M. Kulmala, A. Lintunen, Ilona Ylivinkka, Janne Mukkala, Rosa Rantanen, J. Kujansuu, T. Petäjä, H. Lappalainen
{"title":"Atmospheric and ecosystem big data providing key contributions in reaching United Nations’ Sustainable Development Goals","authors":"M. Kulmala, A. Lintunen, Ilona Ylivinkka, Janne Mukkala, Rosa Rantanen, J. Kujansuu, T. Petäjä, H. Lappalainen","doi":"10.1080/20964471.2021.1936943","DOIUrl":null,"url":null,"abstract":"ABSTRACT Big open data comprising comprehensive, long-term atmospheric and ecosystem in-situ observations will give us tools to meet global grand challenges and to contribute towards sustainable development. United Nations’ Sustainable Development Goals (UN SDGs) provide framework for the process. We present synthesis on how Station for Measuring Earth Surface–Atmosphere Relations (SMEAR) observation network can contribute to UN SDGs. We describe SMEAR II flagship station in Hyytiälä, Finland. With more than 1200 variables measured in an integrated manner, we can understand interactions and feedbacks between biosphere and atmosphere. This contributes towards understanding impacts of climate change to natural ecosystems and feedbacks from ecosystems to climate. The benefits of SMEAR concept are highlighted through outreach project in Eastern Lapland utilizing SMEAR I observations from Värriö research station. In contrast to boreal environment, SMEAR concept was also deployed in Beijing. We underline the benefits of comprehensive observations to gain novel insights into complex interactions between densely populated urban environment and atmosphere. Such observations enable work towards solving air quality problems and improve the quality of life inside megacities. The network of comprehensive stations with various measurements will enable science-based decision making and support sustainable development by providing long-term view on spatio-temporal trends on atmospheric composition and ecosystem parameters.","PeriodicalId":8765,"journal":{"name":"Big Earth Data","volume":"30 1","pages":"277 - 305"},"PeriodicalIF":4.2000,"publicationDate":"2021-07-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"7","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Big Earth Data","FirstCategoryId":"89","ListUrlMain":"https://doi.org/10.1080/20964471.2021.1936943","RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"COMPUTER SCIENCE, INFORMATION SYSTEMS","Score":null,"Total":0}
引用次数: 7
Abstract
ABSTRACT Big open data comprising comprehensive, long-term atmospheric and ecosystem in-situ observations will give us tools to meet global grand challenges and to contribute towards sustainable development. United Nations’ Sustainable Development Goals (UN SDGs) provide framework for the process. We present synthesis on how Station for Measuring Earth Surface–Atmosphere Relations (SMEAR) observation network can contribute to UN SDGs. We describe SMEAR II flagship station in Hyytiälä, Finland. With more than 1200 variables measured in an integrated manner, we can understand interactions and feedbacks between biosphere and atmosphere. This contributes towards understanding impacts of climate change to natural ecosystems and feedbacks from ecosystems to climate. The benefits of SMEAR concept are highlighted through outreach project in Eastern Lapland utilizing SMEAR I observations from Värriö research station. In contrast to boreal environment, SMEAR concept was also deployed in Beijing. We underline the benefits of comprehensive observations to gain novel insights into complex interactions between densely populated urban environment and atmosphere. Such observations enable work towards solving air quality problems and improve the quality of life inside megacities. The network of comprehensive stations with various measurements will enable science-based decision making and support sustainable development by providing long-term view on spatio-temporal trends on atmospheric composition and ecosystem parameters.