Comparison between light scattering and gravimetric samplers for PM10 mass concentration in poultry and pig houses

The objective of this study was to compare co-located real-time light scattering devices and equivalent gravimetric samplers in poultry and pig houses for PM10 mass concentration, and to develop animal-specific calibration factors for light scattering samplers. These results will contribute to evaluate the comparability of different sampling instruments for PM10, concentrations. Paired DustTrak light scattering device (DustTrak aerosol monitor, TSI, U.S.) and PM10 gravimetric cyclone sampler were used for measuring PM10 mass concentrations during 24 h periods (from noon to noon) inside animal houses. Sampling was conducted in 32 animal houses in the Netherlands, including broilers, broiler breeders, layers in floor and in aviary system, turkeys, piglets, growing-finishing pigs in traditional and low emission housing with dry and liquid feed, and sows in individual and group housing. A total of 119 pairs of 24 h measurements (55 for poultry and 64 for pigs) were recorded and analyzed using linear regression analysis. Deviations between samplers were calculated and discussed. In poultry, cyclone sampler and DustTrak data fitted well to a linear regression, with a regression coefficient equal to 0.41, an intercept of 0.16 mg m(-3) and a correlation coefficient of 0.91 (excluding turkeys). Results in turkeys showed a regression coefficient equal to 1.1 (P = 0.49), an intercept of 0.06 mg m(-3) (P < 0.0001) and a correlation coefficient of 0.98. In pigs, we found a regression coefficient equal to 0.61, an intercept of 0.05 mg m(-3) and a correlation coefficient of 0.84. Measured PM10 concentrations using DustTraks were clearly underestimated (approx. by a factor 2) in both poultry and pig housing systems compared with cyclone pre-separators. Absolute, relative, and random deviations increased with concentration. DustTrak light scattering devices should be self-calibrated to investigate PM10 mass concentrations accurately in animal houses. We recommend linear regression equations as animal-specific calibration factors for DustTraks instead of manufacturer calibration factors, especially in heavily dusty environments such as animal houses. (C) 2015 Elsevier Ltd. All rights reserved.The study was financed by the Dutch Ministry of Economic affairs, Agriculture and Innovation. Authors wish to thank the Campus de Excelencia Internacional of the Universitat Politecnica de Valencia (Spain) for funding Dr. Cambra-Lopez's postdoc contract.Cambra López, M.; Winkel, A.; Mosquera, J.; Ogink, NW.; Aarnink, AJA. (2015). Comparison between light scattering and gravimetric samplers for PM10 mass concentration in poultry and pig houses. Atmospheric Environment. 111:20-27. doi:10.1016/j.atmosenv.2015.03.051S202711

Measuring gas emissions from livestock buildings: A review on uncertainty analysis and error sources

Measuring gaseous and particulate emissions from livestock houses has been the subject of intensive research over the past two decades. Currently, there is general agreement regarding appropriate methods to measure emissions from mechanically ventilated buildings. However, measuring emissions from naturally ventilated buildings remains an elusive target primarily because there is no reference method for measuring building ventilation rate. Ventilation rates and thus building emissions estimates for naturally ventilated buildings are likely to contain greater errors compared with those from mechanically ventilated buildings. This work reviews the origin and magnitude of errors associated with emissions from naturally ventilated buildings as compared to those typically found in mechanical ventilation. Firstly, some general concepts of error analysis are detailed. Then, typical errors found in the literature for each measurement technique are reviewed, and potential sources of relevant systematic and random errors are identified. The emission standard uncertainty in mechanical ventilation is at best 10% or more of the measured value, whereas in natural ventilation it may be considerably higher and there may also be significant unquantifiable biases. A reference method is necessary to obtain accurate emissions estimates, and for naturally ventilated structures this suggests the need for a new means of ventilation measurement. The results obtained from the analysis of information in this review will be helpful to establish research priorities, and to optimize research efforts in terms of quality of emission measurements. (C) 2012 IAgrE. Published by Elsevier Ltd. All rights reserved.Calvet Sanz, S.; Gates, RS.; Zhang, G.; Estellés, F.; Ogink, NWM.; Pedersen, S.; Berckmans, D. (2013). Measuring gas emissions from livestock buildings: A review on uncertainty analysis and error sources. Biosystems Engineering. 116:221-231. doi:10.1016/j.biosystemseng.2012.11.004S22123111

Application of field blanks in odour emission research

In the Netherlands field blanks are mandatory when sampling odour emission. Field blanks are matrices that<br/>have negligible or unmeasurable amounts of the substance of interest. They are used to document possible<br/>contamination during sampling, transport and storage of samples. Although field blanks are well established in<br/>odour emission research, interpreting the results needs further attention. This can be attributed to the fact that<br/>published information on the topic is rare if not absent. In the present study, general statistical measures of<br/>field blanks used in odour measurement research, are reported. The objective of the study was to provide<br/>insight in the distribution of field blank values.<br/>During 2013 and 2014, field blanks were analysed as part of regular investigations into odour emissions. Point<br/>sources were most frequently observed (87%), as well as the use of diluting stack samplers (72%). It was<br/>found that average odour concentration and standard deviation of the dataset were 1.39 and 0.379<br/>log(ouE/m3) respectively, both expressed on a logarithmic scale (base 10). Median values of odour<br/>concentration of field blanks taken with stack sampler methods, differed significantly from lung sample<br/>methods, being a factor two higher. Since the implementation of stack sampler methods requires more<br/>processing aids than the lung method, the chances are that that traces of odour are carried over from one<br/>sampling sessions to another. This stresses the need for effective cleaning of sampling equipment between<br/>sampling sessions.<p>In the Netherlands field blanks are mandatory when sampling odour emission. Field blanks are matrices that have negligible or unmeasurable amounts of the substance of interest. They are used to document possible contamination during sampling, transport and storage of samples. Although field blanks are well established in odour emission research, interpreting the results needs further attention. This can be attributed to the fact that published information on the topic is rare if not absent. In the present study, general statistical measures of field blanks used in odour measurement research, are reported. The objective of the study was to provide insight in the distribution of field blank values. During 2013 and 2014, field blanks were analysed as part of regular investigations into odour emissions. Point sources were most frequently observed (87%), as well as the use of diluting stack samplers (72%). It was found that average odour concentration and standard deviation of the dataset were 1.39 and 0.379 log(ouE/m3) respectively, both expressed on a logarithmic scale (base 10). Median values of odour concentration of field blanks taken with stack sampler methods, differed significantly from lung sample methods, being a factor two higher. Since the implementation of stack sampler methods requires more processing aids than the lung method, the chances are that that traces of odour are carried over from one sampling sessions to another. This stresses the need for effective cleaning of sampling equipment between sampling sessions.</p

Temporal and spatial variation of methane concentrations around lying cubicles in dairy barns

To breed cows for low methane production, farm measurement methods are required to measure individual methane production of cows. The long lying period of cows in cubicles could be utilised here. However, variable aerial conditions around cubicles may challenge this approach. The objective of this study was to (1) assess temporal and spatial variability of methane concentrations around cubicles; (2) explore influencing factors on them; and (3) assess effects of barn background variability in methane concentrations on assessed individual methane production. Concentrations around two cubicles in a naturally ventilated dairy barn were measured during a summer and a winter period. The effect of barn background variability in methane concentration on individual cow measurements was analysed in relation to the working principles of the breath methane concentration and methane flux methods. Mean methane concentrations around the cubicle were 29–37 ppm in the summer and 33–51 ppm in the winter period. Spatial variations of hourly averages of methane concentration around the cubicle were 71% in the summer and 58% in the winter period. Temporal variations of hourly averages of methane concentration varied from 115 to 153% in the summer, and from 57 to 109% in the winter period among the sample locations. These variations were mainly affected by airflows and barn management. The coefficient of variation (CV) of the background concentration strongly influenced the overall measurement CV of assessed methane production, in both the methane flux and breath methane concentration method. This information can be used to limit measurement variation in methane measurement methods.</p

Measuring and assessing the role of deep litter to estimate the ventilation rate using the CO2 mass balance method

Carbon dioxide (CO2) produced from manure is a necessary input when using CO2 as a naturally produced tracer gas to measure ventilation rate in naturally ventilated livestock buildings. This work compares different chamber calculation methods for measuring CO2 production from solid manure and evaluates the variability, affecting factors and potential contribution of CO2 emissions from manure to total CO2 production in the building. A total of 925 static chamber measurements were used to this aim, conducted in five dairy cattle and three goat houses. Linearity (R2) and curvature (convex or concave) were the main factors explaining differences among models. CO2 emission from manure was on average 20.86 g m-2 h-1, but it was very variable in spatial terms within the same measurement day (coefficient of variation = 48%), among different measurement days in the same farm (coefficient of variation = 30%) and among farms of the same animal type (coefficient of variation = 66% and 48% for dairy and goat farms, respectively). Manure height and temperature were directly correlated with manure CO2 emission (r = +0.36 and + 0.38, respectively). For goats, a prediction equation of CO2 emission was obtained using these two variables (R2 = 0.74). Solid manure had a relevant contribution to the total farm production and needs to be quantified in each case. Models to predict CO2 manure are not available at the moment and therefore, measuring manure contribution using chambers seems the best option according to the current knowledge

Sensitivity analysis of fine dust spreading from litter in poultry houses

Poultry houses are one of the major sources of agricultural particulate matter (PM) emissions into the environment. Litter properties, poultry activities, and indoor climate of poultry houses are the main parameters that influence the dust emission, but precise quantitative effects and their interactions are hardly known. The objective of this study was to gain quantitative insight into the dust spreading process from poultry litter by using the discrete parcel method (DPM) and global sensitivity analysis (GSA).The dust spreading process includes the creep, suspension, and saltation of fine particles was simulated with the DPM within the aerial region close to the litter. The simulations proved that a collision between an object and the litter should happen to release particles from the litter into the air. It was indicated that the released particles with a diameter ≥30 μm and particle density ≥1400 kg m−3 were deposited on the litter for all tested air velocities. Also, particles 1.5 m s−1. The GSA indicated that the creep process has a direct relation with the airflow velocity and coefficient of restitution and an inverse relation with the particle density and the coefficient of friction. Overall, it was shown that the DPM is a suitable numerical technique to simulate the dust spreading process, and hence, it can be recommended for future studies to examine this process on larger scales.</p

Assessment of porous media instead of slatted floor for modelling the airflow and ammonia emission in the pit headspace

In order to reduce the emission, proper understanding of the transportation behaviour of gaseous ammonia inside the slurry pit is required. Numerical simulation by the aid of computational fluid dynamics (CFD) technique can be used for this purpose. However, direct modelling of slatted floors is complicated and may be replaced by the porous media model (PMM) as shown in earlier studies. The objective of our study is to improve the quality of simulation results by PMM, and to assess the effects of air velocity above the slatted floor (as affected by wind), pit headspace height (as affected by amount of slurry in the pit) and sidewall height (as affected by the dairy house sidewall) on the airflow features inside the pit and ammonia emission from the pit. Three different CFD models of a slatted floor were developed to evaluate whether porous media is capable to represent a slatted floor for modelling the airflow inside and ammonia emission from the slurry pit, and to study the effect of turbulence treatment in the porous media on the modelling results: a slatted floor model (SFM) which models the slatted floor as it is, a turbulent porous media model (PMM-T) and a laminar porous media model (PMM-L). Both PMM-T and PMM-L represent the slatted floor by porous media, the PMM-T assumes turbulent airflow and the PMM-L assumes laminar airflow in the porous media. The SFM was verified for a dataset acquired from a 1:8 scale wind tunnel model of the slurry pit. Results showed that the PMM (PMM-T and PMM-L) were able to predict both the airflow features inside the slurry pit and the ammonia emission from the slurry pit if the resistance parameters and flow regime of the porous media were properly set. In comparison to the SFM, the PMM-T predicted the flow pattern better, but overestimated the turbulence intensity and the consequent emission rate. PMM-L performed better in predicting the ammonia emission rate because of the relatively accurate prediction of turbulence intensity. Simulation results also showed that the ammonia emission rate increased with a higher mean airflow velocity, a smaller headspace height and the presence of sidewalls.</p

Evaluation of manure drying tunnels to serve as dust filters in the exhaust of laying hen houses: Emissions of particulate matter, ammonia, and odour

IAgrE Poultry houses are important emission sources of ammonia, odour, and particulate matter (PM). Manure drying tunnels (MDTs) might act as ‘end of pipe’ PM filters, but might also emit additional ammonia and odour. This study aimed to gain insight into this matter (parts A and B) and into the perspective of two strategies to reduce additional emissions: (1) by pre-drying the manure on the belts inside the house (part C), and (2) by reducing manure accumulation time (MAT) in the house to 24-h followed by rapid drying inside the MDT (part D). This study was set up as an emission survey at 16 laying hen farms with a MDT. Results from parts A through C showed that PM 10 removal efficiency of the MDTs increases linearly with manure layer thickness: from about 35% at 4 cm to 84% at 17 cm. Ammonia and odour concentrations in the drying air increased substantially upon passing the manure layers, from on average 5.5 to 13.9 ppm ammonia and from 822 to 1178 OU E m −3 . In part C, ammonia emission decreased with increasing DM content of the manure, but even at DM content levels beyond 50%, substantial ammonia emission remained. In part D, the emission rates of houses and MDTs together were 44% lower for PM 10 , 20% higher for ammonia, and 40% higher for odour compared with the theoretical situation of the houses without MDT. Further shortening MAT to 18, 12, or 6 h might be needed to reduce emissions from MDTs

Comparison of CO2- and SF6- based tracer gas methods for the estimation of ventilation rates in a naturally ventilated dairy barn

Livestock production is a source of numerous environmental problems caused by pollutant gas emissions. In naturally ventilated buildings, estimating air flow rate is complicated due to changing climatic conditions and the difficulties in identifying inlets and outlets. To date no undisputed reference measurement method has been identified. The objective of this paper was to compare CO2- and SF6-based tracer gas methods for the estimation of ventilation rates (VRCO2 vs. VRSF6 ) in naturally ventilated dairy barns both under conventional and very open ventilation situations with different spatial sampling strategies. Measurements were carried out in a commercial dairy barn, equipped with an injection system for the controlled release of SF6, and measurement points for the monitoring of SF6 and CO2 concentrations to consider both horizontal and vertical variability. Methods were compared by analysing daily mean VRCO2 /VRSF6 ratios. Using the average gas concentration over the barn length led to more accurate ventilation rates than using one single point in the middle of the barn. For conventional ventilation situations, measurements in the ridge seem to be more representative of the barn average than in the middle axis. For more open situations, both VRCO2 and VRSF6 were increased, VRCO2 /VRSF6 ratios being also more variable. Generally, both methods for the estimation of ventilation rates gave similar results, being 10–12% lower with the CO2 mass balance method compared to SF6 based measurements. The difference might be attributed to potential bias in both methods