Changes in air and water quality during the Covid-19 Lockdown in the Venice Lagoon
has assertion: assertion
has provenance: provenance
has publication info: pubinfo
type: Nanopublication
created: 2025-11-11T16:13:54.683+01:00
type: RoCrateNanopub

Environmental research
type: DefinedTerm

Applied sciences
type: DefinedTerm

Earth sciences
type: DefinedTerm

Giorgio Castellan
type: Agent
orcid: 0000-0001-6084-1504

Anne Fouilloux
affiliation: Simula Research Laboratory
type: Agent
orcid: 0000-0002-1784-2920

Federica Foglini
type: Agent
orcid: 0000-0002-2736-0052

Jean Iaquinta
type: Agent
orcid: 0000-0002-8763-1643

Malek Belgacem
affiliation: CNR-ISMAR
type: Agent
orcid: 0000-0003-0745-4155

Małgorzata Wolniewicz
type: Agent

Simula Research Laboratory
type: Organization
type: Agent

water quality
type: Lemma
norm score: 26.286966046002192
score: 24.0

earth sciences
type: FieldOfResearch
norm score: 100.0
score: 0.8256614208221436

Changes in air and water quality during the Covid-19 Lockdown in the Venice Lagoon.
type: Sentence
norm score: 25.325325325325323
score: 25.3

social and information sciences
type: NASA
norm score: 100.0
score: 0.658052384853363

Jupyter Notebooks
type: Lemma
norm score: 10.076670317634171
score: 9.2

Venice Lagoon
type: Lemma
norm score: 17.524644030668128
score: 16.0

aim
type: Concept
norm score: 11.596180081855389
score: 8.5

Venice Venice Lagoon
type: Phrase
norm score: 47.76876267748479
score: 47.1

research object
type: Phrase
norm score: 32.961460446247465
score: 32.5

understanding changes in air and water quality
type: Phrase
norm score: 0.8113590263691685
score: 0.8

Venice
type: Concept
norm score: 22.919508867667123
score: 16.8

research
type: Concept
norm score: 15.82537517053206
score: 11.6

water quality
type: Concept
norm score: 30.013642564802183
score: 22.0

In this study, we focusing on understanding changes in air and water quality during the Covid-19 lockdown in the Venice Lagoon.
type: Sentence
norm score: 51.95195195195195
score: 51.9

documentation and information science
type: NASA
norm score: 100.0
score: 0.658052384853363

study
type: Concept
norm score: 11.732605729877218
score: 8.6

Venice
type: Lemma
norm score: 11.71960569550931
score: 10.7

Venice
type: Place
wikidata: https://www.wikidata.org/wiki/Q641

understanding
type: Concept
norm score: 7.91268758526603
score: 5.8

study
type: Lemma
norm score: 9.41949616648412
score: 8.6

geology
type: FieldOfResearch
norm score: 100.0
score: 0.8256614208221436

We are re-using existing Research Objects, and in particular Jupyter Notebooks that were created in previous studies.
type: Sentence
norm score: 22.72272272272272
score: 22.7

existing research object
type: Phrase
norm score: 1.7241379310344829
score: 1.7

research
type: Lemma
norm score: 14.348302300109529
score: 13.1

POLYGON ((-25.000012 29.999997, 44.999988 29.999997, 44.999988 71.999997, -25.000012 71.999997, -25.000012 29.999997))
polygon: -25.000012 29.999997, 44.999988 29.999997, 44.999988 71.999997, -25.000012 71.999997, -25.000012 29.999997
type: GeoShape

https://w3id.org/ro-id/eec6faaa-e133-47d4-b377-44f7d06a9654/#31b0b68d-7999-4e04-8be8-001d4496c246
name: POLYGON ((12.094116155058147 45.146856282945706, 12.094116155058147 45.62908481204897, 12.816467229276897 45.62908481204897, 12.816467229276897 45.146856282945706, 12.094116155058147 45.146856282945706))
polygon: 12.094116155058147 45.146856282945706, 12.094116155058147 45.62908481204897, 12.816467229276897 45.62908481204897, 12.816467229276897 45.146856282945706, 12.094116155058147 45.146856282945706
type: GeoShape

POLYGON ((-25.000012 29.999997, 44.999988 29.999997, 44.999988 71.999997, -25.000012 71.999997, -25.000012 29.999997))
polygon: -25.000012 29.999997, 44.999988 29.999997, 44.999988 71.999997, -25.000012 71.999997, -25.000012 29.999997
type: GeoShape

https://w3id.org/ro-id/eec6faaa-e133-47d4-b377-44f7d06a9654/#8546b63a-68d5-48fe-a174-a70a9b462d92
name: POLYGON ((12.094116155058147 45.146856282945706, 12.094116155058147 45.62908481204897, 12.816467229276897 45.62908481204897, 12.816467229276897 45.146856282945706, 12.094116155058147 45.146856282945706))
type: Place

POLYGON ((-25.000012 29.999997, 44.999988 29.999997, 44.999988 71.999997, -25.000012 71.999997, -25.000012 29.999997))
type: Place

POLYGON ((-25.000012 29.999997, 44.999988 29.999997, 44.999988 71.999997, -25.000012 71.999997, -25.000012 29.999997))
polygon: -25.000012 29.999997, 44.999988 29.999997, 44.999988 71.999997, -25.000012 71.999997, -25.000012 29.999997
type: GeoShape

service-account-enrichment
type: Agent

POLYGON ((-25.000012 29.999997, 44.999988 29.999997, 44.999988 71.999997, -25.000012 71.999997, -25.000012 29.999997))
type: Place

POLYGON ((-25.000012 29.999997, 44.999988 29.999997, 44.999988 71.999997, -25.000012 71.999997, -25.000012 29.999997))
type: Place

Changes in air and water quality during the Covid-19 Lockdown in the Venice Lagoon - snapshot
doi: https://doi.org/10.24424/656f-rf51
is finalized: False
is snapshot of: https://w3id.org/ro-id/998dccd6-7192-4d88-af39-6018c71e6bdf
snapshoted at time: 2023-02-19 13:23:07.862706+00:00
snapshoted by: Anne Fouilloux
about: Environmental research
about: Applied sciences
about: Earth sciences
author: Giorgio Castellan
author: Anne Fouilloux
author: Federica Foglini
content size: 293999
contributor: Jean Iaquinta
contributor: Malek Belgacem
copyright holder: Simula Research Laboratory
creator: Anne Fouilloux
date created: 2023-01-08 18:47:51.996769+00:00
date modified: 2024-03-05 12:17:16.953752+00:00
date published: 2023-01-08 18:47:51.996769+00:00
description: In this study, we focusing on understanding changes in air and water quality during the Covid-19 lockdown in the Venice Lagoon. We are re-using existing Research Objects, and in particular Jupyter Notebooks that were created in previous studies.
encoding format: application/ld+json
keywords: air
keywords: water
license: no-permission
main entity: Jupyter Notebook
name: Changes in air and water quality during the Covid-19 Lockdown in the Venice Lagoon
publisher: Simula Research Laboratory
creation mode: MANUAL
has geometry: https://w3id.org/ro-id/eec6faaa-e133-47d4-b377-44f7d06a9654/4a946757-943c-4bf8-986e-d8984276aed1
type: ResearchObject
type: SnapshotRO
type: Dataset
type: ExecutableResearchObject
place: Venice
concept: aim
concept: Venice
concept: research
concept: water quality
concept: study
concept: understanding
field of research: earth sciences
field of research: geology
lemma: water quality
lemma: Jupyter Notebooks
lemma: Venice Lagoon
lemma: Venice
lemma: study
lemma: research
lemma: object
NASA: social and information sciences
NASA: documentation and information science
phrase: Venice Venice Lagoon
phrase: research object
phrase: understanding changes in air and water quality
phrase: existing research object
phrase: changes in air and water quality
sentence: Changes in air and water quality during the Covid-19 Lockdown in the Venice Lagoon.
sentence: In this study, we focusing on understanding changes in air and water quality during the Covid-19 lockdown in the Venice Lagoon.
sentence: We are re-using existing Research Objects, and in particular Jupyter Notebooks that were created in previous studies.
template: https://w3id.org/ro/terms/earth-science#ExecutableResearchObjectTemplate
cite-as: Fouilloux, Anne, Federica Foglini, Giorgio Castellan, Malek Belgacem, Jean Iaquinta, and Simone Mantovani. "Changes in air and water quality during the Covid-19 Lockdown in the Venice Lagoon." ROHub. Jan 08 ,2023. https://doi.org/10.24424/656f-rf51.

https://w3id.org/ro-id/eec6faaa-e133-47d4-b377-44f7d06a9654/4a946757-943c-4bf8-986e-d8984276aed1
as WKT: POLYGON ((12.094116155058147 45.146856282945706, 12.094116155058147 45.62908481204897, 12.816467229276897 45.62908481204897, 12.816467229276897 45.146856282945706, 12.094116155058147 45.146856282945706))
type: Geometry
type: Polygon

https://w3id.org/ro-id/eec6faaa-e133-47d4-b377-44f7d06a9654/80885ab4-6622-4b21-9e52-5e696aa2d377/b2b4129f-0457-4816-9717-c496bc1ef497
as WKT: POLYGON ((-25.000012 29.999997, 44.999988 29.999997, 44.999988 71.999997, -25.000012 71.999997, -25.000012 29.999997))
type: Geometry
type: Polygon

https://w3id.org/ro-id/eec6faaa-e133-47d4-b377-44f7d06a9654/92c1ed12-2aef-4045-9116-01e1bff3eddd/f557d130-b63e-46cd-868b-6144d36da7c5
as WKT: POLYGON ((-25.000012 29.999997, 44.999988 29.999997, 44.999988 71.999997, -25.000012 71.999997, -25.000012 29.999997))
type: Geometry
type: Polygon

https://w3id.org/ro-id/eec6faaa-e133-47d4-b377-44f7d06a9654/eb1a3994-a796-41c8-8673-80b74c6e3a81/424a95ac-8243-40ef-86c6-0e0648c7765e
as WKT: POLYGON ((-25.000012 29.999997, 44.999988 29.999997, 44.999988 71.999997, -25.000012 71.999997, -25.000012 29.999997))
type: Geometry
type: Polygon

tool
type: Folder
type: Dataset

output
type: Folder
type: Dataset

input
type: Folder
type: Dataset

biblio
type: Folder
type: Dataset

Impact of the Covid-19 Lockdown on Air and Water quality in the Venice Lagoon
author: Anne Fouilloux
creator: Anne Fouilloux
date created: 2023-01-08 19:19:35.675216+00:00
date modified: 2023-02-19 13:22:48.215320+00:00
description: Integration of data on Air and Water quality in the Venice Lagoon to assess the impact of the Covid-19 Lockdown
license: no-permission
sd date published: 2023-01-08 19:19:35.675216+00:00
type: ResearchObject
type: Resource
type: MediaObject

PTF dataset(2009-2020) Piattaforma acqua allta
author: Anne Fouilloux
creator: Anne Fouilloux
date created: 2023-01-08 19:37:15.986538+00:00
date modified: 2023-02-19 13:22:45.129102+00:00
description: Data at the Acqua Alta oceanographic tower is a collection of physical and biogeochemical observation in the northern Adriatic Sea https://www.comune.venezia.it/it/content/3-piattaforma-ismar-cnr http://www.ismar.cnr.it/infrastrutture/piattaforma-acqua-alta
license: no-permission
sd date published: 2023-01-08 19:37:15.986538+00:00
type: Dataset
type: Resource
type: MediaObject

COVID-19 lockdown improved the health of coastal environment and enhanced the population of reef-fish
author: Anne Fouilloux
creator: Anne Fouilloux
date created: 2023-01-08 19:24:00.526730+00:00
date modified: 2023-02-19 13:22:53.090742+00:00
description: Reduction in the impact of human-induced factors is capable of enhancing the environmental health. In view of COVID-19 pandemic, lockdowns were imposed in India. Travel, fishing, tourism and religious activities were halted, while domestic and industrial activities were restricted. Comparison of the pre- and post-lockdown data shows that water parameters such as turbidity, nutrient concentration and microbial levels have come down from pre- to post-lockdown period, and parameters such as dissolved oxygen levels, phytoplankton and fish densities have improved. The concentration of macroplastics has also dropped from the range of 138 ± 4.12 and 616 ± 12.48 items/100 m2 to 63 ± 3.92 and 347 ± 8.06 items/100 m2. Fish density in the reef areas has increased from 406 no. 250 m−2 to 510 no. 250 m−2. The study allows an insight into the benefits of effective enforcement of various eco-protection regulations and proper management of the marine ecosystems to revive their health for biodiversity conservation and sustainable utilization.
keywords: lockdown
license: no-permission
sd date published: 2023-01-08 19:24:00.526730+00:00
type: Paper
type: Resource
type: MediaObject

NO2 CAMS over Europe March-June 2019, 2020 and 2021
author: Anne Fouilloux
creator: Anne Fouilloux
date created: 2023-01-08 19:38:36.937507+00:00
date modified: 2023-02-19 13:22:54.308417+00:00
description: NO2 CAMS over Europe March-June 2019, 2020 and 2021 extracted from ADAM data cube.
encoding format: application/x-netcdf
keywords: NO2
license: no-permission
sd date published: 2023-01-08 19:38:36.937507+00:00
type: Dataset
type: Resource
type: MediaObject

figure.png
author: Anne Fouilloux
content size: 147673
creator: Anne Fouilloux
date created: 2023-05-24 19:00:14.547814+00:00
date modified: 2023-05-24 19:00:16.737992+00:00
encoding format: image/png
license: no-permission
sd date published: 2023-05-24 19:00:14.547814+00:00
type: Resource
type: MediaObject

Impact of the COVID-19 Pandemic Lockdown on Air Quality Pollution in 20 Major cities around the World
author: Anne Fouilloux
creator: Anne Fouilloux
date created: 2023-01-08 19:21:48.221333+00:00
date modified: 2023-02-19 13:22:50.794426+00:00
description: In order to fight against the spread of COVID-19, the most hard-hit countries in the spring of 2020 implemented different lockdown strategies. To assess the impact of the COVID-19 pandemic lockdown on air quality worldwide, Air Quality Index (AQI) data was used to estimate the change in air quality in 20 major cities on six continents. Our results show significant declines of AQI in NO2, SO2, CO, PM2.5 and PM10 in most cities, mainly due to the reduction of transportation, industry and commercial activities during lockdown. This work shows the reduction of primary pollutants, especially NO2, is mainly due to lockdown policies. However, preexisting local environmental policy regulations also contributed to declining NO2, SO2 and PM2.5 emissions, especially in Asian countries. In addition, higher rainfall during the lockdown period could cause decline of PM2.5, especially in Johannesburg. By contrast, the changes of AQI in ground-level O3 were not significant in most of cities, as meteorological variability and ratio of VOC/NOx are key factors in ground-level O3 formation.
license: no-permission
sd date published: 2023-01-08 19:21:48.221333+00:00
type: Paper
type: Resource
type: MediaObject

Impact of the Covid-19 Lockdown on Air and Water quality in the Venice Lagoon
description: Jupyter Notebook to analyse the changes in NO2 during the Covid-19 Lockdown in the Venice Lagoon. Datasets are from Copernicus Atmosphere Monitoring Forecasts and in-situ measurement for water quality
type: Object
type: JupyterNotebook

NO2 water quality in the Venice lagoon between March-June 2019 and 2020.
author: Anne Fouilloux
content size: 39986
creator: Anne Fouilloux
date created: 2023-01-08 20:25:23.565475+00:00
date modified: 2023-02-19 13:23:06.902211+00:00
description: The goal is to compare values of NO2 water quality before and during the covid-19 lockdown.
keywords: NO2
license: no-permission
sd date published: 2023-01-08 20:25:23.565475+00:00
type: Resource
type: MediaObject
type: Plot

CAMS European air quality forecasts: O3
author: Anne Fouilloux
creator: Anne Fouilloux
date created: 2023-01-08 19:41:17.789149+00:00
date modified: 2023-02-19 13:22:49.529744+00:00
description: CAMS OZONE
end date: 2022-12-27T23:00:00Z
keywords: O3
license: no-permission
sd date published: 2023-01-08 19:41:17.789149+00:00
start date: 2018-07-12T00:00:00Z
has geometry: https://w3id.org/ro-id/eec6faaa-e133-47d4-b377-44f7d06a9654/80885ab4-6622-4b21-9e52-5e696aa2d377/b2b4129f-0457-4816-9717-c496bc1ef497
type: Resource
type: MediaObject
type: DataCubeCollection
data type: Float32
max value: [2.2007016298175586e-07]
min value: [0.0]

NO2 Copernicus Air Quality forecasts for March-June 2019-2020
author: Anne Fouilloux
content size: 63516
creator: Anne Fouilloux
date created: 2023-01-08 20:22:56.960407+00:00
date modified: 2023-02-19 13:23:06.267913+00:00
description: Bar plot showing NO2 averaged between March and June for 2019 and 2020. The goal is to compare values before and during the covid-19 lockdown.
keywords: NO2
license: no-permission
sd date published: 2023-01-08 20:22:56.960407+00:00
type: Resource
type: MediaObject
type: Plot

Water quality in the Venice Lagoon between 2010 and 2020.
author: Anne Fouilloux
content size: 46709
creator: Anne Fouilloux
date created: 2023-01-08 19:35:05.569853+00:00
date modified: 2023-02-19 13:23:04.921504+00:00
description: Dataset shows monthly values and error bars.
encoding format: image/png
license: no-permission
sd date published: 2023-01-08 19:35:05.569853+00:00
type: Resource
type: MediaObject
type: Plot

Snapshot 2021 study case: Lockdown impacts on the Northern Adriatic Sea at selected site: AcquaAlta Platform Water quality
author: Anne Fouilloux
creator: Anne Fouilloux
date created: 2023-01-08 19:15:20.212877+00:00
date modified: 2023-02-19 13:22:55.556680+00:00
description: This is a case study of snapshot project http://snapshot.cnr.it/ to investigate the lockdown impact on the water quality at a selected site in the northern Adriatic Sea, precisely in Northern Adriatic Sea, the case of the Gulf of Venice using Machine Learning model.
license: no-permission
sd date published: 2023-01-08 19:15:20.212877+00:00
type: ResearchObject
type: Resource
type: MediaObject

CAMS European air quality forecasts: NO2
author: Anne Fouilloux
creator: Anne Fouilloux
date created: 2023-01-08 19:40:14.176174+00:00
date modified: 2023-02-19 13:22:52.387115+00:00
description: CAMS NITROGEN DIOXIDE
end date: 2022-12-27T23:00:00Z
keywords: NO2
license: no-permission
sd date published: 2023-01-08 19:40:14.176174+00:00
start date: 2018-07-12T00:00:00Z
has geometry: https://w3id.org/ro-id/eec6faaa-e133-47d4-b377-44f7d06a9654/92c1ed12-2aef-4045-9116-01e1bff3eddd/f557d130-b63e-46cd-868b-6144d36da7c5
type: Resource
type: MediaObject
type: DataCubeCollection
data type: Float32
max value: [1.354510459350422e-07]
min value: [0.0]

Impact of the Covid-19 Lockdown on Air quality over Europe
author: Anne Fouilloux
creator: Anne Fouilloux
date created: 2023-01-08 19:14:03.311972+00:00
date modified: 2023-02-19 13:22:50.947789+00:00
description: The COVID-19 pandemic has led to significant reductions in economic activity, especially during lockdowns. Several studies has shown that the concentration of nitrogen dioxyde and particulate matter levels have reduced during lockdown events. Reductions in transportation sector emissions are most likely largely responsible for the NO2 anomalies. In this study, we analyze the impact of lockdown events on the air quality using data from Copernicus Atmosphere Monitoring Service over Europe and at selected locations.
license: no-permission
sd date published: 2023-01-08 19:14:03.311972+00:00
type: ResearchObject
type: Resource
type: MediaObject

Parting the Sea to Save Venice
author: Anne Fouilloux
creator: Anne Fouilloux
date created: 2023-01-08 19:58:47.516622+00:00
date modified: 2023-02-19 13:22:55.402245+00:00
description: The natural-color Landsat images above show some of the MOSE engineering efforts that are visible above the water line near the Lido Inlet. The top image was acquired on June 20, 2000, by the Enhanced Thematic Mapper+ on Landsat 7. The second image, from the Operational Land Imager on Landsat 8, was collected on September 4, 2013. Turn on the image comparison tool to make the changes easier to see. (Note that Landsat 8 has a greater dynamic range than Landsat 7, so the Landsat 8 image is crisper the Landsat 7 image.)
license: no-permission
sd date published: 2023-01-08 19:58:47.516622+00:00
type: Document
type: Resource
type: MediaObject

CAMS European air quality forecasts: PM25
author: Anne Fouilloux
creator: Anne Fouilloux
date created: 2023-01-08 19:42:25.690080+00:00
date modified: 2023-02-19 13:22:51.053690+00:00
description: CAMS SURFACE PARTICULATE METTER D<2.5
end date: 2022-12-27T23:00:00Z
keywords: PM2.5
license: no-permission
sd date published: 2023-01-08 19:42:25.690080+00:00
start date: 2018-07-12T00:00:00Z
has geometry: https://w3id.org/ro-id/eec6faaa-e133-47d4-b377-44f7d06a9654/eb1a3994-a796-41c8-8673-80b74c6e3a81/424a95ac-8243-40ef-86c6-0e0648c7765e
type: Resource
type: MediaObject
type: DataCubeCollection
data type: Float32
max value: [709.8012084960938]
min value: [0.0]

changes in air and water quality
type: Phrase
norm score: 16.734279918864097
score: 16.5

object
type: Lemma
norm score: 10.62431544359255
score: 9.7

Simone Mantovani
type: Agent

Raul Palma
type: Agent

sig
has algorithm: RSA
signed by: RoCrateBot