Pub Date : 2024-04-16DOI: 10.1007/s10453-024-09818-w
Willem W. Verstraeten, Rostislav Kouznetsov, Nicolas Bruffaerts, Mikhail Sofiev, Andy W. Delcloo
In Europe, more than one quarter of the adult population and one third of the children suffer from pollinosis, but the geographical variability is large. In Belgium, at least ~ 10% of the people develop allergies due to birch pollen. These patients may benefit from a forecasting system that raises alerts when episodes with huge amount of airborne birch pollen grains are expected. Such a forecast system for birch pollen was established for the Belgian territory in 2023 based on the pollen emission and transport model System for Integrated modeLling of Atmospheric coMposition (SILAM). The question, however, is which uncertainty in modelling and forecasting airborne pollen levels can be expected? Here, we assess the uncertainty in modelling airborne birch pollen levels near the surface using SILAM in a Monte Carlo error approach summarized by the relative Coefficient of Variation (CV%) as descriptive statistic for the season of 2018 in Belgium. For the major inputs that drive the birch pollen model—the amount and location of birch trees (0.1° × 0.1° map), the start and end of the birch pollen season (1° × 1° map), and the ripening temperature of birch catkins—sets of 100 randomly sampled data layers were prepared for running SILAM 100 times. For each set of model input, 100 spatio-temporal maps of airborne birch pollen levels were produced and its spread was quantified by the CV%. We show that the spatial uncertainty of pollen emissions sources in SILAM is substantially high, but that the uncertainties of the parameters determining the start and end of the season are at least equally important. By accumulating the effects of all investigated model input uncertainties including the impact of the catkins-ripening temperature, CV% values of 50% and more are obtained when quantifying the variation of the modelled airborne birch pollen levels. These errors are in line with reported values from the current reference method for monitoring airborne birch pollen grains near the surface.
{"title":"Assessing uncertainty in airborne birch pollen modelling","authors":"Willem W. Verstraeten, Rostislav Kouznetsov, Nicolas Bruffaerts, Mikhail Sofiev, Andy W. Delcloo","doi":"10.1007/s10453-024-09818-w","DOIUrl":"10.1007/s10453-024-09818-w","url":null,"abstract":"<div><p>In Europe, more than one quarter of the adult population and one third of the children suffer from pollinosis, but the geographical variability is large. In Belgium, at least ~ 10% of the people develop allergies due to birch pollen. These patients may benefit from a forecasting system that raises alerts when episodes with huge amount of airborne birch pollen grains are expected. Such a forecast system for birch pollen was established for the Belgian territory in 2023 based on the pollen emission and transport model System for Integrated modeLling of Atmospheric coMposition (SILAM). The question, however, is which uncertainty in modelling and forecasting airborne pollen levels can be expected? Here, we assess the uncertainty in modelling airborne birch pollen levels near the surface using SILAM in a Monte Carlo error approach summarized by the relative Coefficient of Variation (CV%) as descriptive statistic for the season of 2018 in Belgium. For the major inputs that drive the birch pollen model—the amount and location of birch trees (0.1° × 0.1° map), the start and end of the birch pollen season (1° × 1° map), and the ripening temperature of birch catkins—sets of 100 randomly sampled data layers were prepared for running SILAM 100 times. For each set of model input, 100 spatio-temporal maps of airborne birch pollen levels were produced and its spread was quantified by the CV%. We show that the spatial uncertainty of pollen emissions sources in SILAM is substantially high, but that the uncertainties of the parameters determining the start and end of the season are at least equally important. By accumulating the effects of all investigated model input uncertainties including the impact of the catkins-ripening temperature, CV% values of 50% and more are obtained when quantifying the variation of the modelled airborne birch pollen levels. These errors are in line with reported values from the current reference method for monitoring airborne birch pollen grains near the surface.</p></div>","PeriodicalId":7718,"journal":{"name":"Aerobiologia","volume":"40 2","pages":"271 - 286"},"PeriodicalIF":2.2,"publicationDate":"2024-04-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140617608","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Biological particles known as bioaerosols are present in the atmosphere and have recently been implicated as influencing agriculture, cloud development, biogeography, and human health. The present study was conducted to characterize airborne bacterial heterogeneity at Jeju Island in Korea and at Saitama and Toyama in Japan, focusing on potential human pathogens. Air samples were collected during the winter, when the monsoon blows from the northwest. Samples were analyzed by high-throughput sequencing and denaturing gradient gel electrophoresis of PCR-amplified 16S rRNA genes to detect spatial differences in airborne bacteria and the possible spread of bacteria by transboundary transport. Compositions of the bacterial in samples collected on the same dates from the different sites were similar. Notably, bacteria from two genera that are potentially pathogenic for humans—Acinetobacter and Clostridium—were detected on the same day in both Korea and Japan. These results indicate the possibility of long-range transport of airborne bacteria and its potential impact on human health.
{"title":"Spatial variation of airborne bacterial heterogeneity and potential opportunistic human pathogens: a comparative study of sites in Korea and Japan","authors":"Makoto Seki, Hitoshi Tanaka, Shinichi Yonemochi, Ki-Ho Lee, Young-Ju Kim, Reika Iwamoto, Kei Sato, Daisuke Tanaka","doi":"10.1007/s10453-024-09817-x","DOIUrl":"10.1007/s10453-024-09817-x","url":null,"abstract":"<div><p>Biological particles known as bioaerosols are present in the atmosphere and have recently been implicated as influencing agriculture, cloud development, biogeography, and human health. The present study was conducted to characterize airborne bacterial heterogeneity at Jeju Island in Korea and at Saitama and Toyama in Japan, focusing on potential human pathogens. Air samples were collected during the winter, when the monsoon blows from the northwest. Samples were analyzed by high-throughput sequencing and denaturing gradient gel electrophoresis of PCR-amplified 16S rRNA genes to detect spatial differences in airborne bacteria and the possible spread of bacteria by transboundary transport. Compositions of the bacterial in samples collected on the same dates from the different sites were similar. Notably, bacteria from two genera that are potentially pathogenic for humans—<i>Acinetobacter</i> and <i>Clostridium</i>—were detected on the same day in both Korea and Japan. These results indicate the possibility of long-range transport of airborne bacteria and its potential impact on human health.</p></div>","PeriodicalId":7718,"journal":{"name":"Aerobiologia","volume":"40 2","pages":"287 - 295"},"PeriodicalIF":2.2,"publicationDate":"2024-04-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140582498","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The viable bacterial assemblages in clouds at Réunion Island (Indian Ocean) were examined through culture-based approach. A total of 176 isolates were recovered from 15 independent cloud events collected during 3 field campaigns, and identified to the species level through full length 16S rRNA gene sequencing. As often in atmospheric samples, Alpha-, Beta- and Gamma-proteobacteria dominated, along with Actinobacteria, Firmicutes, and Bacteroidetes, depicting these as the backbone of the global aeromicrobiome. A comparative analysis with similar work from a cloud sampling site in Central France revealed site-specificities, and numerous common species. These latter included members of Pseudomonas, Sphingomonas, Bacillus, Staphylococcus, Rhodococcus and others, whose such widespread presence in clouds supports the existence of a pan-atmospheric microbiome. This also confirms that cultures remain powerful methods in the description of the viable microbial diversity by allowing deep taxonomic affiliation.
{"title":"Culturable bacteria in clouds at Réunion, tropical island","authors":"Thomas Charpentier, Muriel Joly, Céline Judon, Martine Sancelme, Magali Abrantes, Mickaël Vaïtilingom, Christelle Ghaffar, Maxence Brissy, Maud Leriche, Anne-Marie Delort, Laurent Deguillaume, Pierre Amato","doi":"10.1007/s10453-024-09819-9","DOIUrl":"10.1007/s10453-024-09819-9","url":null,"abstract":"<div><p>The viable bacterial assemblages in clouds at Réunion Island (Indian Ocean) were examined through culture-based approach. A total of 176 isolates were recovered from 15 independent cloud events collected during 3 field campaigns, and identified to the species level through full length 16S rRNA gene sequencing. As often in atmospheric samples, Alpha-, Beta- and Gamma-proteobacteria dominated, along with Actinobacteria, Firmicutes, and Bacteroidetes, depicting these as the backbone of the global aeromicrobiome. A comparative analysis with similar work from a cloud sampling site in Central France revealed site-specificities, and numerous common species. These latter included members of <i>Pseudomonas</i>, <i>Sphingomonas</i>, <i>Bacillus</i>, <i>Staphylococcus</i>, <i>Rhodococcus</i> and others, whose such widespread presence in clouds supports the existence of a pan-atmospheric microbiome. This also confirms that cultures remain powerful methods in the description of the viable microbial diversity by allowing deep taxonomic affiliation.</p></div>","PeriodicalId":7718,"journal":{"name":"Aerobiologia","volume":"40 2","pages":"297 - 302"},"PeriodicalIF":2.2,"publicationDate":"2024-04-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140582378","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-04-03DOI: 10.1007/s10453-024-09820-2
Fiona Tummon, Beverley Adams-Groom, Célia M. Antunes, Nicolas Bruffaerts, Jeroen Buters, Paloma Cariñanos, Sevcan Celenk, Marie Choël, Bernard Clot, Antonella Cristofori, Benoît Crouzy, Athanasios Damialis, Alberto Rodríguez Fernández, Délia Fernández González, Carmen Galán, Björn Gedda, Regula Gehrig, Monica Gonzalez-Alonso, Elena Gottardini, Jules Gros-Daillon, Lenka Hajkova, David O’Connor, Pia Östensson, Jose Oteros, Andreas Pauling, Rosa Pérez-Badia, Victoria Rodinkova, F. Javier Rodríguez-Rajo, Helena Ribeiro, Ingrida Sauliene, Branko Sikoparija, Carsten Ambelas Skjøth, Antonio Spanu, Mikhail Sofiev, Olga Sozinova, Lidija Srnec, Nicolas Visez, Letty A. de Weger
The advent of automatic pollen and fungal spore monitoring over the past few years has brought about a paradigm change. The provision of real-time information at high temporal resolution opens the door to a wide range of improvements in terms of the products and services made available to a widening range of end-users and stakeholders. As technology and methods mature, it is essential to properly quantify the impact automatic monitoring has on the different end-user domains to better understand the real long-term benefits to society. In this paper, we focus the main domains where such impacts are expected, using Europe as a basis to provide qualitative estimates and to describe research needs to better quantify impacts in future. This will, in part, also serve to justify further investment and help to expand monitoring networks.
{"title":"The role of automatic pollen and fungal spore monitoring across major end-user domains","authors":"Fiona Tummon, Beverley Adams-Groom, Célia M. Antunes, Nicolas Bruffaerts, Jeroen Buters, Paloma Cariñanos, Sevcan Celenk, Marie Choël, Bernard Clot, Antonella Cristofori, Benoît Crouzy, Athanasios Damialis, Alberto Rodríguez Fernández, Délia Fernández González, Carmen Galán, Björn Gedda, Regula Gehrig, Monica Gonzalez-Alonso, Elena Gottardini, Jules Gros-Daillon, Lenka Hajkova, David O’Connor, Pia Östensson, Jose Oteros, Andreas Pauling, Rosa Pérez-Badia, Victoria Rodinkova, F. Javier Rodríguez-Rajo, Helena Ribeiro, Ingrida Sauliene, Branko Sikoparija, Carsten Ambelas Skjøth, Antonio Spanu, Mikhail Sofiev, Olga Sozinova, Lidija Srnec, Nicolas Visez, Letty A. de Weger","doi":"10.1007/s10453-024-09820-2","DOIUrl":"10.1007/s10453-024-09820-2","url":null,"abstract":"<div><p>The advent of automatic pollen and fungal spore monitoring over the past few years has brought about a paradigm change. The provision of real-time information at high temporal resolution opens the door to a wide range of improvements in terms of the products and services made available to a widening range of end-users and stakeholders. As technology and methods mature, it is essential to properly quantify the impact automatic monitoring has on the different end-user domains to better understand the real long-term benefits to society. In this paper, we focus the main domains where such impacts are expected, using Europe as a basis to provide qualitative estimates and to describe research needs to better quantify impacts in future. This will, in part, also serve to justify further investment and help to expand monitoring networks.</p></div>","PeriodicalId":7718,"journal":{"name":"Aerobiologia","volume":"40 1","pages":"57 - 75"},"PeriodicalIF":2.2,"publicationDate":"2024-04-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://link.springer.com/content/pdf/10.1007/s10453-024-09820-2.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140582435","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-03-27DOI: 10.1007/s10453-024-09815-z
Sefat-E- Barket, Md. Rezaul Karim
In 2019, the world grappled with an unexpected and severe global health crisis—the Coronavirus disease (COVID-19) outbreak, which significantly impacted various aspects of human life. This case study, focusing on Bangladesh, aimed to uncover the complex spatial patterns and potential risk factors influencing the virus’s uneven spread across 64 districts. To analyze spatial patterns, two techniques, namely Moran I and Geary C, were employed to study spatial autocorrelation. Hotspots and coldspots were identified using local Moran I, while spatial hotspots were pinpointed using local Getis Ord G. Exploring spatial heterogeneity involved implementing two non-spatial models (Poisson–Gamma and Poisson-Lognormal) and three spatial models (Conditional Autoregressive model, Convolution model, and Leroux model) through Gibbs sampling. The Leroux model emerged as the optimal choice, meeting criteria based on the lowest values of deviance information criterion and Watanabe–Akaike information criterion. Regression analysis revealed that factors such as humidity, population density, and urbanization were associated with an increase in COVID-19 cases, while the aging index appeared to hinder the virus’s spread. The research outcomes provide a comprehensive framework adaptable to the evolving nature of COVID-19 in Bangladesh. It categorizes influential factors into distinct clusters, enabling government agencies, policymakers, and healthcare professionals to make informed decisions for controlling the pandemic and addressing future infectious diseases.
摘要 2019 年,世界面临着一场意想不到的严重全球健康危机--冠状病毒病(COVID-19)的爆发,对人类生活的各个方面产生了重大影响。本案例研究以孟加拉国为重点,旨在揭示影响病毒在 64 个地区不均衡传播的复杂空间模式和潜在风险因素。为了分析空间模式,我们采用了 Moran I 和 Geary C 两种技术来研究空间自相关性。在探索空间异质性时,通过吉布斯抽样,采用了两个非空间模型(泊松-伽马模型和泊松-对数正态模型)和三个空间模型(条件自回归模型、卷积模型和勒鲁模型)。Leroux 模型符合偏差信息准则和 Watanabe-Akaike 信息准则的最低值标准,成为最佳选择。回归分析表明,湿度、人口密度和城市化等因素与 COVID-19 病例的增加有关,而老龄化指数似乎阻碍了病毒的传播。研究成果提供了一个综合框架,可适应 COVID-19 在孟加拉国不断演变的性质。它将有影响的因素分为不同的群组,使政府机构、政策制定者和医疗保健专业人员能够做出明智的决策,以控制流行病和应对未来的传染病。
{"title":"Spatial analysis of COVID-19 risk factors: a case study in Bangladesh","authors":"Sefat-E- Barket, Md. Rezaul Karim","doi":"10.1007/s10453-024-09815-z","DOIUrl":"10.1007/s10453-024-09815-z","url":null,"abstract":"<div><p>In 2019, the world grappled with an unexpected and severe global health crisis—the Coronavirus disease (COVID-19) outbreak, which significantly impacted various aspects of human life. This case study, focusing on Bangladesh, aimed to uncover the complex spatial patterns and potential risk factors influencing the virus’s uneven spread across 64 districts. To analyze spatial patterns, two techniques, namely Moran <i>I</i> and Geary <i>C</i>, were employed to study spatial autocorrelation. Hotspots and coldspots were identified using local Moran <i>I</i>, while spatial hotspots were pinpointed using local Getis Ord <i>G</i>. Exploring spatial heterogeneity involved implementing two non-spatial models (Poisson–Gamma and Poisson-Lognormal) and three spatial models (Conditional Autoregressive model, Convolution model, and Leroux model) through Gibbs sampling. The Leroux model emerged as the optimal choice, meeting criteria based on the lowest values of deviance information criterion and Watanabe–Akaike information criterion. Regression analysis revealed that factors such as humidity, population density, and urbanization were associated with an increase in COVID-19 cases, while the aging index appeared to hinder the virus’s spread. The research outcomes provide a comprehensive framework adaptable to the evolving nature of COVID-19 in Bangladesh. It categorizes influential factors into distinct clusters, enabling government agencies, policymakers, and healthcare professionals to make informed decisions for controlling the pandemic and addressing future infectious diseases.</p></div>","PeriodicalId":7718,"journal":{"name":"Aerobiologia","volume":"40 2","pages":"247 - 269"},"PeriodicalIF":2.2,"publicationDate":"2024-03-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140315353","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-03-19DOI: 10.1007/s10453-024-09812-2
Swati Tyagi, Arun Srivastava
Suspended particles of biological origin comprising of virus, fragments of plants and animals dander, pollen grains, fungal spores and bacteria known as bioaerosols have become a major concern in the past decades. In the present study reports, the concentration and size distribution of fungal bioaerosol in and around a sugar mill situated in the Muzaffarnagar region of Uttar Pradesh, India, are presented. The sampling was performed in the winter when the mill used to be in the operational mode. The highest mean fungal concentration was observed at the cutter site (4022 ± 321 cfu/m3) and lowest at storage site (832 ± 85 cfu/m3). The maximum and minimum concentration of fungal bioaerosol was observed during January (3090 ± 174 cfu/m3) and March (629 ± 69 cfu/m3) respectively. During the entire sampling period, the fine fraction of fungal bioaerosol was observed to be significantly higher at all the sites, whereas coarse fraction was lower. The association between fine and coarse fractions of bioaerosols showed a very strong positive relationship. The levels of fungal bioaerosol and their association with the meteorological parameters in sugar mill were also conducted. A positive association with the relative humidity and wind speed was observed at significance level of p < 0.05, whereas a negative relation was observed with temperature at p < 0.05. The lifetime average daily dose was calculated for both inhalation and dermal; among them LADDinhalation is ~ 5 times over LADDdermal. The health risk index was observed as < 1 for both inhalation and dermal routes, whereas HIinhalation value was 105 times higher than the HIdermal value. The dominant fungi genera found in the air of examined dwellings were Penicillium spp., Aspergillus spp., Cladosporium spp., and Alternaria spp., which occurred predominantly at all of the studied sites during the sampling period.
过去几十年来,由病毒、动植物皮屑碎片、花粉粒、真菌孢子和细菌组成的生物源悬浮微粒(称为生物气溶胶)已成为人们关注的主要问题。本研究报告介绍了位于印度北方邦 Muzaffarnagar 地区一家糖厂及其周围的真菌生物气溶胶的浓度和大小分布。采样工作在冬季进行,当时糖厂处于运行状态。在切纸机位置观察到的平均真菌浓度最高(4022 ± 321 cfu/m3),在储存位置观察到的平均真菌浓度最低(832 ± 85 cfu/m3)。真菌生物气溶胶的最高和最低浓度分别出现在一月(3090 ± 174 cfu/m3)和三月(629 ± 69 cfu/m3)。在整个采样期间,所有采样点的真菌生物气溶胶细粒度都明显较高,而粗粒度较低。生物气溶胶的细粒部分和粗粒部分之间呈现出很强的正相关关系。还研究了制糖厂的真菌生物气溶胶水平及其与气象参数的关系。在 p < 0.05 的显著性水平下,观察到与相对湿度和风速呈正相关,而在 p < 0.05 的显著性水平下,观察到与温度呈负相关。计算了吸入和皮肤的终生日均剂量,其中吸入的 LADD 是皮肤的 LADD 的 5 倍。吸入和皮肤途径的健康风险指数均为 1,而吸入的 HI 值是皮肤的 HI 值的 105 倍。在受检住宅的空气中发现的主要真菌属有青霉菌属、曲霉菌属、Cladosporium 菌属和 Alternaria 菌属,它们在采样期间主要出现在所有研究地点。
{"title":"Characterization and health risk assessment of size-segregated fungal bioaerosols in and around a sugar mill in India","authors":"Swati Tyagi, Arun Srivastava","doi":"10.1007/s10453-024-09812-2","DOIUrl":"10.1007/s10453-024-09812-2","url":null,"abstract":"<div><p>Suspended particles of biological origin comprising of virus, fragments of plants and animals dander, pollen grains, fungal spores and bacteria known as bioaerosols have become a major concern in the past decades. In the present study reports, the concentration and size distribution of fungal bioaerosol in and around a sugar mill situated in the Muzaffarnagar region of Uttar Pradesh, India, are presented. The sampling was performed in the winter when the mill used to be in the operational mode. The highest mean fungal concentration was observed at the cutter site (4022 ± 321 cfu/m<sup>3</sup>) and lowest at storage site (832 ± 85 cfu/m<sup>3</sup>). The maximum and minimum concentration of fungal bioaerosol was observed during January (3090 ± 174 cfu/m<sup>3)</sup> and March (629 ± 69 cfu/m<sup>3</sup>) respectively. During the entire sampling period, the fine fraction of fungal bioaerosol was observed to be significantly higher at all the sites, whereas coarse fraction was lower. The association between fine and coarse fractions of bioaerosols showed a very strong positive relationship. The levels of fungal bioaerosol and their association with the meteorological parameters in sugar mill were also conducted. A positive association with the relative humidity and wind speed was observed at significance level of <i>p</i> < 0.05, whereas a negative relation was observed with temperature at <i>p</i> < 0.05. The lifetime average daily dose was calculated for both inhalation and dermal; among them LADD<sub>inhalation</sub> is ~ 5 times over LADD<sub>dermal</sub>. The health risk index was observed as < 1 for both inhalation and dermal routes, whereas HI<sub>inhalation</sub> value was 10<sup>5</sup> times higher than the HI<sub>dermal</sub> value. The dominant fungi genera found in the air of examined dwellings were <i>Penicillium</i> spp., <i>Aspergillus</i> spp., <i>Cladosporium</i> spp., and <i>Alternaria</i> spp., which occurred predominantly at all of the studied sites during the sampling period.</p></div>","PeriodicalId":7718,"journal":{"name":"Aerobiologia","volume":"40 2","pages":"201 - 215"},"PeriodicalIF":2.2,"publicationDate":"2024-03-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140204598","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-03-18DOI: 10.1007/s10453-024-09814-0
Md. Mamun Miah, Mohammad Belal Hossain, Sumiya Nur Jannat, Md. Rezaul Karim, Md. Rashedur Rahman, Yasin Arafat, Farjana Haque Pingki
Dengue fever is a virus-borne disease spread by mosquitos, and its global prevalence has risen significantly in recent years. The aim of this study was to analyze the impact and association of climatic factors on the spread of dengue incidence in Bangladesh. From January 2011 to December 2021, the study used secondary data on monthly dengue cases and the monthly average of climatic factors. In addition to the descriptive statistics, bivariate analyses of Kendall’s tau-b and Spearman’s rho have been performed for measuring the association of climatic factors on dengue infection. The generalized linear negative binomial regression model with and without lag was applied to evaluate the impacts of climatic factors on dengue transmission. Results of goodness of fit statistics ((AIC, BIC, and deviance)) showed that NBR model with one month lag best fitted to our data. The model findings revealed that temperature ((IRR:1.223, 95% CI:1.089-1.374)), humidity ((IRR:1.131, 95% CI:1.103-1.159)), precipitation ((IRR:1.158, 95% CI:1.072-1.253)), and air pressure ((IRR:5.279, 95% CI:1.411-19.046)) were significantly positively influenced the spread of dengue incidence in Bangladesh. Additionally, dengue fever cases are anticipated to rise by 1.223, 1.131, 1.158, and 5.279 times, respectively, for the everyone-unit increase in the monthly average mean temperature, humidity, precipitation, and air pressure range. The findings on the epidemiological trends of the dengue epidemic and weather changes may interest policymakers and health officials.
{"title":"Assessing the impact of climatic factors on dengue fever transmission in Bangladesh","authors":"Md. Mamun Miah, Mohammad Belal Hossain, Sumiya Nur Jannat, Md. Rezaul Karim, Md. Rashedur Rahman, Yasin Arafat, Farjana Haque Pingki","doi":"10.1007/s10453-024-09814-0","DOIUrl":"10.1007/s10453-024-09814-0","url":null,"abstract":"<div><p>Dengue fever is a virus-borne disease spread by mosquitos, and its global prevalence has risen significantly in recent years. The aim of this study was to analyze the impact and association of climatic factors on the spread of dengue incidence in Bangladesh. From January 2011 to December 2021, the study used secondary data on monthly dengue cases and the monthly average of climatic factors. In addition to the descriptive statistics, bivariate analyses of Kendall’s tau-b and Spearman’s rho have been performed for measuring the association of climatic factors on dengue infection. The generalized linear negative binomial regression model with and without lag was applied to evaluate the impacts of climatic factors on dengue transmission. Results of goodness of fit statistics <span>((AIC, BIC, and deviance))</span> showed that NBR model with one month lag best fitted to our data. The model findings revealed that temperature <span>((IRR:1.223, 95% CI:1.089-1.374))</span>, humidity <span>((IRR:1.131, 95% CI:1.103-1.159))</span>, precipitation <span>((IRR:1.158, 95% CI:1.072-1.253))</span>, and air pressure <span>((IRR:5.279, 95% CI:1.411-19.046))</span> were significantly positively influenced the spread of dengue incidence in Bangladesh. Additionally, dengue fever cases are anticipated to rise by 1.223, 1.131, 1.158, and 5.279 times, respectively, for the everyone-unit increase in the monthly average mean temperature, humidity, precipitation, and air pressure range. The findings on the epidemiological trends of the dengue epidemic and weather changes may interest policymakers and health officials.</p></div>","PeriodicalId":7718,"journal":{"name":"Aerobiologia","volume":"40 2","pages":"233 - 245"},"PeriodicalIF":2.2,"publicationDate":"2024-03-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140151414","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-03-05DOI: 10.1007/s10453-024-09813-1
A. A. Abdel Hameed, S. El-Gendy, Y. Saeed
Deposited dust represents a nutritional niche for microflora. Inhibiting microflora-associated deposited dust is a critical approach to manage cultural heritage buildings. Knowledge on the effectiveness of commercial disinfection on microflora in a real field environment is limited. The present study aims to: (1) characterize deposited dust composition, and (2) assess the effectiveness of several commercial biocides/and an air ionizer on microflora-associated floor surface and air before and after treatment. Deposited dust was collected using a dust collector and microbial air sampling was conducted via a volumetric impactor sampler. Susceptibility of microorganisms to biocide/ionizer was performed in a naturally ventilated unoccupied room with a floor area of 18 m2. One-treatment protocol, a daily disinfection mode, was applied to each biocide/ionizer. The surface floor was adjacently sprayed by a biocide, and the ionizer was turned on for 30 min. Indoor deposited dust rates varied between 0.75 and 8.7 mg/m2/day with indoor/outdoor ratio of ~ 1:100. Ion concentrations of NH4+, Cl−, SO42− and NO3− were higher indoor than outdoor. The concentration of microorganisms-associated deposited dust averaged 106 CFU/g; 105 CFU/g and 104 CFU/g for bacteria, fungi and actinomycetes, respectively. A total of 23 fungal taxa were identified, with Aspergillus flavus, Asp. fumigatus and Asp. niger were the predominant taxa. Biocides quickly reduced floor surface and airborne microbial loads. The biocidal effect was time limited, as microflora loads increased again after ~ 4 days of the treatment protocol. Benzalkonium chloride (BAC) out-performed other biocides, showed a relatively permanent microbial inhibiting effect. The air ionizer reduced airborne microorganisms and increased surface floor ones. Characterizing of deposited dust (rate and composition) and choice an appropriate biocide may effectively reduce biodeterioration. Further real field treatment trials under various microenvironmental conditions are needed to determine the effectiveness of disinfection treatment.
{"title":"Characterization and decontamination of deposited dust: a management regime at a museum","authors":"A. A. Abdel Hameed, S. El-Gendy, Y. Saeed","doi":"10.1007/s10453-024-09813-1","DOIUrl":"10.1007/s10453-024-09813-1","url":null,"abstract":"<div><p>Deposited dust represents a nutritional niche for microflora. Inhibiting microflora-associated deposited dust is a critical approach to manage cultural heritage buildings. Knowledge on the effectiveness of commercial disinfection on microflora in a real field environment is limited. The present study aims to: (1) characterize deposited dust composition, and (2) assess the effectiveness of several commercial biocides/and an air ionizer on microflora-associated floor surface and air before and after treatment. Deposited dust was collected using a dust collector and microbial air sampling was conducted via a volumetric impactor sampler. Susceptibility of microorganisms to biocide/ionizer was performed in a naturally ventilated unoccupied room with a floor area of 18 m<sup>2</sup>. One-treatment protocol, a daily disinfection mode, was applied to each biocide/ionizer. The surface floor was adjacently sprayed by a biocide, and the ionizer was turned on for 30 min. Indoor deposited dust rates varied between 0.75 and 8.7 mg/m<sup>2</sup>/day with indoor/outdoor ratio of ~ 1:100. Ion concentrations of NH<sub>4</sub><sup>+</sup>, Cl<sup>−</sup>, SO<sub>4</sub><sup>2−</sup> and NO<sub>3</sub><sup>−</sup> were higher indoor than outdoor. The concentration of microorganisms-associated deposited dust averaged 10<sup>6</sup> CFU/g; 10<sup>5</sup> CFU/g and 10<sup>4</sup> CFU/g for bacteria, fungi and actinomycetes, respectively. A total of 23 fungal taxa were identified, with <i>Aspergillus flavus</i>, <i>Asp. fumigatus</i> and <i>Asp. niger</i> were the predominant taxa. Biocides quickly reduced floor surface and airborne microbial loads. The biocidal effect was time limited, as microflora loads increased again after ~ 4 days of the treatment protocol. Benzalkonium chloride (BAC) out-performed other biocides, showed a relatively permanent microbial inhibiting effect. The air ionizer reduced airborne microorganisms and increased surface floor ones. Characterizing of deposited dust (rate and composition) and choice an appropriate biocide may effectively reduce biodeterioration. Further real field treatment trials under various microenvironmental conditions are needed to determine the effectiveness of disinfection treatment.</p></div>","PeriodicalId":7718,"journal":{"name":"Aerobiologia","volume":"40 2","pages":"217 - 232"},"PeriodicalIF":2.2,"publicationDate":"2024-03-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://link.springer.com/content/pdf/10.1007/s10453-024-09813-1.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140036113","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-02-28DOI: 10.1007/s10453-024-09810-4
Merin Ann Ninan, Merin Grace Jiji, Thomas Ponnachen Valukattil, Harikumar Sadasivan Pillai Puthenveedu, Sabu Thomas, Binoy Thomas Thundiathu
This scientific article presents a comprehensive exploration of the intriguing ecological phenomenon known as "red rain", observed in the coastal town located at latitude N 11°.61108 and longitude E 75°.57383 in Kerala, India. The study aims to elucidate the origins, characteristics, and potential environmental implications associated with this phenomenon. Through a meticulous descriptive analysis, incorporating microscopic evaluation, DNA-sequencing, Fourier-transform infrared spectroscopy (FTIR), Gas Chromatography-Mass Spectrometry (GC–MS) analysis, and phylogenetic analysis, we deciphered the underlying factors responsible for the distinct red coloration observed in the rain. Our research findings highlight the presence of specific organic compounds, namely psi-psi Carotene 3,4 didehydro-1,2,7′8'-tetrahydro-1-methoxy-2-oxo and psi-psi and- Carotene 3,3',4,4'-tetradehydro1′2' dihydro 1-hydroxy-1'-methoxy in the algae, Trentepohlia abietina, as the primary contributors to the red color observed in the red rain. The research findings contribute to a deeper understanding of this distinctive occurrence and its implications for the local ecosystem in Kerala.
{"title":"The real hues of Red Rain-Kerala, India","authors":"Merin Ann Ninan, Merin Grace Jiji, Thomas Ponnachen Valukattil, Harikumar Sadasivan Pillai Puthenveedu, Sabu Thomas, Binoy Thomas Thundiathu","doi":"10.1007/s10453-024-09810-4","DOIUrl":"10.1007/s10453-024-09810-4","url":null,"abstract":"<div><p>This scientific article presents a comprehensive exploration of the intriguing ecological phenomenon known as \"red rain\", observed in the coastal town located at latitude N 11°.61108 and longitude E 75°.57383 in Kerala, India. The study aims to elucidate the origins, characteristics, and potential environmental implications associated with this phenomenon. Through a meticulous descriptive analysis, incorporating microscopic evaluation, DNA-sequencing, Fourier-transform infrared spectroscopy (FTIR), Gas Chromatography-Mass Spectrometry (GC–MS) analysis, and phylogenetic analysis, we deciphered the underlying factors responsible for the distinct red coloration observed in the rain. Our research findings highlight the presence of specific organic compounds, namely psi-psi Carotene 3,4 didehydro-1,2,7′8'-tetrahydro-1-methoxy-2-oxo and psi-psi and- Carotene 3,3',4,4'-tetradehydro1′2' dihydro 1-hydroxy-1'-methoxy in the algae, <i>Trentepohlia abietina</i>, as the primary contributors to the red color observed in the red rain. The research findings contribute to a deeper understanding of this distinctive occurrence and its implications for the local ecosystem in Kerala.</p></div>","PeriodicalId":7718,"journal":{"name":"Aerobiologia","volume":"41 1","pages":"79 - 88"},"PeriodicalIF":2.2,"publicationDate":"2024-02-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140006585","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}