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

Simulation models can be valuable tools in supporting development of air pollution policy. However, exploration of future scenarios depends on reliable and robust modelling to provide confidence in outcomes which cannot be tested against measurements. Here we focus on the UK Integrated Assessment Model, a fast reduced-form model with a purpose to support policy development with modelling of multiple alternative future scenarios, and the EMEP4UK model which is a complex Eulerian Atmospheric Chemistry Transport Model requiring significant computing resources. The EMEP4UK model has been used to model selected core scenarios to compare with UKIAM, and to investigate sensitivity studies such as the interannual variability in response to meteorological differences between years. This model intercomparison addresses total PM2.5, primary PM2.5 and Secondary Inorganic Aerosol concentrations for a baseline of 2018 and selected scenarios for projections to 2040. This work has confirmed the robustness of the UK Integrated Assessment Model for assessing alternative futures through a direct comparison with EMEP4UK. Both models have shown good agreement with measurements, and EMEP4UK shows an ability to replicate past trends. These comparisons highlight how a combination of reduced-form modelling (UKIAM) and complex chemical transport modelling (EMEP4UK) can be effectively used in support of air pollution policy development, informing understanding of projected futures in the context of emerging evidence and uncertainties.

An evaluation of the risk of airborne transmission of COVID-19 on an inter-city train carriage.

Experiments were conducted in an UK inter-city train carriage with the aim of evaluating the risk of infection to the SARS-CoV-2 virus via airborne transmission. The experiments included in-service CO2 measurements and the measurement of salt aerosol concentrations released within the carriage. Computational fluid dynamics simulations of the carriage airflow were also used to visualise the airflow patterns, and the efficacy of the HVAC filter material was tested in a laboratory. Assuming an infectious person is present, the risk of infection for a 1-h train journey was estimated to be 6 times lower than for a full day in a well-ventilated office, or 10-12 times lower than a full day in a poorly ventilated office. While the absolute risk for a typical journey is likely low, in the case where a particularly infectious individual is on-board, there is the potential for a number of secondary infections to occur during a 1-h journey. Every effort should therefore be made to minimize the risk of airborne infection within these carriages. Recommendations are also given for the use of CO2 sensors for the evaluation of the risk of airborne transmission on train carriages.

Modeling disease transmission in a train carriage using a simple 1D-model.

Understanding airborne infectious disease transmission on public transport is essential to reducing the risk of infection of passengers and crew members. We propose a new one-dimensional (1D) model that predicts the longitudinal dispersion of airborne contaminants and the risk of disease transmission inside a railway carriage. We compare the results of this 1D-model to the predictions of a model that assumes the carriage is fully mixed. The 1D-model is validated using measurements of controlled carbon-dioxide experiments conducted in a full-scale railway carriage. We use our results to provide novel insights into the impact of various strategies to reduce the risk of airborne transmission on public transport.

The UK Integrated Assessment Model for source apportionment and air pollution policy applications to PM2.5.

Source apportionment and the effect of reducing individual sources is important input for the development of strategies to address air pollution. The UK Integrated Assessment Model, UKIAM, has been developed for this purpose as a flexible framework, combining information from different atmospheric dispersion models to cover different pollutant contributions, and span the range from European to local scale. In this paper we describe the UKIAM as developed for SO2, NOx, NH3, PM2.5 and VOCs. We illustrate its versatility and application with assessment of current PM2.5 concentrations and exposure of the UK population, as a case-study that has been used as the starting point to investigate potential improvement towards attainment of the WHO guideline of 10 µg/m3.

The ventilation of buildings and other mitigating measures for COVID-19: a focus on wintertime.

The year 2020 has seen the emergence of a global pandemic as a result of the disease COVID-19. This report reviews knowledge of the transmission of COVID-19 indoors, examines the evidence for mitigating measures, and considers the implications for wintertime with a focus on ventilation.

A systematic review of the leaf traits considered to contribute to removal of airborne particulate matter pollution in urban areas.

Global urban planning has promoted green infrastructure (GI) such as street trees, shrubs or other greenspace in order to mitigate air pollution. Although considerable attention has been paid to understanding particulate matter (PM) deposition on GI, there has been little focus on identifying which leaf traits might maximise airborne PM removal. This paper examines existing literature to synthesize the state of knowledge on leaf traits most relevant to PM removal. We systematically reviewed measurement studies that evaluated particulate matter accumulated on leaves on street trees, shrubs green roofs, and green walls, for a variety of leaf traits. Our final selection included 62 papers, most from field studies and a handful from wind tunnel studies. The following were variously promoted as useful traits: coniferous needle leaves; small, rough and textured broadleaves; lanceolate and ovate shapes; waxy coatings, and high-density trichomes. Consideration of these leaf traits, many of which are also associated with drought tolerance, may help to maximise PM capture. Although effective leaf traits were identified, there is no strong or consistent evidence to identify which is the most influential leaf trait in capturing PM. The diversity in sampling methods, wide comparison groups and lack of background PM concentration measures in many studies limited our ability to synthesize results. We found that several ancillary factors contribute to variations in the accumulation of PM on leaves, thus cannot recommend that selection of urban planting species be based primarily on leaf traits. Further research into the vegetation structural features and standardization of the method to measure PM on leaves is needed.