Hostname: page-component-78c5997874-ndw9j Total loading time: 0 Render date: 2024-11-10T05:29:47.072Z Has data issue: false hasContentIssue false
  • English
  • Français

Developments in micrometeorological methods for methane measurements

Published online by Cambridge University Press:  06 June 2013

S. M. McGinn
S. M. McGinn*
Affiliation:
Agriculture and Agri-Food Canada, 5403 – 1 Avenue South, PO Box 3000, Lethbridge, Alberta, Canada T1J 4B1
*
†E-mail: sean.mcginn@agr.gc.ca
Get access

Abstract

Micrometeorological techniques can be applied to estimate methane (CH4) emissions from ruminants and livestock manure using CH4 concentration measured within the internal surface boundary layer. The main advantage of these techniques is that they are non-intrusive, thereby eliminating the impact of the measurement set-up on the calculated CH4 emission. This review focuses on four micrometeorological techniques, namely, the integrated horizontal flux (IHF), flux gradient (FG), eddy covariance (EC) and the dispersion modelling using the backward Lagrangian stochastic method (BLS). Each technique has unique advantages and limitations when used for estimating enteric (ruminant) and manure CH4 emissions. The IHF technique may be theoretically simpler then the FG, EC or BLS techniques, but all require high-resolution instruments to measure concentration. The EC and BLS techniques also require a measurement of the wind statistics. This review discusses the appropriate use of these four micrometeorological techniques for estimating CH4 emissions in animal agriculture and the recent advances in measurement technology.

Keywords

methanemicrometeorologytechniquelivestockmanure
Type
Full Paper
Information
animal , Volume 7 , Issue s2: Greenhouse Gases & Animal Agriculture Conference (GGAA 2013), 23rd ‐ 26th June 2013, Dublin, Ireland , June 2013 , pp. 386 - 393
Copyright
Copyright © Her Majesty the Queen in Right of Canada, as represented by the Minister of Agriculture and Agri-Food Canada 2013 

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

Baldocchi, D, Detto, M, Sonnentag, O, Verfaillie, J, Teh, YA, Silver, W, Kelly, NM 2012. The challenges of measuring methane fluxes and concentrations over a peatland pasture. Agricultural and Forest Meteorology 153, 177–187.Google Scholar
Baum, KA, Ham, JM, Brunsell, NA, Coyne, PI 2008. Surface boundary layer of cattle feedlots: implications for air emissions measurement. Agricultural and Forest Meteorology 148, 1882–1893.Google Scholar
Bjorneberg, DL, Leytem, AB, Westermann, DT, Griffiths, PR, Shao, L, Pollard, MJ 2009. Measurements of atmospheric ammonia, methane, and nitrous oxide at a concentrated dairy production facility in southern Idaho using open-path FTIR spectrometry. Transactions of the ASABE 52, 1749–1756.Google Scholar
Broadi, DA, Benchaar, C, Chiquette, J, Massé, D 2004. Mitigation strategies to reduce enteric methane emissions from dairy cows: update review. Canadian Journal of Animal Science 84, 319–335.Google Scholar
Clark, H 2013. Nutritional and host effects on methanogenesis in the grazing ruminant. Animal 7 (suppl. 1), 41–48.Google Scholar
Dengel, S, Levy, PE, Grace, J, Jones, SK, Skiba, UM 2011. Methane emissions from sheep pasture, measured with an open-path eddy covariance system. Global Change Biology 17, 3524–3533.Google Scholar
Denmead, OT 2008. Approaches to measuring fluxes of methane and nitrous oxide between landscapes and the atmosphere. Plant Soil 309, 5–24.Google Scholar
Detto, M, Verfaillie, J, Anderson, F, Xu, L, Baldocchi, D 2011. Comparing laser-based open- and closed-path gas analyzers to measure methane fluxes using the eddy covariance method. Agriculture and Forest Meteorology 151, 1312–1324.Google Scholar
Flesch, TK, Prueger, JH, Hatfield, JL 2002. Turbulent Schmidt number from a tracer experiment. Agricultural and Forest Meteorology 111, 299–307.Google Scholar
Flesch, TK, Wilson, JD, Harper, LA, Crenna, BP 2005. Estimating gas emissions from a farm with an inverse-dispersion technique. Atmospheric Environment 39, 4863–4874.CrossRefGoogle Scholar
Flesch, TK, Harper, LA, Powell, JM, Wilson, JD 2009. Inverse-dispersion calculation of ammonia emission from Wisconsin dairy farms. Transactions of the ASABE 52, 253–265.Google Scholar
Flesch, TK, Wilson, JD, Harper, LA, Crenna, BP, Sharpe, RR 2004. Deducing ground-air emissions from observed trace gas concentrations: a field trial. Journal of Applied Meteorology 43, 487–502.Google Scholar
Flesch, TK, McGinn, SM, Chen, D, Wilson, JD, Desjardins, RL 2013. Data filtering for BLS calculation of emissions rates: improvements to increase data retention. Advances in Animal Biosciences, Proceedings of the Greenhouse Gases and Animal Agriculture Conference, Dublin, lreland.Google Scholar
Gao, Z, Desjardins, RL, Flesch, TK 2009. Comparison of a simplified micrometeorological mass difference technique and an inverse dispersion technique for estimating methane emissions from small area sources. Agricultural and Forest Meteorology 149, 891–898.Google Scholar
Gao, Z, Yuan, H, Ma, W, Liu, XJ, Desjardins, RL 2011. Methane emissions from a dairy feedlot during the fall and winter seasons in northern China. Environmental Pollution 159, 1183–1189.CrossRefGoogle Scholar
Grainger, C, Clarke, T, McGinn, SM, Auldist, MJ, Beauchemin, KA, Hannah, MC, Waghorn, GC, Clark, H, Eckard, RJ 2007. Methane emissions from dairy cows measured using the sulfur hexafluoride (SF6) tracer and chamber techniques. Journal of Dairy Science 90, 2755–2766.CrossRefGoogle ScholarPubMed
Griffith, D, Bryant, GR, Hsu, D, Reisinger, AR 2008. Methane emissions from free-ranging cattle: Comparison of tracer and integrated horizontal flux techniques. Journal of Environmental Quality 37, 582–591.Google Scholar
Harper, LA, Denmead, OT, Flesch, TK 2011. Micrometeorological techniques for measurement of enteric greenhouse gas emissions. Animal Feed Science and Technology 166–167, 227–239.Google Scholar
Harper, LA, Flesch, TK, Weaver, KH, Wilson, JD 2010. The effect of biofuel production on swine farm methane and ammonia emissions. Journal of Environmental Quality 39, 1984–1992.Google Scholar
Harper, LA, Flesch, TK, Powell, JM, Coblentz, WK, Jokela, WE, Martin, NP 2009. Ammonia emissions from dairy production in Wisconsin. Journal of Dairy Science 92, 2326–2337.Google Scholar
Hsieh, C, Katul, G, Chi, T 2000. An approximate analytical model for footprint estimation of scalar fluxes in thermally stratified atmospheric flows. Advances in Water Resources 23, 765–772.Google Scholar
Judd, MJ, Kelliher, FM, Ulyatt, MJ, Lassey, KR, Tate, KR, Shelton, ID, Harvey, MJ, Walker, CF 1999. Net methane emissions from grazing sheep. Global Change Biology 5, 647–657.CrossRefGoogle Scholar
Kaimal, JC, Finnigan, JJ 1994. Atmosphere boundary layer flows: their structure and measurements, pp 234–240. Oxford University Press, New York, USA.CrossRefGoogle Scholar
Laubach, J, Kelliher, FM 2005. Measuring methane emission rates of a dairy cow herd (II): results from a backward-Lagrangian stochastic model. Agricultural and Forest Meteorology 129, 137–150.Google Scholar
Laubach, J, Kelliher, FM, Knight, TW, Clark, H, Molano, G, Cavanagh, A 2008. Methane emissions from beef cattle – acomparison of paddock- and animal-scale measurements. Australian Journal Experimental Agriculture 48, 132–137.Google Scholar
Makkar, HPS, Vercoe, PE 2007. Measuring methane production from ruminants. Springer, Dordrecht, The Netherlands.CrossRefGoogle Scholar
McBain, MC, Desjardins, RL 2005. The evaluation of a backward Lagranfian stochastic (BLS) model to estimate greenhouse gas emissions from agriculture sources using a synthetic tracer source. Agricultural anf Forest Meteorology 135, 61–72.CrossRefGoogle Scholar
McGinn, SM 2006. Measuring greenhouse gas emissions from point sources in agriculture. Canadian Journal of Soil Science 86, 355–371.Google Scholar
McGinn, SM, Beauchemin, KA 2012. Dairy farm methane emissions using a dispersion model. Journal of Environmental Quality 41, 73–79.CrossRefGoogle ScholarPubMed
McGinn, SM, Flesch, TK, Harper, LA, Beauchemin, KA 2006. An approach for measuring methane emissions from whole farms. Journal of Environmental Quality 35, 14–20.Google Scholar
McGinn, SM, Beauchemin, KA, Flesch, TK, Coates, T 2009. Performance of a dispersion model to estimate methane loss from cattle in pens. Journal of Environmental Quality 38, 1796–1802.Google Scholar
McGinn, SM, Turner, D, Tomkins, N, Charmley, E, Bishop-Hurley, G, Chen, D 2011. Methane emissions from grazing cattle using point-source dispersion. Journal of Environmental Quality 40, 22–27.Google Scholar
Monteith, JL 1973. Principles of environmental physics. William Clowes and Sons Limited, London.Google Scholar
Munro, DS, Oke, TR 1975. Aerodynamic boundary-layer adustment over a crop in neutral stability. Boundary Layer Meteorology 9, 53–61.CrossRefGoogle Scholar
National Research Council 2003. Air emissions from animal feeding operations: current knowledge, future needs. The National Academies Press, Washington, DC.Google Scholar
Neftel, A, Fischer, C, Flechard, C 2006. Measurements of greenhouse gas fluxes from agriculture. In Greenhouse gases and animal agriculture: an update (ed. CR Soliva, J Takahashi and M Kreuzer), pp. 3–12. Elsevier, Amsterdam.Google Scholar
Nordbo, A, Katul, G 2013. A wavelet-based correction method for eddy-covariance high-frequency losses in scalar concentration measurements. Boundary Layer Meteorology 146, 81–102.Google Scholar
O'Mara, FP 2011. The significance of livestock as a contributor to global greenhouse gas emissions today and in the near future. Animal Feed Science and Technology 166–167, 7–15.CrossRefGoogle Scholar
Park, K-H, Wagner-Riddle, C, Gordon, RJ 2010. Comparing methane fluxes from stored liquid manure using micrometeorological mass balance and floating chamber methods. Agricultural and Forest Meteorology 150, 175–181.Google Scholar
Peltola, O, Mammarella, I, Haapanala, S, Burba, G, Vesala, T 2012. Field intercomparison of four methane gas analysers suitable for eddy covariance flux measurements. Biogeosciences Discussions 9, 17651–17706.Google Scholar
Ro, KS, Johnson, MH, Hunt, PG, Flesch, TK 2011. Measuring trace gas emission from multi-distributed sources using vertical radial plume mapping (VRPM) and backward Lagrangian stochastic (BLS) techniques. Atmosphere 2, 553–566.Google Scholar
Ryden, JC, McNeill, JE 1984. Application of the micrometorological mass balance method to the determination of ammonia loss from a grazed sward. Journal of the Science of Food and Agriculture 35, 1297–1310.Google Scholar
Schuepp, PH, Leclerc, MY, MacPhereson, JI, Desjardins, RL 1990. Fooprint prediction of scalar fluxes from analytical solutions of the diffusion equation. Boundary Layer Meteorology 50, 355–373.Google Scholar
Smith, P, Matino, D, Cai, Z, Gwary, D, Janzen, H, Kumar, P, McCarl, B, Ogle, S, O'Mara, F, Rice, C, Scholes, B, Sirotenko, O, Howden, M, McAllister, T, Pan, G, Romanenkov, V, Schneidere, U, Towprayoon, S 2007. Policy and technological constraints to implementation of greenhouse gas mitigation options in agriculture. Agriculture, Ecosystems and Environment 118, 6–28.Google Scholar
Storm, IMLD, Hellwing, ALF, Nielsen, NI, Madsen, J 2012. Methods for measuring and estimating methane emission from ruminants. Animals 2, 160–183.Google Scholar
Todd, RW, Cole, NA, Casey, KD, Hagevoort, R, Auvermann, BW 2011. Methane emissions from southern high plains dairy wastewater lagoons in the summer. Animal Feed Science and Technology 166–167, 575–580.Google Scholar
Tomkins, NW, McGinn, SM, Turner, DA, Charmley, E 2011. Comparison of open-circuit respiration chambers with a micrometeorological method for determining methane emissions from beef cattle grazing a tropical pasture. Animal Feed Science and Technology 166–167, 240–247.Google Scholar
van Haarlem, RP, Desjardins, RL, Gao, Z, Flesch, TK, Li, X 2008. Methane and ammonia emissions from a beef feedlot in western Canada for a twelve-day period in the fall. Canadian Journal of Animal Science 88, 641–649.Google Scholar
VanderZaag, AC, Wagner-Riddle, C, Park, K-H, Gordon, RJ 2011. Methane emissions from stored liquid dairy manure in a cold climate. Animal Feed Science and Technology 166–167, 581–589.Google Scholar
Vesala, T, Kljun, N, Rannik, U, Rinne, J, Sogachev, A, Markkanen, T, Sabelfelt, K, Foken, Th, Leclerc, MY 2008. Flux and concentration footprint modelling: state of the art. Environmental Pollution 152, 653–666.Google Scholar