The dataset integrates the comprehensive observational data of atmospheric aerosols at several remote background and urban sites over the Tibetan Plateau (TP) and its surroundings in recent years by our group team. The high-time-resolution dynamic evolution of aerosol physical, chemical, and optical properties in the different TP sites are measured on-line by deploying a suite of advanced high-resolution real-time instruments. The chemical composition, size distribution, bulk acidity, and diurnal variation of submicron aerosols, the high-resolution mass spectrum and components of organic aerosols (OAs), the size distribution of particle number concentration, the particle light scattering and absorption coefficients, the light absorption contributions of black carbon (BC) and brown carbon (BrC) at different wavelengths, the number concentration of cloud condensation nucleus (CCN), and concentrations of gaseous pollutants are obtained. The release of this dataset can provide basic data for related researches in atmospheric, cryospheric, and environmental sciences.
All original data in this dataset are acquired on-line by the high-resolution real-time observation instruments.
1) A high-resolution time-of-flight aerosol mass spectrometer (HR-ToF-AMS) is used to measure the size-resolved chemical compositions of non-refractory submicron aerosol, and further to obtain the diurnal variation, bulk acidity, as well as the high-resolution mass spercrum, component factors, and elemental ratios of organic aerosols;
2) A scanning mobility particle sizer (SMPS) is used to acquire the size distribution of number concentration of submicron particles;
3) A photoacoustic extinctiometer (PAX) is used to acquire the
4) An Aethalometer is used to acquire the particle light absorption coefficients at seven different wavelengths;
5) A cloud condensation nuclei (CCN) counter is used to acquire the number concentration of CCN at different supersaturation of water vapor;
6) A suite of gas analyzers is used to acquire the concentrations of gaseous pollutants of CO, CO2, NOX, O3, and SO2.
All data in this dataset are processed using the Igor Pro software.
1) The HR-TOF-AMS data is processed using the standard data analysis software with SQUIRREL and PIKA toolkits written in Igor Pro;
2) Source apportionment of organic aerosol is conducted by the positive matrix factorization (PMF) analysis method;
3) Other data are processed by the conventional data processing methods to obtian the mean value, diurnal variation, etc.;
1) All instruments are calibrated according to their standard calibration protocols at the beginning and end of each observation to ensure the data accuracy;
2) Strictly quality control of the observation data such as eliminate the interference data due to the instrument failure and artificial influence;
3) Comparison of data from different instruments to ensure the consistency and synchronization of observation data;
| # | number | name | type |
| 1 | 41977189 | Multiple method analysis on light absorption property, source, and chemical composition of brown carbon from the Qinghai-Xizang (Tibet) Plateau | National Natural Science Foundation of China |
| 2 | 41771079 | Organic matters in mountain snow/ice of Western China: temporal and spatial variations, sources, and application in paleoclimate and paleoenvironment research | National Natural Science Foundation of China |
| 3 | 2019QZKK0605 | The Second Tibetan Plateau Scientific Expedition and Research program (STEP) | Major national science and technology projects |
| 4 | XDA20040501 | The Strategic Priority Research Program of Chinese Academy of Sciences | Major national science and technology projects |
| 5 | SKLCS-ZZ-2022 | State Key Laboratory of Cryospheric Sciences Scientific Research Foundation | other |
| 6 | Y529841001 | Study on the characteristics of organic matter in the atmosphere and snow ice in cryospheric regions | Hundred talents program of Chinese Academy of Sciences |
This work is licensed under
CC BY 4.0 (Creative Commons Attribution 4.0 International License).
CSTR:11738.11.ncdc.NIEER.db2200.2022
10.12072/ncdc.NIEER.db2200.2022
