Performance evaluation of oil spill software systems in early fate and trajectory of oil spill: comparison analysis of OILMAP and PISCES 2 in Mersin bay spill

The aim of this study is to evaluate the performance level of two advanced oil spill software systems in early transport and fate of oil spill through algorithms accepted in oil spill literature. To do this, the performance level of software systems mostly used in real cases have been compared. OILMAP (the oil spill prediction modeling system) and PISCES 2 (potential incident simulation, control and evaluation system) have been used for spill trajectory in the light of four spill scenarios. The findings reveal that the OILMAP has predicted a relatively larger area of spill. In addition, OILMAP has achieved closer results to the calculations of approaches adopted in the literature for evaporation calculations. Besides, OILMAP software has provided highly reliable results in the evaporation rates of oil compared to the calculations of PISCES 2. On the other hand, as for the determination of the risky area, both software systems have yielded results with high reliability values, which could be used in taking precautions against oil spill in such areas.     

Application of a battery of biomarkers in mussel digestive gland to assess long-term effects of the Prestige oil spill in Galicia and Bay of Biscay: correlation and multivariate analysis

According to published reports, selected cell and tissue-level biomarkers revealed alterations in the health status of mussels collected after the Prestige oil spill (POS) in Galicia and the Bay of Biscay (2003-2006). Presently, univariate and multivariate analysis provides a comprehensive view of the whole data set. Correlation and principal component analysis (PCA) were performed using biomarkers corresponding to or derived from those data, say: induction, AOX(exp), and inhibition, AOX(eff), of Acyl-CoA oxidase enzyme activity; membrane labilisation period, LP, volume density, Vv(LYS), and surface-to-volume ratio, S/V(LYS), of digestive cell lysosomes; volume density of neutral lipids, Vv(NL); volume density of basophilic cells, Vv(BAS), mean luminal radius to mean epithelial thickness in digestive gland epithelium, MLR/MET; gonad index, GI; cumulative intensity of inflammatory responses, CI(IR) and parasitic infestation, CI(PI). The PCA results were used to classify sampling times and localities by means of hierarchical cluster analysis. Biomarkers were more frequently correlated with naphthalene than with total PAH concentration in mussel tissues. Many biological parameters were correlated with each other in agreement with their involvement in toxic processes or their role in the mussels' response against environmental insult. Naphthalene appears to be the most effective toxic herein, which supports that the reported effects may be mainly due to POS. According to the PCA, 4 groups of biomarkers explained 67.37% variability and the factors that most strongly contributed were S/V(LYS), CI(IR), Vv(BAS) and MLR/MET. These factors were used in the hierarchical cluster analyses carried out. The cluster analysis performed to classify sampling times discriminated 3 significantly different periods after POS: (a) a high affection period (until April-04); (b) the beginning of the recovery; and (c) an advanced recovery status in which geographical variability increased (from April-05 onwards). As regards the clustering of localities, major geographical differences were not detected but three outliers were identified: (a) early and highly impacted localities in Galicia and Bay of Biscay; (b) Agui?o that was characterised by extremely high Vv(BAS) during 2003; and (c) localities that were subjected to persistent chronic pollution.     

The potential and limitations of linking biological monitoring data and restoration needs of urbanized waterways: a case study

The implementation of effective strategies to mitigate the impacts of urbanization on waterways represents a major global challenge. Monitoring data plays an important role in the formulation of these strategies. Using monitoring and historical data compiled from around an urban area (Baltimore, USA), this paper is an assessment of the potential and limitations of the use of fish assemblage monitoring data in watershed restoration. A discriminant analysis between assemblages from urban and reference sites was used to determine faunal components which have been reduced or eliminated from Baltimore area waterways. This analysis produced a strong discrimination between fish assemblages from urban and reference sites. Species primarily associated with reference sites varied taxonomically and ecologically, were generally classified as pollution intolerant, and were native. Species associated with urbanized sites were also native, varied taxonomically and ecologically, and were mixed in pollution tolerance. One factor linking most species associated with reference sites was spawning mode (lithophilic). Spawning habitat limitations may be the mechanism through which these species have been reduced in the urbanized faunas. While this presents a strong general hypothesis, information regarding the specific habitat requirements and responses to urbanization of these species is limited. This represents a limitation to producing effective restoration strategies based on exact goals and targets. Without these, determining the type and number of restoration activities required to restore ecological communities remains problematic.     

Application of a battery of biomarkers in mussel digestive gland to assess long-term effects of the Prestige oil spill in Galicia and the Bay of Biscay: lysosomal responses

In order to assess the long-term lysosomal responses to the Prestige oil spill (POS), mussels, Mytilus galloprovincialis, were collected in 22 localities from Galicia and the Bay of Biscay (North Iberian peninsula) in July, and September 2003, April, July, and October 2004-2005 and April 2006. Lysosomal membrane stability (labilisation period, LP) and lysosomal structural changes (lysosomal volume density, Vv(L) and lysosomal surface-to-volume ratio, S/V(L)) were measured as general stress biomarkers. The most remarkable long-term effects after the POS were drastic changes in lysosomal size (lysosomal enlargement) and membrane stability (extremely low LP values) up to April-04. Later on, a recovery trend was envisaged all along the studied area after July-04, albeit membrane stability continued to be below 20 min throughout the studied period up to April-06, which indicates a "distress-to-moderate-stress" condition. Lysosomal Response Index (LRI) revealed that environmental stress was more marked in Galicia than in the Bay of Biscay, mainly in the first sampling year, although a "moderate-to-high-stress" condition persisted until July-05. Overall, although lysosomal size returned to reference values, membrane stability was not fully recovered indicating a stress situation throughout the studied period.     

Application of a battery of biomarkers in mussel digestive gland to assess long-term effects of the Prestige oil spill in Galicia and Bay of Biscay: tissue-level biomarkers and histopathology

In order to assess the biological effects of the Prestige oil spill (POS), mussels, Mytilus galloprovincialis, were collected in 22 localities along the North coast of the Iberian Peninsula over 3 years (April 2003-April 2006). Different tissue-level biomarkers including cell type composition (volume density of basophilic cells, Vv(BAS)) in digestive gland epithelium, structural changes of digestive alveoli (mean luminal radius to mean epithelial thickness, MLR/MET) and histopathological alterations (prevalence and intensity) of the digestive gland were analysed. Severe alterations in the general condition of the digestive gland tissue were observed all over the study area up to 2004-2005. High Vv(BAS) values were recorded mainly in Galicia but also to a lesser extent in the Bay of Biscay in 2003-2004. Atrophy of the digestive alveoli, measured in terms of MLR/MET, was detected all along the studied area up to 2006. Inflammatory responses cannot be related to pollution due to the POS: (a) prevalence and intensity of focal hemocytic infiltration were higher in the Bay of Biscay than in Galicia but they did not show a clear temporal trend; (b) high intensities of brown cell aggregates were only sporadically recorded; and (c) granulocytomas were more frequently recorded in the Bay of Biscay than in Galicia and especially in localities (i.e. Arrigunaga) subjected to chronic pollution. Likewise, Marteilia, trematodes, intracellular ciliates, unidentified eosinophilic bodies, R/CLO and Mytilicola did not follow any recognisable pattern that could be associated to the POS. In contrast, high Nematopsis intensities recorded in several localities in 2003 might suggest some response of local interest after the POS (i.e., in combination with particular factors/conditions). More data at a regional scale are needed before histopathology may provide a reliable ecosystem health assessment but the present results suggest that the approach is worthwhile. Overall, although Vv(BAS) returned to reference values by 2004-2005, MLR/MET values indicated that the mussel health condition was affected during the whole study period up to April 2006.     

Dealing with heterogeneous regression slopes in analysis of covariance: new methodology applied to environmental effects monitoring fish survey data

Analysis of covariance (ANCOVA) is a powerful statistical method which incorporates one or more covariates into the analysis to reduce error associated with measurement. ANCOVA (modeling response as a function of fish size) is frequently used to analyze environmental effects monitoring (EEM) fish survey data. In approximately 12% of fish survey data sets taken from cycles 1 to 3 of Environment Canada’s EEM database for pulp and paper mills, the standard assumption of parallel regression slopes is not met. For the first three cycles of the EEM program, these data sets were classified as indicating a mill effect, but for the most part were excluded from subsequent analyses aimed at quantifying the effect. We present two different methods for initially dealing with data sets that exhibit heterogeneous slopes so that they can be analyzed using the parallel slope model. The first method identifies data sets where heterogeneous slopes are forced by a few high-influence observations. The second approach identifies data sets where a model with heterogeneous slopes is statistically, but not practically, significant: with a high coefficient of determination for the parallel slope model. These new methodologies are applied to EEM pulp and paper data sets and about 55% of cases with heterogeneous slopes can be described by a parallel slope model. We also discuss a third method that can be used to describe mill effects when regression slopes remain heterogeneous even after applying the above two methods, enabling comparison with a critical effect size. These new methodologies could benefit the EEM program by enabling more data sets to be incorporated into meta-analyses and be used to make more equitable mill monitoring decisions in the future.     

Soil heavy metal contamination in an industrial area: analysis of the data collected during a decade

Soil contamination by heavy metals has become a serious problem mainly because, above certain concentrations, all metals have adverse effects on human health. In particular, the accumulation of heavy metals in agricultural soils leads to elevated uptake by crops and affects food quality and safety. In this paper, we present the results of a study carried out over a decade for evaluating the impact of a new industrial settlement in an area geared to agriculture and livestock and far from urban sites. We focus our study on the bioavailable fraction of Cd, Co, Cr, Cu, Fe, Mn, Ni, Pb and Zn in soil samples. Heavy metal concentrations in soil are analysed with both univariate and multivariate statistical procedures. The main goal of this paper is the development of a statistical procedure, based on a mix of multivariate analysis, able to compare field surveys carried out during different years and to characterize spatial and temporal changes in soil heavy metals concentrations.     

Landscape scale ecological monitoring as part of an EIA of major construction activities: experience at the Turkish section of the BTC crude oil pipeline project

Ecological monitoring is a complementary component of the overall environmental management and monitoring program of any Environmental Impact Assessment (EIA) report. The monitoring method should be developed for each project phase and allow for periodic reporting and assessment of compliance with the environmental conditions and requirements of the EIA. Also, this method should incorporate a variance request program since site-specific conditions can affect construction on a daily basis and require time-critical application of alternative construction scenarios or environmental management methods integrated with alternative mitigation measures. Finally, taking full advantage of the latest information and communication technologies can enhance the quality of, and public involvement in, the environmental management program. In this paper, a landscape-scale ecological monitoring method for major construction projects is described using, as a basis, 20 months of experience on the Baku-Tbilisi-Ceyhan (BTC) Crude Oil Pipeline Project, covering Turkish Sections Lot B and Lot C. This analysis presents suggestions for improving ecological monitoring for major construction activities.     

Effect of data pre-treatment procedures on principal component analysis: a case study for mangrove surface sediment datasets

Principal component analysis (PCA) is capable of handling large sets of data. However, lack of consistent method in data pre-treatment and its importance are the limitations in PCA applications. This study examined pre-treatments methods (log (x?+?1) transformation, outlier removal, and granulometric and geochemical normalization) on dataset of Mengkabong Lagoon, Sabah, mangrove surface sediment at high and low tides. The study revealed that geochemical normalization using Al with outliers removal resulted in a better classification of the mangrove surface sediment than that outliers removal, granulometric normalization using clay and log (x?+?1) transformation. PCA output using geochemical normalization with outliers removal demonstrated associations between environmental variables and tides of mangrove surface sediment, Mengkabong Lagoon, Sabah. The PCA outputs at high and low tides also provided to better interpret information about the sediment and its controlling factors in the intertidal zone. The study showed data pre-treatment method to be a useful procedure to standardize the datasets and reducing the influence of outliers.     

Development of low-cost ammonia gas sensors and data analysis algorithms to implement a monitoring grid of urban environmental pollutants

The present study is focused on the implementation of a novel, low cost, urban grid of nanostructured chemresistor gas sensors for ammonia concentration ([NH(3)]) monitoring, with NH(3) being one of the main precursors of secondary fine particulate. Low-cost chemresistor gas sensors based on carbon nanotubes have been developed, their response to [NH(3)] in the 0.17-5.0 ppm range has been tested, and the devices have been properly calibrated under different relative humidity conditions in the 33-63% range. In order to improve the chemresistor selectivity towards [NH(3)], an Expert System, based on fuzzy logic and genetic algorithms, has been developed to extract the atmospheric [NH(3)] (with a sensitivity of a few ppb) from the output signal of a model chemresistor gas sensor exposed to an NO(2), NO(X) and O(3) gas mixture. The concentration of these pollutants that are known to be the most significant interfering compounds during ammonia detection with carbon nanotube gas sensors has been tracked by the ARPA monitoring network in the city of Milan and the historical dataset collected over one year has been used to train the Expert System.     

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.     

On the use of multivariate statistical methods for combining in-stream monitoring data and spatial analysis to characterize water quality conditions in the White River Basin,Indiana, USA

Mechanistic hydrologic and water quality models provide useful alternatives for estimating water quality in unmonitored streams. However, developing these elaborate models for large watersheds can be time-consuming and expensive, in addition to challenges that arise during calibration when there is limited spatial and/or temporal monitored in-stream water quality data. The main objective of this research was to investigate different approaches for developing multivariate analysis models as alternative methods for rapidly assessing relationships between spatio-temporal physical attributes of the watershed and water quality conditions in monitored streams, and then using the developed relationships for estimating water quality conditions in unmonitored streams. The study compares the use of various statistical estimates (mean, geometric mean, trimmed mean, and median) of monitored water quality variables to represent annual and seasonal water quality conditions. The relationship between these estimates and the spatial data is then modeled via linear and non-linear multivariate methods. Overall, the non-linear techniques for classification outperformed the linear techniques with an average cross-validation accuracy of 79.7%. Additionally, the geometric mean based models outperformed models based on other statistical indicators with an average cross-validation accuracy of 80.2%. Dividing the data into annual and quarterly datasets also offered important insights into the behavior of certain water quality variables impacted by seasonal variations. The research provides useful guidance on the use and interpretation of the various statistical estimates and statistical models for multivariate water quality analyses.     

Application of water quality indices and analysis of the surface water quality monitoring network in semiarid North-Central Chile

Surface water quality has increasing importance worldwide and is particularly relevant in the semiarid North-Central Chile, where agriculture and mining activities are imposing heavy pressure on limited water resources. The current study presents the application of a water quality index in four watersheds of the 29°-33°S realm for the period 1999-2008, based on the Canadian Council of Ministers for the Environment approach and the Chilean regulation for irrigation water quality. In addition, two modifications to the index are tested and a comprehensive characterization of the existing monitoring network is performed through cluster analysis. The basins studied show fairly good water quality in the overall, specially the Limarí basin. On the other hand, the lower index values were obtained for the headwaters of Elqui, associated with the El Indio mining district. The first modification of the indicator (i.e., to consider parameters differentially according to their effect on human health or the environment) did not produce major differences with respect to the original index, given the generally good water quality. The second modification (i.e., to consider as threshold values the more restrictive figures derived from a set of regulations) yielded important differences in the indicator values. Finally, an adequate characterization of the monitoring network was obtained. The results presented spatial coherence and the information can be used as a basis for the optimization of the monitoring network if required.     

Trends analysis of ambient 8 hour ozone and precursor monitoring data in the south central U.S

For the south central U.S., lower tropospheric ozone pollution has been a persistent and challenging problem. This paper provides long-term trends analyses of the ozone and precursor monitoring data collected over the past 20 years in four south central U.S. cities. The results of these analyses should be useful to air quality scientists, managers, planners, and modelers in assessing the effectiveness of ozone pollution control strategies being implemented or being planned for the future. Results of the data analyses show that all areas have monitored significant decreases in ozone and precursor concentrations over the past 20 years, especially in El Paso, Texas. Continuing challenges include the reduction of the percentage of time that monitors record 8 hour ozone concentrations over the U.S. 8 hour ozone standard, and the future control of highly reactive volatile organic compounds.     

The need for ecological monitoring of freshwaters in a changing world: a case study of Lakes Annecy,Bourget, and Geneva

Lakes Annecy, Bourget, and Geneva are large, deep carbonated peri-alpine lakes in eastern France. They are located in the same ecoregion but have been subject to differing degrees of anthropogenic pressure over the past decades. A comparative analysis of these ecosystems can therefore provide valuable information on how the lakes have responded to changes in phosphorus runoff, fish management practices, and global warming. Each of these lakes has undergone a restoration process, and changes in water quality and trophic state, as measured using parameters like transparency, chlorophyll a, nutrient concentrations, and phytoplankton biomass and structure, can be used to evaluate efforts made to preserve these ecosystems. Our results reveal that (1) peri-alpine lakes are exemplary cases of restoration in the world where freshwater eutrophication is on the increase, and (2) efforts must be maintained because of the new context of climate change, the effects of which on the quality and the ecological functioning of lakes are still poorly understood.     

Land use and land cover (LULC) of the Republic of the Maldives: first national map and LULC change analysis using remote-sensing data

The Maldives islands in recent decades have experienced dramatic land-use change. Uninhabited islands were turned into new resort islands; evergreen tropical forests were cut, to be replaced by fields and new built-up areas. All these changes happened without a proper monitoring and urban planning strategy from the Maldivian government due to the lack of national land-use and land-cover (LULC) data. This study aimed to realize the first land-use map of the entire Maldives archipelago and to detect land-use and land-cover change (LULCC) using high-resolution satellite images and socioeconomic data. Due to the peculiar geographic and environmental features of the archipelago, the land-use map was obtained by visual interpretation and manual digitization of land-use patches. The images used, dated 2011, were obtained from Digital Globe’s WorldView 1 and WorldView 2 satellites. Nine land-use classes and 18 subclasses were identified and mapped. During a field survey, ground control points were collected to test the geographic and thematic accuracy of the land-use map. The final product’s overall accuracy was 85%. Once the accuracy of the map had been checked, LULCC maps were created using images from the early 2000s derived from Google Earth historical imagery. Post-classification comparison of the classified maps showed that growth of built-up and agricultural areas resulted in decreases in forest land and shrubland. The LULCC maps also revealed an increase in land reclamation inside lagoons near inhabited islands, resulting in environmental impacts on fragile reef habitat. The LULC map of the Republic of the Maldives produced in this study can be used by government authorities to make sustainable land-use planning decisions and to provide better management of land use and land cover.     

Analysis of diazinon monitoring data from the Sacramento and Feather River watersheds: 1991-2001

The objectives of this study were to: (1) analyzehistorical diazinon water column monitoring data frominconsistent monitoring programs in mainstem and tributary sitesin the Sacramento and Feather River watersheds from 1991 to 2001to assess possible spatial and temporal trends and (2) determinethe probability of measured diazinon concentrations by site orsimilar pooled sites exceeding various proposed effectsbenchmarks such as Water Quality Criteria and 10th centilesderived from species sensitivity distributions proposed as targetconcentrations for Total Maximum Daily Loads (TMDLs). An analysisof diazinon monitoring data from both fixed and rain eventsampling from the Sacramento/Feather River watersheds from 1991to 2001 showed that 90th centiles for 27 different mainstemand tributary sites ranged from 12 to 14,897 ng L^-1. The 90th centiles were generally higher at tributary sites (as compared to mainstem sites) during rain event sampling prior to 1995. A comparison of rain event samples for similar sites sampled in 1994 and 2000 showed that 90th centiles were lower in seven of eight sites in 2000. A comparison of pooled mainstemsites between 1994 and 2000 for rain event data showed a lower90th centile value for 2000; 90th centiles were alsolower in 2000 at all pooled tributary sites and all sites whendata from a highly influential site was removed. For varioussite designations (all sites, pooled mainstem sites etc.) theprobability of exceeding the acute and chronic diazinon targetsdeveloped by California Department of Fish and Game decreasedfrom 1994 to 2000. These data clearly show progress in the 6 yrperiod in reducing environmental concentrations of diazinon.Probability of exceeding the 10th centile targets based onspecies sensitivity distributions for arthropods (the mostsensitive taxa to diazinon exposure) was similar and fairly lowbetween years; the highest percent probability of exceedance forany site designation was 20%.Results from a two-way ANOVA using individual measurementsfrom all sites sampled showed a significant decrease during rainevents between 1994 and 2000, although the decrease was notequivalent for all sites. Sources of uncertainty identified inthe analysis of rain event data from 1994 and 2000 wereinconsistent frequency of sampling during rain events for eachyear, unknown definition of rain events between the two years andnon-defined measurement point within the hydrograph of rainevents sampled in each year. Analysis of diazinon trends fromfixed sampling was limited due to lack of yearly data by site;therefore, only parametric analysis could be conducted. Based onparametric analysis of diazinon monitoring data from fixedsampling sites, the percent detected concentrations were greaterthan 20% for 12 tributary sites and 5 mainstem sites fromsamples collected during January-March. On the average over allsites and months, diazinon concentrations have decreased at fixedsampling sites in the Sacramento/Feather River watershed from1991 to 2001.     

Use of earth observation satellite data for land degradation mapping and monitoring in Mediterranean ecosystems: Towards a satellite-observatory

The degradation of the permanent seminatural vegetation and the resulting acceleration of soil degradation and erosion processes constitute major elements of land degradation in the Mediterranean basin. Given the European Commission's interest in mapping and controlling desertification phenomena in the Mediterranean member states, the Environmental Mapping and Modelling Unit (EMAP) of the Joint Research Centre is investigating possibilities for using operational earth observation satellites for mapping and repeated monitoring of vegetation and soil characteristics. In the context of previous experiments, approaches have been developed that can already be routinely applied to large regions. This paper discusses the problems of standardized retrieval of remotely sensed primary parameters (such as reflectance), concepts relating to the thematic interpretation of reflectance data, and the definition of satellite-derived degradation indices. In addition, this paper presents requirements for designing an operational satellite observatory for monitoring Mediterranean land degradation.