Integrating stable isotopes and factor analysis to delineate the groundwater provenance and pollution sources in the northwestern part of the Amman-Al Zarqa Basin, Jordan

Globally,groundwater contamination by nitrate is one of the most widespread environmental problems,particularly in arid and semiarid areas,which are characterized by low amounts of rainfall and groundwater recharge.The stable isotope composition of groundwater(δ2H-H2O andδ18O-H2O)and dissolved nitrate(δ15N-NO3–andδ18O-NO3–)and factor analysis(FA)were applied to explore groundwater provenance,pollution,and chemistry evolution in the northwestern part of the Amman-Al Zarqa Basin,Jordan.In this study,we collected 23 samples from the Lower Ajloun aquifer in 2021,including 1 sample from a groundwater well and 22 samples from springs.These samples were tested for electrical conductivity,total dissolved solids,pH,temperature,dissolved oxygen,the concentration of major ions(Ca2+,Mg2+,Na+,K+,HCO3–,Cl–,SO42–,and NO3–),and the stable isotope composition of groundwater and dissolved nitrate.The results revealed that groundwater in the study area is mainly Ca–Mg–HCO3 type and can be classified as fresh water,hard water,and very hard water.The range and average concentration of NO3–were 3.5–230.8 and 50.9 mg/L,respectively.Approximately 33%of the sampling points showed NO3–levels above the maximum allowable concentration of 50.0 mg/L set by the World Health Organization(WHO)guidelines for drinking water quality.The values ofδ18O-H2O andδ2H-H2O showed that groundwater in the study area is part of the current water cycle,originating in the Mediterranean Sea,with significant evaporation,orographic,and amount effects.The values of the stable isotope composition of NO3–corresponded toδ15N-NO3–andδ18O-NO3–values produced by the nitrification process of manure or septic waste and soil NH4+.The FA performed on the hydrochemical parameters and isotope data resulted in three main factors,with Factor 1,Factor 2,and Factor 3,accounting for 50%,21%,and 11%of the total variance,respectively.Factor 1 was considered human-induced factor,named"pollution factor",whereas Factor 2,named"conservative fingerprint factor",and Factor 3,named"hardness factor",were considered natural factors.This study will help local researchers manage groundwater sustainably in the study area and other similar arid and semiarid areas in the world.

An improved genetic algorithm for searching for pollution sources

As an optimization method that has experienced rapid development over the past 20 years, the genetic algorithm has been successfully applied in many fields, but it requires repeated searches based on the characteristics of high-speed computer calculation and conditions of the known relationship between the objective function and independent variables. There are several hundred generations of evolvement, but the functional relationship is unknown in pollution source searches. Therefore, the genetic algorithm cannot be used directly. Certain improvements need to be made based on the actual situation, so that the genetic algorithm can adapt to the actual conditions of environmental problems, and can be used in environmental monitoring and environmental quality assessment. Therefore, a series of methods are proposed for the improvement of the genetic algorithm： （1） the initial generation of individual groups should be artificially set and move from lightly polluted areas to heavily polluted areas; （2） intervention measures should be introduced in the competition between individuals; （3） guide individuals should be added; and （4） specific improvement programs should be put forward. Finally, the scientific rigor and rationality of the improved genetic algorithm are proven through an example.

Analysis of Pollution Sources and Countermeasures against Water Pollution in a Small River Basin of Chaohu Lake——A Case Study of the Shiwulihe River

The Shiwulihe River, the inflow river of Chaohu Lake in Hefei City, was taken as an example. Based on the current status of water quali- ty and analysis of pollution sources in the Shiwulihe River, countermeasures and suggestions of controlling water pollution were proposed to provide effective ways for the control of water pollution and restoration of aquatic ecosystem in the Shiwulihe River and other similar rivers flowing into lakes.

Determination of Air Pollutant Concentrations in Plant Species in Relation to Pollution Sources

Air quality has been a major health issue in urban areas in recent decades. Human activities release a large number of pollutants into the atmosphere which has a direct impact on plant health and leads to ecosystem degradation. The objective of this study is to contribute to a better evaluation of the impact of the air quality of the city of Togo on biological resources. The determination of pollutants was done on samples of plant species with a strong link with the source of pollution. The determination of Sulfur dioxide (SO2) was done by the ripper method. The determination of carbon and estimation of CO2 and CO by the colorimetric method. The determination of nitrogen was done by the Kjeldhal method. The results showed that at the industrial level the amount of CO2 in Alternanthera repens is high with a value of 53.3911 mg/ml. On the other hand, the quantity of CO in Senna occidentalis is 44.3619 mg/ml. In Pithecellobium dulce, the quantity of SO2 and NO2 are evaluated respectively to 0.1588 mg/ml and 0.3696 mg/ml. Regarding to the dumps, the quantity of CO2 in Newbouldia laevis is very high with a value of 65.8508 mg/ml. On the other hand the amount of CO in Senna occidentalis is 51.6106 mg/ml. The quantity of SO2 in Newbouldia laevis is 0.2101 mg/ml and NO2 in Ocimum canum is 0.2744 mg/ml. At the level of roads, the quantities of CO2 and CO in Eragrostis tenella are very high with values respectively equal to 74.4092 mg/ml and 62.2654 mg/ml. On the other hand, the amount of NO2 in Amaranthus sp is 0.2304 mg/ml and that of SO2 in Eragrostis Tenella is 0.1691 mg/ml. The use of a plant bioindicator sensitive to pollutants, allowed concluding that the air of the city of Lome is polluted. The concentration of carbon dioxide and carbon monoxide is much more evident in return when the health of plant species is threatened.

Effects of PHC on Water Quality of Jiaozhou Bay Ⅱ. Changing Process of Pollution Sources

Based on investigation data on PHC content in Jiaozhou Bay, China during 1979 -1983, the horizontal distribution and pollution sources of PHC in Jiaozhou Bay were analyzed. The results showed that from 1979 to 1983, PHC in the water body of Jiaozhou Bay was mainly from rivers such as Haibo River, Licun River and Loushan River, and PHC content ranged from 0.10 to 1.10 mg/L. The pollution sources of PHC were serious during 1979 -1981 and then became slight during 1982 -1983. From 1979 -1981 to 1982 -1983, PHC content, horizontal distribution and degree of pollution sources changed, but the input mode of PHC was constant, that is, PHC was brought into Jiaozhou Bay by rivers.

Study on Pollution Sources and Degree of Sediments in Northwestern Rivers Flowing into Taihu Lake

[ Objective] The study aimed to analyze the pollution sources and degree of sediments in seven northwestern rivers flowing into Taihu Lake. [ Method] Based on a survey for the sediments in seven rivers flowing into the northwestern Taihu Lake from 2005 to 2007, the molar ratio of major elements was used to determine the main pollution sources of each channel, and the heavy metal pollution of sediments in the seven rivers was assessed by enrichment coefficient. [ Result] Mashan River, Liangxi River and Xiwan River mainly suffered municipal pollution; Zhihu Port and Caoqiao River were chiefly subjected to industrial pollution; Dapu River and Wujin River were mainly affected by agricultural pollution. In addition, the rivers mainly suffering industrial pollution had the most serious heavy metal pollution, followed by the rivers mainly undergoing agricultural pollu- tion, while the rivers chiefly affected by municipal pollution had the minimum pollution. [ Conclusion] The research could provide scientific references for the control of river pollution by heavy metals along Taihu Lake basin.

Identification of Unknown Groundwater Pollution Sources and Determination of Optimal Well Locations Using ANN-GA Based Simulation-Optimization Model

The linked simulation-optimization model can be used for solving a complex groundwater pollution source identification problem. Advanced simulators have been developed and successfully linked with numerous optimization algorithms for identification of groundwater pollution sources. However, the identification of pollution sources in a groundwater aquifer using linked simulation-optimization model has proven to be computationally expensive. To overcome this computational burden, an approximate simulator, the artificial neural network (ANN) model can be used as a surrogate model to replace the complex time-consuming numerical simulation model. However, for large-scale aquifer system, the performance of the ANN-based surrogate model is not satisfactory when a single ANN model is used to predict the concentration at different observation locations. In such a situation, the model efficiency can be enhanced by developing separate ANN model for each of the observation locations. The number of ANN models is equal to the number of observation wells in the aquifer. As a result, the complexity of the ANN-based simulation-optimization model will be related to the number of observation wells. Thus, this study used a modified formulation to find out the optimal numbers of observation wells which will eventually reduce the computational time of the model. The performance of the ANN-based simulation-optimization model is evaluated by identifying the groundwater pollutant sources of a hypothetical study area. The limited evaluation shows that the model has the potential for field application.

Identification of pollution sources in rivers using a hydrodynamic diffusion wave model and improved Bayesian-Markov chain Monte Carlo algorithm

Water quality restoration in rivers requires identification of the locations and discharges of pollution sources,and a reliable mathematical model to accomplish this identification is essential.In this paper,an innovative framework is presented to inversely estimate pollution sources for both accident preparedness and normal management of the allowable pollutant discharge.The proposed model integrates the concepts of the hydrodynamic diffusion wave equation and an improved Bayesian-Markov chain Monte Carlo method(MCMC).The methodological framework is tested using a designed case of a sudden wastewater spill incident(i.e.,source location,flow rate,and starting and ending times of the discharge)and a real case of multiple sewage inputs into a river(i.e.,locations and daily flows of sewage sources).The proposed modeling based on the improved Bayesian-MCMC method can effectively solve high-dimensional search and optimization problems according to known river water levels at pre-set monitoring sites.It can adequately provide accurate source estimation parameters using only one simulation through exploration of the full parameter space.In comparison,the inverse models based on the popular random walk Metropolis(RWM)algorithm and microbial genetic algorithm(MGA)do not produce reliable estimates for the two scenarios even after multiple simulation runs,and they fall into locally optimal solutions.Since much more water level data are available than water quality data,the proposed approach also provides a cost-effective solution for identifying pollution sources in rivers with the support of high-frequency water level data,especially for rivers receiving significant sewage discharges.

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.

Numerical Simulation of the Settling Flux of Biodeposition in a Bay with Cage Culture Through Similarity Theory and a Simplified Pollution Source

The settling flux of biodeposition affects the environmental quality of cage culture areas and determines their environmental carrying capacity.Simple and effective simulation of the settling flux of biodeposition is extremely important for determining the spatial distribution of biodeposition.Theoretically,biodeposition in cage culture areas without specific emission rules can be simplified as point source pollution.Fluent is a fluid simulation software that can simulate the dispersion of particulate matter simply and efficiently.Based on the simplification of pollution sources and bays,the settling flux of biodeposition can be easily and effectively simulated by Fluent fluid software.In the present work,the feasibility of this method was evaluated by simulation of the settling flux of biodeposition in Maniao Bay,Hainan Province,China,and 20 sampling sites were selected for determining the settling fluxes.At sampling sites P1,P2,P3,P4,P5,Z1,Z2,Z3,Z4,A1,A2,A3,A4,B1,B2,C1,C2,C3 and C4,the measured settling fluxes of biodeposition were 26.02,15.78,10.77,58.16,6.57,72.17,12.37,12.11,106.64,150.96,22.59,11.41,18.03,7.90,19.23,7.06,11.84,5.19 and 2.57 g d^(−1)m^(−2),respectively.The simulated settling fluxes of biodeposition at the corresponding sites were 16.03,23.98,8.87,46.90,4.52,104.77,16.03,8.35,180.83,213.06,39.10,17.47,20.98,9.78,23.25,7.84,15.90,6.06 and 1.65 g d^(−1)m^(−2),respectively.There was a positive correlation between the simulated settling fluxes and measured ones(R=0.94,P=2.22×10^(−9)<0.05),which implies that the spatial differentiation of biodeposition flux was well simulated.Moreover,the posterior difference ratio of the simulation was 0.38,and the small error probability was 0.94,which means that the simulated results reached an acceptable level from the perspective of relative error.Thus,if nonpoint source pollution is simplified to point source pollution and open waters are simplified based on similarity theory,the setting flux of biodeposition in the open waters can be simply and effectively simulated by the fluid simulation software Fluent.

Ecological Remediation Measures for Non-point Source Pollution Based on Source-Sink Landscape Theory: A Case Study of Huanghou Basin

The growth of society and population has led to a range of water pollution issues.Among these,non-point source pollution assessment and treatment pose a particular challenge due to its formation mechanism.This has become a focal point and challenge in water pollution treatment research.The study area for this research was the Huanghou basin in Guizhou Province,southwest China.The land use type of the basin was analyzed using remote sensing technology,and water quality data was collected by distributing points throughout the basin,based on source-sink landscape theory.The distribution map of the basin’s source-sink landscape and the results of water quality data accurately and efficiently identified the areas with high risk of non-point source pollution in the western and southwestern residential and agricultural areas of the upper basin.Hence,a strategy of“increasing sinks and decreasing sources”was proposed.The strategy was implemented at both macro and micro levels to address non-point source pollution in the basin using ecological remediation techniques.The work to control karst rocky desertification should continue at a macro level.The rocky desertification area in the basin should gradually transform into grassland and forested land,while increasing the overall area of the sink landscape.Ecological restoration techniques,such as slope planting,riparian zone vegetation restoration,increasing plant abundance,and restoring aquatic plants,can effectively control non-point source pollution at the micro level.Compared to traditional control methods,this remediation strategy focuses on source and process control.It is more effective and does not require large-scale water pollution control projects,which can save a lot of environmental control funds and management costs.Therefore,it has greater research significance and application value.

Transport Patterns and Potential Sources of Atmospheric Pollution during the ⅩⅩⅣ Olympic Winter Games Period

The attainment of suitable ambient air quality standards is a matter of great concern for successfully hosting the ⅩⅩⅣ Olympic Winter Games(OWG). Transport patterns and potential sources of pollutants in Zhangjiakou(ZJK) were investigated using pollutant monitoring datasets and a dispersion model. The PM_(2.5) concentration during February in ZJK has increased slightly(28%) from 2018 to 2021, mostly owing to the shift of main potential source regions of west-central Inner Mongolia and Mongolian areas(2015–18) to the North China Plain and northern Shanxi Province(NCPS) after 2018.Using CO as an indicator, the relative contributions of the different regions to the receptor site(ZJK) were evaluated based on the source-receptor-relationship method(SRR) and an emission inventory. We found that the relative contribution of pollutants from NCPS increased from 33% to 68% during 2019–21. Central Inner Mongolia(CIM) also has an important impact on ZJK under unfavorable weather conditions. This study demonstrated that the effect of pollution control measures in the NCPS and CIM should be strengthened to ensure that the air quality meets the standard during the ⅩⅩⅣ OWG.

Optimization of Identifying Point Pollution Sources for the Convection-Diffusion-Reaction Equations

In this paper,we consider the optimization problem of identifying the pollution sources of convection-diffusion-reaction equations in a groundwater process.The optimization model is subject to a convection-diffusion-reaction equation with pumping point and pollution point sources.We develop a linked optimization and simulation approach combining with the Differential Evolution(DE)optimization algorithm to identify the pumping and injection rates from the data at the observation points.Numerical experiments are taken with injections of constant rates and timedependent variable rates at source points.The problem with one pumping point and two pollution source points is also studied.Numerical results show that the proposed method is efficient.The developed optimized identification approach can be extended to high-dimensional and more complex problems.

Atmospheric lead pollution in fine particulate matter in Shanghai, China

The Pb-monitoring program was extended for 6 years from 2002 to 2007 at 17 representative urban sites （6 traffic, 5 industrial, and 6 residential sites）, and 3 suburban sites to assess the lead pollution in fine particulate matter （PM2.5） after phasing out leaded gasoline in Shanghai. Compared with Pb levels reported in other places, the Pb pollution in Shanghai is still serious after phasing out leaded gasoline, which remains at high concentration range （213-176 ng/m^3） in PM2.5 in winter. Significant spatial variation of Pb concentrations and strong seasonal variation of higher Pb concentration in winter than that in summer were detected. The size distribution of Pb in particulate matter has a unimodat mode that peaks at approximately 0.154-1.59 μm particle diameter, indicating that Pb is mainly concentrated in fine fraction. Lead in the fine fraction is enriched by a factor of 103-104 relative to Pb abundance in crust. Eight categories of Pb pollution sources were identified in the PM2.5 in the winter of 2007 in Shanghai. The important emission sources among them are vehicle exhaust derived from combustion of unleaded gasoline, metaUurgic industry emission, and coal combustion emission.

Spatiotemporal characteristics of cultivated land use eco-efficiency and its influencing factors in China from 2000 to 2020

Improving cultivated land use eco-efficiency(CLUE)can effectively promote agricultural sustainability,particularly in developing countries where CLUE is generally low.This study used provincial-level data from China to evaluate the spatiotemporal evolution of CLUE from 2000 to 2020 and identified the influencing factors of CLUE by using a panel Tobit model.In addition,given the undesirable outputs of agricultural production,we incorporated carbon emissions and nonpoint source pollution into the global benchmark-undesirable output-super efficiency-slacks-based measure(GB-US-SBM)model,which combines global benchmark technology,undesirable output,super efficiency,and slacks-based measure.The results indicated that there was an upward trend in CLUE in China from 2000 to 2020,with an increase rate of 2.62%.The temporal evolution of CLUE in China could be classified into three distinct stages:a period of fluctuating decrease(2000-2007),a phase of gradual increase(2008-2014),and a period of rapid growth(2015-2020).The major grain-producing areas(MPAs)had a lower CLUE than their counterparts,namely,non-major grain-production areas(non-MPAs).The spatial agglomeration effect followed a northeast-southwest strip distribution;and the movement path of barycentre revealed a"P"shape,with Luoyang City,Henan Province,as the centre.In terms of influencing factors of CLUE,investment in science and technology played the most vital role in improving CLUE,while irrigation index had the most negative effect.It should be noted that these two influencing factors had different impacts on MPAs and non-MPAs.Therefore,relevant departments should formulate policies to enhance the level of science and technology,improve irrigation condition,and promote sustainable utilization of cultivated land.

A distributed non-point source pollution model: calibration and validation in the Yellow River Basin

The applicability of a non-point source pollution model—SWAT(soil and water assessment tools) in a large river basin with high sediment runoff modulus(770 t/km2 in the Yellow River) was examined. The basic database, which includes DEM, soil and landuse map, weather data, and land management data, was established for the study area using GIS. A two-stage “Brute Force' optimization method was used to calibrate the parameters with the observed monthly flow and sediment data from 1992 to 1997. In the process of calibration automated digital filter technique was used to separate direct runoff and base flow. The direct runoff was firstly calibrated, and the base flow, then the total runoff was matched. The sediment yield was calibrated to match well. Keeping input parameters set during the calibration process unchanged, the model was validated with 1998—1999's observed monthly flow and sediment. The evaluation coefficients for simulated and observed flow and sediment showed that SWAT was successfully applied in the study area: relative error was within 20%, coefficient of determination and Nash-Suttcliffe simulation efficiency were all equal to or above 0.70 during calibration and validation period.

Progress in the research on aquatic environmental nonpoint source pollution in China

In this paper, the authors reviewed the development process of China's research on aquatic environmental nonpoint pollution, and the situation of nonpoint source pollution in east China was also analyzed.

Validation of an agricultural non-point source(AGNPS)pollution model for a catchment in the Jiulong River watershed,China

This study tested and evaluated the agricultural non-point source （AGNPS） model for the Wuchuan catchment, a typical agricultural area in the Jiulong River watershed, Fujian Province, China. The AGNPS model was calibrated and validated for the study area with observed data on ten storms. The data on eight storms in 2002 were used for calibration while data on two storms were used for validation of the model. Considering the lack of water quality data over a long-term series, a novel method, comparing an internal nested catchment with its surrounding catchment, was used to supplement the less long-term series data. Dual calibration and validation of the AGNPS model was obtained by this comparison. The results indicate that the correlation coefficients were 0.99 and 0.98 for runoff, 0.94 and 0.95 for the peak runoff rate of the large catchment and the small catchment, respectively, and 0.76 for the sediment of the small catchment only. Each pair of correlation coefficients is homogeneous for the same event for the two catchments. With the exception of the sediment yield and particulate phosphorus, the peak runoff rate and other nutrients were well predicted. Sensitivity analysis showed that the Soil Conservation Service curve number and rainfall quantity were the most sensitive parameters, which resulted in high output variations. Erosivity and other parameters had little influence on the hydrological and quality outputs.