LONG TERM MEASUREMENTS OF AMMONIA EMISSIONS FROM NATURALLY VENTILATED DAIRY BARN

KÖNIG, M.¹, JANKE, D.¹, HEMPEL, S.¹, AMON, B.¹, AMON, T.^{1, 2}

1 Leibniz Institute for Agricultural Engineering and Bioeconomy, Germany

2 Freie Universität Berlin, Germany

ABSTRACT: Tracer gas balancing methods are commonly used to estimate air exchange rates (AER) and emission factors (EF) of naturally ventilated barns (NVB). These methods highly depend on the choice of position for gas sampling. In most cases, NVB are equipped only for measuring AER and EF from one wind direction, which means that all values that where measured for flow regimes deviant from the main wind direction are skipped. We present our new measurement concept, which is designed to measure AER and EF for any kind of wind direction in temporal and spatial high resolution, taking into account adjacent pollutant sources. The objective of the concept was to increase the number of usable samples in a given time period and so to increase the quality of measurements.

Two FTIR gas analysers in parallel operation, about 1000m of sampling tubes and more than 100 capillary traps were installed to ensure a representative sampling of NH3 and CO2

in high temporal and spatial resolution. Measurements in a NVB in northern Germany were carried out over a period of 7 months with hourly AER derived by CO2 balance and EF for NH3. The results suggest that taking into account all wind directions significantly increases the number of usable samples and so the quality of the measurements, which could compensate the increased effort in the measurement design.

Keywords: measuring method, air exchange rate, NH3, CO2, wind direction

INTRODUCTION: An experimental barn located in Dummerstorf, Germany, was equipped with an extensive measurement program to investigate air exchange rates (AER) and ammonia emission factors (EF) with a high accuracy. The main focus, besides accurcy, was the increase of data usability. That means, independent of pollutant sources like neighboring barns or manure storage, the AER and EF should be measurable for any approaching flow direction.

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Direction Is South West, With Fluctuating Wind Directions. In The Vicinity Of The Barn, Several Obstacles Are Positioned That Could Act As Possible Pollutant Inflow Sources And Bias The Measurements For Co2 And Nh3 Concentrations (See Figure 1). Further Details About The Barn, The Operational Management And The Animals Can Be Found In (Fiedler Et Al., 2014).

1.1. Devices: Gaseous concentrations were measured using two high resolution Fourier-Transform-Infrared- (FTIR-) Spectrometer measurement devices (Gasmet CX4000). Sample air was sucked through PTFE tubes with an inner diameter of 6mm. Every 10m, the tubes had an orifice with a capillary trap, which ensured uniform volumetric flow at every orifice. At the roof of the barn, an ultra-sonic anemometer (USA, Windmaster Pro ultrasonic anemometer, Gill Instruments Limited, Lymington, Hampshire, UK) was installed to measure the wind velocity and direction.

1.2. Setup and Sampling: Inside the barn, six sample lines were installed, so that each side or opening was equipped and two lines were placed in the middle. All lines were positioned at a height of 3m except the second middle line, which was at a height of 5m.

Outside the barn, six sampling lines were installed, one on each side or opening of the barn and two for additional measurements of potential hot spots. The duration of measurement per line was 10 minutes and each FTIR was connected to six lines, so that one cycle per hour was measured.

Figure 2. Left: Sketch of the installed sampling lines. Right up: Installed southern sample line in the barn.

Right down: FTIR in parallel operation.

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Table 1: 1-hour cycle for both FTIR in parallel operation. Suffixes –o and –i indicate outdoor or indoor sample lines, respectively. Extra1 and extra2 are additional lines for future investigations of hot spots.

Time [min] 10 20 30 40 50 60

FTIR 1 line location west-o north-i east-o west-i extra1 extra2 FTIR 2 line location south-o north-i middle1 middle2 north-o south-i

The FTIR were set to measure pairing sequences of sample lines, i.e. first an outdoor line and directly after that, the corresponding indoor sampling line was measured. Figure 3 depicts the pairing of these sample lines and table 1 shows one cycle of measurement.

1.3. Data processing: The AER and EF where hourly estimated by CO2 balancing according to the guidelines of (CIGR, 2002). For that, the sampling lines for outside and inside gas concentrations of CO₂ and NH₃ that would be used for the estimations had to be chosen.

Hence, the wind data from the USA were analysed and for every hour it was determined whether the main flow was coming from north, east, south or west. With that information, the respective corresponding sample line pair was taken from the database to estimate the AER and EF for every hour.

Figure 3: Sampling strategy: The choice of sampling lines as in- or outlet depends on the approaching flow conditions. From left to right: approaching flow from north, east, west or south.

2. RESULTS AND DISCUSSION: The devices measured in the period October 2016 until April 2017. This corresponds to 4165 hours, which is the theoretical maximum number of datasets that could be generated for hourly AER and EF.

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Data were skipped, if the total difference between inside and outside CO2-concentration

∆c = CO2-i – CO2-o was less than 20 ppm, if ∆c was negative and in periods where the curtains of the barn were closed. Due to a power failure, the devices did not measure for several days. Hence, all in all a number of 1850 hourly measured values for AER and EF were available for the whole period, When taking into account every wind direction.

When operating the system only for the main wind direction, these values were reduced to 626 available values, which is a decrease of 66.2%. Figure 4 shows a detailed view of cut out values for non-main direction values. In figure 5, the mean values of all hourly data are sorted by wind direction. The AER is the highest for western winds, which is flow from longitudinal direction. This is surprising, we had expected the highest AER would occur for directions through the largest openings, i.e. northern or soutern. On the other hand, as seen in figure 1, west is the direction, where the flow is not disturbed at all by any obstacles. We will study this phenomena further by analyzing the flow velocity distribution inside the barn.

Figure 5: Mean values for NH3 emissions, AER, CO2 and NH3 differences between inside and outside concentrations. Derived by the whole dataset, clustered in respective wind directions.

3. CONCLUSION: Designing the measuring concept to measure any wind direction significantly increases the number of usable measurement values. The increased effort for installing additional sampling lines and measuring devices can be compensated by shorter measurement periods and more accurate estimations of AER and EF due to the increase in the number of measurement values. AER were highest from a longitudinal approaching flow. More invastigations on the dynamical behavior of the flow field need to be done to explain the found dependency of the AER and NH3 emissions on the wind direction.

REFERENCES:

Fiedler, M., Fischer, J., Hempel, S., Saha, C. K., Loebsin, C., Berg, W., & Amon, T. (2014).

Flow fields within a dairy barn–Measurements, physical modeling and numerical simulation. In Proceedings of the International Conference of Agricultural Engineering, Zurich (pp. 1-8).

CIGR, 2002. 4th report from working group on climatization of animal houses. In:

Pedersen, S., Sällvik, K. (Eds.), Research Centre Bygholm. DIAS, Horsens, Denmark. 45 pp. www.agrsci.dk/jbt/spe/CIGRreport

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