Monitoring and validating spatio-temporal dynamics of biogeochemical properties in Mersin Bay (Turkey) using Landsat ETM+

The objective of this study was to devise and validate simple models for estimating spatio-temporal dynamics of seven optically (in)active biogeochemical properties in Mersin Bay using Landsat 7 Enhanced Thematic Mapper Plus (ETM+) data and GIS. Spatio-temporal dynamics of Secchi depth (S (depth)), dissolved oxygen (DO), nitrite nitrogen (NO(2)-N), nitrate nitrogen (NO?-N), silicate (SiO?), 5-day biological oxygen demand (BOD5), and chlorophyll-a (Chl-a) were estimated using best-fit multiple linear regression (MLR) models as a function of Landsat 7 ETM+ and ground data in 2007 and 2008, latitude, longitude, and day of year. Validation of the MLR models against Landsat and ground data in 2005 led to r values ranging from 0.39 for NO?-N (P?=?0.008) to 0.79 for S (depth) (P?相似文献   

Mapping the spatio-temporal distribution of key vegetation cover properties in lowland river reaches,using digital photography

The presence of vegetation in stream ecosystems is highly dynamic in both space and time. A digital photography technique is developed to map aquatic vegetation cover at species level, which has a very high spatial and a flexible temporal resolution. A digital single-lens reflex (DSLR) camera mounted on a handheld telescopic pole is used. The low-altitude (5 m) orthogonal aerial images have a low spectral resolution (red-green-blue), high spatial resolution (～1.9 pixels cm^?2, ～1.3 cm length) and flexible temporal resolution (monthly). The method is successfully applied in two lowland rivers to quantify four key properties of vegetated rivers: vegetation cover, patch size distribution, biomass and hydraulic resistance. The main advantages are that the method is (i) suitable for continuous and discontinuous vegetation covers, (ii) of very high spatial and flexible temporal resolution, (iii) relatively fast compared to conventional ground survey methods, (iv) non-destructive and (v) relatively cheap and easy to use, and (vi) the software is widely available and similar open source alternatives exist. The study area should be less than 10 m wide, and the prevailing light conditions and water turbidity levels should be sufficient to look into the water. Further improvements of the image processing are expected in the automatic delineation and classification of the vegetation patches.     

Health,safety, and environmental risk assessment of steel production complex in central Iran using TOPSIS

This research was carried out with the aim of presenting an environmental management plan for steel production complex (SPC) in central Iran. Following precise identification of the plant activities as well as the study area, possible sources of environmental pollution and adverse impacts on the air quality, water, soil, biological environment, socioeconomic and cultural environment, and health and safety of the employees were determined considering the work processes of the steel complex. Afterwards, noise, wastewater, and air pollution sources were measured. Subsequently, factors polluting the steel complex were identified by TOPSIS and then prioritized using Excel Software. Based on the obtained results, the operation of the furnaces in hot rolling process with the score 1, effluent derived from hot rolling process with the score 0.565, nonprincipal disposal and dumping of waste at the plant enclosure with the score 0.335, walking beam process with the score 1.483 respectively allocated themselves the highest priority in terms of air, water, soil and noise pollution. In terms of habitats, land cover and socioeconomic and cultural environment, closeness to the forest area and the existence of four groups of wildlife with the score 1.106 and proximity of villages and residential areas to the plant with the score 3.771 respectively enjoyed the highest priorities while impressibility and occupational accidents with the score 2.725 and cutting and welding operations with score 2.134 had the highest priority among health and safety criteria. Finally, strategies for the control of pollution sources were identified and Training, Monitoring and environmental management plan of the SPC was prepared.     

Detecting vegetation cover change on the summit of Cadillac Mountain using multi-temporal remote sensing datasets: 1979, 2001, and 2007

This study examines the efficacy of management strategies implemented in 2000 to reduce visitor-induced vegetation impact and enhance vegetation recovery at the summit loop trail on Cadillac Mountain at Acadia National Park, Maine. Using single-spectral high-resolution remote sensing datasets captured in 1979, 2001, and 2007, pre-classification change detection analysis techniques were applied to measure fractional vegetation cover changes between the time periods. This popular sub-alpine summit with low-lying vegetation and attractive granite outcroppings experiences dispersed visitor use away from the designated trail, so three pre-defined spatial scales (small, 0-30 m; medium, 0-60 m; and large, 0-90 m) were examined in the vicinity of the summit loop trail with visitor use (experimental site) and a site chosen nearby in a relatively pristine undisturbed area (control site) with similar spatial scales. Results reveal significant changes in terms of rates of vegetation impact between 1979 and 2001 extending out to 90 m from the summit loop trail with no management at the site. No significant differences were detected among three spatial zones (inner, 0-30 m; middle, 30-60 m; and outer, 60-90 m) at the experimental site, but all were significantly higher rates of impact compared to similar spatial scales at the control site (all p?< 0.001). In contrast, significant changes in rates of recovery between 2001 and 2007 were observed in the medium and large spatial scales at the experimental site under management as compared to the control site (all p?< 0.05). Also during this later period a higher rate of recovery was observed in the outer zone as compared to the inner zone at the experimental site (p?< 0.05). The overall study results suggest a trend in the desired direction for the site and visitor management strategies designed to reduce vegetation impact and enhance vegetation recovery at the summit loop trail of Cadillac Mountain since 2000. However, the vegetation recovery has been rather minimal and did not reach the level of cover observed during the 1979 time period. In addition, the advantages and some limitations of using remote sensing technologies are discussed in detecting vegetation change in this setting and potential application to other recreation settings.     

Metal concentrations in the soils and native plants surrounding the old flotation tailings pond of the copper mining and smelting complex Bor (Serbia)

In this study concentrations of metals in the native plants and soils surrounding the old flotation tailings pond of the copper mine were determined. It has been established that the soil is heavily contaminated with copper, iron and arsenic, the mean concentrations being 1585.6, 29,462.5 and 171.7 mg kg(-1) respectively. All the plants, except manganese, accumulated metallic elements in concentrations which were either in the range of critical and phytotoxic values (Pb and As) or higher (Zn), and even much higher (Cu and Fe) than these values. Otherwise, the accumulation of Mn, Pb and As was considerably lower than that of Cu, Fe and Zn. In most plants the accumulation of target metals was highest in the root. Several plant species showed high bioaccumulation and translocation factor values, which classify them into species for potential use in phytoextraction. The BCF and TF values determined in Prunus persica were 1.20 and 3.95 for Cu, 1.5 and 6.0 for Zn and 1.96 and 5.44 for Pb. In Saponaria officinalis these values were 2.53 and 1.27 for Zn, and in Juglans regia L. they were 8.76 and 17.75 for Zn. The translocation factor in most plants, for most metals, was higher than one, whereas the highest value was determined in Populus nigra for Zn, amounting to 17.8. Among several tolerant species, the most suitable ones for phytostabilization proved to be Robinia pseudoacacia L. for Zn and Verbascum phlomoides L., Saponaria officinalis and Centaurea jacea L. for Mn, Pb and As.     

Modeling of Cr contamination in the agricultural lands of three villages near the leather industry in Kasur,Pakistan, using statistical and GIS techniques

Kasur is one of the hubs of leather industry in the Punjab, Pakistan, where chrome tanning method of leather processing is extensively being used. Chromium (Cr) accumulation levels in the irrigation water, soil, and seasonal vegetables were studied in three villages located in the vicinity of wastewater treatment plant and solid waste dumping site operated by the Kasur Tanneries Waste Management Agency (KTWMA). The data was interpreted using analysis of variance (ANOVA), clustering analysis (CA), and principal component analysis (PCA). Interpolated surface maps for Cr were generated using the actual data obtained for the 30 sampling sites in each of the three villages for irrigation water, soil, and seasonal vegetables. The level of contamination in the three villages was directly proportional to their distance from KTWMA wastewater treatment plant and the direction of water runoff. The highest level of Cr contamination in soil (mg kg^?1) was observed at Faqeeria Wala (37.67), intermediate at Dollay Wala (30.33), and the least in Maan (25.16). A gradational variation in Cr accumulation was observed in the three villages from contaminated wastewater having the least contamination level (2.02–4.40 mg L^?1), to soil (25.16–37.67 mg kg^?1), and ultimately in the seasonal vegetable crops (156.67–248.33 mg kg^?1) cultivated in the region, having the highest level of Cr contamination above the permissible limit. The model used not only predicted the current situation of Cr contamination in the three villages but also indicated the trend of magnification of Cr contamination from irrigation water to soil and to the base of the food chain. Among the multiple causes of Cr contamination of vegetables, soil irrigation with contaminated groundwater was observed to be the dominant one.     

Accuracy assessment of land surface temperature retrievals from Landsat 7 ETM + in the Dry Valleys of Antarctica using iButton temperature loggers and weather station data

The McMurdo Dry Valleys of Antarctica are the largest snow/ice-free regions on this vast continent, comprising 1 % of the land mass. Due to harsh environmental conditions, the valleys are bereft of any vegetation. Land surface temperature is a key determinate of microclimate and a driver for sensible and latent heat fluxes of the surface. The Dry Valleys have been the focus of ecological studies as they arguably provide the simplest trophic structure suitable for modelling. In this paper, we employ a validation method for land surface temperatures obtained from Landsat 7 ETM + imagery and compared with in situ land surface temperature data collected from four transects totalling 45 iButtons. A single meteorological station was used to obtain a better understanding of daily and seasonal cycles in land surface temperatures. Results show a good agreement between the iButton and the Landsat 7 ETM + product for clear sky cases. We conclude that Landsat 7 ETM + derived land surface temperatures can be used at broad spatial scales for ecological and meteorological research.     

TSP, PM depositions, and trace elements in the vicinity of a cement plant and their source apportionments using chemical mass balance model in Izmir, Turkey

Total suspended particles mass concentrations (TSP) and bulk depositions of particulate matter (PM depositions) were measured around a cement plant located in the multi-impacted area to assess the affect of the plant on the ambient air in the vicinity in Izmir, Turkey. TSP samples were collected five times a month whereas PM depositions were sampled monthly at four sites between August 2003 and January 2004. The concentrations of Al, Ca, Cd, Cr, Cu, Fe, K, Mg, Mn, Na, Ni, Pb, V, and Zn in TSP and PM depositions (except Cu) were reported. Chemical mass balance (CMB) receptor model with local source profiles was run in order to calculate the source contributions of the PM sources to the concentrations of TSP, PM depositions, and trace elements. Traffic was found to be the major contributor to TSP whereas PM depositions dominantly result from area sources including several stone quarries, concrete plants, lime kilns, and asphalt plants in the region. CMB model results indicate that the cement plant is a significant contributor to TSP, PM depositions, and trace elements, particularly Cd.     

Heavy metal assessment using geochemical and statistical tools in the surface sediments of Vembanad Lake, Southwest Coast of India

The geochemical distribution and enrichment of ten heavy metals in the surface sediments of Vembanad Lake, southwest coast of India was evaluated. Sediment samples from 47 stations in the Lake were collected during dry and wet seasons in 2008 and examined for heavy metal content (Al, Fe, Mn, Cr, Zn, Ni, Pb, Cu, Co, Cd), organic carbon, and sediment texture. Statistically significant spatial variation was observed among all sediment variables, but negligible significant seasonal variation was observed. Correlation analysis showed that the metal content of sediments was mainly regulated by organic carbon, Fe oxy-hydroxides, and grain size. Principal component analysis was used to reduce the 14 sediment variables into three factors that reveal distinct origins or accumulation mechanisms controlling the chemical composition in the study area. Pollution intensity of the Vembanad Lake was measured using the enrichment factor and the pollution load index. Severe and moderately severe enrichment of Cd and Zn in the north estuary with minor enrichment of Pb and Cr were observed, which reflects the intensity of the anthropogenic inputs related to industrial discharge into this system. The results of pollution load index reveal that the sediment was heavily polluted in northern arm and moderately polluted in the extreme end and port region of the southern arm of the lake. A comparison with sediment quality guideline quotient was also made, indicating that there may be some ecotoxicological risk to benthic organisms in these sediments.     

Assessment of drinking water quality using ICP-MS and microbiological methods in the Bholakpur area,Hyderabad, India

A total of 16 people died and over 500 people were hospitalized due to diarrhoeal illness in the Bholakpur area of Hyderabad, India on 6th May 2009. A study was conducted with immediate effect to evaluate the quality of municipal tap water of the Bholakpur locality. The study consists of the determination of physico-chemical properties, trace metals, heavy metals, rare earth elements and microbiological quality of drinking water. The data showed the variation of the investigated parameters in samples as follows: pH 7.14 to 8.72, EC 455 to 769 μS/cm, TDS 303.51 to 515.23 ppm and DO 1.01 to 6.83 mg/L which are within WHO guidelines for drinking water quality. The water samples were analyzed for 27 elements (Li, Be, B, Na, Mg, Al, Si, K, Ca, V, Cr, Mn, Fe, Ni, Co, Cu, Zn, As, Se, Rb, Sr, Mo, Ag, Cd, Sb, Ba and Pb) using inductively coupled plasma-mass spectrometry (ICP-MS). The concentrations of Fe (0.12 to 1.13 mg/L), Pb (0.01 to 0.07 mg/L), Cu (0.01 to 0.19 mg/L), Ni (0.01 to 0.15 mg/L), Al (0.16 to 0.49 mg/L), and Na (38.36 to 68.69 mg/L) were obtained, which exceed the permissible limits of the World Health Organization (WHO) for drinking water quality guidelines. The remaining elements were within the permissible limits. The microbiological quality of water was tested using standard plate count, membrane filtration technique, thermotolerant coliform (TTC), and most probable number (MPN) methods. The total heterotrophic bacteria ranged from 1.0 × 10⁵ to 18 × 10⁷ cfu/ml. Total viable bacteria in all the water samples were found to be too numerable to count and total number of coliform bacteria in all water samples were found to be of order of 1,100 to >2,400 MPN index/100 ml. TTC tested positive for coliform bacteria at 44.2°C. All the water samples of the study area exceeded the permissible counts of WHO and that (zero and minimal counts) of the control site (National Geophysical Research Institute) water samples. Excessively high colony numbers indicate that the water is highly contaminated with microorganisms and is hazardous for drinking purposes. Bacteriological pollution of drinking water supplies caused diarrhoeal illness in Bholakpur, which is due to the infiltration of contaminated water (sewage) through cross connection, leakage points, and back siphoning.     

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.     

Modeling the effect of land use/land cover on nitrogen,phosphorous and dissolved oxygen loads in the Velhas River using the concept of exclusive contribution area

Non-point source water pollution is a major problem in most parts of the world, but is also very difficult to quantify and control since it is not easily separated from point sources and can theoretically originate from the whole watershed. In this article, we evaluate the relationship between land use and land cover and four water pollution parameters in a watershed in Southeast Brazil. The four parameters are nitrate, total ammonia nitrogen, total phosphorous, and dissolved oxygen. To help concentrate on non-point source pollution, only data from the wet seasons of the time period (2001–2013) were analysed, based on the fact that precipitation causes runoff which is the main cause of diffuse pollution. The parameters measured were transformed into loads, which were in turn associated with an exclusive contribution area, so that every measuring station could be considered independent. Analyses were also performed on riparian zones of different widths to verify if the effect of the land cover on the water quality of the stream decreases with the increased distance. Pearson correlation coefficients indicate that urban areas and agriculture/pasture tend to worsen water quality (source). Conversely, forest and riparian areas have a reducing effect on pollution (sink). The best results were obtained for total ammonia nitrogen and dissolved oxygen using the whole exclusive contribution areas with determination coefficients better than R²≈0.8. Nitrate and total phosphorous did not produce valid models. We suspect that the transformation delay from total ammonia nitrogen to nitrate might be an important factor for the poor result for this parameter. For phosphorous, we think that the phosphorous sink in the bottom sediment might be the most limiting factor explaining the failure of our models.     

Estimation of nested spatial patterns and seasonal variation in the longitudinal distribution of Sicyopterus japonicus in the Datuan Stream, Taiwan by using geostatistical methods

This study attempts to determine the scale-dependent hierarchical spatial variation and longitudinal distributions of Sicyopterus japonicus year round. The distribution of S. japonicus in the Datuan Stream in northern Taiwan was surveyed during the fall and winter 2007, as well as the spring and summer of 2008. The spatial structure of S. japonicus density was modeled using geostatistics. The longitudinal distributions of S. japonicus density were then estimated using kriging and hydrology distance with nested variogram models. Variography results indicate that nested variogram models could reflect the hierarchical structure in the spatial variation of seasonal S. japonicus density, with the small, median, and large ranges representing three nested scales. Models for the four seasons were consistent in that they shared the same shape of variogram models with various ranges and sill values. This model shape consistency implies stationary spatial correlations in the longitudinal fish distribution across the four seasons. The Kriging geostatistical method based on the multiple scales nested variogram models also provided robust estimates of S. japonicus densities at unsampled sections. We conclude that S. japonicus densities exhibit hierarchical patterns and variation in the four seasons along the study stream. Geostatistical methods with a nested variograms and hydrological distance are a highly effective means of delineating the hierarchical structure in longitudinal patterns of S. japonicus density in each season, providing estimates of the S. japonicus density for hierarchically structured spatial distributions and expanding knowledge of S. japonicus beyond the limits imposed by spatial and temporal scales.