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Particle-bound organic and elemental carbons for source identification of PM<0.1μm from biomass combustion

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Journal of Environmental Sciences 2022年第3期34卷 385-393页

作者： Hisam Samae Surajit Tekasakul Perapong Tekasakul Worradorn Phairuang Masami Furuuchi Surapa Hongtieab Department of Chemistry Division of Physical SciencesFaculty of SciencePrince of Songkla UniversityHat YaiSongkhla 90112Thailand Department of Mechanical Engineering Faculty of EngineeringPrince of Songkla UniversityHat YdiSongkhla 90112Thailand Air Pollution and Health Effect Research Center Prince of Songkla UniversityHat YaiSongkhla90112Thailand Faculty of Environmental Management Prince of Songkla UniversityHat YaiSongkhla90112Thailand Faculty of Geoscience and Civil Engineering Institute of Science and EngineeringKanazawa UniversityKakuma-machiKanazawaIshikawa920-1192Japan Department of Geography Faculty of Social SciencesChiang Mai UniversityMuangChiang Mai50200Thailand

Atmospheric nanoparticles(PM50%)with minor contribution from EC(3%-12%).The higher fraction of carbonaceous components was found in the particulates with smaller sizes,and lignin content may relate to concentration of... 详细信息

Atmospheric nanoparticles(PMsources identification of atmospheric particulates is *** of bituminous coal and biomass includ-ing rubber wood,palm kernel,palm fiber,rice stubble,rice straw,maize residue,sugarcane leaves and sugarcane bagasse,which are considered as sources of air quality problems in many countries,was *** of particle-bound chemical components includ-ing organic carbon(OC),elemental carbon(EC),water-soluble ions(NH4^(+),Cl^(-),NO_(3)^(-),SO_(4)^(2-)),elements(Ca,K,Mg,Na)and heavy metals(Cd,Cr,Ni,Pb)were *** results re-vealed that PM50%)with minor contribution from EC(3%-12%).The higher fraction of carbonaceous components was found in the particulates with smaller sizes,and lignin content may relate to concentration of pyrolyzed organic carbon(PyOC)resulting in the differences of OC/EC *** emit-ted from burning palm fiber and rice stubble showed high values of OC/EC and also high ***-carbonaceous components such as Cl^(-),Cr,Ca,Cd,Ni,Na and Mg may be useful as source indicators,but they did not show any correlation with the size of PM.

关键词： PM<0.1 pm Organic carbon Elemental carbon source identification Emission factors

Exploration of the potential application of plutonium isotopes in source identification of sandstorm in the atmosphere of Beijing

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Chinese Chemical Letters 2022年第7期33卷 3516-3521页

作者： Jie Ouyang Yang Shao Min Luo Jilong Zhang Xiongxin Dai Lingling Ma Diandou Xu Beijing Engineering Research Center of Radiographic Techniques and Equipment Institute of High Energy PhysicsChinese Academy of SciencesBeijing 100049China Institute of Environmental and Health Sciences College of Quality and Safety EngineeringChina Jiliang UniversityHangzhou 310018China State Nuclear Security Technology Center Beijing 102401China China Institute for Radiation Protection Taiyuan 030000China

Plutonium(Pu)is an anthropogenic radionuclide which mainly derived from atmospheric nuclear tests in the *** this study,the Pu isotopes(^(239)Pu and^(240)Pu)in aerosol samples collected during the sandstorm and non-sandstorm period were measured by accelerator mass spectrometry(AMS)and the behavior of Pu was *** activity concentrations of ^(239)Pu and ^(240)Pu in the aerosol samples of Beijing were ranged from 0.62 nB q/m^(3)to 99.6 n Bq/m^(3)for ^(239)Pu and 3.51 nBq/m^(3)to 60.23 n Bq/m^(3)for ^(240)Pu,respectively.^(239)Pu and ^(240)Pu concentrations exhibited a remarkable seasonal variation trend,with the higher results showed in spring,and the relatively lower concentrations in *** observed higher concentration of^(239)Pu and^(240)Pu detected in sandstorm samples further indicated Pu was closely related to the occurrence of *** global fallout characteristics of^(240)Pu/^(239)Pu atom ratios(average0.20,ranging from 0.16 to 0.27)in aerosol samples indicating that global fallout was the major source of Pu in the *** aluminum(Al)as an indicator of soil resuspension,significant positive correlation between^(239)Pu and Al(r^(2)=0.934),240Pu and Al(^(r)2=0.525)revealed that soil resuspension was a primary source of atmospheric Pu in *** results implied that the combination of^(239)Pu,^(240)Pu and Al could be used as the potential tracer of sandstorm.

关键词： Plutonium Atmosphere source identification Sandstorm

On Regularization of a source identification Problem in a Parabolic PDE and its Finite Dimensional Analysis

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Journal of Partial Differential Equations 2021年第3期34卷 240-257页

作者： MONDAL Subhankar NAIR M.Thamban Department of Mathematics IIT MadrasChennai 600036India

We consider the inverse problem of identifying a general source term,which is a function of both time variable and the spatial variable,in a parabolic PDE from the knowledge of boundary measurements of the solution on some portion of the lateral *** transform this inverse problem into a problem of solving a compact linear operator *** the regularization of the operator equation with noisy data,we employ the standard Tikhonov regularization,and its finite dimensional realization is done using a discretization procedure involving the space L^(2)(0,τ;L^(2)(Ω)).For illustrating the specification of an a priori source condition,we have explicitly obtained the range space of the adjoint of the operator involved in the operator equation.

关键词： Ill-posed source identification Tikhonov regularization weak solution

Groundwater contaminant source identification based on iterative local update ensemble smoother

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Journal of Groundwater Science and Engineering 2020年第1期8卷 1-9页

作者： YANG Ai-lin JIANG Si-min LIU Jin-bing JIANG Qian-yun ZHOU Ting ZHANG Wen Department of Hydraulic Engineering College of Civil EngineeringTongji UniversityShanghai 200092China Beijing Haidian International School Beijing 100195China Department of Environmental Science and Engineering Fudan UniversityShanghai 200433China

identification of the location and intensity of groundwater pollution source contributes to the effect of pollution remediation,and is called groundwater contaminant source *** is a kind of typical groundwater inverse problem,and the solution is usually *** considering the spatial variability of hydraulic conductivity field,the identification process is more *** this paper,the solution framework of groundwater contaminant source identification is composed with groundwater pollutant transport model(MT3DMS)and a data assimilation method(Iterative local update ensemble smoother,ILUES).In addition,Karhunen-Loève expansion technique is adopted as a PCA method to realize dimension *** practical problems,the geostatistical method is usually used to characterize the hydraulic conductivity field,and only the contaminant source information is inversely calculated in the identification *** this study,the identification of contaminant source information under Kriging K-field is compared with simultaneous identification of source information and *** results indicate that it is necessary to carry out simultaneous identification under heterogeneous site,and ILUES has good performance in solving high-dimensional parameter inversion problems.

关键词： Groundwater contamination Groundwater inverse problem source identification Ensemble smoother Data assimilation

Trace elements spatial distribution characteristics,risk assessment and potential source identification in surface water from Honghu Lake,China

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Journal of Central South University 2018年第7期25卷 1598-1611页

作者： LIU Chao-yang ZHANG Jing-dong LI Fei） YANG Jun QIU Zhen-zhen CAI Ying ZHU Li-yun XIAO Min-si WU Zi-xian Research Center for Environment and Health Zhongnan University of Economics and LawWuhan 430073China College of Environmental Science and Engineering Hunan UniversityChangsha 410082China

Five trace elements including Zn, Cu, Cd, Cr and As were investigated in surface water from ten typical sampling sites in Honghu Lake. The consequence indicated that all of the detected trace element levels were within the allowed standard of China’s safe water guideline. The hazard quotients （HQ） and the hazard index （HI） value levels of all the five heavy metals in all sampling sites did not exceed the acceptable risk limits of non-carcinogenic value through the selected assessment method. Pearson’s correlation analysis and principal component analysis （PCA） indicated that Zn and Cu mainly originated from the natural alluviation and non-point agricultural sources, whereas Cr and As were mainly derived from industrial effluents. Moreover, Cd mainly originated from both non-point agricultural and industrial pollution sources. In addition, cluster analysis （CA） implied that cluster 1 （including S3, S5, S6 and S10） was considered the set of high pollution sites and cluster 2 （including S4 and S9） was identified as the set of moderate pollution sites.

关键词： spatial distribution characteristic risk assessment source identification trace elements Honghu Lake

source identification of Network Diffusion Processes with Partial Observations

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Source Identification of Network Diffusion Processes with Pa...

Inversion method for multi-point source pollution identification:Sensitivity analysis and application to European Tracer Experiment data

第36届中国控制会议

作者： Chaoyi Shi Qi Zhang Tianguang Chu College of Engineering Peking University

ISBN: (纸本)9781538629185

In this paper,we study the problem of identifying the source of network diffusion processes by using the contact networks and sampled *** dynamic processes are described by the susceptible-infected（SI） model and a maximum likelihood（ML） estimator is formulated for identification of the *** propose a two-stage method that first locates a set of suspected source nodes and then identifies the infection source from the candidate source nodes by using Markov random field *** on regular tree and real-world networks verify the effectiveness of our approach.

关键词： source identification Susceptible-infected(SI) model Maximum likelihood Markov random fields

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Atmospheric and Oceanic Science Letters 2022年第3期15卷 31-36页

作者： Jilin Wang Juanjuan Liu Bin Wang Wei Cheng Jiping Zhang The State Key Laboratory of Numerical Modeling for Atmospheric Sciences and Geophysical Fluid Dynamics Institute of Atmospheric PhysicsChinese Academy of SciencesBeijingChina College of Earth and Planetary Sciences University of Chinese Academy of SciencesBeijingChina Beijing Institute of Applied Meteorology BeijingChina College of Environmental Sciences and Engineering Peking UniversityBeijingChina

Fast and accurate identification of unknown pollution sources plays a crucial role in the emergency response and source control of air *** this work,the applicability of a previously proposed two-step inversion method is investigated with sensitivity experiments and real data from the first release of the European Tracer Experiment(ETEX-1).The two-step inversion method is based on the principle of least squares and carries out additional model correction through the residual iterative *** evaluate its performance,its retrieval results are compared with those of two other existing *** is shown that for those cases with richer measurements,all three methods are less sensitive to errors,while for cases where measurements are sparse,their retrieval accuracy will rapidly decrease as errors *** the results of sensitivity experiments,the new method provides higher estimation accuracy and a more stable performance than the other two *** new method presents the smallest maximum location error of 18.20 km when the amplitude of the measurement error increases to 100%,and 22.67 km when errors in the wind fields increase to 200%.Moreover,when applied to ETEX-1 data,the new method also exhibits good performance,with a location error of 4.71 km,which is the best estimation with respect to source location.

关键词： source identification Multi-point source pollution Sensitivity analysis European Tracer Experiment

Rapid identification of single constant contaminant source by considering characteristics of real sensors

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Journal of Central South University 2012年第3期19卷 593-599页

作者：蔡浩李先庭孔令娟马晓钧邵晓亮 Department of Building Science School of ArchitectureTsinghua University Engineering Institute of Engineering Corps PLA University of Science&Technology Nanjing Artillery Academy

For the release of hazardous contaminant indoors, source identification is critical for developing effective response measures. A method which can quickly and accurately identify the position, emission rate, and release time of a single constant contaminant source by using real sensors was presented. The method was numerically demonstrated and validated by a case study of contaminant release in a three-dimensional office. The effects of the measurement errors and total sampling period of sensor on the performance of source identification were thoroughly studied. The results indicate that the adverse effects of the measurement errors can be mitigated by extending the total sampling period. For reaching a desirable accuracy of source identification, the total sampling period should exceed a certain threshold, which can be determined by repeatedly running the identification method tmtil the results tend to be stable. The method presented can contribute to develop an onsite source identification system for protecting occupants from indoor releases.

关键词： source identification contaminant source indoor environment computational fluid dynamics (CFD) air distribution

Chemical formation and source apportionment of PM_(2.5) at an urban site at the southern foot of the Taihang mountains

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Journal of Environmental Sciences 2021年第5期33卷 20-32页

作者： Xiaoyong Liu Mingshi Wang Xiaole Pan Xiyue Wang Xiaolong Yue Donghui Zhang Zhigang Ma Yu Tian Hang Liu Shandong Lei Yuting Zhang Qi Liao Baozhu Ge Dawei Wang Jie Li Yele Sun Pingqing Fu Zifa Wang Hong He Center for Excellence in Regional Atmospheric Environment Institute of Urban EnvironmentChinese Academy of SciencesXiamen 361021China State Key Laboratory of Atmospheric Boundary Layer Physics and Atmospheric Chemistry Institute of Atmospheric PhysicsChinese Academy of SciencesBeijing 100029China Henan Polytechnic University Jiaozuo 454003China Jiaozuo Ecological Environment Monitoring Center Jiaozuo 454003China Jiaozuo Environmental Science Research Institute Jiaozuo 454003China Research Center for Eco-Environmental Sciences Chinese Academy of SciencesBeijing 100085China Institute of Surface-Earth System Science Tianjin UniversityTianjin 300072China University of Chinese Academy of Sciences Beijing 100049China College of Earth Sciences University of Chinese Academy of SciencesBeijing 100049China

The region along the Taihang Mountains in the North China Plain(NCP) is characterized by serious fine particle pollution. To clarify the formation mechanism and controlling factors, an observational study was conducted to investigate the physical and chemical properties of the fine particulate matter in Jiaozuo city, China. Mass concentrations of the water-soluble ions(WSIs) in PM_(2.5) and gaseous pollutant precursors were measured on an hourly basis from December 1, 2017, to February 27, 2018. The positive matrix factorization(PMF) method and the FLEXible PARTicle(FLEXPART) model were employed to identify the sources of PM_(2.5). The results showed that the average mass concentration of PM_(2.5) was 111 μg/m^(3) during the observation period. Among the major WSIs, sulfate, nitrate, and ammonium(SNA) constituted 62% of the total PM_(2.5) mass, and NO_(3)^(-) ranked the highest with an average contribution of 24.6%. NH_(4)^(+) was abundant in most cases in Jiaozuo. According to chemical balance analysis, SO_(2)-4, NO_(3)^(-), and Cl^(-) might be present in the form of(NH_4)_(2)SO_4, NH_4NO_3, NH_4Cl, and KCl. The liquid-phase oxidation of SO_(2) and NO_(2) was severe during the haze period. The relative humidity and pH were the key factors influencing SO_(4)^(2-) formation. We found that NO_(3)^(-) mainly stemmed from homogeneous gas-phase reactions in the daytime and originated from the hydrolysis of N_(2)O_5 in the nighttime, which was inconsistent with previous studies. The PMF model identified five sources of PM_(2.5) : secondary origin(37.8%), vehicular emissions(34.7%), biomass burning(11.5%), coal combustion(9.4%), and crustal dust(6.6%).

关键词： PM_(2.5) Chemical components source identification