Acid-extractable heavy metals in PM2.5 over Xi’an, China: seasonal distribution and meteorological influence

Li, Pingping; Zhang, Shujun; Wu, Tiantian; Shen, Zhenxing; Xu, Hongmei

doi:10.1007/s11356-019-06366-6

Cited by 22 publications

(10 citation statements)

References 67 publications

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“…Similar to the studies [59,61], in terms of monthly distribution, all airports have low visibility in winter and spring and high visibility in summer and autumn. This is mainly due to the stable atmospheric stratification in winter, which is not conducive to the diffusion of pollutants, while there are many convective weather and rain in summer and autumn, which is conducive to the settlement and removal of pollutants.…”

Section: Distributions and Changes Of Airport Visibility In Different...supporting

confidence: 85%

“…By comparing nine algorithm models for predicting hourly airport visibility, we find that the RF-based model performs best. The good prediction performance, the ability to deal with continuous variables and classified variables, the characteristics of not over fitting data and the ability to reduce deviation of the RF-based model should be the reasons for the best prediction results [42,[54][55][56][57][58][59][60][61][62][63][64][65]. So, due to getting more accurate prediction results without special parameter setting, RF method has better generalization ability, and is a reliable method more suitable for practical application.…”

Section: Prediction Performances Of Different Modelsmentioning

confidence: 99%

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Forecast of Hourly Airport Visibility Based on Artificial Intelligence Methods

et al. 2022

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Based on the hourly visibility data, visibility and its changes during 2010–2020 at monthly and annual time scales over 47 international airports in China are investigated, and nine artificial-intelligence-based hourly visibility prediction models are trained (hourly data in 2018–2019) and tested (hourly data in 2020) at these airports. The analyses show that the visibility of airports in eastern and central China is at a poor level all year round, and LXA (in Lhasa) has good visibility all year round. Airports in south and the northwest China have better visibility from May to October and poorer visibility from November to April. In all months, the increasing visibility mainly occurs in the central, northeast and coastal areas of China, while decreasing visibility mainly appears in the western and northern parts of China. In spring, summer and autumn, the changes difference between east and west is particularly obvious. This East–West distribution of trends is obviously different from the North–South distribution shown by the mean. For all airports, good visibility mainly occurs from 14:00–18:00 p.m. Beijing Time, while poor visibility mainly concentrates from 22:00 p.m. to 12:00 p.m. the next day, especially between 3:00–9:00 a.m. Our proposed artificial intelligence algorithm models can be reasonably used in airport visibility prediction. In particular, most algorithm models have the best results in the visibility prediction over HFE (in Hefei) and SJW (in Shijiazhuang). On the contrary, the worst forecast results appear at LXA and LHW (in Lanzhou) airports. The prediction results of airport visibility in the cold season (October–December) are better than those in the warm season (May–September). Among the algorithm models, the prediction performance of the RF-based model is the best.

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Section: Distributions and Changes Of Airport Visibility In Different...supporting

confidence: 85%

Section: Prediction Performances Of Different Modelsmentioning

confidence: 99%

Forecast of Hourly Airport Visibility Based on Artificial Intelligence Methods

et al. 2022

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“…Formally, this review covers the papers published in the last three decades. In fact, 60% of them were published in the last decade [ 6 , 7 , 8 , 9 , 10 , 11 , 12 , 13 , 14 , 15 , 16 , 17 , 18 , 19 , 20 , 21 , 22 , 23 , 24 , 25 , 26 , 27 , 28 , 29 , 30 , 31 , 32 , 33 ] and 30% were published in the years 2001–2010 [ 34 , 35 , 36 , 37 , 38 , 39 , 40 , 41 , 42 , 43 , 44 , 45 , 46 , 47 , 48 , 49 , 50 , 51 , 52 , 53 , 54 , 55 , 56 ]. The studies on operational speciation of PTEs dealt primarily with air quality in Europe (40%) [ 6 , 10 , 11 , 14 ,…”

Section: Introductionmentioning

confidence: 99%

“…The most frequent subject of these studies was a group of toxic metals: As, Cd, Cr, Cu, Fe, Mn, Ni, Pb and Zn (50–90% of the papers) [ 9 , 12 , 13 , 16 , 21 , 27 , 30 , 33 , 34 , 35 ]. The elements such as Al [ 15 , 18 , 20 , 26 , 32 , 33 ], Co [ 9 , 12 , 14 , 17 , 21 , 23 , 26 , 27 , 28 , 29 , 30 ], V [ 23 , 26 , 27 , 33 , 57 , 58 , 59 , 60 ], Ti [ 10 , 19 , 20 , 23 , 26 , 27 , 32 , 33 ], Sb [ 10 , 11 , 14 , 20 , 27 , 28 , 32 ], Mo [ 20 , 32 , 33 , 59 , 60 , 61 ], Se […”

Section: Introductionmentioning

confidence: 99%

Chemical Fractionation in Environmental Studies of Potentially Toxic Particulate-Bound Elements in Urban Air: A Critical Review

Świetlik

Trojanowska

2022

Toxics

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In recent years, studies of heavy metal air pollution have increasingly gone beyond determining total concentrations of individual toxic metals. Chemical fractionation of potentially toxic elements in airborne particles is becoming an important part of these studies. This review covers the articles that have been published over the last three decades. Attention was paid to the issue of atmospheric aerosol sampling, sample pretreatment, sequential extraction schemes and conditions of individual extractions. Geochemical forms of metals occurring in the air in urban areas were considered in detail. Based on the data sets from chemical fractionation of particulate matter samples by three sequential extraction procedures (SEPs)—Fernández Espinosa, BCR and Chester’s—the compilation of the chemical distribution patterns of As, Cd, Co, Cr, Cu, Fe, Mn, Ni, Pb and Zn was prepared. The human health risk posed by these toxic and/or carcinogenic elements via inhalation of atmospheric particles was estimated for two categories of polluted urban areas: the commonly encountered pollution level and the high pollution level.

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“…Heavy metals were the main inorganic components of PM 2.5 and came from both natural and man-made pollution sources (Liu et al, 2019). From March 2013 to February 2014, Peng and coworkers collected PM 2.5 samples from four different sites in Huzhou, Zhejiang Province, and analyzed the lifetime cancer risks of six kinds of heavy metals (Cr, Pb, AS, Co, Cd and Ni).…”

Section: Introductionmentioning

confidence: 99%

Health risks of PM2.5-bound polycyclic aromatic hydrocarbon (PAH) and heavy metals (PPAH&HM) during the replacement of central heating with urban natural gas in Tianjin, China

Zhang

Yan

et al. 2021

Environ Geochem Health

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To investigate the health effects of fine particulate matter (B 2.5 lm in aerodynamic diameter; PM 2.5 )-bound heavy metals and polycyclic aromatic hydrocarbons (PAHs) before and after the implementation of the Urban Natural Gas Heating Project (UNGHP), the lifetime cancer risks, hazard quotients (HQs) of heavy metals and PAHs were calculated. Seven kinds of heavy metals (Al, As, Cd, Cr, Mn, Ni and Se) and 12 kinds of PAHs including acenaphthylene (ANY), acenaphthene (ANA), fluoranthene (FLT), pyrene (PYR), chrysene (CHR), benz[a]anthracene (BaA), benzo[b]fluoranthene (BbF), benzo[k]fluoranthene (BkF), benzo[a]pyrene (BaP), dibenz[a,h]anthracene (DBA), benzo[ghi]perylene (BPE) and indeno[1,2,3-cd]pyrene (IPY) were analyzed and used for the health risk assessments. It was found that HQ of Mn fell from 1.09 in the coalburning period to 0.72 in the gas-burning period in the suburban area. And lifetime cancer risks of PAHs fell from 35.7 9 10 -6 in the coal-burning period to 17.22 9 10 -6 in the gas-burning period in the urban area. It could be concluded that, during the gasburning period, downward trends were observed for the lifetime cancer risks and HQs of most kinds of heavy metals and PAHs in all regions of Tianjin compared to those during the coal-burning period. The UNGHP was effective, and we should also take other measures to control the pollution.

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Acid-extractable heavy metals in PM2.5 over Xi’an, China: seasonal distribution and meteorological influence

Cited by 22 publications

References 67 publications

Forecast of Hourly Airport Visibility Based on Artificial Intelligence Methods

Forecast of Hourly Airport Visibility Based on Artificial Intelligence Methods

Chemical Fractionation in Environmental Studies of Potentially Toxic Particulate-Bound Elements in Urban Air: A Critical Review

Health risks of PM2.5-bound polycyclic aromatic hydrocarbon (PAH) and heavy metals (PPAH&HM) during the replacement of central heating with urban natural gas in Tianjin, China

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