Showing papers by "Wageningen University and Research Centre published in 2022"

Global Carbon Budget 2021

Abstract: Abstract. Accurate assessment of anthropogenic carbon dioxide (CO2) emissions and their redistribution among the atmosphere, ocean, and terrestrial biosphere in a changing climate is critical to better understand the global carbon cycle, support the development of climate policies, and project future climate change. Here we describe and synthesize datasets and methodology to quantify the five major components of the global carbon budget and their uncertainties. Fossil CO2 emissions (EFOS) are based on energy statistics and cement production data, while emissions from land-use change (ELUC), mainly deforestation, are based on land use and land-use change data and bookkeeping models. Atmospheric CO2 concentration is measured directly, and its growth rate (GATM) is computed from the annual changes in concentration. The ocean CO2 sink (SOCEAN) is estimated with global ocean biogeochemistry models and observation-based data products. The terrestrial CO2 sink (SLAND) is estimated with dynamic global vegetation models. The resulting carbon budget imbalance (BIM), the difference between the estimated total emissions and the estimated changes in the atmosphere, ocean, and terrestrial biosphere, is a measure of imperfect data and understanding of the contemporary carbon cycle. All uncertainties are reported as ±1σ. For the first time, an approach is shown to reconcile the difference in our ELUC estimate with the one from national greenhouse gas inventories, supporting the assessment of collective countries' climate progress. For the year 2020, EFOS declined by 5.4 % relative to 2019, with fossil emissions at 9.5 ± 0.5 GtC yr−1 (9.3 ± 0.5 GtC yr−1 when the cement carbonation sink is included), and ELUC was 0.9 ± 0.7 GtC yr−1, for a total anthropogenic CO2 emission of 10.2 ± 0.8 GtC yr−1 (37.4 ± 2.9 GtCO2). Also, for 2020, GATM was 5.0 ± 0.2 GtC yr−1 (2.4 ± 0.1 ppm yr−1), SOCEAN was 3.0 ± 0.4 GtC yr−1, and SLAND was 2.9 ± 1 GtC yr−1, with a BIM of −0.8 GtC yr−1. The global atmospheric CO2 concentration averaged over 2020 reached 412.45 ± 0.1 ppm. Preliminary data for 2021 suggest a rebound in EFOS relative to 2020 of +4.8 % (4.2 % to 5.4 %) globally. Overall, the mean and trend in the components of the global carbon budget are consistently estimated over the period 1959–2020, but discrepancies of up to 1 GtC yr−1 persist for the representation of annual to semi-decadal variability in CO2 fluxes. Comparison of estimates from multiple approaches and observations shows (1) a persistent large uncertainty in the estimate of land-use changes emissions, (2) a low agreement between the different methods on the magnitude of the land CO2 flux in the northern extra-tropics, and (3) a discrepancy between the different methods on the strength of the ocean sink over the last decade. This living data update documents changes in the methods and datasets used in this new global carbon budget and the progress in understanding of the global carbon cycle compared with previous publications of this dataset (Friedlingstein et al., 2020, 2019; Le Quéré et al., 2018b, a, 2016, 2015b, a, 2014, 2013). The data presented in this work are available at https://doi.org/10.18160/gcp-2021 (Friedlingstein et al., 2021).

Global Carbon Budget 2022

Abstract: Abstract. Accurate assessment of anthropogenic carbon dioxide (CO2) emissions and their redistribution among the atmosphere, ocean, and terrestrial biosphere in a changing climate is critical to better understand the global carbon cycle, support the development of climate policies, and project future climate change. Here we describe and synthesize data sets and methodologies to quantify the five major components of the global carbon budget and their uncertainties. Fossil CO2 emissions (EFOS) are based on energy statistics and cement production data, while emissions from land-use change (ELUC), mainly deforestation, are based on land use and land-use change data and bookkeeping models. Atmospheric CO2 concentration is measured directly, and its growth rate (GATM) is computed from the annual changes in concentration. The ocean CO2 sink (SOCEAN) is estimated with global ocean biogeochemistry models and observation-based data products. The terrestrial CO2 sink (SLAND) is estimated with dynamic global vegetation models. The resulting carbon budget imbalance (BIM), the difference between the estimated total emissions and the estimated changes in the atmosphere, ocean, and terrestrial biosphere, is a measure of imperfect data and understanding of the contemporary carbon cycle. All uncertainties are reported as ±1σ. For the year 2021, EFOS increased by 5.1 % relative to 2020, with fossil emissions at 10.1 ± 0.5 GtC yr−1 (9.9 ± 0.5 GtC yr−1 when the cement carbonation sink is included), and ELUC was 1.1 ± 0.7 GtC yr−1, for a total anthropogenic CO2 emission (including the cement carbonation sink) of 10.9 ± 0.8 GtC yr−1 (40.0 ± 2.9 GtCO2). Also, for 2021, GATM was 5.2 ± 0.2 GtC yr−1 (2.5 ± 0.1 ppm yr−1), SOCEAN was 2.9 ± 0.4 GtC yr−1, and SLAND was 3.5 ± 0.9 GtC yr−1, with a BIM of −0.6 GtC yr−1 (i.e. the total estimated sources were too low or sinks were too high). The global atmospheric CO2 concentration averaged over 2021 reached 414.71 ± 0.1 ppm. Preliminary data for 2022 suggest an increase in EFOS relative to 2021 of +1.0 % (0.1 % to 1.9 %) globally and atmospheric CO2 concentration reaching 417.2 ppm, more than 50 % above pre-industrial levels (around 278 ppm). Overall, the mean and trend in the components of the global carbon budget are consistently estimated over the period 1959–2021, but discrepancies of up to 1 GtC yr−1 persist for the representation of annual to semi-decadal variability in CO2 fluxes. Comparison of estimates from multiple approaches and observations shows (1) a persistent large uncertainty in the estimate of land-use change emissions, (2) a low agreement between the different methods on the magnitude of the land CO2 flux in the northern extratropics, and (3) a discrepancy between the different methods on the strength of the ocean sink over the last decade. This living data update documents changes in the methods and data sets used in this new global carbon budget and the progress in understanding of the global carbon cycle compared with previous publications of this data set. The data presented in this work are available at https://doi.org/10.18160/GCP-2022 (Friedlingstein et al., 2022b).

Blockchain-Based Fully Peer-to-Peer Energy Trading Strategies for Residential Energy Systems

Abstract: This paper proposes two novel strategies for determining the bilateral trading preferences of households participating in a fully Peer-to-Peer (P2P) local energy market. The first strategy matches between surplus power supply and demand of participants, while the second is based on the distance between them in the network. The impact of bilateral trading preferences on the price and amount of energy traded is assessed for the two strategies. A decentralized fully P2P energy trading market is developed to generate the results in a day-ahead setting. After that, a permissioned blockchain-smart contract platform is used for the implementation of the decentralized P2P trading market on a digital platform. Actual data from a residential neighborhood in the Netherlands, with different varieties of distributed energy resources, is used for the simulations. Results show that in the two strategies, the energy procurement cost and grid interaction of all participants in P2P trading are reduced compared to a baseline scenario. The total amount of P2P energy traded is found to be higher when the trading preferences are based on distance, which could also be considered as a proxy for energy efficiency in the network by encouraging P2P trading among nearby households. However, the P2P trading prices in this strategy are found to be lower. Further, a comparison is made between two scenarios: with and without electric heating in households. Although the electrification of heating reduces the total amount of P2P energy trading, its impact on the trading prices is found to be limited.

Preserving Privacy of Smart Meter Data in a Smart Grid Environment

Abstract: The use of data from residential smart meters can help in the management and control of distribution grids. This provides significant benefits to electricity retailers as well as distribution system operators but raises important questions related to the privacy of consumers' information. In this article, an innovative differential privacy (DP) compliant algorithm is developed to ensure that the data from consumer's smart meters are protected. The effects of this novel algorithm on the operation of the distribution grid are thoroughly investigated not only from a consumer's electricity bill point of view but also from a power systems point of view. This method allows for an empirical investigation into the losses, power quality issues, and extra costs that such a privacy-preserving mechanism may introduce to the system. In addition, severalcost allocation mechanisms based on the cooperative game theory are used to ensure that the extra costs are divided among the participants in a fair, efficient, and equitable manner. Overall, the comprehensive results show that the approach provides privacy preservation in line with the consumer's preferences and does not lead to significant cost or loss increases for the energy retailer. In addition, the novel algorithm is computationally efficient and performs very well with a large number of consumers, thus demonstrating its scalability.

The aquaponic principle—It is all about coupling

Abstract: The aquaponic principle is the coupling of animal aquaculture (e.g. fish) with plant production (e.g. vegetables) for saving resources. At present, various definitions of aquaponics exist, some bearing the risk of misinterpretation by dismissing the original meaning or being contradictory. In addition, there is no standard terminology for the aspects of coupling between the aquaponic subsystems. In this study, we addressed both issues. (1) We developed new or revised definitions that are summarised by: Aquaponic farming comprises aquaponics (which couples tank-based animal aquaculture with hydroponics) and trans-aquaponics, which extends aquaponics to tankless aquaculture as well as non-hydroponics plant cultivation methods. Within our conceptual system, the term aquaponics corresponds to the definitions of FAO and EU. (2) A system analysis approach was utilised to explore different aquaponic setups aiming to better describe the way aquaponic subsystems are connected. We introduced the new terms ‘coupling type’ and ‘coupling degree’, where the former qualitatively characterises the water-mediated connections of aquaponic subsystems. A system with on-demand nutrient water supply for the independent operating plant cultivation is an ‘on-demand coupled system’ and we propose to deprecate the counterintuitive term ‘decoupled system’ for this coupling type. The coupling degree comprises a set of parameters to quantitatively determine the coupling's efficiency of internal streams, for example, water and nutrients. This new framework forms a basis for improved communication, provides a uniform metric for comparing aquaponic facilities, and offers criteria for facility optimisation. In future system descriptions, it will simplify evaluation of the coupling's contribution to sustainability of aquaponics.

Positive energy districts: Mainstreaming energy transition in urban areas

Abstract: The concept of Positive Energy Districts (PEDs) has emerged to facilitate the energy transition and contribute to climate neutrality through energy efficiency and net zero energy balance. There are several similar concepts with a common goal that a building, neighborhood, or district can meet its energy demands from low-cost, locally available, environmentally friendly renewable sources. However, there is a lack of comprehensiveness and consistency among these existing concepts that could lead to misinterpretations. Therefore, the main aim of this study is to develop a comprehensive view on the PED concept with a focus on urban residential areas in Europe, with insights also being useful for other areas. The analysis is based on a literature review of PEDs and similar concepts, as well as a review of PED practical examples. The literature review compares PEDs based on geographical scale, identifying defining elements and metrics that provide insights on how to define and operationalize PEDs. The study reveals that real-life PEDs tend to go beyond the frames set by the definitions because the concept fails to consider the contextual factors that are inherent in them. To develop a comprehensive concept of PEDs, a Complex Adaptive System approach is taken, also incorporating the Doughnut view, which represents the system holistically. This view is also important in designing a resilient system, as energy systems are often exposed to disruptions. Additionally, the study discusses the PED concept's limitations and key issues, such as electric mobility, that merit more attention.

The life of soils: Integrating the who and how of multifunctionality

Abstract: Capturing the complexity of soil life for soil quality assessments is one of the most challenging paradoxes of contemporary soil science. Soil biota perform a plethora of processes that are fundamental to soil quality. As the concept of soil quality developed, so have the attempts to integrate soil biological measurements into monitoring schemes from field to regional scale. To date, however, soil science has not yet succeeded to provide flexible yet objective biological indicator methods to assess soil multifunctionality, customised to the user's context. We present an integrative framework and elucidate the who and how of soil multifunctionality. The framework encompasses the current scientific understanding of the role of soil biota in supporting the many soil processes that underly soil quality. We specified these relationships for four soil functions (Carbon and Climate Regulation, Water Regulation and Purification, Nutrient Cycling, and Disease and Pest Regulation). We identify challenges often encountered in soil quality assessment and monitoring schemes and discuss how the framework can be applied to provide a flexible selection tool. Soil quality assessments are conducted in different contexts. As assessment objectives range from mechanistic understanding, to functional land management and large spatial scale monitoring so will the practical and logistical constraints for method selection vary. Biological assessments need to move beyond the quest for a one-size-fits-all minimum dataset, and adopt a more nuanced selection approach founded in soil biology. We stress that biological attributes should not be considered in isolation but alongside soil chemical and physical attributes, as well as management and environmental contextualisation. The presented framework offers a structure to further quantify, understand and communicate the who and how of soil biology in defining multifunctionality.

Reduced tillage in organic farming affects soil organic carbon stocks in temperate Europe

Abstract: For decades, conservation tillage has been promoted as a measure to increase carbon stocks in arable soils. Since organic farming improves soil quality and soil carbon storage, reduced tillage under organic farming conditions may further enhance this potential. Therefore, we assessed soil organic carbon (SOC) stocks of reduced tillage compared with mouldboard ploughing in nine organic farming field trials in France, Germany, the Netherlands, and Switzerland with the same sampling and analytical protocol. We sampled soil cores until a depth of 100 cm to determine soil carbon stocks that are relevant for climate change mitigation but are often overlooked in tillage studies with shallow sampling depths. The studied field experiments were between 8 and 21 years old and comprised different soil types with clay contents ranging from 10% to 50%. SOC stocks increased with increasing clay-to-silt ratio, precipitation and organic fertiliser input. Across sites, reduced tillage in comparison with ploughing increased SOC stocks in the surface layer (0–10/15 cm) by 20.8% or 3.8 Mg ha−1, depleted SOC stocks in the intermediate soil layers to 50 cm soil depth with a maximum depletion of 6.6% or 1.6 Mg ha−1 in 15/20–30 cm and increased SOC stocks in the deepest (70–100 cm) soil layer by 14.4% or 2.5 Mg ha−1. The subsoil SOC stock increase may be linked to the inherent soil heterogeneity. Cumulative SOC stocks increased by 1.7% or 1.5 Mg ha−1 (0–50 cm, n = 9) and 3.6% or 4.0 Mg ha−1 (0–100 cm, n = 7) by reduced tillage compared with ploughing with estimated mean C sequestration rates of 0.09 and 0.27 Mg ha−1 yr−1, respectively. There was no effect of field trial duration on tillage induced cumulative SOC stocks differences. Under reduced tillage, biomass production was 8% lower resulting in a decrease of crop C input by 6%. However, this reduction may have been outbalanced by increased C inputs from weed biomass resulting from a higher weed incidence in reduced tillage, which warrants further research. Thus, reduced tillage in organic farming has the potential to increase total SOC stocks, while crop management has to be improved to increase productivity.

Protein-stabilized interfaces in multiphase food: comparing structure-function relations of plant-based and animal-based proteins

Abstract: Proteins are an important category of stabilizers for multiphase food systems such as foams and emulsions. In recent years, a growing interest can be observed in replacing animal-based by plant-based proteins to stabilize such products. Often, these plant-based proteins have inferior functionality compared to animal-based proteins. In this review, we will discuss recent insights into possible reasons for the differences in behavior between animal- and plant-based proteins, and present an overview of strategies to improve the performance of plant-based extracts. Improving plant-protein functionality may ultimately allow us to engineer interfaces with properties tailored to specific applications.

Back-to-monomer recycling of polycondensation polymers: opportunities for chemicals and enzymes

Abstract: The use of plastics in a wide range of applications has grown substantially over recent decades, resulting in enormous growth in production volumes to meet demand. Though a wide range of biomass-derived chemicals and materials are available on the market, the production volumes of such renewable alternatives are currently not sufficient to replace their fossil-based analogues due to various factors, in particular cost-effectiveness. Hence, the majority of plastics are still industrially produced from fossil-based feedstocks. Moreover, various reports have clearly raised concern about the plastics that are not recycled at their end-of-life and instead end up in landfills or the oceans. To avoid further pollution of our planet, it is highly desirable to develop recycling processes that use plastic waste as feedstock. Chemical recycling processes could potentially offer a solution, since they afford monomers from which new polymers can be produced, with the same performance as virgin plastics. In this manuscript, the opportunities for using either chemical or biochemical (i.e., enzymatic) approaches in the depolymerization of polycondensation polymers for recycling purposes are reviewed. Our aim is to highlight the strategies that have been developed so far to break down plastic waste into monomers, providing the first step in the development of chemical recycling processes for plastic waste, and to create a renewed awareness of the need to valorize plastic waste by efficiently transforming it into virgin plastics.

Deep Reinforcement Learning for Load-Balancing Aware Network Control in IoT Edge Systems

Abstract: Load balancing is directly associated with the overall performance of a parallel and distributed computing system. Although the relevant problems in communication and computation have been well studied in data center environments, few works have considered the issues in an Internet of Things (IoT) edge scenario. In fact, processing data in a load balancing way for the latter case is more challenging. The main reason is that, unlike a data center, both the data sources and the network infrastructure in an IoT edge system can be dynamic. Moreover, with different performance requirements from IoT networks and edge servers, it will be hard to characterize the performance model and to perform runtime optimization for the whole system. To tackle this problem, in this work, we propose a load-balancing aware networking approach for efficient data processing in IoT edge systems. Specifically, we introduce an IoT network dynamic clustering solution using the emerging deep reinforcement learning (DRL), which can both fulfill the communication balancing requirements from IoT networks and the computation balancing requirements from edge servers. Moreover, we implement our system with a long short term memory (LSTM) based Dueling Double Deep Q-Learning Network (D3QN) model, and our experiments with real-world datasets collected from an autopilot vehicle demonstrate that our proposed method can achieve significant performance improvement compared to benchmark solutions.

Population size mediates the contribution of high-rate and large-benefit mutations to parallel evolution

Abstract: Mutations with large fitness benefits and mutations occurring at high rates may both cause parallel evolution, but their contribution is predicted to depend on population size. Moreover, high-rate and large-benefit mutations may have different long-term adaptive consequences. We show that small and 100-fold larger bacterial populations evolve resistance to a β-lactam antibiotic by using similar numbers, but different types of mutations. Small populations frequently substitute similar high-rate structural variants and loss-of-function point mutations, including the deletion of a low-activity β-lactamase, and evolve modest resistance levels. Large populations more often use low-rate, large-benefit point mutations affecting the same targets, including mutations activating the β-lactamase and other gain-of-function mutations, leading to much higher resistance levels. Our results demonstrate the separation by clonal interference of mutation classes with divergent adaptive consequences, causing a shift from high-rate to large-benefit mutations with increases in population size.

The power of seaweeds as plant biostimulants to boost crop production under abiotic stress

Abstract: Abiotic stresses like drought and salinity are major factors resulting in crop yield losses and soil degradation worldwide. To meet increasing food demands, we must improve crop productivity, especially under increasing abiotic stresses due to climate change. Recent studies suggest that seaweed-based biostimulants could be a solution to this problem. Here, we summarize the current findings of using these biostimulants and highlight current knowledge gaps. Seaweed extracts were shown to enhance nutrient uptake and improve growth performance in crops under stressed and normal conditions. Seaweed extracts contain several active compounds, for example, polysaccharides, polyphenols and phytohormones. Although some of these compounds have growth-promoting properties on plants, the molecular mechanisms that underly seaweed extract action remain understudied. In this paper, we review the role of these extracts and their bioactive compounds as plant biostimulants. The targeted application of seaweed extract to improve crop performance and protein accumulation is also discussed.