Impact of intensive agricultural practices on drinking water quality in the EVROS Region (NE GREECE) by GIS analysis

Chemical fertilizers are used extensively in modern agriculture, in order to improve yield and productivity of agricultural products. However, nutrient leaching from agricultural soil into groundwater resources poses a major environmental and public health concern. The Evros region is one of the largest agricultural areas in Northern Greece, extending over 1.5 million acres of cultivated land. Many of its drinking water resources are of groundwater origin and lie within agricultural areas. In order to assess the impact of agricultural fertilizers on drinking water quality in this region, tap-water samples from 64 different locations were collected and analyzed for the presence of nitrates [Formula: see text], nitrites [Formula: see text], ammonium [Formula: see text], sulfate [Formula: see text] and phosphate [Formula: see text]. These chemicals were selected based on the information that ammonium nitrate, ammonium sulfate and inorganic phosphate were the primary fertilizers used in local crop production. [Formula: see text], [Formula: see text] and [Formula: see text] levels exceeding accepted values were recorded in 6.25, 4.70 and 9.38% of all sampling points, respectively. [Formula: see text] and [Formula: see text] concentrations, on the other hand, were inside the permitted range. The data generated were introduced into a geographic information system (GIS) program for computer analysis and projection maps representing afflicted areas were created. Our results indicate a profound geographic correlation in the surface distribution of primary contaminants in areas of intensified agricultural production. Thus, drinking water pollution in these areas can be attributed to excessive fertilizer use from agricultural sources.     

Nitrate occurrence in the groundwater of the Loukkos perimeter

This study assesses the occurrence of nitrate in the groundwater beneath the R'mel area of the Loukkos perimeter (north-west Morocco), which covers an approximate area of 2,560 km2 and is located between the towns of Ksar el Kebir and Larache. It also borders the Atlantic Ocean. Groundwater supplies are the principal source of drinking water in this region and there is no public drinking water network in the rural area. This perimeter has a population of about 500,000 inhabitants of which the rural population represents 60%, many of whom have depended on and used the water from the aquifers for many years. The inhabitants and farmers depend on the groundwater supplies for drinking water, crop irrigation and other uses. The plain provides the ideal conditions for agriculture and the use of chemical fertilisers has been increasing. In this study, 53 water samples were collected from wells and springs. Each well or spring was sampled once or twice during 1998-2000. Nitrate concentrations ranged from extremely low up to 144 mg L(-1). Nitrate concentrations exceeded the maximum contaminant level (MCL) of 50 mg L(-1) in 12 of the 53 groundwater samples (23%), whereas 31 of the 53 samples (58%) had nitrate concentrations of less than 25 mg L(-1).     

Monitoring requirements for groundwaters under the influence of reclaimed water

Monitoring groundwaters under the influence of reclaimedwater must consider the major constituents of concern inreclaimed water. This research focused on the fate ofdissolved organic carbon and nitrogen species at field siteslocated throughout the Southwestern United States. Awatershed approach was developed to predict the fate ofdissolved organic carbon as a function of the drinking waterdissolved organic carbon concentration and the totaldissolved solids concentration in the reclaimed water. Extensive characterization of the dissolved organic carbonrecovered from groundwaters under the influence of reclaimedwater was done. With the exception of fluorescencespectroscopy, the dissolved organic carbon present ineffluent organic matter was similar in structure, characterand reactivity as compared to natural organic matter. Evidence for sustainable nitrogen removal mechanisms duringgroundwater recharge with reclaimed water was obtained. Theautotrophic reaction between ammonia and nitrate appears to amechanism for the removal nitrogen in a carbon-depletedenvironment. The monitoring tools and methodologiesdeveloped in this research can be used to assure protectionof public health and determine the sustainability of indirectpotable reuse projects.     

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.     

The use of multivariate statistical methods for optimization of the surface water quality network monitoring in the Paraopeba river basin,Brazil

This study sought to evaluate and propose adjustments to the water quality monitoring network of surface freshwaters in the Paraopeba river basin (Minas Gerais, Brazil), using multivariate statistical methods. A total of 13,560 valid data were analyzed for 19 water quality parameters at 30 monitoring sites, over a period of 5 years (2008–2013). The cluster analysis grouped the monitoring sites in eight groups based on similarities of water quality characteristics. This analysis made it possible to detect the most relevant monitoring stations in the river basin. The principal components analysis associated with non-parametric tests and the analysis of violation of the standards prescribed by law, allowed for identifying the most relevant parameters which must be maintained in the network (thermotolerant coliforms, total manganese, and total phosphorus). The discharge of domestic sewage and industrial wastewater, that from mining activities and diffuse pollution from agriculture and pasture areas are the main sources of pollution responsible for the surface water quality deterioration in this basin. The BP073 monitoring site presents the most degraded water quality in the Paropeba river basin. The monitoring sites BP094 and BP092 are located geographically close and they measure similar water quality, so a possible assessment of the need to maintain only one of the two in the monitoring network is suggested. Therefore, multivariate analyses were efficient to assess the adequacy of the water quality monitoring network of the Paraopeba river basin, and it can be used in other watersheds.     

Impact of anthropogenic activities on water quality of Lidder River in Kashmir Himalayas

The pristine waters of Kashmir Himalaya are showing signs of deterioration due to multiple reasons. This study researches the causes of deteriorating water quality in the Lidder River, one of the main tributaries of Jhelum River in Kashmir Himalaya. The land use and land cover of the Lidder catchment were generated using multi-spectral, bi-seasonal IRS LISS III (October 2005 and May 2006) satellite data to identify the extent of agriculture and horticulture lands that are the main non-point sources of pollution at the catchment scale. A total of 12 water quality parameters were analyzed over a period of 1 year. Water sampling was done at eight different sampling sites, each with a varied topography and distinct land use/land cover, along the length of Lidder River. It was observed that water quality deteriorated during the months of June–August that coincides with the peak tourist flow and maximal agricultural/horticultural activity. Total phosphorus, orthophosphate phosphorus, nitrate nitrogen, and ammoniacal nitrogen showed higher concentration in the months of July and August, while the concentration of dissolved oxygen decreased in the same period, resulting in deterioration in water quality. Moreover, tourism influx in the Lidder Valley shows a drastic increase through the years, and particularly, the number of tourists visiting the valley has increased in the summer months from June to September, which is also responsible for deteriorating the water quality of Lidder River. In addition to this, the extensive use of fertilizers and pesticides in the agriculture and horticulture lands during the growing season (June–August) is also responsible for the deteriorating water quality of Lidder River.     

Agricultural nitrate monitoring in a lake basin in Central Italy: a further step ahead towards an integrated nutrient management aimed at controlling water pollution

Water pollution from point sources has been considerably reduced over the last few decades. Nevertheless, some water quality problems remain, which can be attributed to non-point pollution sources, and in particular to agriculture. In this paper the results of a study intended to assess the consequences, in terms of NO₃ water pollution, of growing a crop, whose impact in terms of P pollution is already well known, are presented. The potential consequences, in terms of water pollution from nitrates of a BMP expressly applied to reduce P pollution are also discussed. The study site is the Lake Vico basin, Central Italy, which has suffered a shift in trophic state since the mid 1990s, caused by P compounds used for intensive cultivation of hazelnut trees. The results of the monitoring campaign described in this paper allow to assert that hazelnut tree cropping has probably caused a considerable increase in nitrate concentration in the groundwater, although not in the lake water, because of the specific hydrogeological characteristics of the basin. The main conclusion is that monitoring is essential to single out environmental characteristics peculiar of a specific area, which even the most sophisticated model would not have been able to highlight. This is why monitoring and model simulations should be integrated.     

Use of continuous monitoring to assess stream nitrate flux and transformation patterns

Delivery of nitrogen from farmed fields to the stream network is an ongoing water quality issue in central North America and other parts of the world. Although fertilization and other farming practices have been refined to produce environmental improvements, stemming loss of nitrogen, especially in the soluble nitrate form, is a problem that has seemingly defied solution. The Iowa Nutrient Reduction Strategy is a policy initiative designed to implement conservation and other farm management practices to produce reductions in nitrate loading. The strategy does not focus on how the streams themselves may or may not be processing nitrogen and reducing downstream loading. We used continuous high-frequency nitrate and discharge monitoring over 3 years at two sites separated by 18 km in a low-order, agricultural stream in eastern Iowa to estimate how nitrogen is processed, and whether or not these processes are reducing downstream loading. We conclude that the upstream to downstream nitrate concentration decline between the two sites was not driven by denitrification. These data also show that nitrate concentrations are closely coupled to discharge during periods of adequate moisture, but decoupling of concentration from discharge occurs during dry periods. This decoupling is a possible indicator of in-stream nitrate processing. Finally, nitrate concentrations are likely diluted by water sourced from non-row crop land covers in the lower reaches of the watershed.     

Assessment of ground water quality for drinking purpose, District Nainital, Uttarakhand, India

The ground water quality of District Nainital (Uttarakhand, India) has been assessed to see the suitability of ground water for drinking and irrigation applications. This is a two-part series paper and this paper examines the suitability of ground water including spring water for drinking purposes. Forty ground water samples (including 28 spring samples) were collected during pre- and post-monsoon seasons and analyzed for various water quality constituents. The hydrochemical and bacteriological data was analyzed with reference to BIS and WHO standards and their hydrochemical facies were determined. The concentration of total dissolved solids exceeds the desirable limit of 500 mg/L in about 10% of the samples, alkalinity values exceed the desirable limit of 200 mg/L in about 30% of the samples, and total hardness values exceed the desirable limit of 300 mg/L in 15% of the samples. However, no sample crosses the maximum permissible limit for TDS, alkalinity, hardness, calcium, magnesium, chloride, sulfate, nitrate, and fluoride. The concentration of chloride, sulfate, nitrate, and fluoride are well within the desirable limit at all the locations. The bacteriological analysis of the samples does not show any sign of bacterial contamination in hand pump and tube-well water samples. However, in the case of spring water samples, six samples exceed the permissible limit of ten coliforms per 100 ml of sample. It is recommended that water drawn from such sources should be properly disinfected before being used for drinking and other domestic applications. Among the metal ions, the concentration of iron and lead exceeds the permissible limit at one location whereas the concentration of nickel exceeds the permissible limit in 60 and 32.5% of the samples during pre- and post-monsoon seasons, respectively. The grouping of samples according to their hydrochemical facies indicates that majority of the samples fall in Ca–Mg–HCO₃ hydrochemical facies.     

Exploring the Relationship Between Hydrologic Parameters and Nutrient Loads Using Digital Elevation Model and GIS – A Case Study from Sugarcreek Headwaters, Ohio, U.S.A.

Ohio is typical among the Midwestern and Eastern United States with high levels of water pollutants, the main sources being from agriculture. In this study, we used a digital elevation model in conjunction with hydrological indices to determine the role of landscape complexity affecting the spatial and temporal variation in pollutant levels, in one of the most impaired headwater streams in Ohio. More than eighty five percent of the study area is dominated by agriculture. Spatial distribution of slope (S), altitude and wetness index along with other watershed parameters such as flow direction, flow accumulation, stream networks, flow stream orders and erosion index were used within a Geographic Information Systems framework to quantify variation in nitrate and phosphate loads to headwater streams. Stream monitoring data for nutrient loads were used to correlate the observed spatial and temporal patterns with hydrological parameters using multiple linear regressions. Results from the wetness index calculated from a digital elevation model suggested a range of 0.10–16.39, with more than 35% having values less than 4.0. A Revised Universal Soil Loss Equation (RUSLE) predicted soil loss in the range of 0.01–4.0 t/ha/yr. Nitrate nitrogen levels in the study area paralleled precipitation patterns over time, with higher nitrate levels corresponding to high precipitation. Atmospheric deposition through precipitation could explain approximately 35% of total nitrate levels observed in streams. Among the different topographic variables and hydrological indices, results from the step-wise multiple regression suggested the following best predictors, (1) elevation range and upstream flow length for nitrate, (2) flow direction and upstream flow length for ammonia-nitrogen and slope, and (3) elevation range for phosphate levels. Differences in the landscape models observed for nitrate, phosphate and ammonia-nitrogen in the surface waters were attributed partly to differences in the chemical activity and source strengths of the different forms of these nutrients through agricultural management practices. The results identify geomorphologic and landscape characteristics that influence pollutant levels in the study area.     

Assessment of nitrate contamination due to groundwater pollution in north eastern part of Anantapur District, A.P. India

The north eastern part of Anantapur district is in the state of Andhra Pradesh, India, is significant as it is covered by varied geological formations and has different land use and irrigation practices. Though ground water is the major drinking water source, deterioration in its quality is going unchecked. In such agro-economy based rural areas, the nitrate contamination is rampant and much attention has not been drawn towards this anthropogenic pollution. In the study area ground water samples from different hydrogeological set-up have been collected during the pre and post monsoon seasons and analysed for the major ions such as Ca, Mg, Na, K, CO(3), HCO(3), Cl, SO(4), NO(3) and F. The study revealed that 65% of the samples were found to be unsuitable for drinking purposes in the pre monsoon season and 45% in the post monsoon due to excess nitrate (>45 mg/l) content in the ground water. Among the different seasons and environs, nitrate was in highest concentration in the granitic terrain and canal command areas during pre monsoon season. The nitrate was found to decrease with depth in all the hydrogeological set-ups in both the seasons. Intense agriculture practices, improper sewerage and organic waste disposal methods were observed to contribute nitrate to the shallow and moderately deep aquifers.     

Mapping nitrate leaching to upper groundwater in the sandy regions of The Netherlands, using conceptual knowledge

The European Community asks its Member States to provide a comprehensive and coherent overview of their groundwater chemical status. It is stated that simple conceptual models are necessary to allow assessments of the risks of failing to meet quality objectives. In The Netherlands two monitoring networks (one for agriculture and one for nature) are operational, providing results which can be used for an overview. Two regression models, based upon simple conceptual models, link measured nitrate concentrations to data from remote sensing images of land use, national forest inventory, national cattle inventory, fertiliser use statistics, atmospheric N deposition, soil maps and weather monitoring. The models are used to draw a nitrate leaching map and to estimate the size of the area exceeding the EU limit value in the early 1990s. The 95% confidence interval for the fraction nature and agricultural areas where the EU limit value for nitrate (50 mg/l) was exceeded amounted to 0.77–0.85 while the lower 97.5% confidence limit for the fraction agricultural area where the EU limit value was exceeded amounted to 0.94. Although the two conceptual models can be regarded as simple, the use of the models to give an overview was experienced as complex.     

Dynamic regression modeling of daily nitrate-nitrogen concentrations in a large agricultural watershed

Nitrate-nitrogen concentrations in rivers represent challenges for water supplies that use surface water sources. Nitrate concentrations are often modeled using time-series approaches, but previous efforts have typically relied on monthly time steps. In this study, we developed a dynamic regression model of daily nitrate concentrations in the Raccoon River, Iowa, that incorporated contemporaneous and lags of precipitation and discharge occurring at several locations around the basin. Results suggested that 95 % of the variation in daily nitrate concentrations measured at the outlet of a large agricultural watershed can be explained by time-series patterns of precipitation and discharge occurring in the basin. Discharge was found to be a more important regression variable than precipitation in our model but both regression parameters were strongly correlated with nitrate concentrations. The time-series model was consistent with known patterns of nitrate behavior in the watershed, successfully identifying contemporaneous dilution mechanisms from higher relief and urban areas of the basin while incorporating the delayed contribution of nitrate from tile-drained regions in a lagged response. The first difference of the model errors were modeled as an AR(16) process and suggest that daily nitrate concentration changes remain temporally correlated for more than 2 weeks although temporal correlation was stronger in the first few days before tapering off. Consequently, daily nitrate concentrations are non-stationary, i.e. of strong memory. Using time-series models to reliably forecast daily nitrate concentrations in a river based on patterns of precipitation and discharge occurring in its basin may be of great interest to water suppliers.     

Groundwater stress and vulnerability in rural coastal aquifers under competing demands: a case study from Sri Lanka

Rural coastal aquifers are undergoing rapid changes due to increasing population, high water demand with expanding agricultural and domestic uses, and seawater intrusion due to unmanaged water pumping. The combined impact of these activities is the deterioration of groundwater quality, public health concerns, and unsustainable water demands. The Kalpitiya peninsula located northwest of Sri Lanka is one area undergoing such changes. This land area is limited and surrounded almost completely by sea and lagoon. This study consists of groundwater sampling and analysis, and vulnerability assessment using the DRASTIC method. The results reveal that the peninsula is experiencing multiple threats due to population growth, seawater intrusion, land use exploitation for intensive agriculture, groundwater vulnerability from agricultural and domestic uses, and potential public health impacts. Results show that nitrate is a prevalent and serious contaminant occurring in large concentrations (up to 128 mg/l NO₃?CN), while salinity from seawater intrusion produces high chloride content (up to 471 mg/l), affecting freshwater sources. High nitrate levels may have already affected public health based on limited sampling for methemoglobin. The two main sources of nitrogen loadings in the area are fertilizer and human excreta. The major source of nitrogen results from the use of fertilizers and poor management of intense agricultural systems where a maximum application rate of up to 11.21 metric tons N/km² per season is typical. These findings suggest that management of coastal aquifers requires an integrated approach to address both the prevalence of agriculture as an economic livelihood, and increasing population growth.     

Evaluation of wireless sensor networks (WSNs) for remote wetland monitoring: design and initial results

Here, we describe and evaluate two low-power wireless sensor networks (WSNs) designed to remotely monitor wetland hydrochemical dynamics over time scales ranging from minutes to decades. Each WSN (one student-built and one commercial) has multiple nodes to monitor water level, precipitation, evapotranspiration, temperature, and major solutes at user-defined time intervals. Both WSNs can be configured to report data in near real time via the internet. Based on deployments in two isolated wetlands, we report highly resolved water budgets, transient reversals of flow path, rates of transpiration from peatlands and the dynamics of chromophoric-dissolved organic matter and bulk ionic solutes (specific conductivity)—all on daily or subdaily time scales. Initial results indicate that direct precipitation and evapotranspiration dominate the hydrologic budget of both study wetlands, despite their relatively flat geomorphology and proximity to elevated uplands. Rates of transpiration from peatland sites were typically greater than evaporation from open waters but were more challenging to integrate spatially. Due to the high specific yield of peat, the hydrologic gradient between peatland and open water varied with precipitation events and intervening periods of dry out. The resultant flow path reversals implied that the flux of solutes across the riparian boundary varied over daily time scales. We conclude that WSNs can be deployed in remote wetland-dominated ecosystems at relatively low cost to assess the hydrochemical impacts of weather, climate, and other perturbations.     

Probability-based nitrate contamination map of groundwater in Kinmen

Groundwater supplies over 50 % of drinking water in Kinmen. Approximately 16.8 % of groundwater samples in Kinmen exceed the drinking water quality standard (DWQS) of NO₃ ^?-N (10 mg/L). The residents drinking high nitrate-polluted groundwater pose a potential risk to health. To formulate effective water quality management plan and assure a safe drinking water in Kinmen, the detailed spatial distribution of nitrate–N in groundwater is a prerequisite. The aim of this study is to develop an efficient scheme for evaluating spatial distribution of nitrate–N in residential well water using logistic regression (LR) model. A probability-based nitrate–N contamination map in Kinmen is constructed. The LR model predicted the binary occurrence probability of groundwater nitrate–N concentrations exceeding DWQS by simple measurement variables as independent variables, including sampling season, soil type, water table depth, pH, EC, DO, and Eh. The analyzed results reveal that three statistically significant explanatory variables, soil type, pH, and EC, are selected for the forward stepwise LR analysis. The total ratio of correct classification reaches 92.7 %. The highest probability of nitrate–N contamination map presents in the central zone, indicating that groundwater in the central zone should not be used for drinking purposes. Furthermore, a handy EC–pH-probability curve of nitrate–N exceeding the threshold of DWQS was developed. This curve can be used for preliminary screening of nitrate–N contamination in Kinmen groundwater. This study recommended that the local agency should implement the best management practice strategies to control nonpoint nitrogen sources and carry out a systematic monitoring of groundwater quality in residential wells of the high nitrate–N contamination zones.     

Water quality trends in New Zealand rivers: 1989–2009

Recent assessments of water quality in New Zealand have indicated declining trends, particularly in the 40 % of the country’s area under pasture. The most comprehensive long-term and consistent water quality dataset is the National Rivers Water Quality Network (NRWQN). Since 1989, monthly samples have been collected at 77 NRWQN sites on 35 major river systems that, together, drain about 50 % of New Zealand’s land area. Trend analysis of the NRWQN data shows increasing nutrient concentrations, particularly nitrogen (total nitrogen and nitrate), over 21 years (1989–2009). Total nitrogen and nitrate concentrations were increasing significantly over the first 11 years (1989–2000), but for the more recent 10-year period, only nitrate concentrations continued to increase sharply. Also, the increasing phosphorus trends over the first 11 years (1989–2000) levelled off over the later 10-year period (2000–2009). Conductivity has also increased over the 21 years (1989–2009). Visual clarity has increased over the full time period which may be the positive result of soil conservation measures and riparian fencing. NRWQN data shows that concentrations of nutrients increase, and visual clarity decreases (i.e. water quality declines), with increasing proportions of pastoral land in catchments. As such, the increasing nutrient trends may reflect increasing intensification of pastoral agriculture.     

Quality assessment of various bottled waters marketed in Saudi Arabia

This study focuses on the chemical analysis of the available brands of domestic bottled water in Riyadh City, Saudi Arabia. The distribution of the chemical constituents (major, minor, and trace elements) is determined and compared with the chemical content labeled on the bottles and with drinking water standards of Saudi Arabian, World Health Organization, and U.S. Environmental Protection Agency. The obtained results indicated that except for fluoride and bromate, the concentrations of dissolved salts, soluble cations and anions, nitrate, and trace elements of most bottled waters on sale were within the permissible limits set by standards used. On the other hand, the comparison between determined and reported label values recorded a substantial variation in some parameter values. Results indicated that more than 18 % of the sampled bottled waters exceeded the allowable limits for drinking water. Generated Piper diagrams revealed that the majority of investigated waters were sodium chloride–sulfate type; however, the hydrochemical modeling indicated that all water samples were undersaturated for anhydrite, gypsum, and halite.     

A probabilistic methodology to assess the risk of groundwater quality degradation

An approach to assess the risk of groundwater quality degradation with regard to fixed standards, based on DisjunctiveKriging (DK) is presented. The DK allows one to evaluate the Conditional Probability (CP) of overriding a given threshold of concentration of a pollutant at a given time, and at a generic point in a consideredgroundwater system. The result of such investigation over the considered area can be plotted in form of maps of spatial risk. By repeating this analysis at different times, severalspatial riskmaps will be produced, one for each consideredtime. By means of non-parametric statistics, the temporal trendof the CPs can be evaluated at every point of the considered area. The trend index, assessed by means of a sort of classification of the trend values obtained as described above,can be superimposed on the most recent values of the spatialrisk (i.e.: the most recent values of probability). Consequentlya classification of the risk of groundwater quality degradationresults with which to weigh both the spatial distribution and thetemporal behaviour of the probability to exceed a given standardthreshold. The methodology has been applied to values of nitrateconcentration sampled in the monitoring well network of theModena plain, northern Italy. This area is characterised by intensive agricultural exploitation and hog breeding along withindustrial and civil developments. The influence of agriculture on groundwater results in a high nitrate pollution that limitsits use for potable purposes.     

Assessment of water systems for contaminants from domestic and industrial sewages

The State of Minas Gerais represents one of Brazil's most outstanding mining resources. The contamination of river waterfrom kaolin processing activities may be harmful to people inthe way of slow but chronic poisoning. On the other hand, the discharge of untreated or inadequately treated domestic sewage into aquatic environments can also cause deleterious effects to the health. However, no reliable figures are available for pollutant occurrences in river water. This draws attention to thevery precarious situation that exists with respect to pollutionby organic and inorganic toxic wastes, especially with respect to humans and fauna in all its expressions. Thus, with the purpose of establishing a preliminary report to trace out industrialisation outcomes, samples of river water, vegetation and fish were collected and analysed to detect pollutant inputs.The concentration of metals was determined in suspended particle,vegetation and fish, while those of nitrite, nitrate, phosphateand chloride were determined in river water samples. The concentration of dissolved oxygen (DO) was measured in river water at the time of collection. Chemical oxygen demand (COD) and biochemical oxygen demand (BOD) were also determined. Metalinputs in the samples analysed appeared to be related to effluentdischarges into the rivers. The suspended particles showed highconcentrations (in mg kg^-1) of zinc (62 600) and aluminium(559 000), while vegetation samples collected near rivers wereheavily contaminated with iron (7680). The fishes examined werecontaminated with chromium (1.5 mg kg^-1). In general, the concentrations of nitrite, nitrate, chloride, phosphate and BOD in river water were lower than the maximum values established bythe Brazilian Environmental Standards.