Lebanon’s economic crisis has disrupted the country’s energy and water sectors, highlighting their interdependence. The methodologyinvolves surveying 150 municipalities across all Lebanese governorates, ensuring a comprehensive coverage of public and private waterresources. Data on water and energy were collected before and during the crisis to explore this nexus during periods of economic turmoil.The findings reveal a decline in water provision during the crisis, with the average weekly water supply plummeting from 49 h in 2019 to 22 hin 2023. Concurrently, the use of water tankers has surged from 26 to 44%, indicating a concerning shift in water acquisition methods.Despite the crisis, conventional water sources remain predominant, while unconventional sources account for less than 1% of the totalsupply. In response to the energy shortage, renewable energy sources have gained traction in residential, commercial, and industrial sectors.The scarcity and rising cost of electricity have driven the adoption of solar photovoltaics in the water sector, reaching 4.8% for extraction fromunderground reservoirs and 2.8% for distribution. Similarly, the use of solar water heaters has increased from 7.9 to 15.4% in 2023. Thesefindings underscore the interplay between energy and water security during periods of economic instability.
DOCUMENT
Urban communities are particularly vulnerable to the future demand for food, energy and water, and this vulnerability is further exacerbated by the onset of climate change at local. Solutions need to be found in urban spaces. This article based around urban design practice sees urban agriculture as a key facilitator of nexus thinking, needing water and energy to be productive. Working directly with Urban Living Labs, the project team will co-design new food futures through the moveable nexus, a participatory design support platform to mobilize natural and social resources by integrating multi-disciplinary knowledge and technology. The moveable nexus is co-developed incrementally through a series of design workshops moving around living labs with the engagement of stakeholders. The methodology and the platform will be shared outside the teams so that the knowledge can be mobilized locally and globally.
DOCUMENT
The importance of water and energy accessibility and use has become more important as new insight into their role for sustainable development goals has become mainstream. The inclusion of water and energy in strategic decision-making is thus key. Supply chain network design (SCND) in the food industry is an interesting case study for the incorporation of water and energy utilization during the design process of global production systems. In the current green SCND research, frequently, single indicators are used such as carbon emissions to measure environmental impact. This paper presents a case study applied to an orange juice supply chain, formulated as a multi-objective optimization model. A single environmental impact indicator optimization approach is paired against one that includes water and energy use explicitly in the objective function set. Mixed conclusions are shown from the results pairing the two strategies side by side.
DOCUMENT
We summarize what we assess as the past year's most important findings within climate change research: limits to adaptation, vulnerability hotspots, new threats coming from the climate–health nexus, climate (im)mobility and security, sustainable practices for land use and finance, losses and damages, inclusive societal climate decisions and ways to overcome structural barriers to accelerate mitigation and limit global warming to below 2°C.
MULTIFILE
The design of cities has long ignored the flows that shape the city. Water has been the most visible one, but energy and materials were invisible and/or taken for granted. A little over 50 years ago, Abel Wolman was the first to illuminate the role of water flows in the urban fabric. It has long been a search for quantitative data while the flows were mostly seen as separated entities. The fact they invisibly formed the way the city appears has been neglected for many years. In this thematic issue the “city of flows” is seen as a design task. It aims to bring to the fore the role flows can play to be consciously used to make spatial decisions in how and where certain uses and infrastructure is located. Efficient and sustainable
DOCUMENT
The built environment requires energy-flexible buildings to reduce energy peak loads and to maximize the use of (decentralized) renewable energy sources. The challenge is to arrive at smart control strategies that respond to the increasing variations in both the energy demand as well as the variable energy supply. This enables grid integration in existing energy networks with limited capacity and maximises use of decentralized sustainable generation. Buildings can play a key role in the optimization of the grid capacity by applying demand-side management control. To adjust the grid energy demand profile of a building without compromising the user requirements, the building should acquire some energy flexibility capacity. The main ambition of the Brains for Buildings Work Package 2 is to develop smart control strategies that use the operational flexibility of non-residential buildings to minimize energy costs, reduce emissions and avoid spikes in power network load, without compromising comfort levels. To realise this ambition the following key components will be developed within the B4B WP2: (A) Development of open-source HVAC and electric services models, (B) development of energy demand prediction models and (C) development of flexibility management control models. This report describes the developed first two key components, (A) and (B). This report presents different prediction models covering various building components. The models are from three different types: white box models, grey-box models, and black-box models. Each model developed is presented in a different chapter. The chapters start with the goal of the prediction model, followed by the description of the model and the results obtained when applied to a case study. The models developed are two approaches based on white box models (1) White box models based on Modelica libraries for energy prediction of a building and its components and (2) Hybrid predictive digital twin based on white box building models to predict the dynamic energy response of the building and its components. (3) Using CO₂ monitoring data to derive either ventilation flow rate or occupancy. (4) Prediction of the heating demand of a building. (5) Feedforward neural network model to predict the building energy usage and its uncertainty. (6) Prediction of PV solar production. The first model aims to predict the energy use and energy production pattern of different building configurations with open-source software, OpenModelica, and open-source libraries, IBPSA libraries. The white-box model simulation results are used to produce design and control advice for increasing the building energy flexibility. The use of the libraries for making a model has first been tested in a simple residential unit, and now is being tested in a non-residential unit, the Haagse Hogeschool building. The lessons learned show that it is possible to model a building by making use of a combination of libraries, however the development of the model is very time consuming. The test also highlighted the need for defining standard scenarios to test the energy flexibility and the need for a practical visualization if the simulation results are to be used to give advice about potential increase of the energy flexibility. The goal of the hybrid model, which is based on a white based model for the building and systems and a data driven model for user behaviour, is to predict the energy demand and energy supply of a building. The model's application focuses on the use case of the TNO building at Stieltjesweg in Delft during a summer period, with a specific emphasis on cooling demand. Preliminary analysis shows that the monitoring results of the building behaviour is in line with the simulation results. Currently, development is in progress to improve the model predictions by including the solar shading from surrounding buildings, models of automatic shading devices, and model calibration including the energy use of the chiller. The goal of the third model is to derive recent and current ventilation flow rate over time based on monitoring data on CO₂ concentration and occupancy, as well as deriving recent and current occupancy over time, based on monitoring data on CO₂ concentration and ventilation flow rate. The grey-box model used is based on the GEKKO python tool. The model was tested with the data of 6 Windesheim University of Applied Sciences office rooms. The model had low precision deriving the ventilation flow rate, especially at low CO2 concentration rates. The model had a good precision deriving occupancy from CO₂ concentration and ventilation flow rate. Further research is needed to determine if these findings apply in different situations, such as meeting spaces and classrooms. The goal of the fourth chapter is to compare the working of a simplified white box model and black-box model to predict the heating energy use of a building. The aim is to integrate these prediction models in the energy management system of SME buildings. The two models have been tested with data from a residential unit since at the time of the analysis the data of a SME building was not available. The prediction models developed have a low accuracy and in their current form cannot be integrated in an energy management system. In general, black-box model prediction obtained a higher accuracy than the white box model. The goal of the fifth model is to predict the energy use in a building using a black-box model and measure the uncertainty in the prediction. The black-box model is based on a feed-forward neural network. The model has been tested with the data of two buildings: educational and commercial buildings. The strength of the model is in the ensemble prediction and the realization that uncertainty is intrinsically present in the data as an absolute deviation. Using a rolling window technique, the model can predict energy use and uncertainty, incorporating possible building-use changes. The testing in two different cases demonstrates the applicability of the model for different types of buildings. The goal of the sixth and last model developed is to predict the energy production of PV panels in a building with the use of a black-box model. The choice for developing the model of the PV panels is based on the analysis of the main contributors of the peak energy demand and peak energy delivery in the case of the DWA office building. On a fault free test set, the model meets the requirements for a calibrated model according to the FEMP and ASHRAE criteria for the error metrics. According to the IPMVP criteria the model should be improved further. The results of the performance metrics agree in range with values as found in literature. For accurate peak prediction a year of training data is recommended in the given approach without lagged variables. This report presents the results and lessons learned from implementing white-box, grey-box and black-box models to predict energy use and energy production of buildings or of variables directly related to them. Each of the models has its advantages and disadvantages. Further research in this line is needed to develop the potential of this approach.
DOCUMENT
We need mental and physical reference points. We need physical reference points such as signposts to show us which way to go, for example to the airport or the hospital, and we need reference points to show us where we are. Why? If you don’t know where you are, it’s quite a difficult job to find your way, thus landmarks and “lieux de memoire” play an important role in our lives.
LINK
Het tekort aan handjes in de accountancy neemt toe. Tegelijk groeit de maatschappelijk druk om bedrijven zo goed mogelijk te controleren, om te zorgen dat ze financieel, fiscaal en qua duurzaamheid in de pas blijven lopen met de (toenemende) regelgeving. Gelukkig komt er steeds meer technologie voorhanden die de accountant kan helpen bij het controleren van de boeken, schetst Eric Mantelaers, hoofd Bureau Vaktechniek, RSM Accountants. Medio juni is hij aan de Open Universiteit gepromoveerd op zijn proefschrift ‘An evaluation of technologies to improve auditing’.
LINK
Adopted on the fifteenth anniversary of resolution 1325, Security Council resolution 2242 has recognized for the first time the substantial link between climate change and the “Women, Peace and Security” (WPS) framework. Despite this landmark resolution, the intersections of environmental factors, conflict and violence against women remain largely absent from the Security Council's WPS agenda. Competition over natural resources is generally understood as a driver of conflict. The risk of insecurity and conflict are further increased by environmental degradation and climate change. It is therefore clear that the environment and natural resources must be integrated into the WPS agenda. This should necessarily include a discussion of indigenous rights to land and the gender-related dimensions of environmental factors. Indigenous women are disproportionately affected by environmental degradation, caused by resource extraction and increasingly compounded by climatic changes. This in turn exacerbates other vulnerabilities, including sexual and gender-based violence and other forms of marginalization. This article argues, by reference to the situation in West Papua, that unfettered resource extraction not only amplifies vulnerabilities and exacerbates preexisting inequalities stemming from colonial times, it also gives rise to gendered consequences flowing from the damage wreaked on the natural environment and thus poses a danger to international peace and security. As such, the Security Council's failure to recognize the continuous struggle of women in indigenous and rural communities against extractive economies and climate change impact as a security risk forms a serious lacuna within its WPS agenda. Originally published by Oxford University Press in Global Studies Quarterly, Volume 1, Issue 3, September 2021, ksab018, https://doi.org/10.1093/isagsq/ksab018
MULTIFILE
Two key air pollutants that affect asthma are ozone and particle pollution. Studies show a direct relationship between the number of deaths and hospitalizations for asthma and increases of particulate matter in the air, including dust, soot, fly ash, diesel exhaust particles, smoke, and sulfate aerosols. Cars are found to be a primary contributor to this problem. However, patient awareness of the link is limited. This chapter begins with a general discussion of vehicular dependency or ‘car culture’, and then focuses on the discussion of the effects of air pollution on asthma in the Netherlands. I argue that international organizations and patient organizations have not tended to put pressure on air-control, pollution-control or environmental standards agencies, or the actual polluters. While changes in air quality and the release of greenhouse gases are tied to practices like the massive corporate support for the ongoing use of motor vehicles and the increased prominence of ‘car culture’ globally, patient organizations seem more focused on treating the symptoms rather than addressing the ultimate causes of the disease. Consequently, I argue that to fully address the issue of asthma the international health organizations as well as national health ministries, patient organizations, and the general public must recognize the direct link between vehicular dependency and asthma. The chapter concludes with a recommendation for raising environmental health awareness by explicitly linking the vehicular dependency to the state of poor respiratory health. Strategic policy in the Netherlands then should explicitly link the present pattern of auto mobility to public health. https://onlinelibrary.wiley.com/doi/book/10.1002/9781118786949 LinkedIn: https://www.linkedin.com/in/helenkopnina/
MULTIFILE
