Using airborne technology to quantify and apportion emissions of CH4 and NH3 from feedlots

Jorg Hacker, Deli Chen, Mei Bai, Cacilia Ewenz, Wolfgang Junkermann, Wolfgang Lieff, Barry McManus, Bruno Neininger, Jianlei Sun, Trevor Coates, Tom Denmead, Thomas Flesch, Sean McGinn, Julian Hill

    Research output: Contribution to journalArticlepeer-review

    19 Citations (Scopus)


    A novel airborne approach using the latest technology in concentration measurements of methane (CH4) and ammonia (NH3), with quantum cascade laser gas analysers (QCLAs) and high-resolution wind, turbulence and other atmospheric parameters integrated into a low- and slow-flying modern airborne platform, was tested at a 17000 head feedlot near Charlton, Victoria, Australia, in early 2015. Aircraft flights on 7 days aimed to define the lateral and vertical dimensions of the gas plume above and downwind of the feedlot and the gas concentrations within the plume, allowing emission rates of the target gases to be calculated. The airborne methodology, in the first instance, allowed the emissions to be qualitatively apportioned to individual rows of cattle pens, effluent ponds and manure piles. During each flight, independent measurements of emissions were conducted by ground-based inverse-dispersion and eddy covariance techniques, simultaneously. The aircraft measurements showed good agreement with earlier studies using more traditional approaches and the concurrent ground-based measurements. It is envisaged to use the aircraft technology for determining emissions from large-scale open grazing farms with low cattle densities. Our results suggested that this technique is able to quantify emissions from various sources within a feedlot (pens, manure piles and ponds), as well as the whole feedlot. Furthermore, the airborne technique enables tracing emissions for considerable distances downwind. In the current case, it was possible to detect elevated CH4 to at least 25 km and NH3 at least 7 km downwind of the feedlot.

    Original languageEnglish
    Pages (from-to)190-203
    Number of pages14
    JournalAnimal Production Science
    Issue number3
    Publication statusPublished - 2016


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