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In 2019 the EU Waste Electrical and Electronic Equipment (WEEE) Directive documented a sizable increase in e-waste collection targets alongside a wider scope of electronic and electrical products covered by the legislation. These changes have significant impact for the UK, as for the past two years UK waste collected has failed to meet the newly adopted set of targets. Understanding the flows and fates of products on and off the market becomes of paramount importance, especially for producer-led organisations who have the responsibility to achieve the targets and cover the operational costs. Historic e-waste estimation methods often assume that one product on the market will equate to one product in the waste stream. In this article, we report on a project commissioned by one of the largest UK producer-led organizations – REPIC Ltd, in search of an explanation of the observed dropin products on the market and WEEE collected, and the relationship between the two. We argue that we should move away from “one product in and one product out” assumption to include wider parameters that are tailored specifically for the UK, including those linked with the state of the market for electronic and electrical products and of the wider economy, examples include inflation-adjusted GDP per capita, consumer confidence index (CCI), inflation indices (CPI or RPI), number of households, wealth distribution etc. We show how this can be achieved by adapting a state-of the-art e-waste estimation model (Waste Over Time) to the UK context and developing it further to include additional drivers.

In 2019 the EU Waste Electrical and Electronic Equipment (WEEE) Directive documented a sizable increase in e-waste collection targets alongside widening the scope of electrical and electronic products covered by the legislation. These changes have significant impact for the UK, where e-waste collection has been below the levels necessary to meet the targets. Understanding the flows and fates of products on and off the market becomes of paramount importance, especially for producer-led organisations who have the responsibility to achieve the targets and cover the operational costs. Historic e-waste estimation methods often assume that one product on the market will equate to one product in the waste stream. In this article, we introduce our research commissioned by one of the largest UK producer-led organisations, REPIC Ltd, to explain the gap in products on the market and WEEE collected, and the relationship between the two. We argue that we should move away from the “one-in-one-out” estimation to include a wider set of parameters that are tailored specifically for the UK, including those linked with the state of the market for electronic and electrical products and a broader range of socioeconomic indicators. We show how this can be achieved by adapting a state-of-the-art e-waste estimation model, Waste Over Time, to the UK context and developing it further to include additional drivers.

We develop a decision-making model that describes optimal protection and recovery strategies for a single economic location affected by radioactive release from the nearby Nuclear Power Plant. The initial period of release and deposition is characterised by high degrees of uncertainty, which is likely to lead to precautionary emergency measures being carried out regardless of the actual dangers to the public, and therefore it is excluded from the optimisation problem. Instead, the analysis is performed on the timescale of weeks, months, years and decades after the accident, implying that the problem is largely deterministic if one disregards long-term economic uncertainties. It is on these longer timescales that economically-driven decisions could be made on whether or not to implement various protection and recovery measures, which include relocation, remediation, repopulation and food banning. Our model allows one to find the joint cost-minimal strategy across the set of measures, providing certain spatial and temporal flexibilities are permitted. Several qualitatively different strategies are identified, including those with no relocation and delayed remediation. Which strategy is optimal depends on the initial radiation levels, the rates and costs of the individual actions, and the preferred economic valuation of the relevant health effects associated with radiation. Our main message is that in many possible settings relocation should be used sparingly and repopulation should be delayed to exploit natural decay of the radioactive elements. These findings could provide useful recommendations to regulators in civil nuclear industry and help devise better policies for implementing emergency response and recovery measures.

Arctic feedbacks accelerate climate change through carbon releases from thawing permafrost and higher solar absorption from reductions in the surface albedo, following loss of sea ice and land snow. Here, we include dynamic emulators of complex physical models in the integrated assessment model PAGE-ICE to explore nonlinear transitions in the Arctic feedbacks and their subsequent impacts on the global climate and economy under the Paris Agreement scenarios. The permafrost feedback is increasingly positive in warmer climates, while the albedo feedback weakens as the ice and snow melt. Combined, these two factors lead to significant increases in the mean discounted economic effect of climate change: +4.0% ($24.8 trillion) under the 1.5 °C scenario, +5.5% ($33.8 trillion) under the 2 °C scenario, and +4.8% ($66.9 trillion) under mitigation levels consistent with the current national pledges. Considering the nonlinear Arctic feedbacks makes the 1.5 °C target marginally more economically attractive than the 2 °C target, although both are statistically equivalent.