Evidence map›Paper›PMID 41150577›Full record

ArticleToxics2025

Extended Environmental Multimedia Modeling System (EEMMS) with Analytic Hierarchy Process for Dual Evaluation of Energy Consumption and Pollutants in Solid Waste.

Jing Yuan, Heng Wang, Meifeng Chen

Abstract read
In one paragraph

Article in Toxics, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors.

Jing YuanDepartment of Civil Engineering, Tongling University, Tongling 244000, China.ORCID 0000-0002-8839-925X
Heng WangEngineering Research Institute, Anhui University of Technology, Ma'anshan 243002, China.ORCID 0009-0009-7996-2088
Meifeng ChenEngineering Research Institute, Anhui University of Technology, Ma'anshan 243002, China.

Funding

Anhui University Excellent Research and Innovation 2022AH010094National Natural Science Foundation of China 42271301
6 · The paper itself

Abstract

The dual assessment of environmental risks and energy consumption of solid waste is crucial for ensuring environmental safety and energy consumption management. Using risk assessment tools to inform best management practices for reclamation is very important. In this paper, a former Extended Environmental Multimedia Modeling System (EEMMS) combined with the Monte Carlo Method (MCM) of risk assessment was further used for exploring the fate and migration of pollutant leakage in the CFSWMA landfill. Specifically, MODFLOW combined with the EEMMS-MCM system has been applied using Biochemical Oxygen Demand (BOD) as a typical indicator to model the behavior of leachate components. An EEMMS-MCM integrated risk assessment for a 20-year period was conducted. The case study of BOD emissions from the CFSWMA landfill shows that even the leachate did not have a serious impact on Canadian territory during the 20 years; however, non-sorption chemicals are mainly affected by the groundwater flow, whereas sorption chemicals are affected by the partition coefficient (or sorption). Further, this study introduces energy consumption factors such as soil and surface water bodies, and constructs an integrated dual assessment framework for the environmental risks and energy consumption of pollutants. In summary, by integrating the EEMMS pollutant migration model with an environmental risk and energy consumption assessment, a dual assessment of environmental risks and energy consumption is achieved.

Indexed as

energy consumptionExtended Environmental Multimedia Modeling System (EEMMS)landfill leachateMODFLOWMonte Carlo Method (MCM)

Identifiers

PMID41150577
PMCPMC12568080

What OpenQuestion holds

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.