In order to identify the day and night pollution sources of PM10 in ambient air in Longyan City,the authors analyzed the elemental composition of respirable particulate matters in the day and night ambient air samples...In order to identify the day and night pollution sources of PM10 in ambient air in Longyan City,the authors analyzed the elemental composition of respirable particulate matters in the day and night ambient air samples and various pollution sources which were collected in January 2010 in Longyan with inductivity coupled plasma-mass spectrometry（ICP-MS）.Then chemical mass balance（CMB） model and factor analysis（FA） method were applied to comparatively study the inorganic components in the sources and receptor samples.The results of factor analysis show that the major sources were road dust,waste incineration and mixed sources which contained automobile exhaust,soil dust/secondary dust and coal dust during the daytime in Longyan City,China.There are two major sources of pollution which are soil dust and mixture sources of automobile exhaust and secondary dust during the night in Longyan.The results of CMB show that the major sources are secondary dust,automobile exhaust and road dust during the daytime in Longyan.The major sources are secondary dust,soil dust and automobile exhaust during the night in Longyan.The results of the two methods are similar to each other and the results will guide us to plan to control the PM10 pollution sources in Longyan.展开更多
The economics of electrochemical depolymerization of lignin are most likely unfavorable without having control over the oxidation mechanism because many unwanted compounds are generated during depolymerization.Control...The economics of electrochemical depolymerization of lignin are most likely unfavorable without having control over the oxidation mechanism because many unwanted compounds are generated during depolymerization.Control over the depolymerization process can lead to high-yield chemical products like aromatic phenols and carboxylic acids.While previous literature has reported the formation of hydroxyl radicals(·OH)during electrochemical oxidation,the studies have not proved whether·OH or electrocatalysis depolymerizes lignin.This study addresses a critical question:whether·OH radicals or direct electrochemical routes drive depolymerization using a well-studied lignin model compound benzyl phenyl ether.Electrochemical oxidation was performed using a nickel–cobalt(Ni–Co)electrocatalyst at varying electrode potentials.Analysis of oxidation products was conducted using headspace solid-phase micro-extraction(SPME)gas chromatographymass spectrometry(GC–MS).Factor analysis(FA)was applied to the two-way GC–MS data,facilitating a statistical and visual assessment of the variations between samples treated with the radical quencher dimethylsulfoxide(DMSO)and those untreated.This work successfully revealed that·OH radicals primarily contribute to the electrochemical depolymerization of lignin,with direct oxidation occurring to a much lesser extent.This study advances our understanding of the electrochemical oxidation process and underscores the pivotal role of integrating chemometrics,a novel approach to unraveling complex electrochemical reaction mechanisms.These insights are crucial for steering the design of efficient and sustainable lignin depolymerization strategies in biomass valorization.展开更多
Principal component analysis(PCA),factor analysis(FA),latent class analysis(LCA),and latent profile analysis(LPA)are prominent statistical models in the social and behavioral sciences,employed to reveal underlying pat...Principal component analysis(PCA),factor analysis(FA),latent class analysis(LCA),and latent profile analysis(LPA)are prominent statistical models in the social and behavioral sciences,employed to reveal underlying patterns and relationships within extensive datasets.PCA involves reducing observed variables while retaining dataset variance by generating principal components.FA aims to decrease observed variable dimensions by identifying underlying factors.LCA and LPA,respectively,focus on discerning latent classes and profiles based on response patterns to categorical and continuous variables.Recently,latent Dirichlet allocation(LDA)method has gained increasing popularity for its application in analyzing textual data alongside numerical responses,contributing to the extraction of hidden structures within complex textual data.Topic modeling(TM),a broader method,is used to identify underlying themes or topics in text corpora,with LDA representing a specific application of TM.Despite some common goals of uncovering hidden structures,these models vary in statistical theory,algorithms,and applications.This paper seeks to investigate these differences and similarities,facilitating researchers in selecting the appropriate model to address their specific research questions.Each model is introduced first,outlining its statistical form and relevant theory.A comprehensive comparison of these models emphasizing their distinguishing features is provided,followed by the illustration of these models and methods.Finally,practical recommendations are offered to aid researchers in effectively implementing these models in their own research.展开更多
The Beijing“Coal to Electricity”program provides a unique opportunity to explore air quality impacts by replacing residential coal burning with electrical appliances.In this study,the atmospheric ROS(Gas-phase ROS a...The Beijing“Coal to Electricity”program provides a unique opportunity to explore air quality impacts by replacing residential coal burning with electrical appliances.In this study,the atmospheric ROS(Gas-phase ROS and Particle-phase ROS,abbreviated to G-ROS and P-ROS)were measured by an online instrument in parallel with concurrent PM_(2.5) sample collections analyzed for chemical composition and cellular ROS in a baseline year(Coal Use Year-CUY)and the first year following implementation of the“Coal to Electricity”program(Coal Ban Year-CBY).The results showed PM_(2.5) concentrations had no significant difference between the two sampling periods,but the activities of G-ROS,P-ROS,and cellular ROS in CBY were 8.72 nmol H_(2)O_(2)/m^(3),9.82 nmol H 2 O 2/m 3,and 2045.75μg UD/mg PM higher than in CUY.Six sources were identified by factor-analysis from the chemical components of PM_(2.5).Secondary sources(SECs)were the dominant source of PM_(2.5) in the two periods,with 15.90%higher contribution in CBY than in CUY.Industrial Emission&Coal Combustion sources(Ind.&CCs),mainly from regional transport,also increased significantly in CBY.The contributions of Aged Sea Salt&Residential Burning sources to PM_(2.5) decreased 5.31% from CUY to CBY.The correlation results illustrated that Ind.&CCs had significant positive correlations with atmospheric ROS,and SECs significantly associated with cellular ROS,especially nitrates(r=0.626,p=0.000).Therefore,the implementation of the“Coal to Electricity”program reduced PM_(2.5) contributions from coal and biomass combustion,but had little effect on the improvement of atmospheric and cellular ROS.展开更多
With frontal analysis (FA), the dependence of adsorption isotherms of insulin on the composition of mobile phase in reversed phase liquid chromatography (RPLC) has been investigated. This is also a good example to em...With frontal analysis (FA), the dependence of adsorption isotherms of insulin on the composition of mobile phase in reversed phase liquid chromatography (RPLC) has been investigated. This is also a good example to employ the stoichiometric displacement theory (SDT) for investigating solute adsorption in physical chemistry. Six kinds of mobile phase in RPLC were employed to study the effects on the elution curves and adsorption isotherms of insulin. The key points of this paper are: (1) The stability of insulin due to delay time after preparing, the organic solvent concentration, the kind and the concentration of ion pairing agent in mobile phase were found to affect both elution curve and adsorption isotherm very seriously. (2) To obtain a valid and comparable result, the composition of the mobile phase employed in FA must be as same as possible to that in usual RPLC of either analytical scale or preparative purpose. (3) Langmuir Equation and the SDT were employed to imitate these obtained adsorption isotherms. The expression for solute adsorption from solution of the SDT was found to have a better elucidation to the insulin adsorption from mobile phase in RPLC.展开更多
基金Supported by the Natural Basic Research Program of China(No.2005CB422207)the Fund of Eco-enviromental Impacts and Protection in Devoloping and Utilizing of Oil-shale Resources(No.OSR-01-06)
文摘In order to identify the day and night pollution sources of PM10 in ambient air in Longyan City,the authors analyzed the elemental composition of respirable particulate matters in the day and night ambient air samples and various pollution sources which were collected in January 2010 in Longyan with inductivity coupled plasma-mass spectrometry（ICP-MS）.Then chemical mass balance（CMB） model and factor analysis（FA） method were applied to comparatively study the inorganic components in the sources and receptor samples.The results of factor analysis show that the major sources were road dust,waste incineration and mixed sources which contained automobile exhaust,soil dust/secondary dust and coal dust during the daytime in Longyan City,China.There are two major sources of pollution which are soil dust and mixture sources of automobile exhaust and secondary dust during the night in Longyan.The results of CMB show that the major sources are secondary dust,automobile exhaust and road dust during the daytime in Longyan.The major sources are secondary dust,soil dust and automobile exhaust during the night in Longyan.The results of the two methods are similar to each other and the results will guide us to plan to control the PM10 pollution sources in Longyan.
基金supported by the United States National Science Foundation(grant number 1939948)。
文摘The economics of electrochemical depolymerization of lignin are most likely unfavorable without having control over the oxidation mechanism because many unwanted compounds are generated during depolymerization.Control over the depolymerization process can lead to high-yield chemical products like aromatic phenols and carboxylic acids.While previous literature has reported the formation of hydroxyl radicals(·OH)during electrochemical oxidation,the studies have not proved whether·OH or electrocatalysis depolymerizes lignin.This study addresses a critical question:whether·OH radicals or direct electrochemical routes drive depolymerization using a well-studied lignin model compound benzyl phenyl ether.Electrochemical oxidation was performed using a nickel–cobalt(Ni–Co)electrocatalyst at varying electrode potentials.Analysis of oxidation products was conducted using headspace solid-phase micro-extraction(SPME)gas chromatographymass spectrometry(GC–MS).Factor analysis(FA)was applied to the two-way GC–MS data,facilitating a statistical and visual assessment of the variations between samples treated with the radical quencher dimethylsulfoxide(DMSO)and those untreated.This work successfully revealed that·OH radicals primarily contribute to the electrochemical depolymerization of lignin,with direct oxidation occurring to a much lesser extent.This study advances our understanding of the electrochemical oxidation process and underscores the pivotal role of integrating chemometrics,a novel approach to unraveling complex electrochemical reaction mechanisms.These insights are crucial for steering the design of efficient and sustainable lignin depolymerization strategies in biomass valorization.
文摘Principal component analysis(PCA),factor analysis(FA),latent class analysis(LCA),and latent profile analysis(LPA)are prominent statistical models in the social and behavioral sciences,employed to reveal underlying patterns and relationships within extensive datasets.PCA involves reducing observed variables while retaining dataset variance by generating principal components.FA aims to decrease observed variable dimensions by identifying underlying factors.LCA and LPA,respectively,focus on discerning latent classes and profiles based on response patterns to categorical and continuous variables.Recently,latent Dirichlet allocation(LDA)method has gained increasing popularity for its application in analyzing textual data alongside numerical responses,contributing to the extraction of hidden structures within complex textual data.Topic modeling(TM),a broader method,is used to identify underlying themes or topics in text corpora,with LDA representing a specific application of TM.Despite some common goals of uncovering hidden structures,these models vary in statistical theory,algorithms,and applications.This paper seeks to investigate these differences and similarities,facilitating researchers in selecting the appropriate model to address their specific research questions.Each model is introduced first,outlining its statistical form and relevant theory.A comprehensive comparison of these models emphasizing their distinguishing features is provided,followed by the illustration of these models and methods.Finally,practical recommendations are offered to aid researchers in effectively implementing these models in their own research.
基金supported by the National Natural Science Foundation of China(NSFC)(No.41877310)partly by the National Key Research and Development Program of China(No.2016YFC0503600).
文摘The Beijing“Coal to Electricity”program provides a unique opportunity to explore air quality impacts by replacing residential coal burning with electrical appliances.In this study,the atmospheric ROS(Gas-phase ROS and Particle-phase ROS,abbreviated to G-ROS and P-ROS)were measured by an online instrument in parallel with concurrent PM_(2.5) sample collections analyzed for chemical composition and cellular ROS in a baseline year(Coal Use Year-CUY)and the first year following implementation of the“Coal to Electricity”program(Coal Ban Year-CBY).The results showed PM_(2.5) concentrations had no significant difference between the two sampling periods,but the activities of G-ROS,P-ROS,and cellular ROS in CBY were 8.72 nmol H_(2)O_(2)/m^(3),9.82 nmol H 2 O 2/m 3,and 2045.75μg UD/mg PM higher than in CUY.Six sources were identified by factor-analysis from the chemical components of PM_(2.5).Secondary sources(SECs)were the dominant source of PM_(2.5) in the two periods,with 15.90%higher contribution in CBY than in CUY.Industrial Emission&Coal Combustion sources(Ind.&CCs),mainly from regional transport,also increased significantly in CBY.The contributions of Aged Sea Salt&Residential Burning sources to PM_(2.5) decreased 5.31% from CUY to CBY.The correlation results illustrated that Ind.&CCs had significant positive correlations with atmospheric ROS,and SECs significantly associated with cellular ROS,especially nitrates(r=0.626,p=0.000).Therefore,the implementation of the“Coal to Electricity”program reduced PM_(2.5) contributions from coal and biomass combustion,but had little effect on the improvement of atmospheric and cellular ROS.
文摘With frontal analysis (FA), the dependence of adsorption isotherms of insulin on the composition of mobile phase in reversed phase liquid chromatography (RPLC) has been investigated. This is also a good example to employ the stoichiometric displacement theory (SDT) for investigating solute adsorption in physical chemistry. Six kinds of mobile phase in RPLC were employed to study the effects on the elution curves and adsorption isotherms of insulin. The key points of this paper are: (1) The stability of insulin due to delay time after preparing, the organic solvent concentration, the kind and the concentration of ion pairing agent in mobile phase were found to affect both elution curve and adsorption isotherm very seriously. (2) To obtain a valid and comparable result, the composition of the mobile phase employed in FA must be as same as possible to that in usual RPLC of either analytical scale or preparative purpose. (3) Langmuir Equation and the SDT were employed to imitate these obtained adsorption isotherms. The expression for solute adsorption from solution of the SDT was found to have a better elucidation to the insulin adsorption from mobile phase in RPLC.
