Uncertainty of eddy covariance flux measurements over an urban area based on two towers

The eddy covariance (EC) technique is the most direct method for measuring the exchange between the surface and the atmosphere in different ecosystems. Thus, it is commonly used to get information on air pollutant and greenhouse gas emissions, and on turbulent heat transfer. Typically an ecosystem is monitored by only one single EC measurement station at a time, making the ecosystem-level flux values subject to random and systematic uncertainties. Furthermore, in urban ecosystems we often have no choice but to conduct the single-point measurements in non-ideal locations such as close to buildings and/or in the roughness sub-layer, bringing further complications to data analysis and flux estimations. In order to tackle the question of how representative a single EC measurement point in an urban area can be, two identical EC systems - measuring momentum, sensible and latent heat, and carbon dioxide fluxes - were installed on each side of the same building structure in central Helsinki, Finland, during July 2013-September 2015. The main interests were to understand the sensitivity of the vertical fluxes on the single measurement point and to estimate the systematic uncertainty in annual cumulative values due to missing data if certain, relatively wide, flow-distorted wind sectors are disregarded. The momentum and measured scalar fluxes respond very differently to the distortion caused by the building structure. The momentum flux is the most sensitive to the measurement location, whereas scalar fluxes are less impacted. The flow distortion areas of the two EC systems (40-150 and 230-340 degrees) are best detected from the mean-wind-normalised turbulent kinetic energy, and outside these areas the median relative random uncertainties of the studied fluxes measured by one system are between 12 % and 28 %. Different gap-filling methods with which to yield annual cumulative fluxes show how using data from a single EC measurement point can cause up to a 12 % (480 g C m(-2)) underestimation in the cumulative carbon fluxes as compared to combined data from the two systems. Combining the data from two EC systems also increases the fraction of usable half-hourly carbon fluxes from 45 % to 69 % at the annual level. For sensible and latent heat, the respective underestimations are up to 5 % and 8 % (0.094 and 0.069 TJ m(-2)). The obtained random and systematic uncertainties are in the same range as observed in vegetated ecosystems. We also show how the commonly used data flagging criteria in natural ecosystems, kurtosis and skewness, are not necessarily suitable for filtering out data in a densely built urban environment. The results show how the single measurement system can be used to derive representative flux values for central Helsinki, but the addition of second system to other side of the building structure decreases the systematic uncertainties. Comparable results can be expected in similarly dense city locations where no large directional deviations in the source area are seen. In general, the obtained results will aid the scientific community by providing information about the sensitivity of EC measurements and their quality flagging in urban areas.Peer reviewe

Finnish Centre of Excellence in Physics, Chemistry, Biology and Meteorology of Atmospheric Composition and Climate Change : summary and outlook

Peer reviewe

Pan-Eurasian Experiment (PEEX) : towards a holistic understanding of the feedbacks and interactions in the land–atmosphere–ocean–society continuum in the northern Eurasian region

Contributors: Hanna K. Lappalainen1,2, Veli-Matti Kerminen1, Tuukka Petäjä1, Theo Kurten3, Aleksander Baklanov4,5, Anatoly Shvidenko6, Jaana Bäck7, Timo Vihma2, Pavel Alekseychik1, Stephen Arnold8, Mikhail Arshinov9, Eija Asmi2, Boris Belan9, Leonid Bobylev10, Sergey Chalov11, Yafang Cheng12, Natalia Chubarova11, Gerrit de Leeuw1,2, Aijun Ding13, Sergey Dobrolyubov11, Sergei Dubtsov14, Egor Dyukarev15, Nikolai Elansky16, Kostas Eleftheriadis17, Igor Esau18, Nikolay Filatov19, Mikhail Flint20, Congbin Fu13, Olga Glezer21, Aleksander Gliko22, Martin Heimann23, Albert A. M. Holtslag24, Urmas Hõrrak25, Juha Janhunen26, Sirkku Juhola27, Leena Järvi1, Heikki Järvinen1, Anna Kanukhina28, Pavel Konstantinov11, Vladimir Kotlyakov29, Antti-Jussi Kieloaho1, Alexander S. Komarov30, Joni Kujansuu1, Ilmo Kukkonen31, Ella Kyrö1, Ari Laaksonen2, Tuomas Laurila2, Heikki Lihavainen2, Alexander Lisitzin32, Aleksander Mahura5, Alexander Makshtas33, Evgeny Mareev34, Stephany Mazon1, Dmitry Matishov35,†, Vladimir Melnikov36, Eugene Mikhailov37, Dmitri Moisseev1, Robert Nigmatulin33, Steffen M. Noe38, Anne Ojala7, Mari Pihlatie1, Olga Popovicheva39, Jukka Pumpanen40, Tatjana Regerand19, Irina Repina16, Aleksei Shcherbinin27, Vladimir Shevchenko33, Mikko Sipilä1, Andrey Skorokhod16, Dominick V. Spracklen8, Hang Su12, Dmitry A. Subetto19, Junying Sun41, Arkady Yu Terzhevik19, Yuri Timofeyev42, Yuliya Troitskaya34, Veli-Pekka Tynkkynen42, Viacheslav I. Kharuk43, Nina Zaytseva22, Jiahua Zhang44, Yrjö Viisanen2, Timo Vesala1, Pertti Hari7, Hans Christen Hansson45, Gennady G. Matvienko9, Nikolai S. Kasimov11, Huadong Guo44, Valery Bondur46, Sergej Zilitinkevich1,2,11,34, and Markku Kulmala1 1Department of Physics, University of Helsinki, 00014 Helsinki, Finland 2Finnish Meteorological Institute, Research and Development, 00101 Helsinki, Finland 3Department of Chemistry, University of Helsinki, 00014 Helsinki, Finland 4World Meteorological Organization, 1211 Genève, Switzerland 5Danish Meteorological Institute, Research and Development Department, 2100, Copenhagen 6International Institute for Applied Systems Analysis, 2361 Laxenburg, Austria 7Department of Forest Sciences, University of Helsinki, 00014 Helsinki, Finland 8Institute for Climate and Atmospheric Science, School of Earth and Environment, University of Leeds, Leeds, LS2 9JT, UK 9Institute of Atmospheric Optics, Russian Academy of Sciences, Tomsk 634021, Russia 10Nansen International Environmental and Remote Sensing Center, St. Petersburg, Russia 11Lomonosov Moscow State University, Faculty of Geography, Moscow 119899, Russia 12Max Planck Institute for Chemistry, 55128 Mainz, Germany 13Institute for Climate and Global Change Research & School of Atmospheric Sciences, Nanjing University, 210023 Nanjing, China 14Institute of Chemical Kinetics & Combustion, Russian Academy of Sciences, 630090 Novosibirsk, Russia 15Institute of Monitoring of Climatic & Ecological Systems SB RAS, 634055 Tomsk, Russia 16A. M. Obukhov Institute of Atmospheric Physics, Russian Academy of Sciences, Russia 17National Centre of Scientific Research "DEMOKRITOS", Greece 18Nansen Environmental and Remote Sensing Center/Bjerknes Centre for Climate Research, 5006 Bergen, Norway 19Northern Water Problems Institute, Karelian Research Center, Russian Academy of Sciences,185003 Petrozavodsk, Russia 20P. P. Shirshov, Institute of Oceanology, Russian Academy of Sciences, Russian Academy of Sciences, 117997 Moscow, Russia 21Institute of Geography, Russian Academy of Sciences, Moscow, Russia 22Depart ment of Earth Sciences of the Russian Academy of Sciences, Russian Academy of Sciences, 119991, Moscow, Russia 23Max-Planck-Institute for Biogeochemistry, 07745 Jena, Germany 24Wageningen University, 6708 Wageningen, Nederland 25Institute of Physics, University of Tartu, 18 Ülikooli St., 50090 Tartu, Estonia 26University of Helsinki, Department of World Cultures, 00014 Helsinki, Finland 27Department of Environmental Sciences, University of Helsinki, 00014 Helsinki, Finland 28Russian State Hydrometeorological University, 195196 Saint Petersburg, Russia 29Institute of Geography, Russian Academy of Sciences, Moscow, Russia 30Institute of Physico-chemical & Biological Problems in Soil Science, Russian Academy of Sciences, 142290 Institutskaya, Russia 31University of Helsinki, Geophysics and Astronomy, 00014 Helsinki, Finland 32Shirshov Institute of Oceanology, Russian Academy of Sciences, 117997 Moscow, Russia 33Actic & Antarctic Research Institute, Russian Academy of Sciences, St. Petersburg 199397, Russia 34Department of Radiophysics, Nizhny Novgorod State University, Nizhny Novgorod, Russia 35Southern Center of Russian Academy of Sciences, Rostov on Don, Russia 36Tyumen Scientific Center, Siberian Branch, Russian Academy of Science, Russia 37Saint Petersburg State University, 7/9 Universitetskaya nab., St. Petersburg, 199034 Russia 38Institute of Agricultural and Environmental Sciences, Estonian University of Life Sciences, 51014 Tartu, Estonia 39Skobeltsyn Institute of Nuclear Physics, Moscow State University, Department Microelectronics, Russia 40University of Eastern Finland, Department of Environmental Science, P.O. Box 1627, FI-70211 Kuopio, Finland 41Craduate University of Chinese Academy of Sciences, 100049 Beijing, China 42Aleksanteri Institute and Department of Social Research, 00014 University of Helsinki, Finland 43Sukachev Forest Institute, Russian Academy of Sciences, Krasnoyarsk 660036, Russia 44Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences, Beijing, 100094, China 45Environmental Science and Analytical Chemistry, Stockholm University, Sweden 46AEROCOSMOS Research Institute for Aerospace Monitoring, 105064, Moscow, Russia †deceased, 20 August 2015The Northern Eurasian regions and Arctic Ocean will very likely undergo substantial changes during the next decades. The arctic-boreal natural environments play a crucial role in the global climate via the albedo change, carbon sources and sinks, as well as atmospheric aerosol production via biogenic volatile organic compounds. Furthermore, it is expected that the global trade activities, demographic movement and use of natural resources will be increasing in the Arctic regions. There is a need for a novel research approach, which not only identifies and tackles the relevant multi-disciplinary research questions, but is also able to make a holistic system analysis of the expected feedbacks. In this paper, we introduce the research agenda of the Pan-Eurasian Experiment (PEEX), a multi-scale, multi-disciplinary and international program started in 2012 (https://www.atm.helsinki.fi/peex/). PEEX is setting a research approach where large-scale research topics are investigated from a system perspective and which aims to fill the key gaps in our understanding of the feedbacks and interactions between the land–atmosphere–aquatic–society continuum in the Northern Eurasian region. We introduce here the state of the art of the key topics in the PEEX research agenda and give the future prospects of the research which we see relevant in this context.Peer reviewe

The Center of Excellence in Atmospheric Science (2002–2019) — from molecular and biological processes to the global climate

The study of atmospheric processes related to climate requires a multidisciplinary approach, encompassing physics, chemistry, meteorology, forest science, and environmental science. The Academy of Finland Centre of Excellence in atmospheric sciences (CoE ATM) responded to that need for 18 years and produced extensive research and eloquent results, which are summarized in this review. The work in the CoE ATM enhanced our understanding in biogeochemical cycles, ecosystem processes, dynamics of aerosols, ions and neutral clusters in the lower atmosphere, and cloud formation and their interactions and feedbacks. The CoE ATM combined continuous and comprehensive long-term in-situ observations in various environments, ecosystems and platforms, ground- and satellitebased remote sensing, targeted laboratory and field experiments, and advanced multi-scale modeling. This has enabled improved conceptual understanding and quantifications across relevant spatial and temporal scales. Overall, the CoE ATM served as a platform for the multidisciplinary research community to explore the interactions between the biosphere and atmosphere under a common and adaptive framework

Case study - Finland

The ultimate purpose of the transport system is to serve the needs and expectations of the end users, who in turn shape the system by their own behaviour, actions and investments. This paper examines, within the framework of the Large Technological Systems theory the possibility to categorise users of the transport system into homogeneous segments on the basis of their differences in daily mobility and transportation of goods. Furthermore, the potential to deepen this segmentation to describe the needs of, but later in the policy process also the social acceptance by, different user groups for new transport technology or policy, is examined