Regional to local scale air quality modelling

Quick links: DHAQ-SEA Punjab road impacts Ireland maps MAQS-Health PRAISE-HK Guangdong forecasting CureAir

The World Health Organisation has stated that air pollution is one of the greatest environmental risks to health. The air pollutant concentrations to which people are exposed are a result of interactions between pollutant emissions, atmospheric and chemical processes. These processes occur over both long (hours to days) and short (seconds to hours) time scales, and also distant (many 100 km) and local (metres to many km) spatial scales. The different pollutants with associated health risks are influenced by different processes: for example, urban NO₂ concentrations are primarily dependent on local combustion sources (e.g. traffic); whereas PM_2.5 is strongly influenced by long-range pollutant transport (e.g. the generation of secondary inorganic aerosols such as ammonium nitrate) as well as by local pollution sources (e.g. domestic burning).

Coupling local and regional models allows both the resolution of high concentration gradients close to a source (as modelled by ADMS-Urban), and the accurate representation of transport and chemistry over large spatial and temporal scales (modelled by a regional chemical transport model). CERC's Multi-Model Air Quality System (MAQS) combines regional and local concentrations in such a way as to minimise double-counting of emissions, while remaining computationally efficient and user-friendly. Spatially varying meteorological data is used consistently within both the regional and local models.

Accurate estimates of pollutant emission rates are key to sucessful air quality modelling. CERC's EMIT tool can be used to combine activity data, such as traffic counts, with emission factors and vehicle fleets which can be adjusted to reflect local conditions or specific interventions such as low-emission zones. EMIT can also be used to generate 3D hourly emissions grid files which are used as input to MAQS.

MAQS can be used for baseline historical modelling, scenario assessment and forecasting applications. The projects described below give examples. Contact us if you would like to know more or if you would like to set up your own system.

DHAQ-SEA - Demonstration of High-resolution Air Quality forecasting in South East Asia

The DHAQ-SEA project was a feasibility study which demonstrated the development of a high resolution (street-scale) air quality forecasting system for ASEAN regions. The MAQS coupled system was used to ensure that both regional (using data from CAMS) and local (modelled using ADMS-Urban) pollution were accounted for. The system could be implemented throughout ASEAN, as it relies primarily on open data sources.

The project focussed on the priority area 'Health', addressing Sustainable Development Goal (SDG) 3 'Ensure healthy lives and promote well-being for all at all ages'. There is an increased risk of certain health conditions where ambient air pollution levels are high. ASEAN countries can be subject to poor air quality as a consequence of transboundary pollution as well as local pollutant sources. Alerting the public prior to air pollution episodes allows vulnerable and other individuals to take action to reduce the health impacts of poor air quality.

CERC worked on DHAQ-SEA with project partners from the Institute for Environment and Resources, Vietnam National University, Ho Chi Minh City and the Department of Earth Sciences and Environment, Faculty of Science and Technology, Universiti Kebangsaan Malaysia. The project received Official Development Assistance (ODA) funding from the UK government Foreign, Commonwealth & Development Office (FCDO) under the Research and Innovation for Development in ASEAN (RIDA) programme.

Key DHAQ-SEA project outputs included:

• Technical: high resolution pollution maps corresponding to air pollution episodes for two distinct domains: a 200 km × 200 km region covering Ho Chi Minh City in Vietnam, including the Svay Rieng Province in Cambodia; and a 200 km × 200 km area, including the Kuala Lumpur mega-urban area.
• Stakeholder engagement: An online workshop for key ASEAN stakeholders in May 2024. Presentations included: an overview of the project's technical methodology and outcomes; and an outline of the steps required to develop an operational high-resolution system for any ASEAN region.
• Reporting: a comprehensive report was produced following completion of the project, including details of stakeholder engagement outcomes, modelling results and evaluation of model performance. The report also described how an operational AQ forecasting service based on the demonstration modelling could be developed for ASEAN regions.

Economic and health outcomes of road building in the Punjab region of Pakistan

Researchers in spatial economics, development, and trade have studied how improvements in transportation infrastructure generate welfare benefits by reducing the costs of within-country trade and commuting. Simultaneously, economists are increasingly recognizing the negative consequences of air pollution, such as reduced life expectancy and decreased productivity. Consequently, it is crucial to consider the local pollutant emissions resulting from road traffic when evaluating the impacts of transport improvements.

As part of a project seeking to estimate the local economic costs resulting from transportation infrastructure and road traffic in Pakistan, and compare them to the estimated benefits, CERC have been contracted by a team of researchers from MIT (USA), the London School of Economics (UK) and Sciences Po (Paris) to support air quality modelling over the Punjab.

The modelling uses the MAQS coupled system with publicly available: meteorological data from ECMWF; concentration reanalysis data from CAMS; and gridded emissions data from EDGAR. The researchers have used multiple data sources, statistical methods, and CERC's emissions database tool EMIT, to develop an explicit road traffic emissions dataset for all major routes in the Punjab. Some traffic data comes from GPS trackers installed on many thousands of trucks travelling across Pakistan over a 7-year period. Fleet technology information has been provided by The Urban Unit.

After baseline air quality and economic modelling to study the welfare benefits of transportation infrastructure, the researchers will conduct counterfactual air pollution modelling and analyses to investigate the impact of road improvement projects on welfare across different locations in Pakistan. The research project aims to inform the design of infrastructure policies by reconciling the need for market integration with the need to shield populations from environmental harm.

Street-scale pollution maps for Ireland

CERC were commissioned by the Irish EPA to provide street-scale modelling of Ireland for 2018 and 2019. The MAQS coupled system was used to link regional scale hourly pollution predictions from the EMEP model with local ADMS-Urban modelling. The UK Centre for Ecology & Hydrology (UK CEH) ran the WRF mesoscale meteorological model and EMEP chemical transport model with 1 km horizontal grid resolution over Ireland. CERC carried out detailed road traffic emissions calculations in EMIT based on traffic flow data supplied by the National Transport Authority (NTA) and Transport Infrastructure Ireland (TII). Gridded emissions from non-traffic sources were obtained from the MapEire inventory.

Selected results from the modelling have been published as part of the Irish Environmental Protection Agency (EPA) report 'Air quality in Ireland 2022'. The full CERC report with high-resolution maps for a wider range of regulated air pollutants is also available. The predicted concentrations were evaluated by comparison with measured concentrations, showing generally good performance for both years at all site types and meeting the FAIRMODE model quality objectives. Modelled concentrations were compared to current Irish air quality standards, with exceedances generally associated with the major road network. Most of Ireland meets the World Health Organisation (WHO) guideline for annual average NO₂ concentrations, with exceedences in urban areas, while a substantial proportion of Ireland does not meet the lowest guideline for annual average PM_2.5 concentrations.

Street canyon effects on dispersion were included in major urban areas. Three major road tunnels were also included in the modelling using the ADMS-Urban tunnels module, with high concentrations noticeable around the portals of the Dublin Port tunnel. The model output is at hourly temporal resolution and irregular spatial resolution. The MAQS PostProcessor utility was used to calculate annual average and high percentiles of hourly concentrations on regular grids for plotting, at 20 m resolution for whole country maps and 5 m resolution for individual cities.

The 2019 mapped concentrations were uploaded to the recent FAIRMODE composite mapping exercise, which combines and assesses modelling results for different parts of Europe. Preliminary results from this exercise were presented in October 2023, with CERC's modelling results showing good performance in the 'high resolution, unassimilated' category. Presentations describing the Irish emissions inventory development and coupled system modelling were given by CERC at the 2023 ADMS-Urban and ADMS-Roads User Group Meeting.

MAQS-Health – A Multi-Model Air Quality System for Health Research

This ambitious SPF Clean Air project, led by CERC, developed a world-leading coupled air quality modelling system spanning national to urban street scales and accounting for physical and chemical processes at all relevant temporal and spatial scales: from thousands of kilometres to metres; and from seconds to days or weeks. The interactive map shows example output from the system, creating using data sources including Defra background mapped air pollutant concentration data, DUKEMS major road emissions data, and UK CEH WRF meteorological data.

The system is flexible, linking the most advanced regional chemical transport models available, including CMAQ, CAMx, EMEP, AQUM/UKCA and WRF-CHEM, to a new street-scale dispersion model, ADMS-Local, and to CERC's widely used ADMS-Urban model. ADMS-Local is computationally efficient, calculates gradients in pollutant concentrations at street-scale resolution including allowance for chemical reactions relevant at local scales, and accounts for the impacts of complex urban morphology, including street canyons, on flow and dispersion. The system's verification module enables validation of predictions against measurements even where there are large gradients in concentration (as often found in urban environments), which is not possible with grid based regional models. The system predictions are available at a wide range of spatial and temporal resolutions, enabling personal exposure and population health impact modelling using a range of metrics at national, city, neighbourhood and local scales. Researchers using the system are able to assess a wide range of national and local policy measures, such as Clean Air Zones and reduced ammonia emissions from farming, and also investigate health inequalities.

The project team was led by CERC, and brought together our experts in software development and application of local dispersion models (ADMS) with regional modelling experts from the Universities of Edinburgh, Birmingham and Lancaster and the UK Met Office, who trialled the system across different regions of the UK. The project team worked closely with the Met Office, and liaised with government, academic and commercial stakeholders throughout the project. The coupled system and ADMS-Local are available for research projects. Please do contact us to discuss your use of the system.

PRAISE-HK health exposure forecasting for Hong Kong

CERC were partners in the ground-breaking 5-year Personalised Real-time Air quality Information System for Exposure – Hong Kong (PRAISE-HK) project to develop a real-time, regional-to-local scale air quality forecasting system for Hong Kong. The PRAISE-HK app is now available and provides GPS-based personal exposure information down to individual street level. This smart city project was led by the Hong Kong University of Science and Technology (HKUST) with contributions from a number of other Hong Kong partners and CERC. The project was funded by the HSBC 150^th anniversary charity programme.

The PRAISE-HK system uses MAQS, with ADMS-Urban coupled to CMAQ, with AI used to calibrate the model output in line with available air pollution measurement information (schematic indicates PRAISE-HK structure). The app helps the public answer questions such as:

• What is the air quality currently like? What will it be like over the next 2 days?
• Which streets around my home and office are the least polluted? And the most?
• What is the difference in my pollution exposure along different commuting routes?
• What is my overall personal exposure?

Details of the system can be found in this brochure.

Air Pollution Monitoring and High Resolution Early Warning Platform for Guangdong

China's Pearl River Delta agglomeration in Guangdong is the largest urban area in the world. Despite significant investment into improving the environment, the magnitude of the problems faced frequently results in hazardous levels of air pollution.

This project brought together UK and Chinese air quality experts to demonstrate the feasibility of a street level resolution air quality forecasting system for dissemination of both real time and forecast air quality, together with high pollution alerts via an integrated smart platform. The project coupled the WRF/CMAQ regional models with the ADMS-Urban local model using MAQS. It enabled the development and testing of air pollution control strategies both for short-term episodes and for longer term improvement. The system was tested and optimised using air quality measurement data from reference monitors, in addition to a number of innovative low cost, small sensors deployed as part of the project.

This 24 month project was led by CERC and the Guangzhou HKUST FYT Research Institute, and was funded by Innovate UK and the Guangdong Science and Technology Cooperation Centre. Key project outcomes included an assessment of the impact of implementing regional and local traffic and industrial source pollution mitigation scenarios on a range of toxic air pollutants, including ozone. The study concluded that the ozone formation regime in Guangzhou is VOC-limited and the traffic sector is of paramount importance for controlling NO_x and ozone. Also, investigation of the frequent summer O₃ episodes emphasized the value of more stringent VOC controls in the region, particularly for the industrial sector; results have been published. The figure shows simulated high-resolution spatial maps of ozone concentration (µg/m³) for the Guangzhou city model domain at 14:00, 10 May 2019 generated by the MAQS system model for (a) Base case, (b) Half-traffic control scenario, (c) Half-industry VOC control scenario, and (d) Both-control scenarios.

Coupling Urban and Regional processes: Effects on Air Quality (CureAir)

CERC collaborated with the Universities of Edinburgh and Leeds and the UK Centre for Ecology and Hydrology on the NERC-funded CureAir project which investigated regional and local effects on urban air quality. CERC contributed to a coupled EMEP4UK and ADMS-Urban model for London, with MAQS (formerly ADMS-Urban RML) developed to send ADMS-Urban runs to the ARCHER high-performance computing system. Results were published in Hood et al. (2018).

Working in collaboration with the University of Leeds, the ADMS-Urban GRS chemistry scheme was evaluated in comparison with the Master Chemical Mechanism. CERC also extended the ADMS-Urban chemistry scheme to include some effects of HONO and Isoprene. Work also involved evaluation of the coupled model results and investigation of the effects on air quality of the urban heat island temperature predicted by the ADMS-Urban Temperature and Humidity model under current and future climate scenarios.

The project generated a London urban canopy flow dataset for use with the Urban Canopy Flow module in ADMS, ADMS-Roads and ADMS-Urban, published in Jackson et al. (2016). This module accounts for the effects of urban buildings on local air flow at neighbourhood scales, calculating a spatially varying flow field due to variations in building density and geometry.