Practical considerations for addressing uncertainties in monitoring bulk deposition

The assessment of the deposition of both wet (rain and cloud) and dry sedimenting particles is a prerequisite for estimating element fluxes in ecosystem research. Many nations and institutions operate deposition networks using different types of sampler. However, these samplers have rarely been characterized with respect to their sink properties. Major errors in assessing bulk deposition can result from poor sampling properties and defective sampling strategies. Relevant properties are: sampler geometry and material, in particular the shape of the rim; sink properties for gases and aerosols; and microbial transformations of the collected samples. An adequate number of replicates allows the identification of samples which are contaminated, in particular by bird droppings. The paper discusses physical and chemical properties of the samplers themselves. The dependence of measurement accuracy on the number of replicates and the sampling area exposed is discussed. Recommendations are given for sampling strategies, and for making corrections and substitution of missing data. Recommendations are given for sampling strategies and for making corrections and substitution of missing data

Comparison of models used for national agricultural ammonia emission inventories in Europe: Litter-based manure systems

Six N-flow models, used to calculate national ammonia (NH3) emissions from agriculture in different European countries, were compared using standard data sets. Scenarios for litter-based systems were run separately for beef cattle and for broilers, with three different levels of model standardisation: (a) standardized inputs to all models (FF scenario); (b) standard N excretion, but national values for emission factors (EFs) (FN scenario); (c) national values for N excretion and EFs (NN scenario). Results of the FF scenario for beef cattle produced very similar estimates of total losses of total ammoniacal-N (TAN) (±6% of the mean total), but large differences in NH3 emissions (±24% of the mean). These differences arose from the different approaches to TAN immobilization in litter, other N losses and mineralization in the models. As a result of those differences estimates of TAN available at spreading differed by a factor of almost 3. Results of the FF scenario for broilers produced a range of estimates of total changes in TAN (±9% of the mean total), and larger differences in the estimate of NH3 emissions (±17% of the mean). The different approaches among the models to TAN immobilization, other N losses and mineralization, produced estimates of TAN available at spreading which differed by a factor of almost 1.7. The differences in estimates of NH3 emissions decreased as estimates of immobilization and other N losses increased. Since immobilization and denitrification depend also on the C:N ratio in manure, there would be advantages to include C flows in mass-flow models. This would also provide an integrated model for the estimation of emissions of methane, non-methane VOCs and carbon dioxide. Estimation of these would also enable an estimate of mass loss, calculation of the N and TAN concentrations in litter-based manures and further validation of model output

Comparison of models used for national agricultural ammonia emission inventories in Europe: liquid manure systems

Ammonia (NH3) emissions from agriculture commonly account for >80% of the total NH3 emissions. Accurate agricultural NH3 emission inventories are therefore required for reporting within the framework of the Gothenburg Protocol of the UN Convention on Long-range Transboundary Air Pollution. To allow a co-ordinated implementation of the Protocol, different national inventories should be comparable. A core group of emission inventory experts therefore developed a network and joint programme to achieve a detailed overview of the best inventory techniques currently available and compiled and harmonized the available knowledge on emission factors (EFs) for nitrogen (N)-flow emission calculation models and initiated a new generation of emission inventories. As a first step in summarizing the available knowledge, six N-flow models, used to calculate national NH3 emissions from agriculture in different European countries, were compared using standard datasets. Two scenarios for slurry-based systems were run separately for dairy cattle and for pigs, with three different levels of model standardisation: (a) standardised inputs to all models (FF scenario); (b) standard N excretion, but national values for EFs (FN scenario); (c) national values for N excretion and EFs (NN scenario). Results of the FF scenario showed very good agreement among models, indicating that the underlying N flows of the different models are highly similar. As a result of the different national EFs and N excretion rates, larger differences among the results were observed for the FN and the NN scenarios. Reasons for the differences were primarily attributed to differences in the agricultural practices and climatic factors reflected in the EFs and the N excretion rates. The scientific debate necessary to understand the variation in the results generated awareness and consensus concerning available scientific data and the importance of specific processes not yet included in some models