Environmental Impacts of Industrial Energy Systems in the Coastal Zone

1978 ◽  
Vol 3 (1) ◽  
pp. 395-475 ◽  
Author(s):  
C A S Hall ◽  
R Howarth ◽  
B Moore ◽  
C J Vorosmarty
2021 ◽  
Author(s):  
Samuel Robinson ◽  
Alona Armstrong

<p>Energy systems around the world are rapidly transitioning towards decentralised and digitalised systems as countries aim to decarbonise their economies. However, broader environmental effects of the upscaling of these smart local energy systems (SLES) beyond reducing carbon emissions remain unclear. Land-use change associated with increased deployment of renewables, new infrastructures required for energy distribution and storage, and resource extraction for emerging energy technologies may have significant environmental impacts, including consequences for ecosystems within and beyond energy system project localities. This has major implications for biodiversity, natural capital stocks and provision of ecosystem services, the importance of which are increasingly recognised in development policy at local to international scales. This study assessed current understanding of the broader environmental impacts and potential co-benefits of SLES through a global Rapid Evidence Assessment of peer-reviewed academic literature, with a critical evaluation and synthesis of existing knowledge of effects of SLES on biodiversity, natural capital and ecosystem services. There was a striking overall lack of evidence of the environmental impacts of SLES. The vast majority of studies identified considered only energy technology CO<sub>2</sub> emissions through simulation modelling; almost no studies made explicit reference to effects on ecosystems. This highlights an urgent need to improve whole system understanding of environmental impacts of SLES, crucial to avoid unintended ecosystem degradation as a result of climate change mitigation. This will also help to identify potential techno-ecological synergies and opportunities for improvement of degraded ecosystems alongside reaching decarbonisation goals.</p>


2021 ◽  
Author(s):  
Carles Ribas Tugores ◽  
Gerald Birngruber ◽  
Jürgen Fluch ◽  
Angelika Swatek ◽  
Gerald Schweiger

2020 ◽  
Vol 110 (01-02) ◽  
pp. 12-17
Author(s):  
Niklas Panten ◽  
Heiko Ranzau ◽  
Thomas Kohne ◽  
Daniel Moog ◽  
Eberhard Abele ◽  
...  

Die optimierte Betriebsweise von industriellen Energiesystemen ist eine Schlüsseltechnologie, um signifikante Kosteneinsparpotenziale durch Steigerung der Energieeffizienz und -flexibilität zu heben. Weil dabei eine Vielzahl dynamischer und stochastischer Einflüsse berücksichtigt werden müssen, spielt die Simulation des Energiesystems eine entscheidende Rolle. Zur Evaluierung unterschiedlicher Betriebsoptimierungsverfahren wird ein simulationsgestütztes Framework vorgestellt, welches bei KI (Künstliche Intelligenz)-Algorithmen unter anderem für das Anlernen mit synthetischen Daten verwendet werden kann.   The optimized operation of industrial energy systems is a key technology to unlock significant cost savings by increasing energy efficiency and flexibility. Since a variety of dynamic and stochastic influences must be considered, the simulation of the energy system plays a decisive role. A simulation-based framework is presented for evaluating various operational optimization methods, which can also be used for learning based on synthetic data with AI (artificial intelligence) algorithms.


Sign in / Sign up

Export Citation Format

Share Document