Metadata about: Abstract The holiday effect is a useful tool to estimate the impact on air pollution due to changes in human activities. In this study, we assessed the variations in concentrations of fine particulate matter (PM2.5) and nitrogen dioxide (NO2) during the holidays in the heating season from 2014 to 2018 based on daily surface air quality monitoring measurements in Beijing. A Generalized Additive Model (GAM) is used to analyze pollutant concentrations for 34 sites by comprehensively accounting for annual, monthly, and weekly cycles as well as the nonlinear impacts of meteorological factors. A Saturday effect was found in the downtown area, with about 4% decrease in PM2.5 and 3% decrease in NO2 relative to weekdays. On Sundays, the PM2.5 concentrations increased by about 5% whereas there were no clear changes for NO2. In contrast to the small effect of the weekend, there was a strong holiday effect throughout the region with average increases of about 22% in PM2.5 and average reductions of about 11% in NO2 concentrations. There was a clear geographical pattern in the strength of the holiday effect. In rural areas the increase in PM2.5 is related to the proportion of coal and biomass consumption for household heating. In the suburban areas between the Fifth Ring Road and Sixth Ring Road there were larger reductions in NO2 than downtown which might be due to decreased traffic as many people return to their hometown for the holidays. This study provides insights into the pattern of changes in air pollution due to human activities. By quantifying the changes, it also provides insights for improvements in air quality due to control policies implemented in Beijing during the heating season.

About: Abstract The holiday effect is a useful tool to estimate the impact on air pollution due to changes in human activities. In this study, we assessed the variations in concentrations of fine particulate matter (PM2.5) and nitrogen dioxide (NO2) during the holidays in the heating season from 2014 to 2018 based on daily surface air quality monitoring measurements in Beijing. A Generalized Additive Model (GAM) is used to analyze pollutant concentrations for 34 sites by comprehensively accounting for annual, monthly, and weekly cycles as well as the nonlinear impacts of meteorological factors. A Saturday effect was found in the downtown area, with about 4% decrease in PM2.5 and 3% decrease in NO2 relative to weekdays. On Sundays, the PM2.5 concentrations increased by about 5% whereas there were no clear changes for NO2. In contrast to the small effect of the weekend, there was a strong holiday effect throughout the region with average increases of about 22% in PM2.5 and average reductions of about 11% in NO2 concentrations. There was a clear geographical pattern in the strength of the holiday effect. In rural areas the increase in PM2.5 is related to the proportion of coal and biomass consumption for household heating. In the suburban areas between the Fifth Ring Road and Sixth Ring Road there were larger reductions in NO2 than downtown which might be due to decreased traffic as many people return to their hometown for the holidays. This study provides insights into the pattern of changes in air pollution due to human activities. By quantifying the changes, it also provides insights for improvements in air quality due to control policies implemented in Beijing during the heating season.

an Entity references as follows:

Graph IRI	Count
http://ns.inria.fr/covid19/graph/entityfishing	9
http://ns.inria.fr/covid19/graph/articles	3

Faceted Search & Find service v1.13.91

This work is licensed under a Creative Commons Attribution-Share Alike 3.0 Unported License.
OpenLink Virtuoso version 07.20.3229 as of Jul 10 2020, on Linux (x86_64-pc-linux-gnu), Single-Server Edition (94 GB total memory)
Copyright © 2009-2025 OpenLink Software