A hierarchical approach for desertification assessment

Environmental systems are complex and multi-scaled open systems. To understand land degradation, one has to consider the interactions between landscape patterns and environmental processes at different scales. Patterns and processes in the landscape are perceived to be organized in nested hierarchical structures. To study land degradation in this context, a coupled top-bottom/bottom-up approach was developed. The top-bottom landscape analysis is aimed at identifying landscape systems at different scales. The bottom-up analysis focuses on system dynamics at finer scales. Applied in a study in central Spain, the approach is aimed at understanding the functional differences between three types of degraded seminatural slopes at different scales. Six levels of organization were distinguished: ped-level, terracette-level, hummock-level, slope part-level, slope level, and watershed level. Properties that characterize these levels were selected for different disciplines. The bottom-up analysis focused on water movement at different spatial scales. Successfully applying this approach revealed the importance for land degradation of the close linkage between spatial patterns and hydrological processes at different spatial scales. Identifying constraining and dynamic indicators related to water conservation at different scales can be useful for assessing desertification.     

Vulnerability of the Nile Delta coastal areas to inundation by sea level rise

Sea level changes are typically caused by several natural phenomena, including ocean thermal expansion, glacial melt from Greenland and Antarctica. Global average sea level is expected to rise, through the twenty-first century, according to the IPCC projections by between 0.18 and 0.59 cm. Such a rise in sea level will significantly impact coastal area of the Nile Delta, consisting generally of lowland and is densely populated areas and accommodates significant proportion of Egypt’s economic activities and built-up areas. The Nile Delta has been examined in several previous studies, which worked under various hypothetical sea level rise (SLR) scenarios and provided different estimates of areas susceptible to inundation due to SLR. The paper intends, in this respect, to identify areas, as well as land use/land cover, susceptible to inundation by SLR based upon most recent scenarios of SLR, by the year 2100 using GIS. The results indicate that about 22.49, 42.18, and 49.22 % of the total area of coastal governorates of the Nile Delta would be susceptible to inundation under different scenarios of SLR. Also, it was found that 15.56 % of the total areas of the Nile Delta that would be vulnerable to inundation due to land subsidence only, even in the absence of any rise in sea level. Moreover, it was found that a considerable proportion of these areas (ranging between 32.32 and 53.66 %) are currently either wetland or undeveloped areas. Furthermore, natural and/or man-made structures, such as the banks of the International Coastal Highway, were found to provide unintended protection to some of these areas. This suggests that the inundation impact of SLR on the Nile Delta is less than previously reported.     

Some statistical considerations in the assessment of compliance

Compliance with criteria limiting the discharge of pollutants or standards of water quality in the reveiving water body are assessed by monitoring. In order to set limits or standards, the features of the discharge or the water body to be monitored must be characterized. This generally involves the fitting of a probability distribution to historical data or data from preliminary sampling and the choice of a statistic for the limit or standard. Monitoring data collected to assess compliance are assumed to follow data will help to ensure that the assumption is met. Statistical methods which either assume a distribution for the quality variable or involve a transformation to a binary variable are compared. The validity of the underlying assumptions in the application of the methods to water or effluent quality data is discussed.     

Impact of Hazardous Exposure to Metals in the Nile and Delta Lakes on the Catfish, Clarias lazera

The impact of metal pollution in the Nile and Delta lakes was studied in Clarias lazera. Lake Edku is grouped as the site highest in metal concentrations. Compared to Lakes Maryût and Edku, the Nile stations displayed lower levels of metal contamination signifying their selection as reference sites. Metals were accumulated most by the liver, less by muscles and least by serum. Iron showed the highest bioconcentration factors (BCF) in liver, muscles or serum compared to other metals. Even after the refinement of the surrounding water, fish seem to uphold the metals that have been previously ingested. Mercury, in particular, seems to eventually reside in muscles rather than in liver. The positive relationship between total serum protein and metal contents may indicate the formation of specific metal-binding proteins. Meanwhile, serum hyperalbuminemia in polluted fish is probably a shock response towards the high stress index induced by metals. The hypothesis that most of serum copper is bound to ceruloplasmin is documented also in C. lazera. Moderate, but not extennsive, exposure to metals was quite stimulatory to liver alkaline phosphatase (AP) biosynthesis. AP could, thus, be considered as a promising bioindicator for assessing sublethal water intoxicosis.     

A corporate approach to social monitoring and assessment for development in a fragile environment

The prevailing corporate trend regardingdevelopment of energy resources in the tropics emphasizesfinancial gain over long-term societal benefits. Somecorporations are beginning to find a competitive advantage linkedto proactive relations with host communities and adequateprotection of fragile ecosystems. Herein, we describe a casestudy where an international energy production company workedwith stakeholders to achieve social capital and sustainabledevelopment. The strategies aimed to strengthen local capacity toimprove social welfare and to ensure conservation and wise use ofbiodiversity. We provide examples, discuss lessons learned andmake recommendations for future development projects.     

Impact assessment of subsurface drainage on waterlogged and saline lands

Waterlogging and salinity due to seepage from canals have polluted land and environment in various parts of Pakistan. A sustainable environment requires urgent remedial measures for this problem. The research in this paper presents the impacts of the Fourth Drainage Project, Faisalabad on the twin problem of waterlogging and salinity. Monitoring of the project was made on regular basis. The key performance indicators for the project include the lowering of water table, improvement of water quality and soil salinity, increase in area under cultivation, cropping intensity, and socioeconomic status of the project population. Data regarding water levels and discharge from the drain pipes were collected to monitor the impact on waterlogging. Soil samples were tested to evaluate the impact of drainage on land. It has been found that the percentage of the contaminated land in the project area has considerably been decreased, while the cropping intensities have been increased.     

Application of multivariate statistical methods for groundwater physicochemical and biological quality assessment in the context of public health

Three representative areas (lowland, semi-mountainous, and coastal) have been selected for the collection of drinking water samples, and a total number of 28 physical, chemical, and biological parameters per water sample have been determined and analyzed. The mean values of the physical and chemical parameters were found to be within the limits mentioned in the 98/83/EEC directive. The analysis of biological parameters shows that many of the water samples are inadequate for human consumption because of the presence of bacteria. Cluster analysis (CA) first was used to classify sample sites with similar properties and results in three groups of sites; discriminant analysis (DA) was used to construct the best discriminant functions to confirm the clusters determined by CA and evaluate the spatial variations in water quality. The standard mode discriminant functions, using 17 parameters, yielded classification matrix correctly assigning 96.97% of the cases. In the stepwise mode, the DA produced a classification matrix with 96.36% correct assignments using only ten parameters (EC, Cl^???, NO₃ ^???, HCO₃ ^???, CO₃ ^???2, Ca^?+?2, Na^?+?, Zn, Mn, and Pb). CA and factor analysis (FA) are used to characterize water quality and assist in water quality monitoring planning. CA proved that two major groups of similarity (six subclusters) between 17 physicochemical parameters are formed, and FA extracts six factors that account for 66.478% of the total water quality variation, when all samples’ physicochemical data set is considered. It is noteworthy that the classification scheme obtained by CA is completely confirmed by principal component analysis.     

Multivariate statistical techniques for the assessment of seasonal variations in surface water quality of pasture ecosystems

This study investigates the applicability of multivariate statistical techniques including cluster analysis (CA), discriminant analysis (DA), and factor analysis (FA) for the assessment of seasonal variations in the surface water quality of tropical pastures. The study was carried out in the TPU catchment, Kuala Lumpur, Malaysia. The dataset consisted of 1-year monitoring of 14 parameters at six sampling sites. The CA yielded two groups of similarity between the sampling sites, i.e., less polluted (LP) and moderately polluted (MP) at temporal scale. Fecal coliform (FC), NO₃, DO, and pH were significantly related to the stream grouping in the dry season, whereas NH₃, BOD, Escherichia coli, and FC were significantly related to the stream grouping in the rainy season. The best predictors for distinguishing clusters in temporal scale were FC, NH₃, and E. coli, respectively. FC, E. coli, and BOD with strong positive loadings were introduced as the first varifactors in the dry season which indicates the biological source of variability. EC with a strong positive loading and DO with a strong negative loading were introduced as the first varifactors in the rainy season, which represents the physiochemical source of variability. Multivariate statistical techniques were effective analytical techniques for classification and processing of large datasets of water quality and the identification of major sources of water pollution in tropical pastures.     

A statistical F test for the natural attenuation of contaminants in groundwater

Natural attenuation (NA) is a catchall explanation for the overall decay and slowed movement of the contaminants in the subsurface. One direct support to NA is to demonstrate that contaminant concentrations from monitoring wells located near the source are decreasing over time. The decrease is summarily expressed in terms of an apparent half-life that is determinedfrom the line best fitting the observed log-transformed concentration data and time. This simple (time-only) decay modelassumes other factors are invariant, and so is flawed when complicating factors – such as a fluctuating water table – are present. A history of the water-table fluctuation can track changes in important NA factors like recharge, groundwater flow direction and velocity, as well as other non-NA factors like volume of water in and purged from the well before a sample is collected. When the trend in the concentrations is better associated with the water table rising or falling, any conclusionabout degradation rate may be premature. We develop simple regressions to predict contaminant concentration (c) by two line models: one involving time (c c(t)), and another involving groundwater elevation (c c(z)). We develop a third model that includesboth factors (c c(t, z)). Using an F-test to compare the fits to the models, we determine which modelis statistically better in explaining the observed concentrations. We applied the test to sites where benzene degradation rates had previously been estimated. The F-testcan be used to determine the suitability of applying non-parametric statistics, like the Mann-Kendall, to the concentration data, because the result from the F-test canindicate instability of the contaminant plume that may bemasked when the water table fluctuates.     

Use of water quality index and multivariate statistical techniques for the assessment of spatial variations in water quality of a small river

Rapid urban development has led to a critical negative impact on water bodies flowing in and around urban areas. In the present study, 25 physiochemical and biological parameters have been studied on water samples collected from the entire section of a small river originating and ending within an urban area. This study envisaged to assess the water quality status of river body and explore probable sources of pollution in the river. Weighted arithmetic water quality index (WQI) was employed to evaluate the water quality status of the river. Multivariate statistical techniques namely cluster analysis (CA) and principal component analysis (PCA) were applied to differentiate the sources of variation in water quality and to determine the cause of pollution in the river. WQI values indicated high pollution levels in the studied water body, rendering it unsuitable for any practical purpose. Cluster analysis results showed that the river samples can be divided into four groups. Use of PCA identified four important factors describing the types of pollution in the river, namely (1) mineral and nutrient pollution, (2) heavy metal pollution, (3) organic pollution, and (4) fecal contamination. The deteriorating water quality of the river was demonstrated to originate from wide sources of anthropogenic activities, especially municipal sewage discharge from unplanned housing areas, wastewater discharge from small industrial units, livestock activities, and indiscriminate dumping of solid wastes in the river. Thus, the present study effectively demonstrates the use of WQI and multivariate statistical techniques for gaining simpler and meaningful information about the water quality of a lotic water body as well as to identify of the pollution sources.     

Water quality assessment and source identification of Daliao river basin using multivariate statistical methods

Multivariate statistical methods, such as cluster analysis (CA), discriminant analysis (DA) and principal component analysis (PCA), were used to analyze the water quality dataset including 13 parameters at 18 sites of the Daliao River Basin from 2003-2005 (8424 observations) to obtain temporal and spatial variations and to identify potential pollution sources. Using Hierarchical CA it is classified 12 months into three periods (first, second and third period) and the 18 sampling sites into three groups (groups A, B and C). Six significant parameters (temperature, pH, DO, BOD(5), volatile phenol and E. coli) were identified by DA for distinguishing temporal or spatial groups, with close to 84.5% correct assignment for temporal variation analysis, while five parameters (DO, NH(4)(+)-N, Hg, volatile phenol and E. coli) were discovered to correctly assign about 73.61% for the spatial variation analysis. PCA is useful in identifying five latent pollution sources for group B and C (oxygen consuming organic pollution, toxic organic pollution, heavy metal pollution, fecal pollution and oil pollution). During the first period, sites received more oxygen consuming organic pollution, toxic organic pollution and heavy metal pollution than those in the other two periods. For group B, sites were mainly affected by oxygen consuming organic pollution and toxic organic pollution during the first period. The level of pollution in the second period was between the other two periods. For group C, sites were mainly affected by oil pollution during the first period and oxygen consuming organic pollution during the third period. Furthermore, source identification of each period for group B and group C provided useful information about seasonal pollution. Sites were mainly affected by fecal pollution in the third period for group B, indicating the character of non-point source pollution. In addition, all the sites were also affected by physical-chemistry pollution. In the second and third period for group B and second period for group C sites were also affected by natural pollution.     

An approach to the assessment of the quality of environmental monitoring data

This paper reports an approach to the assessment of the validity of environmental monitoring data--a 'data filter'. The strategy has been developed through the UK National Marine Analytical Quality Control (AQC) Scheme for application to data collected for the UK National Marine Monitoring Plan, although the principles described are applicable more widely. The proposed data filter is divided into three components: Part A, 'QA/QC'--an assessment of the laboratory's practices in Quality Assurance/Quality Control; Part B, 'fitness for purpose'--an evaluation of the standard of accuracy that can be demonstrated by activities in (A), in relation to the intended application of the data; and Part C, the overall assessment on which data will be accepted as usable or rejected as being of suspect quality. A pilot application of the proposed approach is reported. The approach described in this paper is intended to formalise the assessment of environmental monitoring data for fitness for a chosen purpose. The issues important to fitness for purpose are discussed and assigned a relative priority order on which to judge the reliability/usefulness of monitoring data.     

A statistical approach to field measurements of the chemical evolution of cold (<0°C) snow cover

Two statistical methods for the analysis of data on the evolution of the chemical composition of cold snow (<0°C) in the field (Lac Laflamme, Quebec) were compared. The methods used on the data were regression analysis (One sample per sampling date over a long cold period) and ANOVA (replicate samples on a restricted number of sampling dates over shorter periods). The relative power of the tests to determine the detectable amplitude of chemical changes was derived from the theoretical power of the tests under comparable conditions of sampling (number of observations) and from the estimated error variances of the measured data.The results of the study on the evolution of sulfates (SO₄) concentrations in discretely identified snow strate clearly showed that for six of the eight strata, significant losses of SO₄ occurred in snow during cold periods. The relative amplitude of the significant losses varied between 1% per day and 4% per day depending on the initial concentrations in the snow and the prevailing meteorological conditions.The analysis of the data also demonstrated that for the same number of samples, the regression analysis is more efficient in detecting the chemical changes in snow than the alternative ANOVA method. The use of this information to plan sampling programs of cold snow under both field and laboratory conditions is discussed.     

Quantitative assessment of eutrophication: A scoring system for characterising water quality in coastal marine ecosystems

A scoring system based on nutrient concentrations was developed to assess coastal water quality according to the trophic level. Three nutrient data sets from eutrophic, mesotrophic and oligotrophic waters were used as the reference information for setting up a semi quantitative water quality scale (from 0 to 5) to express different nutrient loadings. The validity and sensitivity of the method was applied to a number of stations spaced out along the coastal area of Rhodes (Greece). A score for each nutrient/sampling site was calculated and the scorecard formed, was the data matrix used for numerical classification of the stations. The results showed (a) good discrimination between cutrophic, mesotrophic and oligotrophic waters (b) nitrate among the nutrients showed the maximum sensitivity in characterising pollution levels. The reference data sets used for assessing eutrophication levels ensured the objectivity of the method. The proposed method is described step-by-step and it is suggested that the method can be further adapted to describe other forms of pollution becoming a useful quantitative technique in coastal management practices.     

A new approach for estimating the phytotoxicity limits

A pot experiment was carried out on a Typic ustipsamment to study the effect of Cd concentration on the yield of wheat (Triticum aestivum) and soybean (Glycine max). Cd levels taken were 1, 5, 10, 20, 40, 80, and 160 g g^-1 of soil. Three different statistical procedures were employed to evaluate the phytotoxicity limits. The non-linear regression technique was found to be more effective in calculating C ₀ (threshold concentration) and C ₁₀₀ (toxic concentration) in comparison to Cate and Nelson (1971) and Beckett and Davis (1977) procedures. This technique was unaffected by the nature of the distribution of the data and did not require any initial value of concentration as a starting point.     

Statistical approach for the assessment of water pollution around industrial areas: A case study from Patancheru,Medak district,India

Industrial effluents, surface waters, and subsurface groundwaters were sampled in and around the Patancheru industrial area of Nakkavagu basin, India and analysed. The parameters such as TDS, BOD, COD, and abundances of elements such as Cu, As, Se, F, Fe, are 5 to 10 times more than the permissible limits. These pollutants are contaminating the groundwaters at a faster rate than anticipated. A statistical approach is used to express the magnitude of pollution. Initially, correlation matrices of the major parameters and trace elements followed by factor analysis on them are presented to quantify the aspect of pollution. Factor 1 explaining 43.6% variance has positive loadings for variables TDS, BOD, COD, As, Cu, Se, SO ₄ ^–2 , and Cr, suggesting the factor is interpreted to be the Pollution or Migration of Pollutants. The same variables have negative loadings in the subsurface groundwaters suggesting that Factor 1 for these samples is a the depositionn or precipitation phenomenon. With a critical look at the Factor 1 of both surface and subsurface water samples it is indicated that pollutants migrated and became deposited in the environs of the Patancheru industrial area.     

Reduction and avoidance of lubricant mist demands an integrated assessment approach

A case study to identify major factors for lubricant mist exposure covered 15 metal machining sites. The investigation included milling, turning, drilling and grinding applications. Systematic analysis considered all relevant data concerning the machine tool, the lubricant and the suction plant. The efficiency of the implemented maintenance program at the installed filter systems was checked by concentration measurements immediately before and after service. All performed measurements of lubricant aerosol and vapor loads upstream and downstream of the installed filter systems were carried out according to VDI 2066 and BIA 3110, respectively. The selection criteria for the sites to be investigated, the systematic nature of the data acquisition and the procedure of the analysis are demonstrated in detail by performing comparisons between selected applications using emulsions and those employing straight oil for lubrication. The results of the study identify recirculation of ventilated air as the major source of workplace exposure to airborne lubricant emissions. More than 60% of the demisters investigated emit air at total lubricant loads (aerosols and vapor) above the limit of 20 mg m-3 at any time of operation; which also means immediately after service. A common reason for exceeded aerosol loads in recirculated air is e.g. the fact that the type of filter system applied is often not suitable for the separation problem. Loads of lubricant vapor are usually higher at the processes which use water emulsions as lubricant. In a quarter of the cases the limits were exceeded solely due to high vapor loads even immediately after service. The exposure can be reduced by replacing the lubricant, installation of a vapor separation plant or avoiding air recirculation. Maintenance time of the demisting system and aerosol separation efficiency of state-of-the-art demisting systems can be expanded by implementation of enhanced preliminary filter stages. This study confirms that appropriate service measures lower both aerosol emissions and lubricant vapor concentrations due to the reduction of exposed oil-wetted surfaces. The performed measurements show no significant relationship between loads of airborne lubricants and the type of machining process. Therefore, investigations at a much more detailed level have to be performed. However, the individual assessment of any workplace due to the complex situation remains essential.