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Atmosphere
Special Issues
Novel Techniques for Measuring Greenhouse Gases
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Novel Techniques for Measuring Greenhouse Gases

A special issue of Atmosphere (ISSN 2073-4433). This special issue belongs to the section "Atmospheric Techniques, Instruments, and Modeling".

Deadline for manuscript submissions: closed (27 June 2022) | Viewed by 13067

Special Issue Editors

Dr. Ge Han

E-Mail Website
Guest Editor
School of Remote Sensing and Information Engineering, Wuhan University, Wuhan 4730079, China
Interests: CO2; CH4; remote sensing; Lidar
Special Issues, Collections and Topics in MDPI journals
Dr. Miao Zhang

E-Mail Website
Guest Editor
School of Geographic Science and Tourism, Nanyang Normal University, Nanyang 473061, China
Interests: atmospheric lidar remote sensing
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Currently, most of the world’s major countries and regions have announced their own plans for carbon neutrality. Greenhouse gas (GHG) measurement technology is an integral part of achieving the goal of carbon neutrality. In this new era, the scientific community expects and welcomes new monitoring technologies for quantifying carbon dioxide (CO2) and methane (CH4) emissions, and for distinguishing between anthropogenic and natural fluxes. This Special Issue calls for papers regarding developments and applications of novel GHG measurement techniques including but not limited to Lidar, FTIR , AirCore, low-cost miniaturized equipment, etc. We are also keen to see advances in greenhouse gas monitoring methodologies, especially with regard to quantifications of methane emissions, obtaining high-resolution CO2 fluxes with urban scale, measurements of point CO2 sources, and monitoring natural CO2/CH4 fluxes.

Dr. Ge Han
Dr. Miao Zhang
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

  • Greenhouse gases
  • CO2 and CH4 fluxes
  • In situ measurements
  • Lidar
  • FTIR
  • NDIR
  • Multi-platform remote sensing
  • Carbon neutral

Published Papers (6 papers)

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Research

13 pages, 5903 KiB  
Article
Measuring Greenhouse Gas Emissions from Point Sources with Mobile Systems
by Mengyang Cai, Huiqin Mao, Cuihong Chen, Xvpeng Wei and Tianqi Shi
Atmosphere 2022, 13(8), 1249; https://0-doi-org.brum.beds.ac.uk/10.3390/atmos13081249 - 06 Aug 2022
Cited by 2 | Viewed by 1715
Abstract
The traditional least squares method for the retrieval of CO2 emissions from CO2 emission sources is affected by the nonlinear characteristics of the Gaussian plume model, which leads to the optimal estimation of CO2 emissions easily falling into local minima. [...] Read more.
The traditional least squares method for the retrieval of CO2 emissions from CO2 emission sources is affected by the nonlinear characteristics of the Gaussian plume model, which leads to the optimal estimation of CO2 emissions easily falling into local minima. In this study, ACA–IPFM (ant colony algorithm and interior point penalty function) is proposed to remedy the shortcomings of the traditional least squares method, which makes full use of the global search property of the ant colony algorithm and the local exact search capability of the interior point penalty function to make the optimal estimation of CO2 emissions closer to the global optimum. We evaluate the errors of several parameters that are most likely to affect the accuracy of the CO2 emission retrieval and analyze these errors jointly. These parameters include wind speed measurement error, wind direction measurement error, CO2 concentration measurement error, and the number of CO2 concentration measurements. When the wind speed error is less than 20%, the inverse error of CO2 concentration emission is less than 1% and the uncertainty is less than 3%, when the wind direction error is less than 55 degrees, the inverse error is less than 1% and the uncertainty is less than 3%, when the CO2 concentration measurement error is less than 10%, the inverse error is less than 1% and the uncertainty is less than 3.3%, and when the measurement quantity is higher than 60, the inverse error is less than 1% and the uncertainty is less than 3%. In addition, we simulate the concentration observations on different paths under the same conditions, and invert the CO2 emissions based on these simulated values. Through the retrieval results, we evaluate the errors caused by different paths of measurements, and have demonstrated that different paths are affected by different emission sources to different degrees, resulting in different inversion accuracies for different paths under the same conditions in the end, which can provide some reference for the actual measurement route planning of the mobile system. Combined with the characteristics of the agility of the mobile system, ACA–IPFM can extend the monitoring of CO2 emissions to a wider area. Full article
(This article belongs to the Special Issue Novel Techniques for Measuring Greenhouse Gases)
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15 pages, 4553 KiB  
Article
Development of an Integrated Lightweight Multi-Rotor UAV Payload for Atmospheric Carbon Dioxide Mole Fraction Measurements
by Tonghui Zhao, Dongxu Yang, Yi Liu, Zhaonan Cai, Lu Yao, Ke Che, Xiaoyu Ren, Yongheng Bi, You Yi, Jing Wang and Sihong Zhu
Atmosphere 2022, 13(6), 855; https://0-doi-org.brum.beds.ac.uk/10.3390/atmos13060855 - 24 May 2022
Cited by 3 | Viewed by 2261
Abstract
Records and projections of increasing global average temperature call for improvements of global stocktake inputs, which are vital to achieving targets of intergovernmental agreements on climate change. Unmanned Aerial Vehicle (UAV)-based atmospheric observation of greenhouse gas (GHG) concentrations is an upcoming addition to [...] Read more.
Records and projections of increasing global average temperature call for improvements of global stocktake inputs, which are vital to achieving targets of intergovernmental agreements on climate change. Unmanned Aerial Vehicle (UAV)-based atmospheric observation of greenhouse gas (GHG) concentrations is an upcoming addition to the top-down measurement methods due to its advantageous spatial-temporal resolutions, greater coverage area and lower costs. Hence, we developed and tested a lightweight UAV payload enclosure integrating a non-dispersive diffusion infrared (NDIR) spectrometer and two electrochemical sensors for measurements of carbon dioxide (CO2), carbon monoxide (CO) and nitrogen dioxide (NO2). To achieve higher response times and maintain measurement qualities, we designed a custom air inlet on the rotor-facing side of the enclosure to reduce measurement fluctuations caused by rotor downwash airflow. To validate the payload design, we conducted a controlled test for comparing chambered and chamber-less NDIR spectrometer measurements. From the test we observed a reduction of 0.48 hPa in terms of standard deviation of pressure measurements and minimised downwash-flow-induced anomalous biases (+0.49 ppm and +0.08 hpa for chambered compared to −1.33 ppm and −1.05 hpa for chamber-less). We also conducted an outdoor in-situ measurement test with multiple flights reaching 500 m above ground level (ABGL). The test yielded high resolution results representing vertical distributions of mole fraction concentrations of three types of gases via two types of flight trajectory planning methods. Therefore, we provide an alternative UAV payload integration method for NDIR spectrometer CO2 measurements that complement existing airborne GHG observation methodologies. Additionally, we also introduced an aerodynamic approach in reducing measurement noises and biases for a low response time sensor configuration. Full article
(This article belongs to the Special Issue Novel Techniques for Measuring Greenhouse Gases)
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17 pages, 4503 KiB  
Article
Occurrence and Discrepancy of Surface and Column Mole Fractions of CO2 and CH4 at a Desert Site in Dunhuang, Western China
by Chong Wei, Zheng Lyu, Lingbing Bu and Jiqiao Liu
Atmosphere 2022, 13(4), 571; https://0-doi-org.brum.beds.ac.uk/10.3390/atmos13040571 - 01 Apr 2022
Cited by 2 | Viewed by 1959
Abstract
Carbon dioxide (CO2) and methane (CH4) are the two major radiative forcing factors of greenhouse gases. In this study, surface and column mole fractions of CO2 and CH4 were first measured at a desert site in Dunhuang, [...] Read more.
Carbon dioxide (CO2) and methane (CH4) are the two major radiative forcing factors of greenhouse gases. In this study, surface and column mole fractions of CO2 and CH4 were first measured at a desert site in Dunhuang, west China. The average column mole fractions of CO2 (XCO2) and CH4 (XCH4) were 413.00 ± 1.09 ppm and 1876 ± 6 ppb, respectively, which were 0.90 ppm and 72 ppb lower than their surface values. Diurnal XCO2 showed a sinusoidal mode, while XCH4 appeared as a unimodal distribution. Ground observed XCO2 and XCH4 were compared with international satellites, such as GOSAT, GOSAT-2, OCO-2, OCO-3, and Sentinel-5P. The differences between satellites and EM27/SUN observations were 0.26% for XCO2 and −0.38% for XCH4, suggesting a good consistency between different satellites and ground observations in desert regions in China. Hourly XCO2 was close to surface CO2 mole fractions, but XCH4 appeared to have a large gap with CH4, probably because of the additional chemical removals of CH4 in the upper atmosphere. It is necessary to carry out a long-term observation of column mole fractions of greenhouse gases in the future to obtain their temporal distributions as well as the differences between satellites and ground observations. Full article
(This article belongs to the Special Issue Novel Techniques for Measuring Greenhouse Gases)
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14 pages, 11527 KiB  
Article
The Spatial and Temporal Distribution Patterns of XCH4 in China: New Observations from TROPOMI
by Jiaxing Zhang, Ge Han, Huiqin Mao, Zhipeng Pei, Xin Ma, Weijie Jia and Wei Gong
Atmosphere 2022, 13(2), 177; https://0-doi-org.brum.beds.ac.uk/10.3390/atmos13020177 - 21 Jan 2022
Cited by 14 | Viewed by 3218
Abstract
Methane is the second most important greenhouse gas after carbon dioxide. The intensity and distribution of methane source/sink in China are unknown. We collected the column-averaged dry air mixing ratio of CH4 (abbreviated as XCH4 hereafter) from TROPOMI for the period [...] Read more.
Methane is the second most important greenhouse gas after carbon dioxide. The intensity and distribution of methane source/sink in China are unknown. We collected the column-averaged dry air mixing ratio of CH4 (abbreviated as XCH4 hereafter) from TROPOMI for the period from 2018 to 2021, to study spatial distribution and temporal change of atmospheric CH4 concentration, providing clues and foundations for understanding the source/sink in China. It was found that the distribution of XCH4 is roughly high in the East, low in the West, high in the South and low in the North. Additionally, an evidently positive linear relationship between XCH4 and population density was witnessed, suggesting anthropogenic emissions may account for a large portion of total methane emissions. XCH4 exhibits evident seasonal characteristics, with the peak in summer and trough in winter, regardless of the different regions. Moreover, we used XCH4 anomalies to identify the emission sources and found its great potential in the detection of methane emission from mining plants, landfill, rice fields and even geological fracture zones. Full article
(This article belongs to the Special Issue Novel Techniques for Measuring Greenhouse Gases)
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13 pages, 4292 KiB  
Article
Analog and Photon Signal Splicing for CO2-DIAL Based on Piecewise Nonlinear Algorithm
by Chengzhi Xiang and Ailin Liang
Atmosphere 2022, 13(1), 109; https://0-doi-org.brum.beds.ac.uk/10.3390/atmos13010109 - 10 Jan 2022
Viewed by 1187
Abstract
In the CO2 differential absorption lidar (DIAL) system, signals are simultaneously collected through analog detection (AD) and photon counting (PC). These two kinds of signals have their own characteristics. Therefore, a combination of AD and PC signals is of great importance to [...] Read more.
In the CO2 differential absorption lidar (DIAL) system, signals are simultaneously collected through analog detection (AD) and photon counting (PC). These two kinds of signals have their own characteristics. Therefore, a combination of AD and PC signals is of great importance to improve the detection capability (detection range and accuracy) of CO2-DIAL. The traditional signal splicing algorithm cannot meet the accuracy requirements of CO2 inversion due to unreasonable data fitting. In this paper, a piecewise least square splicing algorithm is developed to make signal splicing more flexible and efficient. First, the lidar signal is segmented, and according to the characteristics of each signal, the best fitting parameters are obtained by using the least square fitting with different steps. Then, all the segmented and fitted signals are integrated to realize the effective splicing of the near-field AD signal and the far-field PC signal. A weight gradient strategy is also adopted in signal splicing, and the weights of the AD and PC signals in the spliced signal change with the height. The splicing effect of the improved algorithm is evaluated by the measured signal, which are obtained in Wuhan, China, and the splice of the AD and PC signals in the range of 800–1500 m are completed. Compared with the traditional method, the evaluation parameter R2 and the residual sum of squares of the spliced signal are greatly improved. The linear relationship between the AD and PC signals is improved, and the fitting R2 of differential absorption optical depth reaches 0.909, indicating that the improved signal splicing algorithm can well splice the near-field AD signal and the far-field PC signal. Full article
(This article belongs to the Special Issue Novel Techniques for Measuring Greenhouse Gases)
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15 pages, 2899 KiB  
Article
Emission Determination by Three Remote Sensing Methods in Two Release Trials
by Imke Elpelt-Wessel, Martin Reiser, Daniel Morrison and Martin Kranert
Atmosphere 2022, 13(1), 53; https://0-doi-org.brum.beds.ac.uk/10.3390/atmos13010053 - 29 Dec 2021
Cited by 2 | Viewed by 1763
Abstract
Concentrations of greenhouse gases such as carbon dioxide (CO2), nitrous dioxide (N2O) and methane (CH4) in the atmosphere are rising continuously. The first step to reduce emissions from landfills is to gain better knowledge about the quantities [...] Read more.
Concentrations of greenhouse gases such as carbon dioxide (CO2), nitrous dioxide (N2O) and methane (CH4) in the atmosphere are rising continuously. The first step to reduce emissions from landfills is to gain better knowledge about the quantities emitted. There are several ways to quantify CH4 emissions at landfills. Comprehensive quality analyses of individual methods for emission rate quantification at landfills are few to date. In the present paper, the authors conducted two field trials with three different remote sensing methods to gain more knowledge about the possibilities and challenges in quantification of CH4 emissions from landfills. One release trial was conducted with released N2O as tracer and CH4 for quality assessment of the methods. In the second trial, the N2O tracer was released on a landfill to gain experience under field conditions. The well-established inverse dispersion modelling method (IDMM) was used based on concentration data of TDLAS (Tunable Diode Laser Absorption Spectroscopy)-instruments and on concentration data of a partly drone based Fourier-Transformation-Infrared-Spectroscopy (FTIR)-instrument. Additionally, a tracer-method with N2O-tracer and FTIR measurements was conducted. In both trials, IDMM based on TDLAS data and FTIR data provided the best results for high emission rates (15% deviation) and low emission rates (47% deviation). However, both methods have advantages, depending on the field of application. IDMM based on TDLAS measurements is the best choice for long-term measurements over several hours with constant wind conditions (8% deviation). The IDMM based on drone based FTIR measurements is the means of choice for measurements under changing wind conditions and where no linear measurement distances are possible. Full article
(This article belongs to the Special Issue Novel Techniques for Measuring Greenhouse Gases)
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