2016 field campaign BEST-ONE (Beijing winter fine particulate Study - Oxidation, Nucleation, and light Extinctions)

Version 1.1

Gkatzelis, Georgios; Dimitrios K. Papanastasiou; Vlassis A. Karydis; Thorsten Hohaus; Ying Liu; Sebastian H. Schmitt; Patrick Schlag; Hendrik Fuchs; Anna Novelli; Qi Chen; Xi Cheng; Sebastian Broch; Huabin Dong; Frank Holland; Xin Li; Yuhan Liu; Xuefei Ma; David Reimer; Franz Rohrer; Min Shao; Zhaofeng Tan; Domenico Taraborrelli; Ralf Tillmann; Haichao Wang; Yu Wang; Yusheng Wu; Zhijun Wu; Limin Zheng; Jun Zheng; Min Hu; Keding Lu; Andreas Hofzumahaus; Yuanhang Zhang; Andreas Wahner; Astrid Kiendler-Scharr, 2020, "2016 field campaign BEST-ONE (Beijing winter fine particulate Study - Oxidation, Nucleation, and light Extinctions)", https://doi.org/10.26165/JUELICH-DATA/BQOLQF, Jülich DATA, V1

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Description	This dataset is based on the 2016 field campaign BEST-ONE (Beijing winter fine particulate Study - Oxidation, Nucleation, and light Extinctions) and is a product of the International Joint Laboratory for Regional Pollution Control, Jülich, Germany, and Beijing, China. More specifically, this dataset is provided in order for users to replicate the results from the Gkatzelis et al. publication. It includes time-series of species in the gas- and particle-phase during measurements performed in Huairou, Northeast of Beijing, in the winter of 2016. Also, provided is the output of the Positive Matrix Factorization model analysis. (2020-11-2)
Subject	Chemistry; Earth and Environmental Sciences
Keyword	Urban pollution, haze events, China
Institute	IEK-8

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	GasPhase_GCMS_ConcentrationData_timeseries.csv Plain Text - 465.7 KB - Nov 3, 2020 - 50 Downloads SHA-256: 72cc1d63c0dab342f8fee40d38720ba0c6e56a7f2d8c4a668c30aedf843ed1e9 Time-series of gas-phase compounds measured by Gas Chromatography-Mass Spectrometry (GC-MS). For each column, the naming e.g. "MethyleneChloride_ppbv", corresponds to the name of the compound (MethyleneChloride), and the measurement units (ppbv=parts per billion). The value -9999 is given to non-existing data. File delimiter is the tabstop.	Download
	GasPhase_NO3CIMS_ConcentrationData_timeseries.csv Plain Text - 460.9 KB - Nov 3, 2020 - 55 Downloads SHA-256: 4eee46ddf4d610b0a00881531dbc3da7c12c477b14b737bb2594b0a6adc4414a Time-series of gas-phase compounds measured by Nitrate Chemical Ionization Mass Spectrometry (NO3-CIMS). For each column, the naming e.g. "SumofMassRange_220to250_pptv", corresponds to the sum of the masses detected in the range from 220 to 250 u. The measurement units are in pptv=parts per trillion. The value -9999 is given to non-existing data. File delimiter is the tabstop.	Download
	GasPhase_PTRToFMS_ConcentrationData_timeseries.csv Plain Text - 5.5 MB - Nov 3, 2020 - 6 Downloads SHA-256: f21496f8db50236018745f1c0afddeb381eecf5f63f627dc65c04151593dbc89 Time-series of gas-phase compounds measured by a Proton Transfer Reaction - Time of Flight - Mass Spectrometer (PTR-ToF-MS). For each column, the naming e.g. "m31_CH2O_ppbv", corresponds to the unit mass of detection (m31 = 31 u), the chemical formula of the detected compound (CH2O), and the measurement units (ppbv=parts per billion). The value -9999 is given to non-existing data. File delimiter is the tabstop.	Download
	Meteorology_RawData_timeseries.csv Plain Text - 215.6 KB - Nov 3, 2020 - 67 Downloads SHA-256: 32afb580ce5d70108fba0180137b0f1d5143019e7a9246ff2a71a52df854b1a9 Time-series of temperature in Celsius units and relative humidity (RH) in %. The value -9999 is given to non-existing data. File delimiter is the tabstop.	Download
	ParticlePhase_AerosolLiquidWater_ConcentrationData_timeseries.csv Plain Text - 154.9 KB - Nov 3, 2020 - 130 Downloads SHA-256: 8b41fc7b28e428dbac5e2d2a523868582fbf583ba7518b7a1c338d12f3d44e1b Time-series of aerosol liquid water in micrograms per cubic meter (ugm3). The value -9999 is given to non-existing data. File delimiter is the tabstop.	Download
	ParticlePhase_AMS_ConcentrationData_timeseries.csv Plain Text - 398.4 KB - Nov 3, 2020 - 2 Downloads SHA-256: 9dd6ca94a422f5b36ae847285c6f1c345d4eb84b45b8f94d85af64e0b1d07826 Time-series of aerosol organics, nitrate, ammonium, sulfate, and chloride in micrograms per cubic meter (ugm3) as derived by an Aerosol Mass Spectrometer. The value -9999 is given to non-existing data. File delimiter is the tabstop.	Download
	PositiveMatrixFactorization_GasPhase_Profiles.csv Plain Text - 9.8 KB - Nov 3, 2020 - 5 Downloads SHA-256: ec01f533a753dcd5eb94419a459d707cd7d9e8f97a1c95b991bd63d8d67b2967 Profiles of the different pollution sources in the gas-phase based on the outcome of the positive matrix factorization model. File delimiter is the tabstop.	Download
	PositiveMatrixFactorization_GasPhase_Timeseries.csv Plain Text - 409.5 KB - Nov 3, 2020 - 3 Downloads SHA-256: 1c6f5dfe7162cee14e48b6774e38d6d6d7ec1bcac4f499cf8fdc75bedbde8d36 Time-series of the different pollution sources in the gas-phase based on the outcome of the positive matrix factorization model. The value -9999 is given to non-existing data. File delimiter is the tabstop.	Download
	PositiveMatrixFactorization_ParticlePhase_Profiles.csv Plain Text - 53.5 KB - Nov 3, 2020 - 3 Downloads SHA-256: 92f62d627219d8612a516446e96e3ca0363d969e236b233907141346619979dc Profiles of the different pollution sources in the particle-phase based on the outcome of the positive matrix factorization model. File delimiter is the tabstop.	Download
	PositiveMatrixFactorization_ParticlePhase_Timeseries.csv Plain Text - 375.8 KB - Nov 3, 2020 - 5 Downloads SHA-256: 04c1af1388f28d4c534155be6c3d685120a5638862450b3a9345a04170125da1 Time-series of the different pollution sources in the particle-phase based on the outcome of the positive matrix factorization model. The value -9999 is given to non-existing data. File delimiter is the tabstop.	Download

Citation Metadata

Dataset Persistent ID	doi:10.26165/JUELICH-DATA/BQOLQF
Publication Date	2020-11-03
Title	2016 field campaign BEST-ONE (Beijing winter fine particulate Study - Oxidation, Nucleation, and light Extinctions)
Author	Gkatzelis, Georgios (Institute of Energy and Climate Research, IEK-8: Troposphere, Forschungszentrum Jülich GmbH, Jülich, Germany.) - ORCID: https://orcid.org/0000-0002-4608-3695 Dimitrios K. Papanastasiou (Independent Researcher, Buffalo NY USA.) - ORCID: https://orcid.org/0000-0003-3963-162X Vlassis A. Karydis (Institute of Energy and Climate Research, IEK-8: Troposphere, Forschungszentrum Jülich GmbH, Jülich, Germany.) - ORCID: https://orcid.org/0000-0002-1616-9746 Thorsten Hohaus (Institute of Energy and Climate Research, IEK-8: Troposphere, Forschungszentrum Jülich GmbH, Jülich, Germany.) - ORCID: https://orcid.org/0000-0001-5722-6244 Ying Liu (State Key Joint Laboratory of Environmental Simulation and Pollution Control, College of Environmental Sciences and Engineering, Peking University, Beijing, China.) Sebastian H. Schmitt (Institute of Energy and Climate Research, IEK-8: Troposphere, Forschungszentrum Jülich GmbH, Jülich, Germany.) - ORCID: https://orcid.org/0000-0002-5491-3572 Patrick Schlag (Institute of Energy and Climate Research, IEK-8: Troposphere, Forschungszentrum Jülich GmbH, Jülich, Germany.) - ORCID: https://orcid.org/0000-0002-0206-8987 Hendrik Fuchs (Institute of Energy and Climate Research, IEK-8: Troposphere, Forschungszentrum Jülich GmbH, Jülich, Germany.) Anna Novelli (Institute of Energy and Climate Research, IEK-8: Troposphere, Forschungszentrum Jülich GmbH, Jülich, Germany.) - ORCID: https://orcid.org/0000-0003-2077-7573 Qi Chen (State Key Joint Laboratory of Environmental Simulation and Pollution Control, College of Environmental Sciences and Engineering, Peking University, Beijing, China.) Xi Cheng (State Key Joint Laboratory of Environmental Simulation and Pollution Control, College of Environmental Sciences and Engineering, Peking University, Beijing, China.) Sebastian Broch (Institute of Energy and Climate Research, IEK-8: Troposphere, Forschungszentrum Jülich GmbH, Jülich, Germany.) - ORCID: https://orcid.org/0000-0001-6768-9058 Huabin Dong (State Key Joint Laboratory of Environmental Simulation and Pollution Control, College of Environmental Sciences and Engineering, Peking University, Beijing, China.) Frank Holland (Institute of Energy and Climate Research, IEK-8: Troposphere, Forschungszentrum Jülich GmbH, Jülich, Germany.) - ORCID: https://orcid.org/0000-0002-2278-4761 Xin Li (State Key Joint Laboratory of Environmental Simulation and Pollution Control, College of Environmental Sciences and Engineering, Peking University, Beijing, China.) Yuhan Liu (State Key Joint Laboratory of Environmental Simulation and Pollution Control, College of Environmental Sciences and Engineering, Peking University, Beijing, China.) Xuefei Ma (State Key Joint Laboratory of Environmental Simulation and Pollution Control, College of Environmental Sciences and Engineering, Peking University, Beijing, China.) David Reimer (Institute of Energy and Climate Research, IEK-8: Troposphere, Forschungszentrum Jülich GmbH, Jülich, Germany.) - ORCID: https://orcid.org/0000-0002-0741-9854 Franz Rohrer (Institute of Energy and Climate Research, IEK-8: Troposphere, Forschungszentrum Jülich GmbH, Jülich, Germany.) Min Shao (State Key Joint Laboratory of Environmental Simulation and Pollution Control, College of Environmental Sciences and Engineering, Peking University, Beijing, China.) Zhaofeng Tan (Institute of Energy and Climate Research, IEK-8: Troposphere, Forschungszentrum Jülich GmbH, Jülich, Germany.) - ORCID: http://orcid.org/0000-0002-3808-1964 Domenico Taraborrelli (Institute of Energy and Climate Research, IEK-8: Troposphere, Forschungszentrum Jülich GmbH, Jülich, Germany.) Ralf Tillmann (Institute of Energy and Climate Research, IEK-8: Troposphere, Forschungszentrum Jülich GmbH, Jülich, Germany.) Haichao Wang (State Key Joint Laboratory of Environmental Simulation and Pollution Control, College of Environmental Sciences and Engineering, Peking University, Beijing, China.) - ORCID: https://orcid.org/0000-0001-6161-1874 Yu Wang (State Key Joint Laboratory of Environmental Simulation and Pollution Control, College of Environmental Sciences and Engineering, Peking University, Beijing, China.) Yusheng Wu (State Key Joint Laboratory of Environmental Simulation and Pollution Control, College of Environmental Sciences and Engineering, Peking University, Beijing, China.) Zhijun Wu (State Key Joint Laboratory of Environmental Simulation and Pollution Control, College of Environmental Sciences and Engineering, Peking University, Beijing, China.) Limin Zheng (State Key Joint Laboratory of Environmental Simulation and Pollution Control, College of Environmental Sciences and Engineering, Peking University, Beijing, China.) Jun Zheng (State Key Joint Laboratory of Environmental Simulation and Pollution Control, College of Environmental Sciences and Engineering, Peking University, Beijing, China.) Min Hu (State Key Joint Laboratory of Environmental Simulation and Pollution Control, College of Environmental Sciences and Engineering, Peking University, Beijing, China.) Keding Lu (State Key Joint Laboratory of Environmental Simulation and Pollution Control, College of Environmental Sciences and Engineering, Peking University, Beijing, China.) - ORCID: https://orcid.org/0000-0001-9425-9520 Andreas Hofzumahaus (Institute of Energy and Climate Research, IEK-8: Troposphere, Forschungszentrum Jülich GmbH, Jülich, Germany.) - ORCID: https://orcid.org/0000-0003-2876-0880 Yuanhang Zhang (International Joint Laboratory for Regional Pollution Control, Jülich, Germany, and Beijing, China) Andreas Wahner (Institute of Energy and Climate Research, IEK-8: Troposphere, Forschungszentrum Jülich GmbH, Jülich, Germany.) - ORCID: https://orcid.org/0000-0001-8948-1928 Astrid Kiendler-Scharr (Institute of Energy and Climate Research, IEK-8: Troposphere, Forschungszentrum Jülich GmbH, Jülich, Germany.) - ORCID: https://orcid.org/0000-0003-3166-2253
Contact	Use email button above to contact. Gkatzelis, Georgios (Institute of Energy and Climate Research, IEK-8: Troposphere, Forschungszentrum Jülich GmbH, Jülich, Germany.)
Description	This dataset is based on the 2016 field campaign BEST-ONE (Beijing winter fine particulate Study - Oxidation, Nucleation, and light Extinctions) and is a product of the International Joint Laboratory for Regional Pollution Control, Jülich, Germany, and Beijing, China. More specifically, this dataset is provided in order for users to replicate the results from the Gkatzelis et al. publication. It includes time-series of species in the gas- and particle-phase during measurements performed in Huairou, Northeast of Beijing, in the winter of 2016. Also, provided is the output of the Positive Matrix Factorization model analysis. (2020-11-2)
Subject	Chemistry; Earth and Environmental Sciences
Keyword	Urban pollution, haze events, China
Language	English
Depositor	Gkatzelis, Georgios
Deposit Date	2020-11-02
Time Period Covered	Start: 2016-01-01 ; End: 2016-03-07
Date of Collection	Start: 2016-01-01 ; End: 2016-03-07
Kind of Data	observation data; process-produced data
Software	IGOR Pro, Version: 6

FZJ Metadata

Institute	IEK-8
PoF III topic	Tropospheric trace substances and their transformation processes (POF3-243)
PoF IV topic	Acquisition before PoF IV (2021-2026) (POF4-898)

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