Atmosphere最新文献

{"title":"Concurrent Particulate Matter and Heat Exposure in Working and Non-working Women in Rural Guatemala.","authors":"Jaime Butler-Dawson, Grant Erlandson, Diana Jaramillo, Laura Calvimontes, Daniel Pilloni, James Seidel, Colton Castro, Karely Villarreal Hernandez, Lyndsay Krisher, Stephen Brindley, Miranda Dally, Alex Cruz, Katherine A James, Lee S Newman, Joshua Schaeffer, John L Adgate","doi":"10.3390/atmos15101175","DOIUrl":"10.3390/atmos15101175","url":null,"abstract":"<p><p>High temperatures and air pollution exposure are individually known risks to human health, with amplifying adverse health effects during periods of co-exposure. This study compared co-occurring individual-level exposures to particulate matter (PM₅, aerodynamic diameter of ≤ 5 micrometers) and heat among women in residential and agricultural settings in Guatemala. We measured personal and ambient exposure to PM₅, temperature, and humidity among 21 female sugarcane workers in the fields and on their off days. We measured similar exposures among a group of 30 community members not involved in sugarcane work. We collected 171 personal PM₅ measurements across 18 sampling days. The median workday personal PM₅ concentration was 271 μg/m³, which was 3.6-fold higher than ambient area levels in the fields. The median personal PM₅ concentration was 95.8 ug/m³ for off-work days and 83.5 ug/m³ for community days. The average workday individual-level temperature and humidity were 39.4°C and 82.4%, respectively, with significantly lower temperatures on off-work and community days. The women workers and community members were exposed to high levels of PM₅ and heat in both occupational and residential settings. Research needs to consider individual-level exposures at both work and home to help tailor more effective comprehensive prevention efforts to reduce risks.</p>","PeriodicalId":8580,"journal":{"name":"Atmosphere","volume":"15 10","pages":""},"PeriodicalIF":2.6,"publicationDate":"2024-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12448059/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145111907","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Effects of Wildfire Smoke on Volatile Organic Compound (VOC) and PM2.5 Composition in a United States Intermountain Western Valley and Estimation of Human Health Risk.","authors":"Damien T Ketcherside, Dylan D Miller, Dalynn R Kenerson, Phillip S Scott, John P Andrew, Melanie A Y Bakker, Brandi A Bundy, Brian K Grimm, Jiahong Li, Laurel A Nuñez, Dorian L Pittman, Reece P Uhlorn, Nancy A C Johnston","doi":"10.3390/atmos15101172","DOIUrl":"10.3390/atmos15101172","url":null,"abstract":"<p><p>With warmer and drier climate there has been an increase in wildfire events in the Northwest US, posing a potential health risk to downwind communities. The Lewis-Clark Valley (LCV), a small metropolitan area on the Washington/Idaho border in the United States Intermountain West region, was studied over the time period of 2017-2018. The main objective was to determine the community's exposure to particulate matter (PM2.5) and volatile organic compounds (VOCs) during wildfire smoke events and estimate the associated health risk. VOCs were analyzed in the LCV using sorbent tube sampling and thermal desorption-gas chromatography-mass spectrometry (TD-GC-MS) during several local smoke events in the 2017-2018 fire seasons. PM_2.5 measurements were obtained from nearby agency monitors. PM_2.5 reached up to 200 μg/m³ in 2017 and over 100 μg/m³ in 2018 in the LCV and was observed to be increasing at a rate of 0.10 μg/m³/yr over the past two decades. Benzene, a carcinogen and air toxic, was measured with concentrations up to 11 μg/m³, over ten times the normal level in some instances in the LCV. The health risk in the LCV from benzene was calculated at 7 extra cancers per million for lifetime exposure and 13 extra cancers per million considering all air toxics measured. The other cities monitored showed similar lifetime cancer risk due to benzene of about 6-7 extra cancers per million. This work is important as it measures ground-level exposures of VOCs and demonstrates decreases in PM air quality over time in the region.</p>","PeriodicalId":8580,"journal":{"name":"Atmosphere","volume":"15 10","pages":""},"PeriodicalIF":2.6,"publicationDate":"2024-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13229577/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148155150","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Risk Assessment of Community-Scale High-Temperature and Rainstorm Waterlogging Disasters: A Case Study of the Dongsi Community in Beijing","authors":"Pei Xing, Ruozi Yang, Wupeng Du, Ya Gao, Chunyi Xuan, Jiayi Zhang, Jun Wang, Mengxin Bai, Bing Dang, Feilin Xiong","doi":"10.3390/atmos15091132","DOIUrl":"https://doi.org/10.3390/atmos15091132","url":null,"abstract":"With the advancement of urbanization and acceleration of global warming, extreme weather and climate events are becoming increasingly frequent and severe, and climate risk continues to rise. Each community is irreplaceable and important in coping with extreme climate risk and improving urban resilience. In this study, the Dongsi Community in the functional core area of Beijing was explored, and the risk assessment of high temperatures and rainstorm waterlogging was implemented at the community scale. Local navigation observations were integrated into a theoretical framework for traditional disaster risk assessment. The risk assessment indicator system for community-scale high-temperature and rainstorm waterlogging disasters was established and improved from a microscopic perspective (a total of 22 indicators were selected from the three dimensions of hazard, exposure, and vulnerability). Geographic Information Systems (GIS) technology was used to integrate geographic information, meteorological, planning, municipal, socioeconomic and other multisource information layers, thus enabling more detailed spatial distribution characteristics of the hazard, exposure, vulnerability, and risk levels of community-scale high temperatures and rainstorm waterlogging to be obtained. The results revealed that the high-risk area and slightly high-risk area of high-temperature disasters accounted for 13.5% and 15.1%, respectively. The high-risk area and slightly high-risk area of rainstorm waterlogging disasters accounted for 9.8% and 31.6%, respectively. The high-risk areas common to high temperatures and waterlogging accounted for 3.9%. In general, the risk of high-temperature and rainstorm waterlogging disasters at the community scale showed obvious spatial imbalances; that is, the risk in the area around the middle section of Dongsi Santiao was the lowest, while a degree of high temperatures or rainstorm waterlogging was found in other areas. In particular, the risk of high-temperature and rainstorm waterlogging disasters along Dongsi North Street, the surrounding areas of Dongsi Liutiao, and some areas along the Dongsi Jiutiao route was relatively high. These spatial differences were affected to a greater extent by land cover (buildings, vegetation, etc.) and population density within the community. This study is a useful exploration of climate risk research for resilient community construction, and provides scientific support for the planning of climate-adaptive communities, as well as the proposal of overall adaptation goals, action frameworks, and specific planning strategies at the community level.","PeriodicalId":8580,"journal":{"name":"Atmosphere","volume":"1 1","pages":""},"PeriodicalIF":2.9,"publicationDate":"2024-09-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142248090","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Investigating Radon Concentrations in the Cango Cave, South Africa","authors":"Jacques Bezuidenhout, Rikus le Roux","doi":"10.3390/atmos15091133","DOIUrl":"https://doi.org/10.3390/atmos15091133","url":null,"abstract":"Radon concentrations in the tourist part of the Cango cave were measured using 25 strategically placed electret ion chambers. Airflow rates were also measured and found to be less than 1 m/s throughout the cave. An IDW interpolated radon concentration overlay was constructed using QGIS and overlayed on maps of the cave. The maximum radon concentration of 2625 Bq/m3 was measured in the Grand Hall, located in the central part of the cave following a narrow passage. The initial part of the cave near the entrance exhibited normal cave breathing characteristics, with radon concentrations of less than 300 Bq/m3. The deepest section of the cave, however, demonstrated an unexpected decrease in radon levels, temperature, and humidity. The average radon concentration in the Cango cave, measured at 1265 Bq/m3, is relatively low compared to other caves worldwide that need mitigation measures according to the International Commission on Radiological Protection (ICRP).","PeriodicalId":8580,"journal":{"name":"Atmosphere","volume":"13 1","pages":""},"PeriodicalIF":2.9,"publicationDate":"2024-09-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142248122","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Radon Equilibrium Factor and the Assessment of the Annual Effective Dose at Underground Workplaces","authors":"Agata Grygier, Krystian Skubacz","doi":"10.3390/atmos15091131","DOIUrl":"https://doi.org/10.3390/atmos15091131","url":null,"abstract":"The equilibrium factor F is one of the parameters that should be considered when assessing the effective dose based on radon activity concentration. Since the equilibrium factor in various environments ranges theoretically from a value close to 0 to 1, it is expected that dose assessment based on one recommended coefficient value may lead to an underestimation or overestimation of the dose. That is why it is essential to measure this quantity if the basis for dose assessment is the radon concentration and not the concentration of radon decay products. The equilibrium factors were determined based on measurements of radon activity concentration and potential alpha energy concentration and varied from 0.15 to 0.94, with an arithmetic mean of 0.55. The average effective dose calculated for the employee taking into account these values was 31 mSv, assuming an annual working time of 1800 h. In turn, the average effective dose calculated for the equilibrium factor of 0.2 as recommended by the International Commission on Radiological Protection (ICRP) was equal to 13 mSv.","PeriodicalId":8580,"journal":{"name":"Atmosphere","volume":"41 1","pages":""},"PeriodicalIF":2.9,"publicationDate":"2024-09-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142248089","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"In-Vehicle Air Pollutant Exposures from Daily Commute in the San Francisco Bay Area, California","authors":"Reshmasri Deevi, Mingming Lu","doi":"10.3390/atmos15091130","DOIUrl":"https://doi.org/10.3390/atmos15091130","url":null,"abstract":"With urbanization and increased vehicle usage, understanding the exposure to air pollutants inside the vehicles is vital for developing strategies to mitigate associated health risks. In-vehicle air quality influences the comfort of the driver during long commutes and has gained significant interest. This study focuses on studying in-vehicle air quality in the San Francisco Bay Area in California, an urban setting with significant traffic congestion and varied emission sources and road conditions. Each trip is about 80.5 km (50 miles) in length, with commute times of approximately one hour. Two low-cost portable sensors were employed to simultaneously measure in-vehicle pollutants (PM2.5, PM10, and CO2) during morning and evening rush hours from May 2023 to December 2023. Seasonally averaged PM2.5 varied from 5.07 µg/m3 to 6.55 µg/m3 during morning rush hours and from 4.38 µg/m3 to 4.47 µg/m3 during evening rush hours. In addition, the impacts of local PM2.5, vehicle ventilation settings, and speed of the vehicle on in-vehicle PM concentrations were also analyzed. CO2 buildup in vehicles was studied for two scenarios: one with inside recirculation enabled (RC on) and the other with circulation from outside (RC off). With RC off, CO2 concentrations are largely within the 1100 ppm range recommended by many organizations, while the average CO2 concentrations can be three times high under recirculation mode. This research suggests that low-cost sensors can provide valuable insights into the dynamics of air pollution in the in-vehicle microenvironment, which can better help commuters reduce health risks.","PeriodicalId":8580,"journal":{"name":"Atmosphere","volume":"36 1","pages":""},"PeriodicalIF":2.9,"publicationDate":"2024-09-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142248088","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Emissions of Polychlorinated Dibenzo-p-Dioxins/Dibenzofurans during Coffee Roasting: Exploring the Influence of Roasting Methods and Formulations","authors":"Li-Man Lin, I-Jen Chen, Bo-Wun Huang, Nicholas Kiprotich Cheruiyot, Guo-Ping Chang-Chien","doi":"10.3390/atmos15091127","DOIUrl":"https://doi.org/10.3390/atmos15091127","url":null,"abstract":"Polychlorinated dibenzo-p-dioxin/dibenzofuran (PCDD/F) emissions during the roasting of green Arabica coffee and coffee formulations containing alcohol, sugar, and honey were investigated in this study. Fast and slow roasting methods, which took 5.62 and 9.65 min to achieve a light roast, respectively, were used to evaluate the emissions. The concentrations in the flue gas during the fast roasting of green coffee (0.0296 ng Nm−3 and 0.00364 ng WHO-TEQ Nm−3) were 13.9% and 70.5% higher than during slow roasting, respectively. However, this was only the trend for some formulations, and no significant differences in concentrations were found between the methods at p = 0.05. Thus, the slow roasting method might not necessarily reduce formation when additives are included. The emission factors were 2.86 ng kg−1 and 0.352 ng WHO-TEQ kg−1, and 4.17 ng kg−1 and 0.176 ng WHO-TEQ kg−1 for the fast and slow roasting of green coffee, respectively. Further investigations are warranted to understand the formation mechanism, assess potential health risks, and explore mitigation strategies. These findings have implications for both coffee processing industries and regulatory bodies, as understanding the impact of roasting methods and additives could inform the development of cleaner production practices and targeted emission reduction policies.","PeriodicalId":8580,"journal":{"name":"Atmosphere","volume":"2 1","pages":""},"PeriodicalIF":2.9,"publicationDate":"2024-09-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142248127","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Agricultural Drought Monitoring: A Comparative Review of Conventional and Satellite-Based Indices","authors":"Ali Gholinia, Peyman Abbaszadeh","doi":"10.3390/atmos15091129","DOIUrl":"https://doi.org/10.3390/atmos15091129","url":null,"abstract":"Drought is a natural hazard that causes significant economic and human losses by creating a persistent lack of precipitation that impacts agriculture and hydrology. It has various characteristics, such as delayed effects and variability across dimensions like severity, spatial extent, and duration, making it difficult to characterize. The agricultural sector is especially susceptible to drought, which is a primary cause of crop failures and poses a significant threat to global food security. To address these risks, it is crucial to develop effective methods for identifying, classifying, and monitoring agricultural drought, thereby aiding in planning and mitigation efforts. Researchers have developed various tools, including agricultural drought indices, to quantify severity levels and determine the onset and evolution of droughts. These tools help in early-stage forecasting and ongoing monitoring of drought conditions. The field has been significantly advanced by remote sensing technology, which now offers high-resolution spatial and temporal data, improving our capacity to monitor and assess agricultural drought. Despite these technological advancements, the unpredictable nature of environmental conditions continues to pose challenges in drought assessment. It remains essential to provide an overview of agricultural drought indices, incorporating both conventional methods and modern remote sensing-based indices used in drought monitoring and assessment.","PeriodicalId":8580,"journal":{"name":"Atmosphere","volume":"17 1","pages":""},"PeriodicalIF":2.9,"publicationDate":"2024-09-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142248126","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A New Method Proposed for the Estimation of Exposure to Atmospheric Pollution through the Analysis of Black Pigments on the Lung Surface","authors":"Dunia Waked, Mariana Matera Veras, Paulo Hilário Nascimento Saldiva, Ana Paula Cremasco Takano","doi":"10.3390/atmos15091126","DOIUrl":"https://doi.org/10.3390/atmos15091126","url":null,"abstract":"Megacities can be considered excellent laboratories for studying the effects of the urban environment on human health. Typically, exposure to pollution is estimated according to daily or annual averages of pollutant concentrations, collected at monitoring stations, using satellite data for remote sensing of pollutant levels, considering proximity to major roads, or through personal exposure monitoring with portable sensors. However, these approaches fall short in identifying individual exposure values over a lifetime. It is well established that individuals living in large urban areas inhale atmospheric particles containing carbonaceous components, resulting in the deposition of black pigments in lung tissue, known as black carbon or anthracosis. This study aims to detail the procedures for assessing the deposition of such pigments, which serve as an estimate of an individual’s exposure to atmospheric pollution particles. Data collection involves administering detailed questionnaires and capturing lung images in the autopsy room. The analysis is based on macroscopic quantification of black pigments, supplemented by an evaluation of personal habits and the clinical histories of the individuals. This method of estimating lifetime exposure to inhaled particles provides a valuable tool for understanding the correlation between urban living and its potential health effects.","PeriodicalId":8580,"journal":{"name":"Atmosphere","volume":"16 1","pages":""},"PeriodicalIF":2.9,"publicationDate":"2024-09-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142248129","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Calibration of Typhoon Track Forecasts Based on Deep Learning Methods","authors":"Chengchen Tao, Zhizu Wang, Yilun Tian, Yaoyao Han, Keke Wang, Qiang Li, Juncheng Zuo","doi":"10.3390/atmos15091125","DOIUrl":"https://doi.org/10.3390/atmos15091125","url":null,"abstract":"An accurate forecast of typhoon tracks is crucial for disaster warning and mitigation. However, existing numerical weather prediction models, such as the Weather Research and Forecasting (WRF) model, still exhibit significant errors in track forecasts. This study aims to improve forecast accuracy by correcting WRF-forecasted tracks using deep learning models, including Bidirectional Long Short-Term Memory (BiLSTM) + Convolutional Long Short-Term Memory (ConvLSTM) + Wide and Deep Learning (WDL), BiLSTM + Convolutional Gated Recurrent Unit (ConvGRU) + WDL, and BiLSTM + ConvLSTM + Extreme Deep Factorization Machine (xDeepFM), with a comparison to the Kalman Filter. The results demonstrate that the BiLSTM + ConvLSTM + WDL model reduces the 72 h track prediction error (TPE) from 255.18 km to 159.23 km, representing a 37.6% improvement over the original WRF model, and exhibits significant advantages across all evaluation metrics, particularly in key indicators such as Bias2, Mean Squared Error (MSE), and Sequence. The decomposition of MSE further validates the importance of the BiLSTM, ConvLSTM, WDL, and Temporal Normalization (TN) layers in enhancing the model’s spatio-temporal feature-capturing ability.","PeriodicalId":8580,"journal":{"name":"Atmosphere","volume":"14 1","pages":""},"PeriodicalIF":2.9,"publicationDate":"2024-09-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142248124","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}