Country-scale complementary passive and active biomonitoring of airborne trace elements for environmental risk assessment

Ştefănuţ, S.; Öllerer, Kinga; Ion, Mihaela C.; Florescu, Larisa I.; Constantin, Marian; Banciu, Cristian; Onete, Marilena; Manu, Minodora; Vicol, Ioana; Moldoveanu, Mirela; Maican, Sanda; Cobzaru, Ioana; Nicoară, Roxana G.; Mogîldea, Elena D.; Purice, Dorina; Nicolae, Claudia D.; Catană, Rodica D.; Teodosiu, Gabriela; Dumitrache, Cristina A.; Maria, Gabriel M.; Moroșanu, Ana-Maria; Paica, Ioana C.; Bîrsan, Constantin-Ciprian; Tamas, Gabriela; Vladimirescu, Mihnea; Manole, Anca

doi:10.1016/j.ecolind.2021.107357

Cited by 10 publications

(3 citation statements)

References 35 publications

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“…Passive biomonitoring reflects more long-term changes in environmental quality, it has some limitations such as: the scale of a study can be restrained due to varying environmental conditions, local situations and survey area characteristics as well as the limitation of species variety or mass and their morphological and physiological differences in a given location [25] [26] [31]. However, active biomonitoring overcomes these limitations as selected species or sampling equipment can be translocated to the study area for a specified duration of time enabling the use of the same species on a larger scale, independently of its natural occurrence giving spatial and temporal information on sources and deposition patterns of atmospheric contaminants leading to a higher degree of standardization [25] [32].…”

Section: Introductionmentioning

confidence: 99%

“…ensure particles of edaphic origin are detached and the standardization of samples from any environmental factors[33]. There are relatively few studies that compare passive and active biomonitoring studies of the same regions and these focus on the geochemical concentrations of air pollutants and utilize plants species and mosses that are not present in arid dry regions (e.g.Ștefănuț et al 2021, da Costa et al 2016; Fleck et al 2016)[25] [34][35]. In this study, dust samplers will be applied as active biomonitors and P. dactylifera as passive biomonitors in the assessment of PM in a Kuwait by de-…”

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confidence: 99%

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The Spatial Distribution Assessment of Particulate Matter by Biomagnetic Monitoring Using Phoenix dactylifera Leaf Samples and Azimuthal Dust Samplers in Kuwait

Almutawa¹,

Samson²

2022

ACS

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This study employs multi-magnetic parametric methods as proxies to measure particulate matter (PM) concentration and spread in Kuwait. It examines the reliability of biomonitoring receptors in the assessment of atmospheric air quality through the utilization of passive biomonitoring methodology using cleaned and non-cleaned Phoenix dactylifera leaves and active biomonitoring through the application of dust samplers in the study area. Four radial sampling areas are located at 2, 6, 10, 14 km from Kuwait's city center with 10 sampling degree points selected from each radial area, and the closest palm tree in the vicinity to the preselected sampling point with a height of 4 m were sampled. Using a compass, the 4 azithumal points were pin pointed on the selected tree and a 2 × 2 cm dust sampler was attached to each direction at a height of 2 m. The dust sampler was made of clear plastic paper attached with double sided tape. Magnetic susceptibility and Saturation Isothermic Remanent Magnetization (SIRM), Natural Remanent Magnetization (NRM), Hard Isothermal Remanent Magnetization (HIRM), Soft Isothermal Remanent Magnetization (SOFT), HIRM%, soft IRM% and s-ratio were determined for P. dactylifera and dust samplers. Magnetic parameters were mapped to assess the spatial variation of air quality in Kuwait and the values between dust samplers and P. dactylifera. Results indicate that the highest magnetic concentration values for NRM and SIRM for P. dactylifera occurred near Kuwait bay and that the majority of the samples contain ferromagnetic minerals with magnetite most likely from anthropogenic sources. The results of the interpolation How to cite this paper: Almutawa, A. and Roeland, S. (2022) The Spatial Distribution Assessment of Particulate Matter by Biomagnetic Monitoring Using Phoenix dactylifera Leaf Samples and Azimuthal Dust Samplers in Kuwait. Atmospheric and Climate Sciences, 12, 532-563.

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Section: Introductionmentioning

confidence: 99%

mentioning

confidence: 99%

The Spatial Distribution Assessment of Particulate Matter by Biomagnetic Monitoring Using Phoenix dactylifera Leaf Samples and Azimuthal Dust Samplers in Kuwait

Almutawa¹,

Samson²

2022

ACS

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“…Özellikle hızla artan sanayileşme ve kentleşme bir dizi çevre kirliliğinin oluşmasına neden olmaktadır [2]. Çevre kirliliğinin nitel ve nicel olarak belirlenmesinde biyoizleme yöntemleri sıklıkla kullanılmaktadır [3], [4]. Bu alandaki araştırmalar sayesinde, çevre kirliliğinin tahmini ile olumsuz değişikliklerin türü ve ölçeği belirlenebilmektedir [5].…”

Section: Introductionunclassified

Determination of organochlorine pesticide (OCP) residues in air and pollen samples and pollutant partition between these environments

Sari

Esen

2022

Pamukkale J Eng Sci

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Bu çalışmada, kentsel ve yarı kentsel bölgelerdeki hava ve polen örneklerinde organoklorlu pestisit (OCP) konsantrasyonlarının bölgesel ve zamansal değişimleri ile hava/polen arasındaki dağılımların belirlenmesi amaçlanmıştır. Örnekleme periyodu boyunca hava ve polen örneklerindeki toplam 10 OCP (∑10OCP) konsantrasyonları kentsel örnekleme noktası için sırasıyla 318.2±73.7 pg/m 3 v 21.7±5.1 ng/g, yarı-kentsel örnekleme noktası için ise sırasıyla 390.1±103.5 pg/m 3 ve 20.0±3.3 ng/g olarak belirlenmiştir. Ayrıca α-HCH ve endosülfan-ß bileşiklerinin hem polen hem de hava örneklerinde en baskın OCP bileşikleri olduğu belirlenmiştir. Her iki örnekleme noktasında genellikle yaz aylarında yüksek OCP konsantrasyonları ölçülmüştür. Hava ve polen arasındaki OCP geçişlerinin belirlenmesi için polen/hava dağılım katsayısı (𝐾 𝑃𝐴 ) hesaplanmıştır. Elde edilen sonuçlara göre, hem kentsel hem de yarı-kentsel örnekleme noktasında genellikle polenden dış ortam havasına OCP geçişlerinin olduğu belirlenmiştir.In this study, it was aimed to determine the regional and temporal variations of organochlorine pesticide (OCP) concentrations in air and pollen samples in urban and semi-urban areas and the distribution between air/pollen. A total of 10 OCP (∑10OCP) concentrations in air and pollen samples during the sampling period were determined as 318.2±73.7 pg/m 3 and 21.7±5.1 ng/g for the urban sampling point and 390.1±103.5 pg/m 3 and 20.0±3.3 ng/g for the semi-urban point, respectively. In addition, it was determined that α-HCH and endosulfanß compounds were the most dominant OCP compounds in both pollen and air samples. High OCP concentrations were measured at both sampling points, usually during the summer months. Pollen/air partition coefficient (𝐾 𝑃𝐴 ) was calculated to determine OCP exchange between air and pollen. According to the results obtained, it has been determined that there are generally OCP transitions from pollen to ambient air at both urban and semi-urban sampling points.

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Assessment of Air Pollution in Ulaanbaatar Using the Moss Bag Technique

Zinicovscaia,

Narmandakh,

Yushin

et al. 2024

Arch Environ Contam Toxicol

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Country-scale complementary passive and active biomonitoring of airborne trace elements for environmental risk assessment

Cited by 10 publications

References 35 publications

The Spatial Distribution Assessment of Particulate Matter by Biomagnetic Monitoring Using Phoenix dactylifera Leaf Samples and Azimuthal Dust Samplers in Kuwait

The Spatial Distribution Assessment of Particulate Matter by Biomagnetic Monitoring Using Phoenix dactylifera Leaf Samples and Azimuthal Dust Samplers in Kuwait

Determination of organochlorine pesticide (OCP) residues in air and pollen samples and pollutant partition between these environments

Assessment of Air Pollution in Ulaanbaatar Using the Moss Bag Technique

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