Developing estimates for the valuation of air pollution removal in ecosystem accounts. Final report for Office of National Statistics

Brief summary: This report develops a natural capital account for air pollution removal by vegetation in the UK, over four time periods: 2007, 2011, 2015 and 203

An adaptable integrated modelling platform to support rapidly evolving agricultural and environmental policy

The utility of integrated models for informing policy has been criticised due to limited stakeholder engagement, model opaqueness, inadequate transparency in assumptions, lack of model flexibility and lack of communication of uncertainty that, together, lead to a lack of trust in model outputs. We address these criticisms by presenting the ERAMMP Integrated Modelling Platform (IMP), developed to support the design of new “business-critical” policies focused on agriculture, land-use and natural resource management. We demonstrate how the long-term (>5 years), iterative, two-way and continuously evolving participatory process led to the co-creation of the IMP with government, building trust and understanding in a complex integrated model. This is supported by a customisable modelling framework that is sufficiently flexible to adapt to changing policy needs in near real-time. We discuss how these attributes have facilitated cultural change within the Welsh Government where the IMP is being actively used to explore, test and iterate policy ideas prior to final policy design and implementation

Ammonia reduction by trees (ART). Priority targeting of treebelts for ammonia mitigation in the landscape

In this study we look at the potential of developing a framework to model targeted areas that are suitable for planting trees in order to recapture NH3 emissions close to source (and typically on agricultural land) and lower N concentration and depositions received by Special Areas of Conservation (SACs) and SSSIs

Scenario modelling - spatial targeting of ammonia mitigation measures in Northern Ireland

This report describes the scenario modelling undertaken to test the potential impact of bundles of ammonia (NH3) mitigation measures on atmospheric emissions, concentrations and deposition as well as effects on sensitive vegetation, and, in particular, on designated sites (SACs, ASSIs). The scenarios tested both Northern Ireland-wide and spatially targeted options near designated sites. Ammonia is very reactive and effects are known to occur locally, close to emission sources, and spatial targeting has previously been shown in UK studies to be more cost-effective per unit of emission reduction than country-wide measures where reductions are spread more thinly over a much larger area (i.e. same overall emission reduction)

Quantifying and valuing the role of UK vegetation in the removal of particulate matter

Air pollution presents a major risk to human health, resulting in premature deaths and reduced quality of life. Vegetation can play a role in reducing concentrations of air pollutants, but estimates of the service that vegetation provides are highly variable. The majority of methods used to calculate pollution removal are driven with static concentrations and therefore ignore the feedback of removal on concentrations, and interactions with wet deposition processes and between compounds. In this study we applied an atmospheric chemistry and transport model (EMEP4UK) to calculate the amount of pollutant removal in the UK by current vegetation for PM2.5, but also gaseous pollutants (NO2, NH3, SO2, O3) by comparing a model run with current landcover to a baseline scenario in which vegetation was replaced by bare soil. From these data we calculated the health benefits from the changes in pollutant concentrations (i.e. change in exposure) induced by the additional pollution removal by the vegetation. Results show that current UK vegetation as a whole reduces concentrations of PM2.5 by around 10%, far greater than in previous studies. The economic value of the health benefits are substantial: £1 billion in avoided health costs estimated for 2015, resulting from 1900 avoided deaths, 27,000 avoided life years lost, 5,800 fewer respiratory hospital admissions and 1,300 fewer cardiovascular hospital admissions. We also show that the benefits do not always occur in the same location as the pollutant removal. In other words the benefits, defined in terms of reduced pollutant concentrations, are also transported in the atmosphere. Copyright © 2018 by the International Aerosol Conference (IAC)

Life Course Air Pollution Exposure and Cognitive Decline: Modelled Historical Air Pollution Data and the Lothian Birth Cohort 1936

Background: Air pollution has been consistently linked with dementia and cognitive decline. However, it is unclear whether risk is accumulated through long-term exposure or whether there are sensitive/critical periods. A key barrier to clarifying this relationship is the dearth of historical air pollution data. Objective: To demonstrate the feasibility of modelling historical air pollution data and using them in epidemiological models. Methods: Using the EMEP4UK atmospheric chemistry transport model, we modelled historical fine particulate matter (PM2.5) concentrations for the years 1935, 1950, 1970, 1980, and 1990 and combined these with contemporary modelled data from 2001 to estimate life course exposure in 572 participants in the Lothian Birth Cohort 1936 with lifetime residential history recorded. Linear regression and latent growth models were constructed using cognitive ability (IQ) measured by the Moray House Test at the ages of 11, 70, 76, and 79 years to explore the effects of historical air pollution exposure. Covariates included sex, IQ at age 11 years, social class, and smoking. Results: Higher air pollution modelled for 1935 (when participants would have been in utero) was associated with worse change in IQ from age 11-70 years (β=-0.006, SE=0.002, P=0.03) but not cognitive trajectories from age 70-79 years (P>0.05). There was no support for other critical/sensitive periods of exposure or an accumulation of risk (all P>0.05). Conclusions: The life course paradigm is essential in understanding cognitive decline and this is the first study to examine life course air pollution exposure in relation to cognitive health