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- ItemAirborne bacterial emission fluxes from manure-fertilized agricultural soil(Oxford : Wiley-Blackwell, 2020) Thiel, Nadine; Münch, Steffen; Behrens, Wiebke; Junker, Vera; Faust, Matthias; Biniasch, Oliver; Kabelitz, Tina; Siller, Paul; Boedeker, Christian; Schumann, Peter; Roesler, Uwe; Amon, Thomas; Schepanski, Kerstin; Funk, Roger; Nübel, UlrichThis is the first study to quantify the dependence on wind velocity of airborne bacterial emission fluxes from soil. It demonstrates that manure bacteria get aerosolized from fertilized soil more easily than soil bacteria, and it applies bacterial genomic sequencing for the first time to trace environmental faecal contamination back to its source in the chicken barn. We report quantitative, airborne emission fluxes of bacteria during and following the fertilization of agricultural soil with manure from broiler chickens. During the fertilization process, the concentration of airborne bacteria culturable on blood agar medium increased more than 600 000-fold, and 1 m3 of air carried 2.9 × 105 viable enterococci, i.e. indicators of faecal contamination which had been undetectable in background air samples. Trajectory modelling suggested that atmospheric residence times and dispersion pathways were dependent on the time of day at which fertilization was performed. Measurements in a wind tunnel indicated that airborne bacterial emission fluxes from freshly fertilized soil under local climatic conditions on average were 100-fold higher than a previous estimate of average emissions from land. Faecal bacteria collected from soil and dust up to seven weeks after fertilization could be traced to their origins in the poultry barn by genomic sequencing. Comparative analyses of 16S rRNA gene sequences from manure, soil and dust showed that manure bacteria got aerosolized preferably, likely due to their attachment to low-density manure particles. Our data show that fertilization with manure may cause substantial increases of bacterial emissions from agricultural land. After mechanical incorporation of manure into soil, however, the associated risk of airborne infection is low.
- ItemAirflow Characteristics Downwind a Naturally Ventilated Pig Building with a Roofed Outdoor Exercise Yard and Implications on Pollutant Distribution(Basel : MDPI AG, 2020) Yi, Qianying; Janke, David; Thormann, Lars; Zhang, Guoqiang; Amon, Barbara; Hempel, Sabrina; Nosek, Štěpán; Hartung, Eberhard; Amon, ThomasThe application of naturally ventilated pig buildings (NVPBs) with outdoor exercise yards is on the rise mainly due to animal welfare considerations, while the issue of emissions from the buildings to the surrounding environment is important. Since air pollutants are mainly transported by airflow, the knowledge on the airflow characteristics downwind the building is required. The objective of this research was to investigate airflow properties downwind of a NVPB with a roofed outdoor exercise yard for roof slopes of 5°, 15°, and 25°. Air velocities downwind a 1:50 scaled NVPB model were measured using a Laser Doppler Anemometer in a large boundary layer wind tunnel. A region with reduced mean air velocities was found along the downwind side of the building with a distance up to 0.5 m (i.e., 3.8 times building height), in which the emission concentration might be high. Additional air pollutant treatment technologies applied in this region might contribute to emission mitigation effectively. Furthermore, a wake zone with air recirculation was observed in this area. A smaller roof slope (i.e., 5° slope) resulted in a higher and shorter wake zone and thus a shorter air pollutant dispersion distance.
- ItemSupervised Machine Learning to Assess Methane Emissions of a Dairy Building with Natural Ventilation(Basel : MDPI, 2020) Hempel, Sabrina; Adolphs, Julian; Landwehr, Niels; Willink, Dilya; Janke, David; Amon, ThomasA reliable quantification of greenhouse gas emissions is a basis for the development of adequate mitigation measures. Protocols for emission measurements and data analysis approaches to extrapolate to accurate annual emission values are a substantial prerequisite in this context. We systematically analyzed the benefit of supervised machine learning methods to project methane emissions from a naturally ventilated cattle building with a concrete solid floor and manure scraper located in Northern Germany. We took into account approximately 40 weeks of hourly emission measurements and compared model predictions using eight regression approaches, 27 different sampling scenarios and four measures of model accuracy. Data normalization was applied based on median and quartile range. A correlation analysis was performed to evaluate the influence of individual features. This indicated only a very weak linear relation between the methane emission and features that are typically used to predict methane emission values of naturally ventilated barns. It further highlighted the added value of including day-time and squared ambient temperature as features. The error of the predicted emission values was in general below 10%. The results from Gaussian processes, ordinary multilinear regression and neural networks were least robust. More robust results were obtained with multilinear regression with regularization, support vector machines and particularly the ensemble methods gradient boosting and random forest. The latter had the added value to be rather insensitive against the normalization procedure. In the case of multilinear regression, also the removal of not significantly linearly related variables (i.e., keeping only the day-time component) led to robust modeling results. We concluded that measurement protocols with 7 days and six measurement periods can be considered sufficient to model methane emissions from the dairy barn with solid floor with manure scraper, particularly when periods are distributed over the year with a preference for transition periods. Features should be normalized according to median and quartile range and must be carefully selected depending on the modeling approach.
- ItemOpening Size E ects on Airflow Pattern and Airflow Rate of a Naturally Ventilated Dairy Building : A CFD Study(Basel : MDPI, 2020) Saha, Chayan Kumer; Yi, Qianying; Janke, David; Hempel, Sabrina; Amon, Barbara; Amon, ThomasAirflow inside naturally ventilated dairy (NVD) buildings is highly variable and difficult to understand due to the lack of precious measuring techniques with the existing methods. Computational fluid dynamics (CFD) was applied to investigate the effect of different seasonal opening combinations of an NVD building on airflow patterns and airflow rate inside the NVD building as an alternative to full scale and scale model experiments. ANSYS 2019R2 was used for creating model geometry, meshing, and simulation. Eight ventilation opening combinations and 10 different reference air velocities were used for the series of simulation. The data measured in a large boundary layer wind tunnel using a 1:100 scale model of the NVD building was used for CFD model validation. The results show that CFD using standard k-ε turbulence model was capable of simulating airflow in and outside of the NVD building. Airflow patterns were different for different opening scenarios at the same external wind speed, which may affect cow comfort and gaseous emissions. Guiding inlet air by controlling openings may ensure animal comfort and minimize emissions. Non-isothermal and transient simulations of NVD buildings should be carried out for better understanding of airflow patterns.
- ItemFunctional relationship of particulate matter (PM) emissions, animal species, and moisture content during manure application(Amsterdam [u.a.] : Elsevier Science, 2020) Kabelitz, Tina; Ammon, Christian; Funk, Roger; Münch, Steffen; Biniasch, Oliver; Nübel, Ulrich; Thiel, Nadine; Rösler, Uwe; Siller, Paul; Amon, Barbara; Aarnink, André J.A.; Amon, ThomasLivestock manure is recycled to agricultural land as organic fertilizer. Due to the extensive usage of antibiotics in conventional animal farming, antibiotic-resistant bacteria are highly prevalent in feces and manure. The spread of wind-driven particulate matter (PM) with potentially associated harmful bacteria through manure application may pose a threat to environmental and human health. We studied whether PM was aerosolized during the application of solid and dried livestock manure and the functional relationship between PM release, manure dry matter content (DM), treatment and animal species. In parallel, manure and resulting PM were investigated for the survival of pathogenic and antibiotic-resistant bacterial species. The results showed that from manure with a higher DM smaller particles were generated and more PM was emitted. A positive correlation between manure DM and PM aerosolization rate was observed. There was a species-dependent critical dryness level (poultry: 60% DM, pig: 80% DM) where manure began to release PM into the environment. The maximum PM emission potentials were 1 and 3 kg t−1 of applied poultry and pig manure, respectively. Dried manure and resulting PM contained strongly reduced amounts of investigated pathogenic and antibiotic-resistant microorganisms compared to fresh samples. An optimal manure DM regarding low PM emissions and reduced pathogen viability was defined from our results, which was 55–70% DM for poultry manure and 75–85% DM for pig manure. The novel findings of this study increase our detailed understanding and basic knowledge on manure PM emissions and enable optimization of manure management, aiming a manure DM that reduces PM emissions and pathogenic release into the environment.
- ItemOn the feasibility of using open source solvers for the simulation of a turbulent air flow in a dairy barn(Amsterdam [u.a.] : Elsevier, 2020) Janke, David; Caiazzo, Alfonso; Ahmed, Naveed; Alia, Najib; Knoth, Oswald; Moreau, Baptiste; Wilbrandt, Ulrich; Willink, Dilya; Amon, Thomas; John, VolkerTwo transient open source solvers, OpenFOAM and ParMooN, and the commercial solver Ansys Fluent are assessed with respect to the simulation of the turbulent air flow inside and around a dairy barn. For this purpose, data were obtained in an experimental campaign at a 1:100 scaled wind tunnel model. All solvers used different meshes, discretization schemes, and turbulence models. The experimental data and numerical results agree well for time-averaged stream-wise and vertical-wise velocities. In particular, the air exchange was predicted with high accuracy by both open source solvers with relative differences less than 4% and by the commercial solver with a relative difference of 9% compared to the experimental results. With respect to the turbulent quantities, good agreements at the second (downwind) half of the barn inside and especially outside the barn could be achieved, where all codes accurately predicted the flow separation and, in many cases, the root-mean-square velocities. Deviations between simulations and experimental results regarding turbulent quantities could be observed in the first part of the barn. These deviations can be attributed to the utilization of roughness elements between inlet and barn in the experiment that were not modeled in the numerical simulations. Both open source solvers proved to be promising tools for the accurate prediction of time-dependent phenomena in an agricultural context, e.g., like the transport of particulate matter or pathogen-laden aerosols in and around agricultural buildings. © 2020 The Authors
- ItemCalculation of ventilation rates and ammonia emissions : Comparison of sampling strategies for a naturally ventilated dairy barn(San Diego, Calif. : Academ. Press, 2020) Janke, David; Willink, Dylia; Ammon, Christian; Hempel, Sabrina; Schrade, Sabine; Demeyer, Peter; Hartung, Eberhard; Amon, Barbara; Ogink, Nico; Amon, ThomasEmissions and ventilation rates (VRs) in naturally ventilated dairy barns (NVDBs) are usually measured using indirect methods, where the choice of inside and outside sampling locations (i.e. sampling strategy) is crucial. The goal of this study was to quantify the influence of the sampling strategy on the estimation of emissions and VRs. We equipped a NVDB in northern Germany with an extensive measuring setup capable of measuring emissions under all wind conditions. Ammonia (NH3) and carbon dioxide (CO2) concentrations were measured with two Fourier-transform infrared spectrometers. Hourly values for ventilation rates and emissions for ammonia over a period of nearly a year were derived using the CO2 balance method and five different sampling strategies for the acquisition of indoor and outdoor concentrations were applied. When comparing the strategy estimating the highest emission level to the strategy estimating the lowest, the differences in NH3 emissions in winter, transition, and summer season were +26%, +19% and +11%, respectively. For the ventilation rates, the differences were +80%, +94%, and 63% for the winter, transition and summer season, respectively. By accommodating inside/outside concentration measurements around the entire perimeter of the barn instead of a reduced part of the perimeter (aligned to a presumed main wind direction), the amount of available data substantially increased for around 210% for the same monitoring period.
- ItemMethane Emission Characteristics of Naturally Ventilated Cattle Buildings(Basel : MDPI AG, 2020) Hempel, Sabrina; Willink, Diliara; Janke, David; Ammon, Christian; Amon, Barbara; Amon, ThomasThe mandate to limit global temperature rise calls for a reliable quantification of gaseous pollutant emissions as a basis for effective mitigation. Methane emissions from ruminant fermentation are of particular relevance in the context of greenhouse gas mitigation. The emission dynamics are so far insufficiently understood. We analyzed hourly methane emission data collected during contrasting seasons from two naturally ventilated dairy cattle buildings with concrete floor and performed a second order polynomial regression. We found a parabolic temperature dependence of the methane emissions irrespective of the measurement site and setup. The position of the parabola vertex varied when considering different hours of the day. The circadian rhythm of methane emissions was represented by the pattern of the fitted values of the constant term of the polynomial and could be well explained by feeding management and air flow conditions. We found barn specific emission minima at ambient temperatures around 10 °C to 15 °C. As this identified temperature optimum coincides with the welfare temperature of dairy cows, we concluded that temperature regulation of dairy cow buildings with concrete floor should be considered and further investigated as an emission mitigation measure. Our results further indicated that empirical modeling of methane emissions from the considered type of buildings with a second order polynomial for the independent variable air temperature can increase the accuracy of predicted long-term emission values for regions with pronounced seasonal temperature fluctuations
- ItemDirect Measurements of the Volume Flow Rate and Emissions in a Large Naturally Ventilated Building(Basel : MDPI, 2020) Janke, David; Yi, Qianying; Thormann, Lars; Hempel, Sabrina; Amon, Barbara; Nosek, Štepán; van Overbeke, Philippe; Amon, ThomasThe direct measurement of emissions from naturally ventilated dairy barns is challenging due to their large openings and the turbulent and unsteady airflow at the inlets and outlets. The aim of this study was to quantify the impacts of the number and positions of sensors on the estimation of volume flow rate and emissions. High resolution measurements of a naturally ventilated scaled building model in an atmospheric boundary layer wind tunnel were done. Tracer gas was released inside the model and measured at the outlet area, using a fast flame ionization detector (FFID). Additionally, the normal velocity on the area was measured using laser Doppler anemometry (LDA). In total, for a matrix of 65 × 4 sensor positions, the mean normal velocities and the mean concentrations were measured and used to calculate the volume flow rate and the emissions. This dataset was used as a reference to assess the accuracy while systematically reducing the number of sensors and varying the positions of them. The results showed systematic errors in the emission estimation up to +97%, when measurements of concentration and velocity were done at one constant height. This error could be lowered under 5%, when the concentrations were measured as a vertical composite sample.
- ItemHow the Selection of Training Data and Modeling Approach Affects the Estimation of Ammonia Emissions from a Naturally Ventilated Dairy Barn—Classical Statistics versus Machine Learning(Basel : MDPI AG, 2020) Hempel, Sabrina; Adolphs, Julian; Landwehr, Niels; Janke, David; Amon, ThomasEnvironmental protection efforts can only be effective in the long term with a reliable quantification of pollutant gas emissions as a first step to mitigation. Measurement and analysis strategies must permit the accurate extrapolation of emission values. We systematically analyzed the added value of applying modern machine learning methods in the process of monitoring emissions from naturally ventilated livestock buildings to the atmosphere. We considered almost 40 weeks of hourly emission values from a naturally ventilated dairy cattle barn in Northern Germany. We compared model predictions using 27 different scenarios of temporal sampling, multiple measures of model accuracy, and eight different regression approaches. The error of the predicted emission values with the tested measurement protocols was, on average, well below 20%. The sensitivity of the prediction to the selected training dataset was worse for the ordinary multilinear regression. Gradient boosting and random forests provided the most accurate and robust emission value predictions, accompanied by the second-smallest model errors. Most of the highly ranked scenarios involved six measurement periods, while the scenario with the best overall performance was: One measurement period in summer and three in the transition periods, each lasting for 14 days.