Synergies between energy system decarbonisation and air quality in the UK
File(s)
Author(s)
Brighty, Adam
Type
Thesis
Abstract
Energy system decarbonisation strategies are expected to improve UK air quality, yet these two areas have largely been studied in isolation. The limited existing research base has prevented a holistic understanding of the air pollution impacts of future energy strategies. This thesis uses modelling tools such as the UK Integrated Assessment Model to better understand these air pollution and energy system decarbonisation synergies.
The first half of the thesis examines potential policy implications. A screening study assesses emissions and contributions to population-weighted mean concentrations (PWMC), highlighting how decarbonisation pathways influence future air pollution abatement measures. A second study focuses on black carbon, a pollutant with both health and climate impacts, comparing emissions from two inventories based on different methodologies. Biomass combustion emerges as a key concern for future black carbon emissions.
The second half of the thesis starts with a detailed modelling assessment of uncertainty and sensitivity in future scenarios. Results did not show a significant improvement in PM2.5 PWMC contributions from the energy system by 2050 when comparing net zero-only futures to broader energy scenarios with sustained fossil fuel usage. Sensitivity analysis using Sobol indices identifies biomass combustion, hydrogen production, and road transport tyre wear as dominant sources of uncertainty in these PM2.5 projections.
Finally, spatial modelling of UK future energy scenarios reveals similar PM2.5 concentrations across scenarios with varying levels of hydrogen deployment, with most areas falling below 6 µg m-3. Total PM2.5 PWMC drops from 8.73 µg m-3 in 2020 to between 5.98 and 6.41 µg m-3 in 2050. The largest potential hydrogen economy contributes 0.3 µg m-3 to PM2.5 PWMC, indicating minimal risk to air quality targets.
The findings in this thesis underline the importance of integrated modelling and collaboration between air quality and climate communities to achieve the greatest co-benefits for health and the environment.
The first half of the thesis examines potential policy implications. A screening study assesses emissions and contributions to population-weighted mean concentrations (PWMC), highlighting how decarbonisation pathways influence future air pollution abatement measures. A second study focuses on black carbon, a pollutant with both health and climate impacts, comparing emissions from two inventories based on different methodologies. Biomass combustion emerges as a key concern for future black carbon emissions.
The second half of the thesis starts with a detailed modelling assessment of uncertainty and sensitivity in future scenarios. Results did not show a significant improvement in PM2.5 PWMC contributions from the energy system by 2050 when comparing net zero-only futures to broader energy scenarios with sustained fossil fuel usage. Sensitivity analysis using Sobol indices identifies biomass combustion, hydrogen production, and road transport tyre wear as dominant sources of uncertainty in these PM2.5 projections.
Finally, spatial modelling of UK future energy scenarios reveals similar PM2.5 concentrations across scenarios with varying levels of hydrogen deployment, with most areas falling below 6 µg m-3. Total PM2.5 PWMC drops from 8.73 µg m-3 in 2020 to between 5.98 and 6.41 µg m-3 in 2050. The largest potential hydrogen economy contributes 0.3 µg m-3 to PM2.5 PWMC, indicating minimal risk to air quality targets.
The findings in this thesis underline the importance of integrated modelling and collaboration between air quality and climate communities to achieve the greatest co-benefits for health and the environment.
Version
Open Access
Date Issued
2025-07-05
Date Awarded
01/02/2026
License URL
Advisor
ApSimon, Helen
Staffell, Iain
Publisher Department
Centre for Environmental Policy
Publisher Institution
Imperial College London
Qualification Level
Doctoral
Qualification Name
Doctor of Philosophy (PhD)