Measuring gas emissions from livestock buildings: A review on uncertainty analysis and error sources - Calvet, Salvador; Gates, Richard S.; Zhang, GuoQiang; Estellés, Fernando; Ogink, Nico W.M.; Pedersen, Søren; Berckmans, Daniel (Biosystems engineering, 2013)
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. ► Recent research on uncertainties of emissions measured in animal houses is reviewed. ► For mechanical ventilation, errors can be quantified and reduced to acceptable levels. ► For natural ventilation, errors are higher and significant biases may be committed. ► Error analysis is critical for sound conclusions and to establish research priorities.