Integrated Assessment Modelling of Future Air Quality in the UK to 2050, and Synergies with Net Zero Strategies

Abstract

Integrated assessment modelling (IAM) has been successfully used in the development of international agreements to reduce transboundary pollution in Europe, based on the GAINS model of IIASA. At a national level in the UK a similar approach has been taken with the UK Integrated Assessment Model, UKIAM, superimposing pollution abatement measures and behavioural change on energy projections designed to meet targets set for reduction of greenhouse gas emissions, and allowing for natural and imported contributions from other countries and shipping. This paper describes how UKIAM has been used in development of proposed targets for reduction of fine particulate PM2.5 in the Environment Act, exploring scenarios encompassing different levels of ambition up to 2050 with associated health and other environmental benefits. There are two PM2.5 targets, an annual mean concentration target setting a maximum concentration to be reached by a future year, and a population exposure reduction target with benefits for health across the whole population. The work goes further, to also demonstrate links to social deprivation. There is a strong connection between climate measures aimed at reducing net GHG emissions to zero by 2050 and future air quality, which may be positive or negative, as illustrated by sectoral studies for road transport where electrification of the fleet needs to match the evolution of energy production, and for domestic heating where use of wood for heating is an air quality issue. UKIAM has been validated against air pollution measurements and other modelling, but there are many uncertainties including future energy projections. New work is beginning to link UKIAM directly with the TIMES model addressing future energy projections, to explore different uptake scenarios for hydrogen production and use with respect to air quality.

Integrated Assessment Modelling of Future Air Quality in the UK to 2050 and Synergies with Net-Zero Strategies

“…These clearly show the improvement over time for each scenario and the reduction not only in areas of red calculated as above 10 µg m −3 but also in the orange area between 9 and 10 µg m −3 and eventually in the yellow area between 8 and 9 µg m −3 . In this context, allowing for model uncertainties [18], the areas in orange are clearly at risk of exceeding 10 µg m −3 ; in more adverse meteorological years, areas in yellow may also be at risk, as noted above. The divergence between scenarios is also clear, with lower concentrations for the speculative scenario, which is the most successful in eliminating these higher concentration bands.…”

“…It should be noted that there are very large uncertainties in PM2.5 emissions from wood burning, as emphasized by [34] and reported elsewhere by [18]. These reflect not only uncertainties in the quantities of wood burned, the type of wood, and whether wet or dry, but also in how it is burned, whether in open grates or stoves with different efficiencies and modes of operation.…”

“…These include non-exhaust emissions from road transport and domestic combustion of wood, which are examined further in Section 4, below. Additional uncertainties have been reported elsewhere [3,18], notably, emissions from cooking, which are not included in the NAEI but have been found to have a significant impact on exposure to PM 2.5 [19], and the non-linear response of SIA to changes in pre-cursor emissions [9].…”

Reduced-form and complex ACTM modelling for air quality policy development: A model inter-comparison

“…Other contributions from SOA, natural dusts, sea salt and water content represent a substantial addition to total PM 2.5 , amounting to over 3 µg m −3 for parts of England. Clearly, there are large uncertainties (see ApSimon et al, 2020;2022), but it is important that this contribution is considered when calculating total PM 2.5 concentrations.…”

“…The analysis of a large number of scenarios required a model that is fast to run and that could represent total primary and secondary PM 2.5 concentrations spanning atmospheric transport over European to local scales, combining imported contributions from other countries and from international shipping, with more detailed consideration of UK emissions and enhanced concentrations in urban areas. Inevitably, there are many assumptions and uncertainties throughout the process, from quantification of emissions and atmospheric dispersion to impacts on health and the environment, which need to be recognised to inform robust policy decisions (see, for example, ApSimon et al, 2020;2022). To safeguard that model assessments of the scenarios are able to account for variability in meteorological parameters and that potential nonlinear responses to precursor emission changes are picked up, the more complex EMEP4UK model has been used to model selected scenarios to compare with UKIAM, and to investigate sensitivity studies such as the interannual variability in response to meteorological differences between years.…”