Heavy Metal Atmospheric Deposition Study in Moscow Region, Russia

Vergel, Konstantin; Zinicovscaia, Inga; Yushin, Nikita; Frontasyeva, M. V.

doi:10.1007/s00128-019-02672-4

Cited by 22 publications

(13 citation statements)

References 21 publications

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“…In 1947, all forests of the Moscow Region were recognized as a green zone, including a ban on industrial felling. However, up to the end of the 20th century, there was an increase in the pace of industrial development: the construction and operation of machine-building plants and related infrastructure, including enterprises of the energy complexes and oil refining complexes [35]. This has led to an increase in emissions of pollutants into the atmosphere and hydrosphere.…”

Section: Design Of the Studymentioning

confidence: 99%

Modeling of Forest Communities’ Spatial Structure at the Regional Level through Remote Sensing and Field Sampling: Constraints and Solutions

Kotlov

Chernen’kova

2020

Forests

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This study tests modern approaches to spatial modeling of forest communities at the regional level based on a supervised classification. The study is conducted by the example of mapping the composition of forest communities in a large urbanized region (the Moscow Region, area 4.69 million hectares). A database of 1684 field descriptions is used as sample plots. As environmental variables, Landsat spectral reflectances, vegetation indices (5 images), digital elevation model and morphometric parameters of the relief, 54 layers in total, are used. Additionally, the Palsar-2 radar dataset is included. The main mapped units are formations and groups of associations identified on the basis of the ecological-phytocoenotic classification. Formations and groups of associations are similar in semantics and principles of allocation to units of forest typology. It is shown that the maximum entropy method has a wide range of applications, in particular, for mapping the typological diversity of forest cover. The method is used in combination with geographically structured spatial jack-knifing, spatial rarefication of occurrence data and independent testing of model feature classes and regularization parameters. Spatial rarefication is a critical technique when points are not evenly distributed in space. The resulting model of the spatial structure of forest cover is based on the integration of the best models of each thematic class of different types of forest cover into a single cartographic layer. It is shown that under conditions of uneven and sparse distribution of points, it is possible to provide an average point matching level of 0.45 for formations and 0.29 for association groups. Herewith, the spatial structure and the ratio of the formation’s composition correspond to the official data of the forest inventory. An attempt is made to identify and evaluate the distribution of more detailed syntaxonomic units: association groups. The necessary requirements for improving the quality of the forest cover model of the study area for 2 hierarchical typological units of forest cover are formulated. These include the additional sampling in order to equalize their spatial density, as well as to achieve equality of samples based on stratification according to the resulting map.

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Section: Design Of the Studymentioning

confidence: 99%

Modeling of Forest Communities’ Spatial Structure at the Regional Level through Remote Sensing and Field Sampling: Constraints and Solutions

Kotlov

Chernen’kova

2020

Forests

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“…Notably, the resuspension and dispersion of urban dust particles in Barranquilla are associated with a high vehicular density, pedestrian activities (Ali et al., 2019), and the tropical climate, characterized by high temperatures and frequent winds that promote the transport and exposure through different routes. Dust deposited superficially in urban areas is a sink and source of pollutants (Vergel et al., 2019) and tends to accumulate more trace PTEs than in the surrounding soil (Acosta et al., 2015; Gabarrón et al., 2017).…”

Section: Discussionmentioning

confidence: 99%

“…This is reflected in increasing rates of respiratory, cardiovascular, and cerebrovascular diseases as well as cancer (Anderson et al., 2012; Falcon et al., 2016). Sources of pollution in cities include vehicle traffic (Pan et al., 2016), atmospheric particle deposition (Vergel et al., 2019), construction activities (Alvanchi et al., 2020), industrial emissions (Hanfi et al., 2020), activities associated with mining (Saedpanah & Amanollahi, 2019), and the use of pharmaceuticals and personal care products (Pico et al., 2020).…”

Section: Introductionmentioning

confidence: 99%

Environmental and human health risks associated with exposure to hazardous elements present in urban dust from Barranquilla, Colombian Caribbean

et al. 2021

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Urban dust is a mixture of deposited particles from different sources usually linked to potentially toxic elements (PTEs). Despite the industrialization of many South American countries, little is known about the impact of particulate matter in large cities; these data are necessary to promote environmental policies aiming to protect human health. The main objective of this work was to evaluate the particle size distribution, composition, and environmental and human health risks of settled dust particles from Barranquilla, a Colombian Caribbean industrialized area. Trace elements were analyzed by inductively coupled plasma-mass spectrometry from 35 different sites, covering all city areas. Dust was mostly composed of 10-to-70-μm particles. The average concentrations of V,

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“…INAA has been previously applied in environmental studies (soils, sediments, biological samples), nevertheless, it is not a commonly used technique especially for the vegetal samples, and therefore it is worth to further explore its potential and limitations for plant analysis. [13][14][15][16] X-ray fluorescence (XRF) is another nondestructive technique that has also been used for plant material analysis. [17][18][19][20][21] XRF spectrometry provides the possibility of performing direct multielement analysis of solid samples with a wide dynamic range and low cost per measurement.…”

Section: Introductionmentioning

confidence: 99%

Comparison of non-destructive techniques and conventionally used spectrometric techniques for determination of elements in plant samples (coniferous leaves)

Orlić

Anicic-Urosevic

Vergel

et al. 2022

JSCS

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Conventionally used spectrometric techniques (ICP-OES, ICP-MS) usually involve time-consuming sample preparation procedure of sample dissolution which requires the usage of aggressive and toxic chemicals. The need for suitable and sustainable analytical methods for direct multi-elemental analysis of plant samples has been increased in recent years. Spectrometric techniques for direct sample analysis (INAA, XRF) have been applied in environmental studies and various fields of screening tests. Nevertheless, these techniques are not commonly used for plant sample analysis and their performances need to be evaluated. This research aimed to assess how reliable non-destructive techniques are in the determination of elements in plants compared to conventionally used spectrometric techniques. A total of 49 plant samples of four conifer species (Pinus nigra, Abies alba, Taxus baccata, and Larix decidua) were measured using two conventionally used (ICP-MS, ICP-OES) and two non-destructive techniques (WD-XRF, INAA). The comparison was performed by investigation of relative ratios of concentrations and by correlation analysis. Moreover, precision of the techniques was examined and compared. The quality control included analysis of NIST pine needles certified reference material (1575a) using all examined techniques. Our results suggest that additional analytical and quality control steps are necessary for reaching the highest accuracy of multi-elemental analysis.

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Heavy Metal Atmospheric Deposition Study in Moscow Region, Russia

Cited by 22 publications

References 21 publications

Modeling of Forest Communities’ Spatial Structure at the Regional Level through Remote Sensing and Field Sampling: Constraints and Solutions

Modeling of Forest Communities’ Spatial Structure at the Regional Level through Remote Sensing and Field Sampling: Constraints and Solutions

Environmental and human health risks associated with exposure to hazardous elements present in urban dust from Barranquilla, Colombian Caribbean

Comparison of non-destructive techniques and conventionally used spectrometric techniques for determination of elements in plant samples (coniferous leaves)

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