Water quality trend analysis for the Karoon River in Iran

The Karoon River basin, with a basin area of 67,000 km², is located in the southern part of Iran. Monthly measurements of the discharge and the water quality variables have been monitored at the Gatvand and Khorramshahr stations of the Karoon River on a monthly basis for the period 1967–2005 and 1969–2005 for Gatvand and Khorramshahr stations, respectively. In this paper the time series of monthly values of water quality parameters and the discharge were analyzed using statistical methods and the existence of trends and the evaluation of the best fitted models were performed. The Kolmogorov–Smirnov test was used to select the theoretical distribution which best fitted the data. Simple regression was used to examine the concentration-time relationships. The concentration-time relationships showed better correlation in Khorramshahr station than that of Gatvand station. The exponential model expresses better concentration – time relationships in Khorramshahr station, but in Gatvand station the logarithmic model is more fitted. The correlation coefficients are positive for all of the variables in Khorramshahr station also in Gatvand station all of the variables are positive except magnesium (Mg²⁺), bicarbonates () and temporary hardness which shows a decreasing relationship. The logarithmic and the exponential models describe better the concentration-time relationships for two stations.     

Multiple-point variance analysis for optimal adjustment of a monitoring network

The selection of sampling sites is one of the major tasks in thedesign of a monitoring network. Many environmental networkssuffer from either insufficient information or redundantinformation. This study presents a new, effective algorithm thataddresses the issues of insufficient and reduction information.The new algorithm is denoted as Multiple-Point Variance Analysis(MPV). MPV includes both Multiple-Point Variance ReductionAnalysis (MPVR) for adding information-effectives sites, andMultiple-Point Variance Increase Analysis (MPVI) for deletinginformation-redundant sites. The MPVR and MPVI equations areverified under two hypothetical cases. The optimal procedures ofthis new algorithm include determination of simultaneousadditions or deletions of groups of sampling points. Theseproposed optimization procedures eliminate the need for anyspatial discretizations or sequential selections. The efficiencyof these optimal procedures is tested under actual fieldconditions. The results show that the optimal MPV is aneffective tool for adjustment of existing sampling networks.     

Qualitative time trend analysis of ground water monitoring networks

The detection of significant (short-term) time trends is one of the major goals of ground water monitoring networks. These trends can be used to recognize active geochemical processes and potential environmental threats. This paper presents a case history of time trend analysis on macrochemical parameters of ground water quality. It shows the difficulties and traps that are generally encountered in such studies. The data used originated from the Dutch National Groundwater Quality Monitoring Network. This network is operative since 1979, and keeps track of the ground water composition at 350 locations at two depths (ca. 10 and 25 m below surface; general density, one location per 100 km²). Prior to the trend analysis the data set was divided into geochemically homogeneous groups using fuzzy c-means clustering. Each group represents a specific ground water type, characterized by a distinct source (seawater, surface water or precipitation) and a unique combination of dominant geochemical processes (e.g. mineralization of organic matter, carbonate dissolution and cation exchange).To study trends qualitatively, the concentrations of the various macro-constituents in ground water are correlated with time of sampling. The nonparametric and outlier insensitive Spearman rank correlation coefficient is computed per well screen. A frequency distribution of correlation coefficients is formed by combining the Spearman correlation coefficients of all individual wells within a homogeneous group. This distribution is tested for trends against the appropriate theoretical distribution of zero correlation by use of the Kolmogorov-Smirnov one-sample test. The type of trend is derived from the shape of the distribution.Most ground water types show statistically significant qualitative trends, of which many, however, are caused by changes in the sampling and analytical procedures over the monitoring period. After elimination of differences in limits of detection for NO₃, total-P, and NH₄, most trends in these compounds disappeared. In some water types trends for alkalinity, apparent trends for pH, Ec, and total-P are caused by variations in the laboratory practice, e.g. varying storage procedures, leading to erroneous analyses. Other parameters showed statistically significant trends, related to geochemical processes.The most interesting and most substantial trends are observed in the water type characterized by infiltrating rainwater with agricultural pollutants. In this water type the lowering ground water table induces lower rates of evapotranspiration, giving lower concentrations in time of conservative parameters (Cl, Na, Ca). The aerated zone is enlarged, resulting in increased oxidation of organic material, less efficient nutrient (NO₃, K) uptake by plant roots, leading to increased ground water concentrations of nutrients. In other water types trends are quantitatively small. However, trends are not necessarily linear, and all should be closely monitored in future.     

苏州市区大气监测点位调整中的相关性和聚类分析

根据苏州市8个国控大气监测站点2013—2015年的PM_(10)、PM_(2.5)、O_3、SO_2监测数据,计算了各站点之间监测数据的相关系数;通过分析相关系数矩阵,发现苏州市大气国控点位的监测数据相关性均较高,点位设置存在一定的冗余,国控监测点位的优化调整十分必要。利用最长距离法对各站点的监测数据进行聚类分析,从而得出中心城区的点位调整方案。点位调整前后4种污染物监测数据四季平均值的相对误差均小于5%;正负偏差的二项检验结果表明,调整后未对监测结果产生显著的正/负影响。因此,经过优化的大气监测网络具有较好的客观性和代表性。     

Meteorological normalisation and non-parametric smoothing for quality assessment and trend analysis of tropospheric ozone data

Despite extensive efforts to ensure that sampling and installation and maintenance of instruments are as efficient as possible when monitoring air pollution data, there is still an indisputable need for statistical post processing (quality assessment). We examined data on tropospheric ozone and found that meteorological normalisation can reveal (i) errors that have not been eliminated by established procedures for quality assurance and control of collected data, as well as (ii) inaccuracies that may have a detrimental effect on the results of statistical tests for temporal trends. Moreover, we observed that the quality assessment of collected data could be further strengthened by combining meteorological normalisation with non-parametric smoothing techniques for seasonal adjustment and detection of sudden shifts in level. Closer examination of apparent trends in tropospheric ozone records from EMEP (European Monitoring and Evaluation Programme) sites in Finland showed that, even if potential raw data errors were taken into account, there was strong evidence of upward trends during winter and early spring.     

Spatiotemporal trend analysis of recent river water quality conditions in Japan

In order to promote pollutant monitoring and preservation of water resources, we evaluate the spatiotemporal trends in recent water quality conditions in Japanese rivers. Trend analysis is conducted on the 92 major rivers in Japan using the available water quality data recorded from 1992 to 2005 and the characteristics of major pollutants in these rivers are analyzed. Spatial and temporal analysis of trends for six water quality indicators is conducted using the Mann Kendall test, a non-parametric statistical method. The indicators analyzed are biochemical oxygen demand (BOD), chemical oxygen demand (COD), dissolved oxygen (DO), total nitrogen (TN), total phosphorus (TP) and pH. The majority of sampling locations monitoring BOD, COD, TN and TP show trends toward decreasing concentrations over time. Many sampling locations show increasing DO concentrations. Our results show that water quality in Japanese rivers has improved dramatically over the past decade, although there are still problems in some places, most notably in the Hokkaido, Kanto, Kinki and Kyushu regions. The improvements seen in water quality appear to be the result of improved wastewater treatment and other water quality improvement efforts achieved through government initiative.     

Multivariate analysis of heavy metals concentrations in river estuary

Multivariate statistical techniques such as multivariate analysis of variance (MANOVA) and discriminant analysis (DA) were applied for analyzing the data obtained from two rivers in the Penang State of Malaysia for the concentration of heavy metal ions (As, Cr, Cd, Zn, Cu, Pb, and Hg) using a flame atomic absorption spectrometry (F-AAS) for Cr, Cd, Zn, Cu, Pb, As and cold vapor atomic absorption spectrometry (CV-AAS) for Hg. The two locations of interest with 20 sampling points of each location were Kuala Juru (Juru River) and Bukit Tambun (Jejawi River). MANOVA showed a strong significant difference between the two rivers in terms of heavy metal concentrations in water samples. DA gave the best result to identify the relative contribution for all parameters in discriminating (distinguishing) the two rivers. It provided an important data reduction as it used four parameters (Zn, Pb, Cd and Cr) affording 100% correct assignations. Results indicated that the two rivers were different in terms of heavy metals concentrations in water, and the major difference was due to the contribution of Zn. A negative correlation was found between discriminate functions (DF) and Cr and As, whereas positive correlation was exhibited with other heavy metals. Therefore, DA allowed a reduction in the dimensionality of the data set, delineating a few indicator parameters responsible for large variations in heavy metal concentrations. Correlation matrix between the parameters exhibited a strong evidence of mutual dependence of these metals.     

Assessing the impact of FDI on PM2.5 concentrations: A nonlinear panel data analysis for emerging economies

While emerging markets have obtained powerful growth for foreign direct investment (FDI) inflows, they are facing severe smog pollution, and this contradiction has become increasingly prominent since the financial crisis. Assessing the influence of FDI on pollutant emissions is of great significance for determining how to attract FDI to promote environmental sustainability. The present study simultaneously investigates the direct and indirect effects of FDI on PM_2.5 contamination for emerging countries spanning the period 2010–2016. Due to the features of the nonlinear analysis, a generalized panel smooth transition regression (GPSTR) model was introduced, and cross-sectional dependence, heterogeneity, nonlinear unit root, nonlinear cointegration tests and non-parametric kernel density estimation were applied to achieve this goal. The results reveal that FDI directly contributes to decreasing PM_2.5, but indirectly has on increasing PM_2.5 emissions. The total effect of FDI on PM_2.5 concentrations is proven to be negative, which confirms the pollution halo hypothesis. Moreover, the connection between FDI inflows and PM_2.5 emissions displays a threshold and dynamic characteristic and is “S-shaped”. At lower levels of FDI, the inflows of FDI exert a positive effect on reducing PM_2.5 concentrations, whereas when FDI exceeds the threshold of 23.2981, such influence is gradually weakened with an increase in its own accumulation. The study provides new assessments on FDI's contribution to pollutant emissions and evidence for environmental sustainability in the post-financial crisis era.     

Statistical analysis of PM10 concentrations at different locations in Malaysia

Malaysia has experienced several haze events since the 1980s as a consequence of the transboundary movement of air pollutants emitted from forest fires and open burning activities. Hazy episodes can result from local activities and be categorized as "localized haze". General probability distributions (i.e., gamma and log-normal) were chosen to analyze the PM(10) concentrations data at two different types of locations in Malaysia: industrial (Johor Bahru and Nilai) and residential (Kota Kinabalu and Kuantan). These areas were chosen based on their frequently high PM(10) concentration readings. The best models representing the areas were chosen based on their performance indicator values. The best distributions provided the probability of exceedances and the return period between the actual and predicted concentrations based on the threshold limit given by the Malaysian Ambient Air Quality Guidelines (24-h average of 150 μg/m(3)) for PM(10) concentrations. The short-term prediction for PM(10) exceedances in 14 days was obtained using the autoregressive model.     

连续流动分析在水质监测中的应用

连续流动分析技术具有分析速度快、准确度和精密度高、操作简单、通用性强、样品和试剂消耗量少等一系列优点。灵活运用连续流动分析技术可对大多数水性样品如水和废水、土壤(或固体废弃物)提取液、饮料等进行分析。本文中着重介绍了氨氮、硝酸盐氮/亚硝酸盐氮、挥发酚以及总氰化物等几个连续流动分析在水质监测中的应用实例。     

Optimizing the removal of small fish passage barriers

Removing small artificial barriers that hinder upstream migrations of fish is a major problem in riparian habitat restoration. Because of budgetary limitations, it is necessary to prioritize barrier removal and repair decisions. These have usually been based on scoring and ranking procedures, which, although simple to use, can be very inefficient in terms of increasing the amount of accessible instream habitat. We develop a novel decision-making approach, based on integer programming techniques, which optimizes repair and removal decisions. Results show based on real datasets of barrier culverts located in Washington State that scoring and ranking is over 25% below the optimum on average and a full 100% below in the worst case, producing no net habitat gain whatsoever. This is compared to a dynamic programming method that was able to find optimal solutions in less than a second, even for problems with up to several hundred variables, and a heuristic method, which found solutions with less than a 1% average optimality gap in even less time.     

Real-time quantitative PCR with gene probe, fluorochrome and flow cytometry for microorganism analysis

Microorganism concentrations and viability can be better understood and clarified by using both culture and non-culture methods. Here, using pure suspensions of E. coli, three non-culture methods, namely, flow cytometry (FCM), epifluorescence microscopy (EFM), and real-time quantitative polymerase chain reaction (real-time qPCR), were compared with a traditional culture-based method. Using fluorocome-labeling methods with FCM and EFM applications, acridine orange (AO) and propidium iodide (PI) dyes were used to determine the total cell concentration and microorganism viability, respectively. The results indicated that total cell concentrations determined using FCM were statistically higher (2.62-4.94 times) than those determined using EFM. The difference might be due to cell losses induced by extensive preparations needed for EFM. In addition, EFM and FCM were highly associated for both the total cell concentration and viability. FCM-measured viability was the highest, whereas the culture-measured viability was the lowest. Furthermore, DNA concentrations measured by real-time qPCR with gene probe were highly associated with the total number concentrations measured by either the EFM or FCM. In summary, the three non-culture methods compared here could provide rapid and accurate information about microorganism concentrations and viabilities.     

Method for the determination of sub-ppm concentrations of perfluoroalkylsulfonate anions in water

The determination of sub-ppm concentrations of aqueous perfluoroalkylsulfonate (PFSt) anions, including perfluorooctylsulfonate (PFOS), has been accomplished with a relatively simple mass spectrometric procedure that does not require extraction of the analytes into an organic solvent or a chromatographic separation prior to injection into the negative-ion electrospray ionization mass spectrometer. Sample pretreatment was minimized and consisted of dilution of the aqueous samples of groundwater, surface water, tap water, and distilled water with acetonitrile, addition of dodecylsulfate (DDS) as an internal standard, and, in some cases, addition of known amounts of perfluorobutylsulfonate (PFBS) or PFOS for standard-addition experiments. The linear-response range for PFOS is 25.0 microg L(-1) to 2.5 mg L(-1). The lower limit of this range is three orders of magnitude lower than an equally straightforward chromatographic method. The relative errors for standard aqueous solutions containing only 25.0 microg L(-1) and 2.5 mg L(-1) PFOS are +/- 14% and +/- 7%, respectively, with 133 microg L(-1) DDS as the internal standard. The detection limit and quantification limit for PFOS in these standards are 5.0 microg L(-1) and 25.0 microg L(-1), respectively. Six different PFS anions, containing three to eight carbon atoms, were identified and quantified in an aqueous film-forming foam (AFFF) formulation using the method of standard additions. Two alkylsulfate anions and two perfluoroalkylcarboxylate anions were also identified in the AFFF formulation.     

A GIS-based Study for Optimizing the Total Emission Control Strategy in Lanzhou City

A geographic information system (GIS)-based approach with spatial analysis advantages was developed to optimize the total emission control scheme on air pollution in Lanzhou, combined with Models-3 modeling system and a linear programming model. GIS system is mainly used for establishing a multifactor assessment model to quantitatively divide environmental functional zone, and also used for selecting control sites in linear programming model. The results show that most of the urban area belongs to the second type of function, which is 122.8 km² occupying about 76.5% and the third type of about 32.9 km² occupying 20.5%. To reach the air quality up to the national standard in the entire control area, some large-emission factories need to cut emissions from 19% to 27%. For small but low-emission height sources, the cut may be as high 40%. The improvement of the ecological environment is urgently needed for controlling the background particle pollution in Lanzhou city.     

Optimum spatial analysis of monitoring data on temperature,salinity and nutrient concentrations in the Baltic Proper

In spite of the large number of monitoring data on hydrography and nutrients collected from the Baltic Sea, it is still difficult to describe large-scale distribution patterns of these variables. We therefore suggest a stochastic approach that allows the spatial reconstruction of the fields for the entire sea. The Baltic Sea monitoring data on temperature, salinity and nutrient concentrations from the years 1972–1991 are each divided into twenty data sets: five regions, times four seasons. The spatial regions are the Southern Baltic Proper, the Northern and Central Baltic Proper, both above and below halocline, and the region of the Gulf of Finland and the Gulf of Riga. The four seasons consist of three-month periods: January–March (winter), April–June (spring), July–September (summer) and October–December (fall). Each monthly subset of a regional and seasonal data set is modeled as a sample out of a monthly realization of a random field. The data sets are decomposed into mean and fluctuational components. The mean is determined as an average over the space cells with dimensions of standard sampling depth intervals vertically, 10 in meridional (south-north), 20 in zonal (west-east) directions and over five-year periods in time. The fluctuation fields are considered second-order stationary, homogeneous and horizontally isotropic. Estimated horizontal (surface) and vertical (depth) components of the spatial correlations are approximated by Gaussian functions. The correlation scales for the fields of the Baltic Proper are mostly larger than 100 nautical miles horizontally and 40 m vertically and their dependence on the sea region or season is relatively weak. The most probable noise-to-signal ratio values of the data lie in the interval 0.6 to 1.2. The estimated correlation functions and noise-to-signal ratios allow the optimum analysis technique to assess the correctness of each datum of a sample on the background of the field statistics. The outliers of each monthly sample are excluded from the analysis. The observed fluctuations are interpolated into locations with missing data by an optimum interpolation procedure. The discrete cell-and-five-year mean values are interpolated by a different, piece-wise linear technique. Since the data number for the mean interpolation considerably exceeds the data number for the fluctuation interpolation, the interpolation errors for the mean are assumed negligible compared to the interpolation errors for the fluctuation. The sums of the mean and fluctuation, interpolated into the withheld observation points, are compared to the actually observed values and to some other linear interpolation estimates. In all test cases the optimum interpolation procedure performs the best.     

密云水库浮游藻类和细菌污染现状及趋势分析

为评价密云水库水体富营养化的现状及发展趋势,在水库水面不同方位和不同水深分别布点采样,对水库水质的浮游藻类群落结构、密度和卫生学性状进行了初步监测和评价。结果显示,水体浮游藻类总量有增加趋势,但主要群落结构变化不大,仍以绿藻-硅藻型为主;但蓝藻的比例随水温的增加显著;各项卫生学指标基本在正常范围;同时发现其内湖的蓝藻污染较为严重,对大库区水质形成潜在威胁,应予重视。     

Application of flow cytometry and cell sorting to the bacterial analysis of environmental aerosol samples

Flow cytometry (FCM) combined with viability staining is a useful tool in discerning viable bacteria in environmental samples where traditional culture methods may fail. Contamination of aerosol samples with dust and other non-biological particles can interfere with accurate sample analysis and therefore there is a desire to exclude those particles from analysis. Particles were sorted according to their light scattering properties, cultured and isolates obtained. Isolates were cultured in suspension and reanalyzed by flow cytometry. The isolates were also analyzed and identified by DNA sequence analysis. Isolates with statistically similar light scattering properties shared common sequence identification. Isolates exhibited distinct light scattering profiles that roughly correlated with their originating gate, but often the peak of the profile was outside that gate.     

An analysis of total gaseous mercury (TGM) concentrations across the UK from a rural sampling network

Total gaseous mercury was collected at ten sites, which comprise part of the UK rural heavy metals monitoring network, between 2005 and 2008. Using the gold amalgam technique to capture total gaseous mercury, samples were analysed using a Tekran 2537A mercury vapour analyser. The data showed no upward or downward trend in atmospheric mercury concentrations over the period, with 4 year average concentrations between 1.3 and 1.9 ng m(-3), which are in line with other studies' observed northern hemispheric background concentrations of between 1.5 and 1.7 ng m(-3). Using data from nine of the sites, we were able to show seasonality within the data and through kriging we were able to interpolate the TGM concentrations over the UK, revealing a south-east to north-west declining concentration gradient. Using continuous speciated mercury measurements from one of the network sites, we show through wind sector analysis and air-mass back trajectories that this spatial trend is likely to be due to air masses moving over the UK from continental Europe on easterly winds. The levels of TGM recorded in the south-east of the UK also more closely match observed background TGM levels on the continent, which could indicate that the TGM concentrations from the north of the UK are a better reflection of the true North Atlantic atmospheric mercury background level.     

间隔流动分析仪在环境监测应用中的评估报告

根据本站购置的SFA-2000型间隔流动分析仪的调试和应用情况,对该类仪器在环境监测工作中的应用状况和前景进行了比较评估,并提出了在购置该类仪器时所应注意的问题和配置方案。     

Optimizing a GC-MS method for screening of Stachybotrys mycotoxins in indoor environments

Presence of Stachybotrys chartarum in indoor environments has been linked to building-associated disease, however, the causative agents are unknown. Verrucarol (VER) and trichodermol (TRID) are hydrolysis products of some major S. chartarum mycotoxins, i.e. macrocyclic trichothecenes and trichodermin. We optimized gas chromatography-mass spectrometry (GC-MS) methods for detecting VER and TRID in S. chartarum-contaminated indoor environmental samples. Heptafluorobutyryl derivatives of both VER and TRID exhibited little MS fragmentation and gave much higher detection sensitivity (sub-picogram injected onto the GC column), both in GC-MS and GC-MSMS, than trimethylsilyl derivatives. Optimal detection sensitivity and specificity was achieved by combining chemical ionization and negative ion (NICI) detection with MSMS. With this method, VER and TRID were detected in building materials colonized by S. chartarum and TRID was demonstrated in dust settled in the breathing zone in a house where an inner wall was colonized. In summary, we have shown that NICI-GC-MSMS can be used to demonstrate mycotoxins in house dust in S. chartarum-contaminated dwellings.