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Derivation methods of remediation criteria for contaminated soils under different land uses and analysis of their standard values

2015· article· en· W3172097037 on OpenAlexaboutno aff
Zhou Qixing, Yong Teng

Bibliographic record

VenueDOAJ (DOAJ: Directory of Open Access Journals) · 2015
Typearticle
Languageen
FieldEngineering
TopicMining and Gasification Technologies
Canadian institutionsnot available
Fundersnot available
KeywordsEnvironmental remediationContaminationEnvironmental scienceSoil waterSoil contaminationContaminated landSoil remediationSoil scienceEnvironmental chemistryChemistryBiologyEcology

Abstract

fetched live from OpenAlex

Many countries such as USA, Canada, Denmark and Swiss, and their states or provinces, have carried out systematic researches on the remediation criteria of contaminated soils, and their relevant remediation standards for contaminated soils have also been enacted nationwide or statewide. Especially for USA, it has so many states that there are a series of methodologies provided for references, just as “soil cleanup levels” in Alaska, “soil remediation standards” in Arizona, “soil cleanup target levels” in Florida, “soil remediation goals” in North Carolina, and so do many other countries such as “Canada soil quality guidelines” and “Canada-wide standards for petroleum hydrocarbons”, “cut-off criteria” in Denmark, “action values” in Germany, “target cleanup levels” in Italy, “soil remediation intervention values” in Netherlands, and “clean-up values” in Swiss. Generally speaking, the protection of human health is the key point in most of the remediation standards among various countries or states. Meanwhile, ecosystem safety is also included as the protected objects independently, and sometimes groundwater protection is also taken into consideration directly or indirectly. At the same time, the past, current or future land uses are often discriminated in the remediation criteria for most of the countries or states. Nevertheless, the remediation standard for contaminated soils is still a gap in China and thus it is of great urgency to carry out the systematic and comprehensive research on the remediation criteria to meet the need for contaminated soil remediation under various land uses. In general, the research about “derivation methods of remediation criteria/standards for contaminated soils under different land uses and analysis of their standard values” is of great significance and necessity.Firstly, the connotation and function of remediation criteria and standards for contaminated soils are explained in brief combined with the screening values. Noticeably, the preliminary remediation goal is that remediation standards of contaminated soils intend for the protection of human health, was firstly developed at the national level in USA, while its guidance was commonly used to derive some screening levels under the similar supposed contexts and thus the screening values were used as the remediation goals for these soils. However, in 1996, the Soil Screening Guidance (SSG) was enacted by US EPA for the derivation of screening values specially, and stated that the function of soil screening levels is to screen out a contaminated site and its potential pollutants. And in most European countries, the screening values are regarded as soil-environmental quality standards rather than remediation standards of contaminated soils. In fact, remediation standards of contaminated soils should be the guidance for the nationwide or statewide remediation projects and the protection of plow lands.Land uses should be considered in derivation and development of remediation standards for contaminated soils, and the reference methods are suggested for the development of remediation standards for contaminated soils under various land uses. Then, it is followed by deriving and enacting methods of remediation criteria for contaminated soils under different land uses and the analysis of their standard values. We set forth the variations of the methods and the standard values under various land uses as the result of various remedial requirements and exposure scenarios from three aspects, that is, human health, ecosystem safety and groundwater protection. Generally speaking, exposure scenarios are different in various land uses, and there are some discrimination on exposure population, exposure pathways, and exposure parameters based on human health, while the differences are mainly reflected on receptors, and toxic indicators for eco-based remediation criteria. As for groundwater protection based remediation criteria, water quality standards are often used for the back calculation of soil remediation criteria by the soil-water partition equation, and they are somewhat different in terms of the function of groundwater under various land uses. Otherwise, remediation standards for Cd and benzene contaminated soils in some countries and states are compared qualitatively.In conclusion, many countries have enacted the nationwide or statewide remediation standards for contaminated soils, and are expressed by different denominations. In general, four types of land uses (agricultural, residential, commercial/industrial, groundwater-protection land uses) are considered in development of remediation standards, and there are some discrimination on the methods and the standard values under various land uses.

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.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.004
metaresearch head score (Gemma)0.010
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: Methods
Teacher disagreement score0.009
Threshold uncertainty score0.019

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.010
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0010.002
Bibliometrics0.0070.004
Science and technology studies0.0010.001
Scholarly communication0.0030.003
Open science0.0020.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.001

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 head0.369
GPT teacher head0.566
Teacher spread0.197 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designTheoretical or conceptual
Domainnot available
GenreMethods

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

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Citations1
Published2015
Admission routes1
Has abstractyes

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