SPM （Suspended Particulate Matter） Air Quality Improvement in Tokyo and Vehicle Emission Control

2010 ◽  
Vol 47 (11) ◽  
pp. 779-784
Author(s):  
Hiroaki Minoura
Keyword(s):  
Quality Improvement ◽  
Particulate Matter ◽  
Air Quality ◽  
Suspended Particulate Matter ◽  
Emission Control ◽  
Vehicle Emission ◽  
Suspended Particulate ◽  
Air Quality Improvement

scholarly journals Air quality improvement in a megacity: implications from 2015 Beijing Parade Blue pollution control actions

2017 ◽  
Vol 17 (1) ◽  
pp. 31-46 ◽  
Author(s):  
Wen Xu ◽  
Wei Song ◽  
Yangyang Zhang ◽  
Xuejun Liu ◽  
Lin Zhang ◽  
...  
Keyword(s):  
Quality Improvement ◽  
Air Quality ◽  
Control Period ◽  
Emission Control ◽  
Monitoring Network ◽  
Control Measures ◽  
Integrated Analysis ◽  
Air Quality Improvement ◽  
Emission Control Measures ◽  
Control Regions

Abstract. The implementation of strict emission control measures in Beijing and surrounding regions during the 2015 China Victory Day Parade provided a valuable opportunity to investigate related air quality improvements in a megacity. We measured NH3, NO2 and PM2.5 at multiple sites in and outside Beijing and summarized concentrations of PM2.5, PM10, NO2, SO2 and CO in 291 cities across China from a national urban air quality monitoring network between August and September 2015. Consistently significant reductions of 12–35 % for NH3 and 33–59 % for NO2 in different areas of Beijing during the emission control period (referred to as the Parade Blue period) were observed compared with measurements in the pre- and post-Parade Blue periods without emission controls. Average NH3 and NO2 concentrations at sites near traffic were strongly correlated and showed positive and significant responses to traffic reduction measures, suggesting that traffic is an important source of both NH3 and NOx in urban Beijing. Daily concentrations of PM2.5 and secondary inorganic aerosol (sulfate, ammonium and nitrate) at the urban and rural sites both decreased during the Parade Blue period. During (after) the emission control period, concentrations of PM2.5, PM10, NO2, SO2 and CO from the national city-monitoring network showed the largest decrease (increase) of 34–72 % (50–214 %) in Beijing, a smaller decrease (a moderate increase) of 1–32 % (16–44 %) in emission control regions outside Beijing and an increase (decrease) of 6–16 % (−2–7 %) in non-emission-control regions of China. Integrated analysis of modelling and monitoring results demonstrated that emission control measures made a major contribution to air quality improvement in Beijing compared with a minor contribution from favourable meteorological conditions during the Parade Blue period. These results show that controls of secondary aerosol precursors (NH3, SO2 and NOx) locally and regionally are key to curbing air pollution in Beijing and probably in other mega cities worldwide.

scholarly journals Air Quality Improvement in a Megacity: Implications from 2015 Beijing Parade Blue Pollution-Control Actions

2016 ◽  
Author(s):  
Wen Xu ◽  
Wei Song ◽  
Yangyang Zhang ◽  
Xuejun Liu ◽  
Lin Zhang ◽  
...  
Keyword(s):  
Quality Improvement ◽  
Air Quality ◽  
Control Period ◽  
Emission Control ◽  
Monitoring Network ◽  
Control Measures ◽  
Integrated Analysis ◽  
Beijing City ◽  
Air Quality Improvement ◽  
Emission Control Measures

Abstract. The implementation of strict emission control measures in Beijing and surrounding regions during the 2015 China Victory Day Parade provided a valuable opportunity to investigate related air quality improvements in a megacity. We measured NH3, NO2 and PM2.5 at multiple sites in and outside Beijing and summarized concentrations of PM2.5, PM10, NO2, SO2 and CO in 291 cities across China from a national urban air quality monitoring network between August and September 2015. Consistently significant reductions of 12–35 % for NH3 and 33–59 % for NO2 in different areas of Beijing city during the emission control period (referred to as the Parade Blue period) were observed compared with measurements in the pre- and post-Parade Blue periods without emission controls. Average NH3 and NO2 concentrations at sites near traffic were strongly correlated and showed positive and significant responses to traffic reduction measures, suggesting that traffic is an important source of both NH3 and NOx in urban Beijing. Daily concentrations of PM2.5 and secondary inorganic aerosol (sulfate, ammonium, and nitrate) at the urban and rural sites both decreased during the Parade Blue period. Concentrations of PM2.5, PM10, NO2, SO2 and CO from the national city-monitoring network showed the largest decrease (34–72 %) in Beijing, a smaller decrease (1–32 %) in North China (excluding Beijing), and an increase (6–16 %) in other regions of China during the emission control period. Integrated analysis of modeling and monitoring results demonstrated that emission control measures made a major contribution to air quality improvement in Beijing compared with a minor contribution from favorable meteorological conditions during the Parade Blue period. These results show that controls of secondary aerosol precursors (NH3, SO2 and NOx) locally and regionally are key to curbing air pollution in Beijing and probably in other mega cities worldwide.

scholarly journals Diagnostic Analysis and Modelling of Air Quality for Medium Sized City

YMER Digital ◽  
2021 ◽  
Vol 20 (12) ◽  
pp. 475-497
Author(s):  
Nitin W Ingole ◽  
◽  
Sachin V Dharpal ◽  
Keyword(s):  
Particulate Matter ◽  
Air Quality ◽  
Suspended Particulate Matter ◽  
Building Materials ◽  
Predictive Performance ◽  
Suspended Particulate ◽  
Regression Approach ◽  
Day By Day ◽  
Pollution Concentrations

It is witnessed that air pollution is an important issue regarding not only for human health but also for plants, animals and building materials. Increase in industrialisation, abundant use of automobiles, and network of highways, the quality of air of Amravati city is degrading day by day. The data has been collected for a period ranging from March 2020 to February 2021 for analysis and pollution forecasting model work. The concentration of Suspended Particulate Matter (SPM), Respiratory Suspended Particulate Matter (RSPM), Sulphur dioxide (SO2), Nitrogen dioxide (NO2) and Ozone (O3) have been monitored over successive periods of time and also data is collected from monitoring stations controlled by MPCB. Numerous studies have been proposed for predicting pollution concentrations and improvement of performance of predictable models is an important issue. As is well known, collaborative observations proved that it can improve predictive performance. In this study, multivariate linear regression approach-based model was constructed to predict the RSPM in the air using the meteorological (air temperature, relative humidity, wind speed, rainfall) and air quality monitoring data (SPM, NO2, SO2, O3). Correlation between measured and model predicted vales of RSPM were 0.717,0.691,0.64 and 0.60 for winter, summer, monsoon and annual seasons respectively. However, the regression model based on seasonal data for winter was found to be more effective.

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