1b:I[76749,["/_next/static/chunks/bf18fea59be6d5b1.js","/_next/static/chunks/1ba21a8e081e29d1.js","/_next/static/chunks/0383663887945ae7.js","/_next/static/chunks/2060b26370dc6c0a.js","/_next/static/chunks/dda00c7627406bba.js","/_next/static/chunks/8ddf2550f38c2f2a.js","/_next/static/chunks/5bf36002c846d2d8.js"],"default"] 1c:I[3486,["/_next/static/chunks/bf18fea59be6d5b1.js","/_next/static/chunks/1ba21a8e081e29d1.js","/_next/static/chunks/0383663887945ae7.js","/_next/static/chunks/2060b26370dc6c0a.js","/_next/static/chunks/dda00c7627406bba.js","/_next/static/chunks/8ddf2550f38c2f2a.js","/_next/static/chunks/5bf36002c846d2d8.js"],"default"] 1d:I[17707,["/_next/static/chunks/bf18fea59be6d5b1.js","/_next/static/chunks/1ba21a8e081e29d1.js","/_next/static/chunks/0383663887945ae7.js","/_next/static/chunks/2060b26370dc6c0a.js","/_next/static/chunks/dda00c7627406bba.js","/_next/static/chunks/8ddf2550f38c2f2a.js","/_next/static/chunks/5bf36002c846d2d8.js"],"default"] 1e:I[66528,["/_next/static/chunks/bf18fea59be6d5b1.js","/_next/static/chunks/1ba21a8e081e29d1.js","/_next/static/chunks/0383663887945ae7.js","/_next/static/chunks/2060b26370dc6c0a.js","/_next/static/chunks/dda00c7627406bba.js","/_next/static/chunks/8ddf2550f38c2f2a.js","/_next/static/chunks/5bf36002c846d2d8.js"],"default"] 1f:I[63176,["/_next/static/chunks/bf18fea59be6d5b1.js","/_next/static/chunks/1ba21a8e081e29d1.js","/_next/static/chunks/0383663887945ae7.js","/_next/static/chunks/2060b26370dc6c0a.js","/_next/static/chunks/dda00c7627406bba.js","/_next/static/chunks/8ddf2550f38c2f2a.js","/_next/static/chunks/5bf36002c846d2d8.js"],"default"] 20:I[87099,["/_next/static/chunks/bf18fea59be6d5b1.js","/_next/static/chunks/1ba21a8e081e29d1.js","/_next/static/chunks/0383663887945ae7.js","/_next/static/chunks/2060b26370dc6c0a.js","/_next/static/chunks/dda00c7627406bba.js","/_next/static/chunks/8ddf2550f38c2f2a.js","/_next/static/chunks/5bf36002c846d2d8.js"],"default"] 21:I[26200,["/_next/static/chunks/bf18fea59be6d5b1.js","/_next/static/chunks/1ba21a8e081e29d1.js","/_next/static/chunks/0383663887945ae7.js","/_next/static/chunks/2060b26370dc6c0a.js","/_next/static/chunks/dda00c7627406bba.js","/_next/static/chunks/8ddf2550f38c2f2a.js","/_next/static/chunks/5bf36002c846d2d8.js"],"Group"] 22:I[23365,["/_next/static/chunks/bf18fea59be6d5b1.js","/_next/static/chunks/1ba21a8e081e29d1.js","/_next/static/chunks/0383663887945ae7.js","/_next/static/chunks/2060b26370dc6c0a.js","/_next/static/chunks/dda00c7627406bba.js","/_next/static/chunks/8ddf2550f38c2f2a.js","/_next/static/chunks/5bf36002c846d2d8.js"],"default"] 23:T42f,Hydrogen sulfide (H₂S) represents one of the main odorant gases emitted from sewer networks. A mathematical model can be a fast and low-cost tool for estimating its emission. This study investigates two approaches to modeling H₂S gas transfer at a waterfall in a discharge manhole. The first approach is based on an adaptation of oxygen models for H₂S emission at a waterfall and the second consists of a new model. An experimental set-up and a statistical data analysis allowed the main factors affecting H₂S emission to be studied. A new model of the emission kinetics was developed using linear regression and taking into account H₂S liquid concentration, waterfall height and fluid velocity at the outlet pipe of a rising main. Its prediction interval was estimated by the residual standard deviation (15.6%) up to a rate of 2.3 g H₂S·h^-1. Finally, data coming from four sampling campaigns on sewer networks were used to perform simulations and compare predictions of all developed models.

Laetitia Hatrait

Publications