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Record W4408286962 · doi:10.1016/j.wmb.2025.100193

Optimizing drying of municipal dewatered sludge using heat-assisted microorganisms and pig manure addition: A process and economic analysis

2025· article· en· W4408286962 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueWaste Management Bulletin · 2025
Typearticle
Languageen
FieldEnvironmental Science
TopicCoagulation and Flocculation Studies
Canadian institutionsUniversity of Alberta
FundersQinghai Provincial Key Laboratory of Qinghai‐Tibet Plateau Biological Resources
KeywordsManureMicroorganismWaste managementProcess (computing)Environmental sciencePulp and paper industryEconomic analysisAgronomyBiologyEngineeringBacteriaComputer scienceEconomicsAgricultural economics

Abstract

fetched live from OpenAlex

• Multi-source heat and PM synergistically achieved rapid bio-drying of MDS. • The dried products met all the specifications for subsequent thermal treatment • The drying system was characterized by high energy efficiency and spontaneous drying. • Drying technology saved US $11.46–16.84/ton (¥83-122.10/ton) of MDS treated. Sludge drying is an important pretreatment step for municipal dewatered sludge (MDS) treatment and disposal, but the time-consuming and high cost of existing processes have hindered the development of MDS treatment and disposal. In this study, a novel sludge drying technology was proposed on the basis of the characteristics and treatment needs of MDS in China. Pig manure (PM) addition and multisource heat assistance together assisted hyperthermophilic bacteria in achieving rapid drying of MDS. Mechanical factors were optimized via orthogonal experiments, and the optimum PM addition ratio was determined. The relationship between energy input (generation) and output in the system was explored to reveal the reasons why the novel drying technology exhibited superiority. Compared with the traditional biological drying technique and the thermal drying technique, the novel technique has the advantages of high efficiency, time savings and low cost. After 24 h of drying, the moisture content, organic matter content and net calorific value on an air-dried basis ( Q net, V,Mad ) of the dried products were 31.43 ± 0.91 %, 72.47 ± 1.89 % and 16.94 ± 0.35 MJ/kg, respectively, which met the requirements of heat recovery and utilization for subsequent thermal treatment. The energy input (generation) to the system exceeded the energy output, indicating that the drying process was positively spontaneous. Multisource heat assistance accounted for 81.6 % of the total generated (input) energy, and 86.43 % of the energy was used for moisture evaporation, indicating high energy utilization of the drying system. In addition, cost savings of US $11.46–16.84/ton (¥83-122.10/ton) were achieved when MDS was treated via the novel drying technology. Overall, the novel drying technology proposed in this study provides feasible, efficient and cost-saving pretreatment technology and ideas for MDS treatment and disposal engineering.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.410
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.013
GPT teacher head0.247
Teacher spread0.234 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it