Investigate Secondary Aerosol Formation and Source by Stable Isotopes

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

Deadline for manuscript submissions: closed (31 December 2022) | Viewed by 3596

Special Issue Editor


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Guest Editor
Yale-NUIST Center on Atmospheric Environment, Nanjing University of Information Science and Technology, Nanjing 210044, China
Interests: atmospheric chemistry; reactive nitrogen; ammonia; isotopic analysis; haze; secondary aerosol formation
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Special Issue Information

Dear Colleagues,

Nitrate, sulfate, ammonium and carbonaceous aerosols are the main compositions of atmospheric fine particles, and most of them are secondary aerosols formed by gas phase NOx, SOx, NH3 and volatile organic compounds in the atmosphere. Stable isotopic compositions, such as C (13C), N (15N) and S (34S and 33S), take their unique values from different emission sources, which can be used to indicate the potential emission source. During the oxidation of gas phase precursors into secondary aerosols, isotopic fractionations always couple with these chemical reactions. Thus, isotopic fractionation factors can be used to indicate secondary aerosol formation pathways. In addition, stable oxygen isotopic compositions (18O and 17O) provide information for nitrate and sulfate formation pathways. Therefore, multiple stable isotopes have been identified to investigate the formation and source of secondary aerosols.

In this Special Issue, study areas including, but not limited to, the following topics:

  1. new methods for isotopic analysis;
  2. stable isotopic signatures from different emission sources;
  3. theoretical estimation and/or in situ observation of isotopic fractionation factors;
  4. how isotopic compositions constrain secondary aerosol formation mechanism and emission sources;
  5. the expanding application of isotopes on the atmospheric chemistry and physics.

Prof. Dr. Yunhua Chang
Guest Editor

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Published Papers (2 papers)

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Research

15 pages, 5201 KiB  
Article
Improving Intra-Urban Prediction of Atmospheric Fine Particles Using a Hybrid Deep Learning Approach
by Zhengyu Zhang, Jiuchun Ren and Yunhua Chang
Atmosphere 2023, 14(3), 599; https://doi.org/10.3390/atmos14030599 - 21 Mar 2023
Cited by 1 | Viewed by 1357
Abstract
Growing evidence links intra-urban gradients in atmospheric fine particles (PM2.5), a complex and variable cocktail of toxic chemicals, to adverse health outcomes. Here, we propose an improved hierarchical deep learning model framework to estimate the hourly variation of PM2.5 mass [...] Read more.
Growing evidence links intra-urban gradients in atmospheric fine particles (PM2.5), a complex and variable cocktail of toxic chemicals, to adverse health outcomes. Here, we propose an improved hierarchical deep learning model framework to estimate the hourly variation of PM2.5 mass concentration at the street level. By using a full-year monitoring data (including meteorological parameters, hourly concentrations of PM2.5, and gaseous precursors) from multiple stations in Shanghai, the largest city in China, as a training dataset, we first apply a convolutional neural network to obtain cross-domain and time-series features so that the inherent features of air quality and meteorological data associated with PM2.5 can be effectively extracted. Next, a Gaussian weight calculation layer is used to determine the potential interaction effects between different regions and neighboring stations. Finally, a long and short-term memory model layer is used to efficiently extract the temporal evolution characteristics of PM2.5 concentrations from the previous output layer. Further comparative analysis reveals that our proposed model framework significantly outperforms previous benchmark methods in terms of the stability and accuracy of PM2.5 prediction, which has important implications for the intra-urban health assessment of PM2.5-related pollution exposures. Full article
(This article belongs to the Special Issue Investigate Secondary Aerosol Formation and Source by Stable Isotopes)
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14 pages, 6751 KiB  
Article
Characteristics and Sources of Water-Soluble Inorganic Ions in PM2.5 in Urban Nanjing, China
by Qinghao Guo, Kui Chen and Guojie Xu
Atmosphere 2023, 14(1), 135; https://doi.org/10.3390/atmos14010135 - 7 Jan 2023
Cited by 3 | Viewed by 1926
Abstract
In this study, the water-soluble inorganic ions (WSIIs) composition of fine particulate matter (PM2.5) was measured in the northern Nanjing city from 2015 to 2021. NH4+, NO3 and SO42− concentrations dominated in total WSIIs [...] Read more.
In this study, the water-soluble inorganic ions (WSIIs) composition of fine particulate matter (PM2.5) was measured in the northern Nanjing city from 2015 to 2021. NH4+, NO3 and SO42− concentrations dominated in total WSIIs (Na+, NH4+, K+, Mg2+, Ca2+, Cl, NO3 and SO42−), accounting for 87.8%. The nitrate with highest average concentration among all ions was 11.0 μg·m−3. Total WSIIs concentrations were higher in winter and lower in summer, with the highest levels in December (45.6 μg·m−3) and the lowest levels in August (15.1 μg·m−3). NO3/SO42− was higher than 1, indicating the important contribution of mobile sources. The aerosols exhibited a weak acidic by the molar ratio of water-soluble anions and cations. Positive matrix factorization (PMF) analysis results showed that secondary nitrate and sulfate were the major pollution sources in December 2016 and 2020. The contribution of secondary nitrate in 2020 increased by 47.6% compared to 2016, while that of secondary sulfate decreased by 42.4%. The potential source contribution results demonstrated that for secondary aerosol concentrations, the contribution of regional transport from north of Anhui increased, while the contribution of local emissions decreased. The results from this study could contribute to the better prevention and control of regional air pollution in the future. Full article
(This article belongs to the Special Issue Investigate Secondary Aerosol Formation and Source by Stable Isotopes)
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