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The EU has set the ambitious target of raising the share of EU energy consumption produced from renewable resources to 32% by 2030, with a target of climate neutrality by 2050. The aim of this paper is to assess the role of biomass usage in the context of these targets. The paper identifies the progress made between 2013 and 2022 by focusing on a selection of EU countries. The largest bioenergy increments of 130, 77, and 60 PJ were reported for Poland, Sweden, and the Netherlands. This study evaluates the crucial role of co-generation and heat in EU regions, with biomass usage between 55 and 80% of the combined heat and power (CHP) energy in Nordic countries. The future perspectives for bioenergy based on EU policies, biomass resources, and technical issues were addressed. The EU possesses around 9% of the global biomass supply, ensuring a certain level of biomass resource dependence. Thus, the biomass usage demand in energy production, non-energy sectors, and transport is expected to rise, leading to increments of 13–76% on biomass imports. It appears that bioenergy development is mostly limited by economic issues and uneven support for bioenergy in different EU countries as well as environmental issues. The study shows a promising and sustainable potential of bioenergy in the EU as a renewable energy source while minimizing negative impacts on the environment and the economy. By 2050, liquid biofuels are likely to be increasingly used in the transport sector. Non-energy sector usage of biomass is still in an early stage of development, except for the pulp and paper industry, and significant use of biomass in non-energy sectors seems unlikely in the near future. [ABSTRACT FROM AUTHOR]

Background: The transition to carbon neutral mobility will require a lot of carbon neutral energy, but a lot of space as well. In many countries, it will be a challenge to find this space or to import enough energy. Land use indicators related to sustainable mobility usually focus on space for transport infrastructure and parking, i.e. direct land use, and do not include energy supply. Existing literature on the emerging research field of 'energy landscapes' has not covered the transport sector. Objective: The aim of this paper is to estimate the order of magnitude of land or sea area required for carbon neutral mobility. Method: In a well-to-wheel analysis, we investigate the land use for the production, transport, storage, distribution, and charging/refuelling of carbon neutral energy carriers for various modes of transport. The analysis focuses on the Netherlands, but part of the results are expected to be broadly applicable to other countries as well. Findings: The results show that electricity from wind or solar energy supplied to electric vehicles is the most space efficient. Use of hydrogen and synthetic fuels in vehicles takes 2–5 times more land, while use of biofuels from energy crops takes 100 times more land compared to the electricity route. We also conclude that the indirect land use for energy supply for carbon neutral road transport in the Netherlands is in the same order of magnitude as the current direct land use of road mobility. [ABSTRACT FROM AUTHOR]

This paper investigates the design of policy packages to enable carbon neutrality in the manufacturing sector by 2050, based on the case of the Netherlands. It first models potential pathways to net-zero emissions by 2050 in the Dutch manufacturing sector, and then evaluates the current policy framework's ability to catalyse the transition. The analysis shows that the Netherlands' credible commitment to raising carbon prices combined with ambitious technology support provides strong incentives for manufacturing to significantly decarbonise. However, even if the carbon levy sets an ambitious price trajectory to 2030, it is tempered by extensive preferential treatment to energy-intensive users, yielding a highly unequal carbon price across firms and sectors. Moreover, the country's technology support focuses on the cost-effective deployment of low-carbon options, which ensures least-cost decarbonisation in the short run but favours relatively mature technologies. The paper offers recommendations for policy adjustments to reach the country's carbon neutrality objective, including the gradual removal of exemptions, enhanced support for emerging technologies and greater visibility over future infrastructure plans. Other countries can learn from the Dutch experience when designing their own decarbonisation strategy for the manufacturing sector. • The Dutch policy package provides strong incentives for manufacturing to decarbonise. • Carbon pricing exemptions for energy-intensive users increase abatement costs. • Technology support favours short-term efficiency over long-term deep decarbonisation. • Dutch transition hinges on regulatory certainty and swift infrastructure deployment. • The Dutch case offers insights for other countries to design net-zero strategies. [ABSTRACT FROM AUTHOR]

[Display omitted] • High resolution data from a Dutch net zero energy neighborhood is analysed. • Most buildings are positive energy, emit less carbon than they offset. • Large occupant differences in energy demand are visible across the households. • Occupant preferences and weather conditions greatly influence thermal energy demand. • Due to the high thermal efficiency, there is a high risk for summer overheating. Decarbonizing the building stock is a central component of global climate change mitigation efforts. In practice, this decarbonization can be achieved by a variety of different measures, including improvements in building energy efficiency, electrification of energy demand to reduce reliance on fossil fuels, and installation of distributed (renewable) generation in conjunction with flexible storage. However, these large-scale, often disruptive changes to the built environment also raise a number of concerns, such as loss of occupant comfort exacerbated by climate change, and introduction of additional stressors on the distribution grid. In this paper, we demonstrate several conclusions using detailed sub-hourly data of two years (2019–2020) collected from 40 homes in a recently refurbished net-zero energy neighborhood in the Netherlands. This paper shows that, in renovation projects like the case study, net-zero energy balances should be considered on a neighborhood, rather than building level to minimize worst case planning by accounting for occupant influences and seasonal effects. Furthermore, the energy flexibility and climate resilience in the buildings seems to be rather limited, as a result of energy efficiency improvements. While helpful in climate change mitigation efforts, the large seasonal differences in energy demand and generation imply that this evolution is perhaps sub-optimal from the grid perspective. The results illustrate that all homes in the study were net-zero energy over the two year period, sometimes net positive by up to a factor of three. This led to considerable excess generation especially during the summer months. In addition, it was found that indoor air temperature sensors in a number of buildings showed overheating beyond guideline thermal comfort temperature of 25°C, showing potential thermal comfort and heat stress for vulnerable occupants. These results motivate energy storage or modifications of the installed heat pumps to leverage summer excess generation while reducing the impact of summer heat waves. These findings should enable the Netherlands and other countries aiming to fully decarbonize the building stock formulate better, future-proof policies. [ABSTRACT FROM AUTHOR]

With worldwide activities of carbon neutrality, clean energy is playing an important role these days. Natural gas (NG) is one of the most efficient clean energies with less harmful emissions and abundant reservoirs. This work aims at developing a swarm intelligence-based tool for NG forecasting to make more convincing projections of future energy consumption, combining Extreme Gradient Boosting (XGBoost) and the Salp Swarm Algorithm (SSA). The XGBoost is used as the core model in a nonlinear auto-regression procedure to make multi-step ahead forecasting. A cross-validation scheme is adopted to build a nonlinear programming problem for optimizing the most sensitive hyperparameters of the XGBoost, and then the nonlinear optimization is solved by the SSA. Case studies of forecasting the Natural gas consumption (NGC) in the United Kingdom (UK) and Netherlands are presented to illustrate the performance of the proposed hybrid model in comparison with five other intelligence optimization algorithms and two other decision tree-based models (15 hybrid schemes in total) in 6 subcases with different forecasting steps and time lags. The results show that the SSA outperforms the other 5 algorithms in searching the optimal parameters of XGBoost and the hybrid model outperforms all the other 15 hybrid models in all the subcases with average MAPE 4.9828% in NGC forecasting of UK and 9.0547% in NGC forecasting of Netherlands, respectively. Detailed analysis of the performance and properties of the proposed model is also summarized in this work, which indicates it has high potential in NGC forecasting and can be expected to be used in a wider range of applications in the future. [ABSTRACT FROM AUTHOR]