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Atmosphere
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Anthropogenic Pollutants in Environmental Geochemistry
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Anthropogenic Pollutants in Environmental Geochemistry

A special issue of Atmosphere (ISSN 2073-4433). This special issue belongs to the section "Aerosols".

Deadline for manuscript submissions: closed (18 December 2022) | Viewed by 10618

Special Issue Editors

Dr. Jun Li

E-Mail Website
Guest Editor
School of the Earth Sciences and Resources, China University of Geosciences, Beijing 100083, China
Interests: source apportionment; persistent organic pollutants; road dust; sediment; atmospheric transport
Special Issues, Collections and Topics in MDPI journals
Dr. Zhixiong Li

E-Mail Website
Guest Editor
School of Earth Sciences and Resources, China University of Geosciences, Beijing 100083, China
Interests: natural organic matter; nanoparticles; environmental process; remediation; emerging pollutant
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Atmosphere dedicates this Special Issue to anthropogenic pollutants (APs). APs, including synthetic organic materials and toxic elements, are known to adversely affect human health because of their persistent, bioaccumulative, and toxic characteristics. Once released from mid- and low-latitude anthropogenic sources, three major groups of APs (persistent organic pollutants, microplastics, and heavy metals) can be atmospherically transported thousands of kilometers away and spread to every corner of the Earth. Geochemical surveys show that bedrock geochemistry controls not only the content of heavy metals, but also the composition of soil and even that of water and vegetation, which affect the global cycles of APs. These APs are therefore found to be geographically distributed, and their fate depends on the geochemical conditions. There is also increasing recognition that changes in the geochemistry of the Earth’s surface as a result of human activity have an impact on AP emissions and sink. In the context of these concerns, there is a serious lack of monitoring and information on the environmental occurrences and geochemical behaviors of APs and little information on associated exposure and the effects of that exposure on people and ecosystems.

The main goal of this Special Issue is to provide informative data to reveal the linkage between the environmental geochemistry of the Earth’s surface and the occurrences and fates of APs. Studies related to environmental quality assessment, source appointment, and the transformation pathway of APs as well as to their atmospheric transport/deposition process and historic reconstruction are welcome. Contributions from monitoring programs, field experiments, and associated laboratory/modelling studies are all welcome as well.

Dr. Jun Li
Dr. Zhixiong Li
Guest Editors

Manuscript Submission Information

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Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Atmosphere is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2400 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • atmospheric deposition
  • historic record
  • long-term monitoring
  • geochemical conditions
  • soil properties
  • source appointment
  • persistent organic pollutants
  • microplastics
  • heavy metals

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Published Papers (5 papers)

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Research

14 pages, 2426 KiB  
Article
Deep Learning-Based PM2.5 Long Time-Series Prediction by Fusing Multisource Data—A Case Study of Beijing
by Meng Niu, Yuqing Zhang and Zihe Ren
Atmosphere 2023, 14(2), 340; https://doi.org/10.3390/atmos14020340 - 8 Feb 2023
Cited by 15 | Viewed by 3445
Abstract
Accurate air quality prediction is of great significance for pollution prevention and disaster prevention. Effective and reliable prediction models are needed not only for short time prediction, but are even more important for long time-series future predictions. In the long time series, most [...] Read more.
Accurate air quality prediction is of great significance for pollution prevention and disaster prevention. Effective and reliable prediction models are needed not only for short time prediction, but are even more important for long time-series future predictions. In the long time series, most of the current models might not function as accurately as in the short period and thus a new model is required. In this paper, the new PM2.5 predictor is proposed to achieve accurate long time series PM2.5 prediction in Beijing. The predictor simplifies the input parameters through Spearman correlation analysis and implements the long time series prediction through Informer. The results show that AQI, CO, NO2, and PM10 concentrations are selected from the air quality data, and Dew Point Temperature (DEWP) and wind speed are incorporated from two meteorological data to better improve the prediction efficiency by almost 27%. By comparing with LSTM and attention-LSTM models, the model constructed in this paper performs well in different prediction time periods, with at least 21%, 19%, 28%, and 35% improvement in accuracy in four prediction time series: 48 h, 7 days, 14 days, and 30 days. In conclusion, the proposed model is proved to solve the problem of predicting long time series PM2.5 concentrations in the future, which can make up for the shortcomings of the currently existing models and have good application value. Full article
(This article belongs to the Special Issue Anthropogenic Pollutants in Environmental Geochemistry)
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10 pages, 2278 KiB  
Article
Research on Prospecting Prediction Based on Evidence Weight
by Zhen Chen and Mingde Lang
Atmosphere 2022, 13(12), 2125; https://doi.org/10.3390/atmos13122125 - 17 Dec 2022
Cited by 3 | Viewed by 1404
Abstract
There are many small and medium-sized orogenic copper deposits in the Jinman–Lanping area of Yunnan. In order to standardize mining, long-term planning, and unified management, it is necessary to further delineate prospecting areas. In order to improve the efficiency of prospecting, a data-driven [...] Read more.
There are many small and medium-sized orogenic copper deposits in the Jinman–Lanping area of Yunnan. In order to standardize mining, long-term planning, and unified management, it is necessary to further delineate prospecting areas. In order to improve the efficiency of prospecting, a data-driven approach is established. This paper uses the weight of evidence model to make prospecting predictions, and it then delineates the prospective prospecting area. The relevant evidence layers in the weight of evidence model are geochemical anomalies and remote sensing iron staining anomalies. Among them, the geochemical anomaly layer mainly uses the concentration-area (C-A) fractal model to separate the geochemical background and anomaly acquisition. The remote sensing iron-stained anomaly layer mainly uses bands (1, 4, 5, 7), and bands (1, 3, 4, 5) were combined for principal component analysis to extract abnormal iron staining. Finally, using the weight of evidence model, the spatial element layers (evidence layers) from different sources were combined, and the interaction between them was analyzed. It is pointed out that the area has good prospects for prospecting, and the prospective prospecting area was thus delineated. Full article
(This article belongs to the Special Issue Anthropogenic Pollutants in Environmental Geochemistry)
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13 pages, 2003 KiB  
Article
A Study of Land Ecological Environment Evaluation Based on an Ideal Point Model
by Zhen Chen and Lianwu Shi
Atmosphere 2022, 13(12), 1955; https://doi.org/10.3390/atmos13121955 - 23 Nov 2022
Viewed by 1223
Abstract
The paper took Guang’an City in Sichuan Province of China as a research region, and it built an evaluation index system based on 14 evaluation indices according to four criteria, namely, ecological background, ecological structure, ecological benefits, and ecological stress. The Delphi algorithm [...] Read more.
The paper took Guang’an City in Sichuan Province of China as a research region, and it built an evaluation index system based on 14 evaluation indices according to four criteria, namely, ecological background, ecological structure, ecological benefits, and ecological stress. The Delphi algorithm and entropy weight (a combination of subjective and objective methods) were used to calculate the weight value of each evaluation index, and an ideal point model was used to calculate the ideal point value. The ideal point ecological grade was classified, and the principal component analysis method was used to obtain the main control factors of each year, which revealed the relationship between the ecological distribution of ideal points and the environmental impact factor, with the changing characteristics of the ecology in the research region according to the hotspot model of the spatial differentiation of land ecological quality as the main control factor. Lastly, the paper also analyzed the land ecological quality of Guangan City in 2000, 2005, 2010, and 2015. The study results show that the overall land ecological quality in Guang’an City generally increased from 2005 to 2015. The proportion of forest land area and the temperature were the most important main control factors. The air temperature and the land ecological quality were positively correlated. Full article
(This article belongs to the Special Issue Anthropogenic Pollutants in Environmental Geochemistry)
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13 pages, 3196 KiB  
Article
A Facilely Synthesized Tourmaline–Biochar Composite for Enhanced Removal of Cr (VI) from Aqueous Solution
by Siyi Huang, Qi Lu, Xiaorui Ma, Yunwen Chen and Reziya Maimaiti
Atmosphere 2022, 13(10), 1643; https://doi.org/10.3390/atmos13101643 - 9 Oct 2022
Cited by 6 | Viewed by 1645
Abstract
Hexavalent chromium (Cr (VI)), an anthropogenic heavy metal pollutant, is harmful to human beings, due to its carcinogenicity. In this study, a tourmaline–biochar composite (TMBC) was synthesized to remove Cr (VI) from an aqueous solution. The effects of different ratios (TM:BC) and pyrolysis [...] Read more.
Hexavalent chromium (Cr (VI)), an anthropogenic heavy metal pollutant, is harmful to human beings, due to its carcinogenicity. In this study, a tourmaline–biochar composite (TMBC) was synthesized to remove Cr (VI) from an aqueous solution. The effects of different ratios (TM:BC) and pyrolysis temperatures on TMBC adsorption performance were compared. The TMBC samples were characterized by X-ray diffraction (XRD), Fourier transform infrared (FTIR) and scanning electron microscope–energy-dispersive spectrometry (SEM-EDS). The kinetics and thermodynamics were analyzed to investigate the sorption mechanism. The results showed that the proper pyrolysis temperature was 650 °C, and the ratio of TM:BC was 1:3. SEM results showed the TM was well attached to the BC which assisted tourmaline dispersion. The adsorption kinetics were well fitted by the pseudo-second-order model, indicating that the sorption was related to chemical absorption. Langmuir adsorption isotherms suggested monolayer adsorption between the Cr (VI) and the TMBC, and the maximum adsorption capacity of the TMBC for Cr (VI) was 43.64 mg/g, which was more than twice the amount for the pristine TM (17.84 mg/g). The automatic polarization of water caused by tourmaline was the unique adsorption property of the TMBC. Therefore, TMBCs can be used as an economic adsorbent in the remediation of heavy metal pollution. Full article
(This article belongs to the Special Issue Anthropogenic Pollutants in Environmental Geochemistry)
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12 pages, 2630 KiB  
Article
Characteristics and Provenance Implications of Rare Earth Elements and Nd Isotope in PM2.5 in a Coastal City of Southeastern China
by Yihong Li, Shanshan Wang, Yu Yan, Jinpei Yan, Ruilian Yu and Gongren Hu
Atmosphere 2022, 13(9), 1367; https://doi.org/10.3390/atmos13091367 - 26 Aug 2022
Viewed by 1649
Abstract
The source apportionment of fine particulate matters, especially PM2.5, has drawn great attention worldwide. Since rare earth elements (REEs) and Nd isotopes can serve as source tracers, in this study, the characteristics and provenance implications of REEs and Nd isotopes in [...] Read more.
The source apportionment of fine particulate matters, especially PM2.5, has drawn great attention worldwide. Since rare earth elements (REEs) and Nd isotopes can serve as source tracers, in this study, the characteristics and provenance implications of REEs and Nd isotopes in PM2.5 of four seasons in Xiamen city, China, were investigated. The range of the ratios of ΣREE to PM2.5 was 1.04 × 10−5 to 8.06 × 10−4, and the mean concentration of REEs in PM2.5 were in the order of spring > autumn > winter > summer. According to the geoaccumulation index (Igeo), spring was the season in which anthropogenic sources had the greatest impact on the REEs in PM2.5. The chondrite-normalized REE distribution patterns exhibited light rare earth elements (LREEs, including La, Ce, Pr, Nd, Pm, Sm and Eu) enrichment and a flat heavy rare earth elements (HREEs, including Gd, Tb, Dy, Ho, Er, Tm, Yb and Lu) pattern. Significant negative Eu anomalies and no significant Ce anomalies were observed in the PM2.5. The results of La-Ce-Sm ternary plots indicated that the REEs in the PM2.5 might be related to both natural and anthropogenic sources. Combined with the Nd isotope, the 143Nd/144Nd versus Ce/Ce* plot further illustrated that the REEs in the PM2.5 seemed to mostly originate from multiple potential sources, in which vehicle exhaust emissions, coal burning and cement dust made a great contribution to REEs in PM2.5. Full article
(This article belongs to the Special Issue Anthropogenic Pollutants in Environmental Geochemistry)
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