Name
Title | ||
|---|---|---|
Variation Characteristics And Transportation Of Aerosol, No2, So2, And Hcho In Coastal Cities Of Eastern China: Dalian, Qingdao, And Shanghai |
Abstract | ||
|---|---|---|
This paper studied the method for converting the aerosol extinction to the mass concentration of particulate matter (PM) and obtained the spatio-temporal distribution and transportation of aerosol, nitrogen dioxide (NO2), sulfur dioxide (SO2), and formaldehyde (HCHO) based on multi-axis differential optical absorption spectroscopy (MAX-DOAS) observations in Dalian (38.85 degrees N, 121.36 degrees E), Qingdao (36.35 degrees N, 120.69 degrees E), and Shanghai (31.60 degrees N, 121.80 degrees E) from 2019 to 2020. The PM2.5 measured by the in situ instrument and the PM2.5 simulated by the conversion formula showed a good correlation. The correlation coefficients R were 0.93 (Dalian), 0.90 (Qingdao), and 0.88 (Shanghai). A regular seasonality of the three trace gases is found, but not for aerosols. Considerable amplitudes in the weekly cycles were determined for NO2 and aerosols, but not for SO2 and HCHO. The aerosol profiles were nearly Gaussian, and the shapes of the trace gas profiles were nearly exponential, except for SO2 in Shanghai and HCHO in Qingdao. PM2.5 presented the largest transport flux, followed by NO2 and SO2. The main transport flux was the output flux from inland to sea in spring and winter. The MAX-DOAS and the Copernicus Atmosphere Monitoring Service (CAMS) models' results were compared. The overestimation of NO2 and SO2 by CAMS is due to its overestimation of near-surface gas volume mixing ratios. |
Year | DOI | Venue |
|---|---|---|
2021 | 10.3390/rs13050892 | REMOTE SENSING |
Keywords | DocType | Volume |
AOD, PM2.5, NO2, SO2, HCHO, coastal city, flux, MAX-DOAS, CA, MS | Journal | 13 |
Issue | Citations | PageRank |
5 | 0 | 0.34 |
References | Authors | |
0 | 13 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Xiaomei Li | 1 | 0 | 1.01 |
| Pinhua Xie | 2 | 1 | 2.51 |
| Ang Li | 3 | 2 | 2.19 |
| Jin Xu | 4 | 0 | 1.01 |
| Zhaokun Hu | 5 | 0 | 1.01 |
| Hongmei Ren | 6 | 0 | 1.01 |
| Hongyan Zhong | 7 | 0 | 1.01 |
| Bo Ren | 8 | 0 | 1.01 |
| Xin Tian | 9 | 0 | 1.01 |
| Yeyuan Huang | 10 | 0 | 1.01 |
| Wenxuan Chai | 11 | 0 | 0.68 |
| Shuai Wang | 12 | 0 | 0.68 |
| Qingbo Li | 13 | 0 | 0.34 |