Browsing by Author "Janke, David"

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    Airflow 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, Thomas
    The 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.
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    Calculation 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, Thomas
    Emissions 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.
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    CFD modelling of an animal occupied zone using an anisotropic porous medium model with velocity depended resistance parameters
    (Amsterdam [u.a.] : Elsevier, 2021) Doumbia, E. Moustapha; Janke, David; Yi, Qianying; Amon, Thomas; Kriegel, Martin; Hempel, Sabrina
    The airflow in dairy barns is affected by many factors, such as the barn’s geometry, weather conditions, configurations of the openings, cows acting as heat sources, flow obstacles, etc. Computational fluids dynamics (CFD) has the advantages of providing detailed airflow information and allowing fully-controlled boundary conditions, and therefore is widely used in livestock building research. However, due to the limited computing power, numerous animals are difficult to be designed in detail. Consequently, there is the need to develop and use smart numerical models in order to reduce the computing power needed while at the same time keeping a comparable level of accuracy. In this work the porous medium modeling is considered to solve this problem using Ansys Fluent. A comparison between an animal occupied zone (AOZ) filled with randomly arranged 22 simplified cows’ geometry model (CM) and the porous medium model (PMM) of it, was made. Anisotropic behavior of the PMM was implemented in the porous modeling to account for turbulence influences. The velocity at the inlet of the domain has been varied from 0.1 m s−1 to 3 m s−1 and the temperature difference between the animals and the incoming air was set at 20 K. Leading to Richardson numbers Ri corresponding to the three types of heat transfer convection, i.e. natural, mixed and forced convection. It has been found that the difference between two models (the cow geometry model and the PMM) was around 2% for the pressure drop and less than 6% for the convective heat transfer. Further the usefulness of parametrized PMM with a velocity adaptive pressure drop and heat transfer coefficient is shown by velocity field validation of an on-farm measurement.
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    Comparison of Methane Emission Patterns from Dairy Housings with Solid and Slatted Floors at Two Locations
    (Basel : MDPI, 2022) Hempel, Sabrina; Janke, David; Losand, Bernd; Zeyer, Kerstin; Zähner, Michael; Mohn, Joachim; Amon, Thomas; Schrade, Sabine
    Methane (CH4) emissions from dairy husbandry are a hot topic in the context of active climate protection, where housing systems with slatted floors and slurry storage inside are in general expected to emit more than systems with solid floors. There are multiple factors, including climate conditions, that modulate the emission pattern. In this study, we investigated interrelations between CH4 emission patterns and climate conditions as well as differences between farm locations versus floor effects. We considered three data sets with 265, 264 and 275 hourly emission values from two housing systems (one slatted, one solid floor) in Switzerland and one system with solid floors in Germany. Each data set incorporated measurements in summer, winter and a transition season. The average CH4 emission was highest for the slatted floor system. For the solid floor systems, CH4 emissions at the Swiss location were around 30% higher compared to the German location. The shape of the distributions for the two solid floor systems was rather similar but very different from the distribution for the slatted floor system, which showed higher prevalence for extreme emissions. Rank correlations, which measure the degree of similarity between two rankings in terms of linear relation, were not able to detect dependencies at the selected significance level. In contrast, mutual information, which measures more general statistical dependencies in terms of shared information, revealed highly significant dependencies for almost all variable pairs. The weakest statistical relation was found between winds speed and CH4 emission, but the convection regime was found to play a key role. Clustering was consistent among the three data sets with five typical clusters related to high/low temperature and wind speed, respectively, as well as in some cases to morning and evening hours. Our analysis showed that despite the disparate and often insignificant correlation between environmental variables and CH4 emission, there is a strong relation between both, which shapes the emission pattern in many aspects much more in addition to differences in the floor type. Although a clear distinction of high and low emission condition clusters based on the selected environmental variables was not possible, trends were clearly visible. Further research with larger data sets is advisable to verify the detected trends and enable prognoses for husbandry systems under different climate conditions.
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    Direct 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, Thomas
    The 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.
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    Effect of Fans’ Placement on the Indoor Thermal Environment of Typical Tunnel-Ventilated Multi-Floor Pig Buildings Using Numerical Simulation
    (Basel : MDPI AG, 2022) Wang, Xiaoshuai; Cao, Mengbing; Hu, Feiyue; Yi, Qianying; Amon, Thomas; Janke, David; Xie, Tian; Zhang, Guoqiang; Wang, Kaiying
    An increasing number of large pig farms are being built in multi-floor pig buildings (MFPBs) in China. Currently, the ventilation system of MFPB varies greatly and lacks common standards. This work aims to compare the ventilation performance of three popular MFPB types with different placement of fans using the Computational Fluid Dynamics (CFD) technique. After being validated with field-measured data, the CFD models were extended to simulate the air velocity, air temperature, humidity, and effective temperature of the three MFPBs. The simulation results showed that the ventilation rate of the building with outflowing openings in the endwall and fans installed on the top of the shaft was approximately 25% less than the two buildings with fans installed on each floor. The ventilation rate of each floor increased from the first to the top floor for both buildings with a shaft, while no significant difference was observed in the building without a shaft. Increasing the shaft’s width could mitigate the variation in the ventilation rate of each floor. The effective temperature distribution at the animal level was consistent with the air velocity distribution. Therefore, in terms of the indoor environmental condition, the fans were recommended to be installed separately on each floor.
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    Heat stress risk in European dairy cattle husbandry under different climate change scenarios – uncertainties and potential impacts
    (Göttingen : Copernicus, 2019) Hempel, Sabrina; Menz, Christoph; Pinto, Severino; Galán, Elena; Janke, David; Estellés, Fernando; Müschner-Siemens, Theresa; Wang, Xiaoshuai; Heinicke, Julia; Zhang, Guoqiang; Amon, Barbara; del Prado, Agustín; Amon, Thomas
    In the last decades, a global warming trend was observed. Along with the temperature increase, modifications in the humidity and wind regime amplify the regional and local impacts on livestock husbandry. Direct impacts include the occurrence of climatic stress conditions. In Europe, cows are economically highly relevant and are mainly kept in naturally ventilated buildings that are most susceptible to climate change. The high-yielding cows are particularly vulnerable to heat stress. Modifications in housing management are the main measures taken to improve the ability of livestock to cope with these conditions. Measures are typically taken in direct reaction to uncomfortable conditions instead of in anticipation of a long-term risk for climatic stress. Measures that balance welfare, environmental and economic issues are barely investigated in the context of climate change and are thus almost not available for commercial farms. Quantitative analysis of the climate change impacts on animal welfare and linked economic and environmental factors is rare. Therefore, we used a numerical modeling approach to estimate the future heat stress risk in such dairy cattle husbandry systems. The indoor climate was monitored inside three reference barns in central Europe and the Mediterranean regions. An artificial neuronal network (ANN) was trained to relate the outdoor weather conditions provided by official meteorological weather stations to the measured indoor microclimate. Subsequently, this ANN model was driven by an ensemble of regional climate model projections with three different greenhouse gas concentration scenarios. For the evaluation of the heat stress risk, we considered the number and duration of heat stress events. Based on the changes in the heat stress events, various economic and environmental impacts were estimated. The impacts of the projected increase in heat stress risk varied among the barns due to different locations and designs as well as the anticipated climate change (considering different climate models and future greenhouse gas concentrations). There was an overall increasing trend in number and duration of heat stress events. At the end of the century, the number of annual stress events can be expected to increase by up to 2000, while the average duration of the events increases by up to 22 h compared to the end of the last century. This implies strong impacts on economics, environment and animal welfare and an urgent need for mid-term adaptation strategies. We anticipated that up to one-tenth of all hours of a year, correspondingly one-third of all days, will be classified as critical heat stress conditions. Due to heat stress, milk yield may decrease by about 2.8 % relative to the present European milk yield, and farmers may expect financial losses in the summer season of about 5.4 % of their monthly income. In addition, an increasing demand for emission reduction measures must be expected, as an emission increase of about 16 Gg of ammonia and 0.1 Gg of methane per year can be expected under the anticipated heat stress conditions. The cattle respiration rate increases by up to 60 %, and the standing time may be prolonged by 1 h. This causes health issues and increases the probability of medical treatments. The various impacts imply feedback loops in the climate system which are presently underexplored. Hence, future in-depth studies on the different impacts and adaptation options at different stress levels are highly recommended.
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    How 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, Thomas
    Environmental 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.
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    The impact of atmospheric boundary layer, opening configuration and presence of animals on the ventilation of a cattle barn
    (Amsterdam [u.a.] : Elsevier Science, 2020) Nosek, Štěpán; Kluková, Zuzana; Jakubcová, Michaela; Yi, Qianying; Janke, David; Demeyer, Peter; Jaňour, Zbyněk
    Naturally ventilated livestock buildings (NVLB) represent one of the most significant sources of ammonia emissions. However, even the dispersion of passive gas in an NVLB is still not well understood. In this paper, we present a detailed investigation of passive pollutant dispersion in a model of a cattle barn using the wind tunnel experiment method. We simulated the pollution of the barn by a ground-level planar source. We used the time-resolved particle image velocimetry (TR-PIV) and the fast flame ionisation detector (FFID) to study the flow and dispersion processes at high spatial and temporal resolution. We employed the Proper Orthogonal Decomposition (POD) and Oscillating Patterns Decomposition (OPD) methods to detect the coherent structures of the flow. The results show that the type of atmospheric boundary layer (ABL) and sidewall opening height have a significant impact on the pollutant dispersion in the barn, while the presence of animals and doors openings are insignificant under conditions of winds perpendicular to the sidewall openings. We found that the dynamic coherent structures, developed by the Kelvin-Helmholtz instability, contribute to the pollutant transport in the barn. We demonstrate that in any of the studied cases the pollutant was not well mixed within the barn and that a significant underestimation (up to by a factor 3) of the barn ventilation might be obtained using, e.g. tracer gas method. © 2020 The Authors
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    Methane Emission Characteristics of Naturally Ventilated Cattle Buildings
    (Basel : MDPI AG, 2020) Hempel, Sabrina; Willink, Diliara; Janke, David; Ammon, Christian; Amon, Barbara; Amon, Thomas
    The 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
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    On Finding the Right Sampling Line Height through a Parametric Study of Gas Dispersion in a NVB
    (Basel : MDPI, 2021) Doumbia, E. Moustapha; Janke, David; Yi, Qianying; Zhang, Guoqiang; Amon, Thomas; Kriegel, Martin; Hempel, Sabrina
    The tracer gas method is one of the common ways to evaluate the air exchange rate in a naturally ventilated barn. One crucial condition for the accuracy of the method is that both considered gases (pollutant and tracer) are perfectly mixed at the points where the measurements are done. In the present study, by means of computational fluids dynamics (CFD), the mixing ratio NH3/CO2 is evaluated inside a barn in order to assess under which flow conditions the common height recommendation guidelines for sampling points (sampling line and sampling net) of the tracer gas method are most valuable. Our CFD model considered a barn with a rectangular layout and four animal-occupied zones modeled as a porous medium representing pressure drop and heat entry from lying and standing cows. We studied three inflow angles and six combinations of air inlet wind speed and temperatures gradients covering the three types of convection, i.e., natural, mixed, and forced. Our results showed that few cases corresponded to a nearly perfect gas mixing ratio at the currently common recommendation of at least a 3 m measurement height, while the best height in fact lied between 1.5 m and 2.5 m for most cases.
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    On 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, Volker
    Two 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
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    On the feasibility of using open source solvers for the simulation of a turbulent air flow in a dairy barn
    (Berlin : Weierstraß-Institut für Angewandte Analysis und Stochastik, 2019) Janke, David; Caiazzo, Alfonso; Ahmed, Naveed; Alia, Najib; Knoth, Oswald; Moreau, Baptiste; Wilbrandt, Ulrich; Willink, Dilya; Amon, Thomas; John, Volker
    Two transient open source solvers, OpenFOAM and ParMooN, 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. Both 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 solvers with relative errors less than 5 % 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 both codes accurately predicted the flow separation and the root-mean-square velocities. Deviations between simulations and experimental results regarding turbulent quantities could be observed in the first part of the barn, due to different inlet conditions between the experimental setup and the numerical simulations. Both 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.
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    Opening 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, Thomas
    Airflow 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.
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    A Parametric Model for Local Air Exchange Rate of Naturally Ventilated Barns
    (Basel : MDPI AG, 2021) Doumbia, E. Moustapha; Janke, David; Yi, Qianying; Prinz, Alexander; Amon, Thomas; Kriegel, Martin; Hempel, Sabrina
    With an increasing number of naturally ventilated dairy barns (NVDBs), the emission of ammonia and greenhouse gases into the surrounding environment is expected to increase as well. It is very challenging to accurately determine the amount of gases released from a NVDB on-farm. Moreover, control options for the micro-climate to increase animal welfare are limited in an NVDB at present. Both issues are due to the complexity of the NVDB micro-environment, which is subject to temporal (such as wind direction and temperature) and spatial (such as openings and animals acting as airflow obstacles) fluctuations. The air exchange rate (AER) is one of the most valuable evaluation entities, since it is directly related to the gas emission rate and animal welfare. In this context, our study determined the general and local AERs of NVDBs of different shapes under diverse airflow conditions. Previous works identified main influencing parameters for the general AER and mathematically linked them together to predict the AER of the barn as a whole. The present research study is a continuation and extension of previous studies about the determination of AER. It provides new insights into the influence of convection flow regimes. In addition, it goes further in precision by determining the local AERs, depending on the position of the considered volume inside the barn. After running several computational fluid dynamics (CFD) simulations, we used the statistical tool of general linear modeling in order to identify quantitative relationships between the AER and the following five influencing parameters, the length/width ratio of the barn, the side opening configuration, the airflow temperature, magnitude and incoming direction. The work succeeded in taking the temperature into account as a further influencing parameter in the model and, thus, for the first time, in analysing the effect of the different types of flow convection in this context. The resulting equations predict the barn AER with an R2 equals 0.98 and the local AER with a mean R2 equals around 0.87. The results go a step further in the precise determination of the AER of NVDB and, therefore, are of fundamental importance for a better and deeper understanding of the interaction between the driving forces of AER in NVDB.
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    Particulate Matter Dispersion Modeling in Agricultural Applications: Investigation of a Transient Open Source Solver
    (Basel : MDPI, 2021) Janke, David; Swaminathan, Senthilathiban; Hempel, Sabrina; Kasper, Robert; Amon, Thomas
    Agriculture is a major emitter of particulate matter (PM), which causes health problems and can act as a carrier of the pathogen material that spreads diseases. The aim of this study was to investigate an open-source solver that simulates the transport and dispersion of PM for typical agricultural applications. We investigated a coupled Eulerian–Lagrangian solver within the open source software package OpenFOAM. The continuous phase was solved using transient large eddy simulations, where four different subgrid-scale turbulence models and an inflow turbulence generator were tested. The discrete phase was simulated using two different Lagrangian solvers. For the validation case of a turbulent flow of a street canyon, the flowfield could be recaptured very well, with errors of around 5% for the non-equilibrium turbulence models (WALE and dynamicKeq) in the main regions. The inflow turbulence generator could create a stable and accurate boundary layer for the mean vertical velocity and vertical profile of the turbulent Reynolds stresses R11. The validation of the Lagrangian solver showed mixed results, with partly good agreements (simulation results within the measurement uncertainty), and partly high deviations of up to 80% for the concentration of particles. The higher deviations were attributed to an insufficient turbulence regime of the used validation case, which was an experimental chamber. For the simulation case of PM dispersion from manure application on a field, the solver could capture the influence of features such as size and density on the dispersion. The investigated solver is especially useful for further investigations into time-dependent processes in the near-source area of PM sources.
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    Particulate matter emissions during field application of poultry manure - The influence of moisture content and treatment
    (Amsterdam [u.a.] : Elsevier Science, 2021) Kabelitz, Tina; Biniasch, Oliver; Ammon, Christian; Nübel, Ulrich; Thiel, Nadine; Janke, David; Swaminathan, Senthilathiban; Funk, Roger; Münch, Steffen; Rösler, Uwe; Siller, Paul; Amon, Barbara; Aarnink, André J. A.; Amon, Thomas
    Along with industry and transportation, agriculture is one of the main sources of primary particulate matter (PM) emissions worldwide. Bioaerosol formation and PM release during livestock manure field application and the associated threats to environmental and human health are rarely investigated. In the temperate climate zone, field fertilization with manure seasonally contributes to local PM air pollution regularly twice per year (spring and autumn). Measurements in a wind tunnel, in the field and computational fluid dynamics (CFD) simulations were performed to analyze PM aerosolization during poultry manure application and the influence of manure moisture content and treatment. A positive correlation between manure dry matter content (DM) and PM release was observed. Therefore, treatments strongly increasing the DM of poultry manure should be avoided. However, high manure DM led to reduced microbial abundance and, therefore, to a lower risk of environmental pathogen dispersion. Considering the findings of PM and microbial measurements, the optimal poultry manure DM range for field fertilization was identified as 50–70%. Maximum PM10 concentrations of approx. 10 mg per m3 of air were measured during the spreading of dried manure (DM 80%), a concentration that is classified as strongly harmful. The modeling of PM aerosolization processes indicated a low health risk beyond a distance of 400 m from the manure application source. The detailed knowledge about PM aerosolization during manure field application was improved with this study, enabling manure management optimization for lower PM aerosolization and pathogenic release into the environment.
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    Review of Wind Tunnel Modelling of Flow and Pollutant Dispersion within and from Naturally Ventilated Livestock Buildings
    (Basel : MDPI, 2021) Nosek, Štěpán; Jaňour, Zbyněk; Janke, David; Yi, Qianying; Aarnink, André; Calvet, Salvador; Hassouna, Mélynda; Jakubcová, Michala; Demeyer, Peter; Zhang, Guoqiang
    Ammonia emissions from naturally ventilated livestock buildings (NVLBs) pose a serious environmental problem. However, the mechanisms that control these emissions are still not fully understood. One promising method for understanding these mechanisms is physical modelling in wind tunnels. This paper reviews studies that have used this method to investigate flow or pollutant dispersion within or from NVLBs. The review indicates the importance of wind tunnels for understanding the flow and pollutant dispersion processes within and from NVLBs. However, most studies have investigated the flow, while only few studies have focused on pollutant dispersion. Furthermore, only few studies have simulated all the essential parameters of the approaching boundary layer. Therefore, this paper discusses these shortcomings and provides tips and recommendations for further research in this respect.
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    Supervised 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, Thomas
    A 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.
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    Uncertainty in the measurement of indoor temperature and humidity in naturally ventilated dairy buildings as influenced by measurement technique and data variability
    (Amsterdam : Elsevier, 2017) Hempel, Sabrina; König, Marcel; Menz, Christoph; Janke, David; Amon, Barbara; Banhazi, Thomas M.; Estellés, Fernando; Amon, Thomas
    The microclimatic conditions in dairy buildings affect animal welfare and gaseous emissions. Measurements are highly variable due to the inhomogeneous distribution of heat and humidity sources (related to farm management) and the turbulent inflow (associated with meteorologic boundary conditions). The selection of the measurement strategy (number and position of the sensors) and the analysis methodology adds to the uncertainty of the applied measurement technique. To assess the suitability of different sensor positions, in situations where monitoring in the direct vicinity of the animals is not possible, we collected long-term data in two naturally ventilated dairy barns in Germany between March 2015 and April 2016 (horizontal and vertical profiles with 10 to 5 min temporal resolution). Uncertainties related to the measurement setup were assessed by comparing the device outputs under lab conditions after the on-farm experiments. We found out that the uncertainty in measurements of relative humidity is of particular importance when assessing heat stress risk and resulting economic losses in terms of temperature-humidity index. Measurements at a height of approximately 3 m–3.5 m turned out to be a good approximation for the microclimatic conditions in the animal occupied zone (including the air volume close to the emission active zone). However, further investigation along this cross-section is required to reduce uncertainties related to the inhomogeneous distribution of humidity. In addition, a regular sound cleaning (and if possible recalibration after few months) of the measurement devices is crucial to reduce the instrumentation uncertainty in long-term monitoring of relative humidity in dairy barns. © 2017 The Authors