TOWARD A SCIENCE-BASED AGRICULTURAL ODOUR PROGRAM FOR ONTARIO: A COMPARISON OF THE MDS AND OFFSET ODOUR SETBACK SYSTEMS
Notice bibliographique
Résumé
Ontario has a long history of using prescribed separation distances to minimize nuisance disturbances related to odours from livestock facilities. The Minimum Distance Separation (MDS) system is an experiential, empirically based system that has been used to effectively minimized livestock related odour complaints for over 25 years. Odour complaints are rare where livestock facilities are properly managed and sited using MDS. In spite of its effectiveness, MDS is coming under increasing criticism from both farmers and the public as follows:<br><br>--It is subjective and not based on clear, documented scientific data<br><br>--It is cumbersome and difficult to use and understand<br><br>--The MDS expansion factor is confusing and appears to allow uncontrolled livestock operation<br><br>--MDS is outdated and unable to predict adequate separation distances for the newer, larger barns<br><br>--MDS unable to quantitatively account for odour control technologies, such as biofilters and manure treatment systems<br><br>The livestock unit (LU) based MDS system is unable to predict separation distances for independent manure storage processing facilities and other agricultural odour sources where no animals are present.<br><br>These criticisms have lead Ontario to initiate a program to reevaluate the MDS system. A first step toward modifying the MDS system is to develop analytical comparisons with some of the more science-based odour emissions models to allow calibration of the MDS curves. This paper compares separation distance predicted by MDS to those predicted by Minnesotas Odour From Feedlot Setback Estimation Tool (OFFSET). The OFFSET model was developed using real odour emissions data and dispersion modeling techniques. To allow reasonable comparisons the OFFSET model was calibrated to Ontarios climatic conditions and calculations were made using both systems under similar construction and management regimes for swine, poultry, dairy and beef cattle facilities. Results from the two separation distance models were compared using 93% and 96% annoyance-free criteria from the OFFSET model to emulate the MDS nearest single neighbor and high occupancy/sensitive land use criteria, respectively. Results of the comparison show that MDS separation distances compare favorably to those from the more science-based OFFSET model. Where under-barn manure storage was used, only large (> 10,000 animals) SEW weaner barns were shown to be sited too close to neighboring land uses by the MDS methodology. Where, manure was stored in uncovered, exterior storage systems only finishing and farrow-to-finish hog operations consistently meet the selected OFFSET annoyance-free criteria when sited using the MDS system. It was concluded that work is needed to verify and modify the MDS system to increase public confidence and improve the utility of the MDS system. The MDS expansion factor needs to be verified and a mechanism to account for odourcontrol technologies should be developed. Future research should be collaborative to improve research efficiencies and improve public acceptance of the system.
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Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,000 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».