• Energy Research
• 2021-2025close
• Open Access close
• Closed Access close
• NL close

AbstractElevated CO2 concentration has been reported to decrease grain nutrient concentrations and thus worsen nutritional deficiency and hidden hunger. One nutritional aspect is mineral content, yet mineral bioavailability can be limited by the presence of phytic acid. Given that future climate scenarios predict elevated global temperature driven by elevated atmospheric CO2 concentrations, we used Temperature by Free‐Air CO2 Enrichment (T‐FACE) field experiments to investigate whether elevated temperature alters the effects of elevated CO2 on grain mineral concentrations, grain mineral yields, and their bioavailability in a range of wheat and rice genotypes. We found that the negative effects of elevated CO2 were compensated for by positive effects of elevated temperature. As a result, the combined elevated CO2 and elevated temperature increased concentrations of some minerals by up to ~15% in both rice and wheat relative to control conditions. Moreover, the combined elevated CO2 and elevated temperature did not significantly change total yields of some minerals despite lower grain yields. The combined CO2 and temperature elevation increased phytic acid concentration in rice by 18.1% but decreased it in wheat by 3.5%. The mineral bioavailability, estimated as the mole ratio of phytic acid to minerals in rice and wheat grains, was limited by the combined CO2 and temperature elevation in only a few cases. Our results indicate that under future climate conditions of elevated temperature and CO2, the nutritional quality of rice and wheat with respect to minerals may remain unchanged.

This deliverable includes the methodology in EnergyPROSPECTS for an in-depth study of energy citizenship. It features the criteria used for selecting the cases for indepth study, the list of cases selected for in-depth study as well as key research foci and empirical research questions.

This paper develops a data-driven model for assessing the availability of flexibility from individual household devices, at house level. The model predicts the potential shift, increase or decrease of the energy consumption of a particular type of device at a given time, in response to a price signal, and for each house separately. Therefore, the location of the flexibility source is known with accuracy. The model has an Auto-Encoder architecture based on Convolution Neural Network. The augmented model demonstrates good performance in terms of predicting the time-shift in load.

Owing to the complexity of the sector, industrial activities are often represented with limited technological resolution in integrated energy system models. In this study, we enriched the technological description of industrial activities in the integrated energy system analysis optimisation (IESA-Opt) model, a peer-reviewed energy system optimisation model that can simultaneously provide optimal capacity planning for the hourly operation of all integrated sectors. We used this enriched model to analyse the industrial decarbonisation of the Netherlands for four key activities: high-value chemicals, hydrocarbons, ammonia, and steel production. The analyses performed comprised 1) exploring optimality in a reference scenario; 2) exploring the feasibility and implications of four extreme industrial cases with different technological archetypes, namely a bio-based industry, a hydrogen-based industry, a fully electrified industry, and retrofitting of current assets into carbon capture utilisation and storage; and 3) performing sensitivity analyses on key topics such as imported biomass, hydrogen, and natural gas prices, carbon storage potentials, technological learning, and the demand for olefins. The results of this study show that it is feasible for the energy system to have a fully bio-based, hydrogen-based, fully electrified, and retrofitted industry to achieve full decarbonisation while allowing for an optimal technological mix to yield at least a 10% cheaper transition. We also show that owing to the high predominance of the fuel component in the levelled cost of industrial products, substantial reductions in overnight investment costs of green technologies have a limited effect on their adoption. Finally, we reveal that based on the current (2022) energy prices, the energy transition is cost-effective, and fossil fuels can be fully displaced from industry and the national mix by 2050.

Abstract Developing countries are growing apart on environmental issues. International environmental negotiations are no longer characterized merely by the North–South conflict. Rising powers have come to divide the Global South and redefine the Common-But-Differentiated Responsibilities principle. This article explains the divergence of China and India at the Kigali Amendment to the Montreal Protocol, one of the first global environmental agreements to differentiate obligations between developing countries. China and India, the world’s two largest hydrofluorocarbon producers, ended decades of collaboration and split the rest of the developing world behind them. I argue that developmental strategy and political institutions shape the preferences and influences of industrial, governmental, and social stakeholders, thereby explaining their negotiation behavior and outcome. This article explains why China moved faster and further than India on negotiations for hydrofluorocarbon regulation. It has important implications for the two rising powers’ implementation of the Kigali Amendment and for their position formulations on other environmental issues.

AbstractDeriving active pharmaceutical agents from renewable resources is crucial to increasing the economic feasibility of modern biorefineries and promises to alleviate critical supply‐chain dependencies in pharma manufacturing. Our multidisciplinary approach combines research in lignin‐first biorefining, sustainable catalysis, and alternative solvents with bioactivity screening, an in vivo efficacy study, and a structural‐similarity search. The resulting sustainable path to novel anti‐infective, anti‐inflammatory, and anticancer molecules enabled the rapid identification of frontrunners for key therapeutic indications, including an anti‐infective against the priority pathogen Streptococcus pneumoniae with efficacy in vivo and promising plasma and metabolic stability. Our catalytic methods provided straightforward access, inspired by the innate structural features of lignin, to synthetically challenging biologically active molecules with the core structure of dopamine, namely, tetrahydroisoquinolines, quinazolinones, 3‐arylindoles and the natural product tetrahydropapaveroline. Our diverse array of atom‐economic transformations produces only harmless side products and uses benign reaction media, such as tunable deep eutectic solvents for modulating reactivity in challenging cyclization steps.

In view of the growing shares of renewables in the electricity grid in combination with the electrification of hvac (heating, ventilation, air conditioning) systems in residential buildings, the grid intensity (in terms of carbon dioxide emissions per unit of electric energy) becomes increasingly sensitive to weather conditions, and synchronicity between weather and the grid becomes a more critical aspect in building performance assessment. Using building performance simulation techniques to seek robust building designs requires awareness about the uncertainties in circumstantial factors that affect performance. This 2016 – 2022 retrospective study highlights the effects of using low or high temporal resolution grid emissions intensity data on projected operation-induced carbon dioxide emissions for a terraced dwelling in the Netherlands. Building fabric quality, the occupant profile, and systems configurations (i.e., hvac and photovoltaics) are varied to investigate the effects of the applied grid model resolution. This study shows that ignoring high-resolution grid intensity data is getting increasingly problematic; applying low resolution (annual) instead of high-resolution (15-minute) grid intensity data leads to an increasingly unjustified optimistic assessment both for net and gross emissions (either or not allowing for carbon displacement by feeding locally generated electricity into the grid).