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Long-term trends in NO2 columns related to economic developments and air quality policies from 1997 to 2016 in China.
- Source :
-
Science of the Total Environment . Oct2018, Vol. 639, p146-155. 10p. - Publication Year :
- 2018
-
Abstract
- This study detected the long-term trends in NO 2 concentrations in China from 1997 to 2016 based on the NO 2 columns from GOME, SCIAMACHY, and GOME-2A. Both differences in the time-overlapped NO 2 columns from GOME vs. SCIAMACHAY and SCIAMACHAY vs. GOME-2A showed seasonal variations, and the annual NO 2 columns from GOME were 0.9% higher than those from SCIAMACHY, which exceeded that from GOME-2A by 14%. The long-term trends of the NO 2 columns on a provincial scale could be simulated by cubic models (0.60 < R 2 < 0.96, p < 0.05) and presented three shapes: first decreasing then increasing and decreasing again; first decreasing then increasing; and continuously decreasing. The peak years of NO 2 columns in 17 provinces occurred in 2011 and 2012. These trends in NO 2 columns were determined by the economic developments and enacted air quality policies in nearly all the provinces except for Xizang and Qinghai Provinces, where the trends were determined by natural NO x emission sources. In detail, the panel data analysis showed that the simulated model had fixed effects, and the thermal power generation, consumption of diesel oil in agriculture, passenger traffic by highways, and freight traffic by highways significantly increased NO 2 , while the air quality policies in the 12th five-year plan decreased NO 2 columns from 1997 to 2016. The benefits to decreasing NO 2 columns from the air quality policies issued in the 10th and 11th five-year plans were offset by the quickly increasing economies. [ABSTRACT FROM AUTHOR]
- Subjects :
- *NITROGEN dioxide
*AIR quality
*SIMULATION methods & models
*STEAM power plants
Subjects
Details
- Language :
- English
- ISSN :
- 00489697
- Volume :
- 639
- Database :
- Academic Search Index
- Journal :
- Science of the Total Environment
- Publication Type :
- Academic Journal
- Accession number :
- 130224253
- Full Text :
- https://doi.org/10.1016/j.scitotenv.2018.04.435