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Food systems can negatively impact health outcomes through unhealthy diets and indirectly through ammonia emissions originating from agricultural production, which contribute to air pollution and consequently cardiovascular and respiratory health outcomes. In the UK, ammonia emissions from agriculture have not declined in the same way as other air pollutants in recent years. We applied a novel integrated modelling framework to assess the health impacts from six ammonia reduction scenarios to 2030: two agriculture scenarios - a "Current trends" scenario projecting current mitigation measures to reflect a low ambition future, and "High ambition mitigation" based on measures included in the Climate Change Committee's Balanced Pathway to Net Zero; three dietary scenarios - a "Business as usual" based on past trajectories, "Fiscal" applying 20% tax on meat and dairy and 20% subsidy on fruit and vegetables, and "Innovation" applying a 30% switch to plant-based alternatives; one combination of "High ambition mitigation" and "Innovation". Compared to "Current trends", the "High ambition mitigation" scenario would result in a reduction in premature mortality of 13,000, increase life years by 90,000 and reduce incidence of respiratory diseases by 270,000 cases over a 30 year period. Compared to Business as Usual, the dietary scenarios would reduce the number of premature deaths by 65,000 and 550,000-600,000 life years gained over 30 years, with most of the benefits gained by reducing ischemic heart disease (incidence reduction: 190,000). The "High ambition combination" would lead to 67,000 deaths averted, 536,000 incidence reductions and 650,000 life-years gained. For all scenarios, older age groups and those living in lower income households would experience the greatest benefits, because of higher underlying mortality rates or higher levels of risk factors. Our study shows that combining mitigation policies targeting agricultural production systems with diet-related policies would lead to significant reductions in emissions and improvement in health outcomes., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024. Published by Elsevier Inc.)

The potential to capture additional air pollutants by introducing more vegetation or changing existing short vegetation to woodland on first sight provides an attractive route for lowering urban pollution. Here, an atmospheric chemistry and transport model was run with a range of landcover scenarios to quantify pollutant removal by the existing total UK vegetation as well as the UK urban vegetation and to quantify the effect of large-scale urban tree planting on urban air pollution. UK vegetation as a whole reduces area (population)-weighted concentrations significantly, by 10% (9%) for PM 2.5 , 30% (22%) for SO 2 , 24% (19%) for NH 3 and 15% (13%) for O 3 , compared with a desert scenario. By contrast, urban vegetation reduces average urban PM 2.5 by only approximately 1%. Even large-scale conversion of half of existing open urban greenspace to forest would lower urban PM 2.5 by only another 1%, suggesting that the effect on air quality needs to be considered in the context of the wider benefits of urban tree planting, e.g. on physical and mental health. The net benefits of UK vegetation for NO 2 are small, and urban tree planting is even forecast to increase urban NO 2 and NO x concentrations, due to the chemical interaction with changes in BVOC emissions and O 3 , but the details depend on tree species selection. By extrapolation, green infrastructure projects focusing on non-greenspace (roadside trees, green walls, roof-top gardens) would have to be implemented at very large scales to match this effect. Downscaling of the results to micro-interventions solely aimed at pollutant removal suggests that their impact is too limited for their cost-benefit analysis to compare favourably with emission abatement measures. Urban vegetation planting is less effective for lowering pollution than measures to reduce emissions at source. The results highlight interactions that cannot be captured if benefits are quantified via deposition models using prescribed concentrations, and emission damage costs. This article is part of a discussion meeting issue 'Air quality, past present and future'.

Background: In light of the coronavirus disease 2019 (COVID-19) pandemic, cancer centres in the United Kingdom and Europe re-organised their services at an unprecedented pace, and many patients with cancer have had their treatments severely disrupted. Patients with cancer were considered at high risk on sparse evidence, and despite a small number of emerging observational studies, the true incidence and impact of COVID-19 in the 'at-risk' population of patients with cancer is yet to be defined., Methods: Epidemiological and clinical data were collected prospectively for patients attending the Royal Marsden Hospital and three network hospitals between March 1st and April 30th 2020 that were confirmed to have Severe acute respiratory syndrome coronavirus 2 (SARS-CoV2) infection. Significance of clinical and pathological characteristics was assessed using the Fisher's exact test and Wilcoxon rank sum test, whilst univariate and multivariate logistic regression models were used to further assess risk. The number of patients attending in March/April 2020 for face-to-face attendances was also extracted., Findings: During the 2-month study period, 867 of 13,489 (6.4%) patients met the criteria leading to swab testing. Of the total at-risk population, only 113 of 13,489 (0.84%) were swab positive, 101 of 13,489 (0.75%) required hospital admission and 29 of 13,489 (0.21%) died of COVID-19. Of the patients that attended the hospital to receive cytotoxic chemotherapy alone or in combination with other therapy, 59 of 2001 (2.9%) were admitted to the hospital for COVID-19-related issues and 20 of 2001 (1%) died. Of the patients that collected targeted treatments, 16 of 1126 (1.4%) were admitted and 1 of 1126 (0.1%) died. Of the 11 patients that had received radiotherapy, 6 of 1042 (0.6%) required inpatient admission and 2 of 1042 (0.2%) died., Interpretations: Administration of systemic anticancer therapy appears to be associated with a modest risk of severe COVID-19 infection. Based on this snapshot taken as the first wave of COVID-19 hit our practice, we conclude that continuation of active cancer treatment, even in the palliative setting, is appropriate., Competing Interests: Conflict of interest statement R.J. reports receiving grants/research support from MSD and GSK and consultation fees from Adaptimmune, Athenex, Blueprint, Clinigen, Eisai, Epizyme, Daichii, Deciphera, Immunedesign, Lilly, Merck, Pharmamar and UptoDate, outside the submitted work. S.S. reports receiving grants and personal fees from Roche, outside the submitted work. All other authors declare no competing interests., (Copyright © 2020 The Authors. Published by Elsevier Ltd.. All rights reserved.)

Traditional approaches of quantifying population-level exposure to air pollution assume that concentrations of air pollutants at the residential address of the study population are representative for overall exposure. This introduces potential bias in the quantification of human health effects. Our study combines new UK Census data comprising information on workday population densities, with high spatio-temporal resolution air pollution concentration fields from the WRF-EMEP4UK atmospheric chemistry transport model, to derive more realistic estimates of population exposure to NO 2 , PM 2.5 and O 3 . We explicitly allocated workday exposures for weekdays between 8:00 am and 6:00 pm. Our analyses covered all of the UK at 1 km spatial resolution. Taking workday location into account had the most pronounced impact on potential exposure to NO 2 , with an estimated 0.3 μg m -3 (equivalent to 2%) increase in population-weighted annual exposure to NO 2 across the whole UK population. Population-weighted exposure to PM 2.5 and O 3 increased and decreased by 0.3%, respectively, reflecting the different atmospheric processes contributing to the spatio-temporal distributions of these pollutants. We also illustrate how our modelling approach can be utilised to quantify individual-level exposure variations due to modelled time-activity patterns for a number of virtual individuals living and working in different locations in three example cities. Changes in annual-mean estimates of NO 2 exposure for these individuals were considerably higher than for the total UK population average when including their workday location. Conducting model-based evaluations as described here may contribute to improving representativeness in studies that use small, portable, automatic sensors to estimate personal exposure to air pollution., (Copyright © 2018 The Authors. Published by Elsevier Ltd.. All rights reserved.)