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Population-dense urban areas often concentrate high commercial and industrial activity and intricate transportation systems. In crowded cities, extreme events can be even more damaging due to the high population they affect and the social inequalities that are likely to emerge. Extreme heat is a climate hazard that has been linked to high morbidity and mortality, especially in cities with high population densities. The way extreme heat events are felt in the population varies depending on a variety of factors, such as age, employment status, living conditions, air-conditioning, housing conditions, habits, behaviors and other socio-demographic parameters. In this article, we quantify and locate vulnerabilities of populations to extreme heat in order to formulate policy and practice recommendations that will make communities resilient and will shape the transition to a more sustainable future. This work contributes towards the achievement of Sustainable Development Goal 11—Sustainable Cities and Communities—by developing the tools to make cities and settlements resilient and sustainable. To this end, we analyze socioeconomic data at the NUTS3 level for the national case study of Greece and at the census tract level for the local case study of the city of Athens. The target variable for this study is defined as the average daily mortality during heatwaves per 100,000 individuals, and a methodology is developed for constructing this variable based on socioeconomic data available in public databases. The independent variables were selected based on their contribution to socioeconomic vulnerability; they include the percentage of elderly individuals, retirees, unemployed persons, renters, those living alone, those residing in smaller houses, those living in older houses and immigrants from developing countries. An ensemble gradient boosted tree model was employed for this study to obtain feature importance metrics that was used to construct a composite index of socioeconomic heat vulnerability. The socioeconomic heat vulnerability index (SHVI) was calculated for each prefecture in Greece and for each census tract in the city of Athens, Greece. The unique feature of this SHVI is that it can be applied to any geographical resolution using the same methodology and produces a result that is not only quantifiable, but also facilitates a comparison between vulnerability scores across different regions. This application aimed to map the SHVI of both prefecture and city, to examine the significance of scale, to identify vulnerability hotspots, and rank the most vulnerable areas, which are prioritized by authorities for interventions that protect public health. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

In 2015 the updated Agenda 2030, outlining the new priorities towards future sustainability, was published by the United Nations reflecting the general directions towards a fairer and more sustainable pattern of socio-economic development. The specialisation of the 17 Sustainable Development Goals (SDGs) and indicators into local contexts constitutes a basic prerequisite as particular characteristics, needs and peculiarities should be considered. This paper focuses on the exploration of local-oriented indicators and policy recommendations that have the potential to boost the successful implementation of SDGs in Greece. A nexus approach is adopted underlining the need to analyse complexities, motivate systemic thinking and develop integrated policies targeting at the sustainable and efficient use of resources. It also highlights the need for designing local-specific indicators and policy initiatives, encapsulating particular characteristics and conditions and boosting the advancement of SDGs. Such an approach has the potential to be implemented not only at national but also at an operational level in local scale (e.g., River Basin Scale). The outcomes indicate that emphasis should be given on smart water management and precision agriculture, extensive use of technologies capturing Greenhouse Gases (GHGs), dynamic penetration of Renewable Energy Sources (RES) in gross final energy production/consumption and protection of terrestrial ecosystems. [ABSTRACT FROM AUTHOR]

Water, energy, food, land and climate form a tightly-connected nexus in which actions on one sector impact other sectors, creating feedbacks and unanticipated consequences. This is especially because at present, much scientific research and many policies are constrained to single discipline/sector silos that are often not interacting (e.g., water-related research/policy). However, experimenting with the interaction and determining how a change in one sector could impact another may require unreasonable time frames, be very difficult in practice and may be potentially dangerous, triggering any one of a number of unanticipated side-effects. Current modelling often neglects knowledge from practice. Therefore, a safe environment is required to test the potential cross-sectoral implications of policy decisions in one sector on other sectors. Serious games offer such an environment by creating realistic 'simulations', where long-term impacts of policies may be tested and rated. This paper describes how the ongoing (2016-2020) Horizon2020 project SIM4NEXUS will develop serious games investigating potential plausible cross-nexus implications and synergies due to policy interventions for 12 multi-scale case studies ranging from regional to global. What sets these games apart is that stakeholders and partners are involved in all aspects of the modelling definition and process, from case study conceptualisation, quantitative model development including the implementation and validation of each serious game. Learning from playing a serious game is justified by adopting a proof-of-concept for a specific regional case study in Sardinia (Italy). The value of multi-stakeholder involvement is demonstrated, and critical lessons learned for serious game development in general are presented. [ABSTRACT FROM AUTHOR]

Toxins produced by cyanobacteria in freshwater ecosystems constitute a serious health risk worldwide for humans that may use the affected water bodies for recreation, drinking water, and/or irrigation. Cyanotoxins have also been deemed responsible for loss of animal life in many places around the world. This paper explores the effect of HO treatments on cyanobacteria and microcystins in natural samples from a hypertrophic reservoir in microcosm experiments. According to the results, cyanobacteria were more easily affected by HO than by other phytoplanktonic groups. This was shown by the increase in the fractions of chlorophyll-a (a proxy for phytoplankton) and chlorophyll-b (a proxy for green algae) over total phytoplankton pigments and the decrease in the fraction of phycocyanin (a proxy for cyanobacteria) over total phytoplankton pigments. Thus, while an overall increase in phytoplankton occurred, a preferential decrease in cyanobacteria was observed with HO treatments over a few hours. Moreover, significant degradation of total microcystins was observed under HO treatments, while more microcystins were degraded when UV radiation was used in combination with HO. The combination of HO and ultraviolet (UV) treatment in natural samples resulted in total microcystin concentrations that were below the World Health Organization limit for safe consumption of drinking water of 1 μg/L. Although further investigation into the effects of HO addition on ecosystem function must be performed, our results show that the application of HO could be a promising method for the degradation of microcystins in reservoirs and the reduction of public health risks related to the occurrence of harmful algal blooms. [ABSTRACT FROM AUTHOR]

The nitrogen and phosphorus loadings coming from diffuse, non-point pollution sources related to agriculture and animal husbandry in the Penios river basin in the region of Thessaly, Greece, were estimated. Detailed data on types of crops and field area as well as types and numbers of animals bred in the municipal districts included in the Penios River Basin District were collected from agricultural cooperatives and rural agencies in Thessaly. Related nitrogen and phosphorus loadings were calculated and all data were mapped in a geographic information system (GIS) environment to show how diffuse pollution is spatially distributed in the Penios basin and to identify areas with the highest anthropogenic pressures. This type of data is useful to a driving forces–pressures–state–impacts–responses (DPSIR) analysis – a tool suitable for the analysis of environmental decisions in the direction of sustainable development. [ABSTRACT FROM AUTHOR]

The use of photovoltaic (PV) panels as an alternative energy source has a great potential for countries with high solar potential like Greece. We examined the incentives offered by the Greek government to private consumers for the installation and operation of such a system on their houses—either on the roof, or embodied with building materials for the construction of a house. We used two software packages, PVGIS and PVSYST, specifically developed for the design of PV systems, in order to take into account solar radiation and other meteorological conditions for the design of a PV system on a house in Xanthi, Greece. The expected power generation was calculated and was proved to be sufficient to cover the energy needs of the household; the number of panels for roof installation, u well as inclination angle were also specified. An economic analysis (break-even point and external rate of return) of the investment was also conducted, proving that PV installation is a solid investment thatis also sustainable and environment-friendly. [ABSTRACT FROM AUTHOR]

Fresh water shortage is one of the greatest problems of modern society; the explosive increase in world population, along with the unusual socio-economic development have led to an. increased water demand, making water shortage a critical issue for countries like Greece. Desalination of seawater is suitable for supplying arid regions of the country with potable water and is becoming the dominant alternative in drinking water production, but may be energy intensive. On the other hand, global warming initiatives push for sustainable alternatives that will produce minimal or negligible quantities of CO2 to prevent climate change conditions. In this paper, a survey of several desalination plants in Greece is conducted, studying their energy usage patterns, in an effort to determine their carbon footprint. Specifically, a questionnaire has been sent out to desalination plants that addresses questions relative to the location and size of the plants, plant equipment condition, water production seasonality, whether energy required is generated on-site, or is purchased by a power plant and possible use of renewable energy sources. A different survey of the Greek Public Power Corporation has been conducted, in order to determine the type of fuel used by the power plants that supply each desalination plant with energy. Taking into account all this information and other energy-related factors, we provide estimates of the carbon footprint of several desalination plants in Greece. [ABSTRACT FROM AUTHOR]

Cyanobacterial blooms have been known since ancient times; however, they are currently increasing globally. Human and ecological health risks posed by harmful cyanobacterial blooms have been recorded around the world. These risks are mainly associated with their ability to affect the ecosystem chain by different mechanisms like the production of cyanotoxins, especially microcystins. Their expansion and their harmful effects have led many researchers to seek techniques and strategies to control them. Among them, hydrogen peroxide could be a promising tool against cyanobacteria and cyanotoxins and it is well-established as an environmentally friendly oxidizing agent because of its rapid decomposition into oxygen and water. The aim of the present study was to evaluate the effect of hydrogen peroxide on phytoplankton from two hypertrophic waterbodies in Greece. The effect of hydrogen peroxide on concentration of microcystins found in the waterbodies was also studied. Treatment with 4 mg/L hydrogen peroxide was applied to water samples originated from the waterbodies and Cyanobacterial composition and biomass, phycocyanin, chlorophyll-a, and intra-cellular and total microcystin concentrations were studied. Cyanobacterial biomass and phycocyanin was reduced significantly after the application of 4 mg/L hydrogen peroxide in water treatment experiments while chlorophytes and extra-cellular microcystin concentrations were increased. Raphidiopsis (Cylindrospermopsis) raciborskii was the most affected cyanobacterial species after treatment of the water of the Karla Reservoir in comparison to Aphanizomenon favaloroi, Planktolyngbya limnetica, and Chroococcus sp. Furthermore, Microcystis aeruginosa was more resistant to the treatment of Pamvotis lake water in comparison with Microcystis wesenbergii and Microcystis panniformis. Our study showed that hydrogen peroxide differentially impacts the members of the phytoplankton community, affecting, thus, its overall efficacy. Different effects of hydrogen peroxide treatment were observed among cyanobacerial genera as well as among cyanobacterial species of the same genus. Different effects could be the result of the different resistance mechanisms of each genus or species to hydrogen peroxide. Hydrogen peroxide could be used as a treatment for the mitigation of cyanobacterial blooms in a waterbody; however, the biotic and abiotic characteristics of the waterbody should be considered. [ABSTRACT FROM AUTHOR]

A 25.4-mm diameter hydrocyclone with an underflow receiver was evaluated for its ability to achieve separation of fine particles from water at elevated temperatures and pressures relevant to supercritical oxidation. Temperature was varied from 25°C to 340°C, while pressure was maintained at 27.6 MPa. The particles studied were α-alumina. Particle-removal efficiency was affected by the separation capabilities of the hydrocyclone, deposition on the heater surface, and flocculation of the particles. Particle-size distributions and suspended solids analyses confirmed that cyclone, separation efficiency was controlled by the (densityparticle - densitywater)/viscositywater ratio. Because this ratio is sensitive to temperature, especially in the neighborhood of the supercritical point, separation efficiencies sharply increased with temperature. Contrary to traditional air cyclone theory, removal efficiency was inversely correlated to flow rate. This result was caused by particle deposition and particle flocculation in the heater. Low flow rates increased heater detention times and, thus, opportunities for flocculation and particle deposition. Therefore, the performance of a hydrocyclone used in conjunction with supercritical oxidation depends on phenomena occurring in the heater and the hydrocyclone. [ABSTRACT FROM AUTHOR]

The prediction of sediment levels in combined sewer system (CSS) would result in enormous savings in resources for their maintenance as a reduced number of inspections would be needed. In this paper, we benchmark different machine learning (ML) methodologies to improve the maintenance schedules of the sewerage and reduce the number of cleanings using historical sediment level and inspection data of the combined sewer system in the city of Barcelona. Two ML methodologies involve the use of spatial features for sediment prediction at critical sections of the sewer, where the cost of maintenance is high because of the dangerous access; one uses a regression model to predict the sediment level of a section, and the other one a binary classification model to identify whether or not a section needs cleaning. The last ML methodology is a short-term forecast of the possible sediment level in future days to improve the ability of operators to react and solve an imminent sediment level increase. Our study concludes with three different models. The spatial and short-term regression methodologies accomplished the best results with Artificial Neural Networks (ANN) with 0.76 and 0.61 R2 scores, respectively. The classification methodology resulted in a Gradient Boosting (GB) model with an accuracy score of 0.88 and an area under the curve (AUC) of 0.909. [ABSTRACT FROM AUTHOR]

As water scarcity becomes more prevalent, the analysis of urban water consumption patterns at the consumer level and the estimation of the corresponding water demand for water utility are expected to be among the top priorities of water companies in the near future. This study proposes a comprehensive methodology for water managers to achieve an efficient operation of urban water networks, by successfully detecting residential water consumption patterns corresponding to different household needs and behaviors. The methodology uses Self Organizing Maps as the main clustering algorithm in combination with K-means and Hierarchical Agglomerative Clustering. The objective is to create clusters in a literature dataset that includes water consumption from 21 customers located in Milford, Ohio, USA, for a 7-month period. Originally, water consumption data was recorded for every water use incident in the household, while for this analysis, the information is converted to half-hourly water consumption. Individual customers with similar consumption behavior are clustered and water-consumption curves are calculated for each cluster; these curves can be used by the water utility to obtain estimates of the spatio-temporal distribution of demand, thus giving insight into peak demands at different locations. Statistical indices of agreement are used to confirm a good agreement between the estimated and observed water use, when clustering is employed. The resulting curves show a clear improvement in capturing water consumption behavior at household level, when compared to corresponding curves obtained without clustering. This analysis offers water utilities an innovative solution that relies on real time data and uses data science principles for optimizing water supply and network operation and provides tools for the efficient use of water resources. [ABSTRACT FROM AUTHOR]

The Netherlands has the ambitious target of transitioning to a low-carbon economy by 2050. One factor that may constrain this progress, however, is the large spatial requirements of renewable energy technologies, and resulting competition for land through interlinkages between the Climate (C), Land (L), Energy (E), Water (W) and Food (F) domains—the CLEWF nexus. This study aims at identifying innovations that can improve the performance of the nexus by addressing the land scarcity constraint while supporting the low-carbon economy transition. A framework for the identification of potential innovations applicable in the nexus context was developed and applied. It is derived from a Driver-Pressure-State-Impact-Response (DPSIR) analysis of land scarcity in the Dutch nexus and a stock-taking benchmarking analysis of European countries. An inventory of innovations was prepared based on several classifications of innovations, collecting examples from the Netherlands, Belgium, Denmark, Germany, Latvia and Sweden. Three innovations were identified as particularly promising: district heating, Energy Service Companies and peak shaving through water pumping. Furthermore, the DPSIR framework was also used to identify overarching societal elements common to countries that successfully implemented sustainable innovations. These were found to relate to long-term political commitments, geopolitical and economic drivers, and pioneering approaches building from and towards national strengths. [ABSTRACT FROM AUTHOR]

Cyanobacterial blooms are considered a major threat to global water security with documented impacts on lake ecosystems and public health. Given that cyanobacteria possess highly adaptive traits that favor them to prevail under different and often complicated stressor regimes, predicting their abundance is challenging. A dataset from 822 Northern European lakes is used to determine which variables better explain the variation of cyanobacteria biomass (CBB) by means of stepwise multiple linear regression. Chlorophyll-a (Chl-a) and total nitrogen (TN) provided the best modelling structure for the entire dataset, while for subsets of shallow and deep lakes, Chl-a, mean depth, TN and TN/TP explained part of the variance in CBB. Path analysis was performed and corroborated these findings. Finally, CBB was translated to a categorical variable according to risk levels for human health associated with the use of lakes for recreational activities. Several machine learning methods, namely Decision Tree, K-Nearest Neighbors, Support-vector Machine and Random Forest, were applied showing a remarkable ability to predict the risk, while Random Forest parameters were tuned and optimized, achieving a 95.81% accuracy, exceeding the performance of all other machine learning methods tested. A confusion matrix analysis is performed for all machine learning methods, identifying the potential of each method to correctly predict CBB risk levels and assessing the extent of false alarms; random forest clearly outperforms the other methods with very promising results. [ABSTRACT FROM AUTHOR]

An annual and lumped water balance assessment of a water distribution network is recommended by the International Water Association as a first step and prerequisite for improving the performance of the network by minimizing real/physical water losses, burst incidents, water theft, nonrevenue water, and energy consumption, among others. The current work suggests a modeling approach for developing the water balance of a network spatio-temporarily, in hour time-scale and neighborhood granularity. It exploits already established key performance indicators and introduces some new ones to highlight the potential in improving the management of a water distribution network when having a detailed spatio-temporal supervision, especially when the spatial and temporal conditions are variable. The methodology is applied in a seasonally touristic and hilly case study. Additionally, a pressure management scheme is applied to further exploit the potential of such a toolkit. For the investigated case study, the town of Skiathos, the annual real losses are estimated equal to 50.9–52.2% of the system input volume, while apparent losses are estimated to be about 5.6–6.6%. Losses depict intense seasonal variability. Real losses range from 38.8–39.6% in summer months to 63.3–64.7% in winter months, while apparent losses range from 8.4–9.3% in summer to 1.3–2.5% in winter. Annual water theft is estimated to be at least 3.6% of system input volume. Spatial variability, which is linked to the elevation and the different urban land uses is proven to play a significant role in the neighborhoods' water balances and various key performance indicators are suggested and applied for the pressure control scheme. The annual potential savings due to the applied scheme rise up to 51,300 m3 for leakage and 53,730 m3 for pressure-driven demand. [ABSTRACT FROM AUTHOR]

The sustainable management of natural resources under climate change conditions is a critical research issue. Among the many approaches emerged in recent times, the so-called 'nexus approach' is gaining traction in academic and policy circles. The nexus approach presupposes the analysis of bio-physical, socio-economic and policy interlinkages among sectors (e.g., water, energy, food) for the identification of integrated solutions and the support of policy decisions. Ultimately, the nexus approach aims to identify synergies and trade-offs among the nexus dimensions. Concerning policy, the nexus approach focuses on policy coherence, i.e., the systematic identification and management of trade-offs and synergies between policies across sectors. This paper investigates the coherence between policies on the water-land-energy-food-climate nexus in Greece. The systematic analysis of policy documents led to the elicitation of nexus-related policy objectives and instruments. Then, the coherence among objectives and between objectives and instruments was assessed using the methodology proposed by Nilsson et al. A stakeholder (trans-disciplinary) orientation was adopted and the need to incorporate stakeholders' recommendations as to policy coherence assessment was highlighted. Overall, the findings revealed that climate and food/agricultural policies represent critical future priorities in Greece by stimulating progress in other nexus-related policies (energy, water, land policies) and being positively influenced by them. [ABSTRACT FROM AUTHOR]

The concept of the Water–Energy–Food nexus (WEF), as documented by the United Nations Food and Agriculture Organization (FAO), suggests that the three resources are thoroughly interrelated, shaping a complicated web of interlinkages. Perceiving the three commodities as an interdependent variable system, rather than isolated subsystems is a step towards a more holistic approach, and thus a prerequisite to introducing a sustainable scheme for better managing resources. In this work, the well-documented WEF nexus is broadened to a five-dimensional nexus, also involving land use and climate. A methodology for drawing the interrelations among the five dimensions and unreeling the complicated system of direct and indirect interlinkages is given. The intensity of interlinkages among nexus components is initially assessed through a three-point typology with interlinkage scoring corresponding to resource use in Greece. The typology is used and is further expanded to quantify successfully all interlinkages among nexus components with a proposed heuristic algorithm. Results are used to create the cross-interlinkage matrix that identifies food as the most influencing resource and water as the resource mostly influenced by other nexus elements. Results show that indirect interlinkages of multiple resources can be very significant and should not be ignored when planning nexus-coherent policy initiatives and investments in different sectors, in order to promote resource efficiency. [ABSTRACT FROM AUTHOR]

An analysis of virtual crop water export through international trade is conducted for Greece, downscaled to the River Basin District (RBD) level, in order to identify critical “hotspots” of localized water shortage in the country. A computable general equilibrium model (MAGNET) was used to obtain the export shares of crops and associated irrigation water was calculated for all major crops in Greece. A distinction between virtual crop water locally consumed and traded internationally was made for all Greek RBDs. Cotton was identified as a large water consumer and virtual water exporter, while GR08 and GR10 were identified as the RBDs mostly impacted. The value of virtual water exported was calculated for all crop types and fruits and vegetables were identified as the crop most beneficial, since they consume the least water for the obtained value. [ABSTRACT FROM AUTHOR]