Meteorological conditions during a severe, prolonged regional heavy air pollution episode in eastern China from December 2016 to January 2017

Deng, Xiaodong; Cao, Weihua; Huo, Yanfeng; Yang, Guo-Jing; Yu, Chao; He, Dandan; Deng, Wei; Fu, Wei; Ding, Heming; Zhai, Jing; Cheng, Long

doi:10.1007/s00704-018-2426-4

Cited by 16 publications

(16 citation statements)

References 40 publications

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“…When the horizontal and vertical air mixing processes increase, they reduce the concentration of the pollutants in it. Wind speed showed positive correlation with emission concentrations (Deng et al, 2018;Guo et al, 1999). In Autumn 2009, PM 2.5 (366.87 ug/ m ) maximum concentration was recorded with an increase in wind speed with a value of 1.21 m/sec (Fig.…”

Section: Annual Trends Of Emissions and Relationship With Meteorologimentioning

confidence: 85%

“…Temperature showed an inverse relation with most of the pollutants because of the role of the heat in warming up the surface of the earth by the incoming radiation that strike the earth and warms it, thus making the surface air warmer and consequently reducing its density, so it expands and goes upward to be replaced by cold air and so on. This process increases the amounts of the up going air currents (Deng et al, 2018;Ilyas et al, 2010). When the horizontal and vertical air mixing processes increase, they reduce the concentration of the pollutants in it.…”

Section: Annual Trends Of Emissions and Relationship With Meteorologimentioning

confidence: 99%

“…Both minimum and maximum temperature showed a negative correlation with the emission concentrations. When the temperature is high, there are turbulent flows and dramatic convective motions and the atmosphere is unstable (Deng et al, 2018). On contrary, when the temperature is low, the atmosphere is so stable that the pollution concentration becomes high (Zhao and Shi, 2012).…”

Section: Annual Trends Of Emissions and Relationship With Meteorologimentioning

confidence: 99%

“…Usually, Karachi experience less precipitation due to inversion layer that traps the contaminants during winter season. In winter season Islamabad is more polluted because winter smog is caused when a mixture of pollutants builds up at ground level and layer of cold air traps the warm air containing pollutants and elevates the levels (Amato et al, 2014;Deng et al, 2018).…”

Section: Annual Trends Of Emissions and Relationship With Meteorologimentioning

confidence: 99%

“…Downwind areas from proximate emission sources, such as industrial locations and highways exhibited the significantly higher levels of air pollutants (Li et al, 2010). Traffic emissions are known to be responsible for a substantial share of urban air pollution, such as nitrogen dioxide (NO 2 ), carbon monoxide and particulate matters (Deng et al, 2018). In recent years, the aerosol problem has become increasingly acute due to increased loadings of atmospheric pollutants in Asian countries with monsoonal climates, such as India and China (Christodoulakis et al, 2018, Srivastava, 2006, Tsang, 2008Zhang et al, 2008).…”

Section: Introductionmentioning

confidence: 99%

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Status of Air Quality with Potential Linkage to the Metrological Conditions in Three Major Cities of Pakistan

Hamid

Junaid

Ali

et al. 2019

American Journal of Environmental Sciences

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Environmental pollution being fatal for all living organisms is growing adversely due to excessive industrialization and urbanization. Vehicular emissions have aggravated the situation and pose detrimental effects on human health. In this study, the trend of ambient air quality was analyzed in the three metropolitan cities of Pakistan, including Karachi, Lahore and Islamabad for a period of three years (2008-2010). Air pollutants, such as NO, NO x , NO 2 and PM 2.5 were recorded usingmobile air quality monitoring stations in the target areas. Results from statistical analysis revealed PM 2.5 with highest levels in all the cities, albeit exceeded the World Health Organization (WHO) guideline limits. Spearman correlation revealed that the levels of air pollutants were negatively correlated with the temperature and rainfall, whereas positively correlated with the wind speed. Annual and seasonal variations in the concentrations of the air pollutants was also observed and the highest concentration was recorded in Karachi during the winter season that could be attributed to inversion phenomenon. In addition, the elevated vehicular emissions were observed in Lahore, implied comparatively high air pollution loads, comparison to those of Karachi and Islamabad. The widespread use of low-quality fuel, coupled with a dramatic expansion in the number of vehicles has led to significant air pollution problems, especially in Lahore and Karachi. Therefore, the efficient mass transit system and urban forests should be introduced to abate the ever-increasing levels of organic pollutants and improve the state of ambient air quality in the major cities of Pakistan.

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Section: Annual Trends Of Emissions and Relationship With Meteorologimentioning

confidence: 85%

Section: Annual Trends Of Emissions and Relationship With Meteorologimentioning

confidence: 99%

Section: Annual Trends Of Emissions and Relationship With Meteorologimentioning

confidence: 99%

Section: Annual Trends Of Emissions and Relationship With Meteorologimentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Status of Air Quality with Potential Linkage to the Metrological Conditions in Three Major Cities of Pakistan

Hamid

Junaid

Ali

et al. 2019

American Journal of Environmental Sciences

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Comparison of horizontal wind observed by wind profiler radars with ERA5 reanalysis data in Anhui, China

Deng

He²,

Zhang³

et al. 2022

Theor Appl Climatol

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The wind pro ler radar network at Anhui province in China was completely constructed for improving warning capacity of meteorological disasters in 2019. In order to verify its proper performance, vertical pro les of horizontal winds were compared with ERA5 reanalysis data during the period January to December in 2021. The wind pro ler radars behave good capability in measuring the atmospheric wind with high data collection rates (> 80%). Furthermore, data availabilities of WPRs decrease with the increase of altitudes and they are mostly greater than 90% below 3km in day without precipitation, indicating that the annual mean of the effective detection height is about 2-3km with maximum value (4-6km) in summer and minimum value (around 2km) in winter. More importantly, the WPRs shows excellent agreement with the ERA5 zonal (correlation coe cients > 0.89 and standard deviations < 2.57m/s) and meridional winds (correlation coe cients > 0.76 and standard deviations < 3.26 m/s) in most stations. Also, the biases show a broadly Gaussian character in zonal winds and meridional winds and they are all close to zero. The differences of horizontal wind between wind pro ler radars and ERA5 present a function of altitude. Normally, not only zonal winds but also meridional winds at low level can performance better than those at upper level. Meanwhile, due to the difference of atmospheric turbulent between day and night, statistical parameters of comparison during day time behave better than those at night. The result shows that the wind pro ler radar network at Anhui is capable of providing good quality wind data in PBL for numerical model and weather processes studies in future.

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Persistent pollution episodes, transport pathways, and potential sources of air pollution during the heating season of 2016–2017 in Lanzhou, China

Guo

Lin

et al. 2021

Environ Monit Assess

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Meteorological conditions during a severe, prolonged regional heavy air pollution episode in eastern China from December 2016 to January 2017

Cited by 16 publications

References 40 publications

Status of Air Quality with Potential Linkage to the Metrological Conditions in Three Major Cities of Pakistan

Status of Air Quality with Potential Linkage to the Metrological Conditions in Three Major Cities of Pakistan

Comparison of horizontal wind observed by wind profiler radars with ERA5 reanalysis data in Anhui, China

Persistent pollution episodes, transport pathways, and potential sources of air pollution during the heating season of 2016–2017 in Lanzhou, China

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