Changes in Sediment Sources in the Southern Muddy Area of Weihai,China,Since the Late Pleistocene:A Record from Rare Earth Elements

The small muddy areas developed in the southern Shandong Peninsula have attracted increasing attention from researchers because of complex changes in sediment sources driven by sea-level fluctuations and land-sea interactions since the late Pleistocene.This study investigates the evolution of sediment sources and their responses to environmental changes since the late Pleistocene,using core WHZK01 collected from the nearshore muddy area in southern Weihai for rare earth element(REE)analysis.In doing so,this work highlights the changing patterns of material sources and the primary control factors.The results reveal that the sedimentary deposits in core WHZK01 exhibit distinct terrestrial characteristics.Discriminant function analysis(F_(D))and source discrimination dia-grams both suggest that the primary sources of these deposits are the Yellow River and adjacent small and medium-sized rivers,although the sources vary among different sedimentary units.Furthermore,the DU3 layer(17.82-25.10 m)displays typical riverine sedimentation,dominated by terrestrial detrital input,primarily from the local rivers,namely the Huanglei and Muzhu Rivers.The material in the DU2 layer(14.91-17.82 m)is mainly influenced by a mixture of the Qinglong and Yellow Rivers.The DU1 layer(0-14.91 m)is influenced by sea-level changes during the Holocene,with the Yellow River being the primary source,although there is also some input from local rivers.The changes in sea level during the Holocene and the input of Yellow River material carried by the coastal currents of the Yellow Sea are identified as the main controlling factors for the changes in material sources in the study area since the late Pleistocene,with small and mediumsized rivers also exerting some influence on the material sources.The above mentioned findings not only contribute to a better understanding of the source-sink systems of the Yellow River and adjacent small and mediumsized rivers but also deepen our understanding of the late Quaternary land-sea interactions in the Shandong Peninsula.

Occurrence,Spatial Distribution,Sources and Risk Assessment of Per-and Polyfluoroalkyl Substances in Surface Sediments of the Yellow River Delta Wetland

Per-and polyfluoroalkyl substances(PFASs)are emerging persistent organic pollutants(POPs).In this study,47 surface sediment samples were collected from the Yellow River Delta wetland(YRDW)to investigate the occurrence,spatial distribution,potential sources,and ecological risks of PFASs.Twenty-three out of 26 targeted PFASs were detected in surface sediment samples from the YRDW,with totalΣ23PFASs concentrations ranging from 0.23 to 16.30 ng g^(-1) dw and a median value of 2.27 ng g^(-1) dw.Perfluorooctanoic acid(PFOA),perfluorobutanoic acid(PFBA)and perfluorooctanesulfonic acid(PFOS)were the main contaminants.The detection frequency and concentration of perfluoroalkyl carboxylic acids(PFCAs)were higher than those of perfluoroal-kanesulfonic acids(PFSAs),while those of long-chain PFASs were higher than those of short-chain PFASs.The emerging PFASs substitutes were dominated by 6:2 chlorinated polyfluoroalkyl ether sulfonic acid(6:2 Cl-PFESA).The distribution of PFASs is significantly influenced by the total organic carbon content in the sediments.The concentration of PFASs seems to be related to human activities,with high concentration levels of PFASs near locations such as beaches and villages.By using a positive matrix factorization model,the potential sources of PFASs in the region were identified as metal plating mist inhibitor and fluoropolymer manufacturing sources,metal plating industry and firefighting foam and textile treatment sources,and food packaging material sources.The risk assessment indicated that PFASs in YRDW sediments do not pose a significant ecological risk to benthic organisms in the region overall,but PFOA and PFOS exert a low to moderate risk at individual stations.

Identification of the sources of polycyclic aromatic hydrocarbons based on molecular and isotopic characterization from the Yangtze estuarine and nearby coastal areas

Samples of suspended particulate matters （SPMs）, surface sediment and road dust were collected from the Yangtze estuarine and nearby coastal areas, coastal rivers, and central Shanghai. The samples were analyzed for the presence of 16 polycyclic aromatic hydrocarbons （PAHs） in the USEPA priority-controlled list by GC-MS. The compound-specific stable carbon isotopes of the individual PAHs were also analyzed by GC-C-IRMS. The sources of PAHs in the SPMs and surface sediments in the Yangtze estuarine and nearby coastal areas were then identified using multiple source identification techniques that integrated molecular mass indices with organic compound-specific stable isotopes. The results revealed that 3-ring and 4-ring PAH compounds were dominant in the SPMs and surface sediments, which are similar to the PAH compounds found in samples from the Wusong sewage discharge outlet, Shidongkou sewage disposal plant, Huangpu River, coastal rivers and central Shanghai. Principal component analysis （PCA） integrated with molecular mass indices indicated that gasoline, diesel, coal and wood combustion and petroleum-derived residues were the main sources of PAHs in the Yangtze Estuary. The use of PAH compound-specific stable isotopes also enabled identification of the PAHs input pathways. PAHs derived from wood and coal combustion and petroleum-derived residues were input into the Yangtze Estuary and nearby coastal areas by coastal rivers, sewage discharge outlets during the dry season and urban storm water runoff during the flood season. PAHs derived from vehicle emissions primarily accumulated in road dust from urban traffic lines and the commercial district and then entered the coastal area via the northwest prevailing winds in the dry season and storm water runoff during flood season.

Encapsulating the Role of Solution Response Space Roughness on Global Optimal Solution: Application in Identification of Unknown Groundwater Pollution Sources

A major challenge of any optimization problem is to find the global optimum solution. In a multi-dimensional solution space which is highly non-linear, often the optimization algorithm gets trapped around some local optima. Optimal Identification of unknown groundwater pollution sources poses similar challenges. Optimization based methodology is often applied to identify the unknown source characteristics such as location and flux release history over time, in a polluted aquifer. Optimization based models for identification of these characteristics of unknown ground-water pollution sources rely on comparing the simulated effects of candidate solutions to the observed effects in terms of pollutant concentration at specified sparse spatiotemporal locations. The optimization model minimizes the difference between the observed pollutant concentration measurements and simulated pollutant concentration measurements. This essentially constitutes the objective function of the optimization model. However, the mathematical formulation of the objective function can significantly affect the accuracy of the results by altering the response contour of the solution space. In this study, two separate mathematical formulations of the objective function are compared for accuracy, by incorporating different scenarios of unknown groundwater pollution source identification problem. Simulated Annealing (SA) is used as the solution algorithm for the optimization model. Different mathematical formulations of the objective function for minimizing the difference between the observed and simulated pollutant concentration measurements show different levels of accuracy in source identification results. These evaluation results demonstrate the impact of objective function formulation on the optimal identification, and provide a basis for choosing an appropriate mathematical formulation for unknown pollution source identification in contaminated aquifers.

Pollution source identification methods and remediation technologies of groundwater: A review

Groundwater is an important source of drinking water.Groundwater pollution severely endangers drinking water safety and sustainable social development.In the case of groundwater pollution,the top priority is to identify pollution sources,and accurate information on pollution sources is the premise of efficient remediation.Then,an appropriate pollution remediation scheme should be developed according to information on pollution sources,site conditions,and economic costs.The methods for identifying pollution sources mainly include geophysical exploration,geochemistry,isotopic tracing,and numerical modeling.Among these identification methods,only the numerical modeling can recognize various information on pollution sources,while other methods can only identify a certain aspect of pollution sources.The remediation technologies of groundwater can be divided into in-situ and ex-situ remediation technologies according to the remediation location.The in-situ remediation technologies enjoy low costs and a wide remediation range,but their remediation performance is prone to be affected by environmental conditions and cause secondary pollution.The ex-situ remediation technologies boast high remediation efficiency,high processing capacity,and high treatment concentration but suffer high costs.Different methods for pollution source identification and remediation technologies are applicable to different conditions.To achieve the expected identification and remediation results,it is feasible to combine several methods and technologies according to the actual hydrogeological conditions of contaminated sites and the nature of pollutants.Additionally,detailed knowledge about the hydrogeological conditions and stratigraphic structure of the contaminated site is the basis of all work regardless of the adopted identification methods or remediation technologies.

Blind identification and DOA estimation for array sources in presence of scattering

A novel identification method for point source,coherently distributed（CD） source and incoherently distributed（ICD） source is proposed.The differences among the point source,CD source and ICD source are studied.According to the different characters of covariance matrix and general steering vector of the array received source,a second order blind identification method is used to separate the sources,the mixing matrix could be obtained.From the mixing matrix,the type of the source is identified by using an amplitude criterion.And the direction of arrival for the array received source is estimated by using the matching pursuit algorithm from the vectors of the mixing matrix.Computer simulations validate the efficiency of the method.

Sources and health risks of nitrate pollution in surface water in the Weihe River watershed,China

Owing to the significant reductions in streamflow and an increase in human activities in recent years,the quality of surface water in Weihe River continues to pose environmental health concerns.We utilized hydrochemistry and nitrogen and oxygen isotopes to elucidate the status and identify sources of nitrate pollution in the south and north banks for three seasons(flood,dry,and mean-flow periods)in the Weihe River watershed.A Bayesian isotope mixing model was applied to estimate the contributions of four potential NO_(3)-sources to river pollution(manure and sewage,soil nitrogen,inorganic fertilizer,and nitrate in precipitation).The U.S.Environmental Protection Agency(USEPA)evaluation model was implemented to evaluate the health risks associated with nitrate pollution in the surface water.Nitrate pollution was most severe during the dry period because the river flow was small.Due to the influence of the topography and land use type of the Weihe River,the pollution in the main stream was greater than that of the tributaries,and the pollution of the south bank was greater than that of the north bank.During the flood and mean-flow periods,δ^(15)N and δ^(18)O were mainly distributed in the NH_(4)^(+) of the fertilizer and soil nitrogen.During the dry period,δ^(15)N and δ^(18)O were mainly distributed in domestic sewage and manure regions.According to the Stable Isotope Analysis in R(SIAR)model,manure and sewage were the major nitrate sources during the dry period(73%).However,a decrease in the contribution from domestic sewage and manure was observed during the flood period(45%)compared to the dry period,but with a significantly increased contribution from soil nitrogen(23%)and inorganic fertilizer(21%).The health risk value in the dry period was higher than that in the wet and mean flow periods,and children are more susceptible to nitrate pollution than adults.Therefore,reducing the discharge of domestic sewage and manure and improving the utilization rate of nitrogen fertilizers may be effective measures to improve water quality in the watershed.

Identification and spatial patterns of coastal water pollution sources based on GIS and chemometric approach

Comprehensive and joint applications of GIS and chemometric approach were applied in identification and spatial patterns of coastal water pollution sources with a large data set （5 years （2000-2004）, 17 parameters） obtained through coastal water monitoring of Southern Water Control Zone in Hong Kong. According to cluster analysis the pollution degree was significantly different between September-next May （the 1st period） and June-August （the 2nd period）. Based on these results, four potential pollution sources, such as organic/eutrophication pollution, natural pollution, mineral/anthropic pollution and fecal pollution were identified by factor analysis/principal component analysis. Then the factor scores of each monitoring site were analyzed using inverse distance weighting method, and the results indicated degree of the influence by various potential pollution sources differed among the monitoring sites. This study indicated that hybrid approach was useful and effective for identification of coastal water pollution source and spatial patterns.

Active Source Seismic Identification and Automatic Picking of the P-wave First Arrival Using a Convolutional Neural Network

In seismic data processing,picking of the P-wave first arrivals takes up plenty of time and labor,and its accuracy plays a key role in imaging seismic structures.Based on the convolution neural network(CNN),we propose a new method to pick up the P-wave first arrivals automatically.Emitted from MINI28 vibroseis in the Jingdezhen seismic experiment,the vertical component of seismic waveforms recorded by EPS 32-bit portable seismometers are used for manually picking up the first arrivals(a total of 7242).Based on these arrivals,we establish the training and testing sets,including 25,290 event samples and 710,616 noise samples(length of each sample:2 s).After 3,000 steps of training,we obtain a convergent CNN model,which can automatically classify seismic events and noise samples with high accuracy(>99%).With the trained CNN model,we scan continuous seismic records and take the maximum output(probability of a seismic event)as the P-wave first arrival time.Compared with STA/LTA(short time average/long time average),our method shows higher precision and stronger anti-noise ability,especially with the low SNR seismic data.This CNN method is of great significance for promoting the intellectualization of seismic data processing,improving the resolution of seismic imaging,and promoting the joint inversion of active and passive sources.

Numerical and experimental evaluation on methods for parameter identification of thermal response tests

Several parameter identification methods of thermal response test were evaluated through numerical and experimental study.A three-dimensional finite-volume numerical model was established under the assumption that the soil thermal conductivity had been known in the simulation of thermal response test.The thermal response curve was firstly obtained through numerical calculation.Then,the accuracy of the numerical model was verified with measured data obtained through a thermal response test.Based on the numerical and experimental thermal response curves,the thermal conductivity of the soil was calculated by different parameter identification methods.The calculated results were compared with the assumed value and then the accuracy of these methods was evaluated.Furthermore,the effects of test time,variable data quality,borehole radius,initial ground temperature,and heat injection rate were analyzed.The results show that the method based on cylinder-source model has a low precision and the identified thermal conductivity decreases with an increase in borehole radius.For parameter estimation,the measuring accuracy of the initial temperature of the deep ground soil has greater effect on identified thermal conductivity.

Tracing environmental lead sources on the Ao mountain of China using lead isotopic composition and biomonitoring

Atmospheric lead （Pb） and other trace metals can transport over long distance and deposit on remote alpine ecosystems. In this work, the soil profiles, litter and dominant mosses along a large altitude were collected on Ao Mountain, Central China, to obtain the spatial distributions of Pb in these materials, decipher the possible factors controlling the distribution, and quantitatively distinguish the natural versus anthropogenic sources of Pb through the Pb isotopic tracing and biomonitoring. The results show that soil Pb concentrations （mg/kg） decreased significantly with depth, and they were markedly higher in the 0 （42.6 ＋ 2.7） and A （36.4 ＋ 2.2） horizons than in the litter （7.20 ~ 1.9） and mosses （28.o ~ 3-9）- The Pb enrichment in the surface soils （0 and A horizons）, litter and mosses existed in the relatively high altitudes, which was attributed to the influences from atmospheric wet deposition, plants, soil Dhvsicochemical DroDerties and human activitv. ThePb isotopic ratios identified the Pb sources as originating mainly from Chinese coal combustion, mining and smelting. Atmospheric Pb from southeastern, southwestern and northwestern regions could be deposited in the alpine ecosystem by long distance atmospheric transport. The anthropogenic Pb reached over 50% in the 0 and A horizons, and over 70% in the litter and mosses, which corresponded to the concentrations of 26.9, 17.7, 5.92 and 21.2 mg/kg, respectively. The results indicate that the mutual effects of climate and regional human activity could increase the Pb accumulation in remote alpine ecosystems.

Optimization of Well Position and Sampling Frequency for Groundwater Monitoring and Inverse Identification of Contamination Source Conditions Using Bayes’Theorem

Coupling Bayes’Theorem with a two-dimensional(2D)groundwater solute advection-diffusion transport equation allows an inverse model to be established to identify a set of contamination source parameters including source intensity(M),release location(0 X,0 Y)and release time(0 T),based on monitoring well data.To address the issues of insufficient monitoring wells or weak correlation between monitoring data and model parameters,a monitoring well design optimization approach was developed based on the Bayesian formula and information entropy.To demonstrate how the model works,an exemplar problem with an instantaneous release of a contaminant in a confined groundwater aquifer was employed.The information entropy of the model parameters posterior distribution was used as a criterion to evaluate the monitoring data quantity index.The optimal monitoring well position and monitoring frequency were solved by the two-step Monte Carlo method and differential evolution algorithm given a known well monitoring locations and monitoring events.Based on the optimized monitoring well position and sampling frequency,the contamination source was identified by an improved Metropolis algorithm using the Latin hypercube sampling approach.The case study results show that the following parameters were obtained:1)the optimal monitoring well position(D)is at(445,200);and 2)the optimal monitoring frequency(Δt)is 7,providing that the monitoring events is set as 5 times.Employing the optimized monitoring well position and frequency,the mean errors of inverse modeling results in source parameters(M,X0,Y0,T0)were 9.20%,0.25%,0.0061%,and 0.33%,respectively.The optimized monitoring well position and sampling frequency canIt was also learnt that the improved Metropolis-Hastings algorithm(a Markov chain Monte Carlo method)can make the inverse modeling result independent of the initial sampling points and achieves an overall optimization,which significantly improved the accuracy and numerical stability of the inverse modeling results.

Source identification of methane in groundwater in shale gas development areas:A critical review of the state of the art,prospects,and future challenges

The study aims to identify a suitable site for open and bore well in a farmhouseusing ground magnetic survey in south India.It also aims to define depth to granitoid and structural elements which traverse the selected area.Magnetic data(n=84)measured,processed and interpreted as qualitative and quantitatively.The results of total magnetic intensities indicate that the area is composed of linear magnetic lows trending NE-SW direction and circular to semi-circular causative bodies.The magnetic values ranged from-137 nT to 2345 nT with a mean of 465 nT.Reduction to equator shows significant shifting of causative bodies in the southern and northern directions.Analytical signal map shows exact boundary of granitic bodies.Cosine directional filter has brought out structural element trending NE-SW direction.Results of individual profile brought to light structurally weak zone between 90 m and 100 m in all the profile lines.Sudden decrease of magnetic values from 2042 nT to 126 nT noticed in profile line 6 between 20 m and 30 m indicates fault occurrence.Magnetic breaks obtained from these maps were visualized,interpreted and identified two suitable sites for open and bore well.Radially averaged power spectrum estimates depth of shallow and deep sources in 5 m and 50 m,respectively.Euler method has also been applied to estimate depth of granitoid and structural elements using structural indexes 0,1,2,and 3 and found depth ranges from<10 m to>90 m.Study indicates magnetic method is one of the geophysical methods suitable for groundwater exploration and site selection for open and borewells.

Spatial Source Contributions Identification of Acid Rain over the Yangtze River Delta Using a Variety of Methods

The source-receptor relation of wet deposition has been a continuous issue in studies of regional environmental pollution over the past two decades.In the absence of direct observational evidence,the problem is difficult to solve—a topic of broad international debate since the turn of the present century.In the present study,a variety of methods focused on the sources of the wet deposition of acidic substances,like sulfate and nitrate,were used to investigate the precipitation chemistry over the Yangtze River Delta(YRD)during 2007.Back-trajectory analysis associated with the observation data and a source tracing method coupled with the Nested Air Quality Prediction Modeling System(NAQPMS)are proved to be effective methods for investigating the sources of wet deposition over the YRD.Comparison among the back-trajectory,footprint,and NAQPMS results shows good consistency,both qualitatively and quantitatively.The most important contributor to acidic substances in the YRD,as well as heavy acid rain over the region,is the anthropogenic pollution from East China,which accounts for more than 70%.

Source identification of aluminum in surface sediments of the Yellow Sea off the Shandong Peninsula

Surface sediment samples in the near shore area of the north Shandong Peninsula are collected for grain size and element analyses. The results indicate that the surface sediments in the study area are primarily composed of the silt-sized components similar to the Huanghe River. The total concentration of aluminum varies from 5.57% to7.37%（average（6.33 ± 0.40）%）, and its spatial distribution is mainly controlled by the grain size. Correlations between the ratio of aluminum to titanium concentration and aluminum concentration, titanium concentration and the mean grain size indicate that aluminum in the near shore surface sediments is affected majorly by the terrigenous source, and partially by the anthropogenic source. The ratios of aluminum to titanium concentrations are larger than the background value of loess matter at some stations due to the existence of excess aluminum associated with human activities. Thus, the sources of aluminum should be identified firstly when aluminum is used as an index of terrigenous matter even in the near shore area dominated by terrigenous deposits.

Quantitative identification of coal-type gas and oil-type gas in source-mixed gas at the northern margin of Qaidam Basin

The current study tested the gas component and carbon isotopic composition of gas samples from 6 oilgas fields at the northern margin of Qaidam Basin, and established a chart to quantitatively identify the mixing ratio of source-mixed gas. Besides, this research quantitatively investigated the natural gas generated by different types of organic matter. The results show that different ratios of source-mixed gas exist in the 6 oil-gas fields at the northern margin of Qaidam Basin. Among them, Mabei has the highest mixing ratio of coal-type gas, followed by Nanbaxian, Mahai, Lenghu-4, Lenghu-3 and Lenghu-5, with the ratios of coal-type gas 91%, 87%, 83%, 66%, 55% and 36%, respectively. Lenghu-3 and Lenghu-4 oil-gas fields were mainly filled by coal-type gas earlier. For Lenghu-3, the gas was mainly generated from low matured source rocks in lower Jurassic Series of Lengxi sub-sag. For Lenghu-4, the gas was mainly generated from humus-mature source rocks in lower Jurassic Series of the northern slope of Kunteyi sub-sag. Gas in Lenghu-5 was mainly later filled oil-type gas, which was generated from high matured sapropelics in lower Jurassic Series of Kunteyi sub-sag. Earlier filled coal-type gas was the main part of Mahai, Nanbaxian and Mabei oil-gas fields. Gas source of Mahai was mainly generated from high mature humics in lower Jurassic Series of Yibei sub-sag; for Nanbaxian, the gas was mainly generated from high matured humics in middle-lower Jurassic Series of Saishiteng sub-sag; for Mabei, the gas was mainly generated from humus-mature source rocks in middle Jurassic Series of Yuqia sub-sag.

Artificial Neural Network Method Based on Expert Knowledge and Its Application to Quantitative Identification of Potential Seismic Sources

In this paper,an approach is developed to optimize the quality of the training samples in the conventional Artificial Neural Network(ANN)by incorporating expert knowledge in the means of constructing expert-rule samples from rules in an expert system,and through training by using these samples,an ANN based on expert-knowledge is further developed.The method is introduced into the field of quantitative identification of potential seismic sources on the basis of the rules in an expert system.Then it is applied to the quantitative identification of the potential seismic sources in Beijing and its adjacent area.The result indicates that the expert rule based on ANN method can well incorporate and represent the expert knowledge in the rules in an expert system,and the quality of the samples and the efficiency of training and the accuracy of the result are optimized.

New Individual Identification Method of Radiation Source Signal Based on Entropy Feature and SVM

In this paper,according to the defect of methods which have low identification rate in low SNR,a new individual identification method of radiation source based on information entropy feature and SVM is presented. Firstly,based on the theory of multi-resolution wavelet analysis,the wavelet power spectrum of noncooperative signal can be gotten. Secondly,according to the information entropy theory,the wavelet power spectrum entropy is defined in this paper. Therefore,the database of signal's wavelet power spectrum entropy can be built in different SNR and signal parameters. Finally,the sorting and identification model based on SVM is built for the individual identification of radiation source signal. The simulation result indicates that this method has a high individual's identification rate in low SNR,when the SNR is greater than 4 dB,the identification rate can reach 100%. Under unstable SNR conditions,when the range of SNR is between 0 dB and 24 dB,the average identification rate is more than 92. 67%. Therefore,this method has a great application value in the complex electromagnetic environment.

Identification of diesel front sound source based on continuous wavelet transform

Acoustic signals from diesel engines contain useful information but also include considerable noise components To extract information for condition monitoring purposes, continuous wavelet transform (CWT) is used for the characterization of engine acoustics. This paper first reviews CWT characteristics represented by short duration transient signals. Wavelet selection and CWT are then implemented and wavelet transform is used to analyze the major sources of the engine front's exterior radiation sound. The research provides a reliable basis for engineering practice to reduce vehicle sound level. Comparison of the identification results of the measured acoustic signals with the identification results of the measured surface vibration showed good agreement.

Spatial Distribution and Risk Assessment of Heavy Metals in Paddy Soils of Yongshuyu Irrigation Area from Songhua River Basin,Northeast China

There is an increasing concern for potentially hazardous metals pollution, which can threaten crops production and human health. In this study, the spatial distribution and environmental risks of eight heavy metals in surface soil samples collected from the paddy fields in Yongshuyu irrigation area, Northeast China were investigated. The mean concentrations of Pb, Cr, Cu, Ni, Zn, Cd, Hg and As were 34.6 ± 4.67, 82.8 ± 9.51, 17.3 ± 4.09, 21.2 ± 12.0, 88.6 ± 17.9, 0.18 ± 0.15, 0.22 ± 0.07 and 8.77 ± 2.47 mg/kg, respectively, which were slightly higher than their corresponding background values of Jilin Province, indicating enrichment of these metals in the paddy soils, especially for Ni, Cd and Hg. The spatial distribution of heavy metals was closely correlated with local anthropogenic activities, such as agricultural production, mining and transportation. The hot-spot areas of As and Cd were mainly concentrated in the up-midstream where were associated with agricultural activities. Cr and Cu showed similar spatial distributions with hot-spot areas distributed the whole irrigation area uniformly. Ni was mainly distributed in the downstream where Ni quarries concentrated, while the spatial distribution patterns of Hg was mainly located in the upstream and downstream where the soil was significantly influenced by irrigation and coal mining emission. The spatial distributions of Pb and Zn were mainly concentrated along the highway side. The pollution levels of Yongshuyu irrigation area were estimated through index of geo-accumulation(Igeo), Nemerow integrated pollution index(NIPI) and potential ecological risk index(PERI). The results showed that Cd and Hg were the main pollutants in the study area. Health risk assessment results indicated that children were in higher non-carcinogenic and carcinogenic risks than adults with the carcinogenic metal of As. Ingestion was the main exposure pathway to non-carcinogenic and carcinogenic risk for both adults and children. Principal component analysis(PCA) indicated that Cr and Cu were mainly from parent materials, while Cd and As were mainly affected by agricultural activities. Pb and Zn were controlled by traffic activities, and the accumulations of Ni and Hg were associated with mining activities. This study would be valuable for preventing heavy metals inputs and safety in rice production of the Songhua river basin.