Improving the low-wind performance of the AERMOD atmospheric dispersion model for predicting short-range impacts of livestock ammonia emissions.

Short-range impacts to sensitive ecosystems as a result of ammonia emitted by livestock farms are often assessed using atmospheric dispersion modelling systems such as AERMOD. These assessments evaluate mean annual atmospheric concentrations of ammonia and nitrogen deposition rates at the ecosystem location for comparison with ecosystem damage thresholds. However, predictions of mean annual atmospheric concentrations can be dominated by periods of stable night-time conditions, which can contribute significantly to mean concentrations. AERMOD has been demonstrated to overestimate concentrations in certain stable low-wind conditions and so the model could potentially overestimate the short-range impacts of livestock ammonia emissions. This paper tests several modifications to the parameterisation of AERMOD (v12345) that aim to improve model predictions in low-wind conditions. The modifications are first described and then are applied to three pig farm case studies in the USA, Denmark and Spain to assess whether the modifications improve long-term mean ammonia concentration predictions through improved model performance. For these three case studies, most of the modifications tested improved model performance as a result of reducing the long-term mean concentration predictions, with the largest effect for low- or ground-level sources (e.g. slurry lagoons or naturally ventilated housing)

Suitability and uncertainty of two models for the simulation of ammonia dispersion from a pig farm located in an area with frequent calm conditions

We used two atmospheric dispersion models (ADMS and AERMOD) to simulate the short-range dispersion of ammonia emitted by two pig farms to assess their suitability in situations with frequent calm meteorological conditions. Simulations were carried out both using constant and temporally-varying emission rates to evaluate the effect on the model predictions. Monthly and annual mean concentrations predicted by the models at locations within one kilometre of the farms were compared with measured values. AERMOD predicted higher concentrations than ADMS (by a factor of 6–7, on average) and predicted the atmospheric concentrations more accurately for both the monthly and annual simulations. The differences between the concentrations predicted by the two models were mainly the result of different calm wind speed thresholds used by the models. The use of temporally-varying emission rates improved the performance of both models for the monthly and annual simulations with respect to the constant emission simulations. A Monte Carlo uncertainty analysis based on the inputs judged to be the most uncertain for the selected case study estimated a prediction uncertainty of ± a factor of two for both models with most of this due to uncertainty in emission rates

Modelling the contribution of SO2 and NOx emissions from international shipping to sulphur and oxidised nitrogen deposition in the United Kingdom

A statistical Lagrangian atmospheric transport model was used to generate annual maps of deposition of sulphur and nitrogen for the United Kingdom at a 5 x 5 km2 resolution for the year 2005 and to assess the contribution attributed to emissions of SO2 and NOx from international shipping. A future emissions scenario for the year 2020 was used to investigate changes in the relative contribution of shipping emissions. The results show that, if shipping emissions are assumed to increase at a rate of 2.5% per year, their relative contribution to total sulphur and oxidised nitrogen deposition are expected to increase from 15% and 12% respectively to 37% and 28% between 2005 and 2020. Enforcement of the International Maritime Organisation (IMO) agreement to reduce the sulphur content in marine fuel to 0.5% was estimated to result in a 30% reduction in total sulphur deposition to the UK for the year 2020 compared to a business as usual scenario, with the result that the relative contribution from shipping to sulphur deposition in the UK would be reduced to 9% of the tota

A climate-dependent global model of ammonia emissions from chicken farming

Ammonia (NH3) has significant impacts on the environment, which can influence climate and air quality and cause acidification and eutrophication in terrestrial and aquatic ecosystems. Agricultural activities are the main sources of NH3 emissions globally. Emissions of NH3 from chicken farming are highly dependent on climate, affecting their environmental footprint and impact. In order to investigate the effects of meteorological factors and to quantify how climate change affects these emissions, a process-based model, AMmonia–CLIMate–Poultry (AMCLIM–Poultry), has been developed to simulate and predict temporal variations in NH3 emissions from poultry excretion, here focusing on chicken farms and manure spreading. The model simulates the decomposition of uric acid to form total ammoniacal nitrogen, which then partitions into gaseous NH3 that is released to the atmosphere at an hourly to daily resolution. Ammonia emissions are simulated by calculating nitrogen and moisture budgets within poultry excretion, including a dependence on environmental variables. By applying the model with global data for livestock, agricultural practice and meteorology, we calculate NH3 emissions from chicken farming on a global scale (0.5∘ resolution). Based on 2010 data, the AMCLIM–Poultry model estimates NH3 emissions from global chicken farming of 5.5 ± 1.2 Tg N yr−1, about 13 % of the agriculture-derived NH3 emissions. Taking account of partial control of the ambient environment for housed chicken (layers and broilers), the fraction of excreted nitrogen emitted as NH3 is found to be up to 3 times larger in humid tropical locations than in cold or dry locations. For spreading of manure to land, rain becomes a critical driver affecting emissions in addition to temperature, with the emission fraction being up to 5 times larger in the semi-dry tropics than in cold, wet climates. The results highlight the importance of incorporating climate effects into global NH3 emissions inventories for agricultural sources. The model shows increased emissions under warm and wet conditions, indicating that climate change will tend to increase NH3 emissions over the coming century

Effect of mattress deflection on CPR quality assessment for older children and adolescents

Appropriate chest compression (CC) depth is associated with improved CPR outcome. CCs provided in hospital are often conducted on a compliant mattress. The objective was to quantify the effect of mattress compression on the assessment of CPR quality in children. Methods: A force and deflection sensor (FDS) was used during CPR in the Pediatric Intensive Care Unit and Emergency Department of a children's hospital. The sensor was interposed between the chest of the patient and hands of the rescuer and measured CC depth. Following CPR event, each event was reconstructed with a manikin and an identical mattress/backboard/patient configuration. CCs were performed using FDS on the sternum and a reference accelerometer attached to the spine of the manikin, providing a means to Calculate the mattress deflection. Results: Twelve CPR events with 14,487 CC (11 patients, median age 14.9 years) were recorded and reconstructed: 9 on ICU beds (9296 CC), 3 on stretchers (5191 CC). Measured mean CC depth during CPR was 47 +/- 8 mm on ICU beds, and 45 +/- 7 mm on stretcher beds with overestimation of 13 +/- 4 mm and 4 +/- 1 mm, respectively, due to mattress compression. After adjusting for this, the proportion of CC that met the CPR guidelines decreased from 88.4 to 31.8% on ICU beds (p < 0.001), and 86.3 to 64.7% on stretcher (p < 0.001 The proportion of appropriate depth CC was significantly smaller on ICU beds (p < 0.001). Conclusion: CC conducted on a non-rigid surface may not be deep enough. FDS may overestimate CC depth by 28% on ICU beds, and 10% on stretcher beds

An intercomparison of models used to simulate the short range atmospheric dispersion and deposition of agricultural ammonia emissions

Ammonia (NH3) emitted into the atmosphere from agricultural sources can have an impact on nearby sensitive ecosystems either through elevated ambient concentrations or dry/wet deposition to vegetation and soil surfaces. Environmental impact assessments are often carried out using short-range atmospheric dispersion models to estimate mean annual atmospheric concentrations and total annual deposition of NH3 at the ecosystem location. A range of different atmospheric dispersion models are used for these assessments depending on the location and experience of the assessors and have not, until now, been compared for these types of assessments. This poster compares and validates concentration predictions of four commonly used models (ADMS v4.11, AERMOD v070262, LADD3 and OPS-st4,5) for dispersion from agricultural sources using hypothetical and real case studie

The Connectedness of Ivory Towers and Inner Cities - Conversations About Us and Them

Also PCMA Working Paper #46.http://deepblue.lib.umich.edu/bitstream/2027.42/51291/1/527.pd

Mapping portuguese Natura 2000 sites in risk of biodiversity change caused by atmospheric nitrogen pollution

In this paper, we assess and map the risk that atmospheric nitrogen (atN) pollution poses to biodiversity in Natura 2000 sites in mainland Portugal. We first review the ecological impacts of atN pollution on terrestrial ecosystems, focusing on the biodiversity of Natura 2000 sites. These nature protection sites, especially those located within the Mediterranean Basin, are under-characterized regarding the risk posed by atN pollution. We focus on ammonia (NH ) because this N form is mostly associated with agriculture, which co-occurs at or in the immediate vicinity of most areas of conservation interest in Portugal. We produce a risk map integrating NH emissions and the susceptibility of Natura 2000 sites to atN pollution, ranking habitat sensitivity to atN pollution using expert knowledge from a panel of Portuguese ecological and habitat experts. Peats, mires, bogs, and similar acidic and oligotrophic habitats within Natura 2000 sites (most located in the northern mountains) were assessed to have the highest relative risk of biodiversity change due to atN pollution, whereas Natura 2000 sites in the Atlantic and Mediterranean climate zone (coastal, tidal, and scrubland habitats) were deemed the least sensitive. Overall, results allowed us to rank all Natura 2000 sites in mainland Portugal in order of evaluated risk posed by atN pollution. The approach is of great relevance for stakeholders in different countries to help prioritize site protection and to define research priorities. This is especially relevant in countries with a lack of expertise to assess the impacts of nitrogen on biodiversity and can represent an important step up from current knowledge in such countriesinfo:eu-repo/semantics/publishedVersio