A software developed to study the odours dispersion is presented. This tool is developed based on Hogstrom theory of odours dispersion of puff emissions applied to Gaussian models. Concentration peaks are taken into account. ODODIS (Odours Dispersion Software) propose nine options within the Gaussian domain to explore different solutions for atmospheric dispersion problems for odorous as well as odourless gases using different input such as g\/s, ppb and UO (unit odour). Testing for data collection and validation of the software has been done with a normal scale odour source (chimney giving off given concentrations of acetone, a gas easily measured) to control the emission and meteorological data acquisition station. Sampling collections were done at different locations few meters to the source and a data base could be developed. Simulation were done with the software to verify the ability of the nine solutions to evaluate correctly the concentrations at the sampling points. Two of the nine solutions proposed give interesting results that demonstrated that such application of gaussian models can be satisfactory in estimating dispersion patterns rapidly.<\/p>\n
This research is interesting because data collection was done and a data base could be done to validate the proposed models. The use of a gas as source simplify the data collection because the gas concentration evaluation is more easy and rapid than odour quantification. Further work done directly with odour would substantiate this project.<\/p>\n","protected":false},"excerpt":{"rendered":"
A software developed to study the odours dispersion is presented. This tool is developed based on Hogstrom theory of odours dispersion of puff emissions applied to Gaussian models. Concentration peaks are taken into account. ODODIS (Odours Dispersion Software) propose nine options within the Gaussian domain to explore different solutions for atmospheric dispersion problems for odorous […]<\/p>\n","protected":false},"author":1,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[9],"tags":[8882,10033,19712,1701,23694,696,4663,313,314,1761,316,13370,1675,2897,615,795,198,199,200,202,3465,15459,16262,13636,1240,14980,1020,20911,4874,1579,6053,2481],"class_list":["post-1716","post","type-post","status-publish","format-standard","hentry","category-environment","tag-al","tag-arc","tag-de-melo-lisboa-h-dispersion-atmospherique","tag-dilution","tag-dir","tag-dispersion","tag-don","tag-emission","tag-emissions","tag-estimation","tag-gas","tag-ken","tag-location","tag-mating","tag-model","tag-models","tag-odor","tag-odors","tag-odour","tag-odours","tag-pea","tag-ped","tag-pl","tag-project","tag-research","tag-search","tag-software","tag-t","tag-tan","tag-test","tag-use","tag-work"],"_links":{"self":[{"href":"http:\/\/prairieswine.com\/rsc\/wp-json\/wp\/v2\/posts\/1716","targetHints":{"allow":["GET"]}}],"collection":[{"href":"http:\/\/prairieswine.com\/rsc\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"http:\/\/prairieswine.com\/rsc\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"http:\/\/prairieswine.com\/rsc\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"http:\/\/prairieswine.com\/rsc\/wp-json\/wp\/v2\/comments?post=1716"}],"version-history":[{"count":0,"href":"http:\/\/prairieswine.com\/rsc\/wp-json\/wp\/v2\/posts\/1716\/revisions"}],"wp:attachment":[{"href":"http:\/\/prairieswine.com\/rsc\/wp-json\/wp\/v2\/media?parent=1716"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"http:\/\/prairieswine.com\/rsc\/wp-json\/wp\/v2\/categories?post=1716"},{"taxonomy":"post_tag","embeddable":true,"href":"http:\/\/prairieswine.com\/rsc\/wp-json\/wp\/v2\/tags?post=1716"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}