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Biogenic emission algorithms predict that oak forests account for ∼ 70 % of the total European isoprene budget. Yet the isoprene emission potentials (IEPs) that underpin these model estimates are calculated from a very limited number of leaf-level observations and hence are highly uncertain. Increasingly, micrometeorological techniques such as eddy covariance are used to measure whole-canopy fluxes directly, from which isoprene emission potentials can be calculated. Here, we review five observational datasets of isoprene fluxes from a range of oak forests in the UK, Italy and France. We outline procedures to correct the measured net fluxes for losses from deposition and chemical flux divergence, which were found to be on the order of 5–8 and 4–5 %, respectively. The corrected observational data were used to derive isoprene emission potentials at each site in a two-step process. Firstly, six commonly used emission algorithms were inverted to back out time series of isoprene emission potential, and then an “average” isoprene emission potential was calculated for each site with an associated uncertainty. We used these data to assess how the derived emission potentials change depending upon the specific emission algorithm used and, importantly, on the particular approach adopted to derive an average site-specific emission potential. Our results show that isoprene emission potentials can vary by up to a factor of 4 depending on the specific algorithm used and whether or not it is used in a “big-leaf” or “canopy environment (CE) model” format. When using the same algorithm, the calculated average isoprene emission potential was found to vary by as much as 34 % depending on how the average was derived. Using a consistent approach with version 2.1 of the Model for Emissions of Gases and Aerosols from Nature (MEGAN), we derive new ecosystem-scale isoprene emission potentials for the five measurement sites: Alice Holt, UK (10 500 ± 2500 µg m−2 h−1); Bosco Fontana, Italy (1610

The report outlines the bespoke monitoring conducted for the validation of the SCAIL tool in order to better assess that the tool provides realistic yet conservative results. Two farm sites were selected for the validation monitoring. The study collected data for odour, ammonia and airborne particulate data as well as recording on-site meteorological information. In conclusion the SCAIL-Agriculture model was found to broadly meet recognised acceptability criteria for the prediction of ammonia, PM10 and odour concentration arising from farm buildings. There are however a number of areas where further research could clearly improve the assessment of agricultural sources.

A sandwich placement report.