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Air Quality in Ningbo and Transport Trajectory Characteristics of Primary Pollutants in Autumn and Winter
By using meteorology and pollution observation data from Zhejiang province, and data from the National Centers for Environmental Prediction’s Global Data Assimilation System from 1 June 2013, to 31 May 2016, we analyzed air quality characteristics in Ningbo and applied the HYSPLIT model to do backwa...
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Published in: | Atmosphere 2019-03, Vol.10 (3), p.120 |
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Main Authors: | , , , |
Format: | Article |
Language: | English |
Subjects: | |
Citations: | Items that this one cites Items that cite this one |
Online Access: | Get full text |
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Summary: | By using meteorology and pollution observation data from Zhejiang province, and data from the National Centers for Environmental Prediction’s Global Data Assimilation System from 1 June 2013, to 31 May 2016, we analyzed air quality characteristics in Ningbo and applied the HYSPLIT model to do backward trajectory clustering statistics for pollution cases of moderate, heavy and severe (henceforth referred to as moderate-and-above) levels. The results indicated that the percentage of moderate-and-above pollution was approximately 6%, which mostly occurred from November to February, with the primary pollutant being particulate matter with a diameter of ≤2.5 μm; Moderate-and-above pollution was mainly caused by pollutants from three types of trajectories (type mx, type 1, and type 2), with type 2 differing significantly from types 1 and mx. Type 2 occurred in stable boundary layers, whereas types mx and 1 occurred in unstable and conditionally unstable layers respectively. These three trajectory types were all related to cold air, but type 2 was weaker than the other two. Analysis of typical cases of various pollution types revealed that a heavy pollution outbreak was due to continuous superposition of pollutants. The input particles most likely originated from the northwest. The upstream situation was the focus of investigation to assist in local pollution forecasting. |
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ISSN: | 2073-4433 2073-4433 |
DOI: | 10.3390/atmos10030120 |