Economics of ground-water quality monitoring: A survey of experts

The cost of a monitoring program can be easily ascertained in terms of the expenditures incurred for such items as personnel, supplies, field visits, instrumentation and laboratory analyses. The benefits of a monitoring program, however, cannot be easily evaluated due to the diversity of objectives for which monitoring programs are initiated and operated. The case study and the results of the follow-up exploratory survey reported in this paper were intended to capture the objective as well as the subjective reasons employed by a group of experts in responding to selected socio-economic questions related to the design of monitoring programs. Ninety-seven individuals, through a formal questionnaire, participated in the survey. They showed definite preferences, although there was some variability in responses due to such factors as residential status, institutional affiliation, education, and the length of professional experience. It was clear that the respondents favored the inclusion of cost-effectiveness criteria in monitoring programs; were ambivalent to the idea of initiating a regulatory program to monitor the wells of a large number of private owners; and if such a program were to be initiated they recommended that individual well owners share the bulk of the financial burden. Preliminary results from such exploratory surveys can lead to the framing of insightful research questions or hypotheses for further evaluation. Confirmatory testing of such questions or hypotheses in real world settings is a valuable area for further research.     

Assessment of the impact of landfill on groundwater quality: A case study of the Pirana site in western India

In present study focus has been given on estimating quality and toxicity of waste with respect to heavy metals and its impact on groundwater quality, using statistical and empirical relationships between different hydrochemical data, so that easy monitoring may be possible which in turn help the sustainable management of landfill site and municipal solid waste. Samples of solid waste, leachate and groundwater were analyzed to evaluate the impact of leachates on groundwater through the comparison of their hydrochemical nature. Results suggest the existence of an empirical relationship between some specific indicator parameters like heavy metals of all three above mentioned sample type. Further, K/Mg ratio also indicates three groundwater samples heavily impacted from leachate contamination. A good number of samples are also showing higher values for and Pb than that of World Health Organization (WHO) drinking water regulation. Predominance of Fe and Zn in both groundwater and solid waste samples may be due to metal plating industries in the area. Factor analysis is used as a tool to explain observed relation between numerous variables in term of simpler relation, which may help to deduce the strength of relation. Positive loading of most of the factors for heavy metal clearly shows landfill impact on ground water quality especially along the hydraulic gradient. Cluster analysis, further substantiates the impact of landfill. Two major groups of samples obtained from cluster analysis suggest that one group comprises samples that are severely under the influence of landfill and contaminated leachates along the groundwater flow direction while other assorted with samples without having such influence.     

Inorganic nitrogen transformations in the treatment of landfill leachate with a high ammonium load: A case study

The inorganic nitrogen transformations occurring at a municipal waste leachate treatment facility were investigated. The treatment facility consisted of a collection well and an artificial wetland between two aeration ponds. The first aeration pond showed a decrease in ammonium (from 3480 (± 120) to 630(± 90) mg ⋅ L⁻¹), a reduction in inorganic nitrogen load (3480 to 1680 mg N ⋅ L⁻¹), and an accumulation of nitrite (< 1.3 mg-N ⋅ L⁻¹ in the collection well, to 1030 mg-N ⋅ L⁻¹). Incomplete ammonium oxidation was presumably the result of the low concentration of carbonate alkalinity (∼2 mg ⋅ L⁻¹), which may cause a limitation in the ammonium oxidation rate of nitrifiers. Low carbonate alkalinity levels may have been the result of stripping of CO₂ from the first aeration pond at the high aeration rates and low pH. Various chemodenitrification mechanisms are discussed as the reason for the reduction in the inorganic nitrogen load, including; the reduction of nitrite by iron (II) (producing various forms of gaseous nitrogen); and reactions involving nitrous acid. It is suggested that the accumulation of nitrite may be the result of inhibition of nitrite oxidizers by nitrous acid and low temperatures. Relative to the first aeration pond, the speciation and concentration of inorganic nitrogen was stable in the wetlands and 2nd aeration pond. The limited denitrification in the wetlands most probably occurred due to low concentrations of organic carbon, and short retention times.     

Establishment of a structural equation model for ground-level ozone: a case study at an urban roadside site

This study established a cause–effect relationship between ground-level ozone and latent variables employing partial least-squares analysis at an urban roadside site in four distinct seasons. Two multivariate analytic methods, factor analysis, and cluster analysis were adopted to cite and identify suitable latent variables from 14 observed variables (i.e., meteorological factors, wind and primary air pollutants) in 2008–2010. Analytical results showed that the first six components explained 80.3 % of the variance, and eigenvalues of the first four components were greater than 1. The effectiveness of this model was empirically confirmed with three indicators. Except for surface pressure, factor loadings of observed variables were 0.303–0.910 and reached statistical significance at the 5 % level. Composite reliabilities for latent variables were 0.672–0.812 and average variances were 0.404–0.547, except for latent variable “primary” in spring; thus, discriminant validity and convergent validity were marginally accepted. The developed model is suitable for the assessment of urban roadside surface ozone, considering interactions among meteorological factors, wind factors, and primary air pollutants in each season.     

Optimizing water quality monitoring networks using continuous longitudinal monitoring data: a case study of Wen-Rui Tang River, Wenzhou, China

Identification of representative sampling sites is a critical issue in establishing an effective water quality monitoring program. This is especially important at the urban-agriculture interface where water quality conditions can change rapidly over short distances. The objective of this research was to optimize the spatial allocation of discrete monitoring sites for synoptic water quality monitoring through analysis of continuous longitudinal monitoring data collected by attaching a water quality sonde and GPS to a boat. Sampling was conducted six times from March to October 2009 along a 6.5 km segment of the Wen-Rui Tang River in eastern China that represented an urban-agricultural interface. When travelling at a velocity of ～2.4 km h(-1), this resulted in water quality measurements at ～20 m interval. Ammonia nitrogen (NH(4)(+)-N), electrical conductivity (EC), dissolved oxygen (DO), and turbidity data were collected and analyzed using Cluster Analysis (CA) to identify optimal locations for establishment of long-term monitoring sites. The analysis identified two distinct water quality segments for NH(4)(+)-N and EC and three distinct segments for DO and turbidity. According to our research results, the current fixed-location sampling sites should be adjusted to more effectively capture the distinct differences in the spatial distribution of water quality conditions. In addition, this methodology identified river reaches that require more comprehensive study of the factors leading to the changes in water quality within the identified river segment. The study demonstrates that continuous longitudinal monitoring can be a highly effective method for optimizing monitoring site locations for water quality studies.     

Statistical models for evaluating suspected artefacts in long-term environmental monitoring data

Long-term water quality monitoring is of high value for environmental management as well as for research. Artificial level shifts in time series due to method improvements, flaws in laboratory practices or changes in laboratory are a common limitation for analysis, which, however, are often ignored. Statistical estimation of such artefacts is complicated by the simultaneous existence of trends, seasonal variation and effects of other influencing factors, such as weather conditions. Here, we investigate the performance of generalised additive mixed models (GAMM) to simultaneously identify one or more artefacts associated with artificial level shifts, longitudinal effects related to temporal trends and seasonal variation, as well as to model the serial correlation structure of the data. In the same model, it is possible to estimate separate residual variances for different periods so as to identify if artefacts not only influence the mean level but also the dispersion of a series. Even with an appropriate statistical methodology, it is difficult to quantify artificial level shifts and make appropriate adjustments to the time series. The underlying temporal structure of the series is especially important. As long as there is no prominent underlying trend in the series, the shift estimates are rather stable and show less variation. If an artificial shift occurs during a slower downward or upward tendency, it is difficult to separate these two effects and shift estimates can be both biased and have large variation. In the case of a change in method or laboratory, we show that conducting the analyses with both methods in parallel strongly improves estimates of artefact effects on the time series, even if certain problems remain. Due to the difficulties of estimating artificial level shifts, posterior adjustment is problematic and can lead to time series that no longer can be used for trend analysis or other analysis based on the longitudinal structure of the series. Before carrying out a change in analytic method or laboratory, it should be considered if this is absolutely necessary. If changes cannot be avoided, the analysis of the two methods considered, or the two laboratories contracted, should be run in parallel for a considerable period of time so as to enable a good assessment of changes introduced to the data series.     

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.     

Optimal redesign of groundwater quality monitoring networks: a case study

Assessment and redesign of water quality monitoring networks is an important task in water quality management. This paper presents a new methodology for optimal redesign of groundwater quality monitoring networks. The measure of transinformation in discrete entropy theory and the transinformation–distance (T–D) curves are used to quantify the efficiency of sampling locations and sampling frequencies in a monitoring network. The existing uncertainties in the T–D curves are taken in to account using the fuzzy set theory. The C-means clustering method is also used to classify the study area to some homogenous zones. The fuzzy T–D curve of the zones is then used in a multi-objective hybrid genetic algorithm-based optimization model. The proposed methodology is utilized for optimal redesign of monitoring network of the Tehran aquifer in the Tehran metropolitan area, Iran.     

Optimising vegetation monitoring. A case study in A French lowland forest

Biodiversity monitoring surveys are rarely optimised statistically before being initiated. Here, we optimised the monitoring of plants in a temperate forest. The total inventory cost, the number and size of quadrats were optimised to detect a 10% change in species richness over 5 years with α = β = 0.05, using data from ongoing long-term floristic monitoring programs. The procedure showed that the inventory cost would be ca 15% lower using 100-, 200-m² quadrats instead of 300- or 400-m² quadrats. Despite the cost associated with the optimisation (e.g. gathering preliminary data) and the imprecise estimates (due to the typically small sample size of the pilot studies), optimisation would often be a better option than expert opinion when designing a monitoring survey.     

Statistical models and time series forecasting of sulfur dioxide: a case study Tehran

This study performed a time-series analysis, frequency distribution and prediction of SO(2) levels for five stations (Pardisan, Vila, Azadi, Gholhak and Bahman) in Tehran for the period of 2000-2005. Most sites show a quite similar characteristic with highest pollution in autumn-winter time and least pollution in spring-summer. The frequency distributions show higher peaks at two residential sites. The potential for SO(2) problems is high because of high emissions and the close geographical proximity of the major industrial and urban centers. The ACF and PACF are nonzero for several lags, indicating a mixed (ARMA) model, then at Bahman station an ARMA model was used for forecasting SO(2). The partial autocorrelations become close to 0 after about 5 lags while the autocorrelations remain strong through all the lags shown. The results proved that ARMA (2,2) model can provides reliable, satisfactory predictions for time series.     

Issues in monitoring wilderness lake chemistry: A case study in the Sawtooth Mountains,Idaho

A probability-based sample of 48 of the 152 lakes in the Sawtooth Wilderness, Idaho was conducted in summer 1988. Results from this sample were compared to the Environmental Protection Agency's 1985 probability survey of lakes throughout the western United States, which included 17 lakes in the Sawtooth Wilderness. Although methods differed in several respects, including year, season, sampling location within the lakes, holding times, and sample size, general characterization of lake chemistry for the population of lakes in the wilderness based on the two surveys was very similar. The results indicate that general lake characterization in difficult-to-access wilderness areas of the West can be achieved with a modest investment in resources with the use of volunteers. However, accurate measurement of some non-conservative and low-level analytes such as NO ₃ ^– ,NH ₄ ⁺ , total P, and aluminiun in the lakes probably requires more rigorous attention to sampling protocols and holding times. A two-stage sampling strategy employing extensive use of conductivity on a large number of lakes and intensive detailed chemical characterization on a smaller number of lakes offers an alternative design for describing large populations of wilderness lakes. The relatively high concentrations of fluoride and sulfate in many of the study lakes reflect the weathering of minerals not usually identified on geologic maps. These natural sources of acid anions violate the assumptions in commonly employed empirical models of acidification.     

Phytoextraction and phytostabilization potential of plants grown in the vicinity of heavy metal-contaminated soils: a case study at an industrial town site

With the development of urbanization and industrialization, soils have become increasingly polluted by heavy metals. Phytoremediation, an emerging cost-effective, nonintrusive, and aesthetically pleasing technology that uses the remarkable ability of plants to concentrate elements, can be potentially used to remediate metal-contaminated sites. In this research, two processes of phytoremediation (phytoextraction and phytostabilization) were surveyed in some plant species around an industrial town in the Hamedan Province in the central-western part of Iran. To this purpose, shoots and roots of the seven plant species and the associated soil samples were collected and analyzed by measuring Pb, Fe, Mn, Cu, and Zn concentrations using ICP-AES and then calculating the biological absorption coefficient, bioconcentration factor, and translocation factor parameters for each element. The obtained results showed that among the collected plants, Salsola soda is the most effective species for phytoextraction and phytostabilization and Cirsium arvense has the potential for phytostabilization of the measured heavy metals.     

Statistical analysis of trends in organic pollution and pollution by nutrients at selected Danube river stations

The paper describes an application of a statistical analysis for estimating long-term trends in pollutant concentrations of selected pollutants in the Danube river. The results show the changes of concentrations of NH(4)(+)-N, NO(3)(-)-N, PO(4)(3-)-P, total P, BOD(5) and COD(Cr) in a ten year period with the aim to find how the concentrations vary in the whole stretch of this river. The study was based on the data collected in the frame of Transnational Monitoring Network of the ICPDR. To obtain plausible results we have chosen statistical methods, such as tests based on the Spearman correlation coefficient and median regression, which are not sensitive to departures from normality as high skewness or outliers.     

Environmental change monitoring in the arid and semi-arid regions: a case study Al-Basrah Province, Iraq

In recent years, land use/cover dynamic change has become a key subject urgently to be dealt with in the study of global environmental change. This research utilizes the integrated remote sensing and geographic information systems (GIS) in the southern part of Iraq (Basrah Province was taken as a case) to monitor, map, and quantify the environmental change using a 1:250,000 mapping scale. Remote sensing and GIS software were used to classify Landsat TM in 1990 and Landsat ETM+ in 2003 imagery into five land use and land cover (LULC) classes: vegetation land, sand land, urban area, unused land, and water bodies. Supervised classification and normalized difference buildup index, normalized difference vegetation index, normalized difference bare land index, the normalized differential water index, crust index (CI) algorithms, and change detection techniques were adopted in this research and used, respectively, to retrieve its class boundary. An accuracy assessment was performed on the 2003 LULC map to determine the reliability of the map. Finally, GIS software was used to quantify and illustrate the various LULC conversions that took place over the 13-year span of time. The results showed that the urban area, sand lands, and bare lands had increased by the rate of 1.2%, 0.8%, and 0.4% per year, with area expansion from 3,299.1, 4,119.1 km², and 3,201.9 km² in 1990 to 3,794.9, 4,557.7, and 3,351.7 km² in 2003, respectively. While the vegetation cover and water body classes were about 43.5% in 1990, the percentage decreased to about 39.6% in 2003. This study demonstrates the effectiveness of the remote sensing and GIS technologies in detecting, assessing, mapping, and monitoring the environmental changes.     

Design of on-line river water quality monitoring systems using the entropy theory: a case study

The design of a water quality monitoring network is considered as the main component of water quality management including selection of the water quality variables, location of sampling stations and determination of sampling frequencies. In this study, an entropy-based approach is presented for design of an on-line water quality monitoring network for the Karoon River, which is the largest and the most important river in Iran. In the proposed algorithm of design, the number and location of sampling sites and sampling frequencies are determined by minimizing the redundant information, which is quantified using the entropy theory. A water quality simulation model is also used to generate the time series of the concentration of water quality variables at some potential sites along the river. As several water quality variables are usually considered in the design of water quality monitoring networks, the pair-wise comparison is used to combine the spatial and temporal frequencies calculated for each water quality variable. After selecting the sampling frequencies, different components of a comprehensive monitoring system such as data acquisition, transmission and processing are designed for the study area, and technical characteristics of the on-line and off-line monitoring equipment are presented. Finally, the assessment for the human resources needs, as well as training and quality assurance programs are presented considering the existing resources in the study area. The results show that the proposed approach can be effectively used for the optimal design of the river monitoring systems.     

Continuous high-frequency monitoring of estuarine water quality as a decision support tool: a Dublin Port case study

High-frequency, continuous monitoring using in situ sensors offers a comprehensive and improved insight into the temporal and spatial variability of any water body. In this paper, we describe a 7-month exploratory monitoring programme in Dublin Port, demonstrating the value of high-frequency data in enhancing knowledge of processes, informing discrete sampling, and ultimately increasing the efficiency of port and environmental management. Kruskal–Wallis and Mann–Whitney tests were used to show that shipping operating in Dublin Port has a small–medium effect on turbidity readings collected by in situ sensors. Turbidity events are largely related to vessel activity in Dublin Port, caused by re-suspension of sediments by vessel propulsion systems. The magnitudes of such events are strongly related to water level and tidal state at vessel arrival times. Crucially, measurements of Escherichia coli and enterococci contamination from discrete samples taken at key periods related to detected turbidity events were up to nine times higher after vessel arrival than prior to disturbance. Daily in situ turbidity patterns revealed time-dependent water quality “hot spots” during a 24-h period. We demonstrate conclusively that if representative environmental assessment of water quality is to be performed at such sites, sampling times, informed by continous monitoring data, should take into account these daily variations. This work outlines the potential of sensor technologies and continuous monitoring, to act as a decision support tool in both environmental and port management.     

A study on the waste metal remediation using floriculture at East Calcutta Wetlands, a Ramsar site in India

Use of specific plant species in remediation of heavy metal-contaminated soil and water was a promising eco-friendly technology. The present study indicated the possibilities of phytoremediation of metal-contaminated (namely Ca, Cr, Mn, Fe, Cu, Zn, and Pb) soil by using plant species important for floriculture of East Calcutta Wetlands, a Ramsar site at the eastern fringe of Calcutta city. Plant species like sunflower (Helianthus annuus), marigold (Tagetes patula), and cock's comb (Celocia cristata) grew on soil contaminated by industrial sludge and irrigated regularly with wastewater accumulated different metals in different plant parts in varied concentrations. Pot culture study in the laboratory setup was also done to ascertain the efficiency of these plants for ameliorating contaminated soil. It was found that general accumulation patterns of metals concerned in different plant parts were root > leaf > stem > flower. This work indicated the importance of cultivation of economically important, non-edible, ornamental plant species as an alternative cost-effective practice to remediate heavily contaminated farmlands of East Calcutta Wetlands.     

Environmental monitoring of heavy metals and arsenic from Ag-Pb-Zn mining: a case study over two millennia

2000 years of mining activity at Wiesloch, Germanyleft behind a legacy of mining wastes, some of which haveextremely high contents of toxic elements like As, Cd, Tl,Sb, Pb and Zn. To evaluate their long-term impact ondifferent environmental compartments, the detailedenvironmental monitoring presented here focused on themineralogical and chemical characterization of thedifferent waste materials, consisting of dumpings with orefragments, flotation tailings and medieval metallurgicalslags. Leaching experiments with these materials, usingeluents of different compositions and pHs were carried outto assess the conditions governing the mobilization and re-fixation of these species. It was shown, that the carbonatehost rock of the mineralization, the loess blanket coveringthe area and the organically rich municipal sewage sludgesdeposited on top of the tailings, represent potentialbarriers to the dispersion of toxic elements over a muchlarger area. Moreover, particulate emissions from thesteep, unvegetated escarpments of the tailing heapsrepresent a continuous thread to the environment.     

The value of long-term environmental monitoring programs: an Ohio River case study

As a subset of environmental monitoring, fish sampling programs have been an important part of assessing the potential impacts of water withdrawals and effluent discharges on fish populations for many years. New environmental regulations often require that adverse environmental impacts to fish populations be minimized. Without long-term field data, population evaluations may incorrectly indicate adverse impacts where none exist or no impact where one is likely to occur. Several electric utility companies have funded the Ohio River Ecological Research Program, which has been in existence for over 40 years and consists of fish, habitat, and water quality studies at multiple power plant sites on the mainstem Ohio River. Sampling includes seasonal night-time electrofishing and daytime beach seining at three upstream and three downstream locations near each plant. The long-term nature of the program allows for the establishment of aquatic community indices to support evaluations of technology performance, the collaborative development of compliance metrics, and the assessment of fish population trends. Studies have concluded that the Ohio River fish community has improved in response to better water quality and that power plant fish entrainment and impingement and thermal discharges have had little or no measureable impact. Through collaboration and the use of long-term data, $6.3 million in monitoring costs have been saved during recent fish impingement studies. The ability to access a multiyear fish abundance database, with its associated data on age, growth, and fecundity, improves the quality of such evaluations and reduces the need for extensive field sampling at individual locations.