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ZENODO
Dataset . 2022
License: CC BY
Data sources: Datacite
image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
ZENODO
Dataset . 2022
License: CC BY
Data sources: ZENODO
image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
ZENODO
Dataset . 2022
License: CC BY
Data sources: Datacite
image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
https://doi.org/10.5281/zenodo...
Dataset . 2022
License: CC BY
Data sources: Sygma
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Webgis data 2020 and 2021

Authors: CAP; UNIMI;

Webgis data 2020 and 2021

Abstract

Starting from the data measured through laboratory tests during 2020 and 2021, a set of parameters have been evaluated. Each day of analysis has been associated to a class, basing on thementioned values. In such a way it was possible to compute the percentage of times in which the water from a specific plant has been in the different classes . Collecting the data measured in each plant, the four classes have been defined setting limit values of these parameters. a set of rules was defined in order to identify the dominant water quality class for each WWT plant, based on the previously obtained percentages. :•If the effluent falls in water quality class A at least 90% of the time →the dominant class for that plant is A. •If the effluent falls in water quality class A less than 90% of the time AND 0% of the time in class D →the dominant class for that plant is B. •If the effluent falls in water quality class A less than 90% of the time AND below 10% in class D →the dominant class for that plant is C. •If the effluent fallsin water quality class D more than 10% of the time →the dominant class for that plant is D. This allowed a classification of the available WWTPs according to their dominant class and, thus, application of the EU regulation 2020/741. Therefore, for each WWTP, the WebGIS can show what crop types can be irrigated with their effluent, as well as the allowed irrigation method/s

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
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