Tags

Type your tag names separated by a space and hit enter

[Source Apportionment and Size Distribution of Aerosols at Lin'an Atmosphere Regional Background Station During Winter].
Huan Jing Ke Xue 2017; 38(10):4024-4033HJ

Abstract

Using a wide-range particle spectrometer (WPS), an environmental management system (EMS), KC-120H middle volume sampler, a 850 professional ion chromatography analyzer, and heat/light carbon analyzer (DRI2001A), we observed the number concentration of aerosols with sizes ranging from 10 nm to 10 μm, gas concentrations, and concentrations of PM2.5, water-soluble ions, OC, and EC in a Lin'an atmospheric background station from January 9 to 31, 2015. The positive matrix factorization (PMF) model was applied for source apportionment, and the size distribution and diurnal variations of emission sources were analyzed based on the meteorological data. The average aerosol concentration was 5062 cm-3·nm-1 and PM2.5 mass concentration was 123.6 μg·m-3. The average concentrations of NO3-, SO42-, and NH4+, the main water-soluble ions in PM2.5 were 19.2, 15.4, and 10.8 μg·m-3, which accounted for 37.9%, 30.4%, and 21.4% of total water-soluble ions, respectively. Theaverage concentrations of OC and EC were 24.4 μg·m-3 and 6.6 μg·m-3. Secondary aerosol formation, coal combustion, motor vehicle emissions, dust, andbiomass burning were the main sources of PM2.5 in Lin'an during winter with contributions of 42.3%, 21.4%, 17.1%, 8.7%, and 10.6%, respectively. Different sources had different aerosol number concentration distributions. The aerosol number concentration spectra of secondary sources, vehicle emissions, dust, and biomass burning followed unimodal-type distributions with peaks at 120, 50, 100, and 90 nm. Coal particle number concentration was a bimodal distribution which exhibited peak values at 25 nm and 100 nm (19842 cm-3·nm-1 and 18372 cm-3·nm-1, respectively). The spectra of surface concentrations of secondary sources, coal combustion, motor vehicle emissions, dust, and biomass burning followed a three-peak distribution. The peaks were at 650, 210, 160, 180, and 575 nm. The diurnal variations of particle number concentrations influenced by diurnal variations in the boundary layer and human activities were consistent with the variations in surface concentrations, which displayed bimodal-type distribution.

Authors+Show Affiliations

Key Laboratory of Meteorological Disaster, Ministry of Education(KLME), Joint International Research Laboratory of Climate and Environment Change(ILCEC), Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters, Key Laboratory for Aerosol-Cloud-Precipitation of China Meteorological Administration, Nanjing University of Information Science & Technology, Nanjing 210044, China.Key Laboratory of Meteorological Disaster, Ministry of Education(KLME), Joint International Research Laboratory of Climate and Environment Change(ILCEC), Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters, Key Laboratory for Aerosol-Cloud-Precipitation of China Meteorological Administration, Nanjing University of Information Science & Technology, Nanjing 210044, China.Key Laboratory of Meteorological Disaster, Ministry of Education(KLME), Joint International Research Laboratory of Climate and Environment Change(ILCEC), Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters, Key Laboratory for Aerosol-Cloud-Precipitation of China Meteorological Administration, Nanjing University of Information Science & Technology, Nanjing 210044, China.Hangzhou Environmental Monitoring Center, Hangzhou 310007, China.Bengbu Meteorological Bureau, Bengbu 233040, China.Key Laboratory of Meteorological Disaster, Ministry of Education(KLME), Joint International Research Laboratory of Climate and Environment Change(ILCEC), Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters, Key Laboratory for Aerosol-Cloud-Precipitation of China Meteorological Administration, Nanjing University of Information Science & Technology, Nanjing 210044, China.Key Laboratory of Meteorological Disaster, Ministry of Education(KLME), Joint International Research Laboratory of Climate and Environment Change(ILCEC), Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters, Key Laboratory for Aerosol-Cloud-Precipitation of China Meteorological Administration, Nanjing University of Information Science & Technology, Nanjing 210044, China.Key Laboratory of Meteorological Disaster, Ministry of Education(KLME), Joint International Research Laboratory of Climate and Environment Change(ILCEC), Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters, Key Laboratory for Aerosol-Cloud-Precipitation of China Meteorological Administration, Nanjing University of Information Science & Technology, Nanjing 210044, China.Key Laboratory of Meteorological Disaster, Ministry of Education(KLME), Joint International Research Laboratory of Climate and Environment Change(ILCEC), Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters, Key Laboratory for Aerosol-Cloud-Precipitation of China Meteorological Administration, Nanjing University of Information Science & Technology, Nanjing 210044, China.

Pub Type(s)

English Abstract
Journal Article

Language

chi

PubMed ID

29965184

Citation

Shi, Shuang-Shuang, et al. "[Source Apportionment and Size Distribution of Aerosols at Lin'an Atmosphere Regional Background Station During Winter]." Huan Jing Ke Xue= Huanjing Kexue, vol. 38, no. 10, 2017, pp. 4024-4033.
Shi SS, Wang HL, Zhu B, et al. [Source Apportionment and Size Distribution of Aerosols at Lin'an Atmosphere Regional Background Station During Winter]. Huan Jing Ke Xue. 2017;38(10):4024-4033.
Shi, S. S., Wang, H. L., Zhu, B., Lin, X., Guo, T., Sha, D. D., ... Shi, Y. Z. (2017). [Source Apportionment and Size Distribution of Aerosols at Lin'an Atmosphere Regional Background Station During Winter]. Huan Jing Ke Xue= Huanjing Kexue, 38(10), pp. 4024-4033. doi:10.13227/j.hjkx.201703239.
Shi SS, et al. [Source Apportionment and Size Distribution of Aerosols at Lin'an Atmosphere Regional Background Station During Winter]. Huan Jing Ke Xue. 2017 Oct 8;38(10):4024-4033. PubMed PMID: 29965184.
* Article titles in AMA citation format should be in sentence-case
TY - JOUR T1 - [Source Apportionment and Size Distribution of Aerosols at Lin'an Atmosphere Regional Background Station During Winter]. AU - Shi,Shuang-Shuang, AU - Wang,Hong-Lei, AU - Zhu,Bin, AU - Lin,Xu, AU - Guo,Ting, AU - Sha,Dan-Dan, AU - Jiang,Lin, AU - Zhang,Yu-Xin, AU - Shi,Yuan-Zhe, PY - 2018/7/3/entrez PY - 2018/7/3/pubmed PY - 2018/7/3/medline KW - PM2.5 KW - diurnal variation KW - positive matrix factorization (PMF) KW - size distribution KW - source apportionment SP - 4024 EP - 4033 JF - Huan jing ke xue= Huanjing kexue JO - Huan Jing Ke Xue VL - 38 IS - 10 N2 - Using a wide-range particle spectrometer (WPS), an environmental management system (EMS), KC-120H middle volume sampler, a 850 professional ion chromatography analyzer, and heat/light carbon analyzer (DRI2001A), we observed the number concentration of aerosols with sizes ranging from 10 nm to 10 μm, gas concentrations, and concentrations of PM2.5, water-soluble ions, OC, and EC in a Lin'an atmospheric background station from January 9 to 31, 2015. The positive matrix factorization (PMF) model was applied for source apportionment, and the size distribution and diurnal variations of emission sources were analyzed based on the meteorological data. The average aerosol concentration was 5062 cm-3·nm-1 and PM2.5 mass concentration was 123.6 μg·m-3. The average concentrations of NO3-, SO42-, and NH4+, the main water-soluble ions in PM2.5 were 19.2, 15.4, and 10.8 μg·m-3, which accounted for 37.9%, 30.4%, and 21.4% of total water-soluble ions, respectively. Theaverage concentrations of OC and EC were 24.4 μg·m-3 and 6.6 μg·m-3. Secondary aerosol formation, coal combustion, motor vehicle emissions, dust, andbiomass burning were the main sources of PM2.5 in Lin'an during winter with contributions of 42.3%, 21.4%, 17.1%, 8.7%, and 10.6%, respectively. Different sources had different aerosol number concentration distributions. The aerosol number concentration spectra of secondary sources, vehicle emissions, dust, and biomass burning followed unimodal-type distributions with peaks at 120, 50, 100, and 90 nm. Coal particle number concentration was a bimodal distribution which exhibited peak values at 25 nm and 100 nm (19842 cm-3·nm-1 and 18372 cm-3·nm-1, respectively). The spectra of surface concentrations of secondary sources, coal combustion, motor vehicle emissions, dust, and biomass burning followed a three-peak distribution. The peaks were at 650, 210, 160, 180, and 575 nm. The diurnal variations of particle number concentrations influenced by diurnal variations in the boundary layer and human activities were consistent with the variations in surface concentrations, which displayed bimodal-type distribution. SN - 0250-3301 UR - https://www.unboundmedicine.com/medline/citation/29965184/[Source_Apportionment_and_Size_Distribution_of_Aerosols_at_Lin'an_Atmosphere_Regional_Background_Station_During_Winter]_ DB - PRIME DP - Unbound Medicine ER -