Estimating greenhouse gas emissions from land-applied biosolids in Canada: A mathematical modelling approach
Notice bibliographique
Résumé
Municipal wastewater biosolids are increasingly used to fertilize crops on Canadian farmland with the attendant effect of greenhouse gas (GHG) emissions. As part of their national inventories to the United Nations Framework Convention on Climate Change, countries are required to estimate GHG emissions from the land application of biosolids and report them using Intergovernmental Panel on Climate Change (IPCC) protocols. However, Canada currently does not have N2O emission factors to accurately model emissions from biosolids because of scarce empirical data. This study therefore measured emissions, generated emissions factors, and refined models of biosolids-induced GHG emissions to improve Canada’s national GHG inventory. To do this, laboratory and field experiments were used to assess three types of biosolids (i.e., composted, mesophilic anaerobically digested called “digested”, and alkaline-stabilized). In an incubation experiment, soil samples were amended with the three biosolids to assess the rate of C and N mineralization under 29% and 49% water-filled pore space (WFPS) soil moisture conditions. Under 49% WFPS, 79%, 52%, and 8% of C was mineralized in the digested, alkaline-stabilized, and composted biosolids, respectively. A first-order mathematical equation was fitted to the cumulative CO2-C and N2O-N emissions data, with R2 > 0.98 and p < 0.05. This study also highlighted the potential of composted biosolids to sequester carbon in soil and mitigate soil N2O emissions. The results of this experiment helped to calibrate the DeNitrification and DeComposition (DNDC) model to simulate C and N dynamics in a biosolids-fertilized corn (Zea mays L.) field in Quebec from 2017 to 2019. Pearson’s correlation coefficients between measured and simulated data ranged between 0.3 and 0.8 for crop yield, daily and cumulative CO2 and N2O emissions, and soil organic carbon, while being 0.1 for total soil N. In addition to the Quebec (mixed wood plains) site, DNDC was then used to simulate N2O emissions from two other sites in Nova Scotia (Atlantic maritime) and Alberta (prairie). Overall, N2O emissions were highest for digested biosolids and overall emissions were influenced by site-specific factors, with emissions magnitudes following the order: Quebec > Nova Scotia > Alberta. The DNDC simulations were contrasted with IPCC Tier 1 and Tier 2 methods, and root mean-square error and coefficient of determination values between measured and simulated values showed that the DNDC (Tier 3) approach was more accurate than the Tier 1 and 2 methods. Empirically derived correction factors for each of the biosolids were proposed to improve the accuracy of Tier 2 method, which fits the proposed update to the Canadian GHG inventory methodology.This study resulted in improved estimates of biosolids-induced N2O emissions from Canadian farmlands, with the option to use an improved Tier 2 method to report such emissions in the national GHG inventory until the Tier 3 method is implemented
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,001 | 0,001 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,001 |
| Méta-épidémiologie (sens large) | 0,000 | 0,001 |
| Bibliométrie | 0,001 | 0,002 |
| Études des sciences et des technologies | 0,001 | 0,001 |
| Communication savante | 0,001 | 0,001 |
| Science ouverte | 0,002 | 0,001 |
| Intégrité de la recherche | 0,001 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,001 | 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 source (Gemma direct ou Codex distillé), 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 ».