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http://schema.org/dateCreated 2021-12-20 11:04:49.605037+00:00 https://w3id.org/ro-id/374d0d3a-4807-4925-be83-b9eea52356e3/ http://schema.org/dateModified 2025-03-05 12:47:13.501356+00:00 https://w3id.org/ro-id/374d0d3a-4807-4925-be83-b9eea52356e3/ http://schema.org/datePublished 2021-12-20 11:04:49.605037+00:00 https://w3id.org/ro-id/374d0d3a-4807-4925-be83-b9eea52356e3/ http://schema.org/description Collection of scientific articles and other communications related to the impact of COVID-19 pandemic lockdown on air quality pollution. https://w3id.org/ro-id/374d0d3a-4807-4925-be83-b9eea52356e3/ http://schema.org/encodingFormat application/ld+json https://w3id.org/ro-id/374d0d3a-4807-4925-be83-b9eea52356e3/ http://schema.org/hasPart https://w3id.org/ro-id/374d0d3a-4807-4925-be83-b9eea52356e3/folders/22473b08-969d-4ddc-a4fc-f76cf4b4ed7b https://w3id.org/ro-id/374d0d3a-4807-4925-be83-b9eea52356e3/ http://schema.org/hasPart 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http://w3id.org/ro/earth-science#Sentence Collection of scientific articles and other communications related to the impact of COVID-19 pandemic lockdown on air quality pollution. https://w3id.org/ro-id/374d0d3a-4807-4925-be83-b9eea52356e3/ http://w3id.org/ro/earth-science#Sentence Figure summarizes the main statistics (normalized meanbias, NMB; normalized root mean square error, NRMSE;and correlation, r) obtained from the comparison betweenmeasured and ML based electricity demand during the first months of for selected countries. https://w3id.org/ro-id/374d0d3a-4807-4925-be83-b9eea52356e3/ http://w3id.org/ro/earth-science#Sentence In this study, ML models are used for predictingthe fluctuations of electricity demand based on the temper ature (and additional time features) assuming that temper ature is a strong driver of electricity demand (for heatingand air conditioning) However, temperature is obviously notthe only driver of electricity demand variability that can beinfluenced by various other factors (e.g. change of technol ogy, behaviour, regulation) In addition, the GBM modelsused in this study are non parametric, meaning that they can not extrapolate, i.e. predict electricity demand values out side the range of values used during the training phase. https://w3id.org/ro-id/374d0d3a-4807-4925-be83-b9eea52356e3/ http://w3id.org/ro/earth-science#Sentence The ECHAM HAM and CESM NoT ensembles allow more freedom for temperature adjustment. https://w3id.org/ro-id/374d0d3a-4807-4925-be83-b9eea52356e3/ http://w3id.org/ro/earth-science#Sentence The ECHAM HAM simulation set up is most similar to the CESM NoT ensemble described below. https://w3id.org/ro-id/374d0d3a-4807-4925-be83-b9eea52356e3/ http://w3id.org/ro/earth-science#Sentence The average temperature was not availablefor Los Angeles (LA) New York City (NYC) and Sydney, so the maximum temperature was used,as the maximum temperature is important for ozone formation. https://w3id.org/ro-id/374d0d3a-4807-4925-be83-b9eea52356e3/ http://w3id.org/ro/earth-science#Sentence The daily median AQI was used in this study for each of major cities. https://w3id.org/ro-id/374d0d3a-4807-4925-be83-b9eea52356e3/ http://w3id.org/ro/earth-science#Sentence The datasetprovides a statistical summary for each of the air pollutant species, all air pollutants are converted toan Air Quality Index (AQI) with the U.S. Environmental Protection Agency (EPA) standard calculation. https://w3id.org/ro-id/374d0d3a-4807-4925-be83-b9eea52356e3/ http://w3id.org/ro/earth-science#Sentence The same emissions scenario (from Forster et al.) is run as for CESM using monthly emissions. https://w3id.org/ro-id/374d0d3a-4807-4925-be83-b9eea52356e3/ http://w3id.org/ro/earth-science#Sentence Thepoorest performance was obtained in Finland (r.) dueto a strong negative anomaly (on average) of elec tricity demand in January February compared to pre vious years used for training. 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https://w3id.org/ro-id/374d0d3a-4807-4925-be83-b9eea52356e3/ https://w3id.org/contentdesc#Place China https://w3id.org/ro-id/374d0d3a-4807-4925-be83-b9eea52356e3/ https://w3id.org/contentdesc#Place Claremont https://w3id.org/ro-id/374d0d3a-4807-4925-be83-b9eea52356e3/ https://w3id.org/contentdesc#Place Croatia https://w3id.org/ro-id/374d0d3a-4807-4925-be83-b9eea52356e3/ https://w3id.org/contentdesc#Place Cyprus https://w3id.org/ro-id/374d0d3a-4807-4925-be83-b9eea52356e3/ https://w3id.org/contentdesc#Place Czech Republic https://w3id.org/ro-id/374d0d3a-4807-4925-be83-b9eea52356e3/ https://w3id.org/contentdesc#Place Delaware https://w3id.org/ro-id/374d0d3a-4807-4925-be83-b9eea52356e3/ https://w3id.org/contentdesc#Place Delhi https://w3id.org/ro-id/374d0d3a-4807-4925-be83-b9eea52356e3/ https://w3id.org/contentdesc#Place Denmark https://w3id.org/ro-id/374d0d3a-4807-4925-be83-b9eea52356e3/ https://w3id.org/contentdesc#Place Estonia 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"Bibliography on air quality before, during and after lockdown.." ROHub. 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https://w3id.org/ro-id/374d0d3a-4807-4925-be83-b9eea52356e3/folders/22473b08-969d-4ddc-a4fc-f76cf4b4ed7b http://www.w3.org/1999/02/22-rdf-syntax-ns#type http://schema.org/Dataset https://w3id.org/ro-id/374d0d3a-4807-4925-be83-b9eea52356e3/resources/116dfa4e-7918-403c-b4ef-1f995d91c775 http://schema.org/author mailto:jean.iaquinta@geo.uio.no https://w3id.org/ro-id/374d0d3a-4807-4925-be83-b9eea52356e3/resources/116dfa4e-7918-403c-b4ef-1f995d91c775 http://schema.org/contentSize 2737177 https://w3id.org/ro-id/374d0d3a-4807-4925-be83-b9eea52356e3/resources/116dfa4e-7918-403c-b4ef-1f995d91c775 http://schema.org/contentUrl https://api.rohub.org/api/resources/116dfa4e-7918-403c-b4ef-1f995d91c775/download/ https://w3id.org/ro-id/374d0d3a-4807-4925-be83-b9eea52356e3/resources/116dfa4e-7918-403c-b4ef-1f995d91c775 http://schema.org/creator mailto:jean.iaquinta@geo.uio.no https://w3id.org/ro-id/374d0d3a-4807-4925-be83-b9eea52356e3/resources/116dfa4e-7918-403c-b4ef-1f995d91c775 http://schema.org/dateCreated 2021-12-20 11:37:53.147412+00:00 https://w3id.org/ro-id/374d0d3a-4807-4925-be83-b9eea52356e3/resources/116dfa4e-7918-403c-b4ef-1f995d91c775 http://schema.org/dateModified 2021-12-20 14:02:16.465674+00:00 https://w3id.org/ro-id/374d0d3a-4807-4925-be83-b9eea52356e3/resources/116dfa4e-7918-403c-b4ef-1f995d91c775 http://schema.org/description The COVID-19 pandemic led to dramatic changes in economic activity in 2020. In this paper the authors use estimates of emission changes for 2020 in two Earth System Models (ESMs) to simulate the impacts of the COVID-19 economic changes. https://w3id.org/ro-id/374d0d3a-4807-4925-be83-b9eea52356e3/resources/116dfa4e-7918-403c-b4ef-1f995d91c775 http://schema.org/encodingFormat application/pdf https://w3id.org/ro-id/374d0d3a-4807-4925-be83-b9eea52356e3/resources/116dfa4e-7918-403c-b4ef-1f995d91c775 http://schema.org/license https://choosealicense.com/no-permission/ https://w3id.org/ro-id/374d0d3a-4807-4925-be83-b9eea52356e3/resources/116dfa4e-7918-403c-b4ef-1f995d91c775 http://schema.org/name Climate Impacts of COVID-19 Induced Emission Changes https://w3id.org/ro-id/374d0d3a-4807-4925-be83-b9eea52356e3/resources/116dfa4e-7918-403c-b4ef-1f995d91c775 http://schema.org/sdDatePublished 2021-12-20 11:37:53.147412+00:00 https://w3id.org/ro-id/374d0d3a-4807-4925-be83-b9eea52356e3/resources/116dfa4e-7918-403c-b4ef-1f995d91c775 http://www.w3.org/1999/02/22-rdf-syntax-ns#type http://purl.org/wf4ever/roterms#Paper https://w3id.org/ro-id/374d0d3a-4807-4925-be83-b9eea52356e3/resources/116dfa4e-7918-403c-b4ef-1f995d91c775 http://www.w3.org/1999/02/22-rdf-syntax-ns#type http://purl.org/wf4ever/wf4ever#Resource https://w3id.org/ro-id/374d0d3a-4807-4925-be83-b9eea52356e3/resources/116dfa4e-7918-403c-b4ef-1f995d91c775 http://www.w3.org/1999/02/22-rdf-syntax-ns#type http://schema.org/MediaObject https://w3id.org/ro-id/374d0d3a-4807-4925-be83-b9eea52356e3/resources/1189b793-4040-49f4-bd1a-de0a03b83de8 http://schema.org/author https://orcid.org/0000-0002-1784-2920 https://w3id.org/ro-id/374d0d3a-4807-4925-be83-b9eea52356e3/resources/1189b793-4040-49f4-bd1a-de0a03b83de8 http://schema.org/contentUrl https://www.frontiersin.org/articles/10.3389/frsc.2021.705051/full https://w3id.org/ro-id/374d0d3a-4807-4925-be83-b9eea52356e3/resources/1189b793-4040-49f4-bd1a-de0a03b83de8 http://schema.org/creator https://orcid.org/0000-0002-1784-2920 https://w3id.org/ro-id/374d0d3a-4807-4925-be83-b9eea52356e3/resources/1189b793-4040-49f4-bd1a-de0a03b83de8 http://schema.org/dateCreated 2021-12-20 13:52:44.528252+00:00 https://w3id.org/ro-id/374d0d3a-4807-4925-be83-b9eea52356e3/resources/1189b793-4040-49f4-bd1a-de0a03b83de8 http://schema.org/dateModified 2021-12-20 13:52:44.528673+00:00 https://w3id.org/ro-id/374d0d3a-4807-4925-be83-b9eea52356e3/resources/1189b793-4040-49f4-bd1a-de0a03b83de8 http://schema.org/description The COVID-19 pandemic has affected severely the economic structure and health care system, among others, of India and the rest of the world. The magnitude of its aftermath is exceptionally devastating in India, with the first case reported in January 2020, and the number has risen to ~31.3 million as of July 23, 2021. India imposed a complete lockdown on March 25, which severely impacted migrant population, industrial sector, tourism industry, and overall economic growth. Herein, the impacts of lockdown and unlock phases on ambient atmospheric air quality variables have been assessed across 16 major cities of India covering the north-to-south stretch of the country. In general, all assessed air pollutants showed a substantial decrease in AQI values during the lockdown compared with the reference period (2017–2019) for almost all the reported cities across India. On an average, about 30–50% reduction in AQI has been observed for PM2.5, PM10, and CO, and maximum reduction of 40–60% of NO2 has been observed herein, while the data was average for northern, western, and southern India. SO2 and O3 showed an increase over a few cities as well as a decrease over the other cities. Maximum reduction (49%) in PM2.5 was observed over north India during the lockdown period. Furthermore, the changes in pollution levels showed a significant reduction in the first three phases of lockdown and a steady increase during subsequent phase of lockdown and unlock period. Our results show the substantial effect of lockdown on reduction in atmospheric loading of key anthropogenic pollutants due to less-to-no impact from industrial activities and vehicular emissions, and relatively clean transport of air masses from the upwind region. These results indicate that by adopting cleaner fuel technology and avoiding poor combustion activities across the urban agglomerations in India could bring down ambient levels of air pollution at least by 30%. https://w3id.org/ro-id/374d0d3a-4807-4925-be83-b9eea52356e3/resources/1189b793-4040-49f4-bd1a-de0a03b83de8 http://schema.org/license https://choosealicense.com/no-permission/ https://w3id.org/ro-id/374d0d3a-4807-4925-be83-b9eea52356e3/resources/1189b793-4040-49f4-bd1a-de0a03b83de8 http://schema.org/name Effect of Lockdown Amid COVID-19 on Ambient Air Quality in 16 Indian Cities https://w3id.org/ro-id/374d0d3a-4807-4925-be83-b9eea52356e3/resources/1189b793-4040-49f4-bd1a-de0a03b83de8 http://schema.org/sdDatePublished 2021-12-20 13:52:44.528252+00:00 https://w3id.org/ro-id/374d0d3a-4807-4925-be83-b9eea52356e3/resources/1189b793-4040-49f4-bd1a-de0a03b83de8 http://www.w3.org/1999/02/22-rdf-syntax-ns#type http://purl.org/wf4ever/wf4ever#Resource https://w3id.org/ro-id/374d0d3a-4807-4925-be83-b9eea52356e3/resources/1189b793-4040-49f4-bd1a-de0a03b83de8 http://www.w3.org/1999/02/22-rdf-syntax-ns#type http://schema.org/MediaObject https://w3id.org/ro-id/374d0d3a-4807-4925-be83-b9eea52356e3/resources/1189b793-4040-49f4-bd1a-de0a03b83de8 http://www.w3.org/1999/02/22-rdf-syntax-ns#type http://schema.org/publication https://w3id.org/ro-id/374d0d3a-4807-4925-be83-b9eea52356e3/resources/6021e080-1951-495c-97d1-3fd1b4e3b0bb http://schema.org/author mailto:jean.iaquinta@geo.uio.no https://w3id.org/ro-id/374d0d3a-4807-4925-be83-b9eea52356e3/resources/6021e080-1951-495c-97d1-3fd1b4e3b0bb http://schema.org/contentUrl https://apps.who.int/iris/bitstream/handle/10665/345329/9789240034228-eng.pdf?sequence=1&isAllowed=y&utm_source=north%20shore%20news&utm_campaign=north%20shore%20news%3A%20outbound&utm_medium=referral https://w3id.org/ro-id/374d0d3a-4807-4925-be83-b9eea52356e3/resources/6021e080-1951-495c-97d1-3fd1b4e3b0bb http://schema.org/creator mailto:jean.iaquinta@geo.uio.no https://w3id.org/ro-id/374d0d3a-4807-4925-be83-b9eea52356e3/resources/6021e080-1951-495c-97d1-3fd1b4e3b0bb http://schema.org/dateCreated 2021-12-20 12:21:55.614484+00:00 https://w3id.org/ro-id/374d0d3a-4807-4925-be83-b9eea52356e3/resources/6021e080-1951-495c-97d1-3fd1b4e3b0bb http://schema.org/dateModified 2021-12-20 12:21:55.615043+00:00 https://w3id.org/ro-id/374d0d3a-4807-4925-be83-b9eea52356e3/resources/6021e080-1951-495c-97d1-3fd1b4e3b0bb http://schema.org/description There is a strong body of evidence to show how air pollution affects different aspects of health at even lower concentrations than previously understood. But here’s what hasn’t changed: every year, exposure to air pollution is still estimated to cause millions of deaths and the loss of healthy years of life. https://w3id.org/ro-id/374d0d3a-4807-4925-be83-b9eea52356e3/resources/6021e080-1951-495c-97d1-3fd1b4e3b0bb http://schema.org/encodingFormat application/pdf https://w3id.org/ro-id/374d0d3a-4807-4925-be83-b9eea52356e3/resources/6021e080-1951-495c-97d1-3fd1b4e3b0bb http://schema.org/license https://choosealicense.com/no-permission/ https://w3id.org/ro-id/374d0d3a-4807-4925-be83-b9eea52356e3/resources/6021e080-1951-495c-97d1-3fd1b4e3b0bb http://schema.org/name WHO global air quality guidelines. Particulate matter (PM2.5 and PM10), ozone, nitrogen dioxide, sulfur dioxide and carbon monoxide https://w3id.org/ro-id/374d0d3a-4807-4925-be83-b9eea52356e3/resources/6021e080-1951-495c-97d1-3fd1b4e3b0bb http://schema.org/sdDatePublished 2021-12-20 12:21:55.614484+00:00 https://w3id.org/ro-id/374d0d3a-4807-4925-be83-b9eea52356e3/resources/6021e080-1951-495c-97d1-3fd1b4e3b0bb http://www.w3.org/1999/02/22-rdf-syntax-ns#type http://purl.org/dc/terms/BibliographicResource https://w3id.org/ro-id/374d0d3a-4807-4925-be83-b9eea52356e3/resources/6021e080-1951-495c-97d1-3fd1b4e3b0bb http://www.w3.org/1999/02/22-rdf-syntax-ns#type http://purl.org/wf4ever/wf4ever#Resource https://w3id.org/ro-id/374d0d3a-4807-4925-be83-b9eea52356e3/resources/6021e080-1951-495c-97d1-3fd1b4e3b0bb http://www.w3.org/1999/02/22-rdf-syntax-ns#type http://schema.org/MediaObject https://w3id.org/ro-id/374d0d3a-4807-4925-be83-b9eea52356e3/resources/729c0b49-df8a-42de-8059-1a220c51f353 http://schema.org/author mailto:jean.iaquinta@geo.uio.no https://w3id.org/ro-id/374d0d3a-4807-4925-be83-b9eea52356e3/resources/729c0b49-df8a-42de-8059-1a220c51f353 http://schema.org/contentSize 12135323 https://w3id.org/ro-id/374d0d3a-4807-4925-be83-b9eea52356e3/resources/729c0b49-df8a-42de-8059-1a220c51f353 http://schema.org/contentUrl https://api.rohub.org/api/resources/729c0b49-df8a-42de-8059-1a220c51f353/download/ https://w3id.org/ro-id/374d0d3a-4807-4925-be83-b9eea52356e3/resources/729c0b49-df8a-42de-8059-1a220c51f353 http://schema.org/creator mailto:jean.iaquinta@geo.uio.no https://w3id.org/ro-id/374d0d3a-4807-4925-be83-b9eea52356e3/resources/729c0b49-df8a-42de-8059-1a220c51f353 http://schema.org/dateCreated 2021-12-20 11:30:13.530879+00:00 https://w3id.org/ro-id/374d0d3a-4807-4925-be83-b9eea52356e3/resources/729c0b49-df8a-42de-8059-1a220c51f353 http://schema.org/dateModified 2021-12-20 13:58:53.392534+00:00 https://w3id.org/ro-id/374d0d3a-4807-4925-be83-b9eea52356e3/resources/729c0b49-df8a-42de-8059-1a220c51f353 http://schema.org/description In this paper the authors quantify the reductions in primary emissions due to the COVID-19 lockdowns in Europe. Their estimates are provided in the form of a dataset of reduction factors varying per country and day that will allow the modelling and identification of the associated impacts upon air quality. https://w3id.org/ro-id/374d0d3a-4807-4925-be83-b9eea52356e3/resources/729c0b49-df8a-42de-8059-1a220c51f353 http://schema.org/encodingFormat application/pdf https://w3id.org/ro-id/374d0d3a-4807-4925-be83-b9eea52356e3/resources/729c0b49-df8a-42de-8059-1a220c51f353 http://schema.org/license https://choosealicense.com/no-permission/ https://w3id.org/ro-id/374d0d3a-4807-4925-be83-b9eea52356e3/resources/729c0b49-df8a-42de-8059-1a220c51f353 http://schema.org/name Time-resolved emission reductions for atmospheric chemistry modelling in Europe during the COVID-19 lockdowns https://w3id.org/ro-id/374d0d3a-4807-4925-be83-b9eea52356e3/resources/729c0b49-df8a-42de-8059-1a220c51f353 http://schema.org/sdDatePublished 2021-12-20 11:30:13.530879+00:00 https://w3id.org/ro-id/374d0d3a-4807-4925-be83-b9eea52356e3/resources/729c0b49-df8a-42de-8059-1a220c51f353 http://www.w3.org/1999/02/22-rdf-syntax-ns#type http://purl.org/wf4ever/roterms#Paper https://w3id.org/ro-id/374d0d3a-4807-4925-be83-b9eea52356e3/resources/729c0b49-df8a-42de-8059-1a220c51f353 http://www.w3.org/1999/02/22-rdf-syntax-ns#type http://purl.org/wf4ever/wf4ever#Resource https://w3id.org/ro-id/374d0d3a-4807-4925-be83-b9eea52356e3/resources/729c0b49-df8a-42de-8059-1a220c51f353 http://www.w3.org/1999/02/22-rdf-syntax-ns#type http://schema.org/MediaObject https://w3id.org/ro-id/374d0d3a-4807-4925-be83-b9eea52356e3/resources/9c87dcef-0fd1-4225-8134-a79e4eaa2da3 http://schema.org/author mailto:jean.iaquinta@geo.uio.no https://w3id.org/ro-id/374d0d3a-4807-4925-be83-b9eea52356e3/resources/9c87dcef-0fd1-4225-8134-a79e4eaa2da3 http://schema.org/contentUrl https://earthobservatory.nasa.gov/images/87910/scientists-show-connection-between-gas-flaring-and-arctic-pollution https://w3id.org/ro-id/374d0d3a-4807-4925-be83-b9eea52356e3/resources/9c87dcef-0fd1-4225-8134-a79e4eaa2da3 http://schema.org/creator mailto:jean.iaquinta@geo.uio.no https://w3id.org/ro-id/374d0d3a-4807-4925-be83-b9eea52356e3/resources/9c87dcef-0fd1-4225-8134-a79e4eaa2da3 http://schema.org/dateCreated 2021-12-20 11:35:42.183038+00:00 https://w3id.org/ro-id/374d0d3a-4807-4925-be83-b9eea52356e3/resources/9c87dcef-0fd1-4225-8134-a79e4eaa2da3 http://schema.org/dateModified 2021-12-20 11:36:06.522620+00:00 https://w3id.org/ro-id/374d0d3a-4807-4925-be83-b9eea52356e3/resources/9c87dcef-0fd1-4225-8134-a79e4eaa2da3 http://schema.org/description Waste natural gas from industrial oil and gas fields could be a source of nitrogen dioxide and black carbon pollution, according to new research. https://w3id.org/ro-id/374d0d3a-4807-4925-be83-b9eea52356e3/resources/9c87dcef-0fd1-4225-8134-a79e4eaa2da3 http://schema.org/license https://choosealicense.com/no-permission/ https://w3id.org/ro-id/374d0d3a-4807-4925-be83-b9eea52356e3/resources/9c87dcef-0fd1-4225-8134-a79e4eaa2da3 http://schema.org/name Scientists Show Connection Between Gas Flaring and Arctic Pollution https://w3id.org/ro-id/374d0d3a-4807-4925-be83-b9eea52356e3/resources/9c87dcef-0fd1-4225-8134-a79e4eaa2da3 http://schema.org/sdDatePublished 2021-12-20 11:35:42.183038+00:00 https://w3id.org/ro-id/374d0d3a-4807-4925-be83-b9eea52356e3/resources/9c87dcef-0fd1-4225-8134-a79e4eaa2da3 http://www.w3.org/1999/02/22-rdf-syntax-ns#type http://purl.org/dc/terms/BibliographicResource https://w3id.org/ro-id/374d0d3a-4807-4925-be83-b9eea52356e3/resources/9c87dcef-0fd1-4225-8134-a79e4eaa2da3 http://www.w3.org/1999/02/22-rdf-syntax-ns#type http://purl.org/wf4ever/wf4ever#Resource https://w3id.org/ro-id/374d0d3a-4807-4925-be83-b9eea52356e3/resources/9c87dcef-0fd1-4225-8134-a79e4eaa2da3 http://www.w3.org/1999/02/22-rdf-syntax-ns#type http://schema.org/MediaObject https://w3id.org/ro-id/374d0d3a-4807-4925-be83-b9eea52356e3/resources/a64fed5b-e924-4d23-b778-9832e56115bc http://schema.org/author mailto:jean.iaquinta@geo.uio.no https://w3id.org/ro-id/374d0d3a-4807-4925-be83-b9eea52356e3/resources/a64fed5b-e924-4d23-b778-9832e56115bc http://schema.org/contentUrl https://www.scitepress.org/Papers/2021/103972/103972.pdf https://w3id.org/ro-id/374d0d3a-4807-4925-be83-b9eea52356e3/resources/a64fed5b-e924-4d23-b778-9832e56115bc http://schema.org/creator mailto:jean.iaquinta@geo.uio.no https://w3id.org/ro-id/374d0d3a-4807-4925-be83-b9eea52356e3/resources/a64fed5b-e924-4d23-b778-9832e56115bc http://schema.org/dateCreated 2021-12-20 13:56:47.380772+00:00 https://w3id.org/ro-id/374d0d3a-4807-4925-be83-b9eea52356e3/resources/a64fed5b-e924-4d23-b778-9832e56115bc http://schema.org/dateModified 2021-12-20 13:56:47.381322+00:00 https://w3id.org/ro-id/374d0d3a-4807-4925-be83-b9eea52356e3/resources/a64fed5b-e924-4d23-b778-9832e56115bc http://schema.org/description This study has used, in a first stage, Sentinel-5P and CAMS service to analyze the air quality in the territory of Iberian Peninsula, as well as assess in detail major cities within the region (Lisbon, Porto and Madrid), for a period from January 2018 to April 2020. On a later stage, the data from Sentinel-3A and 3B allowed the analysis of water quality during the months March, April and May 2020, in the Portuguese coast. Regarding the air quality, NO2 and PM10 levels in the Iberian Peninsula were consistently lower compared to the same periods in the two past years. https://w3id.org/ro-id/374d0d3a-4807-4925-be83-b9eea52356e3/resources/a64fed5b-e924-4d23-b778-9832e56115bc http://schema.org/encodingFormat application/pdf https://w3id.org/ro-id/374d0d3a-4807-4925-be83-b9eea52356e3/resources/a64fed5b-e924-4d23-b778-9832e56115bc http://schema.org/license https://choosealicense.com/no-permission/ https://w3id.org/ro-id/374d0d3a-4807-4925-be83-b9eea52356e3/resources/a64fed5b-e924-4d23-b778-9832e56115bc http://schema.org/name Air and Water Quality Improvement during COVID-19 lockdown https://w3id.org/ro-id/374d0d3a-4807-4925-be83-b9eea52356e3/resources/a64fed5b-e924-4d23-b778-9832e56115bc http://schema.org/sdDatePublished 2021-12-20 13:56:47.380772+00:00 https://w3id.org/ro-id/374d0d3a-4807-4925-be83-b9eea52356e3/resources/a64fed5b-e924-4d23-b778-9832e56115bc http://www.w3.org/1999/02/22-rdf-syntax-ns#type http://purl.org/wf4ever/roterms#Paper https://w3id.org/ro-id/374d0d3a-4807-4925-be83-b9eea52356e3/resources/a64fed5b-e924-4d23-b778-9832e56115bc http://www.w3.org/1999/02/22-rdf-syntax-ns#type http://purl.org/wf4ever/wf4ever#Resource https://w3id.org/ro-id/374d0d3a-4807-4925-be83-b9eea52356e3/resources/a64fed5b-e924-4d23-b778-9832e56115bc http://www.w3.org/1999/02/22-rdf-syntax-ns#type http://schema.org/MediaObject https://w3id.org/ro-id/374d0d3a-4807-4925-be83-b9eea52356e3/resources/acb77822-d471-413d-a825-ad569e28f4dd http://schema.org/author mailto:jean.iaquinta@geo.uio.no https://w3id.org/ro-id/374d0d3a-4807-4925-be83-b9eea52356e3/resources/acb77822-d471-413d-a825-ad569e28f4dd http://schema.org/contentUrl https://arxiv.org/pdf/2106.13750.pdf https://w3id.org/ro-id/374d0d3a-4807-4925-be83-b9eea52356e3/resources/acb77822-d471-413d-a825-ad569e28f4dd http://schema.org/creator mailto:jean.iaquinta@geo.uio.no https://w3id.org/ro-id/374d0d3a-4807-4925-be83-b9eea52356e3/resources/acb77822-d471-413d-a825-ad569e28f4dd http://schema.org/dateCreated 2021-12-20 13:51:17.829614+00:00 https://w3id.org/ro-id/374d0d3a-4807-4925-be83-b9eea52356e3/resources/acb77822-d471-413d-a825-ad569e28f4dd http://schema.org/dateModified 2021-12-20 13:57:34.731243+00:00 https://w3id.org/ro-id/374d0d3a-4807-4925-be83-b9eea52356e3/resources/acb77822-d471-413d-a825-ad569e28f4dd http://schema.org/description In this work the authors investigate the short-term variations in air quality emissions, attributed to the prevention measures, applied in different cities, to mitigate the COVID-19 spread. Part of the analysis employs a variety of machine learning tools. https://w3id.org/ro-id/374d0d3a-4807-4925-be83-b9eea52356e3/resources/acb77822-d471-413d-a825-ad569e28f4dd http://schema.org/encodingFormat application/pdf https://w3id.org/ro-id/374d0d3a-4807-4925-be83-b9eea52356e3/resources/acb77822-d471-413d-a825-ad569e28f4dd http://schema.org/license https://choosealicense.com/no-permission/ https://w3id.org/ro-id/374d0d3a-4807-4925-be83-b9eea52356e3/resources/acb77822-d471-413d-a825-ad569e28f4dd http://schema.org/name Assessing the Lockdown Effects on Air Quality during COVID-19 Era https://w3id.org/ro-id/374d0d3a-4807-4925-be83-b9eea52356e3/resources/acb77822-d471-413d-a825-ad569e28f4dd http://schema.org/sdDatePublished 2021-12-20 13:51:17.829614+00:00 https://w3id.org/ro-id/374d0d3a-4807-4925-be83-b9eea52356e3/resources/acb77822-d471-413d-a825-ad569e28f4dd http://www.w3.org/1999/02/22-rdf-syntax-ns#type http://purl.org/wf4ever/roterms#Paper https://w3id.org/ro-id/374d0d3a-4807-4925-be83-b9eea52356e3/resources/acb77822-d471-413d-a825-ad569e28f4dd http://www.w3.org/1999/02/22-rdf-syntax-ns#type http://purl.org/wf4ever/wf4ever#Resource https://w3id.org/ro-id/374d0d3a-4807-4925-be83-b9eea52356e3/resources/acb77822-d471-413d-a825-ad569e28f4dd http://www.w3.org/1999/02/22-rdf-syntax-ns#type http://schema.org/MediaObject https://w3id.org/ro-id/374d0d3a-4807-4925-be83-b9eea52356e3/resources/b37476c6-244e-4b80-8268-03c5fc1c7de6 http://schema.org/author https://orcid.org/0000-0002-1784-2920 https://w3id.org/ro-id/374d0d3a-4807-4925-be83-b9eea52356e3/resources/b37476c6-244e-4b80-8268-03c5fc1c7de6 http://schema.org/contentSize 1297785 https://w3id.org/ro-id/374d0d3a-4807-4925-be83-b9eea52356e3/resources/b37476c6-244e-4b80-8268-03c5fc1c7de6 http://schema.org/contentUrl https://api.rohub.org/api/resources/b37476c6-244e-4b80-8268-03c5fc1c7de6/download/ https://w3id.org/ro-id/374d0d3a-4807-4925-be83-b9eea52356e3/resources/b37476c6-244e-4b80-8268-03c5fc1c7de6 http://schema.org/creator https://orcid.org/0000-0002-1784-2920 https://w3id.org/ro-id/374d0d3a-4807-4925-be83-b9eea52356e3/resources/b37476c6-244e-4b80-8268-03c5fc1c7de6 http://schema.org/dateCreated 2022-03-17 17:37:17.618246+00:00 https://w3id.org/ro-id/374d0d3a-4807-4925-be83-b9eea52356e3/resources/b37476c6-244e-4b80-8268-03c5fc1c7de6 http://schema.org/dateModified 2022-03-17 17:37:24.230848+00:00 https://w3id.org/ro-id/374d0d3a-4807-4925-be83-b9eea52356e3/resources/b37476c6-244e-4b80-8268-03c5fc1c7de6 http://schema.org/description Paris coronavirus. Man wearing a mask walking in front of the Eiffel Tower on the first day of Paris lock-down. Photo by The Paris Photographer on Unsplash https://w3id.org/ro-id/374d0d3a-4807-4925-be83-b9eea52356e3/resources/b37476c6-244e-4b80-8268-03c5fc1c7de6 http://schema.org/encodingFormat image/jpeg https://w3id.org/ro-id/374d0d3a-4807-4925-be83-b9eea52356e3/resources/b37476c6-244e-4b80-8268-03c5fc1c7de6 http://schema.org/license https://choosealicense.com/no-permission/ https://w3id.org/ro-id/374d0d3a-4807-4925-be83-b9eea52356e3/resources/b37476c6-244e-4b80-8268-03c5fc1c7de6 http://schema.org/name Paris during the lockdown https://w3id.org/ro-id/374d0d3a-4807-4925-be83-b9eea52356e3/resources/b37476c6-244e-4b80-8268-03c5fc1c7de6 http://schema.org/sdDatePublished 2022-03-17 17:37:17.618246+00:00 https://w3id.org/ro-id/374d0d3a-4807-4925-be83-b9eea52356e3/resources/b37476c6-244e-4b80-8268-03c5fc1c7de6 http://www.w3.org/1999/02/22-rdf-syntax-ns#type http://purl.org/wf4ever/roterms#Sketch https://w3id.org/ro-id/374d0d3a-4807-4925-be83-b9eea52356e3/resources/b37476c6-244e-4b80-8268-03c5fc1c7de6 http://www.w3.org/1999/02/22-rdf-syntax-ns#type http://purl.org/wf4ever/wf4ever#Resource https://w3id.org/ro-id/374d0d3a-4807-4925-be83-b9eea52356e3/resources/b37476c6-244e-4b80-8268-03c5fc1c7de6 http://www.w3.org/1999/02/22-rdf-syntax-ns#type http://schema.org/MediaObject https://w3id.org/ro-id/374d0d3a-4807-4925-be83-b9eea52356e3/resources/bc3d57ea-d82b-4261-9af7-24e949d1d5f5 http://schema.org/author mailto:jean.iaquinta@geo.uio.no https://w3id.org/ro-id/374d0d3a-4807-4925-be83-b9eea52356e3/resources/bc3d57ea-d82b-4261-9af7-24e949d1d5f5 http://schema.org/contentSize 291862 https://w3id.org/ro-id/374d0d3a-4807-4925-be83-b9eea52356e3/resources/bc3d57ea-d82b-4261-9af7-24e949d1d5f5 http://schema.org/contentUrl https://api.rohub.org/api/resources/bc3d57ea-d82b-4261-9af7-24e949d1d5f5/download/ https://w3id.org/ro-id/374d0d3a-4807-4925-be83-b9eea52356e3/resources/bc3d57ea-d82b-4261-9af7-24e949d1d5f5 http://schema.org/creator mailto:jean.iaquinta@geo.uio.no https://w3id.org/ro-id/374d0d3a-4807-4925-be83-b9eea52356e3/resources/bc3d57ea-d82b-4261-9af7-24e949d1d5f5 http://schema.org/dateCreated 2021-12-20 11:28:32.188824+00:00 https://w3id.org/ro-id/374d0d3a-4807-4925-be83-b9eea52356e3/resources/bc3d57ea-d82b-4261-9af7-24e949d1d5f5 http://schema.org/dateModified 2021-12-20 13:59:25.789565+00:00 https://w3id.org/ro-id/374d0d3a-4807-4925-be83-b9eea52356e3/resources/bc3d57ea-d82b-4261-9af7-24e949d1d5f5 http://schema.org/description Concawe has undertaken a city-level analysis to quantify the ways in which the Covid-19 lockdown measures have had an impact on air quality in Europe. This article presents the results of the analysis for particulate matter (PM 2.5 ), nitrogen dioxide (NO2 ) and ozone (O3 ). https://w3id.org/ro-id/374d0d3a-4807-4925-be83-b9eea52356e3/resources/bc3d57ea-d82b-4261-9af7-24e949d1d5f5 http://schema.org/encodingFormat application/pdf https://w3id.org/ro-id/374d0d3a-4807-4925-be83-b9eea52356e3/resources/bc3d57ea-d82b-4261-9af7-24e949d1d5f5 http://schema.org/license https://choosealicense.com/no-permission/ https://w3id.org/ro-id/374d0d3a-4807-4925-be83-b9eea52356e3/resources/bc3d57ea-d82b-4261-9af7-24e949d1d5f5 http://schema.org/name How Covid-19 lockdown affected air pollution in Europe — a multi-city analysis https://w3id.org/ro-id/374d0d3a-4807-4925-be83-b9eea52356e3/resources/bc3d57ea-d82b-4261-9af7-24e949d1d5f5 http://schema.org/sdDatePublished 2021-12-20 11:28:32.188824+00:00 https://w3id.org/ro-id/374d0d3a-4807-4925-be83-b9eea52356e3/resources/bc3d57ea-d82b-4261-9af7-24e949d1d5f5 http://www.w3.org/1999/02/22-rdf-syntax-ns#type http://purl.org/wf4ever/wf4ever#Resource https://w3id.org/ro-id/374d0d3a-4807-4925-be83-b9eea52356e3/resources/bc3d57ea-d82b-4261-9af7-24e949d1d5f5 http://www.w3.org/1999/02/22-rdf-syntax-ns#type http://schema.org/MediaObject https://w3id.org/ro-id/374d0d3a-4807-4925-be83-b9eea52356e3/resources/bc3d57ea-d82b-4261-9af7-24e949d1d5f5 http://www.w3.org/1999/02/22-rdf-syntax-ns#type http://schema.org/publication https://w3id.org/ro-id/374d0d3a-4807-4925-be83-b9eea52356e3/resources/bc6922f1-debf-46ae-ba79-d574f6f5c064 http://schema.org/author mailto:jean.iaquinta@geo.uio.no https://w3id.org/ro-id/374d0d3a-4807-4925-be83-b9eea52356e3/resources/bc6922f1-debf-46ae-ba79-d574f6f5c064 http://schema.org/contentSize 2276065 https://w3id.org/ro-id/374d0d3a-4807-4925-be83-b9eea52356e3/resources/bc6922f1-debf-46ae-ba79-d574f6f5c064 http://schema.org/contentUrl https://api.rohub.org/api/resources/bc6922f1-debf-46ae-ba79-d574f6f5c064/download/ https://w3id.org/ro-id/374d0d3a-4807-4925-be83-b9eea52356e3/resources/bc6922f1-debf-46ae-ba79-d574f6f5c064 http://schema.org/creator mailto:jean.iaquinta@geo.uio.no https://w3id.org/ro-id/374d0d3a-4807-4925-be83-b9eea52356e3/resources/bc6922f1-debf-46ae-ba79-d574f6f5c064 http://schema.org/dateCreated 2021-12-20 11:33:04.445345+00:00 https://w3id.org/ro-id/374d0d3a-4807-4925-be83-b9eea52356e3/resources/bc6922f1-debf-46ae-ba79-d574f6f5c064 http://schema.org/dateModified 2021-12-20 13:59:59.434971+00:00 https://w3id.org/ro-id/374d0d3a-4807-4925-be83-b9eea52356e3/resources/bc6922f1-debf-46ae-ba79-d574f6f5c064 http://schema.org/description 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, PM 2.5 and PM 10 in most cities, mainly due to the reduction of transportation, industry and commercial activities during lockdown. https://w3id.org/ro-id/374d0d3a-4807-4925-be83-b9eea52356e3/resources/bc6922f1-debf-46ae-ba79-d574f6f5c064 http://schema.org/encodingFormat application/pdf https://w3id.org/ro-id/374d0d3a-4807-4925-be83-b9eea52356e3/resources/bc6922f1-debf-46ae-ba79-d574f6f5c064 http://schema.org/license https://choosealicense.com/no-permission/ https://w3id.org/ro-id/374d0d3a-4807-4925-be83-b9eea52356e3/resources/bc6922f1-debf-46ae-ba79-d574f6f5c064 http://schema.org/name Impact of the COVID-19 Pandemic Lockdown on Air Pollution in 20 Major Cities around the World https://w3id.org/ro-id/374d0d3a-4807-4925-be83-b9eea52356e3/resources/bc6922f1-debf-46ae-ba79-d574f6f5c064 http://schema.org/sdDatePublished 2021-12-20 11:33:04.445345+00:00 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