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The fishing industry is heavily reliant on the use of fossil fuel and emits large quantities of greenhouse gases and other atmospheric pollutants. Methods used to calculate fishing vessel emissions inventories have traditionally utilised estimates of fuel efficiency per unit of catch. These methods have weaknesses because they do not easily allow temporal and geographical allocation of emissions. A large proportion of fishing and other small commercial vessels are also omitted from global shipping emissions inventories such as the International Maritime Organisation's Greenhouse Gas Studies. This paper demonstrates an activity-based methodology for the production of temporally- and spatially-resolved emissions inventories using data produced by Automatic Identification Systems (AIS). The methodology addresses the issue of how to use AIS data for fleets where not all vessels use AIS technology and how to assign engine load when vessels are towing trawling or dredging gear. The results of this are compared to a fuel-based methodology using publicly available European Commission fisheries data on fuel efficiency and annual catch. The results show relatively good agreement between the two methodologies, with an estimate of 295.7 kilotons of fuel used and 914.4 kilotons of carbon dioxide emitted between May 2012 and May 2013 using the activity-based methodology. Different methods of calculating speed using AIS data are also compared. The results indicate that using the speed data contained directly in the AIS data is preferable to calculating speed from the distance and time interval between consecutive AIS data points. [ABSTRACT FROM AUTHOR]

Elevated surface ozone during heatwaves and recent hot summers raises concerns over the potential for climate change to exacerbate ozone air pollution in the UK. In this paper, we perform a robust statistical analysis of four decades worth of daily maximum 8-h (MDA8) ozone measurements from the UK's Automated Urban and Rural Network. A temperature dependent extreme value model is developed to characterise the magnitude and frequency of extreme ozone events and to determine probabilities for ozone exceeding health thresholds, as defined in the UK's air quality index. Our model is found to describe the tails of the MDA8 ozone distributions well at all 119 monitoring sites considered. For the decade 2010–2019, we estimate that >90% of sites have a 1-year MDA8 ozone return level greater than the 'moderate' ozone threshold of 100 μg/m3. We also find that 33% of sites are currently expected to breach the UK government's national air quality objective that MDA8 ozone should not exceed 100 μg/m3 more than ten times per year. We estimate the present overall probability of MDA8 ozone exceeding 100 μg/m3 on a given day to be between <0.1% and 5.4%, depending on site, with averages of 2.7% (rural) and 1.6% (urban background locations). Our analysis reveals a significant decline over time in the likelihood of the UK experiencing extreme ozone episodes, with 1-year return levels in the 1980s now roughly comparable to 10-year return levels in the present. Similarly, probabilities of MDA8 ozone exceeding 100 μg/m3 have decreased by a factor of ∼2–6 since the 1980s in some locations. However, our results also highlight a strong positive temperature dependence to the risk of ozone exceedances. In consequence, increasingly hot summers due to climate change may offset some of these gains. • Extreme value analysis used to quantify probability of UK extreme ozone episodes. • Considerable decline in likelihood of UK experiencing extreme ozone episodes. • Reduced probability of ozone exceeding 'moderate' health threshold (100 μg/m3). • Non-linear increase in risk of extreme ozone with unusually high temperatures. [ABSTRACT FROM AUTHOR]

Abstract: The Ozone Source–Receptor Model (OSRM) is a Lagrangian trajectory model developed to describe photochemical ozone production in the UK. The OSRM builds on existing boundary layer trajectory models used previously for assisting the development of UK ozone policy, but has a number of notable differences. A novel feature of the OSRM is a surface conversion module to represent the vertical gradient in ozone arising from chemical loss and deposition to the surface. This has significantly improved the performance of the model, especially in urban areas. In this paper, the modelling system is described and its performance against measured ozone concentrations and metrics and other UK ozone models is discussed. The model has been used to calculate future ozone concentrations in the UK and thus to assess a number of possible control measures developed for the UK Air Quality Strategy. [Copyright &y& Elsevier]

CORINAIR atmospheric emission inventories are frequently used input data for air quality models with a domain situated in Europe. In CORINAIR emission inventories, sources are broken down over 11 major source categories. This paper presents spatial surrogates for the disaggregation of CORINAIR atmospheric emission inventories for input of air pollutants and particulate matter to grid or polygon based air quality model domains inside Europe. The basis for the disaggregation model was the CLC2000 land cover data to which statistical weights were added. Weights were population census data for residential emissions, employment statistics for agricultural and industrial area emissions, livestock statistics for ammonia emissions and annual aircraft movements for emissions realized by air transport. Additional road and off-road network information was used to disaggregate emissions realized by traffic. A comparison of top down produced emission estimates with spatially resolved national emission data for The Netherlands and the United Kingdom gave confidence in the present spatial surrogates as a tool for the top down production of atmospheric emission maps. Explained variance at a spatial resolution of 5km was >70% for CO, NMVOC and NO x , >60% for PM10 and almost 50% for SO2. [Copyright &y& Elsevier]