Atmosphere

16 pages, 5823 KiB

Open AccessArticle

Influence of Dynamic and Thermal Effects of Asian Topography on Tropical Cyclone Activity as Simulated in a Global Climate Model

by Jinxiao Li

Atmosphere 2023, 14(5), 905; https://doi.org/10.3390/atmos14050905 - 22 May 2023

Viewed by 1624

Abstract

Asian topography plays a significant role in regional and global weather and climate change. Based on the dataset of climate system model named CAS FGOALS-f3 participated in Global monsoons Model Inter-comparison (GMMIP), the MIP endorsement of Coupled Model Intercomparison Project Phase 6 (CMIP6), [...] Read more.

Asian topography plays a significant role in regional and global weather and climate change. Based on the dataset of climate system model named CAS FGOALS-f3 participated in Global monsoons Model Inter-comparison (GMMIP), the MIP endorsement of Coupled Model Intercomparison Project Phase 6 (CMIP6), the role of Asian topography to the formation and movement of tropical cyclones (TCs) are discussed in this study. This study provides the first comparative analysis of the dynamic and thermal effects of Asian topography on the regional and global activity of TCs. The results indicate that the Asian topography promotes the generation and development of TCs, especially in the Northwest Pacific (WNP). The contribution of the Asian topography to the number of TCs reached about 50% in WNP. It is worth noting that there are still positive biases of TC track density in the experiment named “AMIP-NS”, which means the thermal effect of Asian topography is also essential for TC formation and development in WNP, which has not received much attention before. Besides, the possible reasons for the modulation of TC activity are given from two aspects: (1) The existence of Asian topography has changed the large-scale factors related to TC activities such as warm core, sea-level pressure, genesis potential index (GPI), which are beneficial to the generation and movement of TC. (2) Asian topography promotes the spread of Madden–Julian oscillation (MJO), which is also beneficial to the generation and movement of TC. It is worthwhile to investigate further the mechanisms by which Asian topography affects the activity of TCs. Full article

(This article belongs to the Special Issue Advances in Tropical Cyclone Prediction: Observation, Simulation, and Verification)

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2 pages, 186 KiB

Open AccessEditorial

Student-Led Research in Atmospheric Science

by Ari D. Preston and David E. Reed

Atmosphere 2023, 14(5), 904; https://doi.org/10.3390/atmos14050904 - 22 May 2023

Viewed by 1021

Abstract

Engaging students in research is critical to their development as atmospheric scientists [...] Full article

(This article belongs to the Special Issue Student-Led Research in Atmospheric Science)

17 pages, 2890 KiB

Open AccessArticle

PM_2.5 Concentration Prediction in Six Major Chinese Urban Agglomerations: A Comparative Study of Various Machine Learning Methods Based on Meteorological Data

by Min Duan, Yufan Sun, Binzhe Zhang, Chi Chen, Tao Tan and Yihua Zhu

Atmosphere 2023, 14(5), 903; https://doi.org/10.3390/atmos14050903 - 22 May 2023

Cited by 2 | Viewed by 2427

Abstract

The escalating issue of air pollution in China’s rapidly developing urban areas has prompted increased attention to the role of meteorological conditions in PM_2.5 pollution. This study examines the spatiotemporal distribution of PM_2.5 concentrations and their relationship with meteorological factors in [...] Read more.

The escalating issue of air pollution in China’s rapidly developing urban areas has prompted increased attention to the role of meteorological conditions in PM_2.5 pollution. This study examines the spatiotemporal distribution of PM_2.5 concentrations and their relationship with meteorological factors in six major Chinese urban agglomerations from 2017 to 2020, using daily average data. Statistical and spatial analysis techniques are employed, alongside the construction of eight machine learning models for prediction purposes. The study also compares the feature importance of various meteorological factors impacting PM_2.5 concentrations. Results reveal significant regional differences in both average PM_2.5 levels and meteorological influences. The Multilayer Perceptron (MLP) model demonstrates the highest prediction accuracy for PM_2.5 concentrations. According to the MLP model’s feature importance identification, temperature is the most significant factor affecting PM_2.5 concentrations across all urban agglomerations, while wind speed and precipitation have the least impact. Contributions from air pressure and dew point temperature, however, vary among different urban agglomerations. This research considers the impact of urban agglomerations and meteorological conditions on PM_2.5 and also offers valuable artificial intelligence-based insights into the key meteorological factors influencing PM_2.5 concentrations in diverse regions, thereby informing the development of effective air pollution control policies. Full article

(This article belongs to the Special Issue Urban Microclimate: Thermal Comfort, Air Quality and Green Building as Drivers of Healthy Urban Design)

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23 pages, 5932 KiB

Open AccessArticle

Predicting the Impact of Change in Air Quality Patterns Due to COVID-19 Lockdown Policies in Multiple Urban Cities of Henan: A Deep Learning Approach

by Mughair Aslam Bhatti, Zhiyao Song, Uzair Aslam Bhatti and Naushad Ahmad

Atmosphere 2023, 14(5), 902; https://doi.org/10.3390/atmos14050902 - 22 May 2023

Cited by 4 | Viewed by 1931

Abstract

Several countries implemented prevention and control measures in response to the 2019 new coronavirus virus (COVID-19) pandemic. To study the impact of the lockdown due to COVID-19 on multiple cities, this study utilized data from 18 cities of Henan to understand the air [...] Read more.

Several countries implemented prevention and control measures in response to the 2019 new coronavirus virus (COVID-19) pandemic. To study the impact of the lockdown due to COVID-19 on multiple cities, this study utilized data from 18 cities of Henan to understand the air quality pattern change during COVID-19 from 2019 to 2021. It examined the temporal and spatial distribution impact. This study firstly utilized a deep learning bi-directional long-term short-term (Bi-LSTM) model to predict air quality patterns during 3 periods, i.e., COVID-A (before COVID-19, i.e., 2019), COVID-B (during COVID-19, i.e., 2020), COVID-C (after COVID-19 cases, i.e., 2021) and obtained the R² value of more than 72% average in each year and decreased MAE value, which was better than other studies’ deep learning methods. This study secondly focused on the change of pollutants and observed an increase in Air Quality Index by 10%, a decrease in PM_2.5 by 14%, PM₁₀ by 18%, NO₂ by 14%, and SO₂ by 16% during the COVID-B period. This study found an increase in O₃ by 31% during the COVID-C period and observed a significant decrease in pollutants during the COVID-C period (PM₁₀ by 42%, PM_2.5 by 97%, NO₂ by 89%, SO₂ by 36%, CO by 58%, O₃ by 31%). Lastly, the impact of lockdown policies was studied during the COVID-B period and the results showed that Henan achieved the Grade I standards of air quality standards after lockdown was implemented. Although there were many severe effects of the COVID-19 pandemic on human health and the global economy, lockdowns likely resulted in significant short-term health advantages owing to reduced air pollution and significantly improved ambient air quality. Following COVID-19, the government must take action to address the environmental problems that contributed to the deteriorating air quality. Full article

(This article belongs to the Section Air Quality)

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16 pages, 3709 KiB

Open AccessArticle

Remote Polar Boundary Layer Wind Profiling Using an All-Fiber Pulsed Coherent Doppler Lidar at Zhongshan Station, Antarctica

by Hui Li, Zhangjun Wang, Quanfeng Zhuang, Rui Wang, Wentao Huang, Chao Chen, Xianxin Li, Xiufen Wang, Boyang Xue, Yang Yu and Xin Pan

Atmosphere 2023, 14(5), 901; https://doi.org/10.3390/atmos14050901 - 22 May 2023

Cited by 2 | Viewed by 1770

Abstract

A compact all-fiber pulsed coherent Doppler lidar (PCDL) for boundary layer wind measurement was developed by the Institute of Oceanographic Instrumentation, Qilu University of Technology (Shandong Academy of Sciences). It has been deployed at Zhongshan Station (69.4° S, 76.4° E) during the 2020 [...] Read more.

A compact all-fiber pulsed coherent Doppler lidar (PCDL) for boundary layer wind measurement was developed by the Institute of Oceanographic Instrumentation, Qilu University of Technology (Shandong Academy of Sciences). It has been deployed at Zhongshan Station (69.4° S, 76.4° E) during the 2020 austral summer season by the 36th Chinese National Antarctic Research Expedition (CHINARE) and started routine observation in January 2020. This system, based on the 1550 nm all-fiber components, employs a 100 mm telescope with a long focal length of 632.6 mm to emit and collect laser pulses. It provides the ability to measure vertically resolved wind fields with a spatial resolution of 30 m and a temporal resolution of 1 min; the maximum detection range is up to 1.5 km in Antarctica. Wind speed and direction inversion methods were introduced subsequently. Preliminary measurement results of wind profiles indicate that this Doppler lidar can be operated successfully in Antarctica. The synchronous observations between the lidar, anemometer, and radiosondes at Zhongshan station are presented and have good consistency with each other. The comparison results between the lidar and anemometer indicate a root mean square deviation (RMSD) of 0.98 m s⁻¹ and 10.55° for wind speed and direction, respectively. The lidar continuous observations of wind profiles provide an opportunity to study the spatiotemporal variation of Antarctic wind with high resolutions, which is useful for further understanding of the atmosphere in Antarctic regions. Full article

(This article belongs to the Section Atmospheric Techniques, Instruments, and Modeling)

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18 pages, 1327 KiB

Open AccessEditor’s ChoiceArticle

Nexus between Social Vulnerability and Resilience to Agricultural Drought amongst South African Smallholder Livestock Households

by Yonas T. Bahta and Willem A. Lombard

Atmosphere 2023, 14(5), 900; https://doi.org/10.3390/atmos14050900 - 21 May 2023

Cited by 6 | Viewed by 1864

Abstract

Livestock farmers in Sub-Saharan Africa rely on rain-fed agriculture, which exposes them to the risks of agricultural drought. Agricultural drought has become a significant threat to the extreme mortality of livestock, thus negatively impacting social vulnerability and household resilience to agricultural drought and [...] Read more.

Livestock farmers in Sub-Saharan Africa rely on rain-fed agriculture, which exposes them to the risks of agricultural drought. Agricultural drought has become a significant threat to the extreme mortality of livestock, thus negatively impacting social vulnerability and household resilience to agricultural drought and extreme events. Researchers rarely empirically assess the connection between vulnerability and resilience, which are highly related concepts. By measuring and connecting vulnerability and resilience concepts closely related to disasters such as agricultural drought, this article makes a contribution to the body of disaster literature. The study aimed to empirically examine the relationship between smallholder livestock farming households’ social vulnerability and their resilience to agricultural drought. A survey of 217 smallholder livestock farmers was conducted. The Social Vulnerability Index (SVI), the Agricultural Drought Resilience Index (ADRI), and Pearson’s correlation coefficient were used for data analysis. A correlation was identified between resilience to agricultural drought and social vulnerability, indicating that smallholder livestock farmers are more susceptible to harm and lack the means to rebound effectively. Unsurprisingly, the majority of resource-poor smallholder livestock farmers (79%) lack safety nets during agricultural droughts. They are less resilient and more vulnerable households, leading them to social vulnerability. This study provides input/guidance to identify farming households with high social vulnerability and less resilience to threats and their capabilities of recouping and adopting after experiencing an agricultural drought. Additionally, looking at household resilience and social vulnerability to agricultural droughts could provide a way to pinpoint at-risk areas, assisting emergency planners in directing resources and intervention programs to those areas where assistance is most likely to be needed during disasters such as agricultural droughts. This implies that thorough policy intervention programs need to be tailored toward reducing damage or finding the path to recovery. Full article

(This article belongs to the Special Issue Agrometeorology, Agricultural Water Management and Impacts of Extreme Events)

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24 pages, 3887 KiB

Open AccessArticle

Time–Frequency Characteristics and SARIMA Forecasting of Atmospheric Water Vapor in East Asia

by Chaoli Tang, Ziyue Tong, Yuanyuan Wei, Xin Wu, Xiaomin Tian and Jie Yang

Atmosphere 2023, 14(5), 899; https://doi.org/10.3390/atmos14050899 - 21 May 2023

Cited by 1 | Viewed by 1881

Abstract

Given the increasing impact of extreme rainfall and flooding on human life, studying and predicting changes in atmospheric water vapor (AWV) becomes particularly important. This paper analyzes the moderate-resolution imaging spectroradiometer (MODIS) data of the East Asian region from January 2003 to February [...] Read more.

Given the increasing impact of extreme rainfall and flooding on human life, studying and predicting changes in atmospheric water vapor (AWV) becomes particularly important. This paper analyzes the moderate-resolution imaging spectroradiometer (MODIS) data of the East Asian region from January 2003 to February 2023. The AWV data are examined in the time and frequency domain using methods such as empirical orthogonal function (EOF), Mann–Kendall (MK) analysis, and others. Additionally, four prediction models are applied to forecast the monthly average AWV data for the next year. The accuracy of these models is evaluated using metrics such as mean square error (MSE), mean absolute error (MAE), root mean square error (RMSE), and coefficient of determination (R²). The findings reveal several key insights: (1) The East Asian region exhibits highly variable seasonal variability in AWV, with identified mutation points after the MK test. (2) Spatial analysis shows high AWV data in the southern coastal areas of China, Thailand, Myanmar, Nansha Islands, and other regions during winter, while the Qinghai-Tibet Plateau region experiences low AWV during summer. (3) The first mode obtained through EOF decomposition contributes over 60% of the variance. Analysis of this mode reveals an increasing trend in AWV data for regions such as the Indian peninsula, Mongolia, and central and northeastern China over the past nine years. Conversely, the Bay of Bengal, Spratly Islands, eastern coast, and certain areas display a decreasing trend. (4) Employing the ensemble empirical mode decomposition (EEMD), the study identifies AWV data as a non-stationary series with an overall decreasing trend from 2003 to 2022. The filtered AWV series undergoes fast Fourier transform (FFT), uncovering periodicities of 2.6 years, 5 years, and 19 years. (5) Among the four forecasting models compared, the seasonal autoregressive integrated moving average model (SARIMA) demonstrates superior performance with the smallest MSE of 0.00782, MAE of 0.06977, RMSE of 0.08843, and the largest R² value of 0.98454. These results clearly indicate that the SARIMA model provides the best fit. Therefore, the SARIMA forecasting model can be effectively utilized for forecasting AWV data, offering valuable insights for studying weather variability. Full article

(This article belongs to the Section Meteorology)

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17 pages, 7856 KiB

Open AccessArticle

The Impact of COVID-19 Lockdown on Ambient Air Quality in Shanghai, 2022

by Qi Zhang, Qian Zhang, Hui Liu and Mingyue Lu

Atmosphere 2023, 14(5), 898; https://doi.org/10.3390/atmos14050898 - 21 May 2023

Cited by 1 | Viewed by 1927

Abstract

The COVID-19 lockdown contributes to the improvement of air quality. Most previous studies have attributed this to the reduction of human activity while ignoring the meteorological changes, this may lead to an overestimation or underestimation of the impact of COVID-19 lockdown measures on [...] Read more.

The COVID-19 lockdown contributes to the improvement of air quality. Most previous studies have attributed this to the reduction of human activity while ignoring the meteorological changes, this may lead to an overestimation or underestimation of the impact of COVID-19 lockdown measures on air pollution levels. To investigate this issue, we propose an XGBoost-based model to predict the concentrations of PM_2.5 and PM₁₀ during the COVID-19 lockdown period in 2022, Shanghai, and thus explore the limits of anthropogenic emission on air pollution levels by comprehensively employing the meteorological factors and the concentrations of other air pollutants. Results demonstrate that actual observations of PM_2.5 and PM₁₀ during the COVID-19 lockdown period were reduced by 60.81% and 43.12% compared with the predicted values (regarded as the period without the lockdown measures). In addition, by comparing with the time series prediction results without considering meteorological factors, the actual observations of PM_2.5 and PM₁₀ during the lockdown period were reduced by 50.20% and 19.06%, respectively, against the predicted values during the non-lockdown period. The analysis results indicate that ignoring meteorological factors will underestimate the positive impact of COVID-19 lockdown measures on air quality. Full article

(This article belongs to the Section Air Pollution Control)

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14 pages, 3082 KiB

Open AccessArticle

Exploring the Relationship between Hydroclimate and Lake Area in Source Area of the Yellow River: Implications for the Paleoclimate Studies

by Shuying Bai, Jixi Gao, Yang Pu, Da Zhi and Jiaojiao Yao

Atmosphere 2023, 14(5), 897; https://doi.org/10.3390/atmos14050897 - 21 May 2023

Viewed by 1610

Abstract

The large tectonic lake is one of the most important water bodies in the source area of the Yellow River (SAYR), northeastern Qinghai-Tibet Plateau (QTP). It plays a key role in decelerating climatic change and regulating regional climate patterns. In this study, we [...] Read more.

The large tectonic lake is one of the most important water bodies in the source area of the Yellow River (SAYR), northeastern Qinghai-Tibet Plateau (QTP). It plays a key role in decelerating climatic change and regulating regional climate patterns. In this study, we used Landsat images (MSS, TM, ETM⁺ and OLI) of Lake Gyaring and Lake Ngoring (the Two Sisters Lakes), which are the two largest tectonic lakes in the SAYR, to determine annual lake area fluctuations from 1986 to 2020. The results show that lake area increases were generally consistent with a warming trend in the SAYR. The temperature signals were separated from the lake area changes by using a detrending analysis and found that the processed data are closely correlated with variations of precipitation and streamflow in the SAYR, and the previously reported paleoclimate records, which include the δ¹⁸O record from stalagmite, A/C (Artemisia/Chenopodiaceae) ratio from lake sediment and scPDSI (self-calibrating Palmer Drought Severity Index) from the tree ring on the northeastern margin of the QTP. The phase of relatively large lake areas typically coincides with a negative excursion in δ¹⁸O, a high A/C ratio, and elevated scPDSI values, while the opposite is true for smaller lake areas. It is suggested that the total area of the Two Sisters Lakes is closely associated with hydroclimatic conditions in the SAYR. Furthermore, an association of high TSI anomalies with the water area expansion of the Two Sisters Lakes is also observed, implying that solar activity is the key driving factor for the hydrologic variability in the SAYR on decadal timescales. The findings of our study highlight the validity of previous paleoclimate archives in the northeastern QTP and demonstrate the potential of using remote sensing techniques to investigate paleoclimate. Full article

(This article belongs to the Special Issue Paleoclimate Reconstruction)

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11 pages, 1805 KiB

Open AccessArticle

Brightness Temperature Characteristics of Short-Duration Heavy Rainfall in the Chengdu–Chongqing Railway Region in China

by Xinchao Liu, Yongren Chen, Jie Guo, Wenwen Song and Jia Dan

Atmosphere 2023, 14(5), 896; https://doi.org/10.3390/atmos14050896 - 20 May 2023

Cited by 1 | Viewed by 1619

Abstract

In this study, we analyzed the brightness temperature characteristics of short-duration heavy rainfall (SDHR) along the Chengdu–Chongqing Railway (CCR), an important corridor of economic and transportation activity in southwest China. Our findings could prove useful in the monitoring and advance warning of SDHR [...] Read more.

In this study, we analyzed the brightness temperature characteristics of short-duration heavy rainfall (SDHR) along the Chengdu–Chongqing Railway (CCR), an important corridor of economic and transportation activity in southwest China. Our findings could prove useful in the monitoring and advance warning of SDHR events: (1) SDHR predominantly occurred from July to August, with a peak frequency in July in the CCR area. In terms of diurnal variation, SDHR was mainly observed at night, particularly between 22:00–05:00 and 06:00–09:00 (local time), with a peak at 01:00; (2) The relationship between SDHR and equivalent blackbody temperature (TBB) further showed that the occurrence of SDHR was accompanied by TBB decreasing to its minimum value, after which it increased, and SDHR ceased. In cases where TBB approached its minimum value after 1 h but continued to decrease slightly, SDHR continued. When SDHR occurred, the majority of the TBB values were recorded in the range 190–230 K; within this range, values between 190 and 200 K were most frequently recorded. In general, lower TBB values are associated with more intense SDHR. Based on this finding, we used linear regression to establish an estimating equation for SDHR. Full article

(This article belongs to the Section Meteorology)

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15 pages, 2199 KiB

Open AccessArticle

Detection of Migrating and Non-Migrating Atmospheric Tides Derived from ERA5 Temperature Meteorological Analyses

by Philippe Keckhut, Thomas Lefebvre, Alain Hauchecorne, Mustapha Meftah and Sergey Khaykin

Atmosphere 2023, 14(5), 895; https://doi.org/10.3390/atmos14050895 - 20 May 2023

Viewed by 1764

Abstract

To better extract the tides represented in the European meteorological analysis ERA5, an analysis of the histograms of the diurnal and semi-diurnal modes as a function of longitudes was performed. This analysis revealed that modes with different characteristics appeared regionally along a single [...] Read more.

To better extract the tides represented in the European meteorological analysis ERA5, an analysis of the histograms of the diurnal and semi-diurnal modes as a function of longitudes was performed. This analysis revealed that modes with different characteristics appeared regionally along a single longitude. Retrieved migrating tides were compared with a tidal model showing global agreement below 60 km and twice the amplitude in meteorological analyses at mid-latitude. Non-migrating tidal modes have been identified along the tropical band. They logically appear above the convective zones, probably due to water vapor excess. Their characteristics are different from migrating components. This preliminary study has shown that it is necessary to develop additional observations allowing for more frequent sampling to retrieve migrating and non-migrating tides that can only be achieved with satellite constellations from space. Full article

(This article belongs to the Special Issue Waves and Variability in Terrestrial and Planetary Atmospheres)

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13 pages, 3525 KiB

Open AccessArticle

The Vertical Distributions of Aerosol Optical Characteristics Based on Lidar in Nanyang City from 2021 to 2022

by Miao Zhang, Si Guo, Yunuo Wang, Shiyong Chen, Jinhan Chen, Mingchun Chen and Muhammad Bilal

Atmosphere 2023, 14(5), 894; https://doi.org/10.3390/atmos14050894 - 20 May 2023

Cited by 1 | Viewed by 1606

Abstract

To investigate the vertical distribution of aerosol optical characteristics in Nanyang City, a ground-based dual-wavelength (532 nm and 355 nm) lidar system was developed for aerosol observation at the Nanyang Normal University Station (NYNU) from November 2021 to December 2022. Spatio-temporal dynamics information [...] Read more.

To investigate the vertical distribution of aerosol optical characteristics in Nanyang City, a ground-based dual-wavelength (532 nm and 355 nm) lidar system was developed for aerosol observation at the Nanyang Normal University Station (NYNU) from November 2021 to December 2022. Spatio-temporal dynamics information on vertical distributions of aerosol optical properties during polluted and non-polluted days was obtained. Aerosols were characterized by low altitudes (up to 2 km), thinner layers, and high-altitude (up to 4 km) thick layers during non-polluted and polluted days, with extinction coefficient values of ~0.03 km⁻¹ and ~0.2 km⁻¹, respectively. The mean values of the extinction coefficient at different altitudes (0~5 km) were all about ten-times higher on polluted days (0.04~0.19 km⁻¹) than on non-polluted days (0.004~0.02 km⁻¹). These results indicate that aerosol loadings and variations at different altitudes (0~5 km) were much higher and more prominent on polluted days than non-polluted days. The results show ten-times larger aerosol optical depth (AOD) values (0.4~0.6) on polluted days than on non-polluted days (0.05~0.08). At the same time, AOD values on both polluted and non-polluted days slightly decreased from 19:00 to 05:00, possibly due to dry depositions at nighttime. For the first time, this study established a ground-based lidar remote sensing system to investigate the vertical distribution of atmospheric aerosol optical characteristics in Henan Province. The experimental results can provide scientific dataset support for the local government to prevent and control air pollution. Full article

(This article belongs to the Special Issue Development of LIDAR Techniques for Atmospheric Remote Sensing)

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14 pages, 2104 KiB

Open AccessArticle

Comparison of Trace Element Deposition in Cupressus macrocarpa Leaves and Soils from a High-Pollution Area in the Puchuncaví Valley (Chile) Using a Biomonitoring Method

by Tamara Gorena, Franco Sandoval, Ximena Fadic and Francisco Cereceda-Balic

Atmosphere 2023, 14(5), 893; https://doi.org/10.3390/atmos14050893 - 20 May 2023

Viewed by 1508

Abstract

Located in the Puchuncaví Valley (PV) in central Chile is one of the most important and oldest industrial complexes (ICs) in the country. The PV is affected by anthropogenic emissions from the IC where the most important industry is a copper smelter and [...] Read more.

Located in the Puchuncaví Valley (PV) in central Chile is one of the most important and oldest industrial complexes (ICs) in the country. The PV is affected by anthropogenic emissions from the IC where the most important industry is a copper smelter and refinery. In this context, this study assessed the profile, concentration, and enrichment factors of the trace elements, both in the soil and in Cupressus macrocarpa leaves from this high-pollution-load area. The soil and leaf samples were taken from five selected sites, located between 0.8 and 15 km away from the IC. A total of 24 elements were analyzed by ICP-MS and examined by enrichment factor (EF), and PCA source analysis. Leaf concentrations of Ba, Ca, Cd, Cu, K, and Sr showed statistically significant differences between sampling sites (p-value < 0.05). In soil, element concentrations of Al, As, Ba, Cr, Cu, K, Li Mg, Mn, Na, Ni, Pb, and Ti showed statistically significant differences between sampling sites (p-value < 0.05). The source analysis of EFs in the samples of both soil and leaves detected three and four factors, respectively, related mainly to the industrial complex’s copper smelter and refinery, coal-fired power plants, and geogenic sources. According to the PCA, the leaf EFs of anthropogenic elements from copper smelting showed that La Greda (LG, site closest to the IC) was significantly enriched in the elements Cu, Zn, As, Mo, and Pb, while the EF in the soil from LG showed high enrichment in Cu and significant enrichment in Pb. Full article

(This article belongs to the Special Issue Biomonitoring - an Effective Tool for Air Pollution Assessment)

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16 pages, 1743 KiB

Open AccessArticle

Analysis of Data on Air Pollutants in the City by Machine-Intelligent Methods Considering Climatic and Geographical Features

by Nurlan Temirbekov, Syrym Kasenov, Galym Berkinbayev, Almas Temirbekov, Dinara Tamabay and Marzhan Temirbekova

Atmosphere 2023, 14(5), 892; https://doi.org/10.3390/atmos14050892 - 20 May 2023

Cited by 11 | Viewed by 1704

Abstract

In the world, air pollution ranks among the primary sources of risk to human health and the environment. To assess the risk of impact of atmospheric pollution, a comprehensive research cycle was designed to develop a unified ecosystem for monitoring air pollution in [...] Read more.

In the world, air pollution ranks among the primary sources of risk to human health and the environment. To assess the risk of impact of atmospheric pollution, a comprehensive research cycle was designed to develop a unified ecosystem for monitoring air pollution in industrial cities in Kazakhstan. Research involves analyzing data for the winter period from 20 automated monitoring stations (AMS) located in Almaty and conducting chemical-analytical studies of snowmelt water samples from 22 points to identify such pollutants as fine particulate matters, petroleum products, and heavy metals. Research includes a bio-experiment involving the cultivation of watercress on samples of melt water collected from snow cover to examine the effects of pollution on plants. In the framework of this research, we determined API based on data obtained from AMS. In order to determine the influence of atmospheric pollution on the environment, a multiple regression model was developed using machine learning algorithms to reveal the relationship between the bio-experiment data and data on pollutants of chemical-analytical research. The results revealed a wide spread of pollutants in the snow cover of the urban environment, a correlation between pollutants in the snow cover and the airspace of the city, and their negative impact on flora. Full article

(This article belongs to the Section Atmospheric Techniques, Instruments, and Modeling)

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16 pages, 4058 KiB

Open AccessArticle

A Two-Stage Hybrid Model for Determining the Scopes and Priorities of Joint Air Pollution Control

by Pingle Yang, Hongru Yi, Laijun Zhao and Luping Chen

Atmosphere 2023, 14(5), 891; https://doi.org/10.3390/atmos14050891 - 19 May 2023

Viewed by 1385

Abstract

Due to the spillover nature of air pollution, the territorial separate governance mode is ineffective in combating pollution, making Joint Prevention and Control of Air Pollution (JPCAP) among multiple regions the only viable option. However, determining the appropriate scopes and priorities for JPCAP [...] Read more.

Due to the spillover nature of air pollution, the territorial separate governance mode is ineffective in combating pollution, making Joint Prevention and Control of Air Pollution (JPCAP) among multiple regions the only viable option. However, determining the appropriate scopes and priorities for JPCAP is known to be a challenging and significant issue. To address this, we propose a new two-stage hybrid model. In the first stage, making use of long-term, wide area monitoring data provided by the air pollution monitoring network, we propose a new method for subdividing large regions into sub-regions by using data mining techniques. In the second stage, we propose a comprehensive decision-making framework to evaluate the priorities of JPCAP sub-regions from three different perspectives, namely, the impact of a sub-region on the pollution level of the entire target region, as well as the urgency and elasticity of sub-regional air pollution control. A case study is conducted on 27 cities of the Yangtze River Delta region of China. The case study demonstrates the validity and practicality of the proposed two-stage hybrid model. This work provides a viable tool for the effective implementation of air pollution control in China and other regions of the world. Full article

(This article belongs to the Special Issue Air Pollution Control in China: Progress, Challenges, and Perspectives (2nd Edition))

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13 pages, 929 KiB

Open AccessEditor’s ChoiceArticle

Investigation of Dynamical Complexity in Swarm-Derived Geomagnetic Activity Indices Using Information Theory

by Georgios Balasis, Adamantia Zoe Boutsi, Constantinos Papadimitriou, Stelios M. Potirakis, Vasilis Pitsis, Ioannis A. Daglis, Anastasios Anastasiadis and Omiros Giannakis

Atmosphere 2023, 14(5), 890; https://doi.org/10.3390/atmos14050890 - 19 May 2023

Cited by 1 | Viewed by 2021

Abstract

In 2023, the ESA’s Swarm constellation mission celebrates 10 years in orbit, offering one of the best ever surveys of the topside ionosphere. Among its achievements, it has been recently demonstrated that Swarm data can be used to derive space-based geomagnetic activity indices, [...] Read more.

In 2023, the ESA’s Swarm constellation mission celebrates 10 years in orbit, offering one of the best ever surveys of the topside ionosphere. Among its achievements, it has been recently demonstrated that Swarm data can be used to derive space-based geomagnetic activity indices, similar to the standard ground-based geomagnetic indices monitoring magnetic storm and magnetospheric substorm activity. Recently, many novel concepts originating in time series analysis based on information theory have been developed, partly motivated by specific research questions linked to various domains of geosciences, including space physics. Here, we apply information theory approaches (i.e., Hurst exponent and a variety of entropy measures) to analyze the Swarm-derived magnetic indices from 2015, a year that included three out of the four most intense magnetic storm events of the previous solar cycle, including the strongest storm of solar cycle 24. We show the applicability of information theory to study the dynamical complexity of the upper atmosphere, through highlighting the temporal transition from the quiet-time to the storm-time magnetosphere, which may prove significant for space weather studies. Our results suggest that the spaceborne indices have the capacity to capture the same dynamics and behaviors, with regards to their informational content, as traditionally used ground-based ones. Full article

(This article belongs to the Special Issue The Effect of Helio-Geomagnetic Activity in the Geo-Environment and by Extension to Human Health)

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13 pages, 6127 KiB

Open AccessArticle

Occurrence Characteristics of VHF Scintillation and Equatorial Spread F over Kwajalein during Moderate Solar Activity in 2012

by Chao-Song Huang

Atmosphere 2023, 14(5), 889; https://doi.org/10.3390/atmos14050889 - 19 May 2023

Viewed by 1247

Abstract

The occurrence probability of equatorial plasma bubbles and the associated spread F (ESF) irregularities have been derived from ground-based and space-borne measurements. In general, ESF occurrence depends on season and longitude and is high in equinoctial months and low around June solstice. In [...] Read more.

The occurrence probability of equatorial plasma bubbles and the associated spread F (ESF) irregularities have been derived from ground-based and space-borne measurements. In general, ESF occurrence depends on season and longitude and is high in equinoctial months and low around June solstice. In the West Pacific sector, previous statistical results show that the ESF occurrence probability increases gradually and continuously from March to August. In this study, we use trans-ionospheric VHF data received at Kwajalein Atoll in 2012 to derive the occurrence characteristics of scintillation. It is found that the occurrence probability of strong scintillation had two maxima in June and September and a minimum in July in the evening and midnight sector but only one maximum in June in the post-midnight sector. The monthly variations of scintillation occurrence at Kwajalein are different from almost all previous studies on ESF and scintillation at or near this longitude. To identify the cause for the June peak and the July minimum of scintillation, the ion density and velocity data measured by the Communication/Navigation Outage Forecasting System (C/NOFS) satellite in 2011–2012 are used to derive the ESF occurrence and the post-sunset vertical ion drift near Kwajalein. The ESF occurrence probability and the ion drift measured by the C/NOFS satellite showed two maxima in May/June and August/September and a minimum in July, verifying that the June peak and the July minimum of the VHF scintillation are realistic and caused by the similar variations in the ionospheric ion drift and density. Full article

(This article belongs to the Special Issue Equatorial-Low-Latitude Plasma Bubble Dynamics: Recent Observations and Simulations)

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15 pages, 3124 KiB

Open AccessArticle

Study of Landfalling Typhoon Potential Maximum Gale Forecasting in South China

by Zhizhong Su, Lifang Li, Fumin Ren, Jing Zhu, Chunxia Liu, Qilin Wan, Qiongbo Sun and Li Jia

Atmosphere 2023, 14(5), 888; https://doi.org/10.3390/atmos14050888 - 19 May 2023

Cited by 1 | Viewed by 1674

Abstract

Based on historical tropical cyclone (TC) tracking data and wind data from observation stations, four comparison experiments were designed that considered TC translation speed similarity and five new ensemble schemes in an improved Dynamical-Statistical-Analog Ensemble Forecast (DSAEF) model for Landfalling Typhoon Gale (LTG), [...] Read more.

Based on historical tropical cyclone (TC) tracking data and wind data from observation stations, four comparison experiments were designed that considered TC translation speed similarity and five new ensemble schemes in an improved Dynamical-Statistical-Analog Ensemble Forecast (DSAEF) model for Landfalling Typhoon Gale (LTG), which was tested in terms of forecast capability in South China. The results showed that the improved DSAEF_LTG model with the incorporation of TC translation speed and a new ensemble scheme could improve the forecast threat score (TS) and reduce both the false alarm ratio and the missing ratio in comparison with corresponding values attained before the improvement. The TS of the new ensemble scheme model (DLTG_3) was 0.34 at threshold above Beaufort Scale 7, which was 31% better than that of the unimproved model (DLTG_1). At a threshold above Beaufort Scale 10, the TS of DLTG_3 indicated even greater improvement, reaching 0.25, i.e., 127% higher than that of DLTG_1. The results of the experiments illustrated the marked improvement achievable when using the new ensemble scheme. The reasons for the differences in the DSAEF_LTG model forecasts before and after the introduction of TC translation speed and the new ensemble scheme were analyzed for the cases of Typhoon Haima and Typhoon Hato. Full article

(This article belongs to the Special Issue Forecasting and Modeling of Tropical Cyclones and Their Induced Wind and Precipitation)

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12 pages, 2372 KiB

Open AccessBrief Report

The Air and Viruses We Breathe: Assessing the Effect the PM_2.5 Air Pollutant Has on the Burden of COVID-19

by Sherrie L. Kelly, Andrew J. Shattock, Martina S. Ragettli, Danielle Vienneau, Ana M. Vicedo-Cabrera and Kees de Hoogh

Atmosphere 2023, 14(5), 887; https://doi.org/10.3390/atmos14050887 - 19 May 2023

Viewed by 2447

Abstract

Evidence suggests an association between air pollutant exposure and worse outcomes for respiratory viral diseases, like COVID-19. However, does breathing polluted air over many years affect the susceptibility to SARS-CoV-2 infection or severity of COVID-19 disease, and how intense are these effects? As [...] Read more.

Evidence suggests an association between air pollutant exposure and worse outcomes for respiratory viral diseases, like COVID-19. However, does breathing polluted air over many years affect the susceptibility to SARS-CoV-2 infection or severity of COVID-19 disease, and how intense are these effects? As climate change intensifies, air pollutant levels may rise, which might further affect the burden of respiratory viral diseases. We assessed the effect of increasing exposure to PM_2.5 (particulate matter ≤ 2.5 microns in diameter) on SARS-CoV-2 susceptibility or COVID-19 severity and projected the impact on infections and hospitalisations over two years. Simulations in a hypothetical, representative population show that if exposure affects severity, then hospital admissions are projected to increase by 5–10% for a one-unit exposure increase. However, if exposure affects susceptibility, then infections would increase with the potential for onward transmission and hospital admissions could increase by over 60%. Implications of this study highlight the importance of considering this potential additional health and health system burden as part of strategic planning to mitigate and respond to changing air pollution levels. It is also important to better understand at which point PM_2.5 exposure affects SARS-CoV-2 infection through to COVID-19 disease progression, to enable improved protection and better support of those most vulnerable. Full article

(This article belongs to the Special Issue Outdoor Air Pollution and Human Health (2nd Edition))

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14 pages, 2779 KiB

Open AccessArticle

System Predictability Assessed by Low Wavenumber Fourier Components and Analogue Pair Progression of Geopotential Height

by Marshall Liddle, Hans Moosmüller and John Lewis

Atmosphere 2023, 14(5), 886; https://doi.org/10.3390/atmos14050886 - 18 May 2023

Viewed by 1146

Abstract

Following Lorenz’s work using analogue pairs for establishing 10-to-14-day predictability limits for synoptic weather regimes, predictability limits for the Rex block, the long-wave wintertime ridge over the eastern Pacific Ocean and the western United States, have been estimated. This was accomplished by using [...] Read more.

Following Lorenz’s work using analogue pairs for establishing 10-to-14-day predictability limits for synoptic weather regimes, predictability limits for the Rex block, the long-wave wintertime ridge over the eastern Pacific Ocean and the western United States, have been estimated. This was accomplished by using mid-latitude geopotential height reanalysis data over a period of 38 years, 1979–2016, and associated 90-day winters (DJF). The metric used to define analogue pairs is the RMS difference assessed for the hemispheric 850, 500, and 200 hPa geopotential height fields. The resultant set of analogue pairs was used to estimate predictability with respect to both a single latitude circle (40° N) that passes through the Rex Block and for a multi-latitude swath (20–80° N). Our methods showed a range of results, by choice of Fourier component wavenumbers 2 through 8. These results indicate system predictability for low wavenumber components to exceed the 10–14-day limit imposed by Lorenz’ results. The results to 21 days, the maximum predictability limit value allowed by our method, do not preclude the possibility of a greater range of system predictability past 21 days. The unique aspect of this work is determination of predictability limits as a function of geopotential wave structure found through Fourier decomposition. Full article

(This article belongs to the Special Issue Statistical Methods in Atmospheric Research)

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15 pages, 2323 KiB

Open AccessArticle

Thermal Hazards Evaluation Based on Weight of Evidence Method in the Resource Area of Datong River in Qinghai-Tibetan Plateau

by Shengting Wang, Yu Sheng, Shuming Jia and Yongzhong Ren

Atmosphere 2023, 14(5), 885; https://doi.org/10.3390/atmos14050885 - 18 May 2023

Viewed by 1149

Abstract

With global warming and increasingly frequent human activities in permafrost regions, it is of great significance to accurately and scientifically evaluate the probability and scope of thermal hazards in permafrost regions. Based on remote sensing image interpretation and field survey, the weight of [...] Read more.

With global warming and increasingly frequent human activities in permafrost regions, it is of great significance to accurately and scientifically evaluate the probability and scope of thermal hazards in permafrost regions. Based on remote sensing image interpretation and field survey, the weight of evidence method (WoEM) was used to comprehensively evaluate the risk of thermal hazards in the source area of the Datong River. There were 10 factors, such as ground ice, mean annual ground temperature, mean annual air temperature, and ground soil type etc., selected in the WoEM. The results showed that the thermal hazard occurrences were closely influenced by ground ice, mean annual ground temperature, ground soil type, etc. The thermal hazards mainly occurred in the unstable permafrost with MAGT of –0.5 to –1.5 °C, accounting for 54.72% of the thermal hazards. The distribution area of thermal hazards in ground ice Level I and II accounts for 66.42%. Thermal hazards mainly occur in the soil types of bog soil and sapropel bog soil, accounting for 41.24% and 29.62% of the total thermal hazards area, respectively. Based on the influence factors and WoEM of thermal hazards occurrence, the probability map of thermal hazards occurrence in the source area was obtained. Additionally, the characteristics of the region with a high probability of thermal hazards occurrence and their causes were also comprehensively analyzed. Full article

(This article belongs to the Special Issue Interactions of Atmosphere and Permafrost)

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22 pages, 30686 KiB

Open AccessArticle

Dynamical Analyses of a Supercell Tornado in Eastern China Based on a Real-Data Simulation

by Shiqi Wang and Jinzhong Min

Atmosphere 2023, 14(5), 884; https://doi.org/10.3390/atmos14050884 - 18 May 2023

Viewed by 1833

Abstract

Tornadoes are extremely destructive natural disasters, and East China has become a high-incidence area for tornadoes in China in recent years. On 7 July 2013, an EF2-intensity tornado occurred in Gaoyou County, Jiangsu Province in eastern China, within a supercell storm near a [...] Read more.

Tornadoes are extremely destructive natural disasters, and East China has become a high-incidence area for tornadoes in China in recent years. On 7 July 2013, an EF2-intensity tornado occurred in Gaoyou County, Jiangsu Province in eastern China, within a supercell storm near a Meiyu frontal system. To investigate the dynamical process of the tornado, a numerical simulation was performed using four one-way nested grids within the Advanced Regional Prediction System (ARPS). Data from a nearby operational S-band Doppler radar are assimilated using a 4D ensemble Kalman filter (4DEnKF) at 5 min intervals. Forecasts are run with a nested 50 m grid, capturing the tornado embedded within the supercell storm with a reasonable agreement with observations. The tornadogenesis processes within the simulation results are analyzed in detail, including the three-dimensional evolution of the tornado vortex. It is found that a cold surge within the rear flank downdraft region plays a key role in instigating tornadogenesis when the leading edge of the cold surge approaches a near-ground convergence center located underneath the main updraft, and the enhancement of the convergence center caused by the descending of the low-level mesocyclone is the direct cause of the rapid increase in tornado vorticity. Backward trajectories are calculated based on model output, and the origins of the parcels feeding the intensifying tornado vortex are identified. It is found that parcels from the mid-level of the rear flank downdraft region follow the cold surge, descending to the ground under the influence of the downdraft in the cold surge, and then entering the convergence center, merging into the core of the tornado and being lifted up. Vertical profiles of the mass and vorticity fluxes into the core of the tornado vortex are examined, and it is found that the near-ground airflow contributes significantly to the growth of the tornado vorticity, with the contribution increasing as it gets closer to the ground. Full article

(This article belongs to the Special Issue Data Assimilation for Predicting Hurricane, Typhoon and Storm)

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20 pages, 9745 KiB

Open AccessArticle

Two Case Studies of the Northwestern Argentinean Low: With and without a Coupled Transient Trough

by Josefina M. Arraut, Maurício R. Rocha, Enio P. Souza and Júlia Amanda Nanini

Atmosphere 2023, 14(5), 883; https://doi.org/10.3390/atmos14050883 - 18 May 2023

Viewed by 1157

Abstract

The Northwestern Argentinean Low (NAL) intensifies the zonal component of the geopotential gradient to its east, intensifying the meridional wind and moisture flow from the tropics to the subtropics contibuting importantly to the South American Low-Level Jet and the Chaco Jet. This study [...] Read more.

The Northwestern Argentinean Low (NAL) intensifies the zonal component of the geopotential gradient to its east, intensifying the meridional wind and moisture flow from the tropics to the subtropics contibuting importantly to the South American Low-Level Jet and the Chaco Jet. This study compares two situations where the NAL is present in the continent’s subtropics: one where it is coupled with an extratropical transient trough to its south and another without this coupling. The coupled case, called the front case, is stronger in two ways: it is warmer and shows lower geopotential at the center of the NAL. It also shows much stronger moisture transport. Both cases show a similar trait in that moisture transport and the zonal component of the geopotential gradient east of the NAL peak in the coolest hours. The geopotential at the center of the no-front case remains roughly constant throughout the event. For the front case, it attains its minimum value in the six hours preceding the northeastward advance of the transient trough. These results suggest that there are different mechanisms acting at the center of the NAL and at its eastern branch, as well as in the front and no-front cases. Full article

(This article belongs to the Special Issue Extreme Weather Events and Atmospheric Circulation)

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15 pages, 14886 KiB

Open AccessArticle

Research on Promotion Pathways for Zero-Emission Medium- and Heavy-Duty Trucks: A Case Study of Hainan Island

by Chunxiao Hao, Yunshan Ge, Jindong Liang, Zhuoshi He, Zhihui Huang and Guangyu Dou

Atmosphere 2023, 14(5), 882; https://doi.org/10.3390/atmos14050882 - 18 May 2023

Cited by 1 | Viewed by 1542

Abstract

Promoting the use of zero-emission vehicles is an important measure for reducing pollutant and carbon dioxide emissions from medium- and heavy-duty trucks (MHDTs). This study took Hainan Island as an example. Based on big data such as industrial layout and traffic flow, it [...] Read more.

Promoting the use of zero-emission vehicles is an important measure for reducing pollutant and carbon dioxide emissions from medium- and heavy-duty trucks (MHDTs). This study took Hainan Island as an example. Based on big data such as industrial layout and traffic flow, it clarified that the main channels of freight transportation on Hainan Island are concentrated in the northern region, including the surrounding areas of Haikou; the important ports of Haikou, Yangpu, and Basuo; and Chengmai and Tunchang counties. Furthermore, pathways for the promotion of zero-emission MHDTs are proposed, which can reduce exhaust emissions by 1549 tons of NOx, 62 tons of particulate matter (PM), and 3.60 million tons of CO₂ by 2030. Compared with the vehicle type categorization plan, the spatial layout plan can achieve higher emission reduction benefits in the medium term (2025). In addition, in conjunction with existing policies and planning requirements, this study also puts forward policy suggestions for the promotion of zero-emission MHDTs. Full article

(This article belongs to the Special Issue Recent Advances in Mobile Source Emissions)

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13 pages, 22229 KiB

Open AccessArticle

Potential Vorticity Generation in Breaking Gravity Waves

by Michael L. Waite and Nicholas Richardson

Atmosphere 2023, 14(5), 881; https://doi.org/10.3390/atmos14050881 - 18 May 2023

Cited by 1 | Viewed by 1750

Abstract

Potential vorticity (PV) is an important quantity in stratified flows because it is conserved following the flow in the absence of forcing and viscous and diffusive effects. However, as shown by previous work for unstratified turbulence, viscosity and diffusion, when present, are not [...] Read more.

Potential vorticity (PV) is an important quantity in stratified flows because it is conserved following the flow in the absence of forcing and viscous and diffusive effects. However, as shown by previous work for unstratified turbulence, viscosity and diffusion, when present, are not purely dissipative and can create potential vorticity even when none is present initially. In this work, we use direct numerical simulations to investigate the viscous and diffusive generation of potential vorticity and potential enstrophy (integrated square PV) in stratified turbulence. Simulations are initialized with a two-dimensional standing internal gravity wave, which has no potential vorticity apart from some low-level random noise; as a result, all potential vorticity and enstrophy comes from viscous and diffusive effects. Significant potential enstrophy is found when the standing wave breaks, and the maximum potential enstrophy increases with increasing Reynolds number. The mechanism for the initial PV generation is spanwise diffusion of buoyancy perturbations, which grow as the standing wave three-dimensionalizes, into the direction of spanwise vorticity. The viscous and diffusive terms responsible are small-scale and are sensitive to under-resolution, so high resolution is required to obtain robust results. Full article

(This article belongs to the Special Issue Turbulence from Earth to Planets, Stars and Galaxies—Commemorative Issue Dedicated to the Memory of Jackson Rea Herring)

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30 pages, 7900 KiB

Open AccessArticle

Chemical Characterization and Source Apportionment of PM₁₀ Using Receptor Models over the Himalayan Region of India

by Nikki Choudhary, Akansha Rai, Jagdish Chandra Kuniyal, Priyanka Srivastava, Renu Lata, Monami Dutta, Abhinandan Ghosh, Supriya Dey, Sayantan Sarkar, Sakshi Gupta, Sheetal Chaudhary, Isha Thakur, Archana Bawari, Manish Naja, Narayanasamy Vijayan, Abhijit Chatterjee, Tuhin Kumar Mandal, Sudhir Kumar Sharma and Ravindra Kumar Kotnala

Atmosphere 2023, 14(5), 880; https://doi.org/10.3390/atmos14050880 - 17 May 2023

Cited by 11 | Viewed by 2447

Abstract

This study presents the source apportionment of coarse-mode particulate matter (PM₁₀) extracted by 3 receptor models (PCA/APCS, UNMIX, and PMF) at semi-urban sites of the Indian Himalayan region (IHR) during August 2018–December 2019. In this study, water-soluble inorganic ionic species (WSIIS), [...] Read more.

This study presents the source apportionment of coarse-mode particulate matter (PM₁₀) extracted by 3 receptor models (PCA/APCS, UNMIX, and PMF) at semi-urban sites of the Indian Himalayan region (IHR) during August 2018–December 2019. In this study, water-soluble inorganic ionic species (WSIIS), water-soluble organic carbon (WSOC), carbon fractions (organic carbon (OC) and elemental carbon (EC)), and trace elements of PM₁₀ were analyzed over the IHR. Nainital (62 ± 39 µg m⁻³) had the highest annual average mass concentration of PM₁₀ (average ± standard deviation at 1 σ), followed by Mohal Kullu (58 ± 32 µg m⁻³) and Darjeeling (54 ± 18 µg m⁻³). The annual total ∑WSIIS concentration order was as follows: Darjeeling (14.02 ± 10.01 µg m⁻³) > Mohal-Kullu (13.75 ± 10.21 µg m⁻³) > Nainital (10.20 ± 6.30 µg m⁻³), contributing to 15–30% of the PM₁₀ mass. The dominant secondary ions (NH₄⁺, SO₄²⁻, and NO₃⁻) suggest that the study sites were strongly influenced by anthropogenic sources from regional and long-range transport. Principal component analysis (PCA) with an absolute principal component score (APCS), UNMIX, and Positive Matrix Factorization (PMF) were used for source identification of PM₁₀ at the study sites of the IHR. All three models showed relatively similar results of source profiles for all study sites except their source number and percentage contribution. Overall, soil dust (SD), secondary aerosols (SAs), combustion (biomass burning (BB) + fossil fuel combustion (FFC): BB+FFC), and vehicular emissions (VEs) are the major sources of PM₁₀ identified by these models at all study sites. Air mass backward trajectories illustrated that PM₁₀, mainly attributed to dust-related aerosols, was transported from the Thar Desert, Indo-Gangetic Plain (IGP), and northwestern region of India (i.e., Punjab and Haryana) and Afghanistan to the IHR. Transported agricultural or residual burning plumes from the IGP and nearby areas significantly contribute to the concentration of carbonaceous aerosols (CAs) at study sites. Full article

(This article belongs to the Section Aerosols)

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16 pages, 2051 KiB

Open AccessEditor’s ChoiceArticle

Future Ship Emission Scenarios with a Focus on Ammonia Fuel

by Daniel A. Schwarzkopf, Ronny Petrik, Josefine Hahn, Leonidas Ntziachristos, Volker Matthias and Markus Quante

Atmosphere 2023, 14(5), 879; https://doi.org/10.3390/atmos14050879 - 17 May 2023

Cited by 5 | Viewed by 3706

Abstract

Current efforts by the International Maritime Organization (IMO) to decarbonize the shipping sector have gained momentum, although the exact path to achieve this goal is currently unclear. However, it can be safely assumed that alternative cleaner and zero-carbon fuels will be key components [...] Read more.

Current efforts by the International Maritime Organization (IMO) to decarbonize the shipping sector have gained momentum, although the exact path to achieve this goal is currently unclear. However, it can be safely assumed that alternative cleaner and zero-carbon fuels will be key components in the strategy. In this work, three ship emission scenarios for 2025, 2040, and 2050 were developed that cover the area of the North and Baltic Seas. They aim at a fundamental transition in the usage of marine fuels towards ammonia as the mainly used fuel in 2050, via an intermediate step in 2040 with liquefied natural gas as the main fuel. Additionally, expected trends and developments for the shipping sector were implemented, i.e., a fleet growth by vessel size and number. Efficiency improvements were included that are in accordance with the Energy Efficiency Design Index of the IMO. The scenarios were created using a novel method based on modifications to a virtual shipping fleet. The vessels in this fleet were subject to decommission and renewal cycles that adapt them to the scenario’s target year. Emissions for this renewed shipping fleet were calculated with the Modular Ship Emission Modeling System (MoSES). With respect to ammonia engine technology, two cases were considered. The first case deals with compression ignition engines and marine gas oil as pilot fuel, while the second case treats spark ignition engines and hydrogen as the pilot fuel. The first case is considered more feasible until 2050. Reductions with the first case in 2050 compared to 2015 were 40% for

{CO}_{2}

emissions. However,

{CO}_{2}

equivalents were only reduced by 22%, with the difference mainly resulting from increased

N_{2} O

emissions.

{NO}_{X}

emissions were reduced by 39%, and different

PM

components and

{SO}_{2}

were between 73% and 84% for the same target year. The estimated

{NH}_{3}

slip from ammonia-fueled ships in the North and Baltic Seas was calculated to be 930

Gg

in 2050. For the second ammonia engine technology that is considered more advanced, emission reductions were generally stronger and ammonia emissions smaller. Full article

(This article belongs to the Special Issue Atmospheric Shipping Emissions and Their Environmental Impacts)

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21 pages, 2327 KiB

Open AccessReview

Review on Source Profiles of Volatile Organic Compounds (VOCs) in Typical Industries in China

by Shuangshuang Wang, Jie Zhang, Yan Zhang, Liwei Wang, Zhongxue Sun and Hailing Wang

Atmosphere 2023, 14(5), 878; https://doi.org/10.3390/atmos14050878 - 17 May 2023

Cited by 9 | Viewed by 3449

Abstract

The source profile of volatile organic compounds (VOCs) is essential for establishing reactivity- and toxicity-based emission inventories and developing effective air pollution control strategies. In this paper, the establishment of VOC source profiles and the VOC emission characteristics are reviewed in the petrochemical, [...] Read more.

The source profile of volatile organic compounds (VOCs) is essential for establishing reactivity- and toxicity-based emission inventories and developing effective air pollution control strategies. In this paper, the establishment of VOC source profiles and the VOC emission characteristics are reviewed in the petrochemical, solvent use, and chemical industries, and the most up-to-date profiles of the three industries in China are compiled via necessary adjustment and reconstruction of the test data from the literature. Alkanes dominated and OVOCs were often neglected in the overall petrochemical industry and refined processes. They accounted for 60.6% and 3.2% in the merged profiles. Aromatics and OVOCs dominated in the industrial solvent use industry. OVOCs were the most prevalent in the printing and dyeing industries, furniture manufacturing industries, and automobile coating process, whereas aromatics were major contributors of the total VOCs in metal surface coating, shipping coating, and other surface coating industries in the merged profiles. A wide range of products and limited profile studies were obtained in chemical industry, and the compositions of VOCs varied significantly in the production of 30 products in the merged profile. The future research directions of VOC source profiles are discussed, mainly focusing on the sampling, establishment, and evaluation of VOC profiles. Full article

(This article belongs to the Section Air Pollution Control)

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22 pages, 14633 KiB

Open AccessArticle

Identification Method of Source Term Parameters of Nuclear Explosion Based on GA and PSO for Lagrange-Gaussian Puff Model

by Yang Zheng, Yuyang Wang, Longteng Wang, Xiaolei Chen, Lingzhong Huang, Wei Liu, Xiaoqiang Li, Ming Yang, Peng Li, Shanyi Jiang, Hao Yin, Xinliang Pang and Yunhui Wu

Atmosphere 2023, 14(5), 877; https://doi.org/10.3390/atmos14050877 - 17 May 2023

Cited by 1 | Viewed by 1553

Abstract

Many well-established models exist for predicting the dispersion of radioactive particles that will be generated in the surrounding environment after a nuclear weapon explosion. However, without exception, almost all models rely on accurate source term parameters, such as DELFIC, DNAF-1, and so on. [...] Read more.

Many well-established models exist for predicting the dispersion of radioactive particles that will be generated in the surrounding environment after a nuclear weapon explosion. However, without exception, almost all models rely on accurate source term parameters, such as DELFIC, DNAF-1, and so on. Unlike nuclear experiments, accurate source term parameters are often not available once a nuclear weapon is used in a real nuclear strike. To address the problems of unclear source term parameters and meteorological conditions during nuclear weapon explosions and the complexity of the identification process, this article proposes a nuclear weapon source term parameter identification method based on a genetic algorithm (GA) and a particle swarm optimization algorithm (PSO) by combining real-time monitoring data. The results show that both the PSO and the GA are able to identify the source term parameters satisfactorily after optimization, and the prediction accuracy of their main source term parameters is above 98%. When the maximum number of iterations and population size of the PSO and GA were the same, the running time and optimization accuracy of the PSO were better than those of the GA. This study enriches the theory and method of radioactive particle dispersion prediction after a nuclear weapon explosion and is of great significance to the study of environmental radioactive particles. Full article

(This article belongs to the Special Issue Atmospheric Dispersion of Pollutants: From Regulatory to Emergency Applications)

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18 pages, 1826 KiB

Open AccessArticle

Comprehensive Analysis and Greenhouse Gas Reduction Assessment of the First Large-Scale Biogas Generation Plant in West Africa

by Haoran Chen, Qian Xu, Shikun Cheng, Ting Wu, Tong Boitin, Sunil Prasad Lohani, Heinz-Peter Mang, Zifu Li and Xuemei Wang

Atmosphere 2023, 14(5), 876; https://doi.org/10.3390/atmos14050876 - 17 May 2023

Cited by 4 | Viewed by 2663

Abstract

More than 500 million people will be added to Africa’s cities by 2040, marking the largest urbanization in history. However, nonrenewable fossil energy sources are inadequate to meet Africa’s energy needs, and their overexploitation leads to intensified global warming. Fortunately, Africa has a [...] Read more.

More than 500 million people will be added to Africa’s cities by 2040, marking the largest urbanization in history. However, nonrenewable fossil energy sources are inadequate to meet Africa’s energy needs, and their overexploitation leads to intensified global warming. Fortunately, Africa has a huge potential for biomass energy, which will be an important option for combating climate change and energy shortage. In this study, we present a typical large-scale biogas plant in Burkina Faso, West Africa (Ouagadougou Biogas Plant, OUA), which is the first large-scale biogas generation plant in West Africa. The primary objective of OUA is to treat human feces, and it serves as a demonstration plant for generating electricity for feed-in tariffs. The objectives of this study are to assess the greenhouse gas reduction capacity and economic, environmental, and social benefits of OUA and to analyze the opportunities and challenges of developing biogas projects in Africa. As a result, the net economic profit of the OUA biogas plant is approximately USD 305,000 per year, with an anticipated static payback period of 14.5 years. The OUA plant has the capacity to treat 140,000 tons of human feces and 3000 tons of seasonal mixed organic waste annually, effectively reducing greenhouse gas emissions by 5232.61 tCO₂eq, improving the habitat, and providing over 30 local jobs. Finally, the development of biogas projects in Africa includes advantages such as suitable natural conditions, the need for social development, and domestic and international support, as well as challenges in terms of national policies, insufficient funding, technical maintenance, and social culture. Full article

(This article belongs to the Special Issue Recent Advances in Greenhouse Gases’ Emission Processes and Potential in Natural and Artificial Anaerobic Systems)

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