Sustainable Water Quality Management Research Articles

Seasonal changes of Chlorophyll-A concentration in Jiujiang city based on remote sensing

Abstract. The Chlorophyll-a (Chla) concentration is an important parameter characterizing the water quality of rivers and lakes. Satellite remote sensing provides new opportunities for the quantitative monitoring of Chla concentration in large-scale water bodies. In this study, Sentinel-2 satellite remote sensing data integrated on the Google Earth Engine (GEE) remote sensing big data platform are employed, along with hourly measured water quality site data, to establish a quantitative inversion model for Chla concentration water quality parameters in Jiujiang City within Jiangxi Province, China. The Chla concentration is estimated for each quarter from 2020 to 2022, and the spatial distribution is analyzed, revealing the changing trend of Chla concentration over the past three years. The key findings are as follows: (1) The quantitative inversion model for Chla concentration has been validated with measured data, achieving a model accuracy of 0.53; (2) The spatial inversion results of Chla concentration exhibit an increasing trend that is consistent with actual measurement site results; (3) Owing to the influence of human activities and the peak-low water level of rivers and lakes, Chla concentration shows a discernible seasonal variation pattern. This methodology offers a new perspective for analyzing the seasonal variation characteristics of Chla concentration in rivers and lakes, providing valuable insights for the sustainable management of river and lake water quality.

Investigating hydrological dynamics and mean residence times of springs in the Tawi catchment, India: Insights into recharge mechanisms and water source variability

This study investigates the hydrological dynamics and Mean Residence Times (MRTs) of springs in the Tawi catchment, India, aiming to elucidate recharge mechanisms and water source variability. The catchment's characteristics, including altitude, geology, and land use, are examined in relation to isotopic composition and residence times of springs at six distinct locations. The study examines seasonal variations in isotopic signatures of precipitation, revealing distinct patterns during Western Disturbances (WDs) and Indian Summer Monsoon (ISM). In addition, a composite δ18O – δ2H regression line (LMWL) is developed, that suggests significant secondary evaporation from falling raindrops as a major process shaping precipitation isotopes in the catchment. The isotopic data from six stations within the catchment demonstrate specific variations influenced by local factors. Enriched rain samples in urban areas like Udhampur and Jammu show higher secondary evaporation, while depleted samples in Chenani and Mantalai suggest a canopy cover influence. Temporal and spatial variations in spring water isotopes suggest either a consistent recharge source or isotopic damping. Mean Residence Times (MRTs) of springs indicate variations in aquifer characteristics, with longer MRTs in Chenani and Mantalai indicating deeper and more complex systems. Moderate MRTs in Pangara Jagir, and Udhampur springs, suggest a balance between storage and recharge. Hydrograph separation analysis demonstrates the dominance of WDs as the precipitation source, except for Chak Rakwal, which exhibits karstified behavior with significant contribution during the ISM. The study underscores the importance of understanding recharge elevations and delineating recharge zones for sustainable groundwater management and preservation of water quality in the Tawi catchment. By elucidating these critical aspects, the study contributes to informed decision-making and effective water resource management in complex catchment areas.

Accounting for water quality—A framework for agricultural water use

Driven by increasing water demand, scarcity concerns, and climate change impacts, numerous countries prioritize solutions for enhanced water use efficiency. However, these solutions often focus primarily on managing water quantities to improve water productivity in agriculture, urban, and industrial sectors. Effective and sustainable water use, however, requires monitoring and management of both water quantity and quality. Traditionally, water quantity and water quality have been managed separately, often by different government agencies with different missions and limited interaction. Ensuring sufficient water quantity for agriculture and food production often takes precedence over managing water quality. Water accounting, as a tool for allocating and managing water quantity is now widely accepted and numerous examples of successful implementation exist worldwide. However, the concept of incorporating water quality into water accounting has not yet been widely promoted. Measuring both quantity and quality in the same water bodies is a fundamental principle of assessment of impacts on water quality through the determination of loads. The load is the amount of a given substance or pollutant for a given period of time. Using the key steps necessary for the development of a water quality monitoring and assessment programme, a framework has been developed that can be applied to water accounting projects using typical water accounting applications. Two examples of potential applications are used to consider the technical, institutional, and financial requirements. Implementing a framework for incorporating water quality monitoring and assessment into water accounting should contribute substantially to the need for more water quality data at global scale. Such data are required to facilitate achievement of Sustainable Development Goal 6 “Ensure availability and sustainable management of water and sanitation for all” through more efficient water resources management and greater awareness of water quality impacts in the agricultural water use sector.

APPLICATION OF IOT PROTOCOLS IN SURFACE WATER POLLUTION MONITORING SYSTEMS

The rapid pace of industrial growth and the rise in consumerism are increasingly contributing to the deterioration of water quality, posing significant risks to both ecological systems and human health. The urgent need for effective monitoring of water resources to mitigate pollution and ensure the sustainability of these vital ecosystems has never been more apparent. The integration of Internet of Things (IoT) technologies into surface water monitoring presents a transformative approach to addressing these challenges. By automating the collection and transmission of data on water quality, IoT technologies offer a leap forward in our ability to efficiently monitor and manage environmental health. This article explores the application of various data transmission protocols, including Wi-Fi, Zigbee, LoRa, NB-IoT, and BLE, in the context of IoT-enabled water resource monitoring systems. Considerable attention was paid to determining the physical conditions of operation and the limitations they impose on the functioning of water monitoring systems. Each protocol is examined for its potential advantages and limitations in terms of energy efficiency, transmission range, and reliability under the specific conditions encountered in surface water monitoring. Through a comparative analysis, this study not only highlights the distinctive features and suitability of each protocol but also proposes a comprehensive framework for selecting the most appropriate technology based on the specific requirements of water monitoring projects. The findings of this research underscore the critical role of IoT technologies in advancing environmental monitoring and offer valuable insights for the development of more effective and sustainable water quality management strategies.

A cooperative construction strategy for multi-parameter spatial variant random fields and its application in groundwater pollution risk assessment.

The spatial variability of hydrogeological parameters is a significant source of uncertainty in groundwater numerical modeling and has a certain risk impact on the prediction of pollutant migration and transformation. Current research has focused on the effects of single-parameter spatial variant random fields or utilizing random sampling methods to randomly combine multiple-parameter spatial variant random fields while ignoring the correlation between parameters. This paper proposes an innovative concept of associated random variables to construct multi-parameter synergistic spatial variant random fields, ensuring both the spatial variability and inherent correlation of the parameters. A hypothetical case was constructed, and the Monte Carlo sampling experiment based on computer simulation was used to assess groundwater pollution risks with multiple associated parameters. The results show that hydraulic conductivity and porosity are the main sensitive parameters. The associated random variable allows for the representation of positive correlation, negative correlation, and no correlation between the hydraulic conductivity and porosity. The pollutant mass concentrations in each observation well conform to the generalized extreme value distribution, and the pollution risks of each water well as well as the concentration distribution intervals of pollutants with different probabilities can be obtained. The influence of associated parameters on the cumulative risk of contaminants in observation wells and pollution degree range is only related to their mathematical distribution and is independent of correlations between parameters. This study addresses the issues of spatial variability and inherent correlation of hydrogeological parameters, which are of great significance for groundwater pollution risk assessment and the promotion of sustainable water quality management of groundwater resources.

Identification of nitrate accumulation mechanism of surface water in a mining-rural-urban agglomeration area based on multiple isotopic evidence

The accumulation of nitrate (NO3−) in surface waters resulting from mining activities and rapid urbanization has raised widespread concerns. Therefore, it is crucial to develop a nitrate transformation information system to elucidate the nitrogen cycle and ensure sustainable water quality management. In this study, we focused on the main river and subsidence area of the Huaibei mining region to monitor the temporal and spatial variations in the NO3− content. Multiple isotopes (δD, δ18O-H2O, δ15N-NO3−, δ18O-NO3−, and δ15N-NH4+) along with water chemistry indicators were employed to identify the key mechanisms responsible for nitrate accumulation (e.g., nitrification and denitrification). The NO3− concentrations in surface water ranged from 0.28 to 7.50 mg/L, with NO3− being the predominant form of nitrogen pollution. Moreover, the average NO3− levels were higher during the dry season than during the wet season. Nitrification was identified as the primary process driving NO3− accumulation in rivers and subsidence areas, which was further supported by the linear relationship between δ15N-NO3− and δ15N-NH4+. The redox conditions and the relationship between δ15N-NO3− and δ18O-NO3−, and lower isotope enrichment factor of denitrification indicated that denitrification was weakened. Phytoplankton preferentially utilized available NH4+ sources while inhibiting NO3− assimilation because of their abundance. These findings provide direct evidence regarding the mechanism underlying nitrate accumulation in mining areas, while aiding in formulating improved measures for effectively managing water environments to prevent further deterioration.

Evaluating the Major Sources of Surface Water Quality in Pokhara Metropolitan City, Gandaki Province, Nepal

The Mardi Watershed serves as a crucial source of drinking water for Pokhara Metropolitan City (PMC), Gandaki Province, Nepal, offering a wide range of ecosystem services including fishing, tourism, transportation, livestock support, and, notably, clean drinking water. However, the main river and its tributaries face degradation due to a blend of human and natural impacts. This comprehensive study rigorously examines the physicochemical and biological attributes that define water quality within the watershed. Recognizing the global importance of water quality for human well-being, this investigation specifically evaluates the suitability of water for drinking purposes. Twenty-three samples were collected and subjected to analysis for the twenty-one distinct physicochemical parameters. The analysis covers physicochemical parameters such as pH, water temperature, conductivity, total dissolved solids, alkalinity as well as concentrations of ions such as calcium (Ca2+), magnesium (Mg2+), sodium (Na+), potassium (K+), ammonium (NH4+), nitrate (NO3-), bicarbonate (HCO3-), sulfate (SO42-), and phosphate (PO43-), free carbon dioxide (CO2), chloride (Cl-), total hardness (TH), calcium hardness (CaH), magnesium hardness (MgH), iron (Fe2+), turbidity (Turb.) Simultaneously, biological markers including total coliforms were assessed. The overall water quality aligns with the World Health Organization (WHO) guidelines, a significant exception lies in microbial indicators. Microbial presence, likely a result of increasing anthropogenic pressures, is relatively elevated in most samples. Furthermore, the cumulative outcome reveals a Water Quality Index (WQI) of 22.04, indicating excellent suitability for drinking. Since, effective management strategies are crucial for ensuring a consistent and sustainable supply of potable water to the urban population, information obtained through this study can contribute to the sustainable management of water quality and maintaining a reliable supply of safe drinking water to urban communities.

Social imaginaries methods and socio-engineering competences in sustainable river management (a case study in the living lab Upper Citarum)

The Living Lab approach has become popular and developed in the past decade. It could provide a configuration to pursue a shared vision of integrated water resources management of the Citarum River in West Java - Indonesia. The multi-stakeholder situation and the growing recognition of interdependencies among stakeholders foster the complexity of addressing sustainable river management for the Upper Citarum River. To gain insights on essential competencies and adaptations in higher education curricula, the Environmental Engineering Department of the Faculty of Civil and Environmental Engineering-ITB, Telkom University Indonesia, and Van Hall Larenstein University of Applied Sciences, Netherlands, joined hands in a collaborative research project. This study aims to develop a socio-engineering aspect for sustainable river water quality management in the Environmental Engineering Field and Curricula. The methods used are social imaginaries of Participatory Mapping and a Poetry Route that allowed the involved river bank communities to activate their role and take positions in the living lab. Institutional stakeholders, acting in a facilitating role, learned to gain and share information from and with the community. The result concludes that social imaginaries methods enable a new perspective in developing community-based programs and advocate further exploring the socio-engineering competencies of environmental professionals.

A Systematic Review on Advancements in Remote Sensing for Assessing and Monitoring Land Use and Land Cover Changes Impacts on Surface Water Resources in Semi-Arid Tropical Environments

This study aimed to provide a systematic overview of the progress made in utilizing remote sensing for assessing the impacts of land use and land cover (LULC) changes on water resources (quality and quantity). This review also addresses research gaps, challenges, and opportunities associated with the use of remotely sensed data in assessment and monitoring. The progress of remote sensing applications in the assessment and monitoring of LULC, along with their impacts on water quality and quantity, has advanced significantly. The availability of high-resolution satellite imagery, the integration of multiple sensors, and advanced classification techniques have improved the accuracy of land cover mapping and change detection. Furthermore, the study highlights the vast potential for providing detailed information on the monitoring and assessment of the relationship between LULC and water resources through advancements in data science analytics, drones, web-based platforms, and balloons. It emphasizes the importance of promoting research efforts, and the integration of remote sensing data with spatial patterns, ecosystem services, and hydrological models enables a more comprehensive evaluation of water quantity and quality changes. Continued advancements in remote sensing technology and methodologies will further improve our ability to assess and monitor the impacts of LULC changes on water quality and quantity, ultimately leading to more informed decision making and effective water resource management. Such research endeavors are crucial for achieving the effective and sustainable management of water quality and quantity.

Investigating non-point pollution mitigation strategies in response to changing environments: A cross-regional study in China and Germany

Climate change and urbanization have altered regional hydro-environments. Yet, the impact of future changes on the pollution risk and associated mitigation strategies requires further exploration. This study proposed a hydraulic and water-quality modeling framework, to investigate the spatiotemporal characteristics of pollution risk mitigation by low impact development (LID) strategies under future Representative Concentration Pathways (RCP) and Shared Socioeconomic Pathways (SSP) scenarios. Results demonstrated that the LID strategies exhibited an effective performance of pollutant removal in the current hydro-environment, with the removal rates ranging from 33% to 56%. In future climate and urbanization scenarios, the LID performance declined and turned to be uncertain as the greenhouse gas (GHG) emissions increased, with the removal rates ranging from 12% to 59%. Scenario analysis suggested that the LID performance was enhanced by a maximum of 73% through the diversified implementation of LID practices, and the performance uncertainty was reduced by a maximum of 67% through the increased LID deployment. In addition, comparative analysis revealed that the LID strategies in a well-developed region (Dresden, Germany) were more resilient in response to changing environments, while the LID strategy in a high-growth region (Chaohu, China) exhibited a better pollutant removal performance under low-GHG scenarios. The methods and findings in this study could provide additional insights into sustainable water quality management in response to climate change and urbanization.

Application of best subset method for river water quality modeling: A study on Godavari River, India

AbstractThe utilization of water quality analysis to inform optimal decision‐making is imperative to achieve sustainable management of river water quality. A multitude of research works in the past has focused on river water quality modeling. Despite being a precise statistical regression technique that allows for fitting separate models for all potential combinations of predictors and selecting the optimal subset model, the application of best subset method in river water quality modeling is not widely adopted. The current research aims to validate the use of best subset method in evaluating the water quality parameters of the Godavari River, one of the largest rivers in India, by developing regression equations for different combinations of its physicochemical parameters. The study involves in formulating best subset regression equations to estimate the concentrations of river water quality parameters while also identifying and quantifying their variations. A total of 17 water quality parameters are analyzed at 13 monitoring sites using 13 years (1993–2005) of observed data for the monsoon (June–October) period and post‐monsoon (November–February) period. The final subset model is selected among model combinations that are developed for each year's dataset through widely used statistical criteria such as R2, F value, adjusted R2a, AICc, and RSS. The final best subset model across all parameters exhibits R2 values surpassing 0.8, indicating that the models possess the ability to account for over 80% of the variations in the concentrations of dependent parameters. Therefore, the findings demonstrated the appropriateness of this method in evaluating the water quality parameters in extensive rivers. This work is very useful for decision‐making and in the management of river water quality for its sustainable use in the study area.

Identification of Sources and Mobilization of Trace Elements in Shallow Groundwater of the Upper Ganges River Basin

The concentration of trace metals in groundwater is still not within the usual standards established by the national and international monitoring authorities. This study aims to evaluate the sources and distribution of trace metals in the shallow aquifer water of the Ganges River basin in the Bangladesh area. A total of 40 groundwater samples were collected and investigated for 11 trace elements and some selected water parameters followed by sophisticated methods. The results presented that three metals, viz. Fe, Mn, and Pb crossed the limit of WHO standard in most of the samples (70-100%), representing severe human health hazards. Besides, the samples are slightly acidic to basic and highly mineralized by divalent cations and bicarbonate because total hardness was found very high. To assess factors affecting the trace metal loads in groundwater samples and determine their possible sources and mobility, multivariate statistical techniques, including Pearson’s correlation coefficient, principal components analysis, and dendrogram cluster analysis are performed. Results revealed that sources of trace elements were identified to be geologic and little from human activities, i.e., application of agrochemicals, excess water mining, and industrial wastewater. It was recognized that the elevated concentration of trace elements in samples was caused by geogenic factors rather than manmade activities. Groundwater in this area poses a large threat due to high levels of trace metals, without any purification, it is essential to avoid this water for drinking. It advised that the groundwater quality should be constantly monitored for sustainable water quality management in the study zone.

Physicochemical pre- and post-treatment of coking wastewater combined for energy recovery and reduced environmental risk

In this study, physicochemical pre- and post-treatment of highly polluting coking wastewater (CWW) for the removal of refractory compounds and recovery of high-energy substances/components was investigated. An economic optimization model targeting the development of a cost-effective and sustainable treatment technology was proposed. At the post-treatment stage, powdered activated carbon (PAC) was used to separate the refractory and toxic pollutants from the bio-treated CWW, with the adsorption capacity ranging from 50 to 120 mg chemical oxygen demand (COD) g−1 PAC. Then, the spent PAC, together with a coagulant, was reused in the pre-treatment of highly concentrated raw CWW, which lifted the adsorption capacity to 800–1200 mg COD g−1 PAC. Results showed that the adsorbent’s high selectivity towards macromolecular and complicated pollutants could remove 25–65 % of COD in both CWW flows. Analysis of pollutants’ molecular weight distribution and GC-MS indicated a good affinity between PAC and high-energy pollutants (phenolic compounds and alkanes), which could transfer 144,555 kJ m−3 of energy from CWW to the adsorption-coagulation sludge. The economic optimization model suggested that the cost of the adsorbent was compensated by the net benefits of energy recovery and that profit was achieved when the PAC price was less than 5562 CNY t−1. The proposed two-stage PAC/coagulant approach offers a way to sustainable water quality and sludge management, plus energy recycling, in CWW treatment. It may also be applied to the treatment of other industrial wastewaters.

Controls on Spatial Variability in Mean Concentrations and Export Patterns of River Chemistry Across the Australian Continent

AbstractThe state and dynamics of river chemistry are influenced by both anthropogenic and natural catchment characteristics. However, understanding key controls on catchment mean concentrations and export patterns comprehensively across a wide range of climate zones is still lacking, as most of this research is focused on temperate regions. In this study, we investigate the catchment controls on mean concentrations and export patterns (concentration–discharge relationship,C–Qslope) of river chemistry, using a long‐term data set of up to 507 sites spanning five climate zones (i.e., arid, Mediterranean, temperate, subtropical, tropical) across the Australian continent. We use Bayesian model averaging (BMA) and hierarchical modeling (BHM) approaches to predict the mean concentrations and export patterns and compare the relative importance of 26 catchment characteristics (e.g., topography, climate, land use, land cover, soil properties and hydrology). Our results demonstrate that mean concentrations result from the interaction of catchment indicators and anthropogenic factors (i.e., land use, topography and soil), while export patterns are influenced by topography. We also found that incorporating the effects of climate zones in a BHM framework improved the predictability of both mean concentrations andC–Qslopes, suggesting the importance of climatic controls on hydrological and biogeochemical processes. Our study provides insights into the contrasting effects of catchment controls across different climate zones. Investigating those controls can inform sustainable water quality management strategies that consider the potential changes in river chemistry state and export behavior.

Long-Term (1990–2013) Changes and Spatial Variations of Cropland Runoff across China

Quantitative information on regional cropland runoff is important for sustainable agricultural water quantity and quality management. This study combined the Soil Conservation Service Curve Number (SCS-CN) method and geostatistical approaches to quantify long-term (1990–2013) changes and regional spatial variations of cropland runoff in China. Estimated CN values from 17 cropland study sites across China showed reasonable agreement with default values from the National Engineering Handbook (R2 = 0.76, n = 17). Among four commonly used geostatistical interpolation methods, the inverse distance weighting (IDW) method achieved the highest accuracy (R2 = 0.67, n = 209) for prediction of cropland runoff. Using default CN values and the IDW method, estimated national annual cropland runoff volume and runoff depth in 1990–2013 were 253 ± 25 km3 yr−1 and 182 ± 15 mm yr−1, respectively. Estimated cropland runoff depth gradually increased from the drier northwest inland region to the wetter southeast coastal region (range: 2–1375 mm yr−1). Regionally, eastern, central and southern China accounted for 39% of the cultivated area and 53% of the irrigated land area and contributed to 68% of the national cropland runoff volume. In contrast, northwestern, northern, southwestern and northeastern China accounted for 61% of the cultivated area and 47% of the irrigated land area and contributed to 32% of the runoff volume. Rainfall was the main source (72%) of cropland runoff for the entire nation, while irrigation became the main source of cropland runoff in drier regions (northwestern and southwestern China). Over the 24-year study period, estimated cropland runoff depth showed no significant trends, whereas cropland runoff volume and irrigation-contributed percentages decreased by 7% and 35%, respectively, owing to implementation of water-saving irrigation technologies. To reduce excessive runoff and increase water utilization efficiencies, regionally specific water management strategies should be further promoted. As the first long-term national estimate of cropland runoff in China, this study provides a simple framework for estimating regional cropland runoff depth and volume, providing critical information for guiding developments of management practices to mitigate agricultural nonpoint source pollution, soil erosion and water scarcity.

Spatiotemporal variations of water quality and their driving forces in the Yangtze River Basin, China, from 2008 to 2020 based on multi-statistical analyses.

Water quality deterioration is a prominent issue threatening water security worldwide. As the largest river in China, the Yangtze River Basin is facing severe water pollution due to intense human activities. Analyzing water quality trends and identifying the corresponding driver factors are important components of sustainable water quality management. Thus, spatiotemporal characteristics of the water quality from 2008 to 2020 were analyzed by using a Mann-Kendall test and rescaled range analysis (R/S). In addition, multi-statistical analyses were used to determine the main driving factors of variation in the permanganate index (CODMn), ammonia nitrogen (NH3-N) concentration, and total phosphorus (TP) concentration. The results showed that the mean concentrations of NH3-N and TP decreased from 0.31 to 0.16mg/L and 0.16 to 0.07mg/L, respectively, from 2008 to 2020, indicating that the water quality improved during this period. However, the concentration of CODMn did not reduce remarkably. Based on R/S analysis, the NH3-N concentration was predicted to continue to decrease from 2020 to 2033, whereas the CODMn concentration was forecast to increase, highlighting an issue of great concern. In terms of spatial distribution, water quality in the upstream was better than that of the mid-downstream. Multi-statistical analyses revealed that the temporal variation in water quality was predominantly influenced by tertiary industry (TI), the nitrogen fertilizer application rate (N-FAR), the phosphate fertilizer application rate (P-FAR), and the irrigation area of arable land (IAAL), with contribution rates of 15.92%, 14.65%, 3.46%, and 2.84%, respectively. The spatial distribution of CODMn was mainly influenced by TI, whereas that of TP was primarily determined by anthropogenic activity factors (e.g., N-FAR, P-FAR). This study provides deep insight into water quality evolution in the Yangtze River Basin that can guide water quality management in this region.

Spatiotemporal water quality variations in the urbanizing Chongqing reach of Jialing River, China

AbstractWater quality in rivers usually exhibits markedly spatiotemporal variations as affected by urbanization, while the magnitude of these effects remain unclear. This study aimed to investigate the spatiotemporal water quality variations in the urbanizing Chongqing reach of Jialing River and its tributary using a 6-yr multisite dataset (January 2010–December 2015). Water quality variables including pH, dissolved oxygen (DO), permanganate index (CODMn), ammonia nitrogen (NH3-N) and total phosphorus (TP) were deciphered. Results showed that the trunk river displayed respectively 1.2 and 39.8% higher pH and DO concentration but 66.9, 94.7 and 85.2% lower CODMn, NH3-N and TP concentrations relative to the tributary (P < 0.05), due largely to the dilution effects occurring in the trunk river. The dry season presented respectively 1.3, 18.2, 102.8 and 32.5% higher pH, DO, NH3-N and TP concentrations than those in the wet season (P < 0.05). DO concentration showed significant inter-annual variations (P < 0.05), and CODMn, NH3-N and TP concentrations all presented markedly declining trends from 2010 to 2015 (P < 0.05). Significant relationships among the study variables were found in different spatiotemporal scales (P < 0.05). Our results are valuable to optimize strategies for sustainable water quality management in rivers experiencing urbanization worldwide.

Fecal indicator organisms in northern oligotrophic rivers: An explorative study on Escherichia coli prevalence in a mountain region with intense tourism and reindeer herding

Increasing pollution levels in waters from remote mountain areas in northern Sweden have been observed. To support a sustainable water quality management, it is necessary to know which environmental and antrophogenic factors influence the water quality. The purpose of this study was to map the Escherichia coli prevalence in the catchment area of the upper part of a large northern Scandinavian river and investigate the controlling factors of microbial contamination. A total of 112 water samples were collected from various locations in the research area between July 2020 and December 2020. These samples were analyzed for microbial and chemical characteristics, and information about tourism and reindeer herding was compiled. Additionally, microbial and physicochemical water characteristics collected by Indalsälven Water Conservation Association (IWCA, 1993–2020) and Swedish Meteorological and Hydrological Institute (SMHI, 2004–2020) were analyzed. The results showed that E. coli enumerations ranged between 0 and 500 CFU/100 ml. There was generally no obvious relation between suspected point sources, e.g., sewage treatment plants at mountain stations, and E. coli levels at downstream sampling points. Principal component analysis showed that E. coli was correlated to coliforms, total heterotrophic count, river discharge, CODMn and river color. Since microbial analyses are time-consuming, expensive and difficult to perform in remote areas, it is important to find more easily extracted water parameters that can serve as a proxy for E. coli. In particular, river color and discharge are promising parameters that may serve as an early indication of bacterial outbreak and fecal contamination in mountain waters.

Common Agricultural Policy (CAP) from a Public Health Perspective

Abstract European Common agricultural policy (CAP) can impact several health outcomes like increased antibiotic resistant infections, poor health of farm workers and unhealthy diets which lead to several non-communicable diseases. Rapid literature review of public health recommendations for a new CAP covers several topics from environment, pesticides, livestock and antimicrobial resistance (AMR) to diet, food systems and others. Recommendations on pesticides are to periodically upgrade minimum standards of pesticides, reduce or abandon the use of pesticides and sustainable management of water quality in agriculture. In relation to livestock and antimicrobial resistance, EU should dedicate financial resources for programmes aimed at decreasing animal numbers, stop support for industrial livestock production through CAP subsidies and adopt low-antibiotics farming methods. To ensure better diet and food systems we need sustainable dietary guidelines, food labelling schemes, public procurement of healthy, local and seasonal foodstuffs, food education and campaigns, promoting food systems thinking at all levels, increase productivity of fruit and vegetable cultivation and social innovation in food supply chains. Other recommendations state that CAP should end support for wine sector and that CAP should include training, payment of adequate wages and health and safety standards, and lastly implementation of Health impact assessment of CAP. Agricultural policy is a very complex field with many stakeholders and consequently also implications on many levels. To make health a more visible and important objective, we need more public health experts to take part in advocacy for healthier CAP.

Physicochemical assessment of leachate from Pokhara landfill site and its impact on the quality of Seti River water, Nepal

The management of municipal solid always poses serious environmental problems on land, air, and groundwater, especially in the case of developing countries. The characterization and assessment of leachates are necessary to understand the water quality in the urban region as well as has enormous importance in sustaining the livelihoods of people in the riverine environment maintaining the ecological balance. Landfill leachate contains thousands of complex components, which contaminate the nearby water bodies, and communities with several hazardous ingredients. The present study was conducted to assess the influence of landfill leachates on the quality of Seti River water. The samples were collected from four stations (Tatopani, Ramghat, Landfill, Below landfill, and Kotre). The samples were analyzed for pH, total hardness, dissolved oxygen, biochemical oxygen demand, turbidity, total dissolved solids, electrical conductivity (EC), Cl-, NH3, and PO43- by standard methods. The pH and EC were measured in situ whereas other parameters were analyzed in the laboratory adopting standard protocols. The physicochemical parameters of river water and that of leachates were compared to monitor the level of contamination. The research reveals the landfill to have insignificant pollution of water on matching the parameters with World Health Organization (WHO) guideline values. Regular monitoring of the quality of river water and sustainable management of solid waste is essential for the ecological quality and integrity of the environment in the region. Scientific information obtained by this study could contribute to policymakers for the sustainable management of water quality and landfill in the downstream and urban segments of the river basins.