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18 pages, 12576 KiB

Open AccessArticle

Global Methane Retrieval, Monitoring, and Quantification in Hotspot Regions Based on AHSI/ZY-1 Satellite

by Tong Lu, Zhengqiang Li, Cheng Fan, Zhuo He, Xinran Jiang, Ying Zhang, Yuanyuan Gao, Yundong Xuan and Gerrit de Leeuw

Atmosphere 2025, 16(5), 510; https://doi.org/10.3390/atmos16050510 - 28 Apr 2025

Viewed by 83

Abstract

Methane is the second largest greenhouse gas. The detection of methane super-emitters and the quantification of their emission rates are necessary for the implementation of methane emission reduction policies to mitigate global warming. High-spectral-resolution satellites such as Gaofen-5 (GF-5), EMIT, GHGSat, and MethaneSAT [...] Read more.

Methane is the second largest greenhouse gas. The detection of methane super-emitters and the quantification of their emission rates are necessary for the implementation of methane emission reduction policies to mitigate global warming. High-spectral-resolution satellites such as Gaofen-5 (GF-5), EMIT, GHGSat, and MethaneSAT have been successfully employed to detect and quantify methane point source leaks. In this study, a matched filter (MF) algorithm is improved using data from the EMIT instrument and applied to data from the Advanced Hyperspectral Imager (AHSI) onboard the Ziyuan-1 (ZY-1) satellite. Validation by comparison with EMIT′s L2 XCH₄ products shows the good performance of the improved MF algorithm, in spite of the lower spectral resolution of AHSI/ZY-1 in comparison with other point source imagers. The improved MF algorithm applied to AHSI/ZY-1 data was used to detect and quantify methane super-emitters in global methane hotspot regions. The results show that the improved MF algorithm effectively suppresses noise in retrieval results over both land and ocean surfaces, enhancing algorithm robustness. Sixteen methane plumes were detected in global hotspot regions, originating from coal mines, oil and gas fields, and landfills, with emission rates ranging from 0.57 to 78.85 t/h. The largest plume was located at an offshore oil and gas field in the Gulf of Mexico, with instantaneous emissions nearly equal to the combined total of the other 15 plumes. The findings demonstrate that AHSI, despite its lower spectral resolution, can detect sources with emission rates as small as 571 kg/h and achieve faster retrieval speeds, showing significant potential for global methane monitoring. Additionally, this study highlights the need to focus on methane emissions from marine sources, alongside terrestrial sources, to efficiently implement reduction strategies. Full article

(This article belongs to the Special Issue Feature Papers in Atmospheric Techniques, Instruments, and Modeling)

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15 pages, 6167 KiB

Open AccessArticle

Comparison of Sensors for Air Quality Monitoring with Reference Methods in Zagreb, Croatia

by Silvije Davila, Marija Jelena Lovrić Štefiček, Ivan Bešlić, Gordana Pehnec, Marko Marić and Ivana Hrga

Atmosphere 2025, 16(4), 472; https://doi.org/10.3390/atmos16040472 - 18 Apr 2025

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Abstract

Within the scope of “Eco Map of Zagreb” project, eight sensor sets (type AQMeshPod) were set up at an automatic measuring station at the Institute for Medical Research and Occupational Health (IMROH) for comparison with reference methods for air quality measurement during 2018. [...] Read more.

Within the scope of “Eco Map of Zagreb” project, eight sensor sets (type AQMeshPod) were set up at an automatic measuring station at the Institute for Medical Research and Occupational Health (IMROH) for comparison with reference methods for air quality measurement during 2018. This station is a city background station within the Zagreb network for air quality monitoring, where measurements of SO₂, CO, NO₂, O₃, PM₁₀ and PM_2.5, are performed using standardized methods accredited according to EN ISO/IEC 17025. This paper presents a comparison of pollutant mass concentrations determined by sensors with reference methods. The data were compared and filtered to remove outliers and handle deviations between the results obtained by sensors and reference methods, considering the different approaches to gas and PM data. A comparison of sensor results with the reference methods showed a large scattering of all gaseous pollutants while the comparison for PM₁₀ and PM_2.5 indicated a satisfactory low dispersion. The results of a regression analysis showed a significant seasonal dependence for all pollutants. Significant statistical differences between the reference methods and sensors for the whole year and in all seasons for all gas pollutants, as well as for PM₁₀, were observed, while for PM_2.5 statistical significance showed varying results. Full article

(This article belongs to the Special Issue Feature Papers in Atmospheric Techniques, Instruments, and Modeling)

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12 pages, 4073 KiB

Open AccessArticle

Characteristics of Observed Electromagnetic Wave Ducts in Tropical, Subtropical, and Middle Latitude Locations

by Sandra E. Yuter, McKenzie M. Sevier, Kevin D. Burris and Matthew A. Miller

Atmosphere 2025, 16(3), 336; https://doi.org/10.3390/atmos16030336 - 17 Mar 2025

Viewed by 189

Abstract

Where and at what altitudes electromagnetic wave ducts within the atmosphere are likely to occur is important for a variety of communication and military applications. We examined the modified refractivity profiles and wave duct characteristics derived from nearly 50,000 observed upper air soundings [...] Read more.

Where and at what altitudes electromagnetic wave ducts within the atmosphere are likely to occur is important for a variety of communication and military applications. We examined the modified refractivity profiles and wave duct characteristics derived from nearly 50,000 observed upper air soundings obtained over four years from seven tropical and subtropical islands, as well as middle latitude sites at four US coastal locations, three sites near the Great Lakes, and four US inland sites. Across all location types, elevated ducts were found to be more common than surface-based ducts, and the median duct thicknesses were ~100 m. There was a weak correlation between duct thickness and strength and, essentially, no correlation between the duct strength and duct base height. EM ducts more frequently occurred at the tropical and subtropical island locations (~60%) and middle latitude coastal locations (70%) as compared to the less than 30% of the time that occurred at the Great Lake and US inland sites. The tropical and subtropical island sites were more likely than the other location types to have ducts at altitudes higher than 2 km, which is above the boundary layer height. Full article

(This article belongs to the Special Issue Feature Papers in Atmospheric Techniques, Instruments, and Modeling)

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26 pages, 13054 KiB

Open AccessArticle

Retrieval of Atmospheric XCH₄ via XGBoost Method Based on TROPOMI Satellite Data

by Wenhao Zhang, Yao Li, Bo Li, Tong Li, Zhengyong Wang, Xiufeng Yang, Yongtao Jin and Lili Zhang

Atmosphere 2025, 16(3), 279; https://doi.org/10.3390/atmos16030279 - 26 Feb 2025

Viewed by 314

Abstract

Accurate retrieval of column-averaged dry-air mole fraction of methane (XCH₄) in the atmosphere is important for greenhouse gas emission management. Traditional XCH₄ retrieval methods are complex, while machine learning can be used to model nonlinear relationships by analyzing large datasets, [...] Read more.

Accurate retrieval of column-averaged dry-air mole fraction of methane (XCH₄) in the atmosphere is important for greenhouse gas emission management. Traditional XCH₄ retrieval methods are complex, while machine learning can be used to model nonlinear relationships by analyzing large datasets, providing an efficient alternative. This study proposes an XGBoost algorithm-based retrieval method to improve the efficiency of atmospheric XCH₄ retrieval. First, the key wavelengths affecting XCH₄ retrieval were determined using a radiative transfer model. The TROPOspheric Monitoring Instrument (TROPOMI) L1B satellite data, L2 XCH₄ products, and auxiliary data were matched to construct the dataset. The dataset constructed was used to train the XGBoost model and obtain the TRO_XGB_XCH₄ model. Finally, the accuracy of the proposed model was evaluated using various parameter values and validated against XCH₄ products and Total Carbon Column Observing Network (TCCON) ground-based observations. The results showed that the proposed TRO_XGB_XCH₄ model had a tenfold cross-validation accuracy R of 0.978, a ground-based validation R of 0.749, and a temporal extension accuracy R of 0.863. Therefore, the accuracy of the TRO_XGB_XCH₄ retrieval model is comparable to that of the official TROPOMI L2 product. Full article

(This article belongs to the Special Issue Feature Papers in Atmospheric Techniques, Instruments, and Modeling)

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30 pages, 6396 KiB

Open AccessArticle

A Modified Kalman Filter Based on Radial Basis Function Neural Networks for the Improvement of Numerical Weather Prediction Models

by Athanasios Donas, George Galanis, Ioannis Pytharoulis and Ioannis Th. Famelis

Atmosphere 2025, 16(3), 248; https://doi.org/10.3390/atmos16030248 - 22 Feb 2025

Viewed by 577

Abstract

This study introduces a novel enhancement to the Kalman filter algorithm by integrating it with Radial Basis Function neural networks to improve numerical weather prediction models. Traditional Kalman filters frequently underperform when used by dynamical systems due to their reliance on fixed covariance [...] Read more.

This study introduces a novel enhancement to the Kalman filter algorithm by integrating it with Radial Basis Function neural networks to improve numerical weather prediction models. Traditional Kalman filters frequently underperform when used by dynamical systems due to their reliance on fixed covariance matrices, resulting in inaccuracies and forecast uncertainty. The proposed modified Kalman filter utilizes Radial Basis Function neural networks to estimate covariance matrices adaptively during the filtering process. This self-adaptive computational system enables the simultaneous targeting of the systematic and the remaining non-systematic parts of the forecast error, producing an innovative and efficient post-process strategy. The suggested methodology is evaluated on predictions of 10-meter wind speed and 2-meter air temperature obtained from the Weather Research and Forecasting model for observation stations in northern Greece. The derived results demonstrate a significant reduction in systematic error, as the bias decreased by up to 88% for 10-meter wind speed and 58% for 2-meter air temperature. Additionally, the forecast variability was successfully mitigated, with the RMSE reduced by 39% and 40%, respectively. Compared to the traditional Kalman filter, which exhibited increased RMSE in several cases and failed to control forecast uncertainty, the proposed approach consistently outperformed by providing stable and reliable predictions across all examined scenarios. These improvements validate the robustness of the method in comparison to conventional techniques, highlighting its potential to produce reliable and stable predictions for environmental applications. Full article

(This article belongs to the Special Issue Feature Papers in Atmospheric Techniques, Instruments, and Modeling)

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17 pages, 4857 KiB

Open AccessArticle

Biomonitoring of Potentially Toxic Elements in the Urban Atmosphere of Tehran Metropolis Using the Lichen Anaptychia setifera (Mereschk.) Räsänen

by Sara Abdollahi, Nasrin Hassanzadeh, Mohammad Sohrabi and Stefano Loppi

Atmosphere 2025, 16(2), 206; https://doi.org/10.3390/atmos16020206 - 11 Feb 2025

Cited by 1 | Viewed by 732

Abstract

This study investigated the bioaccumulation of PTEs in the 22 districts of the Tehran metropolis using the lichen Anaptychia setifera collected from Kalpoosh unpolluted area in Semnan province and exposed for 4 months in the study area using the lichen transplant technique. The [...] Read more.

This study investigated the bioaccumulation of PTEs in the 22 districts of the Tehran metropolis using the lichen Anaptychia setifera collected from Kalpoosh unpolluted area in Semnan province and exposed for 4 months in the study area using the lichen transplant technique. The concentrations of eight potentially toxic elements in the lichen were quantified using ICP-OES analysis. PCA was used to detect common sources of PTEs, and distribution maps were produced using QGIS. A statistically significant difference in the toxic elements was observed among the different stations in the Tehran metropolis. The CF index results indicate severe pollution (CF ≥ 3) for all eight studied toxic elements in the atmosphere of the Tehran metropolis. The values of the PLI index in the monitoring stations were calculated in the range of 14–31, confirming very high pollution (PLI ≥ 2.5) in the study area. The results showed a significant accumulation of all investigated toxic elements. Toxic elements such as Fe, Al, and Cr were primarily derived from natural geogenic sources, whereas Co, Cu, Ni, Pb, and Zn originated from anthropogenic sources, predominantly vehicular traffic, as depicted by the distribution patterns of these toxic elements, with peaks near sites with heavy traffic. Overall, the entire study area exhibited severe pollution levels. Full article

(This article belongs to the Special Issue Feature Papers in Atmospheric Techniques, Instruments, and Modeling)

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20 pages, 11520 KiB

Open AccessArticle

Detection of High Radar Reflectivity Volumes at High Tropospheric Levels in Large Hail Events

by Tomeu Rigo and Carme Farnell

Atmosphere 2025, 16(1), 33; https://doi.org/10.3390/atmos16010033 - 31 Dec 2024

Viewed by 709

Abstract

Different giant and very large hail events have occurred in Catalonia (NE of the Iberian Peninsula) in the last three years, with stones ranging between 8 and more than 10 cm in diameter. These sizes have not occurred in this area in at [...] Read more.

Different giant and very large hail events have occurred in Catalonia (NE of the Iberian Peninsula) in the last three years, with stones ranging between 8 and more than 10 cm in diameter. These sizes have not occurred in this area in at least thirty years. This research analyzed all those events with at least one severe hail register (more than 2 cm diameter) in the region for 2013–2023. The present study considered large volumes of high reflectivity in weather radar 3D fields at high tropospheric levels (more than 10 km). The goal was to determine if high reflectivity cores (over 55 dBZ) occurred at those levels before or during the hail-fall. The main question was whether this radar signature could reveal the occurrence of very large or giant hail. The 55 dBZ volumes occurred and were maintained over 10 km between six and sixty minutes in a high percentage of large-hail cases. However, giant hail cases did not present the maximum duration of high reflectivity at high levels as was initially expected. Full article

(This article belongs to the Special Issue Feature Papers in Atmospheric Techniques, Instruments, and Modeling)

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23 pages, 10950 KiB

Open AccessArticle

Zenith Tropospheric Delay Forecasting in the European Region Using the Informer–Long Short-Term Memory Networks Hybrid Prediction Model

by Zhengdao Yuan, Xu Lin, Yashi Xu, Jie Zhao, Nage Du, Xiaolong Cai and Mengkui Li

Atmosphere 2025, 16(1), 31; https://doi.org/10.3390/atmos16010031 - 29 Dec 2024

Cited by 1 | Viewed by 783

Abstract

Zenith tropospheric delay (ZTD) is a significant atmospheric error that impacts the Global Navigation Satellite System (GNSS). Developing a high-precision, long-term forecasting model for ZTD can provide valuable insights into the overall trends of predicted ZTD, which is essential for improving GNSS positioning [...] Read more.

Zenith tropospheric delay (ZTD) is a significant atmospheric error that impacts the Global Navigation Satellite System (GNSS). Developing a high-precision, long-term forecasting model for ZTD can provide valuable insights into the overall trends of predicted ZTD, which is essential for improving GNSS positioning and analyzing changes in regional climate and water vapor. To address the challenges of incomplete information extraction and gradient explosion in a single neural network when forecasting ZTD long-term, this study introduces an Informer–LSTM Hybrid Prediction Model. This model employs a parallel ensemble learning strategy that combines the strengths of both the Informer and LSTM networks to extract features from ZTD data. The Informer model is effective at capturing the periodicity and long-term trends within the ZTD data, while the LSTM model excels at understanding short-term dependencies and dynamic changes. By merging the features extracted by both models, the prediction capabilities of each can complement one another, allowing for a more comprehensive analysis of the characteristics present in ZTD data. In our research, we utilized ERA5-derived ZTD data from 11 International GNSS Service (IGS) stations in Europe to interpolate the missing portions of GNSS-derived ZTD. We then employed this interpolated data from 2016 to 2020, along with an Informer–LSTM Hybrid Prediction Model, to develop a long-term prediction model for ZTD with a prediction duration of one year. Our numerical results demonstrate that the proposed model outperforms several comparative models, including the LSTM–Informer based on a serial ensemble learning model, as well as the Informer, Transformer, LSTM, and GPT3 empirical ZTD models. The performance metrics indicate a root mean square error (RMSE) of 1.91 cm, a mean absolute error (MAE) of 1.45 cm, a mean absolute percentage error (MAPE) of 0.60, and a correlation coefficient (R) of 0.916. Spatial distribution analysis of the accuracy metrics showed that predictive accuracy was higher in high-latitude regions compared to low-latitude areas, with inland regions demonstrating better performance than those near the ocean. This study introduced a novel methodology for high-precision ZTD modeling, which is significant for improving accurate GNSS positioning and detecting water vapor content. Full article

(This article belongs to the Special Issue Feature Papers in Atmospheric Techniques, Instruments, and Modeling)

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15 pages, 3080 KiB

Open AccessArticle

Assessment of Doppler Wind Lidar Detection Efficiency and Influencing Factors at Plateau Airport: A Case Study of Lhasa Gonggar Airport

by Junjie Wu, Hongyu Du, Chunjiong Xia and Xiaoyuan Huang

Atmosphere 2024, 15(12), 1530; https://doi.org/10.3390/atmos15121530 - 20 Dec 2024

Viewed by 777

Abstract

Doppler wind lidar (DWL) demonstrates significant advantages in wind field detection under clear weather conditions and has been widely applied in airports with complex wind environments. However, its detection performance is highly susceptible to weather conditions and meteorological factors. To address this issue, [...] Read more.

Doppler wind lidar (DWL) demonstrates significant advantages in wind field detection under clear weather conditions and has been widely applied in airports with complex wind environments. However, its detection performance is highly susceptible to weather conditions and meteorological factors. To address this issue, this study analyzes the detection efficiency of DWL based on data collected at Lhasa Gonggar Airport from August 2023 to April 2024, along with ground-based meteorological observations. The results indicate that when the detection efficiency dropped to 40%, the average detection range for the plan position indicator (PPI) mode and Doppler beam swinging (DBS) mode were 5.3 km and 2.7 km, respectively. The influence of different underlying surface types on detection efficiency was minimal, with detection efficiency at a 270° azimuth slightly better than at a 90° azimuth. A 4° elevation angle performed better than a 6° elevation angle. During the study period, the detection efficiency generally improved, with the lowest detection efficiency being observed in August, suggesting that precipitation significantly impacts performance. In August, the detection efficiency of the PPI mode dropped below 50% at 4 km, while the highest detection efficiency occurred in April, where performance remained above 50% at 7 km. This is associated with enhanced thermal and dynamic activity in the lower atmosphere. Low-cloud activity also affected the detection performance of the DBS mode. The daily variation in the detection range in April was more pronounced than in January, with the detection range generally being larger. The increase in detection range was related to the more active vertical atmospheric mixing. The PPI mode was more sensitive to changes in meteorological factors, with its median detection range being 0.2–0.6 km shorter than that of the DBS mode when the meteorological optical range (MOR) was less than 4 km. Additionally, the PPI mode showed weaker stability than the DBS mode when relative humidity was below 75%. When relative humidity exceeded 80%, both modes showed a linear decrease in detection efficiency. Full article

(This article belongs to the Special Issue Feature Papers in Atmospheric Techniques, Instruments, and Modeling)

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26 pages, 13796 KiB

Open AccessArticle

The BIRDIES Experiment: Measuring Beryllium Isotopes to Resolve Dynamics in the Stratosphere

by Sonia Wharton, Alan J. Hidy, Thomas S. Ehrmann, Wenbo Zhu, Shaun N. Skinner, Hassan Beydoun, Philip J. Cameron-Smith, Marisa Repasch, Nipun Gunawardena, Jungmin M. Lee, Ate Visser, Matthew Griffin, Samuel Maddren and Erik Oerter

Atmosphere 2024, 15(12), 1502; https://doi.org/10.3390/atmos15121502 - 17 Dec 2024

Viewed by 1084

Abstract

Cosmogenic beryllium-10 and beryllium-7, and the ratio of the two (10Be/7Be), are powerful atmospheric tracers of stratosphere–troposphere exchange (STE) processes; however, measurements are sparse for altitudes well above the tropopause. We present a novel high-altitude balloon campaign aimed to measure these isotopes in [...] Read more.

Cosmogenic beryllium-10 and beryllium-7, and the ratio of the two (10Be/7Be), are powerful atmospheric tracers of stratosphere–troposphere exchange (STE) processes; however, measurements are sparse for altitudes well above the tropopause. We present a novel high-altitude balloon campaign aimed to measure these isotopes in the mid-stratosphere called Beryllium Isotopes for Resolving Dynamics in the Stratosphere (BIRDIES). BIRDIES targeted gravity waves produced by tropopause-overshooting convection to study their propagation and impact on STE dynamics, including the production of turbulence in the stratosphere. Two custom-designed payloads called FiSH and GASP were flown at altitudes approaching 30 km to measure in situ turbulence and beryllium isotopes (on aerosols), respectively. These were flown on nine high-altitude balloon flights over Kansas, USA, in summer 2022. The atmospheric samples were augmented with a ground-based rainfall collection targeting isotopic signatures of deep convection overshooting. Our GASP samples yielded mostly negligible amounts of both 10Be and 7Be collected in the mid-stratosphere but led to design improvements to increase aerosol capture in low-pressure environments. Observations from FiSH and the precipitation collection were more fruitful. FiSH showed the presence of turbulent velocity, temperature, and acoustic fluctuations in the stratosphere, including length scales in the infra-sonic range and inertial subrange that indicated times of elevated turbulence. The precipitation collection, and subsequent statistical analysis, showed that large spatial datasets of 10Be/7Be can be measured in individual rainfall events with minimum terrestrial contamination. While the spatial patterns in rainfall suggested some evidence for overshooting convection, inter-event temporal variability was clearly observed and predicted with good agreement using the 3D chemical transport model GEOS-CHEM. Full article

(This article belongs to the Special Issue Feature Papers in Atmospheric Techniques, Instruments, and Modeling)

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13 pages, 4497 KiB

Open AccessArticle

A Comparison of the Effects of Climate and Human Variability on the Thermal Resistance of Clothing

by Ferenc Ács, Zsófia Szalkai, Erzsébet Kristóf and Annamária Zsákai

Atmosphere 2024, 15(12), 1474; https://doi.org/10.3390/atmos15121474 - 10 Dec 2024

Viewed by 597

Abstract

We used a clothing thermal resistance model to investigate and compare the effects of climate and human variability on human thermal load. To investigate the effect of climate variability, we introduced the mean clothing thermal resistance

\bar{r_{c l}}

. For characterizing [...] Read more.

We used a clothing thermal resistance model to investigate and compare the effects of climate and human variability on human thermal load. To investigate the effect of climate variability, we introduced the mean clothing thermal resistance

\bar{r_{c l}}

. For characterizing the effect of human variability, we used the standard deviation of clothing thermal resistance

∆ r_{c l}

. We distinguished people based on their body type. We also defined the average human, a man and a woman, with thermal resistances of r_cl,m and r_cl,f. The investigation was carried out for the European region in the cold season for the period of 1981–2010. The climate variables were taken from the ERA5 reanalysis database. Our most important results are the following. (1) The macroscale pattern of the

\bar{r_{c l}}

and

∆ r_{c l}

fields are very similar, based on which it can be stated that human variability does not modify the spatial distribution of

\bar{r_{c l}}

. (2) The

∆ r_{c l}

values are roughly a quarter of the

\bar{r_{c l}}

values. The highest

\bar{r_{c l}}

values (3.2–3.4 clo) are in Lapland, and the smallest (1–1.2 clo) in Andalusia. (3) The macroscale pattern of the r_cl,m and r_cl,f fields is similar to the macroscale pattern of the r_cl values of the mesomorphic person r_cl,2. The field of r_cl,2 can be used for climate classification purposes. Full article

(This article belongs to the Special Issue Feature Papers in Atmospheric Techniques, Instruments, and Modeling)

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31 pages, 7104 KiB

Open AccessArticle

Assessing Nitrogen Dioxide in the Highveld Troposphere: Pandora Insights and TROPOMI Sentinel-5P Evaluation

by Refilwe F. Kai-Sikhakhane, Mary C. Scholes, Stuart J. Piketh, Jos van Geffen, Rebecca M. Garland, Henno Havenga and Robert J. Scholes

Atmosphere 2024, 15(10), 1187; https://doi.org/10.3390/atmos15101187 - 3 Oct 2024

Cited by 1 | Viewed by 986

Abstract

Nitrogen oxides, particularly NO₂, are emitted through a variety of industrial and transport processes globally. The world’s continuous economic development, including in developing countries, results in an increasing concentration of those gases in the atmosphere. Yet, there is scant information on [...] Read more.

Nitrogen oxides, particularly NO₂, are emitted through a variety of industrial and transport processes globally. The world’s continuous economic development, including in developing countries, results in an increasing concentration of those gases in the atmosphere. Yet, there is scant information on the current state and recent evolution of these atmospheric pollutants over a range of spatial and temporal scales, especially in Africa. This, in turn, hinders the assessment of the emissions and the evaluation of potential risks or impacts on societies and their economies, as well as on the environment. This study attempts to fill the gap by leveraging data from a Pandora-2S ground-based, column-integrating instrument located in Wakkerstroom in the Mpumalanga Province of South Africa and space-based remote sensing data obtained from the TROPOMI instrument onboard the ESA Sentinel-5P satellite. We compare these two spatially (horizontal) representative data sets using statistical tools to investigate the concentrations of emitted and transported NO₂ at this particular location, expecting that a significant positive correlation between the NO₂ tropospheric vertical column (TVC) data might justify using the TROPOMI data, available globally, as a proxy for tropospheric and boundary layer NO₂ concentrations over the Highveld of South Africa more generally. The data from the two instruments showed no significant difference between the interannual mean TVC-NO₂ in 2020 and 2021. The seasonal patterns for both instruments were different in 2020, but in 2021, both measured peak TVC-NO₂ concentrations in late winter (week 34). The instruments both detected higher TVC-NO₂ concentrations during transitions between seasons, particularly from winter to spring. The TVC-NO₂ concentrations measured in Wakkerstroom Mpumalanga are mostly contributed to by the emission sources in the low troposphere, such as biomass burning and emissions from local power stations. Full article

(This article belongs to the Special Issue Feature Papers in Atmospheric Techniques, Instruments, and Modeling)

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Review

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14 pages, 2057 KiB

Open AccessReview

Methods, Progress and Challenges in Global Monitoring of Carbon Emissions from Biomass Combustion

by Ge Qu, Yusheng Shi, Yongliang Yang, Wen Wu and Zhitao Zhou

Atmosphere 2024, 15(10), 1247; https://doi.org/10.3390/atmos15101247 - 18 Oct 2024

Cited by 1 | Viewed by 1755

Abstract

Global biomass burning represents a significant source of carbon emissions, exerting a substantial influence on the global carbon cycle and climate change. As global carbon emissions become increasingly concerning, accurately quantifying the carbon emissions from biomass burning has emerged as a pivotal and [...] Read more.

Global biomass burning represents a significant source of carbon emissions, exerting a substantial influence on the global carbon cycle and climate change. As global carbon emissions become increasingly concerning, accurately quantifying the carbon emissions from biomass burning has emerged as a pivotal and challenging area of scientific research. This paper presents a comprehensive review of the primary monitoring techniques for carbon emissions from biomass burning, encompassing both bottom-up and top-down approaches. It examines the current status and limitations of these techniques in practice. The bottom-up method primarily employs terrestrial ecosystem models, emission inventory methods, and fire radiation power (FRP) techniques, which rely on the integration of fire activity data and emission factors to estimate carbon emissions. The top-down method employs atmospheric observation data and atmospheric chemical transport models to invert carbon emission fluxes. Both methods continue to face significant challenges, such as limited satellite resolution affecting data accuracy, uncertainties in emission factors in regions lacking ground validation, and difficulties in model optimization due to the complexity of atmospheric processes. In light of these considerations, this paper explores the prospective evolution of carbon emission monitoring technology for biomass burning, with a particular emphasis on the significance of high-precision estimation methodologies, technological advancements in satellite remote sensing, and the optimization of global emission inventories. This study aims to provide a forward-looking perspective on the evolution of carbon emission monitoring from biomass burning, offering a valuable reference point for related scientific research and policy formulation. Full article

(This article belongs to the Special Issue Feature Papers in Atmospheric Techniques, Instruments, and Modeling)

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