Ultrasound-assisted ionic liquid-based microextraction combined with least squares support vector machines regression for the simultaneous determination of aluminum,gallium, and indium in water and coal samples

A new simple and rapid ultrasound-assisted ionic liquid-based microextraction method was applied to preconcentrate aluminum(III), gallium(III), and indium(III) ions from water samples as a prior step to their simultaneous spectrophotometric determination using least squares support vector machines regression. In the novel procedure, 1-hexyl-3-methylimidazolium hexafluorophosphate [C₆MIM][PF₆] was dispersed into the aqueous sample solution as fine droplets by ultrasonication, and the analytes were extracted into the ionic liquid phase after complexation with 1,2,5,8-tetrahydroxy anthraquinone (quinalizarine). After centrifuging, the fine droplets of extractant phase were settled to the bottom of the conical-bottom glass centrifuge tube. The detection limits for Al(III), Ga(III), and In(III) were 1.70, 2.02, and 2.06 ng mL⁻¹, respectively. The precision of the method, evaluated as the relative standard deviation obtained by analyzing a series of ten replicates, was below 3.2% for all elements. The method was successfully applied for the determination of Al(III), Ga(III), and In(III) in real samples.     

某石化化工行业聚集区室内外PM2.5中多环芳烃分布特征及来源

于非采暖季和采暖季分别采集某石化化工行业聚集城市中心城区室内外PM_(2.5)样品,采用高效液相色谱法分析PM_(2.5)上载带的16种PAHs,对其分布特征、来源以及室外PAHs污染对室内污染的贡献进行了初步探讨。结果表明,研究区域非采暖季和采暖季室外PM_(2.5)中ΣPAHs浓度日均值分别为36.3、294 ng/m~3,室内PM_(2.5)中ΣPAHs浓度分别为14.8、84.6 ng/m~3,均以4、5环PAHs为主;室内PAHs主要来自室外渗透污染,但同时明显存在室内排放源贡献;PAHs来源分析进一步证实研究区域PAHs主要来自煤炭、石油等不完全燃烧,采暖季煤炭燃烧源贡献更突出。     

Simultaneous determination of binary solution of triphenylmethane dyes in complex matrices onto magnetic amino-rich SWCNT using second-order calibration method

This study suggested a new method for simultaneous quantification of two dyes in complex matrices using second-order data by spectrophotometry. Second-order data was generated simply without any expensive instrument using two independent variables including wavelength and the monotonic addition of sodium dodecyl sulfate. Solid-phase extraction (SPE) based on amino-rich magnetic single-walled carbon nanotube as an adsorbent was employed prior to second-order data generation. SPE optimization was performed by Box-Behnken design, and parameters and their interaction which were dependent on the simultaneous extraction of dyes were examined. Competitive Langmuir and Freundlich isotherms for a binary system and individual dyes could all represent the equilibrium data well. The second-order data was processed by parallel factor analysis (PARAFAC and PARAFAC2) and multivariate curve resolution-alternating least squares (MCR-ALS). Figures of merit of the model including a limit of detection of 3.0 and 2.5 ng mL^?1 for crystal violet and malachite green, respectively, were estimated using the MCR-ALS method. The combination of the second-order calibration and SPE presents an easy and versatile method for determination of the mixture of two dyes in the presence of uncalibrated interferences in environmental water, synthetic, and fish samples with the recoveries of 94–104.     

环境监测数据线性回归分析中回归模型的比较

应用偏重于优化因变量拟合效果的最小二乘回归分析法对环境监测随机数据样本进行数值评估原则上是不可取的。文章以降水无机阴阳离子电荷平衡分析为例,对最小二乘法、压轴回归法和最小正交平方和法的回归分析结果进行了比较。结果表明,压轴回归分析法适合于处理随机数据样本,得到的回归系数b值较大,变量之间的数值变化关系较为密切。     

南京市大气颗粒物中多环芳烃变化特征

逐月采集南京市大气中不同粒径的颗粒物,采用HPLC分析了2010年每个月PM_(10)和PM_(2.5)颗粒物样品中的多环芳烃(PAHs)的种类和浓度水平。结果表明:PM_(10)中PAHs年均值为25.07 ng/m~3,范围为11.03~53.56 ng/m3;PM_(2.5)中PAHs年均值为19.04 ng/m~3,范围为10.82~36.43 ng/m~3。PM_(10)和PM_(2.5)中PAHs总体浓度有着相似的变化趋势,呈现凹形变化曲线;在南京市大气颗粒物中吸附的PAHs大部分以5~6环的高环数组分为主,大部分PAHs和∑PAHs的相关性较好,年度变化幅度不大,分析结果表明,颗粒物中PAHs的来源与稳定的排放源相关,机动车排放不容忽视,与北方城市燃煤污染有着较大的区别。     

Simultaneous spectrophotometric determination of crystal violet and malachite green in water samples using partial least squares regression and central composite design after preconcentration by dispersive solid-phase extraction

In this paper, a simple, fast, and inexpensive method is introduced for the simultaneous spectrophotometric determination of crystal violet (CV) and malachite green (MG) contents in aquatic samples using partial least squares regression (PLS) as a multivariate calibration technique after preconcentration by graphene oxide (GO). The method was based on the sorption and desorption of analytes onto GO and direct determination by ultraviolet–visible spectrophotometric techniques. GO was synthesized according to Hummers method. To characterize the shape and structure of GO, FT-IR, SEM, and XRD were used. The effective factors on the extraction efficiency such as pH, extraction time, and the amount of adsorbent were optimized using central composite design. The optimum values of these factors were 6, 15 min, and 12 mg, respectively. The maximum capacity of GO for the adsorption of CV and MG was 63.17 and 77.02 mg g^?1, respectively. Preconcentration factors and extraction recoveries were obtained and were 19.6, 98% for CV and 20, 100% for MG, respectively. LOD and linear dynamic ranges for CV and MG were 0.009, 0.03–0.3, 0.015, and 0.05–0.5 (μg mL^?1), respectively. The intra-day and inter-day relative standard deviations were 1.99 and 0.58 for CV and 1.69 and 3.13 for MG at the concentration level of 50 ng mL^?1, respectively. Finally, the proposed DSPE/PLS method was successfully applied for the simultaneous determination of the trace amount of CV and MG in the real water samples.     

Multivariate assessment of polycyclic aromatic hydrocarbons in surface sediments of the Beijiang, a tributary of the Pearl River in Southern China

To estimate the severity of polycyclic aromatic hydrocarbon (PAH) contamination in the upper sediment of the Beijiang River, 42 sediment samples were analyzed for the presence of 16 key PAHs using gas chromatography–mass spectrometry. The concentrations of PAH in the sediment ranged from 44 to 8,921 ng g^?1 dry weight. The four- to six-ring PAHs, contributing >50 % to PAHs in 34 of the 42 sites, were the dominant species. Based on a principal component analysis, combined with multivariate linear regression, it became clear that the most important contributors of PAH were fossil fuel combustion (48 %), diesel emissions plus oil spillage (33 %), and coke combustion (19 %). The surface sediments of Beijiang River were grossly contaminated by PAHs mainly derived from combustion.     

Assessment of Spatiotemporal Varying Relationships Between Rainfall,Land Cover and Surface Water Area Using Geographically Weighted Regression

Traditional regression techniques such as ordinary least squares (OLS) are often unable to accurately model spatially varying data and may ignore or hide local variations in model coefficients. A relatively new technique, geographically weighted regression (GWR) has been shown to greatly improve model performance compared to OLS in terms of higher R ² and lower corrected Akaike information criterion (AIC_C). GWR models have the potential to improve reliabilities of the identified relationships by reducing spatial autocorrelations and by accounting for local variations and spatial non-stationarity between dependent and independent variables. In this study, GWR was used to examine the relationship between land cover, rainfall and surface water habitat in 149 sub-catchments in a predominately agricultural region covering 2.6 million ha in southeast Australia. The application of the GWR models revealed that the relationships between land cover, rainfall and surface water habitat display significant spatial non-stationarity. GWR showed improvements over analogous OLS models in terms of higher R ² and lower AIC_C. The increased explanatory power of GWR was confirmed by the results of an approximate likelihood ratio test, which showed statistically significant improvements over analogous OLS models. The models suggest that the amount of surface water area in the landscape is related to anthropogenic drainage practices enhancing runoff to facilitate intensive agriculture and increased plantation forestry. However, with some key variables not present in our analysis, the strength of this relationship could not be qualified. GWR techniques have the potential to serve as a useful tool for environmental research and management across a broad range of scales for the investigation of spatially varying relationships.     

Using discriminant analysis to assess polycyclic aromatic hydrocarbons contamination in Yongding New River

Yongding New River has been polluted by polycyclic aromatic hydrocarbons (PAHs) which are carcinogenic and mutagenic. In three periods (the abundant water period, mean water period, dry water period), ten sites (totally 30 samples) in Yongding New River were clustered into four categories by hierarchical cluster analysis (hierarchical CA). In the same cluster, the samples had the same approximate contamination situation. In order to eliminate the dimensional differences, the data in each sample, containing 16 kinds of PAHs, were standardized with normal standardization and maximum difference standardization. According to the results of the cubic clustering criterion, pseudo F, and pseudo t ² (PST2), the proper number of clustering for the 30 samples is 4. Before conducting hierarchical CA and K-means cluster analysis on the samples, we used principal component analysis to obtain another group data set. This data set was composed of the principal component scores which are uncorrelated variables. Hierarchical CA and K-means cluster analysis were used to classify the two data sets into four categories. With the classification results of hierarchical CA and K-means cluster analysis, discriminant analysis is applied to determine which method was better for normalization of the original data and which one was proper to cluster the samples and establish discriminant functions so that a new sample can be grouped into the right categories.     

Development and application of microwave assisted extraction (MAE) for the extraction of five polycyclic aromatic hydrocarbons in sediment samples in Johannesburg area, South Africa

A microwave-assisted extraction (MAE) method was verified and applied for the extraction of polycyclic aromatic hydrocarbons (PAHs) in sediment samples. Soxhlet extraction was used as the reference method. The optimum MAE was carried out with 20 mL of hexane/acetone (1:1, v/v) mixture in a 1-g sample at 250 W for 20 min. Soxhlet extraction was carried out with 250 mL of dichloromethane:hexane (1:1, v/v) mixture in a 15-g sample for 24 h in a water bath maintained at 60 °C. The collected extracts were both cleaned up, reduced to 1 mL under nitrogen and then injected into an HPLC fluorescence. To increase the sample throughput, simultaneous MAE was performed. The obtained percentage recoveries ranged from 61 to 93 and 88–98 for MAE and SE, respectively. The optimised MAE method was validated using certified reference material. It was then applied to real sediment samples from in and around the greater Johannesburg area. The sediments from Jukskei River were found to be the most polluted while Hartbeespoort Dam sediments were found to be least polluted. The overall order of concentrations for the studied PAHs per site was as follows: Jukskei River?>?Kempton Park?>?Centurion Dams?>?Natalspruit River (PIT)?>?Hartbeespoort Dam.     

Multivariate analysis of mixed contaminants (PAHs and heavy metals) at manufactured gas plant site soils

Principal component analysis (PCA) was used to provide an overview of the distribution pattern of polycyclic aromatic hydrocarbons (PAHs) and heavy metals in former manufactured gas plant (MGP) site soils. PCA is the powerful multivariate method to identify the patterns in data and expressing their similarities and differences. Ten PAHs (naphthalene, acenapthylene, acenaphthene, fluorene, phenanthrene, anthracene, fluoranthene, pyrene, chrysene, benzo[a]pyrene) and four toxic heavy metals — lead (Pb), cadmium (Cd), chromium (Cr) and zinc (Zn) — were detected in the site soils. PAH contamination was contributed equally by both low and high molecular weight PAHs. PCA was performed using the varimax rotation method in SPSS, 17.0. Two principal components accounting for 91.7% of the total variance was retained using scree test. Principle component 1 (PC1) substantially explained the dominance of PAH contamination in the MGP site soils. All PAHs, except anthracene, were positively correlated in PC1. There was a common thread in high molecular weight PAHs loadings, where the loadings were inversely proportional to the hydrophobicity and molecular weight of individual PAHs. Anthracene, which was less correlated with other individual PAHs, deviated well from the origin which can be ascribed to its lower toxicity and different origin than its isomer phenanthrene. Among the four major heavy metals studied in MGP sites, Pb, Cd and Cr were negatively correlated in PC1 but showed strong positive correlation in principle component 2 (PC2). Although metals may not have originated directly from gaswork processes, the correlation between PAHs and metals suggests that the materials used in these sites may have contributed to high concentrations of Pb, Cd, Cr and Zn. Thus, multivariate analysis helped to identify the sources of PAHs, heavy metals and their association in MGP site, and thereby better characterise the site risk, which would not be possible if one uses chemical analysis alone.     

Identification of polycyclic aromatic hydrocarbons in unleaded petrol and diesel exhaust emission

Inhalation of emissions from petrol and diesel exhaust particulates is associated with potentially severe biological effects. In the present study, polycyclic aromatic hydrocarbons (PAHs) were identified from smokes released by the automobile exhaust from petrol and diesel. Intensive sampling of unleaded petrol and diesel exhaust were done by using 800-cm³ motor car and 3,455-cm³ vehicle, respectively. The particulate phase of exhaust was collected on Whatman filter paper. Particulate matters were extracted from filter paper by using Soxhlet. PAHs were identified from particulate matter by reverse phase high performance liquid chromatography using C₁₈ column. A total of 14 PAHs were identified in petrol and 13 in case of diesel sample after comparing to standard samples for PAH estimation. These inhalable PAHs released from diesel and petrol exhaust are known to possess mutagenic and carcinogenic activity, which may present a potential risk for the health of inhabitants.     

Seasonal Variation of the Particle Size Distribution of n-Alkanes and Polycyclic Aromatic Hydrocarbons (PAHs) in Urban Aerosol of Guangzhou, China

Seasonal aerosol samples have been collected by Andersen Hi-Vol pumping system equipped with a five stage cascade impactor and a backup filter (size range: 10–7.2 μ m, 7.2–3.0 μ m, 3.0–1.5 μ m, 1.5–0.95 μ m, 0.95–0.49 μ m, ≤0.49 μ m) in the Liwan district, Guangzhou. n-Alkanes were measured using gas chromatography and PAHs were measured using gas chromatography/mass spectrometry analysis. The bimodal log-normal distributions of n-alkanes and semi-volatile PAHs were found, while for non-volatile PAHs that was unimodal, so much as the mode of semi-volatile PAHs was similar with that of the particles. The n-alkanes and PAHs were preferably associated with fine particles. C _max (carbon number maximum) (C₂₂–C₂₆), CPI (carbon preference index) (1.12–1.21), U/R (unresolved to resolved components ratio) (7.42–10.7), wax% (0.9–3.12%) and the diagnostic ratios for PAHs revealed that vehicular emission was the major source of these organic compounds during the study periods, while the contribution of epicuticular waxes emitted by terrestrial plants was minor. CPI₂ (values for petrogenic hydrocarbons), CPI₃ (values for biogenic n-alkanes) and wax% revealed that the natural preferentially accumulated in the larger aerosol while the anthropogenic in the smaller. In addition, the different MMDs (mass median diameters) for n-alkanes and PAHs were observed in different seasons. The MMDs for n-alkanes and PAHs were higher in autumn/winter than those in spring/summer. The seasonal effect was related to the hydrocarbon content in the individual particulate fractions, showing a preferential association of n-alkanes and PAHs with larger particles in the autumn/winter season.     

太湖蓝藻水华暴发程度年度预测

近年来,尽管太湖主要水质指标有所改善,但蓝藻水华暴发的频次和面积并未明显减少。为了探讨太湖蓝藻水华暴发的环境驱动因子,统计了2012—2020年历年4—10月预警期间的太湖蓝藻水华发生规模与频次,结合同步浮标自动监测数据和实验室分析数据,构建了蓝藻水华预测模型。以太湖蓝藻水华综合指数(I_c)表征蓝藻水华强度,并通过I_c与环境因子的相关性分析,筛选出1月水温、1月电导率、1月生化需氧量和3月总氮浓度4项环境指标,最终构建了以该4项环境指标为自变量、I_c为因变量的太湖年度蓝藻水华强度多元线性回归预测模型。该预测模型的决定系数达到了0.908,平均相对误差为10.35%,预测精度总体表现较好。     

Assessment of temporal and spatial water quality in international Gomishan Lagoon,Iran, using multivariate analysis

Coastal lagoon ecosystems are vulnerable to eutrophication, which leads to the accumulation of nutrients from the surrounding watershed over the long term. However, there is a lack of information about methods that could accurate quantify this problem in rapidly developed countries. Therefore, various statistical methods such as cluster analysis (CA), principal component analysis (PCA), partial least square (PLS), principal component regression (PCR), and ordinary least squares regression (OLS) were used in this study to estimate total organic matter content in sediments (TOM) using other parameters such as temperature, dissolved oxygen (DO), pH, electrical conductivity (EC), nitrite (NO₂), nitrate (NO₃), biological oxygen demand (BOD), phosphate (PO₄), total phosphorus (TP), salinity, and water depth along a 3-km transect in the Gomishan Lagoon (Iran). Results indicated that nutrient concentration and the dissolved oxygen gradient were the most significant parameters in the lagoon water quality heterogeneity. Additionally, anoxia at the bottom of the lagoon in sediments and re-suspension of the sediments were the main factors affecting internal nutrient loading. To validate the models, R², RMSECV, and RPDCV were used. The PLS model was stronger than the other models. Also, classification analysis of the Gomishan Lagoon identified two hydrological zones: (i) a North Zone characterized by higher water exchange, higher dissolved oxygen and lower salinity and nutrients, and (ii) a Central and South Zone with high residence time, higher nutrient concentrations, lower dissolved oxygen, and higher salinity. A recommendation for the management of coastal lagoons, specifically the Gomishan Lagoon, to decrease or eliminate nutrient loadings is discussed and should be transferred to policy makers, the scientific community, and local inhabitants.     

Water Quality Prediction of Water Sources Based on Meteorological Factors using the CA-NARX Approach

With the increasingly serious problem of surface water environmental safety, it is of great significance to study the changing trend of reservoir water quality, and it is necessary to establish a water quality prediction and early warning system for the management and maintenance of water resources. Aiming at the problem of water quality prediction in reservoirs, a CA-NARX algorithm is designed, which combines the improved dynamic clustering algorithm with the idea of machine learning and the forward dynamic regression neural network. The improved dynamic clustering algorithm is used to classify the eutrophication degree of waterbodies according to the total phosphorus and total nitrogen content. Considering four meteorological factors, air temperature, water temperature, water surface evaporation, and rainfall, synthetically for each water quality condition, the total phosphorus and total nitrogen in the waterbody are forecasted by an improved forward NARX dynamic regression neural network. Based on this, the CA-NARX prediction algorithm can realize short period water quality prediction. Compared with the traditional support vector regression machine model, improved GA-BP neural network, and exponential smoothing method, the CA-NARX model has the least prediction error.

     

常州市秋季大气PM2.5中多环芳烃污染水平及来源

为了研究常州市秋季大气PM2.5中多环芳烃的污染水平及其来源,在常州市布设了6个采样点,分别代表交通干道区、商业混合区、居民文教区、远郊区、工业区和对照点,于2013年10月进行大气PM2.5的采样,采用微波萃取-高效液相色谱法测定其中16种USEPA优控多环芳烃的浓度值,并分别通过比值法和因子分析法判断其主要来源。结果表明,常州市秋季大气PM2.5中多环芳烃的主要来源为煤燃烧和机动车排放。     

Polycyclic aromatic hydrocarbons in water, sediment and soil of the Songhua River Basin, China

The Songhua River is the third largest river in China and the primary source of drinking and irrigation water for northeastern China. The distribution of 16 priority polycyclic aromatic hydrocarbons (PAHs) in water [dissolved water (DW) and suspended particulate matter (SPM)], sediment, and soil in the river basin was investigated, and the associated risk of cancer from these PAHs was also assessed. The total concentration of PAHs ranged from 13.9 to 161 ng L^?1 in DW, 9.21 to 83.1 ng L^?1 in SPM, 20.5 to 632 ng g^?1 dw (dry weight) in sediment, and from 30.1 to 870 ng g^?1 dw in soil. The compositional pattern of PAHs indicated that three-ring PAHs were predominant in DW and SPM samples, while four-ring PAHs dominated in sediment and soil samples. The spatial distribution of PAHs revealed some site-specific sources along the river, with principal component analysis indicating that these were from pyrogenic sources (such as coal and biomass combustion, and vehicle emissions) and coke oven emission distinguished as the main source of PAHs in the Songhua River Basin. Based on the ingestion of PAH-contaminated drinking water from the Songhua River, cancer risk was quantitatively estimated by combining the Incremental Lifetime Cancer Risk assessment model and BaP-equivalent concentration for five age groups of people (adults, teenagers, children, toddlers, and infants). Overall, the results suggest that the estimated integrated lifetime cancer risk for all groups was in acceptable levels. This study is the first attempt to provide information on the cancer risk of PAHs in drinking water from the Songhua River.     

Predicting bioaccumulation of PAHs in the trophic chain in the estuary region of Paranagua, Brazil

The presence of polycyclic aromatic hydrocarbon (PAH) compounds in sediment and water samples collected in the estuary area of Paranagua, southern Brazil, was investigated. There is a lot of port activity in the region. Recreational fishing is widespread; thus, there is concern about possible contamination by PAHs. The 16 priority PAHs were investigated, and only eight were found. The total concentration of PAHs ranged from 40.8 to 406.8 ng/g. High molecular weight were the most abundant, while PAHs with a low molecular weight were absent. There are suspicions that the main source of PAHs is combustion, but some uncertainties exist, and there may even be the presence of PAHs resulting from accidental spills of crude oil. Although the sediments contain PAHs, the amount is below the maximum concentrations allowed by the Brazilian environmental legislation, as well as the maximum levels at which adverse effects are observed. From the analytical results, a probable bioaccumulation was assessed in the local trophic chain using a mathematical model (Arnot and Gobas, Environ Toxicol Chem 23(10):2343?C2355, 2004). The model showed that there is a possibility of biomagnification along the food chain selected. Three fishes with high local consumption were selected, and the concentration of some PAHs could be found in those fishes.