Search

The tracer gas ratio method, using CO2 as natural tracer, has been suggested as a pragmatic option to measure emissions from naturally ventilated (NV) barns without the need to directly estimate the ventilation rate. The aim of this research was to assess the performance of a low-cost Non-Dispersive Infra-Red (NDIR) sensor for intensive spatial field monitoring of CO2 concentrations in a NV dairy cow house. This was achieved by comparing NDIR sensors with two commonly applied methods, a Photo-Acoustic Spectroscope (PAS) Gas Monitor and an Open-Path laser (OP-laser). First, calibrations for the NDIR sensors were obtained in the laboratory. Then, the NDIR sensors were placed in a dairy cow barn for comparison with the PAS and OP-laser methods. The main conclusions were: (a) in order to represent the overall barn CO 2 concentration of the dairy cow barn, the number of NDIR sensors to be accounted for average concentration calculation was dependent on barn length and on barn area occupation; and (b) the NDIR CO2 sensors are suitable for multi-point monitoring of CO2 concentrations in NV livestock barns, being a feasible alternative for the PAS and the OP-laser methods to monitor single-point or averaged spatial CO2 concentrations in livestock barns. [ABSTRACT FROM AUTHOR]

Inverse dispersion techniques are used to infer the emission rate of gas sources from concentration measurements and dispersion model calculations. Criteria for the selection of measurement intervals having wind conditions conducive to technique accuracy are examined on the basis of a short range tracer experiment. By introducing a supplementary condition that the measured vertical temperature gradient be quantitatively compatible with Monin–Obukhov similarity theory, it was possible to use a less stringent threshold for the friction velocity than has previous been used ( u * ≥ 0.05 m s −1 instead of ≥0.15 m s −1 ). Under the new criteria a larger proportion of measurement intervals are retained (76% versus 49%), while the ratio of inferred to actual emission rate Q LS / Q exhibits negligible bias (average Q LS / Q = 1.00) and an acceptably small level of random error (interval-to-interval standard deviation σ Q / Q = 0.25). [ABSTRACT FROM AUTHOR]

Highlights: [•] Emissions from dairy farms (<100 cows) were measured using bLS and open-path sensors. [•] Implied enteric methane conversion factor (Y m ) was lower than the IPCC default value. [•] Liquid manure contributed from 0% (empty) to 60% (full) of the whole farm emissions. [•] Emissions from barns and manure were partitioned consistently by two bLS approaches. [•] Research is needed to describe temporal emission trends from manure through the year. [Copyright &y& Elsevier]

Abstract: Dispersion techniques are useful for assessing the effectiveness of management practices in mitigating methane (CH4) emissions from animal operations. In this paper, the accuracy of an inverse-dispersion technique was examined for two common situations: 1) emissions from animals in a barn and 2) emissions from animals in a pen. For both situations, the accuracy of emission estimates generally increased with increasing fetch (scaled to barn height, h, or to pen width, X s) between the source and the concentration measurement. The gas recovery ratio increased from 0.66 at 5 h to 0.93–1.03 at 10 h–25 h for the barn, and decreased from 1.59 at 0 X s to 0.99 at 5 X s and from 1.54 at 0 X s to 1.09 at 5 X s for the two small pen scenarios, due to the declining sensitivity of the dispersion model to errors in wind complexity and errors in the assumed source configuration. However, the relative uncertainty of the measured concentration increased with fetch due to the decreasing gas concentrations. Hence, improving the accuracy of emission estimates is a compromise between the source configuration sensitivity and the concentration measurement sensitivity. Fetches of about twice the size of the pen and about 10 times the height of the barn are suggested. [Copyright &y& Elsevier]

Abstract: Continuous measurements of methane (CH4) emissions from agricultural facilities over a period of several days are needed to assess the mitigation effectiveness of management practices. In this study, we examined the feasibility of using an inverse dispersion technique (backward Lagrangian Stochastic model, bLS) for obtaining 15-min averages of CH4 emissions over a period of 5 days in the Ottawa area. Using two open-path lasers and pan-tilt scanning units, a ground level source was enclosed to measure the CH4 emissions (Q) with any wind direction. After application of the recommended data quality criteria screening for low friction velocity and extreme atmospheric stability, the average recovery (ratio of estimates Q bLS to Q) was 1.09 with a standard deviation of 0.45. We observed a tendency in the recovery results toward underestimation during unstable stratification and overestimation during stable stratification. Using a test on developed turbulence instead of a fixed friction velocity threshold improved the accuracy of the emission estimates slightly. An additional data quality criterion based on the standard deviation output of the bLS model led to a significant improvement with a recovery of 1.00 and a standard deviation of 0.30. A strategy for averaging the resulting incomplete dataset is discussed. An assessment of the applicability of this approach to farm-size facilities led to the conclusion that this technique is suitable to determine emissions from realistic CH4 sources, such as dairy cattle barns, continuously in order to characterize both seasonal and diurnal characteristics of CH4 emissions. [Copyright &y& Elsevier]

The accurate measurement of greenhouse gas emissions is a challenge for atmospheric science. Long-range open-path sensors are flexible enough to be applied to a variety of complex emission sources, and single devices are often used to measure both high and low path-integrated concentrations. As this technology develops, it is important to examine potential sources of inaccuracy. A GasFinder3 open-path laser was tested with a range of path-integrated concentrations from 11.7 to 182 ppm∙m CH4 using certified standard gases. The measured path-integrated concentrations had a positive bias which was higher than 10% at low path-integrated concentrations (<50 ppm∙m) with a declining trend expected to be under 2% at 200 ppm∙m. A linear equation was used to correct the measured path-integrated concentrations to fit the expected values. After correction, the average bias was reduced to −0.36% and there was no relationship with path-integrated concentration. A relative bias less than ±3% was achieved above ca. 150 ppm∙m with or without calibration. Measurement campaigns may reduce error by increasing path lengths to maximize path-integrated concentration. When low path-integrated concentrations are expected, calibration over the expected range is beneficial. [ABSTRACT FROM AUTHOR]

• First time of using the bLS technique to measure NH 3 emission from greenhouses. • Determination of the measurement height is critical for the calculation. • Source area accuracy has minor impact on the total emission estimates. • The bLS has a good potential to quantify NH 3 from vegetable greenhouses. China's greenhouse vegetable production is considered an important contributor to the national ammonia (NH 3) inventory because of the excess nitrogen (N) application rate (normally over 1000 N kg ha−1 yr−1) and large N consumption (approximately 10% of the N fertilizer in China). However, the previously measured emission rates are still in question because of the inherent limits of the commonly used techniques (e.g., non-flow-through chamber technique) and the exclusion of the impact of the greenhouse opening/enclosing scheme on NH 3 loss from greenhouse soil to the atmosphere over a growing season. This study examines the ability of an inverse dispersion technique, in combination with an open-path laser system, for measuring NH 3 emissions from vegetable greenhouses. The NH 3 concentrations over the greenhouse areas greatly exceeded the laser's detectable limit and showed a clear diel variation pattern. Determination of the area and height of the greenhouse sources are critical to emission estimates, while removing the periods with inaccurate wind simulations has minimal effect on the daily and total emission estimations since the omitted periods mainly occurred during nighttime (low emission periods). With the application of our findings, the observed diel NH 3 emission patterns are found in good agreement with the air temperature. The NH 3 -N losses during the measurements in terms of proportions to the N fertilization (40.02% in spring, 7.83% in summer) are generally comparable to those of previous studies. Overall, the inverse dispersion technique can be used to provide good NH 3 emission estimates as well as to assess NH 3 emission factors along the opening/enclosing scheme across a growing season of greenhouse vegetables in the future. [ABSTRACT FROM AUTHOR]