A guide to SDG interactions: from science to implementation

Nilsson, Mathias; Griggs, Dana M.; McCollum, D.; Stevance, Anne‐Sophie

doi:10.24948/2017.01

Cited by 89 publications

(41 citation statements)

References 88 publications

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“…Effects of climate change are increasingly visible in marine ecosystems worldwide (IPCC, 2014), and one of the largest concerns is maintaining fish populations and their habitats in states sufficiently stable to enable them to sustain a growing human population, as emphasized by the 14th Sustainable Development Goal of UNESCO (Griggs, Nilsson, Stevance, & McCollum, 2017). Although coastal shelf seas represent only ca.…”

Section: Introductionmentioning

confidence: 99%

Environment outweighs the effects of fishing in regulating demersal community structure in an exploited marine ecosystem

Mérillet

Kopp

Robert

et al. 2020

Global Change Biology

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Global climate change has already caused bottom temperatures of coastal marine ecosystems to increase worldwide. These ecosystems face many pressures, of which fishing is one of the most important. While consequences of global warming on commercial species are studied extensively, the importance of the increase in bottom temperature and of variation in fishing effort is more rarely considered together in these exploited ecosystems. Using a 17 year time series from an international bottom trawl survey, we investigated covariations of an entire demersal ecosystem (101 taxa) with the environment in the Celtic Sea. Our results showed that over the past two decades, biotic communities in the Celtic Sea were likely controlled more by environmental variables than fisheries, probably due to its long history of exploitation. At the scale of the entire zone, relations between taxa and the environment remained stable over the years, but at a local scale, in the center of the Celtic Sea, dynamics were probably driven by interannual variation in temperature. Fishing was an important factor structuring species assemblages at the beginning of the time series (2000) but decreased in importance after 2009. This was most likely caused by a change in spatial distribution of fishing effort, following a change in targeted taxa from nephrops to deeper water anglerfish that did not covary with fishing effort. Increasing bottom temperatures could induce additional changes in the coming years, notably in the cold‐water commercial species cod, hake, nephrops, and American plaice. We showed that analyzing covariation is an effective way to screen a large number of taxa and highlight those that may be most susceptible to future simultaneous increases in temperature and changes in exploitation pattern by fisheries. This information can be particularly relevant for ecosystem assessments.

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Section: Introductionmentioning

confidence: 99%

Environment outweighs the effects of fishing in regulating demersal community structure in an exploited marine ecosystem

Mérillet

Kopp

Robert

et al. 2020

Global Change Biology

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“…To further reinforce the fact that this goal needs to be considered in systems modelling it should be noted that this goal is the most inter-connected goal of all 17 as identified by the International Council for Science [17],…”

Section: Figure 1: the Sustainable Development Goalsmentioning

confidence: 99%

“…In some cases, although it may not be directly possible to incorporate aspects of a goal into a systems model, the goal highlights principles that should be followed in developing models. Following on the work of the International Science Council [17], van Soest et al [18] and Pradhan et al [19], we also attempt to identify linkages and feedbacks between the SDGs that may need to be considered when modelling, but we do not repeat this work of identifying linkages between the different goals. Table 2 provides a summary of the ranking for each SDG in each category to summarize the overall discussion.…”

Section: Figure 1: the Sustainable Development Goalsmentioning

confidence: 99%

“…Although there is significant scope for including health and well-being impacts in systems modelling frameworks, Access to clean water and sanitation is both an important goal in and of itself and is identified as linked to goal 2, no poverty, and goal 7, affordable and clean energy by the International Council for Science [17]. This goal requires identifying available water sources in a country, identifying competing demands for said water sources, identifying the energy and other services required to provide clean water, and many other interactions.…”

Section: Figure 1: the Sustainable Development Goalsmentioning

confidence: 99%

“…The International Council for Science [17] connects this goal to goal 7, affordable and clean energy, goal 3, good health and well being, and goal 14, life below water. The linkages to affordable energy and good health are clear; this goal might be better addressed by incorporating aspects of those goals into the modelling framework.…”

Section: Figure 1: the Sustainable Development Goalsmentioning

confidence: 99%

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Embedding the United Nations Sustainable Development Goals into Systems Analysis – Expanding the Food-Energy-Water Nexus

Niet

Arianpoo

Kuling

et al. 2020

Preprint

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Background: There have been many studies that consider the nexus interactions between energy systems, land use, water use and climate adaptation and impacts. These studies have filled a gap in the literature to allow for more effective policymaking by considering the trade-offs between land use, energy infrastructure as well as the use of water for agriculture and providing energy services. Though these studies fill a significant gap in the modelling literature, we argue that more work is needed to effectively consider policy trade-offs between the 17 United Nations Sustainable Development Goals (SDGs) to avoid missing important interactions.Results: We examine the 17 SDGs to determine if it should be included in a modelling framework and the challenges of doing so. We show that the nexus of climate, land, energy and water needs to be expanded to consider economic well-being of both individuals and the greater economy, health benefits and impacts, as well as land use in terms of both food production and in terms of sustaining ecological diversity and natural capital. Such an expansion will allow systems models to better address the trade-offs and synergies inherent in the SDGs. Luckily, although there are some challenges with expanding the nexus in this way, we feel the challenges are generally modest and that many model structures can already incorporate many of these factors without significant modification.Finally, we argue that SDGs 16 and 17 cannot be met without open-source models and open data to allow for transparent analysis that can be used and reused with a low cost of entry for modellers from less well off nations.Conclusions: To effectively address the SDGs there is a need to expand the common definition of the nexus of climate, land, energy, and water to include the synergies and trade-offs of health impacts, ecological diversity and the system requirements for human and environmental well-being. In most cases, expanding models to be able to incorporate these factors will be relatively straight forward, but open models and analysis are needed to fully support the SDGs.

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HVAC Optimization Genetic Algorithm for Industrial Near‐Zero Energy Building Demand Response

Kampelis¹,

Sifakis²,

Kolokotsa³

et al. 2021

Smart Buildings, Smart Communities and Demand Response

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Demand response offers the possibility of altering the profile of power consumption of individual buildings or building districts, i.e., microgrids, for economic return. There is significant potential of demand response in enabling flexibility via advanced grid management options, allowing higher renewable energy penetration and efficient exploitation of resources. Demand response and distributed energy resource dynamic management are gradually gaining importance as valuable assets for managing peak loads, grid balance, renewable energy source intermittency, and energy losses. In this paper, the potential for operational optimization of a heating, ventilation, and air conditioning (HVAC) system in a smart near-zero-energy industrial building is investigated with the aid of a genetic algorithm. The analysis involves a validated building energy model, a model of energy cost, and an optimization model for establishing HVAC optimum temperature set points. Optimization aims at establishing the trade-off between the minimum daily cost of energy and thermal comfort. Predicted mean vote is integrated in the objective function to ensure thermal comfort requirements are met.

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A guide to SDG interactions: from science to implementation

Cited by 89 publications

References 88 publications

Environment outweighs the effects of fishing in regulating demersal community structure in an exploited marine ecosystem

Environment outweighs the effects of fishing in regulating demersal community structure in an exploited marine ecosystem

Embedding the United Nations Sustainable Development Goals into Systems Analysis – Expanding the Food-Energy-Water Nexus

HVAC Optimization Genetic Algorithm for Industrial Near‐Zero Energy Building Demand Response

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