Characteristics of Aerosol Extinction Hygroscopic Growth in the Typical Coastal City of Qingdao, China
Abstract
:1. Introduction
2. Materials and Methods
2.1. Data
2.1.1. Field Experiment Data
- The automatic weather station WXT520 (Vaisala, Helsinki, Finland) was used to collect near-surface meteorological data, equipped with 6 weather sensors to measure the atmospheric pressure (P), atmospheric temperature (T), RH, wind direction (WD), wind speed (WS). The WXT520 was mounted on a flux-measuring tower at 2 m above the ground to collect the meteorological data every 5 s during the experiment. The specific performances of the WXT520 sensors refer to Villagrán’s paper [44].
- The 6000 forward-scattering visibility meter (Belfort Instrument, Baltimore, MA, USA) was used to collect the VIS. The infrared LED transmitter transmits the light into a sampler, and the receiver collects the forward-scattered light and calculates the extinction to obtain the atmospheric VIS, and it is one of the most commonly used instruments for atmospheric visibility measurement. The device can be deployed and used without frequent maintenance. The temporal resolution of the VIS is 5 s. For more technical parameters, please refer to Dr. Dongsheng Ji’s research [45].
- The OPC was used to collect the aerosol PNC. The OPC is designed to measure aerosol particles such as floating dust. Theoretically, the PNC and the PSD are obtained through the light scattering characteristics of the particles according to the Mie scattering theory [46]. In this paper, we used the DLJ-92 multi-channel OPC developed by the AIOFM, CAS [47]. The detection range of particle diameter size is 0.3–12 μm [47]. The temporal resolution of the OPC data is 60 s in this research.
2.1.2. Remote Sensing and Reanalysis Data
- (1)
- GDAS data
- (2)
- MODIS AOD data
2.2. Methodology
3. Results and Discussion
3.1. Monthly and Seasonal Characteristics of Atmospheric Aerosols in Qingdao
3.1.1. Data Preprocessing
3.1.2. AOD and VIS in Qingdao
3.2. Analysis of Aerosol Source
3.3. Characteristics of Aerosol Extinction HG Factor
3.3.1. Monthly Characteristics in Qingdao
- (1)
- Select the time of all backward trajectories in each clustering result;
- (2)
- Match the VIS, PNC and RH values according to the selected time in Step 1;
- (3)
- Calculate the average extinction coefficient () of each clustering result using Equation (1) to analyze the relationship between and RH, then form a new array against RH;
- (4)
- Classify all the , , corresponding to different aerosol sources in each month, using the aerosol source results identified in Table 2;
- (5)
- Calculate the aerosol extinction HG factor (, and ) for all aerosol types using Equation (2), and establish the power-law curve models for different aerosol types.
3.3.2. Seasonal Characteristics in Qingdao
3.3.3. Characteristics under Different Pollution Backgrounds in Qingdao
4. Conclusions
- Qingdao’s aerosol source is very complicated due to the special geographical location, a typical coastal area in northeastern China. The proportion of different aerosol sources in Qingdao varies greatly from month to month, and shows obvious seasonal fluctuations. The local aerosol sources are mostly terrestrial sources, with marine sources accounting for only about 10–20%, which is slightly higher in summer than that in autumn and winter. Terrestrial aerosols accounted for more than 40% of the total for the year.
- The local aerosol’s of different sources in Qingdao have relatively small monthly variations, but explicit a certain seasonal variation. The seasonal change is mainly manifested as the “floating” of the DPs, and the DP of marine aerosol (RH about 80%) is consistent in different seasons. The seasonal distributions of terrestrial and mixed aerosols’ DPs are different, decreasing as low as to RH = 60–70% in autumn and winter and rising to about RH = 85% in summer. The DPs of mixed- source aerosols are generally intermediate between terrestrial and marine source ones. These variations can be caused by atmospheric circulation and local pollution levels.
- Under the background of different pollution levels, the characteristics of local aerosol from different sources in Qingdao showed considerable discrepancy. In general, when the atmospheric background was relatively clean, the DPs of aerosols from different sources were almost the same (about RH = 80%), but when the pollution was heavy, the DPs of terrestrial aerosols were almost 20% lower than those of marine sources (in the period of heavy pollution, the DPs’ RH of terrestrial, mixed and marine aerosols are 50%, 60%, and 70%, respectively). Therefore, it is necessary to model the local aerosols in Qingdao based on different pollution backgrounds.
Author Contributions
Funding
Data Availability Statement
Acknowledgments
Conflicts of Interest
References
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Technical Specification | Data | Measurement Range | Accuracy | Resolution | Temporal Resolution |
---|---|---|---|---|---|
WXT520 | RH | 0–100% RH | ±3% (0–90%RH) ±5% (90–100%RH) | 0.1% RH | 5 s |
Belfort 6000 | VIS | 200 m~50 km | ±10% | \ | 5 s |
OPC | PNC | 0.3~12 um | \ | 17–20 channels optional | 60–600 s optional |
Time | Land Source Index | Sea Source Index | Mixed Aerosol Index |
---|---|---|---|
September 2019 | 5 | 3, 8 | 1, 2, 4, 6, 7 |
October 2019 | 2, 4, 6 | 1 | 3, 5, 7, 8 |
November 2019 | 3, 5, 7, 8 | 6 | 1,2,4, |
December 2019 | 2, 3, 5, 6, 8 | 7 | 1, 4 |
January 2020 | 1, 5 | 8 | 2, 3, 4, 7, 8 |
February 2020 | 1, 2, 4, 6 | 5 | 3, 7, 8 |
March 2020 | 1, 3, 5, 8 | 2, 7 | 4, 6 |
April 2020 | 2, 3, 5, 7, 8 | 4 | 1, 6 |
May 2020 | 1, 3, 4 | 5, 8 | 2, 6, 7 |
June 2020 | 1, 6 | 2, 5 | 3, 4, 7, 8 |
July 2020 | 3, 6 | 4, 7 | 1, 2, 5, 8 |
August 2020 | 1, 3, 6, 8 | 2, 4 | 5, 7 |
Time | Land Source (%) | Sea Source (%) | Mixed Aerosol (%) |
---|---|---|---|
September 2019 | 6.34 | 26.67 | 66.99 |
October 2019 | 39.38 | 9.38 | 51.25 |
November 2019 | 48.88 | 6.5 | 44.62 |
December 2019 | 66.85 | 6.27 | 26.88 |
January 2020 | 40.5 | 5.59 | 55.25 |
February 2020 | 65.08 | 6.8 | 28.13 |
March 2020 | 67.6 | 11.99 | 20.4 |
April 2020 | 57.97 | 9.34 | 32.69 |
May 2020 | 40.9 | 28.51 | 30.59 |
June 2020 | 28.44 | 34.8 | 36.75 |
July 2020 | 18.8 | 27.36 | 53.84 |
August 2020 | 50.47 | 15.36 | 34.17 |
Season | Land Source | Sea Source | Mixed Aerosol | |||||||||
---|---|---|---|---|---|---|---|---|---|---|---|---|
A | B | RMSE | R-Square | A | B | RMSE | R-Square | A | B | RMSE | R-Square | |
autumn | 0.3165 | 1.81 | 0.34 | 0.92 | 0.3869 | 1.04 | 0.26 | 0.65 | 0.3736 | 1.51 | 0.42 | 0.89 |
winter | 0.0006 | 4.46 | 1.52 | 0.46 | 0.5864 | 0.66 | 0.47 | 0.49 | 0.3713 | 1.29 | 0.35 | 0.79 |
spring | 0.0106 | 3.39 | 0.89 | 0.89 | 0.3443 | 0.94 | 0.54 | 0.32 | 0.6093 | 1.32 | 0.35 | 0.89 |
summer | 0.0962 | 1.29 | 0.52 | 0.41 | 0.0693 | 1.63 | 0.51 | 0.50 | 0.1033 | 1.56 | 0.78 | 0.49 |
Aerosol Source | Period 1 (Polluted) | Period 2 (Clean) |
---|---|---|
Land source | y = 0.56(1 − x/100) − 1.41 | y = 0.59(1 − x/100) − 0.66 |
Sea source | y = 0.61(1 − x/100) − 0.63 | y = 0.32(1 − x/100) − 0.96 |
Mixed aerosol | y = 0.52(1 − x/100) − 1.18 | y = 0.67(1 − x/100) − 0.58 |
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Liu, N.; Cui, S.; Luo, T.; Chen, S.; Yang, K.; Ma, X.; Sun, G.; Li, X. Characteristics of Aerosol Extinction Hygroscopic Growth in the Typical Coastal City of Qingdao, China. Remote Sens. 2022, 14, 6288. https://doi.org/10.3390/rs14246288
Liu N, Cui S, Luo T, Chen S, Yang K, Ma X, Sun G, Li X. Characteristics of Aerosol Extinction Hygroscopic Growth in the Typical Coastal City of Qingdao, China. Remote Sensing. 2022; 14(24):6288. https://doi.org/10.3390/rs14246288
Chicago/Turabian StyleLiu, Nana, Shengcheng Cui, Tao Luo, Shunping Chen, Kaixuan Yang, Xuebin Ma, Gang Sun, and Xuebin Li. 2022. "Characteristics of Aerosol Extinction Hygroscopic Growth in the Typical Coastal City of Qingdao, China" Remote Sensing 14, no. 24: 6288. https://doi.org/10.3390/rs14246288
APA StyleLiu, N., Cui, S., Luo, T., Chen, S., Yang, K., Ma, X., Sun, G., & Li, X. (2022). Characteristics of Aerosol Extinction Hygroscopic Growth in the Typical Coastal City of Qingdao, China. Remote Sensing, 14(24), 6288. https://doi.org/10.3390/rs14246288