scholarly journals To what extents do urbanization and air pollution affect fog?

2020 ◽  
Vol 20 (9) ◽  
pp. 5559-5572
Author(s):  
Shuqi Yan ◽  
Bin Zhu ◽  
Yong Huang ◽  
Jun Zhu ◽  
Hanqing Kang ◽  
...  
Keyword(s):  
Air Pollution ◽  
Eastern China ◽  
Liquid Water Content ◽  
Pollution Level ◽  
Combined Effects ◽  
Promoting Effect ◽  
Radiation Fog ◽  
Rapid Urbanization ◽  
Budget Analysis ◽  
Aerosol Pollution

Abstract. The remarkable development of China has resulted in rapid urbanization (urban heat island and dry island) and severe air pollution (aerosol pollution). Previous studies demonstrate that these two factors have either suppressing or promoting effects on fog, but what are the extents of their individual and combined effects? In this study, a dense radiation fog event in eastern China in January 2017 was reproduced by the Weather Research and Forecasting model coupled with Chemistry (WRF-Chem), and the individual and combined effects of urbanization and aerosols on fog (indicated by liquid water content – LWC) are quantitatively revealed. Results show that urbanization inhibits low-level fog, delays its formation and advances its dissipation due to higher temperatures and lower saturations. In contrast, upper-level fog could be enhanced because of the updraught-induced vapour convergence. Aerosols promote fog by increasing LWC, increasing droplet concentration and decreasing droplet effective radius. Further experiments show that the current pollution level in China could still be below the critical aerosol concentration that suppresses fog. Urbanization influences fog to a larger extent than aerosols do. When urbanization and aerosol pollution are combined, the much weaker aerosol-promoting effect is counteracted by the stronger urbanization-suppressing effect on fog. Budget analysis of LWC reveals that urban development (urbanization and aerosols) alters the LWC profile and fog structure mainly by modulating condensation–evaporation process. Our results infer that urban fog will be further reduced if urbanization keeps developing and air quality keeps deteriorating in the future.

scholarly journals To what extents do urbanization and air pollution affect fog?

2020 ◽  
Author(s):  
Shuqi Yan ◽  
Bin Zhu ◽  
Yong Huang ◽  
Jun Zhu ◽  
Hanqing Kang ◽  
...  
Keyword(s):  
Air Pollution ◽  
Liquid Water Content ◽  
Pollution Level ◽  
Combined Effects ◽  
Promoting Effect ◽  
Radiation Fog ◽  
Rapid Urbanization ◽  
Budget Analysis ◽  
Aerosol Pollution ◽  
The Individual

Abstract. The remarkable development of China has resulted in rapid urbanization (urban heat island and dry island) and severe air pollution (aerosol pollution). Previous studies demonstrate that these two factors have either suppressing or promoting effects on fog, but what are the extents of their individual and combined effects? In this study, a dense radiation fog event in East China in January 2017 was reproduced by the WRF-Chem model, and the individual and combined effects of urbanization and aerosols on fog (indicated by liquid water content (LWC)) are quantitatively revealed. Results show that urbanization inhibits low-level fog, delays its formation and advances its dissipation due to higher temperatures and lower saturations. In contrast, upper-level fog could be enhanced because of the updraft-induced vapour convergence. Aerosols promote fog by increasing LWC, increasing droplet concentration and decreasing droplet effective radius. Further experiments show that the current pollution level in China is still below the critical aerosol concentration that suppresses fog. Urbanization influences fog to a larger extent than do aerosols. When urbanization and aerosol pollution are combined, the much weaker aerosol promoting effect is counteracted by the stronger urbanization suppressing effect on fog. Budget analysis of LWC reveals that urban development (urbanization and aerosols) alters LWC profile and fog structure mainly by modulating condensation/evaporation process. Our results infer that urban fog will be further reduced if urbanization keeps developing and air quality keeps deteriorating in the future.

scholarly journals Integrated impacts of synoptic forcing and aerosol radiative effect on boundary layer and pollution in the Beijing–Tianjin–Hebei region, China

2020 ◽  
Vol 20 (10) ◽  
pp. 5899-5909 ◽  
Author(s):  
Yucong Miao ◽  
Huizheng Che ◽  
Xiaoye Zhang ◽  
Shuhua Liu
Keyword(s):  
Boundary Layer ◽  
Air Quality ◽  
Large Scale ◽  
Eastern China ◽  
Radiative Effect ◽  
Synoptic Pattern ◽  
Rapid Urbanization ◽  
Synoptic Conditions ◽  
Aerosol Pollution ◽  
Aerosol Radiative

Abstract. Rapid urbanization and industrialization have led to deterioration of air quality in the Beijing–Tianjin–Hebei (BTH) region due to high loadings of PM2.5. Heavy aerosol pollution frequently occurs in winter, in close relation to the planetary boundary layer (PBL) meteorology. To unravel the physical processes that influence PBL structure and aerosol pollution in BTH, this study combined long-term observational data analyses, synoptic pattern classification, and meteorology–chemistry coupled simulations. During the winter of 2017 and 2018, Beijing and Tangshan often experienced heavy PM2.5 pollution simultaneously, accompanied by strong thermal inversion aloft. These concurrences of pollution in different cities were primarily regulated by the large-scale synoptic conditions. Using principal component analysis with geopotential height fields at the 850 hPa level during winter, two typical synoptic patterns associated with heavy pollution in BTH were identified. One pattern is characterized by a southeast-to-north pressure gradient across BTH, and the other is associated with high pressure in eastern China. Both synoptic types feature warmer air temperature at 1000 m a.g.l., which could suppress the development of the PBL. Under these unfavorable synoptic conditions, aerosols can modulate PBL structure through the radiative effect, which was examined using numerical simulations. The aerosol radiative effect can significantly lower the daytime boundary layer height through cooling the surface layer and heating the upper part of the PBL, leading to the deterioration of air quality. This PBL–aerosol feedback is sensitive to the aerosol vertical structure, which is more effective when the synoptic pattern can distribute more aerosols to the upper PBL.

scholarly journals THE INFLUENCING FACTORS OF SO42- AND NO3- IN PM10 IN JINHUA, CHINA

2021 ◽  
Vol 9 (4) ◽  
pp. 935-945
Author(s):  
Yeshun Peng ◽  
◽  
Tingting Yan ◽  
Jianming Feng ◽  
Wamono Emma ◽  
...  
Keyword(s):  
Air Pollution ◽  
Oxidation Rate ◽  
Eastern China ◽  
Sulfur Oxidation ◽  
Phase Reaction ◽  
Promoting Effect ◽  
Atmospheric Particulates ◽  
Formation And Evolution ◽  
Increasing Temperature ◽  
Liquid Phase Reaction

Sulfate (SO42-) and nitrate (NO3-) are the main secondary inorganic components in atmospheric particulates. It is of great significance to understand the formation and evolution of air pollution in the process of air pollution. In this study, samples of PM10 were collected in Jinhua City in eastern China from December 2019 to January 2020 and from June 2020 to August 2020, and also analyzed the influence of different meteorological conditions and gaseous pollutants on the formation of SO42- and NO3- in PM10. The results show that high relative humidity has a significant effect on the increase of sulfur oxidation rate (SOR) in winter, indicating that the winter liquid phase reaction is more conducive to the formation of SO42-. SOR and nitrogen oxidation rate (NOR) decrease with increasing temperature in winter, and increase with increasing temperature in summer. The light intensity has an important promoting effect on both SOR and NOR, indicating that the photochemical reaction is beneficial to the formation of SO42- and NO3-. Both the gaseous precursors SO2 and NO2 have significant promoting effects on the formation of SO42- and NO3- in winter, and the promoting effect of O3 on NOR is higher than that on SOR, indicating that atmospheric oxidation capacity has a greater effect on the formation of NO3-, and the effect of CO on SOR is higher than that on NOR, and there is a negative correlation with SOR.

scholarly journals Effects of urban land expansion on the regional meteorology and air quality of Eastern China

2015 ◽  
Vol 15 (7) ◽  
pp. 10299-10340 ◽  
Author(s):  
W. Tao ◽  
J. Liu ◽  
G. A. Ban-Weiss ◽  
D. A. Hauglustaine ◽  
L. Zhang ◽  
...  
Keyword(s):  
Air Pollution ◽  
Air Quality ◽  
Urban Expansion ◽  
Eastern China ◽  
Urban Land ◽  
Pollutant Emissions ◽  
Ozone Pollution ◽  
Rapid Urbanization ◽  
Local Climate ◽  
Analysis Scheme

Abstract. Rapid urbanization throughout Eastern China is imposing an irreversible effect on local climate and air quality. In this paper, we examine the response of a range of meteorological and air quality indicators to urbanization. Our study uses the Weather Research and Forecasting model coupled with Chemistry (WRF/Chem) to simulate the climate and air quality impacts of four hypothetical urbanization scenarios with fixed surface pollutant emissions during the month of July from 2008 to 2012. An improved integrated process rate (IPR) analysis scheme is implemented in WRF/Chem to investigate the mechanisms behind the forcing–response relationship at the process level. For all years, as urban land area expands, concentrations of CO, elemental carbon (EC), and particulate matter with aerodynamic diameter less than 2.5 microns (PM2.5) tend to decrease near the surface (below ~ 500 m), but increase at higher altitudes (1–3 km), resulting in a reduced vertical concentration gradient. On the other hand, the O3 burden averaged over all newly urbanized grid cells consistently increases from the surface to a height of about 4 km. Sensitivity tests show that the response of meteorology and pollutant concentrations to the spatial extent of urbanization are nearly linear near the surface, but nonlinear at higher altitudes. Over eastern China, each 10% increase in nearby urban land coverage (NULC) on average leads to a decrease of approximately 2% in surface concentrations for CO, EC, and PM2.5, while for O3 an increase of about 1% is simulated. At 800 hPa, each 10% increase in the square of NULC enhances air pollution concentrations by 5–10%, depending on species. This indicates that as large tracts of new urban land emerge, the influence of urban expansion on meteorology and air pollution would be amplified. IPR results indicate that, for primary pollutants, the enhanced sink (source) caused by turbulent mixing and vertical advection in the lower (upper) atmosphere could be a key factor in changes to simulated vertical profiles. The evolution of secondary pollutants is further influenced by the upward relocation of precursors that impact gas phase chemistry for O3 and aerosol processes for PM2.5. Our study indicates that dense urbanization has a moderate dilution effect on surface primary airborne contaminants, but may intensify severe haze and ozone pollution if local emissions are not well controlled.

An Urban Air Pollution Early Warning System Based on PM2.5 Prediction Applied in Ploiesti City

2017 ◽  
Vol 68 (4) ◽  
pp. 858-863
Author(s):  
Mihaela Oprea ◽  
Marius Olteanu ◽  
Radu Teodor Ianache
Keyword(s):  
Air Pollution ◽  
Early Warning ◽  
Urban Areas ◽  
Early Warning System ◽  
Urban Air Pollution ◽  
Warning System ◽  
Air Pollutant ◽  
Pollution Level ◽  
Urban Air ◽  
Prediction Approach

Fine particulate matter with a diameter less than 2.5 �m (i.e. PM2.5) is an air pollutant of special concern for urban areas due to its potential significant negative effects on human health, especially on children and elderly people. In order to reduce these effects, new tools based on PM2.5 monitoring infrastructures tailored to specific urban regions are needed by the local and regional environmental management systems for the provision of an expert support to decision makers in air quality planning for cities and also, to inform in real time the vulnerable population when PM2.5 related air pollution episodes occur. The paper focuses on urban air pollution early warning based on PM2.5 prediction. It describes the methodology used, the prediction approach, and the experimental system developed under the ROKIDAIR project for the analysis of PM2.5 air pollution level, health impact assessment and early warning of sensitive people in the Ploiesti city. The PM2.5 concentration evolution prediction is correlated with PM2.5 air pollution and health effects analysis, and the final result is processed by the ROKIDAIR Early Warning System (EWS) and sent as a message to the affected population via email or SMS. ROKIDAIR EWS is included in the ROKIDAIR decision support system.

scholarly journals A global association between Covid-19 cases and airborne particulate matter at regional level

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Angelo Solimini ◽  
F. Filipponi ◽  
D. Alunni Fegatelli ◽  
B. Caputo ◽  
C. M. De Marco ◽  
...  
Keyword(s):  
Air Pollution ◽  
Particulate Matter ◽  
Negative Binomial ◽  
Numerical Models ◽  
Regional Level ◽  
Pollution Level ◽  
Observation Data ◽  
Cumulative Number ◽  
Mixed Effect

AbstractEvidences of an association between air pollution and Covid-19 infections are mixed and inconclusive. We conducted an ecological analysis at regional scale of long-term exposure to air-borne particle matter and spread of Covid-19 cases during the first wave of epidemics. Global air pollution and climate data were calculated from satellite earth observation data assimilated into numerical models at 10 km resolution. Main outcome was defined as the cumulative number of cases of Covid-19 in the 14 days following the date when > 10 cumulative cases were reported. Negative binomial mixed effect models were applied to estimate the associations between the outcome and long-term exposure to air pollution at the regional level (PM10, PM2.5), after adjusting for relevant regional and country level covariates and spatial correlation. In total we collected 237,749 Covid-19 cases from 730 regions, 63 countries and 5 continents at May 30, 2020. A 10 μg/m3 increase of pollution level was associated with 8.1% (95% CI 5.4%, 10.5%) and 11.5% (95% CI 7.8%, 14.9%) increases in the number of cases in a 14 days window, for PM2.5 and PM10 respectively. We found an association between Covid-19 cases and air pollution suggestive of a possible causal link among particulate matter levels and incidence of COVID-19.

scholarly journals Scalable kernel-based SVM classification algorithm on imbalance air quality data for proficient healthcare

2021 ◽  
Author(s):  
Shwet Ketu ◽  
Pramod Kumar Mishra
Keyword(s):  
Air Pollution ◽  
Air Quality ◽  
Class Imbalance ◽  
Imbalanced Data ◽  
Classification Algorithm ◽  
Quality Data ◽  
Pollution Level ◽  
Classification Problems ◽  
Chi Square ◽  
The Impact

AbstractIn the last decade, we have seen drastic changes in the air pollution level, which has become a critical environmental issue. It should be handled carefully towards making the solutions for proficient healthcare. Reducing the impact of air pollution on human health is possible only if the data is correctly classified. In numerous classification problems, we are facing the class imbalance issue. Learning from imbalanced data is always a challenging task for researchers, and from time to time, possible solutions have been developed by researchers. In this paper, we are focused on dealing with the imbalanced class distribution in a way that the classification algorithm will not compromise its performance. The proposed algorithm is based on the concept of the adjusting kernel scaling (AKS) method to deal with the multi-class imbalanced dataset. The kernel function's selection has been evaluated with the help of weighting criteria and the chi-square test. All the experimental evaluation has been performed on sensor-based Indian Central Pollution Control Board (CPCB) dataset. The proposed algorithm with the highest accuracy of 99.66% wins the race among all the classification algorithms i.e. Adaboost (59.72%), Multi-Layer Perceptron (95.71%), GaussianNB (80.87%), and SVM (96.92). The results of the proposed algorithm are also better than the existing literature methods. It is also clear from these results that our proposed algorithm is efficient for dealing with class imbalance problems along with enhanced performance. Thus, accurate classification of air quality through our proposed algorithm will be useful for improving the existing preventive policies and will also help in enhancing the capabilities of effective emergency response in the worst pollution situation.

scholarly journals Meteorological Variables and Synoptic Patterns Associated with Air Pollutions in Eastern China during 2013–2018

2020 ◽  
Vol 17 (7) ◽  
pp. 2528 ◽  
Author(s):  
Zhujun Dai ◽  
Duanyang Liu ◽  
Kun Yu ◽  
Lu Cao ◽  
Youshan Jiang
Keyword(s):  
Air Pollution ◽  
Eastern China ◽  
Meteorological Condition ◽  
Temperature Inversion ◽  
Meteorological Conditions ◽  
Meteorological Variables ◽  
Synoptic Situation ◽  
Factors Affecting ◽  
Air Pollutions ◽  
Meteorological Elements

Steady meteorological conditions are important external factors affecting air pollution. In order to analyze how adverse meteorological variables affect air pollution, surface synoptic situation patterns and meteorological conditions during heavy pollution episodes are discussed. The results showed that there were 78 RPHPDs (regional PM2.5 pollution days) in Jiangsu, with a decreasing trend year by year. Winter had the most stable meteorological conditions, thus most RPHPDs appeared in winter, followed by autumn and summer, with the least days in spring. RPHPDs were classified into three patterns, respectively, as equalized pressure (EQP), advancing edge of a cold front (ACF) and inverted trough of low pressure (INT) according to the SLP (sea level pressure). RPHPDs under EQP were the most (51%), followed by ACF (37%); INT was the minimum (12%). Using statistical methods and meteorological condition data on RPHPDs from 2013 to 2017 to deduce the thresholds and 2018 as an independent dataset to validate the proposed thresholds, the threshold values of meteorological elements are summarized as follows. The probability of RPHPDs without rain was above 92% with the daily and hourly precipitation of all RPHPDs below 2.1 mm and 0.8 mm. Wind speed, RHs, inversion intensity(ITI), height difference in the temperature inversion(ITK), the lower height of temperature inversion (LHTI) and mixed-layer height (MLH) in terms of 25%–75% high probability range were respectively within 0.5–3.6 m s−1, 55%–92%, 0.7–4.0 °C 100 m −1, 42–576 m, 3–570 m, 200–1200 m. Two conditions should be considered: whether the pattern was EQP, ACF or INT and whether the eight meteorological elements are within the thresholds. If both criteria are met, PM2.5 particles tend to accumulate and air pollution diffusion conditions are poor. Unfavorable meteorological conditions are the necessary, but not sufficient condition for RPHPDs.

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