entry point: `source_code/Main.py`: `python3 Main.py`# 3.energyQfcalcs## what does this code do? 1. To determine the occupancy levels in buildings 2. To determine distribution of traffic on transport network 2. To calculate energy use - giving Qf (B, T, and M)## what does this folder include? run tree . -d -L 1 to show the following (may vary over time) +-- Data # input data +-- Runs # runs with cfg and output +-- py2-backup.tar # backup of py2 files before 2to3 conversion +-- source-code # source code## how to run this code? 1. create and install the C code extension in directory `STEBBS`, run: to install the C extension. 2. main file: `Main.py` switch the same folder of this `README.md` file, run the following: python3 source_code/Main.py # 4.visualisation ## what does this code do? 1. Produces graphs of results from 2.movementtravel and 3.energyQfcalcs ## what does this folder include? run `tree . -d -L 1` to show the following (may vary over time) +-- source-code # scripts for creating plots from results ## how to run this code?. Different elements are currently run separately. New ZipFile (7/7/2020) - BESTEST evaluation of STEBBS using EnergyPlus 
Type Of Technology Software 
Year Produced 2020 
Open Source License? Yes  
URL https://zenodo.org/record/3933327
 
Title Dynamic Anthropogenic activitieS impacting Heat emissions (DASH v1.0): Development and evaluation 
Description Dynamic Anthropogenic activitieS impacting Heat emissions (DASH v1.0): Development and evaluation DASH - is undergoing significantly development (e.g. being made more generic, more efficient, more capabilities). Currently, results are benchmarked to this version. Please contact c.s.grimmond@reading.ac.uk to find out about the most appropriate source of code Funding Acknowledgement: UK-China Research & Innovation Partnership Fund through the Met Office Climate Science for Service Partnership (CSSP) China as part of the Newton Fund EPSRC (Reading) NERC APEx:10.13039/501100000690::NE/T001887/1 ERC-2019-SyG: 855005 urbisphere Overview Source code and input data for v1.0 of the Dynamic Anthropogenic activitieS impacting Heat emissions model. DASH considers both urban form and function in simulating QF by use of an agent-based structure that includes behavioural characteristics of city populations. This allows social practices to drive the calculation of QF as occupants move, varying by day type, demographic, location, activity, socio-economic factors and in response to environmental conditions. DASH has simple transport and building energy models to allow simulation of dynamic vehicle use, occupancy and heating/cooling demand, with subsequent release of energy to the outdoor environment through the building fabric. The entire model comprises two parts: 1. Agent interaction (under 2.movementtravel) 2. Agent reaction (under.energyQfcalcs README files can be found in each folder with quick start guides for each. 1.dataprocessing Currently in python 3.7 ## what does this code do? Various scripts transform elements of raw data to input data readable by DASH ## what does this folder include? Input Data Processed Data - source-code # scripts for creating input data from raw data ## how to run this code? 1. Different elements are currently run separately. # 2.movementtravel ## what does this code do? 1. Determines the travel and movement behaviours. 2. Distributes people across the city. 3. Provides occupancy and transport levels across the study area. ## What does this folder include? run `tree . -d -L 1` to show the following (may vary over time) Data # input data +-- Runs # runs with cfg and output +-- py2-backup.tgz # backup of py2 files before 2to3 conversion +-- gen-traveltime-py2 # script to generate travel functions in py2 +-- source-code # source code ## How to run this module Before run this code, 2to3 was executed to convert all code into py3. the py2 version is secured into `py2-backup.tgz` archive QUICK START Run the code: 1. entry point: `source_code/Main.py`: `python3 Main.py`# 3.energyQfcalcs## what does this code do? 1. To determine the occupancy levels in buildings 2. To determine distribution of traffic on transport network 2. To calculate energy use - giving Qf (B, T, and M)## what does this folder include? run tree . -d -L 1 to show the following (may vary over time) +-- Data # input data +-- Runs # runs with cfg and output +-- py2-backup.tar # backup of py2 files before 2to3 conversion +-- source-code # source code## how to run this code? 1. create and install the C code extension in directory `STEBBS`, run: to install the C extension. 2. main file: `Main.py` switch the same folder of this `README.md` file, run the following: python3 source_code/Main.py # 4.visualisation ## what does this code do? 1. Produces graphs of results from 2.movementtravel and 3.energyQfcalcs ## what does this folder include? run `tree . -d -L 1` to show the following (may vary over time) +-- source-code # scripts for creating plots from results ## how to run this code?. Different elements are currently run separately. New ZipFile (7/7/2020) - BESTEST evaluation of STEBBS using EnergyPlus 8/7/20 Update data file - DASH-X-GMD-results.zip 8/7/20 code and input data DASH-X-GMD-1.0r.tar.gz 
Type Of Technology Software 
Year Produced 2020 
Open Source License? Yes  
URL https://zenodo.org/record/3936025
 
Title Dynamic Anthropogenic activitieS impacting Heat emissions (DASH v1.0): Development and evaluation 
Description Dynamic Anthropogenic activitieS impacting Heat emissions (DASH v1.0): Development and evaluation DASH - is undergoing significantly development (e.g. being made more generic, more efficient, more capabilities). Currently, results are benchmarked to this version. Please contact c.s.grimmond@reading.ac.uk to find out about the most appropriate source of code Funding Acknowledgement: UK-China Research & Innovation Partnership Fund through the Met Office Climate Science for Service Partnership (CSSP) China as part of the Newton Fund EPSRC (Reading) NERC APEx:10.13039/501100000690::NE/T001887/1 ERC-2019-SyG: 855005 urbisphere Overview Source code and input data for v1.0 of the Dynamic Anthropogenic activitieS impacting Heat emissions model. DASH considers both urban form and function in simulating QF by use of an agent-based structure that includes behavioural characteristics of city populations. This allows social practices to drive the calculation of QF as occupants move, varying by day type, demographic, location, activity, socio-economic factors and in response to environmental conditions. DASH has simple transport and building energy models to allow simulation of dynamic vehicle use, occupancy and heating/cooling demand, with subsequent release of energy to the outdoor environment through the building fabric. The entire model comprises two parts: 1. Agent interaction (under 2.movementtravel) 2. Agent reaction (under.energyQfcalcs README files can be found in each folder with quick start guides for each. 1.dataprocessing Currently in python 3.7 ## what does this code do? Various scripts transform elements of raw data to input data readable by DASH ## what does this folder include? Input Data Processed Data - source-code # scripts for creating input data from raw data ## how to run this code? 1. Different elements are currently run separately. # 2.movementtravel ## what does this code do? 1. Determines the travel and movement behaviours. 2. Distributes people across the city. 3. Provides occupancy and transport levels across the study area. ## What does this folder include? run `tree . -d -L 1` to show the following (may vary over time) Data # input data +-- Runs # runs with cfg and output +-- py2-backup.tgz # backup of py2 files before 2to3 conversion +-- gen-traveltime-py2 # script to generate travel functions in py2 +-- source-code # source code ## How to run this module Before run this code, 2to3 was executed to convert all code into py3. the py2 version is secured into `py2-backup.tgz` archive QUICK START Run the code: 1. entry point: `source_code/Main.py`: `python3 Main.py`# 3.energyQfcalcs## what does this code do? 1. To determine the occupancy levels in buildings 2. To determine distribution of traffic on transport network 2. To calculate energy use - giving Qf (B, T, and M)## what does this folder include? run tree . -d -L 1 to show the following (may vary over time) +-- Data # input data +-- Runs # runs with cfg and output +-- py2-backup.tar # backup of py2 files before 2to3 conversion +-- source-code # source code## how to run this code? 1. create and install the C code extension in directory `STEBBS`, run: to install the C extension. 2. main file: `Main.py` switch the same folder of this `README.md` file, run the following: python3 source_code/Main.py # 4.visualisation ## what does this code do? 1. Produces graphs of results from 2.movementtravel and 3.energyQfcalcs ## what does this folder include? run `tree . -d -L 1` to show the following (may vary over time) +-- source-code # scripts for creating plots from results ## how to run this code?. Different elements are currently run separately. New ZipFile (7/7/2020) - BESTEST evaluation of STEBBS using EnergyPlus 8/7/20 Update data file - DASH-X-GMD-results.zip 8/7/20 code and input data DASH-X-GMD-1.0r.tar.gz 
Type Of Technology Software 
Year Produced 2020 
Open Source License? Yes  
URL https://zenodo.org/record/3745523
 
Description Presentation at Public Health England Annual UK Review Meeting on Outdoor and Indoor Air Pollution Research 
Form Of Engagement Activity A talk or presentation
Part Of Official Scheme? No
Geographic Reach National
Primary Audience Professional Practitioners
Results and Impact Keynote presentation of the study aims and objectives to the annual conference (virtual).
Year(s) Of Engagement Activity 2020
URL http://www.phe-events.org.uk/airpollution20
 
Description Presentation of the APEx behavioural WP to the Clean Air 4V Network 
Form Of Engagement Activity A talk or presentation
Part Of Official Scheme? No
Geographic Reach National
Primary Audience Professional Practitioners
Results and Impact Virtual presentation of the APEx behavioural WP to the Clean Air 4V Network
Year(s) Of Engagement Activity 2020,2021,2022
 
Description Presentation/facilitation of workshop at the SPF Clean Air conference 
Form Of Engagement Activity Participation in an activity, workshop or similar
Part Of Official Scheme? No
Geographic Reach National
Primary Audience Professional Practitioners
Results and Impact Anomitro Chatterjee and Ganga Shreedhar facilitated three sessions at the SPF Clean Air conference. The aim was to present an overview of APEx and seek input and suggestions around potential policy scenarios to test
Year(s) Of Engagement Activity 2020,2021,2022