Domestic water consumption monitoring and behaviour intervention by employing the internet of things technologies

As the water resource is becoming scarce, conservation of water has a high priority around the globe, study on water management and conservation becomes an important research problem. People are increasingly becoming more individual households, which tend to be less efficient, requiring more resources per capita than larger households. In order to address these challenges, this paper presents the achievements of monitoring domestic water consumption at the appliance level and intervening people's water usage behavior which have been made in ISS-EWATUS (http://www.issewatus.eu), an European Commission funded FP7 project. The water amount consumed by every household appliance is wirelessly recorded with the exact consumption time and stored in a central database. People's water consumption behavior is likely affected by the real-time water consumption awareness, instant practical advices regarding water-saving activities and classification of water consumption behavior for individuals, all of which are provided by a decision support system deployed as a mobile application in a tablet or any other mobile devices. Only the enhanced water consumption awareness is presented in this paper due to the space limitation. The integrated monitoring and decision support system has been deployed and in use in Sosnowiec in Poland and Skiathos in Greece since March 2015. The domestic water consumption monitoring system at appliance level and the local DSS for affecting people's water consumption behavior are innovative and have little seen before according to the knowledge of the authors.This work is part of the ISS-EWATUS project (www.issewatus.eu) and has been funded by the European Union’s Seventh Framework Programme for research, technological development and demonstration under grant agreement no (619228). Appreciation also goes to our former research associates Dr Xi Chen, Dr Xiaomin Chen, Dr Kim Perren, and Dr Yixing Shan who have worked in Loughborough University on the project at various stages

Cross-Mapping Important Interactions between Water-Energy-Food Nexus Indices and the SDGs

Worldwide, many developing countries are making efforts to achieve sustainability through the 17 SDGs and at the same time to contribute to environmental security. The Nexus approach enables a more integrated and sustainable use of resources that extends beyond traditional siloed thinking and is applicable at multiple scales. This is especially important in a globalized world where collaboration is becoming increasingly important for societies. In this framework, we present an analysis that will assist policymakers set priorities in investments by investigating the influence of the WEF nexus on the 17 SDGs and vice versa. Following the Nexus approach may thus enhance synergies and contribute to increased performance in connected SDGs that are positively influenced. In this article, we present an analysis that allows stakeholders to adapt it to their specific needs by entering new scores based on the characteristics of each case study; the results of this methodology should be considered in light of the specific conditions, including socio-cultural aspects and geographical, geopolitical, and governance realities, as well as the scale of the case study in question. A Fuzzy Cognitive Map analysis is also conducted on the scores to quantify SDG impact and identify the SDGs that most strongly “influence” nexus-coherent policies and the SDGs that are most strongly “influenced by” the nexus. This is achieved by analyzing the causality in this complex system of positive and negative interlinkages. Through this analysis, three SDGs, namely SDG 2 (Food), SDG 6 (Water) and SDG 7 (Energy), are indicated as the most influenced by the WEF nexus, revealing either synergies or trade-offs, while other SDGs are identified as having little interaction with the WEF nexus system

Erosion probability for biofilm modeling: analysis of trends

This study presents the strengths and weaknesses of a biofilm erosion probability algorithm that can be used in cellular automaton and individual-based biofilm simulation models. The erosion probability is calculated using data on localized biofilm mechanical properties, expressed through the composite biofilm Young's modulus-a measure of biofilm strength that varies in time and space-and on fluid hydrodynamic shear stress. Analysis of trends shows that biofilm detachment is the process that results from the competition between biofilm strength and hydrodynamic shear stress exerted on it by the fluid, with hydrodynamics being more important when biofilm strength is low and vice versa. From the modeling sample analyzed in this study, it is evident that for biofilms with cluster and mushroom formations, erosion probabilities are lower in the crevices formed between two clusters-where substrate is depleted-and higher at the top of the clusters where there is fresh biomass growth. When compared to other detachment methodologies extensively used by biofilm modeling researchers, such as the detachment speed that is a function of the square of the distance to the solid substratum, it is proved that the probability of erosion algorithm would give similar results

Using Bayesian hierarchical modelling to capture cyanobacteria dynamics in Northern European lakes

Cyanobacteria blooms in lakes and reservoirs currently threaten water security and affect the ecosystem services provided by these freshwater ecosystems, such as drinking water and recreational use. Climate change is expected to further exacerbate the situation in the future because of higher temperatures, extended droughts and nutrient enrichment, due to urbanisation and intensified agriculture. Nutrients are considered critical for the deterioration of water quality in lakes and reservoirs and responsible for the widespread increase in cyanobacterial blooms. We model the response of cyanobacteria abundance to variations in lake Total Phosphorus (TP) and Total Nitrogen (TN) concentrations, using a data set from 822 Northern European lakes. We divide lakes in ten groups based on their physico-chemical characteristics, following a modified lake typology defined for the Water Framework Directive (WFD). This classification is used in a Bayesian hierarchical linear model which employs a probabilistic approach, transforming uncertainty into probability thresholds. The hierarchical model is used to calculate probabilities of cyanobacterial concentrations exceeding risk levels for human health associated with the use of lakes for recreational activities, as defined by the World Health Organization (WHO). Different TN and TP concentration combinations result in variable probabilities to exceed pre-set thresholds. Our objective is to support lake managers in estimating acceptable nutrient concentrations and allow them to identify actions that would achieve compliance of cyanobacterial abundance risk levels with a given confidence level

Geochemical modeling of mercury in coastal groundwater

The systematic analysis of groundwater in the Greek island of Skiathos revealed a seasonal increase of total mercury concentrations after the extensive groundwater abstraction during the busy and heavily touristic summer months. This contamination was accompanied by a corresponding increase of the chloride content of groundwater, attributed to seawater intrusion into the freshwater-depleted aquifer within mercury-rich bedrock. The effects of elevated concentrations of chloride anions in the mobilization of mercury and its speciation were addressed by geochemical equilibrium modeling, considering cinnabar (HgS) as the mineral source of mercury. Adsorption onto hydrous ferric oxide (Fe2O3·H2O) was a necessary ingredient of the geochemical model for bringing the calculated concentrations in agreement with field measurements, after optimization of the cinnabar/adsorbent mass ratio to a value of 4.9 × 10−8. The speciation of mercury was found to depend on the acidity and redox status as well as on the chloride content of groundwater. Mercury concentrations in the groundwater of Skiathos rise above the World Health Organization limit of 1 μg L−1 for a seawater intrusion higher than 3 %, with HgCl2 being the dominant species followed by HgClOH, HgCl3− and HgCl42−. The assumed concentration of dissolved organic matter in groundwater had a negligible impact on the mercury speciation and its mobilization by chloride

Using Bayesian hierarchical modelling to capture cyanobacteria dynamics in Northern European lakes

Cyanobacteria blooms in lakes and reservoirs currently threaten water security and affect the ecosystem services provided by these freshwater ecosystems, such as drinking water and recreational use. Climate change is expected to further exacerbate the situation in the future because of higher temperatures, extended droughts and nutrient enrichment, due to urbanisation and intensified agriculture. Nutrients are considered critical for the deterioration of water quality in lakes and reservoirs and responsible for the widespread increase in cyanobacterial blooms. We model the response of cyanobacteria abundance to variations in lake Total Phosphorus (TP) and Total Nitrogen (TN) concentrations, using a data set from 822 Northern European lakes. We divide lakes in ten groups based on their physico-chemical characteristics, following a modified lake typology defined for the Water Framework Directive (WFD). This classification is used in a Bayesian hierarchical linear model which employs a probabilistic approach, transforming uncertainty into probability thresholds. The hierarchical model is used to calculate probabilities of cyanobacterial concentrations exceeding risk levels for human health associated with the use of lakes for recreational activities, as defined by the World Health Organization (WHO). Different TN and TP concentration combinations result in variable probabilities to exceed pre-set thresholds. Our objective is to support lake managers in estimating acceptable nutrient concentrations and allow them to identify actions that would achieve compliance of cyanobacterial abundance risk levels with a given confidence level.publishedVersio