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Atmosphere
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Carbon Emission and Transport: Measurement and Simulation (2nd Edition)
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Carbon Emission and Transport: Measurement and Simulation (2nd Edition)

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

Deadline for manuscript submissions: closed (31 May 2024) | Viewed by 1103

Special Issue Editors

Dr. Cheng Hu

E-Mail Website
Guest Editor
College of Biology and the Environment, Nanjing Forestry University, Nanjing 210037, China
Interests: CO2; CH4; model; NH3; atmospheric inversion
Special Issues, Collections and Topics in MDPI journals
Prof. Dr. Wei Xiao

E-Mail Website
Guest Editor
Yale-NUIST Center on Atmospheric Environment, International Joint Laboratory on Climate and Environment Change (ILCEC), Nanjing University of Information Science & Technology, Nanjing 211544, China
Interests: GHG; observation; isotope; lake evaporation
Special Issues, Collections and Topics in MDPI journals
Dr. Qitao Xiao

E-Mail Website
Guest Editor
Nanjing Institute of Geography and Limnology, Chinese Academy of Sciences, Nanjing 210008, China
Interests: greenhouse gases fluxes over inland water bodies
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

This Special Issue is the second volume in a series of publications dedicated to “Carbon Emission and Transport: Measurement and Simulation” (https://www.mdpi.com/si/atmosphere/04Z4LIWTD2).

Carbon is one of the main elements in both natural and anthropogenic environments. Gaseous carbon elements (i.e., carbon dioxide (CO2), methane (CH4), and carbon monoxide (CO)) are known to be main greenhouse gases or air pollutants. Hence, the study of their flux (including sources and sinks) or transport (in soil, rivers, or atmosphere) from both natural and anthropogenic sources is essential to better understand regional or global carbon cycles. Here, to improve our scientific knowledge of the carbon cycle via both observation and modeling, we have organized this Special Issue titled “Carbon Emission and Transport: Field Measurement and Model Simulation” in the journal Atmosphere. Any papers related to carbon flux and transport (especially for CO2, CH4, and CO) are warmly welcome to be submitted in this Special Issue. Papers can also focus on observations or model simulations, from natural or anthropogenic sources, and can be carried out at the field, city, regional, or even global scale, using field observations, model simulations, meta-analyses, or a combination of the above methods. Regions of interest include (but are not limited to) forests, grassland, rivers, wetlands, waters, and urban areas.

Dr. Cheng Hu
Prof. Dr. Wei Xiao
Dr. Qitao Xiao
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

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

  • CO2
  • CH4
  • CO
  • model simulation
  • eddy covariance
  • field observation

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Published Papers (1 paper)

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Research

21 pages, 4159 KiB  
Article
Simulation of China’s Carbon Peak Path Based on Random Forest and Sparrow Search Algorithm—Long Short-Term Memory
by Zhoumu Yang, Xiaoying Wu, Yinan Song and Jiao Pan
Atmosphere 2024, 15(8), 907; https://doi.org/10.3390/atmos15080907 - 29 Jul 2024
Viewed by 586
Abstract
How to decouple economic growth from carbon dioxide emissions and achieve low-carbon transformation of the Chinese economy has become an urgent problem that needs to be solved. Firstly, the Tapio index is used to identify China’s carbon peak status, and then the Technology [...] Read more.
How to decouple economic growth from carbon dioxide emissions and achieve low-carbon transformation of the Chinese economy has become an urgent problem that needs to be solved. Firstly, the Tapio index is used to identify China’s carbon peak status, and then the Technology Choice Index (TCI) and economic complexity are introduced into the comprehensive factor analysis framework for carbon dioxide emissions. Key influencing factors are identified using random forest and ridge regression. On this basis, a novel sparrow search algorithm–long short-term memory (SSA-LSTM) model which has more prediction accuracy compared with past studies is constructed to predict the dynamic evolution trend of carbon dioxide emissions, and in combination with scenario analysis, the path towards the carbon peak is simulated. The following conclusions are obtained: The benchmark scenario peaks in 2031, with a peak of 12.346 billion tons, and the low-carbon scenario peaks in 2030, with a peak of 11.962 billion tons. The extensive scenario peaks in 2037, with a peak of 13.291 billion tons. Under six scenarios, it can be concluded that energy intensity is the key factor in reducing the peak. These research results provide theoretical support for decision-makers to formulate emission reduction policies and adjust the carbon peak path. Full article
(This article belongs to the Special Issue Carbon Emission and Transport: Measurement and Simulation (2nd Edition))
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