The Nested Air Quality Prediction Model System(NAQPMS)was used to investigate the temporal and spatial variations of PM2.5over tropospheric central eastern China in January 2013.The impact of regional transport and it...The Nested Air Quality Prediction Model System(NAQPMS)was used to investigate the temporal and spatial variations of PM2.5over tropospheric central eastern China in January 2013.The impact of regional transport and its implications on pollution prevention and control were also examined.Comparison between simulated and observed PM2.5showed NAQPMS was able to reproduce the evolution of PM2.5during heavy haze episodes.The results indicated that regional transport of PM2.5played an important role in regional haze episodes in the city cluster including Hebei,Beijing and Tianjin(HBT).The cross-city clusters transport outside HBT and transport among cities inside HBT contributed 20%–35%and 26%–35%of PM2.5as compared with local emission,in HBT respectively.To meet the Air Quality Standards for Grade II,90%,90%and65%of emissions would have to be cut down in Hebei,Tianjin and Beijing,if non-control strategy was taken in the surrounding city clusters of HBT.This implicated that control of emissions in one city cluster is not sufficient to reduce regional haze events,and joint efforts among city clusters are essential.Besides regional transports,two-way feedback between boundary-layer evolution and PM2.5also significantly contributed to the formation of heavy hazes,which contributed 30%of monthly average PM2.5concentration in HBT.展开更多
Haze is a pollution weather phenomenon that has been widely concerned by people in recent years. It has a significant impact on people’s production, life, and health. This study focuses on large-scale haze weather th...Haze is a pollution weather phenomenon that has been widely concerned by people in recent years. It has a significant impact on people’s production, life, and health. This study focuses on large-scale haze weather that happened in eastern China in late January 2021. The research uses multi-party data and synoptic analysis methods to analyze the occurrence, evolution, and end of the haze weather. The polar vortex, the change of the atmospheric circulation, the change of the cold air force, the temperature and humidity, and the rain and snow weather are the important reasons for this weathering process. It can be used for reference in future research on haze weather.展开更多
The impact of sea surface temperature(SST)on winter haze in Guangdong province(WHDGD)was analyzed on the interannual scale.It was pointed out that the northern Indian Ocean and the northwest Pacific SST play a leading...The impact of sea surface temperature(SST)on winter haze in Guangdong province(WHDGD)was analyzed on the interannual scale.It was pointed out that the northern Indian Ocean and the northwest Pacific SST play a leading role in the variation of WHDGD.Cold(warm)SST anomalies over the northern Indian Ocean and the Northwest Pacific stimulate the eastward propagation of cold(warm)Kelvin waves through the Gill forced response,causing Ekman convergence(divergence)in the western Pacific,inducing abnormal cyclonic(anticyclonic)circulation.It excites the positive(negative)Western Pacific teleconnection pattern(WP),which results in the temperature and the precipitation decrease(increase)in Guangdong and forms the meteorological variables conditions that are conducive(not conducive)to the formation of haze.ENSO has an asymmetric influence on WHDGD.In El Niño(La Niña)winters,there are strong(weak)coordinated variations between the northern Indian Ocean,the northwest Pacific,and the eastern Pacific,which stimulate the negative(positive)phase of WP teleconnection.In El Niño winters,the enhanced moisture is attributed to the joint effects of the horizontal advection from the surrounding ocean,vertical advection from the moisture convergence,and the increased atmospheric apparent moisture sink(Q2)from soil evaporation.The weakening of the atmospheric apparent heat source(Q1)in the upper layer is not conducive to the formation of inversion stratification.In contrast,in La Niña winters,the reduced moisture is attributed to the reduced upward water vapor transport and Q2 loss.Due to the Q1 increase in the upper layer,the temperature inversion forms and suppresses the diffusion of haze.展开更多
Protein haze was one of the main causes of the instability of white wines. Proteins that caused haze or precipitation in white wines mainly came from grape fruits, and their compositions and contents were affected by ...Protein haze was one of the main causes of the instability of white wines. Proteins that caused haze or precipitation in white wines mainly came from grape fruits, and their compositions and contents were affected by many factors such as fruit diseases, harvesting methods and water stress. Unstable wine proteins were usually pathogenesis-related(PR)proteins of grapes, mainly chitinases and thaumatin-like proteins(TLPs), which had lower isoelectric point(pI)and smaller molecular weight, and were highly resistant to the low pH values of wines and the protease hydrolysis during fermentation. At present, the technology of protein stabilization and clarification in white wines mainly included bentonite fining, heat treatment, enzymatic hydrolysis, polysaccharide treatment and ultrafiltration methods. Among them, the most commonly used method was bentonite treatment. In this paper, the research progresses of the origin, mechanism and influencing factors of the unstable proteins in white wines were summarized, and the applications, advantages and disadvantages of various clarification techniques were also concluded, in order to provide some support for the theoretical and technological research of the protein stability in white wines in the future.展开更多
Manual diagnosis of brain tumors usingmagnetic resonance images(MRI)is a hectic process and time-consuming.Also,it always requires an expert person for the diagnosis.Therefore,many computer-controlled methods for diag...Manual diagnosis of brain tumors usingmagnetic resonance images(MRI)is a hectic process and time-consuming.Also,it always requires an expert person for the diagnosis.Therefore,many computer-controlled methods for diagnosing and classifying brain tumors have been introduced in the literature.This paper proposes a novel multimodal brain tumor classification framework based on two-way deep learning feature extraction and a hybrid feature optimization algorithm.NasNet-Mobile,a pre-trained deep learning model,has been fine-tuned and twoway trained on original and enhancedMRI images.The haze-convolutional neural network(haze-CNN)approach is developed and employed on the original images for contrast enhancement.Next,transfer learning(TL)is utilized for training two-way fine-tuned models and extracting feature vectors from the global average pooling layer.Then,using a multiset canonical correlation analysis(CCA)method,features of both deep learning models are fused into a single feature matrix—this technique aims to enhance the information in terms of features for better classification.Although the information was increased,computational time also jumped.This issue is resolved using a hybrid feature optimization algorithm that chooses the best classification features.The experiments were done on two publicly available datasets—BraTs2018 and BraTs2019—and yielded accuracy rates of 94.8%and 95.7%,respectively.The proposedmethod is comparedwith several recent studies andoutperformed inaccuracy.In addition,we analyze the performance of each middle step of the proposed approach and find the selection technique strengthens the proposed framework.展开更多
The residual resources of ramie fiber-based textile products were used as raw materials.Ramie fiber felt(RF)was modified by NaClO_(2) aqueous solution and then impregnated with water-based epoxy resin(WER).RF/WER tran...The residual resources of ramie fiber-based textile products were used as raw materials.Ramie fiber felt(RF)was modified by NaClO_(2) aqueous solution and then impregnated with water-based epoxy resin(WER).RF/WER transparent composite materials were prepared by lamination hot pressing process.The composite materials’color difference,transmittance,haze,density,water absorption,and mechanical properties were determined to assess the effects of NaClO_(2) treatment and the number of ramie fiber layers on the properties of the prepared composites.The results showed significantly improved optical and mechanical properties of the RF/WER transparent composites after NaClO_(2) treatment.With the increase of ramie fiber layers,the composites’whiteness,transmittance,and water absorption decreased while the haze increased.For material with three layers,the optical transmittance in the visible light region was 82%,and the haze was 96%,indicating the material has both high transmittance and high haze characteristics.The tensile strength increases with the increase of the number of layers,and the tensile strength of the composite with six layers is 243 MPa.This study broadens the scope of application of ramie fiber as a new option for home decoration materials.展开更多
Aiming at the complex variation of haze and the influence of various factors,Xi'an is taken as the research area to study the qualitative and quantitative issues between aerosol optical depth(AOD)and haze before a...Aiming at the complex variation of haze and the influence of various factors,Xi'an is taken as the research area to study the qualitative and quantitative issues between aerosol optical depth(AOD)and haze before and after correction.Combining atmospheric water vapor content(PWV)and meteorological factor data,it is proposed to use"backward screening"method to carry out regression modeling and verification of the revised PM_(2.5) mass concentration,AOD,PWV and meteorological factors.The results show that the correlation between AOD and PM_(2.5) is significantly improved after vertical correction and humidity correction.From the model's decision coefficient R^(2) and the relative error of the estimated PM_(2.5) mass concentration,it can be seen that the estimation model of PM_(2.5) mass concentration based on multiple impact factors is better than the estimation model solely based on AOD.展开更多
Based on the observation data of the annual number of haze days,rainy days,fog days and gale days,sunshine hours,relative humidity and maximum wind speed at Hangzhou station from 1960 to 2021,the variation characteris...Based on the observation data of the annual number of haze days,rainy days,fog days and gale days,sunshine hours,relative humidity and maximum wind speed at Hangzhou station from 1960 to 2021,the variation characteristics of haze days and meteorological influencing factors were studied by mathematical statistical methods such as Mann-Kendall nonparametric test,sliding T test,wavelet analysis and Pearson correlation two-tailed test.The results show that the annual number of haze days generally showed an upward trend,and the climate tendency rate was 20 d/a;there was a sudden change around 2001,and it changed from stable to rapid growth;the number of haze days was the largest in spring and winter,followed by autumn,while it was the smallest in summer.The annual number of haze days had a strongly significant period of 40 a and a mesoscale variation period of 13 a.The number of haze days was negatively correlated with the number of rainy days,fog days and gale days,sunshine hours,relative humidity and maximum wind speed,which passed the 0.05 significance test.In recent 60 years,the number of rainy days and gale days,relative humidity,and maximum wind speed in Hangzhou have decreased,resulting in the weakening of atmospheric wet deposition capacity and power transmission conditions,which provided favorable meteorological conditions for the increase of haze weather.展开更多
This study aims to assess and compare levels of particulate matter(PM10 and PM2.5)in urban and industrial areas in Malaysia during haze episodes,which typically occur in the south west monsoon season.The high concentr...This study aims to assess and compare levels of particulate matter(PM10 and PM2.5)in urban and industrial areas in Malaysia during haze episodes,which typically occur in the south west monsoon season.The high concentrations of atmospheric particles are mainly due to pollution from neighbouring countries.Daily PM concentrations were analysed for urban and industrial areas including Alor Setar,Tasek,Shah Alam,Klang,Bandaraya Melaka,Larkin,Balok Baru,and Kuala Terengganu in 2018 and 2019.The analysis employed spatiotemporal to examine how PM levels were distributed.The data summary revealed that PM levels in all study areas were right-skewed,indicating the occurrence of high particulate events.Significant peaks in PM concentrations during haze events were consistently observed between June and October,encompassing the south west monsoon and inter-monsoon periods.The study on acute respiratory illnesses primarily focused on Selangor.Analysis revealed that Klang had the highest mean number of inpatient cases for acute exacerbation of bronchial asthma(AEBA)and acute exacerbation of chronic obstructive pulmonary disease(AECOPD)with values of 260.500 and 185.170,respectively.Similarly,for outpatient cases of AEBA and AECOPD,Klang had the highest average values of 41.67 and 14.00,respectively.Shah Alam and Sungai Buloh did not show a significant increase in cases during periods of biomass burning.The statistical analysis concluded that higher concentrations of PM were associated with increased hospital admissions,particularly from June to September,as shown in the bar diagram.Haze episodes were associated with more healthcare utilization due to haze-related respiratory illnesses,seen in higher inpatient and outpatient visits(p<0.05).However,seasonal variability had minimal impact on healthcare utilization.These findings offer a comprehensive assessment of PM levels during historic haze episodes,providing valuable insights for authorities to develop policies and guidelines for effective monitoring and mitigation of the negative impacts of haze events.展开更多
基金supported by the CAS Strategic Priority Research Program(Grant Nos.XDB05030200 and XDB05030101)the National Natural Science Foundation of China(Grant No.41278138)
文摘The Nested Air Quality Prediction Model System(NAQPMS)was used to investigate the temporal and spatial variations of PM2.5over tropospheric central eastern China in January 2013.The impact of regional transport and its implications on pollution prevention and control were also examined.Comparison between simulated and observed PM2.5showed NAQPMS was able to reproduce the evolution of PM2.5during heavy haze episodes.The results indicated that regional transport of PM2.5played an important role in regional haze episodes in the city cluster including Hebei,Beijing and Tianjin(HBT).The cross-city clusters transport outside HBT and transport among cities inside HBT contributed 20%–35%and 26%–35%of PM2.5as compared with local emission,in HBT respectively.To meet the Air Quality Standards for Grade II,90%,90%and65%of emissions would have to be cut down in Hebei,Tianjin and Beijing,if non-control strategy was taken in the surrounding city clusters of HBT.This implicated that control of emissions in one city cluster is not sufficient to reduce regional haze events,and joint efforts among city clusters are essential.Besides regional transports,two-way feedback between boundary-layer evolution and PM2.5also significantly contributed to the formation of heavy hazes,which contributed 30%of monthly average PM2.5concentration in HBT.
文摘Haze is a pollution weather phenomenon that has been widely concerned by people in recent years. It has a significant impact on people’s production, life, and health. This study focuses on large-scale haze weather that happened in eastern China in late January 2021. The research uses multi-party data and synoptic analysis methods to analyze the occurrence, evolution, and end of the haze weather. The polar vortex, the change of the atmospheric circulation, the change of the cold air force, the temperature and humidity, and the rain and snow weather are the important reasons for this weathering process. It can be used for reference in future research on haze weather.
基金Guangdong Basic and Applied Basic Research Foundation(2019A1515011808)Science and Technology Planning Program of Guangdong Province(2021B1212020016)。
文摘The impact of sea surface temperature(SST)on winter haze in Guangdong province(WHDGD)was analyzed on the interannual scale.It was pointed out that the northern Indian Ocean and the northwest Pacific SST play a leading role in the variation of WHDGD.Cold(warm)SST anomalies over the northern Indian Ocean and the Northwest Pacific stimulate the eastward propagation of cold(warm)Kelvin waves through the Gill forced response,causing Ekman convergence(divergence)in the western Pacific,inducing abnormal cyclonic(anticyclonic)circulation.It excites the positive(negative)Western Pacific teleconnection pattern(WP),which results in the temperature and the precipitation decrease(increase)in Guangdong and forms the meteorological variables conditions that are conducive(not conducive)to the formation of haze.ENSO has an asymmetric influence on WHDGD.In El Niño(La Niña)winters,there are strong(weak)coordinated variations between the northern Indian Ocean,the northwest Pacific,and the eastern Pacific,which stimulate the negative(positive)phase of WP teleconnection.In El Niño winters,the enhanced moisture is attributed to the joint effects of the horizontal advection from the surrounding ocean,vertical advection from the moisture convergence,and the increased atmospheric apparent moisture sink(Q2)from soil evaporation.The weakening of the atmospheric apparent heat source(Q1)in the upper layer is not conducive to the formation of inversion stratification.In contrast,in La Niña winters,the reduced moisture is attributed to the reduced upward water vapor transport and Q2 loss.Due to the Q1 increase in the upper layer,the temperature inversion forms and suppresses the diffusion of haze.
基金The financial support of this work was received from China Agriculture Research System for Grape Industry (CARS-29)。
文摘Protein haze was one of the main causes of the instability of white wines. Proteins that caused haze or precipitation in white wines mainly came from grape fruits, and their compositions and contents were affected by many factors such as fruit diseases, harvesting methods and water stress. Unstable wine proteins were usually pathogenesis-related(PR)proteins of grapes, mainly chitinases and thaumatin-like proteins(TLPs), which had lower isoelectric point(pI)and smaller molecular weight, and were highly resistant to the low pH values of wines and the protease hydrolysis during fermentation. At present, the technology of protein stabilization and clarification in white wines mainly included bentonite fining, heat treatment, enzymatic hydrolysis, polysaccharide treatment and ultrafiltration methods. Among them, the most commonly used method was bentonite treatment. In this paper, the research progresses of the origin, mechanism and influencing factors of the unstable proteins in white wines were summarized, and the applications, advantages and disadvantages of various clarification techniques were also concluded, in order to provide some support for the theoretical and technological research of the protein stability in white wines in the future.
基金supported by“Human Resources Program in Energy Technology”of the Korea Institute of Energy Technology Evaluation and Planning(KETEP)Granted Financial Resources from theMinistry of Trade,Industry&Energy,Republic of Korea(No.20204010600090).
文摘Manual diagnosis of brain tumors usingmagnetic resonance images(MRI)is a hectic process and time-consuming.Also,it always requires an expert person for the diagnosis.Therefore,many computer-controlled methods for diagnosing and classifying brain tumors have been introduced in the literature.This paper proposes a novel multimodal brain tumor classification framework based on two-way deep learning feature extraction and a hybrid feature optimization algorithm.NasNet-Mobile,a pre-trained deep learning model,has been fine-tuned and twoway trained on original and enhancedMRI images.The haze-convolutional neural network(haze-CNN)approach is developed and employed on the original images for contrast enhancement.Next,transfer learning(TL)is utilized for training two-way fine-tuned models and extracting feature vectors from the global average pooling layer.Then,using a multiset canonical correlation analysis(CCA)method,features of both deep learning models are fused into a single feature matrix—this technique aims to enhance the information in terms of features for better classification.Although the information was increased,computational time also jumped.This issue is resolved using a hybrid feature optimization algorithm that chooses the best classification features.The experiments were done on two publicly available datasets—BraTs2018 and BraTs2019—and yielded accuracy rates of 94.8%and 95.7%,respectively.The proposedmethod is comparedwith several recent studies andoutperformed inaccuracy.In addition,we analyze the performance of each middle step of the proposed approach and find the selection technique strengthens the proposed framework.
基金supported by the National Natural Science Foundation of China (No.32171882)the Science and Technology Innovation Program of Hunan Province of China (2021RC4062)Scientific Research Project of Hunan Provincial Department of Education (20K143).
文摘The residual resources of ramie fiber-based textile products were used as raw materials.Ramie fiber felt(RF)was modified by NaClO_(2) aqueous solution and then impregnated with water-based epoxy resin(WER).RF/WER transparent composite materials were prepared by lamination hot pressing process.The composite materials’color difference,transmittance,haze,density,water absorption,and mechanical properties were determined to assess the effects of NaClO_(2) treatment and the number of ramie fiber layers on the properties of the prepared composites.The results showed significantly improved optical and mechanical properties of the RF/WER transparent composites after NaClO_(2) treatment.With the increase of ramie fiber layers,the composites’whiteness,transmittance,and water absorption decreased while the haze increased.For material with three layers,the optical transmittance in the visible light region was 82%,and the haze was 96%,indicating the material has both high transmittance and high haze characteristics.The tensile strength increases with the increase of the number of layers,and the tensile strength of the composite with six layers is 243 MPa.This study broadens the scope of application of ramie fiber as a new option for home decoration materials.
基金Supported by the Natural Science Foundation of Chongqing,China(cstc2020jcyj-msxmX1044).
文摘Aiming at the complex variation of haze and the influence of various factors,Xi'an is taken as the research area to study the qualitative and quantitative issues between aerosol optical depth(AOD)and haze before and after correction.Combining atmospheric water vapor content(PWV)and meteorological factor data,it is proposed to use"backward screening"method to carry out regression modeling and verification of the revised PM_(2.5) mass concentration,AOD,PWV and meteorological factors.The results show that the correlation between AOD and PM_(2.5) is significantly improved after vertical correction and humidity correction.From the model's decision coefficient R^(2) and the relative error of the estimated PM_(2.5) mass concentration,it can be seen that the estimation model of PM_(2.5) mass concentration based on multiple impact factors is better than the estimation model solely based on AOD.
基金Supported the Key Project of Zhejiang Meteorological Bureau(2019ZD14).
文摘Based on the observation data of the annual number of haze days,rainy days,fog days and gale days,sunshine hours,relative humidity and maximum wind speed at Hangzhou station from 1960 to 2021,the variation characteristics of haze days and meteorological influencing factors were studied by mathematical statistical methods such as Mann-Kendall nonparametric test,sliding T test,wavelet analysis and Pearson correlation two-tailed test.The results show that the annual number of haze days generally showed an upward trend,and the climate tendency rate was 20 d/a;there was a sudden change around 2001,and it changed from stable to rapid growth;the number of haze days was the largest in spring and winter,followed by autumn,while it was the smallest in summer.The annual number of haze days had a strongly significant period of 40 a and a mesoscale variation period of 13 a.The number of haze days was negatively correlated with the number of rainy days,fog days and gale days,sunshine hours,relative humidity and maximum wind speed,which passed the 0.05 significance test.In recent 60 years,the number of rainy days and gale days,relative humidity,and maximum wind speed in Hangzhou have decreased,resulting in the weakening of atmospheric wet deposition capacity and power transmission conditions,which provided favorable meteorological conditions for the increase of haze weather.
文摘This study aims to assess and compare levels of particulate matter(PM10 and PM2.5)in urban and industrial areas in Malaysia during haze episodes,which typically occur in the south west monsoon season.The high concentrations of atmospheric particles are mainly due to pollution from neighbouring countries.Daily PM concentrations were analysed for urban and industrial areas including Alor Setar,Tasek,Shah Alam,Klang,Bandaraya Melaka,Larkin,Balok Baru,and Kuala Terengganu in 2018 and 2019.The analysis employed spatiotemporal to examine how PM levels were distributed.The data summary revealed that PM levels in all study areas were right-skewed,indicating the occurrence of high particulate events.Significant peaks in PM concentrations during haze events were consistently observed between June and October,encompassing the south west monsoon and inter-monsoon periods.The study on acute respiratory illnesses primarily focused on Selangor.Analysis revealed that Klang had the highest mean number of inpatient cases for acute exacerbation of bronchial asthma(AEBA)and acute exacerbation of chronic obstructive pulmonary disease(AECOPD)with values of 260.500 and 185.170,respectively.Similarly,for outpatient cases of AEBA and AECOPD,Klang had the highest average values of 41.67 and 14.00,respectively.Shah Alam and Sungai Buloh did not show a significant increase in cases during periods of biomass burning.The statistical analysis concluded that higher concentrations of PM were associated with increased hospital admissions,particularly from June to September,as shown in the bar diagram.Haze episodes were associated with more healthcare utilization due to haze-related respiratory illnesses,seen in higher inpatient and outpatient visits(p<0.05).However,seasonal variability had minimal impact on healthcare utilization.These findings offer a comprehensive assessment of PM levels during historic haze episodes,providing valuable insights for authorities to develop policies and guidelines for effective monitoring and mitigation of the negative impacts of haze events.
