Study on meteorological conditions for heavy air pollution and its climatic characteristics in “2+26” cities around Beijing-Tianjin-Hebei region in autumn and winter

2020 ◽  
Author(s):  
Mei Mei
Keyword(s):  
Air Pollution ◽  
Large Scale ◽  
Evaluation Method ◽  
Meteorological Data ◽  
Reanalysis Data ◽  
Meteorological Conditions ◽  
Hebei Province ◽  
Shanxi Province ◽  
Historical Variation ◽  
Autumn And Winter

<div><strong>Based on surface observation meteorological data during 1961-2017 and ERA-interim reanalysis data, an evaluation method of different meteorological conditions for heavy air pollution (MCHAP) was set up by using atmospheric self-cleaning ability index (ASI). Through analyzing the historical variation characteristics of MCHAP of Beijing-Tianjin-Hebei region in autumn and winter, the results were as follows. During 1961-2017, the frequency and extremity of MCHAP in Jincheng of Shanxi province ranked the frst. MCHAP occurred more frequently in Beijing, Langfang of Hebei province and Zhengzhou of Henan province and more extremely in Baoding, Shijiazhuang and Hengshui of Hebei province. MCHAP had occurred in “2+26” cities around Beijing-Tianjin -Hebei region in history since 1961, but which were more common in recent years and caused much more </strong><strong>sever air pollution events. During the period of 2013-2017, MCHAP occurred the least frequently in 2017 in “2+26” cities around Beijing-Tianjin-Hebei region except Beijing. However the extremity of MCHAP in 2017 receded a lot in Beijing. Both in the 1980s and the period of 2010-2017, MCHAP in the Beijing-Tianjin-Hebei and its surrounding areas took place the most frequently, which was affected by both the cold air intensity and the change of large-scale air stagnation condition. To some extent, the development of urbanization also plays a role in the decadal change of MCHAP.</strong></div>

scholarly journals Large-Scale Spraying of Roads with Water Contributes to, Rather Than Prevents, Air Pollution

Toxics ◽  
2021 ◽  
Vol 9 (6) ◽  
pp. 122
Author(s):  
Fengzhu Tan ◽  
Yuming Guo ◽  
Wei Zhang ◽  
Xingyan Xu ◽  
Ming Zhang ◽  
...  
Keyword(s):  
Air Pollution ◽  
Large Scale ◽  
Cumulative Effect ◽  
Meteorological Conditions ◽  
Air Humidity ◽  
Anthropogenic Aerosol ◽  
Autumn And Winter ◽  
The Impact ◽  
Pollution Events ◽  
Pm2.5 Concentration

Spraying roads with water on a large scale in Chinese cities is one of the supplementary precaution or mitigation actions implemented to control severe air pollution events or heavy haze-fog events in which the mechanisms causing them are not yet fully understood. These air pollution events were usually characterized by higher air humidity. Therefore, there may be a link between this action and air pollution. In the present study, the impact of water spraying on the PM2.5 concentration and humidity in air was assessed by measuring chemical composition of the water, undertaking a simulated water spraying experiment, measuring residues and analyzing relevant data. We discovered that spraying large quantities of tap or river water on the roads leads to increased PM2.5 concentration and humidity, and that daily continuous spraying produces a cumulative effect on air pollution. Spraying the same amount of water produces greater increases in humidity and PM2.5 concentration during cool autumn and winter than during hot summer. Our results demonstrate that spraying roads with water increases, rather than decreases, the concentration of PM2.5 and thus is a new source of anthropogenic aerosol and air pollution. The higher vapor content and resultant humidity most likely create unfavorable meteorological conditions for the dispersion of air pollution in autumn and winter with low temperature.

scholarly journals Application of the Data Mining Methods to Assess the Impact of Meteorological Conditions on the Episodes of High Concentrations of PM10 along the Polish – Czech Border

2018 ◽  
Vol 28 ◽  
pp. 01027
Author(s):  
Leszek Ośródka ◽  
Ewa Krajny ◽  
Marek Wojtylak
Keyword(s):  
Data Mining ◽  
Air Pollution ◽  
Particulate Matter ◽  
Concentration Level ◽  
Meteorological Data ◽  
Meteorological Conditions ◽  
Mining Methods ◽  
High Concentrations ◽  
The Impact ◽  
Derivatives Of

The paper presents an attempt to use selected data mining methods to determine the influence of a complex of meteorological conditions on the concentrations of PM10 (PM2.5) proffering the example of the regions of Silesia and Northern Moravia. The collection of standard meteorological data has been supplemented by increments and derivatives of measurable weather elements such as vertical pseudo-gradient of air temperature. The main objective was to develop a universal methodology for the assessment of these impacts, i.e. one that would be independent of the analysed pollution. The probability of occurrence (at a given location) of the assumed concentration level as exceeding the value of the specified distributional quintile was adopted as the discriminant of the incidence. As a result of the analyses conducted, incidences of elevated concentrations of air pollution particulate matter PM10 have been identified and the types of weather responsible for the emergence of such situations have also been determined.

Meteorological conditions favourable for strong aerosol impacts on clouds

2021 ◽  
Author(s):  
Heido Trofimov ◽  
Velle Toll
Keyword(s):  
Large Scale ◽  
Meteorological Data ◽  
Atmospheric Stability ◽  
Meteorological Conditions ◽  
Anthropogenic Aerosols ◽  
Anthropogenic Aerosol ◽  
Cloud Properties ◽  
Milling Operations ◽  
Track Formation ◽  
Nickel Mining

<p>Pollution tracks in clouds induced by anthropogenic aerosols (Toll et al 2019, Nature, https://doi.org/10.1038/s41586-019-1423-9) are visually detectable ship-track-like quasi-linear polluted cloud features in satellite imagery. Pollution tracks provide a direct way to study aerosol-cloud interactions, the most uncertain mechanism of anthropogenic climate forcing. Here, we study environmental conditions favourable for pollution tracks’ formation. We use meteorological data from in-situ observations and ERA5 reanalysis and cloud properties derived from MODIS retrievals over the period 2000-2019. We detected pollution track occurrences at the anthropogenic air pollution hot spots of Norilsk and Cherepovec in Russia and Thompson in Canada. In Norilsk, there are large Nickel smelters, in Cherepovec, a steel manufacturing plant, and in Thompson nickel mining and milling operations take place. We compare the meteorological conditions of track-days to cloudy no-track-days. Depending on the studied location, polluted cloud tracks occur 2.7% to 3.5% of the time. Preliminary results show track formation dependence on large-scale dynamical situation, atmospheric stability, unperturbed cloud properties and relative humidity below and above clouds. The track formation could be limited by aerosols, aerosol vertical transport and activation or cloud susceptibility. Our results help to reduce the uncertainty associated with the anthropogenic aerosol impacts on clouds.</p>

scholarly journals Statistical classification of synoptic weather patterns associated with Tehran air pollution

2020 ◽  
Author(s):  
Sakineh Khansalari ◽  
Nastran Ghobadi ◽  
Abbasali Aliakbari Bidokhti ◽  
Farahnaz Fazel Rastgar
Keyword(s):  
Air Pollution ◽  
Air Quality ◽  
Meteorological Data ◽  
Principal Component ◽  
Static Stability ◽  
Meteorological Conditions ◽  
Synoptic Patterns ◽  
Weather Patterns ◽  
Concentration Changes ◽  
The Relationship

Introduction: Poor air quality in the heavily polluted cities like Tehran is often the main city problem that influences people health and comfort. The main goals of this study are summarized as: 1) Seasonal pollutants mean variations during 2005, meteorological conditions effects on pollutant concentration; 2) Meteorological conditions case study and pollution spatial distribution for three determining synoptic patterns (MET1, MET4, MET5); 3) Further analysis of the episode from 30th November to 13th December 2005 (MET4); 4) Episode analysis from 30th November to 13th December 2005 (MET4) and 5) Episode analysis from 12th-22th of September 2005 (MET5). These are systematic weather patterns that usually affect the air pollution levels in Tehran. Materials and methods: Concentration changes of CO, PM10, SO2 and O3, as the relationship between the air pollution extreme events and atmospheric conditions in Tehran have been investigated. The hourly air pollution data from 11 representative monitoring sites were used. To understand the relationship between local meteorological synoptic patterns and air pollution, the principal component analysis (PCA) method has been applied to meteorological data. Then for minimizing the data complication the varimax rotations (VR) was used and five synoptic perspectives weather patterns have resulted for highly polluted periods. Results: Pollutants correlation investigation of the five patterns showed that air quality was highly dependent on middle tropospheric high geopotential ridge development, local southerly wind with strong static stability. Conclusion: The most polluted periods were associated with a weak pressure gradient, a weak wind, severe air descent, and radiation inversion.

scholarly journals Downscaling Winter Daily PM2.5 Concentrations From Large-Scale Meteorological Dataset -a Case Study for a City in North China

2021 ◽  
Author(s):  
Yonghe Liu ◽  
Yang Li ◽  
Mingshi Wang ◽  
Hailing Wang ◽  
Xiyue Wang
Keyword(s):  
Air Pollution ◽  
Traffic Control ◽  
Large Scale ◽  
North China ◽  
Daily Variation ◽  
Meteorological Data ◽  
Lower Atmosphere ◽  
Meteorological Variables ◽  
Main Role ◽  
The Government

Abstract Winter air pollution in North China becomes a serious environmental problem in recent years, which has aroused a widespread concern. Estimating PM2.5 concentration is necessary for the government to take actions in leading times, or to reproduce the historical values. In this study, we attempt to construct statistical downscaling (SD) models based on large-scale meteorological variables, to estimate the PM2.5 in Jiaozuo, a city in the heavy-pollution area of North China. Predictors were screened from large-scale meteorological variables, by selecting the grid boxes with the values highly correlated to the PM2.5 in Jiaozuo. Correlation maps show that PM2.5 is usually related to comparatively low pressure and high relative humidity at the lower atmosphere and comparatively high pressure at the upper atmosphere, high air temperature in all the troposphere and weak winter monsoonal winds. After training the SD models with the winter samples during 2014-2017, the daily PM2.5 is simulated with correlation coefficients of 0.607 (mean) and 0.548 (maximum) to the observation, by the logarithmic transformed PM2.5 values. The SD models can roughly reflect the daily variation of PM2.5. Compared to the PM2.5 model based on the local meteorological data, larger correlations are obtained (0.57 versus 0.51-0.53, without logarithmic transformation). In the days of “APEC Blue Sky” and the “SCO Blue Sky” with emissions largely reduced by strict controls on industry and traffic in surrounding areas, low PM2.5 is indeed observed, however, the SD models without considering any change of emissions also produced low PM2.5 simulations, implying that the large-scale circulation plays a main role in the daily variation of air pollution. Similar effects were obtained for the traffic-control month and the Chinese Spring festival with massive fireworks burning. Basing on the large-scale reanalysis variables and assuming the same emission level as that in the model training period, the downscaled winter PM2.5 has a significant decreasing trend during 1979-2017.

scholarly journals Typical synoptic situations and their impacts on the wintertime air pollution in the Guanzhong basin, China

2016 ◽  
Vol 16 (11) ◽  
pp. 7373-7387 ◽  
Author(s):  
Naifang Bei ◽  
Guohui Li ◽  
Ru-Jin Huang ◽  
Junji Cao ◽  
Ning Meng ◽  
...  
Keyword(s):  
Air Pollution ◽  
Air Quality ◽  
Large Scale ◽  
Temperature Inversion ◽  
Reanalysis Data ◽  
Horizontal Wind ◽  
Horizontal Wind Speed ◽  
Synoptic Conditions ◽  
Transport Patterns ◽  
Guanzhong Basin

Abstract. Rapid industrialization and urbanization have caused severe air pollution in the Guanzhong basin, northwestern China, with heavy haze events occurring frequently in recent winters. Using the NCEP reanalysis data, the large-scale synoptic situations influencing the Guanzhong basin during wintertime of 2013 are categorized into six types to evaluate the contribution of synoptic situations to the air pollution, including “north-low”, “southwest-trough”, “southeast-high”, “transition”, “southeast-trough”, and “inland-high”. The FLEXPART model has been utilized to demonstrate the corresponding pollutant transport patterns for the typical synoptic situations in the basin. Except for “southwest-trough” and “southeast-high” (defined as favorable synoptic situations), the other four synoptic conditions (defined as unfavorable synoptic situations) generally facilitate the accumulation of air pollutants, causing heavy air pollution in the basin. In association with the measurement of PM2.5 (particulate matter with aerodynamic diameter less than 2.5 µm) in the basin, the unfavorable synoptic situations correspond to high PM2.5 mass concentrations or poor air quality and vice versa. The same analysis has also been applied to winters of 2008–2012, which shows that the basin was mainly influenced by the unfavorable synoptic situations during wintertime leading to poor air quality. The WRF-CHEM model has further been applied to simulate the selected 6 days representing the typical synoptic situations during the wintertime of 2013, and the results generally show a good agreement between the modeled distributions and variations of PM2.5 and the corresponding synoptic situations, demonstrating reasonable classification for the synoptic situations in the basin. Detailed meteorological conditions, such as temperature inversion, low-level horizontal wind speed, and planetary boundary layer, all contribute to heavy air pollution events in the basin under unfavorable synoptic conditions. Considering the proportion of occurrence of unfavorable synoptic situations during wintertime, reduction of emissions is the optimum approach to mitigate the air pollution in the Guanzhong basin.

scholarly journals Typical synoptic situations and their impacts on the wintertime air pollution in the Guanzhong basin, China

2016 ◽  
Author(s):  
N. Bei ◽  
G. Li ◽  
R. Huang ◽  
J. Cao ◽  
N. Meng ◽  
...  
Keyword(s):  
Air Pollution ◽  
Air Quality ◽  
Large Scale ◽  
Temperature Inversion ◽  
Reanalysis Data ◽  
Horizontal Wind ◽  
Horizontal Wind Speed ◽  
Synoptic Conditions ◽  
Transport Patterns ◽  
Guanzhong Basin

Abstract. Rapid industrialization and urbanization have caused severe air pollution in the Guanzhong basin, northwestern China with heavy haze events occurring frequently in recent winters. Using the NCEP reanalysis data, the large scale synoptic situations influencing the Guanzhong basin during wintertime of 2013 are categorized into six types to evaluate the contribution of synoptic situations to the air pollution, including "north-low", "southwest-trough", "southeast-high", "transition", "southeast-trough", and "inland-high". The FLEXPART model has been utilized to demonstrate the corresponding pollutant transport patterns for the typical synoptic situations in the basin. Except "southwest-trough" and "southeast-high" (defined as favorable synoptic situations), the rest four synoptic conditions (defined as unfavorable synoptic situations) generally facilitate the accumulation of air pollutants, causing heavy air pollution in the basin. In association with the measurement of PM2.5 (particulate matter with aerodynamic diameter less than 2.5 μm) in the basin, the unfavorable synoptic situations correspond to high PM2.5 mass concentrations or poor air quality and vice versa. The same analysis has also been applied to winters of 2008–2012, which shows that the basin was mainly influenced by the unfavorable synoptic situations during wintertime leading to poor air quality. The WRF-CHEM model has further been applied to simulate the selected six days representing the typical synoptic situations during the wintertime of 2013, and the results generally show a good consistence between the modeled distributions and variations of PM2.5 and the corresponding synoptic situations, demonstrating reasonable classification for the synoptic situations in the basin. Detailed meteorological conditions, such as temperature inversion, low-level horizontal wind speed, vertical wind velocity, and convergence all contribute to heavy air pollution events in the basin under unfavorable synoptic conditions. Considering the proportion of occurrence of unfavorable synoptic situations during wintertime, reduction of emissions is the optimum approach to mitigate the air pollution in the Guanzhong basin.

Association between air pollution and chronic rhinosinusitis: a nested case-control study using meteorological data and national health screening cohort data

2021 ◽  
Vol 0 (0) ◽  
pp. 0-0
Author(s):  
J.H. Wee ◽  
C. Min ◽  
H.J. Jung ◽  
M.W. Park ◽  
H.G. Choi
Keyword(s):  
Air Pollution ◽  
Chronic Rhinosinusitis ◽  
National Health ◽  
Sunshine Duration ◽  
Meteorological Data ◽  
Health Screening ◽  
Meteorological Conditions ◽  
Control Group ◽  
Temperature Range ◽  
The Impact

Background: Inconsistent results about the effect of air pollution on chronic rhinosinusitis (CRS) have been reported. This study aimed to evaluate the impact of meteorological conditions/air pollution on the prevalence of CRS in adult Koreans. Methodology: The data from the Korean National Health Insurance Service-Health Screening Cohort from 2002 through 2015 were used. A CRS group (defined as ICD-10 codes J32, n=6159) was matched with a control group (n=24,636) in 1:4 ratios by age, sex, income, and region of residence. The meteorological conditions and air pollution data included the daily mean, highest, and lowest temperature (°C), daily temperature range (°C), relative humidity (%), ambient atmospheric pressure (hPa), sunshine duration (hr), and the rainfall (mm), SO2 (ppm), NO2 (ppm), O3 (ppm), CO (ppm), and PM10 (μg/m3) levels before the CRS diagnosis. Crude and adjusted odds ratios (ORs) and 95% confidence intervals (CIs) for CRS were analyzed using logistic regression analyses. Results: When the NO2 level increased by 0.1 ppm, the odds for CRS increased 5.40 times, and when the CO level increased by 1 ppm and PM10 increased by 10 μg/m3, the odds for CRS decreased 0.75 times and 0.93 times, respectively. Other meteorological conditions, such as the mean/highest/lowest temperature, temperature range, rainfall and other air pollution, such as SO2 and O3, were not statistically significant. NO2 for 90 days before the index date increased the risk of CRS in all subgroups, except for the nasal polyp and older age subgroups. Conclusion: CRS is related to high concentrations of NO2.

Two mechanisms for accelerated diffusion of COVID-19 outbreaks in regions with high intensity of population and polluting industrialization: the air pollution-to-human and human-to-human transmission dynamics (Preprint)

2020 ◽  
Author(s):  
Mario Coccia
Keyword(s):  
Air Pollution ◽  
Wind Speed ◽  
Critical Role ◽  
Meteorological Condition ◽  
Meteorological Conditions ◽  
Lessons Learned ◽  
Transmission Dynamics ◽  
Critical Threshold ◽  
Viral Infectivity ◽  
Low Wind Speed

BACKGROUND Coronavirus disease 2019 (COVID-19) is viral infection that generates a severe acute respiratory syndrome with serious pneumonia that may result in progressive respiratory failure and death. OBJECTIVE This study has two goals. The first is to explain the main factors determining the diffusion of COVID-19 that is generating a high level of deaths. The second is to suggest a strategy to cope with future epidemic threats with of accelerated viral infectivity in society. METHODS Correlation and regression analyses on on data of N=55 Italian province capitals, and data of infected individuals at as of April 2020. RESULTS The main results are: o The accelerate and vast diffusion of COVID-19 in North Italy has a high association with air pollution. o Hinterland cities have average days of exceeding the limits set for PM10 (particulate matter 10 micrometers or less in diameter) equal to 80 days, and an average number of infected more than 2,000 individuals as of April 1st, 2020, coastal cities have days of exceeding the limits set for PM10 equal to 60 days and have about 700 infected in average. o Cities that average number of 125 days exceeding the limits set for PM10, last year, they have an average number of infected individual higher than 3,200 units, whereas cities having less than 100 days (average number of 48 days) exceeding the limits set for PM10, they have an average number of about 900 infected individuals. o The results reveal that accelerated transmission dynamics of COVID-19 in specific environments is due to two mechanisms given by: air pollution-to-human transmission and human-to-human transmission; in particular, the mechanisms of air pollution-to-human transmission play a critical role rather than human-to-human transmission. o The finding here suggests that to minimize future epidemic similar to COVID-19, the max number of days per year in which cities can exceed the limits set for PM10 or for ozone, considering their meteorological condition, is less than 50 days. After this critical threshold, the analytical output here suggests that environmental inconsistencies because of the combination between air pollution and meteorological conditions (with high moisture%, low wind speed and fog) trigger a take-off of viral infectivity (accelerated epidemic diffusion) with damages for health of population, economy and society. CONCLUSIONS Considering the complex interaction between air pollution, meteorological conditions and biological characteristics of viral infectivity, lessons learned for COVID-19 have to be applied for a proactive socioeconomic strategy to cope with future epidemics, especially an environmental policy based on reduction of air pollution mainly in hinterland zones of countries, having low wind speed, high percentage of moisture and fog that create an environment that can damage immune system of people and foster a fast transmission of viral infectivity similar to the COVID-19. CLINICALTRIAL not applicable

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