Atmosphere

23 pages, 3519 KiB

Open AccessArticle

High-Resolution Modeling of Air Quality in Abidjan (Côte d’Ivoire) Using a New Urban-Scale Inventory

by Sylvain Gnamien, Cathy Liousse, Sekou Keita, Rajesh Kumar and Véronique Yoboué

Atmosphere 2024, 15(7), 758; https://0-doi-org.brum.beds.ac.uk/10.3390/atmos15070758 (registering DOI) - 25 Jun 2024

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Abstract

In West African cities, the impacts of the air quality on the health of the population is expected to increase significantly in the near future. For the first time to our knowledge, we conducted a high-resolution modeling study over Abidjan (Côte d’Ivoire) using [...] Read more.

In West African cities, the impacts of the air quality on the health of the population is expected to increase significantly in the near future. For the first time to our knowledge, we conducted a high-resolution modeling study over Abidjan (Côte d’Ivoire) using the WRF-Chem model and the simplified GOCART model to simulate carbonaceous aerosols BC and OC, sulfate, dust, sea salt, PM_2.5, and PM₁₀. The simulations were carried out during January and February 2019, a period over which there are databases of observations available. The DACCIWA inventory provided anthropogenic emissions at the regional scale, whereas a new emission inventory has been developed for the city of Abidjan. In 2019, the emissions were 4986.8 Gg for BC, 14,731.4 Gg for OC, and 7751.6 Gg for SO₂. Domestic fires were the primary OC source (7719.5 Gg), while road traffic was the largest BC emitter (2198.8 Gg). Our modeling results generally overestimate urban particle concentrations, despite having a better agreement for those based on the inventory of the city of Abidjan. Modeled concentrations of BC are higher in administrative centers due to road traffic, while OC concentrations are significant in densely populated neighborhoods. Full article

(This article belongs to the Special Issue Urban Air Quality Modelling)

22 pages, 5339 KiB

Open AccessArticle

Exploring the Spatial Variability of Air Pollution Using Mobile BC Measurements in a Citizen Science Project: A Case Study in Mechelen

by Martine Van Poppel, Jan Peters, Stijn Vranckx, Jo Van Laer, Jelle Hofman, Bram Vandeninden, Charlotte Vanpoucke and Wouter Lefebvre

Atmosphere 2024, 15(7), 757; https://0-doi-org.brum.beds.ac.uk/10.3390/atmos15070757 (registering DOI) - 25 Jun 2024

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Abstract

Mobile monitoring is used as an additional tool to collect air quality data at a high spatial resolution and to complement data from fixed air quality stations. Citizens are interested in contributing to air quality monitoring, and while the availability of low-cost air [...] Read more.

Mobile monitoring is used as an additional tool to collect air quality data at a high spatial resolution and to complement data from fixed air quality stations. Citizens are interested in contributing to air quality monitoring, and while the availability of low-cost air quality sensors can create opportunities to measure the air quality at a high spatial resolution, the data are often of lower quality, and sensors that measure combustion-related aerosols (like black carbon) are not commonly available. Mobile monitoring using a mid-range instrument can fill this gap. We present the results of a mobile BC (black carbon) monitoring campaign performed by citizens in Mechelen as part of a local citizen observatory (CO), Meet Mee Mechelen, initiated as part of the European H2020 project, Ground Truth 2.0. The goal of the study was two-fold: (1) to propose and evaluate a mobile monitoring method (data collection and data processing) to construct pollution maps of BC concentrations and (2) to demonstrate how to organize community-based air quality monitoring to measure both the spatial and temporal variations in air pollution levels. Measurements were taken during peak hours in four campaigns characterized by different meteorological conditions: October–November 2017, February–March 2018, June–July 2018 and September 2018. The results show large spatial and temporal variabilities. Spatial variability is influenced by traffic volume, stop-and-go traffic and also the building environment and the distance of biking paths from road traffic. The four different campaigns show similar spatial patterns, but due to background and meteorological influences, the absolute concentrations differ between seasons. A rescaling method using data from fixed stations in the air quality monitoring network (AQMN) was presented to construct maps representative of longer periods. This paper shows that mobile measurements can be used by CO to assess the spatial variability of air quality in a city. The data can be used to evaluate mobility plans, carry out hot spot detection, evaluate the exposure of cyclists as a function of cycling infrastructure and perform model validation. However, it is important to use high-quality instruments and apply the correct measurement methodology (number of repetitions, season) to obtain meaningful data. Full article

(This article belongs to the Special Issue Development and Application of Low-Cost Environmental Sensors for the Evaluation of Ambient Air Quality and Related Emission Sources)

14 pages, 2146 KiB

Open AccessArticle

The Construction and Application of a Model for Evaluating Tourism Climate Suitability in Terraced Agricultural Cultural Heritage Sites: A Case Study of Longji Terraced Fields in China

by Luyao Hu, Xiaoyu Guo, Pengbo Yan and Xinkai Li

Atmosphere 2024, 15(7), 756; https://0-doi-org.brum.beds.ac.uk/10.3390/atmos15070756 - 24 Jun 2024

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Abstract

As one of the globally significant agricultural cultural heritages, Longji Terraced Fields in Longsheng, Guangxi, China, attract numerous tourists. This study aims to describe the weather phenomena and climate change characteristics of Longji Terraced Fields in recent years to reveal their impact on [...] Read more.

As one of the globally significant agricultural cultural heritages, Longji Terraced Fields in Longsheng, Guangxi, China, attract numerous tourists. This study aims to describe the weather phenomena and climate change characteristics of Longji Terraced Fields in recent years to reveal their impact on the tourism economy. Utilizing meteorological station data and considering the actual situation in Longsheng, Guilin, the existing models for evaluating tourism climate comfort are improved. The tourism climate comfort of Longji Terraced Fields from 2002 to 2022 is discussed. The results show that the improved model can better reflect the local situation. The results show that the current Holiday Climate Index and Modified Climate Index for Tourism are not suitable for evaluating the Longji Terraces. Adjustments were made to these indices to account for the high annual precipitation and relative humidity of Longsheng. Combining extensive questionnaire surveys, it was found that the improved evaluation model better reflects tourists’ perceptions of climate comfort. Analysis indicates that when the modified model value is above 70, tourist satisfaction exceeds 80%. The most comfortable tourism periods for the Longji Terraces are August, September, and October, while the least comfortable periods are January, February, and March. This study helps to understand the seasonal variations in tourism climate comfort at Longji Terraced Fields and provides a scientific basis for local tourism industry responses to climate change, thereby increasing tourism revenue. Full article

(This article belongs to the Section Climatology)

15 pages, 679 KiB

Open AccessArticle

Spatial Analysis of Intra-Urban Air Pollution Disparities through an Environmental Justice Lens: A Case Study of Philadelphia, PA

by Madeline Scolio, Charlotte Borha, Peleg Kremer and Kabindra M. Shakya

Atmosphere 2024, 15(7), 755; https://0-doi-org.brum.beds.ac.uk/10.3390/atmos15070755 - 24 Jun 2024

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Abstract

Urban air pollution has been long understood as a critical threat to human health worldwide. Worsening urban air quality can cause increased rates of asthma, respiratory illnesses, and mortality. Air pollution is also an important environmental justice issue as it disproportionately burdens populations [...] Read more.

Urban air pollution has been long understood as a critical threat to human health worldwide. Worsening urban air quality can cause increased rates of asthma, respiratory illnesses, and mortality. Air pollution is also an important environmental justice issue as it disproportionately burdens populations made vulnerable by their socioeconomic and health status. Using spatially continuous fine-scale air quality data for the city of Philadelphia, this study analyzed the relationship between two air pollutants: particulate matter (PM_2.5, black carbon (BC), and three dimensions of vulnerability: social (non-White population), economic (poverty), and health outcomes (asthma prevalence). Spatial autoregressive models outperformed Ordinary Least Squares (OLS) regression, indicating the importance of considering spatial autocorrelation in air pollution-related environmental-justice modeling efforts. Positive relationships were observed between PM_2.5 concentrations and the socioeconomic variables and asthma prevalence. Percent non-White population was a significant predictor of BC for all models, while percent poverty was shown to not be a significant predictor of BC in the best fitting model. Our findings underscore the presence of distributive environmental injustices, where marginalized communities may bear a disproportionate burden of air pollution within Philadelphia. Full article

(This article belongs to the Special Issue Urban Air Quality Modelling)

12 pages, 847 KiB

Open AccessArticle

Airborne Culturable Fungi in the Indoor and Outdoor Environments of Shrines in Chennai, India

by Sripriya Nannu Shankar, Bhuvaneswari Srinivasan and Udaya Prakash Nyayiru Kannaian

Atmosphere 2024, 15(7), 754; https://0-doi-org.brum.beds.ac.uk/10.3390/atmos15070754 - 24 Jun 2024

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Abstract

The diversity and concentrations of airborne fungi in the environments of 58 temples across a metropolitan city (Chennai) in India were investigated. Air samples from indoors (within 2 m of the Sanctum sanctorum) and outdoors (at least 10 m away from the [...] Read more.

The diversity and concentrations of airborne fungi in the environments of 58 temples across a metropolitan city (Chennai) in India were investigated. Air samples from indoors (within 2 m of the Sanctum sanctorum) and outdoors (at least 10 m away from the Sanctum sanctorum) were collected using the Reuter Centrifugal Sampler (RCS). Of the 90 species isolated, 7 belonged to Zygomycota, 5 to Ascomycota and the remaining 78 to Mitosporic fungi. A total of 3470 colonies were isolated from the indoor environment, which was 13.73% higher than the total recorded outdoors (3051 colonies). An average of 747.7 and 657.5 CFU/m³ of air was recorded in the indoor and outdoor environments, respectively. The predominant species identified in both environments were Aspergillus flavus, A. niger and Cladosporium cladosporioides. While most of the fungal species isolated are considered allergens and pathogens, they can also deteriorate the architecture of shrines. This study indicates the need to implement control measures to minimize the risks of exposure to bioaerosols in public spaces such as shrines. Full article

(This article belongs to the Special Issue Health Impacts Related to Indoor Air Pollutants)

30 pages, 6468 KiB

Open AccessReview

Natural Aerosols, Gaseous Precursors and Their Impacts in Greece: A Review from the Remote Sensing Perspective

by Vassilis Amiridis, Stelios Kazadzis, Antonis Gkikas, Kalliopi Artemis Voudouri, Dimitra Kouklaki, Maria-Elissavet Koukouli, Katerina Garane, Aristeidis K. Georgoulias, Stavros Solomos, George Varlas, Anna Kampouri, Dimitra Founda, Basil E. Psiloglou, Petros Katsafados, Kyriakoula Papachristopoulou, Ilias Fountoulakis, Panagiotis-Ioannis Raptis, Thanasis Georgiou, Anna Gialitaki, Emmanouil Proestakis, Alexandra Tsekeri, Eleni Drakaki, Eleni Marinou, Elina Giannakaki, Stergios Misios, John Kapsomenakis, Kostas Eleftheratos, Nikos Hatzianastassiou, Pavlos Kalabokas, Prodromos Zanis, Mihalis Vrekoussis, Alexandros Papayannis, Andreas Kazantzidis, Konstantinos Kourtidis, Dimitris Balis, Alkiviadis F. Bais and Christos Zerefos Show full author list Hide full author list

Atmosphere 2024, 15(7), 753; https://0-doi-org.brum.beds.ac.uk/10.3390/atmos15070753 - 24 Jun 2024

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Abstract

The Mediterranean, and particularly its Eastern basin, is a crossroad of air masses advected from Europe, Asia and Africa. Anthropogenic emissions from its megacities meet over the Eastern Mediterranean, with natural emissions from the Saharan and Middle East deserts, smoke from frequent forest [...] Read more.

The Mediterranean, and particularly its Eastern basin, is a crossroad of air masses advected from Europe, Asia and Africa. Anthropogenic emissions from its megacities meet over the Eastern Mediterranean, with natural emissions from the Saharan and Middle East deserts, smoke from frequent forest fires, background marine and pollen particles emitted from ocean and vegetation, respectively. This mixture of natural aerosols and gaseous precursors (Short-Lived Climate Forcers—SLCFs in IPCC has short atmospheric residence times but strongly affects radiation and cloud formation, contributing the largest uncertainty to estimates and interpretations of the changing cloud and precipitation patterns across the basin. The SLCFs’ global forcing is comparable in magnitude to that of the long-lived greenhouse gases; however, the local forcing by SLCFs can far exceed those of the long-lived gases, according to the Intergovernmental Panel on Climate Change (IPCC). Monitoring the spatiotemporal distribution of SLCFs using remote sensing techniques is important for understanding their properties along with aging processes and impacts on radiation, clouds, weather and climate. This article reviews the current state of scientific know-how on the properties and trends of SLCFs in the Eastern Mediterranean along with their regional interactions and impacts, depicted by ground- and space-based remote sensing techniques. Full article

(This article belongs to the Special Issue The Drivers and Impacts of Climate Change Over the Eastern Mediterranean)

16 pages, 13049 KiB

Open AccessArticle

Improvement in the Forecasting of Low Visibility over Guizhou, China, Based on a Multi-Variable Deep Learning Model

by Dongpo He, Yuetong Wang, Yuanzhi Tang, Dexuan Kong, Jing Yang, Wenyu Zhou, Haishan Li and Fen Wang

Atmosphere 2024, 15(7), 752; https://0-doi-org.brum.beds.ac.uk/10.3390/atmos15070752 - 24 Jun 2024

Viewed by 175

Abstract

High-quality visibility forecasting benefits traffic transportation safety, public services, and tourism. For a more accurate forecast of the visibility in the Guizhou region of China, we constructed several visibility forecasting models via progressive refinements in different compositions of input observational variables and the [...] Read more.

High-quality visibility forecasting benefits traffic transportation safety, public services, and tourism. For a more accurate forecast of the visibility in the Guizhou region of China, we constructed several visibility forecasting models via progressive refinements in different compositions of input observational variables and the adoption of the Unet architecture to perform hourly visibility forecasts with lead times ranging from 0 to 72 h over Guizhou, China. Three Unet-based visibility forecasting models were constructed according to different inputs of meteorological variables. The model training via multiple observational variables and visibility forecasts of a high-spatiotemporal-resolution numerical weather prediction model (China Meteorological Administration, Guangdong, CMA-GD) produced a higher threat score (TS), which led to substantial improvements for different thresholds of visibility compared to CMA-GD. However, the Unet-based models had a larger bias score (BS) than the CMA-GD model. By introducing the U²net architecture, there was a further improvement in the TS of the model by approximately a factor of two compared to the Unet model, along with a significant reduction in the BS, which enhanced the stability of the model forecast. In particular, the U²net-based model performed the best in terms of the TS below the visibility threshold of 200 m, with a more than eightfold increase over the CMA-GD model. Furthermore, the U²net-based model had some improvements in the TS, BS, and RMSE (root-mean-square error) compared to the LSTM_Attention model. The spatial distribution of the TS showed that the U²net-based model performed better at the model grid scale of 3 km than at the scale of individual weather stations. In summary, the visibility forecasting model based on the U²net algorithm, multiple observational variables, and visibility data from the CMA-GD model performed the best. The compositions of input observational variables were the key factor in improving the deep learning model’s forecasting capability, and these improvements could improve the value of forecasts and support the socioeconomic needs of sectors reliant on visibility forecasting. Full article

(This article belongs to the Special Issue Advance in Transportation Meteorology (2nd Edition))

12 pages, 558 KiB

Open AccessArticle

Particulate Matter Exposure during Pregnancy and Childhood Leukemia Incidence

by Enrique Sanz Olea, Carlos Ojeda Sanchez, Mònica Guxens, Adela Cañete, Elena Pardo Romaguera, Diana Gómez-Barroso, Javier García-Pérez, Beatriz Nuñez-Corcuera, Juan Antonio Ortega-García and Rebeca Ramis

Atmosphere 2024, 15(7), 751; https://0-doi-org.brum.beds.ac.uk/10.3390/atmos15070751 - 24 Jun 2024

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Abstract

Leukemia is the most common childhood cancer and its etiology could be related to various environmental contaminants such as particulate matter (PM). The objective of our study is to evaluate the potential association between exposure to PM during pregnancy and the incidence of [...] Read more.

Leukemia is the most common childhood cancer and its etiology could be related to various environmental contaminants such as particulate matter (PM). The objective of our study is to evaluate the potential association between exposure to PM during pregnancy and the incidence of childhood leukemia. We established a population-based nationwide cohort using the Spanish Birth Registry Statistics database of the National Statistics Institute. We used spatiotemporal land use random forest models to estimate the concentrations of PM₁₀ and PM_2.5 for the entire pregnancy and by trimesters. We conducted logistic regression analyses adjusted for various covariates. In addition, we fitted generalized additive models (GAMs) to estimate the non-linear relationship between PM levels and leukemia incidence. The study included 3,112,123 children and 1066 cases of leukemia. The results for the continuous variable of PM₁₀ exposure levels suggested an increased risk of childhood leukemia to be associated with higher exposure. The results for the categorized PM₁₀ variable suggest an increased risk of childhood leukemia among pregnant women whose exposure levels were higher than the median (third and fourth quartiles). The results for PM_2.5 were weaker. We found association between exposure to PM₁₀ during pregnancy and an increased risk of childhood leukemia. Our findings indicate that public health interventions should aim to reduce air pollution to lower the incidence of childhood leukemia. Full article

(This article belongs to the Special Issue New Insights into Exposure and Health Impacts of Air Pollution)

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17 pages, 3895 KiB

Open AccessArticle

Emergy-Theory-Based Evaluation of Typhoon Disaster Risk in China’s Coastal Zone

by Zhicheng Gao, Jing Li, Rongjin Wan, Xiaobin Dong and Qian Ye

Atmosphere 2024, 15(7), 750; https://0-doi-org.brum.beds.ac.uk/10.3390/atmos15070750 - 22 Jun 2024

Viewed by 350

Abstract

The evaluation of typhoon disaster risk is a widely discussed global topic. Currently, the index system method has become a common approach for the evaluation of typhoon disaster risk. However, the indices within the system are calculated independently, and subjective human factors significantly [...] Read more.

The evaluation of typhoon disaster risk is a widely discussed global topic. Currently, the index system method has become a common approach for the evaluation of typhoon disaster risk. However, the indices within the system are calculated independently, and subjective human factors significantly influence the assignment of index weights. The existing studies lack purely quantitative assessment methods, which makes the studies less precise and more difficult for other researchers to replicate. To bridge this gap, this study employs emergy analysis methods based on thermodynamics to develop a typhoon disaster risk evaluation index system for China’s coastal zone. Without the interference of weights and other human factors, the system contains various quantitative indices, including aggregate impelling energy, typhoon intensity emergy, adaptability emergy, the vulnerability index, and the integrated typhoon hazard index. Subsequently, these indices and socio-economic data were spatialized, and the evaluation of typhoon disaster risk was conducted at the city grid level in the coastal zone of China. The findings reveal that the high-risk areas for typhoon disasters in China are concentrated in prefecture-level cities along the southeast coast. The typhoon disaster risk index is higher in the southern region compared to the northern region, with a decreasing trend in the distribution of the integrated typhoon hazard index from coastal to inland areas. The aim of this study is to use a new quantitative evaluation method (emergy) to evaluate typhoon disasters. It also serves as a theoretical foundation and technical support for national and local governments in the formulation of policies for disaster prevention and reduction. Full article

(This article belongs to the Section Meteorology)

21 pages, 3843 KiB

Open AccessArticle

Evaluating the Performance and Applicability of Satellite Precipitation Products over the Rio Grande–San Juan Basin in Northeast Mexico

by Dariela A. Vázquez-Rodríguez, Víctor H. Guerra-Cobián, José L. Bruster-Flores, Carlos R. Fonseca and Fabiola D. Yépez-Rincón

Atmosphere 2024, 15(7), 749; https://0-doi-org.brum.beds.ac.uk/10.3390/atmos15070749 - 22 Jun 2024

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Abstract

Accurate observation of precipitation data is crucial for hydrometeorological applications, requiring temporal and spatial precision. Satellite precipitation products offer a promising solution for obtaining precipitation estimates, facilitating long-term observations from global to local scales. However, assessing their accuracy compared to rain gauge observations [...] Read more.

Accurate observation of precipitation data is crucial for hydrometeorological applications, requiring temporal and spatial precision. Satellite precipitation products offer a promising solution for obtaining precipitation estimates, facilitating long-term observations from global to local scales. However, assessing their accuracy compared to rain gauge observations is essential. This study aims to assess the accuracy and applicability of precipitation data from CMORPH, IMERG, and PERSIANN CCS in the Rio Grande–San Juan Basin in northeast Mexico. The evaluation of estimated precipitation was assessed using the Pearson and Spearman correlations, RMSE, MAE, and BIAS for both monthly and yearly averages. CMORPH showed minimal errors and low underestimation, while IMERG exhibited high correlations with consistent underestimation. PERSIANN CCS had lower correlations, significant overestimation, and higher errors. The Mann–Kendall (MK) test was used to determinate the precipitation trends of observed and estimated data. The observed data showed a significant positive trend in monthly averages, which is not reflected in the annual trend. Furthermore, negative annual trends were found in at least 10 stations across the basin. The application of satellite precipitation data yielded mixed outcomes, with CMORPH showing the highest level of agreement with the trend analysis results from rain gauge data. This demonstrates its reliability for weather and climate studies and suggests the potential for CMORPH to be used as an input in hydrological modeling. Full article

(This article belongs to the Topic Hydrology and Water Resources Management)

19 pages, 3136 KiB

Open AccessArticle

Sensitivity Analysis of the Inverse Distance Weighting and Bicubic Spline Smoothing Models for MERRA-2 Reanalysis PM_2.5 Series in the Persian Gulf Region

by Alina Bărbulescu and Youssef Saliba

Atmosphere 2024, 15(7), 748; https://0-doi-org.brum.beds.ac.uk/10.3390/atmos15070748 - 22 Jun 2024

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Abstract

Various studies have proved that PM_2.5pollution significantly impacts people’s health and the environment. Reliable models on pollutant levels and trends are essential for policy-makers to decide on pollution reduction. Therefore, this research presents the sensitivity analysis of the Bicubic Spline Smoothing [...] Read more.

Various studies have proved that PM_2.5pollution significantly impacts people’s health and the environment. Reliable models on pollutant levels and trends are essential for policy-makers to decide on pollution reduction. Therefore, this research presents the sensitivity analysis of the Bicubic Spline Smoothing (BSS) and Inverse Distance Weighting (IDW) models built for the PM_2.5monthly series from MERRA-2 Reanalysis collected during January 2010–April 2017 in the region of the Persian Gulf, in the neighborhood of the United Arab Emirates Coast. The models’ performances are assessed using the Mean Absolute Error (MAE), Root Mean Square Error (RMSE), and Mean Absolute Percentage Error (MAPE). RMSE, Mean Bias Error (MBE), and Nash–Sutcliff Efficiency (NSE) were utilized to assess the models’ sensitivity to various parameters. For the IDW, the Mean RMSE decreases as the power parameter increases from 1 to approximately 4 (the optimal beta value) and then stabilizes with a further increase. NSE values close to 1 indicate that the model’s predictions are very efficient in capturing the variance of the observed data. NSE is almost constant as a function of the number of neighbors and the parameter when β > 4. In BSS, the RMSE and NBE plots suggest that incorporating more points into the mean calculation for buffer points leads to a general decrease in model accuracy. Moreover, the MBE plot shows that the mean bias error initially increases with the number of points but then starts to plateau. The increasing trend suggests that the model tends to systematically overestimate the PM_2.5values as more points are included. The leveling-off of the curve indicates that beyond a certain number of points, the bias introduced by including additional points does not significantly increase, suggesting a threshold beyond which further inclusion of points does not markedly change the mean bias. It was also proved that the methods’ generalizability may depend on the dataset’s specific spatial characteristics. Full article

(This article belongs to the Special Issue Measurement and Variability of Atmospheric Ozone)

38 pages, 8459 KiB

Open AccessArticle

Climatic Challenges in the Growth Cycle of Winter Wheat in the Huang-Huai-Hai Plain: New Perspectives on High-Temperature–Drought and Low-Temperature–Drought Compound Events

by Geng Chen, Ke Li, Haoting Gu, Yuexuan Cheng, Dan Xue, Hong Jia, Zhengyu Du and Zhongliang Li

Atmosphere 2024, 15(7), 747; https://0-doi-org.brum.beds.ac.uk/10.3390/atmos15070747 - 22 Jun 2024

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Abstract

Global climate change increasingly impacts agroecosystems, particularly through high-temperature–drought and low-temperature–drought compound events. This study uses ground meteorological and remote sensing data and employs geostatistics, random forest models, and copula methods to analyze the spatial and temporal distribution of these events and their [...] Read more.

Global climate change increasingly impacts agroecosystems, particularly through high-temperature–drought and low-temperature–drought compound events. This study uses ground meteorological and remote sensing data and employs geostatistics, random forest models, and copula methods to analyze the spatial and temporal distribution of these events and their impact on winter wheat in the Huang-Huai-Hai Plain from 1982 to 2020. High-temperature–drought events increased in frequency and expanded from north to south, with about 40% of observation stations recording such events from 2001 to 2020. In contrast, low-temperature–drought events decreased in frequency, affecting up to 80% of stations, but with lower frequency than high-temperature–drought events. Sensitivity analyses show winter wheat is most responsive to maximum and minimum temperature changes, with significant correlations to drought and temperature extremes. Copula analysis indicates temperature extremes and drought severity are crucial in determining compound event probability and return periods. High-temperature–drought events are likely under high temperatures and mild drought, while low-temperature–drought events are more common under low temperatures and mild drought. These findings highlight the need for effective agricultural adaptation strategies to mitigate future climate change impacts. Full article

(This article belongs to the Special Issue The Water Cycle and Climate Change (2nd Edition))

16 pages, 12774 KiB

Open AccessArticle

Correlation between Lunar Phases and Rainfall Patterns in Mexico

by Juan Israel Avila-Carrazco, Ángel Alfonso Villalobos-De Alba, Carlos Alberto Olvera-Olvera, José I. De La Rosa-Vargas, Héctor Gutiérrez-Bañuelos, Luis Octavio Solís-Sánchez, Santiago Villagrana-Barraza, Manuel de Jesús López-Martínez, Diana Isabel Ortíz-Esquivel and Germán Díaz-Flórez

Atmosphere 2024, 15(7), 746; https://0-doi-org.brum.beds.ac.uk/10.3390/atmos15070746 - 21 Jun 2024

Viewed by 453

Abstract

In this study, daily historical records from Mexican weather stations across the country were classified according to corresponding Moon phases at the time of rainfall occurrence: New Moon, Waxing Crescent, First Quarter, Waxing Gibbous, Full Moon, Waning Gibbous, Last Quarter, and Waning Crescent. [...] Read more.

In this study, daily historical records from Mexican weather stations across the country were classified according to corresponding Moon phases at the time of rainfall occurrence: New Moon, Waxing Crescent, First Quarter, Waxing Gibbous, Full Moon, Waning Gibbous, Last Quarter, and Waning Crescent. Out of the 5839 Mexican weather stations analyzed, 2412 met the specified data quality standards, which included a historical daily record period ranging from 30 to 51 years (1960–2011) and a maximum tolerance of 20% missing data. Correlation behavior between Moon phases and historical cumulative rainfall in Mexico was identified at two levels: general and particular. At the general level, the total historical cumulative rainfall by Moon phase was quantified. At the particular level, the correlation patterns between the Moon phases and the highest and lowest historical cumulative rainfall were identified. The results showed that the historical cumulative rainfall was highest at 17.24% during the New Moon and lowest at about 10.01% on average during the Waxing Crescent, First Quarter, and Waning Crescent phases (with 9.64% as the lowest value). During the Waxing Gibbous, Full Moon, and Waning Gibbous phases, rainfall remained at average values of approximately 13.18%. At 89.09% of the weather stations, the rainiest Moon phase was New Moon, and at 56.05%, the least rainy was Waning Crescent. In a few geographical areas, there are clearly defined patterns, which is atypical, given that in other geographical areas, the patterns are typically not so evident. This work demonstrates remarkable and strong correlation behavior between Moon phases and historical cumulative rainfall in Mexico. Full article

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

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10 pages, 1606 KiB

Open AccessArticle

Indoor Radon Testing, Effective Dose and Mitigation Measures in a Residential House of a Mining Area

by Dušica Spasić, Ljiljana Gulan and Biljana Vučković

Atmosphere 2024, 15(7), 745; https://0-doi-org.brum.beds.ac.uk/10.3390/atmos15070745 - 21 Jun 2024

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Abstract

This study presents the results of continuous indoor radon measurements in a test-house in the vicinity of the “Trepča” mine, near the town of Kosovska Mitrovica. Annual measurements were performed using the detector, Airthings Corentium Home, in the bedroom of an old residential [...] Read more.

This study presents the results of continuous indoor radon measurements in a test-house in the vicinity of the “Trepča” mine, near the town of Kosovska Mitrovica. Annual measurements were performed using the detector, Airthings Corentium Home, in the bedroom of an old residential building. A high estimated annual effective dose from radon (33 mSv) was calculated using the last ICRP dose conversion factor and is discussed here regarding the previously recommended ones. There are significant indications concerning the health hazard. Several measures are proposed and serve as a technical solution including other effective, low-cost radon mitigation procedures in order to reduce radon levels. The effectiveness of the applied measures resulted in a 44% reduction in radon concentration. Full article

(This article belongs to the Special Issue Atmospheric Radon Concentration Monitoring and Measurements (2nd Edition))

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19 pages, 4866 KiB

Open AccessArticle

Assessment of Fluxes and Ecological and Health Risks of Toxic Trace Elements in Atmospheric Deposition from the Baicheng-Songyuan Area, Jilin Province, Northeast China

by Yinghong Liu, Wen Gao and Sheli Chai

Atmosphere 2024, 15(7), 744; https://0-doi-org.brum.beds.ac.uk/10.3390/atmos15070744 - 21 Jun 2024

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Abstract

A total of 56 atmospheric deposition samples were collected on a yearly basis from the Baicheng-Songyuan areas, Jilin Province, Northeast China. Each sample was subdivided into wet (soluble) and dry (insoluble) fractions, and the concentrations of toxic trace elements including As, Cd, Co, [...] Read more.

A total of 56 atmospheric deposition samples were collected on a yearly basis from the Baicheng-Songyuan areas, Jilin Province, Northeast China. Each sample was subdivided into wet (soluble) and dry (insoluble) fractions, and the concentrations of toxic trace elements including As, Cd, Co, Cr, Cu, Hg, Mn, Mo, Ni, Pb, Se, and Zn in both fractions were analyzed. The bulk fluxes and ecological and human health risk of these toxic trace elements in atmospheric deposition were evaluated. The bulk deposition fluxes of toxic trace elements decreased in the order of Mn > Zn > Cr > Pb > Cu > Ni > As > Co >Mo > Cd > Se > Hg. The fluxes of toxic trace elements in dry fraction accounted for 74.7–99.9% of their bulk deposition fluxes, indicating that the atmospheric deposition of toxic trace elements in the study area is predominantly dry atmospheric deposition. The mean values of the geo-accumulation index (Igeo) and enrichment factor showed moderately heavy contamination with Cd via dry atmospheric deposition, but no contamination from other toxic trace elements; Cd and Hg in dry atmospheric deposition were in the moderate to considerable ecological risk levels, while other trace elements were at low ecological risk levels. The health risk assessment showed that the effects of toxic trace elements in dry atmospheric deposition via three exposure pathways were in the order of ingestion > inhalation > dermal contact for adults and children. The mean values of hazard quotient (HQ) and hazard index (HI) of toxic trace elements via three pathways were less than one, indicating that their non-carcinogenic risks in dry atmospheric deposition may be low or negligible for adults and children. The mean values of carcinogenic risk (CR) and total carcinogenic risk (TCR) of As and Cr via the three pathways for adults and children were between 10⁻⁶ and 10⁻⁴, indicating that the carcinogenic risk levels of As and Cr were tolerable or acceptable, and the mean TCR value of Cd through the three pathways for adult and children was less than 10⁻⁶, implying that the carcinogenic risk level of Cd was negligible. Mn, Ni, Cr, and Co in dry atmospheric deposition were mainly contributed from the crustal sources, while As, Cd, Cu, Hg, Mo, Pb, Se, and Zn in dry atmospheric deposition were derived from both crustal and anthropogenic sources. The results obtained in this study advocate the necessity for monitoring atmospheric deposition in some rural areas, and also provide a scientific basis for controlling contamination posed by toxic trace elements in dry atmospheric deposition. Full article

(This article belongs to the Special Issue Air Pollution Exposure and Health Impact Assessment (2nd Edition))

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22 pages, 1283 KiB

Open AccessArticle

Improvements and Extension of the Linear Carbon Sink Model

by Joachim Dengler

Atmosphere 2024, 15(7), 743; https://0-doi-org.brum.beds.ac.uk/10.3390/atmos15070743 - 21 Jun 2024

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Abstract

While the simple model of the total atmospheric carbon sink effect as a linear function of concentration has provided excellent prediction results, several problems remained to be investigated and solved. The most obvious open issue is the correct treatment of land use change [...] Read more.

While the simple model of the total atmospheric carbon sink effect as a linear function of concentration has provided excellent prediction results, several problems remained to be investigated and solved. The most obvious open issue is the correct treatment of land use change emissions. It turns out that the model improves by mostly neglecting these emissions after 1950. This effectively implies that land use change emissions have been constant and small since then. The key investigation starts with the observation that the total carbon sink has a short-term component that can be explained by temperature changes. The apparent paradox, why contrary to the short-term changes no temperature-caused trend can be detected, despite the fact that several contributing processes exhibit clear temperature dependency, is analyzed and explained. The result of this analysis leads to the model extension, where the total effect of absorptions and natural emissions are a linear function of concentration and temperature. This extended model not only explains current measurements but also paleo-climate data from ice core time series. Full article

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

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13 pages, 8818 KiB

Open AccessArticle

Precursory Signs of Large Forbush Decreases in Relation to Cosmic Rays Equatorial Anisotropy Variation

by Maria-Christina Papailiou, Maria Abunina, Helen Mavromichalaki, Nataly Shlyk, Semyon Belov, Artem Abunin, Maria Gerontidou, Anatoly Belov, Victor Yanke and Amalia Triantou

Atmosphere 2024, 15(7), 742; https://0-doi-org.brum.beds.ac.uk/10.3390/atmos15070742 - 21 Jun 2024

Viewed by 206

Abstract

Forbush decreases are usually characterized by increased values of cosmic ray anisotropy. The precursory signs, i.e., pre-increases and especially pre-decreases of the cosmic ray intensity, are highly anisotropic phenomena that ordinarily forewarn of such events. Two Cosmic Ray Groups from the National and [...] Read more.

Forbush decreases are usually characterized by increased values of cosmic ray anisotropy. The precursory signs, i.e., pre-increases and especially pre-decreases of the cosmic ray intensity, are highly anisotropic phenomena that ordinarily forewarn of such events. Two Cosmic Ray Groups from the National and Kapodistrian University of Athens (NKUA) and the Pushkov Institute of Terrestrial Magnetism, Ionosphere, and Radiowave Propagation of the Russian Academy of Sciences (IZMIRAN) have been investigating the existence of precursory signs preceding Forbush decreases in relation to different solar phenomena, interplanetary parameters, and geomagnetic conditions. In this study, large Forbush decreases (magnitude > 5%) accompanied by geomagnetic storms (i.e., geomagnetic index Dst < −100 nT and 5 ≤ Kp-index ≤ 9) and characterized by an equatorial anisotropy 1 h before the onset of the event (A_xyb, %) less than 0.8% were examined regarding precursors. In total, 50 events with the aforementioned features were selected and analyzed from the IZMIRAN’s Forbush Effects and Interplanetary Disturbances database concerning the time period from 1969 until 2023. The Ring of Stations method, which depicts the cosmic ray variations for various asymptotic longitudes in relation to time, was applied on each event. The results revealed that clear signs of pre-decreases were not present for the majority of the events. Since particularly strong events were considered, most of them still showed some precursory signs, albeit mainly weak. Despite this, the value of A_xyb = 0.8% proves to be a good threshold for the manual selection of FDs with well-expressed precursors. Full article

(This article belongs to the Special Issue Cosmic Rays, Ozone Depletion and Climate Change)

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18 pages, 4964 KiB

Open AccessArticle

Climate Classification for Major Cities in China Using Cluster Analysis

by Huashuai Duan, Qinglan Li, Lunkai He, Jiali Zhang, Hongyu An, Riaz Ali and Majid Vazifedoust

Atmosphere 2024, 15(7), 741; https://0-doi-org.brum.beds.ac.uk/10.3390/atmos15070741 - 21 Jun 2024

Viewed by 148

Abstract

Climate classification plays a fundamental role in understanding climatic patterns, particularly in the context of a changing climate. This study utilized hourly meteorological data from 36 major cities in China from 2011 to 2021, including 2 m temperature (T2), relative humidity (RH), and [...] Read more.

Climate classification plays a fundamental role in understanding climatic patterns, particularly in the context of a changing climate. This study utilized hourly meteorological data from 36 major cities in China from 2011 to 2021, including 2 m temperature (T2), relative humidity (RH), and precipitation (PRE). Both original hourly sequences and daily value sequences were used as inputs, applying two non-hierarchical clustering methods (k-means and k-medoids) and four hierarchical clustering methods (ward, complete, average, and single) for clustering. The classification results were compared using two clustering evaluation indices: the silhouette coefficient and the Calinski–Harabasz index. Additionally, the clustering was compared with the Köppen–Geiger climate classification based on the maximum difference in intra-cluster variables. The results showed that the clustering method outperformed the Köppen–Geiger climate classification, with the k-medoids method achieving the best results. Our research also compared the effectiveness of climate classification using two variables (T2 and PRE) versus three variables, including the addition of hourly RH. Cluster evaluation confirmed that incorporating the original sequence of hourly T2, PRE, and RH yielded the best performance in climate classification. This suggests that considering more meteorological variables and using hourly observation data can significantly improve the accuracy and reliability of climate classification. In addition, by setting the class numbers to two, the clustering methods effectively identified climate boundaries between northern and southern China, aligning with China’s traditional geographical division along the Qinling–Huaihe River line. Full article

(This article belongs to the Section Climatology)

14 pages, 2804 KiB

Open AccessTechnical Note

Reinterpreting Trends: The Impact of Methodological Changes on Reported Sea Salt Aerosol Levels

by Nakul N. Karle, Ricardo K. Sakai, Sen Chiao, Rosa M. Fitzgerald and William R. Stockwell

Atmosphere 2024, 15(7), 740; https://0-doi-org.brum.beds.ac.uk/10.3390/atmos15070740 - 21 Jun 2024

Viewed by 203

Abstract

Since 2017, there has been a considerable increase in the recorded sea salt aerosol (SSA) levels across the United States, particularly the economically critical Baltimore–Washington Corridor (BWC). This unexpected escalation, as reported in the Environmental Protection Agency’s (EPA) annual air quality report, has [...] Read more.

Since 2017, there has been a considerable increase in the recorded sea salt aerosol (SSA) levels across the United States, particularly the economically critical Baltimore–Washington Corridor (BWC). This unexpected escalation, as reported in the Environmental Protection Agency’s (EPA) annual air quality report, has generated worries about the potential effects on air quality, public health, and regional climate dynamics. However, this technical note demonstrates that the apparent rise in SSA levels is mostly due to a change in the EPA’s Chemical Speciation Network’s (CSN) approach to measuring these aerosols. In 2017, the CSN switched from utilizing chlorine to chloride as a tracer for SSAs. Speciation data for this region show that chloride concentrations are often an order of magnitude greater than chlorine concentrations, explaining the significant increase in SSA levels following the methodological modification. The absence of a similar spike in SSA levels at the nearby IMPROVE site, which has been consistent with its methodology, provides more evidence to corroborate this conclusion. These findings demonstrate the importance of methodological consistency and openness in environmental monitoring networks. Clear documentation of such changes is critical to avoiding data misunderstanding, which might lead to the development of incorrect public health and environmental policies. We advocate for continued collaboration among researchers to establish standardized measuring procedures and data analysis tools to accommodate and clarify methodological changes, resulting in accurate environmental evaluations and informed decision-making. Full article

(This article belongs to the Section Air Quality)

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16 pages, 902 KiB

Open AccessArticle

Comparison of Future Design Rainfall with Current Design Rainfall: A Case Study in New South Wales, Australia

by Iqbal Hossain, Monzur Imteaz, Shirley Gato-Trinidad and Abdullah Gokhan Yilmaz

Atmosphere 2024, 15(7), 739; https://0-doi-org.brum.beds.ac.uk/10.3390/atmos15070739 - 21 Jun 2024

Viewed by 198

Abstract

Climate change impacts have the potential to alter the design rainfall estimates around the world. Decreasing trends in the summer and winter rainfall in New South Wales (NSW), Australia have already been observed due to climate variability and change. The derivation of design [...] Read more.

Climate change impacts have the potential to alter the design rainfall estimates around the world. Decreasing trends in the summer and winter rainfall in New South Wales (NSW), Australia have already been observed due to climate variability and change. The derivation of design rainfall from historical rainfall, which is required for the design of stormwater management infrastructure, may be ineffective and costly. It is essential to consider climate change impacts in estimating design rainfall for the successful design of stormwater management infrastructure. In this study, the probability of the occurrence of daily extreme rainfall has been assessed under climate change conditions. The assessment was performed using data from 29 meteorological stations in NSW, Australia. For the evaluation of future design rainfall, the probability of the occurrence of extreme rainfall for different recurrence intervals was developed from daily extreme rainfall for the periods of 2020 to 2099 and compared with the current Australian Bureau of Meteorology (BoM) design rainfall estimates. The historical mean extreme rainfall across NSW varied from 37.71 mm to 147.3 mm, indicating the topographic and climatic influences on extreme rainfall. The outcomes of the study suggested that the future design rainfall will be significantly different from the current BoM estimates for most of the studied stations. The comparison of the results showed that future rainfall in NSW will change from −4.7% to +60% for a 100-year recurrence interval. However, for a 2-year recurrence interval, the potential design rainfall change varies from an approximately 8% increase to a 40% decrease. This study revealed that the currently designed stormwater management infrastructure will be idle in the changing climate. Full article

(This article belongs to the Special Issue Statistical Approaches in Climatic Parameters Prediction)

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Atmosphere, Volume 15, Issue 7 (July 2024) – 20 articles

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