Student or educator? Sign up with your school email and get 6 months of Pro free.
Cited by 571

The DOI matches its Crossref record; 2 of the 2 references it cites were found in a registry or an index.

Green Chemistry Metrics with Special Reference to Green Analytical Chemistry

Open access
Tobiszewski, Marek, Marć, Mariusz, Gałuszka, Agnieszka, Namieśnik, Jacek·2015·Molecules

Abstract

The concept of green chemistry is widely recognized in chemical laboratories. To properly measure an environmental impact of chemical processes, dedicated assessment tools are required. This paper summarizes the current state of knowledge in the field of development of green chemistry and green analytical chemistry metrics. The diverse methods used for evaluation of the greenness of organic synthesis, such as eco-footprint, E-Factor, EATOS, and Eco-Scale are described. Both the well-established and recently developed green analytical chemistry metrics, including NEMI labeling and analytical Eco-scale, are presented. Additionally, this paper focuses on the possibility of the use of multivariate statistics in evaluation of environmental impact of analytical procedures. All the above metrics are compared and discussed in terms of their advantages and disadvantages. The current needs and future perspectives in green chemistry metrics are also discussed.

Overview

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Integrity signals

Registry

Crossref · 10.3390/molecules200610928

Cites

2 of 2 references verified0 citation errors · 0 not checkable

Statistics

Verification

Claims the paper makes

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

The self-check needs the paper’s full text.

Citations

Cites

Show all 2 references

Cited by

See all 571

Metadata

Authors
Tobiszewski, M., Marć, M., Gałuszka, A., & Namieśnik, J.
Venue
Molecules
Publisher
MDPI AG
Published
2015-06-12
Volume
20
Issue
6
Pages
10928-10946
ISSN
1420-3049 (ISSN-L)
OpenAlex
W1503376607
Cited by
571
References
2
FWCI
9.75
Type
journal article
Language
en
Open access
gold

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review

How to cite

Cite CoChat for the checks on this page, and the paper for its own findings.

This page
CoChat. (2026). Citation check: Green Chemistry Metrics with Special Reference to Green Analytical Chemistry. https://app.cochat.ai/papers/10.3390/molecules200610928
The paper
Tobiszewski, M., Marć, M., Gałuszka, A., & Namieśnik, J. (2015). Green Chemistry Metrics with Special Reference to Green Analytical Chemistry. Molecules. https://doi.org/10.3390/molecules200610928

Data sources

Bibliographic data: Semantic Scholar, OpenAlex, Crossref.

Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.