Relationship among parameters of lake polluted sediments evaluated by multivariate statistical analysis

In the attempt to assess the relationship and interdependency among sediment toxic pollutants, in particular heavy metals, polycyclic aromatic hydrocarbons (PAH), and linear alkyl sulfonates (LAS) and some of the sediment typical components: inorganic carbon (IC), organic material (OM) and acid volatile sulphides (AVS), multivariate techniques of statistical analysis have been applied to a set of chemical data obtained by the analysis of the sediments of the Trasimeno Lake, a central Italy lake characterized by a large surface (128 km(2)) and a low mean depth (about 4.5 m). The results of principal component analysis (PCA) show interrelationships between: OM content and PAH, Pb, and Cu concentrations of the sediments, LAS and AVS, and AVS and IC. The effect of the different sampling periods on sediment composition and contamination level, and the clustering of the sampling sites as a consequence of pollutant load are also shown. The principal component bi-plot of the variables and samples indicates that PAH have the greatest influence on the separation of samples in the different sampling periods.     

Tools based on multivariate statistical analysis for classification of soil and groundwater in Apulian agricultural sites

In this paper, the results obtained from multivariate statistical techniques such as PCA (Principal component analysis) and LDA (Linear discriminant analysis) applied to a wide soil data set are presented. The results have been compared with those obtained on a groundwater data set, whose samples were collected together with soil ones, within the project “Improvement of the Regional Agro-meteorological Monitoring Network (2004–2007)”. LDA, applied to soil data, has allowed to distinguish the geographical origin of the sample from either one of the two macroaeras: Bari and Foggia provinces vs Brindisi, Lecce e Taranto provinces, with a percentage of correct prediction in cross validation of 87%. In the case of the groundwater data set, the best classification was obtained when the samples were grouped into three macroareas: Foggia province, Bari province and Brindisi, Lecce and Taranto provinces, by reaching a percentage of correct predictions in cross validation of 84%. The obtained information can be very useful in supporting soil and water resource management, such as the reduction of water consumption and the reduction of energy and chemical (nutrients and pesticides) inputs in agriculture.     

Delineating the impacts of poultry burial leachate on shallow groundwater in a reclaimed agro-livestock farming area,using multivariate statistical analysis of hydrochemical data

Environmental Science and Pollution Research - Burial is applied to dispose of livestock carcasses due to its convenience and cost efficiency despite concerns about groundwater contamination by...     

A classic critique on concrete adsorbing pollutants emitted by automobiles and statistical envision using trend analysis

Environmental Science and Pollution Research - Globally, road transportation is responsible for about 1/3 of total air pollution, among which Co2 , NoX and SoX are major by volume which are...     

Groundwater quality in Imphal West district, Manipur, India, with multivariate statistical analysis of data

The aim of this paper was to analyze the groundwater quality of Imphal West district, Manipur, India, and assess its suitability for drinking, domestic, and agricultural use. Eighteen physico-chemical variables were analyzed in groundwater from 30 different hand-operated tube wells in urban, suburban, and rural areas in two seasons. The data were subjected to uni-, bi-, and multivariate statistical analysis, the latter comprising cluster analysis (CA), principal component analysis (PCA), and factor analysis (FA). Arsenic concentrations exceed the Indian standard in 23.3 % and the WHO limit in 73.3 % of the groundwater sources with only 26.7 % in the acceptable range. Several variables like iron, chloride, sodium, sulfate, total dissolved solids, and turbidity are also beyond their desirable limits for drinking water in a number of sites. Sodium concentrations and sodium absorption ratio (SAR) are both high to render the water from the majority of the sources unsuitable for agricultural use. Multivariate statistical techniques, especially varimax rotation of PCA data helped to bring to focus the hidden yet important variables and understand their roles in influencing groundwater quality. Widespread arsenic contamination and high sodium concentration of groundwater pose formidable constraints towards its exploitation for drinking and other domestic and agricultural use in the study area, although urban anthropogenic impacts are not yet pronounced.     

Characterizing and locating air pollution sources in a complex industrial district using optical remote sensing technology and multivariate statistical modeling

Emissions of volatile organic compounds (VOCs) are most frequent environmental nuisance complaints in urban areas, especially where industrial districts are nearby. Unfortunately, identifying the responsible emission sources of VOCs is essentially a difficult task. In this study, we proposed a dynamic approach to gradually confine the location of potential VOC emission sources in an industrial complex, by combining multi-path open-path Fourier transform infrared spectrometry (OP-FTIR) measurement and the statistical method of principal component analysis (PCA). Close-cell FTIR was further used to verify the VOC emission source by measuring emitted VOCs from selected exhaust stacks at factories in the confined areas. Multiple open-path monitoring lines were deployed during a 3-month monitoring campaign in a complex industrial district. The emission patterns were identified and locations of emissions were confined by the wind data collected simultaneously. N,N-Dimethyl formamide (DMF), 2-butanone, toluene, and ethyl acetate with mean concentrations of 80.0?±?1.8, 34.5?±?0.8, 103.7?±?2.8, and 26.6?±?0.7 ppbv, respectively, were identified as the major VOC mixture at all times of the day around the receptor site. As the toxic air pollutant, the concentrations of DMF in air samples were found exceeding the ambient standard despite the path-average effect of OP-FTIR upon concentration levels. The PCA data identified three major emission sources, including PU coating, chemical packaging, and lithographic printing industries. Applying instrumental measurement and statistical modeling, this study has established a systematic approach for locating emission sources. Statistical modeling (PCA) plays an important role in reducing dimensionality of a large measured dataset and identifying underlying emission sources. Instrumental measurement, however, helps verify the outcomes of the statistical modeling. The field study has demonstrated the feasibility of using multi-path OP-FTIR measurement. The wind data incorporating with the statistical modeling (PCA) may successfully identify the major emission source in a complex industrial district.     

Assessment of metal pollution based on multivariate statistical modeling of 'hot spot' sediments from the Black Sea

The paper deals with application of different statistical methods like cluster and principal components analysis (PCA), partial least squares (PLSs) modeling. These approaches are an efficient tool in achieving better understanding about the contamination of two gulf regions in Black Sea. As objects of the study, a collection of marine sediment samples from Varna and Bourgas "hot spots" gulf areas are used. In the present case the use of cluster and PCA make it possible to separate three zones of the marine environment with different levels of pollution by interpretation of the sediment analysis (Bourgas gulf, Varna gulf and lake buffer zone). Further, the extraction of four latent factors offers a specific interpretation of the possible pollution sources and separates natural from anthropogenic factors, the latter originating from contamination by chemical, oil refinery and steel-work enterprises. Finally, the PLSs modeling gives a better opportunity in predicting contaminant concentration on tracer (or tracers) element as compared to the one-dimensional approach of the baseline models. The results of the study are important not only in local aspect as they allow quick response in finding solutions and decision making but also in broader sense as a useful environmetrical methodology.     

浙江省船舶修造行业挥发性有机物组分特征及排放系数

基于浙江省29家船舶修造企业的调查数据,研究分析了船舶修造行业挥发性有机物(VOCs)治理情况和VOCs组分特征,并核算了VOCs产生系数和排放系数.结果表明,船舶修造行业VOCs治理设施总体覆盖率为55％,VOCs主要组分为苯系物(BETX)与含氧挥发性有机物(OVOCs).分别以船舶载重量、船舶数量为活动水平时,远...     

Quality assurance of multivariate analytical measurements by principal components analysis

The use of principal components analysis for the quality control of a mass spectrometer is demonstrated and commented upon.     

Objective classification of ecological status in marine water bodies using ecotoxicological information and multivariate analysis

Some relevant shortcomings have been identified in the current approach for the classification of ecological status in marine water bodies, leading to delays in the fulfillment of the Water Framework Directive objectives. Natural variability makes difficult to settle fixed reference values and boundary values for the Ecological Quality Ratios (EQR) for the biological quality elements. Biological responses to environmental degradation are frequently of nonmonotonic nature, hampering the EQR approach. Community structure traits respond only once ecological damage has already been done and do not provide early warning signals. An alternative methodology for the classification of ecological status integrating chemical measurements, ecotoxicological bioassays and community structure traits (species richness and diversity), and using multivariate analyses (multidimensional scaling and cluster analysis), is proposed. This approach does not depend on the arbitrary definition of fixed reference values and EQR boundary values, and it is suitable to integrate nonlinear, sensitive signals of ecological degradation. As a disadvantage, this approach demands the inclusion of sampling sites representing the full range of ecological status in each monitoring campaign. National or international agencies in charge of coastal pollution monitoring have comprehensive data sets available to overcome this limitation.     

Degradation of ethylenethiourea pesticide metabolite from water by photocatalytic processes

In this study, photocatalytic (photo-Fenton and H₂O₂/UV) and dark Fenton processes were used to remove ethylenethiourea (ETU) from water. The experiments were conducted in a photo-reactor with an 80 W mercury vapor lamp. The mineralization of ETU was determined by total organic carbon analysis, and ETU degradation was qualitatively monitored by the reduction of UV absorbance at 232 nm. A higher mineralization efficiency was obtained by using the photo-peroxidation process (UV/H₂O₂). Approximately 77% of ETU was mineralized within 120 min of the reaction using [H₂O₂]₀ = 400 mg L^?1. The photo-Fenton process mineralized 70% of the ETU with [H₂O₂]₀ = 800 mg L^?1 and [Fe²⁺] = 400 mg L^?1, and there is evidence that hydrogen peroxide was the limiting reagent in the reaction because it was rapidly consumed. Moreover, increasing the concentration of H₂O₂ from 800 mg L^?1 to 1200 mg L^?1 did not enhance the degradation of ETU. Kinetics studies revealed that the pseudo-second-order model best fit the experimental conditions. The k values for the UV/H₂O₂ and photo-Fenton processes were determined to be 6.2 × 10^?4 mg L^?1 min^?1 and 7.7 × 10^?4 mg L^?1 min^?1, respectively. The mineralization of ETU in the absence of hydrogen peroxide has led to the conclusion that ETU transformation products are susceptible to photolysis by UV light. These are promising results for further research. The processes that were investigated can be used to remove pesticide metabolites from drinking water sources and wastewater in developing countries.     

Determination of some pesticide residues in conventional-grown and IPM-grown tomato by using QuEChERS method

The present study was conducted to determine pesticide (emamectin-benzoate, penconazole and imidacloprid) residues over tomatoes by using QuEChERS method. The method was validated by spiking tomato matrix at 0.1, 1.0, and 10.0 MRL levels of the pesticides. Tomatoes were harvested from two conventional and two Integrated Pest Management-grown fields. Laboratory samples were taken from the bulk samples. Analyses of spiked and real-field tomatoes were performed with QuEChERS procedure. Experimental samples were subjected to LC-MS/MS analysis. As indicated in “CAC/GL 40-1993,” representative sample matrix (apple) calibration was used for quantification. The overall recovery was 107.12% with a relative standard deviation of 17.96% (n?=?162). Present values were within the specified recovery ranges (60-140%) and repeatability value of (RSD ≤20%) of SANCO. Analysis of field experiment samples showed that both conventional tomato plots had trace levels (less than MRL) of emamectin-benzoate and imidacloprid, whereas there were not any pesticide residues in both IPM tomato plots     

Evaluation of the Swat River,Northern Pakistan,water quality using multivariate statistical techniques and water quality index (WQI) model

Environmental Science and Pollution Research - This study evaluates the characteristics of water along the Swat River, Northern Pakistan. For this purpose, water samples (n = 30) were...     

Identifying sources of soil inorganic pollutants on a regional scale using a multivariate statistical approach: role of pollutant migration and soil physicochemical properties

Principal components analysis (PCA) and correlation analysis were used to estimate the contribution of four components related to pollutant sources on the total variation in concentrations of Cu, Zn, Pb, Cd, As, Se, Hg, Fe and Mn in surface soil samples from a valley in east China with numerous copper and zinc smelters. Results indicate that when carrying out source identification of inorganic pollutants their tendency to migrate in soils may result in differences between the pollutant composition of the source and the receptor soil, potentially leading to errors in the characterization of pollutants using multivariate statistics. The stability and potential migration or movement of pollutants in soils must therefore be taken into account. Soil physicochemical properties may offer additional useful information. Two different mechanisms have been hypothesized for correlations between soil heavy metal concentrations and soil organic matter content and these may be helpful in interpreting the statistical analysis.     

Reducing the pollution risk of pesticide using nano networks induced by irradiation and hydrothermal treatment

Traditional pesticides (TP) often do not adhere tightly to crop foliage. They can easily enter the surrounding environment through precipitation and volatilization. This can result in the pollution of the surrounding soil, water, and air. To reduce pesticide pollution, we developed a loss-control pesticide (LCP) by adding attapulgite with a nano networks structure fabricated using high energy electron beam (HEEB) irradiation and hydrothermal treatment to TP. HEEB irradiation effectively dispersed originally aggregated attapulgite through modified thermal, charge, and physical effects. Hydrothermal treatment further enhanced the dispersion of attapulgite to form nano porous networks via thermal and wet expansion effects, which are beneficial for pesticide binding. An LCP has improved retention on crop leaf surfaces. It has a higher adhesion capacity, reduced leaching and volatilization, and extended residual activity compared with the TP formulation. The treatment increases the residual activity of pesticides on crop foliage and decreases environmental pollution.     

Identification of stationary sources of air pollutants by concentration statistical analysis

The atmospheric concentrations of benzene, toluene, ethylbenzene and isomeric xylenes (BTEX) in a medium-sized town (S. Maria Capua Vetere, about 32000 inhabitants, Southern Italy) have been determined during working days and weekends in 2006. The procedure used was 24h passive adsorption by samplers distributed throughout the town followed by GC/MS analysis. On a yearly base, the arithmetic mean benzene concentrations were above the limit required by the 2000/69/CE European Directive. The Pearson correlation coefficients of the 24h geometric mean BTEX concentrations were indicative of stationary sources of toluene located in a well circumscribed area of the urban territory, active only during the working days and not officially recognized. The results highlight the effectiveness of the statistical approach used in this study for the identification of pollutant sources.     

建筑陶瓷行业SO2污染物评价及总量控制实用方法

采用高斯点源模型对建陶生产造成的SO2地面浓度增量进行计算.利用比例下降模型计算建陶业的SO2允许排放总量,并根据企业的设备生产能力进行了总量分配,在方法上具有较强的可操作性,计算结果表明,可有效降低所在地区的SO2地面浓度.     

The double-edged role of the digital economy in firm green innovation: micro-evidence from Chinese manufacturing industry

Environmental Science and Pollution Research - The digital economy, which gradually emerged with a new generation of information technologies, has become an unavoidable reality for manufacturing...     

利用人工湿地脱除废水中氨氮和磷的统计分析

论述了利用人工湿地脱除废水中氨氮和正磷酸盐类污染物的统计分析,调查基于国外文献报道的研究数据和实际运行数据.结果表明,污染物输入和输出浓度关系可以由线形规律获得关联,这些污染物因子脱除动力学也可以用适于BOD降解的Kichuth一级脱除方程来描述.由不同人工湿地关联的一级动力学常数具有较好的相关性.     

Error propagation in pesticide residue measurements estimated by computational simulations and inter-laboratory sample analysis

An assessment of the error associated with conventional pesticide residue analysis has been conducted based on computer simulations and inter-laboratory residue analysis. Computational simulations were conducted based on (i) typical performance and regulatory acceptance criteria of analytical methods, and (ii) field residue distributions. In addition, field samples with incurred residues were sent to different private laboratories and the results compared. The relative difference in pesticide residues obtained when samples from the same field or produce lot are analyzed at separate laboratories was used to quantify the uncertainty associated with residue analyses performed using common analytical technology, and methods that are in compliance with current regulatory requirements. The study showed that differences of > 100% are common and should be expected when samples from the same crop are analyzed at different laboratories. The results also suggest that the error within residue measurements can be particularly detrimental when a result is reported near the maximum residue limit (MRL).