An integrated approach for spatio-temporal variability analysis of wetlands: a case study of Abaya and Chamo lakes, Ethiopia

Starting with the intensification of irrigation activities in the beginning of 1980s in Abaya and Chamo lakes area, the decreasing water inflow to the lakes caused denudation of the wetlands. The ecological situation in the lake region changed significantly during last four decades. The lakes and associated wetlands change have been studied using Landsat MSS (1973), Landsat TM (1986), and Ladsat ETM (2000) satellite imagery. Along with satellite imagery, other hydro-meteorological data were collected and hydro-meteorological data analyses were done to assess the variability of wetlands. From these data, lakes morphometric property estimation at different time series and water balance analysis for both lakes were done. Wetlands are mapped from the TCT image and these maps are subject to change detection to see the temporal and spatial variability of the wetlands. Moreover, the lake-morphometric area and volume variation have been studied. The result showed that between 1986 and 2000, a significant reduction has been observed but lesser than the previous decades (6.4 km(2)). The identified reason behind this change is that the free settlement and shoreline cultivation of the wetlands causing the soil erosion and eventually adds the sediment to the wetlands.     

A comparison of two procedures to estimate three basic monitoring landscape metrics for monitoring

An interesting alternative to wall-to-wall mapping approaches for the estimation of landscape metrics is to use sampling. Sample-based approaches are cost-efficient, and measurement errors can be reduced considerably. The previous efforts of sample-based estimation of landscape metrics have mainly been focused on data collection methods, but in this study, we consider two estimation procedures. First, landscape metrics of interest are calculated separately for each sampled image and then the image values are averaged to obtain an estimate of the entire landscape (separated procedure, SP). Second, metric components are calculated in all sampled images and then the aggregated values are inserted into the landscape metric formulas (aggregated procedure, AP). The national land cover map (NLCM) of Sweden, reflecting the status of land cover in the year 2000, was used to provide population information to investigate the statistical performance of the estimation procedures. For this purpose, sampling simulation with a large number of replications was used. For all three landscape metrics, the second procedure (AP) produced a lower relative RMSE and bias than the first one (SP). A smaller sample unit size (50 ha) produced larger bias than a larger one (100 ha), whereas a smaller sample unit size produced a lower variance than a larger sample unit. The efficiency of a metric estimator is highly related to the degree of landscape fragmentation and the selected procedure. Incorporating information from all of the sampled images into a single one (aggregated procedure, AP) is one way to improve the statistical performance of estimators.     

Errors in ozone risk assessment using standard conditions for converting ozone concentrations obtained by passive samplers in mountain regions

Passive samplers are often employed to measure ozone concentrations in remote areas such as mountain forests. The potential ozone risk for vegetation is then assessed by calculating the AOT40 exposure index (accumulated hourly ozone concentration exceedances above 40 ppb, i.e. AOT40 = Σ([O(3)] - 40)Δt for any hourly ozone concentration [O(3)] > 40 ppb). AOT40 is customary calculated on the basis of ozone concentrations expressed as a volumetric mixing ratio, while lab sheets normally report ozone concentrations from passive samplers in mass units per cubic metre. Concentrations are usually converted from mass units to ppb using a standard conversion factor taking SATP (Standard Ambient Temperature and Pressure) conditions into account. These conditions, however, can vary considerably with elevation. As a consequence, the blanket application of a standard conversion factor may lead to substantial errors in reporting and mapping ozone concentrations and therefore in assessing potential ozone risk in mountain regions. In this paper we carry out a sensitivity analysis of the effects of uncertainties in estimations of air temperature (T) and atmospheric pressure (P) on the concentration conversion factor, and present two examples from two monitoring and mapping exercises carried out in the Italian Alps. We derived P and T at each site from adiabatic lapse rates for temperature and pressure and analysed the magnitude of error in concentration estimations. Results show that the concentration conversion is much more sensitive to uncertainties in P gradient estimation than to air temperature errors. The concentration conversion factor (cf) deviates 5% from the standard transformation at an elevation of 500 m asl. As a consequence, the standard estimated AOT40 at this elevation is about 13% less than the actual value. AOT40 was found to be underestimated by an average between 25% and 34% at typical elevations of mountain forest stands in the Italian Alps when a correct conversion factor for transforming ozone concentrations from μg m(-3) to ppb is not applied.     

燃煤工业城市大气细颗粒物中水溶性无机离子的季节变化特征及来源解析——以邯郸市为例

为探究典型燃煤工业城市邯郸市的大气细颗粒物(PM2.5)污染水平及水溶性无机离子特征,于2016年1—12月采集了当地大气PM2.5样品,然后利用离子色谱法测得水溶性无机离子的组分,分析了不同季节水溶性无机离子随PM2.5的浓度变化特征。通过对PM2.5中的阴离子、阳离子进行分析发现,SO4^2-、NO3^-和NH4^+在春夏秋冬四季均为PM2.5中的主要离子成分,SO4^2-、NO3^-和NH4^+的浓度之和在春夏秋冬四季占各季节总的水溶性无机离子浓度的百分比分别为84.6%、77.4%、89.9%、62.5%。其中,在春季和冬季含量最高的3种离子分别是NO3^-、SO4^2-和NH4^+,夏季含量最高的3种离子分别是SO4^2-、NH4^+和NO3^-,而秋季含量最高的3种离子分别是NH4^+、SO4^2-和NO3^-。相关性分析发现,2016年春季、夏季和秋季PM2.5为酸性,冬季为碱性。SO4^2-、NO3^-、NH4^+浓度分析表明,冬季PM2.5中的一次建筑扬尘排放较多。通过主成分分析法得出,PM2.5中水溶性无机离子主要来源于二次转化和生物质燃烧。     

Occurrence and exposure assessment of perchlorate, iodide and nitrate ions from dairy milk and water in Japan and Sri Lanka

Perchlorate is known to competitively interfere with iodide uptake by the thyroid gland and thereby human exposure to perchlorate is a public health concern. Prevalence of perchlorate in dairy milk is documented; nevertheless, co-occurrence of perchlorate with other thyroid-binding monovalent ions such as iodide and nitrate is not well understood. In this study, we analyzed perchlorate, iodide, and nitrate-N in dairy milk, water and other dairy-related samples collected from Japan and Sri Lanka. Concentrations of perchlorate in Japanese dairy milk samples ranged from 1.03 to 14.1 ng ml(-1); the corresponding concentrations in dairy milk and powdered milk from Sri Lanka were 1.14-38.5 ng ml(-1). Perchlorate concentrations in commercial milk were significantly higher in Japan than in Sri Lanka, while iodide and nitrate levels in milk between the two countries were comparable. All three ions were ubiquitously found in water samples from Japan and Sri Lanka. Analysis of colostrum and raw milk collected from cows fed with the same feed for over 30 days showed no significant temporal variations in perchlorate, iodide and nitrate-N concentrations. A significant positive correlation was found between the concentrations of perchlorate and iodide in Japanese commercial milk. The concentrations of perchlorate and nitrate-N in water samples analyzed from both countries also showed a significant positive correlation. The exposure estimation revealed that dairy milk provides a greater source for perchlorate and iodide, while water predominantly contributes nitrate-N intake for all age groups in both counties. Infants and children demonstrated the highest estimated perchlorate, iodide and nitrate-N intake on a body weight basis in comparison to other age groups. Therefore, further studies of risk associated with perchlorate may need to reconsider co-existence of iodine and other iodide transport inhibitors in food.     

Uncertainty based optimal monitoring network design for a chlorinated hydrocarbon contaminated site

An application of a newly developed optimal monitoring network for the delineation of contaminants in groundwater is demonstrated in this study. Designing a monitoring network in an optimal manner helps to delineate the contaminant plume with a minimum number of monitoring wells at optimal locations at a contaminated site. The basic principle used in this study is that the wells are installed where the measurement uncertainties are minimum at the potential monitoring locations. The development of the optimal monitoring network is based on the utilization of contaminant concentration data from an existing initial arbitrary monitoring network. The concentrations at the locations that were not sampled in the study area are estimated using geostatistical tools. The uncertainty in estimating the contaminant concentrations at such locations is used as design criteria for the optimal monitoring network. The uncertainty in the study area was quantified by using the concentration estimation variances at all the potential monitoring locations. The objective function for the monitoring network design minimizes the spatial concentration estimation variances at all potential monitoring well locations where a monitoring well is not to be installed as per the design criteria. In the proposed methodology, the optimal monitoring network is designed for the current management period and the contaminant concentration data estimated at the potential observation locations are then used as the input to the network design model. The optimal monitoring network is designed for the consideration of two different cases by assuming different initial arbitrary existing data. Three different scenarios depending on the limit of the maximum number of monitoring wells that can be allowed at any period are considered for each case. In order to estimate the efficiency of the developed optimal monitoring networks, mass estimation errors are compared for all the three different scenarios of the two different cases. The developed methodology is useful in coming up with an optimal number of monitoring wells within the budgetary limitations. The methodology also addresses the issue of redundancy, as it refines the existing monitoring network without losing much information of the network. The concept of uncertainty-based network design model is useful in various stages of a potentially contaminated site management such as delineation of contaminant plume and long-term monitoring of the remediation process.     

Integrating in-situ, Landsat, and MODIS data for mapping in Southern African savannas: experiences of LCCS-based land-cover mapping in the Kalahari in Namibia

Integrated ecosystem assessment initiatives are important steps towards a global biodiversity observing system. Reliable earth observation data are key information for tracking biodiversity change on various scales. Regarding the establishment of standardized environmental observation systems, a key question is: What can be observed on each scale and how can land cover information be transferred? In this study, a land cover map from a dry semi-arid savanna ecosystem in Namibia was obtained based on the UN LCCS, in-situ data, and MODIS and Landsat satellite imagery. In situ botanical relevé samples were used as baseline data for the definition of a standardized LCCS legend. A standard LCCS code for savanna vegetation types is introduced. An object-oriented segmentation of Landsat imagery was used as intermediate stage for downscaling in-situ training data on a coarse MODIS resolution. MODIS time series metrics of the growing season 2004/2005 were used to classify Kalahari vegetation types using a tree-based ensemble classifier (Random Forest). The prevailing Kalahari vegetation types based on LCCS was open broadleaved deciduous shrubland with an herbaceous layer which differs from the class assignments of the global and regional land-cover maps. The separability analysis based on Bhattacharya distance measurements applied on two LCCS levels indicated a relationship of spectral mapping dependencies of annual MODIS time series features due to the thematic detail of the classification scheme. The analysis of LCCS classifiers showed an increased significance of life-form composition and soil conditions to the mapping accuracy. An overall accuracy of 92.48% was achieved. Woody plant associations proved to be most stable due to small omission and commission errors. The case study comprised a first suitability assessment of the LCCS classifier approach for a southern African savanna ecosystem.     

Recent Changes in Soil Total Phosphorus in the Everglades: Water Conservation Area 3

We assessed recent changes in the distribution of soil total phosphorus (TP) in Water Conservation Area 3 (WCA-3) of the Everglades. Soil cores were collected in 1992 and 2003 at 176 sites. To reflect hydrologic boundaries within the system, WCA-3 was divided into three zones (3AN, 3AS, and 3B). Total P was mapped on both a mass (TPm) and a volumetric basis (TPv) to determine if spatial distributions varied depending on the choice of units. Interpolated maps for both years showed that the highest levels of TPm were located in 3AN and in boundary areas of all zones that received surface water inputs of P from canals. Increases in TPm were greatest in central 3AN in an area adjacent to the Miami Canal that received inputs from a water control structure. Interpolated maps for TPv illustrated that a hotspot present in 1992 had disappeared by 2003. The highest levels of TPv in 2003 were located in northwestern 3AN, a region of WCA-3 that has been chronically overdrained and burned in 1999. From 1992 to 2003, increases in TPm were observed for 53% of the area of WCA-3, while only 16% of WCA-3 exhibited increases in TPv. In 1992, approximately 21% of WCA-3 had TPm concentrations in the 0–10 cm layer >500 mg kg⁻¹, indicating P enrichment beyond historic levels. Eleven years later, 30% of the area of WCA-3 had TPm >500 mg kg⁻¹. This indicated that during this period, the area of WCA-3 with enriched TPm concentrations increased about one % year⁻¹.     

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.     

Simplicity versus efficiency in sampling designs and estimation

Simplicity and efficiency in design and estimation are all important in deciding on sampling strategies. A simple model is given and illustrated for four practical situations to show how a good sampling strategy should be selected.The U.S. Government right to retain a non-exclusive, royalty free licence in and to any copyright is acknowledged.     

Assessment of regional metal levels in ambient air by statistical regression models

The assessment of the particulate matter (PM) levels and its constituents presented in the atmosphere is an important requirement of the air quality management and air pollution abatement. The heavy metal levels in PM10 are commonly evaluated by experimental measurements; nevertheless, the EC Directives also allow the Regional Governments to estimate the regulated metal levels (Pb in Directive 2008/50/EC and As, Ni and Cd in Directive 2004/107/EC) by objective estimation and modelling techniques. These techniques are proper alternatives to the experimental determination because the required analysis and/or the number of required sampling sites are reduced. The present work aims to estimate the annual levels of regulated heavy metals by means of multivariate linear regression (MLR) and principal component regression (PCR) at four sites in the Cantabria region (Northern Spain). Since the objective estimation techniques may only be applied when the regulated metal concentrations are below to the lower assessment threshold, a previous evaluation of the determined annual levels of heavy metals is conducted to test the fulfilment of the EC Directives requirements. At the four studied sites, the results show that the objective estimations are allowed alternatives to the experimental determination. The annual average metal concentrations are well estimated by the MLR technique in all the studied sites; furthermore, the EC quality requirements for the objective estimations are fulfilled by the developed statistical MLR models. Hence these estimations may be used by Regional Governments as a proper alternative to the experimental measurements for the regulated metal levels assessment.     

Monitoring of the Endangered Pinna nobilis Linné, 1758 in the Mar Grande of Taranto (Ionian Sea, Italy)

Two methods were used to calculate the meteorologically adjusted ground level ozone trends in southern Taiwan. The first method utilized is a robust linear regression method. The second approach uses a multilayer perceptron (MLP) artificial neural network (ANN) method. The observations obtained from 16 monitoring stations were analyzed and divided into six groups by hierarchical divisive clustering procedure. The daily maximum 1 and 8 h ozone concentrations for each group are then calculated. The meteorologically adjusted trends obtained by linear regression and MLP methods are smaller than the unadjusted trends for all groups and average time. It indicts that the meteorological conditions in Taiwan tend to increase ambient ozone concentrations in recent years.     

A necessary distinction between spatial representativeness of an air quality monitoring station and the delimitation of exceedance areas

The European legislation on ambient air quality introduces the concepts of spatial representativeness of a monitoring station and spatial extent of an exceedance zone. Spatial representativeness is an essential macro-scale siting criterion which should be evaluated before the setting-up and during the life of a monitoring point. As for the exceedance area, it has to be defined each time an environmental objective is exceeded in an assessment zone. No specific approach is prescribed to delimit such areas. A probabilistic methodology is presented, based on a preliminary kriging estimation of atmospheric concentrations at each point of the domain. It is applied to NO₂ pollution on the urban scale. In the proposed approach, a point belongs to the area of representativeness of a station if its concentration differs from the station measurement by less than a given threshold. To take the estimation uncertainty into account, the standard deviation of the kriging error is used in a probabilistic framework. The choice of the criteria used to deal with overlapping areas is first tested on NO₂ annual mean concentration maps of France, built by combining surface monitoring observations and outputs from the CHIMERE chemistry transport model. At the local scale, data from passive sampling surveys and high -resolution auxiliary variables are used to provide a more precise estimation of the background pollution in different French cities. The traffic-related pollution can also be accounted for in the map by additional predictors such as distance to the road, and traffic-related NO_x emissions. Similarly, the proposed approach is implemented to identify the points, at a given statistical risk, where the NO₂ concentration is above the annual limit value.     

Assessment of groundwater vulnerability in the coastal region of Oman using DRASTIC index method in GIS environment

A study was carried out to develop a vulnerability map for Barka region in the North Batina of Oman using DRASTIC vulnerability index method in GIS environment. DRASTIC layers were created using data from published reports and the seven DRASTIC layers were processed by the ArcGIS geographic information system. Finally, DRASTIC maps were created for 1995 and 2004 to understand the long-term changes in the vulnerability index. DRASTIC vulnerability maps were evaluated using groundwater quality data such as chemical and biological parameters. DRASTIC vulnerability maps of 1995 and 2004 indicate that the northern part of Barka is more vulnerable to pollution than southern part and the central part of Barka also shows high relative vulnerability which is mostly related to the high conductivity values. Moreover, the changes in water level due to high abstraction rate of groundwater reflect in the vulnerability maps and low vulnerability area is increased in the southern part during 2004 compared to 1995. Moreover, regional distribution maps of nitrate, chloride and total and fecal coliforms are well correlated with DRASTIC vulnerability maps. In contrast to this, even though DRASTIC method predicted the central part of the study region is highly vulnerable, both chemical and biological parameters show lower concentrations in this region compared to coastal belt, which is mainly due to agricultural and urban development. In Barka, urban development and agricultural activities are very high in coastal region compared to southern and central part of the study area. Hence, this study concluded that DRASTIC method is also applicable in coastal region having ubiquitous contamination sources.     

The impact of poultry litter application on sediment chemistry of the Broadkill River estuary system, Delaware

This project examined the impact of long-term poultry litter application on the chemical signatures of As, Cu, Zn, and P in stream sediments of the Broadkill River watershed within the Delmarva Peninsula, a region of intense poultry production. Thirty-seven sediment samples were collected from Broadkill River drainage systems and analyzed for litter-derived elements (As, Cu, Zn, P) and basic soil parameters such as particle size distribution, organic matter, and soluble salts. Results showed that concentrations of elements in stream sediments are approximately log-normally distributed. Spatial variability in concentrations of elements was evident, with most elements increasing in concentration and enrichment from upgradient headwaters to downgradient reaches draining predominantly agricultural areas. Results of correlation analyses showed positive significant correlation among elements; elements were also positively correlated with percent clay and silt in the sediment. Using GIS maps with overlays of hydrology and land use activities, statistical correlations between As, Cu, Zn, and P enrichment factors and land use were examined. Results showed statistically significant relationships between As, Mn, and Zn enrichment factors and residential areas within the watershed, but did not show a statistically significant relationship between element enrichment factors and agricultural land use. Factors that complicate this type of landscape-scale study include the presence of poultry processing plants, impoundments, changes in land use over time, and the influence of tides, all of which can have direct and indirect influences on element mobility.     

Toxic Metals in the Austrian Pine (Pinus Nigra) Bark in the Thrace Region, Turkey

Austrian pine (Pinus nigra) bark was collected in thirty-seven localities in the Thrace region, Turkey, for the determination of airborne toxic metal distribution. Five toxic metals, As, Cd, Cu, Pb, and Zn, were monitored using atomic absorption spectrometry. Distribution maps of toxic elements in the region were plotted according to Geographic Information System technology. In general, the concentrations of all investigated elements were not high in the region apart from the vicinity of big cities, Tekirdag, Istanbul and, close to Bulgarian border. However, the highest concentrations were not at pollution level. They have a similar distribution pattern throughout the region.     

Global monitoring at the United States baseline stations with emphasis on precipitation chemistry measurements

The National Oceanic and Atmospheric Administration Geophysical Monitoring for Climatic Change program has operated four remote precipitation chemistry stations at two polar and two tropical Pacific locations for over a decade. Station geography and meteorology is discussed and a summary of the hydrogen, sulfate, and nitrate ion data collected since 1980 is presented. Results show that at all four locations, the ions which have major anthropogenic sources were far less concentrated than in samples collected in heavily industrialized areas in the northeastern United States and Europe. Concentrations at American Samoa and the South Pole showed little variability over the year whereas concentrations at Point Barrow, Alaska and Mauna Loa, Hawaii were highly variable.Contribution from Fourth World Wilderness Congress-Acid Rain Symposium, Denver (Estes Park), Colorado, September 11–18, 1987.     

CDOM fluorescence as a proxy of DOC concentration in natural waters: a comparison of four contrasting tropical systems

Chromophoric dissolved organic matter (CDOM) fluorescence or absorption is often proposed as a rapid alternative to chemical methods for the estimation of bulk dissolved organic carbon (DOC) concentration in natural waters. However, the robustness of this method across a wide range of systems remains to be shown. We measured CDOM fluorescence and DOC concentration in four tropical freshwater and coastal environments (estuary and coastal, tropical shallow lakes, water from the freshwater lens of two small islands, and soil leachates). We found that although this method can provide an estimation of DOC concentration in sites with low variability in DOC and CDOM sources in systems where the variability of DOC and CDOM sources are high, this method should not be used as it will lead to errors in the estimation of the bulk DOC concentration.     

Ambient BTX measurements in Suzhou, China

Within the Sino-Italian environmental protection cooperation framework established in 2002, a comprehensive air quality monitoring network has been developed in urban Suzhou, a medium-sized Chinese city, in compliance with European standards (Directive 96/62/EC). This paper is among the first attempts to present a systematic and scientific analysis of benzene, toluene, and xylenes (BTX) pollution in China. It presents our analysis of BTX space-related and time-related measurement results. Background BTX concentrations were investigated by passive sampler Analyst® in 2003. We depicted the spatial distribution of average BTX concentrations collected from three 15-day campaigns on isoconcentration maps. This is the first time such detailed BTX concentration maps have been developed in China in a city scale. Continuous measurement of BTX by automatic gas chromatography was carried out at two fixed monitoring stations, one in an urban residential zone and one in a heavy traffic zone, from April to December 2005. The results show similar seasonal trends at both sites, the similarities reaching their greatest level in December and their lowest level in August. The average daily profile of BTX shows greater fluctuation in spring and winter with clear morning and evening peaks. Daily average benzene, toluene, and m,p-xylenes concentrations for the study period were 2.64, 11.52, and 3.52 μg m^???3, respectively. The benzene/toluene ratio we found was lower in Suzhou than those published in studies of other worldwide cities, which indicates serious levels of toluene pollution from local stationary sources. The similarities in seasonal trend and spatial distribution in these manual and automatic measurement results were compared with each other, though the concentration values differed.     

Spatial patterns of nitrate,chloride, sulfate,and fluoride concentrations in the Woodbine Aquifer of north-central Texas

A geographic information system was used to map and analyze nitrate, chloride, sulfate, and fluoride concentrations in 110 wells tapping the Woodbine Aquifer. The study area, covering ninecounties in north-central Texas, includes large percentages of both urban and agricultural land uses. Land use maps were compared with solute concentration data, and statistics were applied to detect associations between solutes, well depth, andland use. Anthropogenic sources such as fertilizer applications and natural sources such as gypsum, lignite, and clay deposits controlled nitrate, chloride, and sulfate concentrations, each inversely correlated with well depth. However, only one nitrate observation – from a shallow well in the aquifer's outcrop zone – surpassed the maximum contaminant level (MCL) of 44.3 mg L^-1. By comparison, nearly half of the sulfate and several of the chloride observations surpassed the MCL of 250 mg L^-1for each of those ions. Volcanic ash deposits influenced fluorideconcentrations, which directly correlated with well depth. There were no statistically significant associations between solute concentrations and land use. Low recharge rates and confining layers have mitigated anthropogenic impacts on solute levels in the aquifer.