Bioenergy Potential and Greenhouse Gas Emissions from Intensifying European Temporary Grasslands

Wicke, Birka; Kluts, Ingeborg; Lesschen, J.P.

doi:10.3390/land9110457

Cited by 6 publications

(5 citation statements)

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“…The studies conducted so far have confirmed that both perennial and annual grasses can play a key role in the implementation of lignocellulosic biomass for various energy purposes [6]. An analysis by Wicke et al [7] showed that the sustainable intensification of temporary grasslands can provide a total of 853 kha of surplus area for energy production in the European Union. Such action would allow the production of 3.7 to 11 million tonnes of dry mass of biomass, depending on the degree of use of conventional grass species and grassy energy crops, which could be tantamount to obtaining additional energy potential in the amount of 67-213 PJ•year −1 [7].…”

Section: Introductionmentioning

confidence: 90%

“…An analysis by Wicke et al [7] showed that the sustainable intensification of temporary grasslands can provide a total of 853 kha of surplus area for energy production in the European Union. Such action would allow the production of 3.7 to 11 million tonnes of dry mass of biomass, depending on the degree of use of conventional grass species and grassy energy crops, which could be tantamount to obtaining additional energy potential in the amount of 67-213 PJ•year −1 [7]. The importance of grassy biomass and its potential was also confirmed in the Biomass Policies project [8].…”

Section: Introductionmentioning

confidence: 99%

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Determination of Energy Parameters and Their Variability between Varieties of Fodder and Turf Grasses

et al. 2022

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Due to the need to diversify energy sources and transform the energy system and its decarbonization, new paths for obtaining raw materials are being sought. One of the potential options is to increase the use of grasses’ share in bioenergy production, which has a significant area potential. However, the diversified chemical composition of grasses and their anatomical heterogeneity mean that, between the various cultivars and species, the parameters determining their energetic usefulness may differ significantly, hence the key is to know the appropriate parameters at the variety level of a given species in order to effectively carry out the combustion process. In this experiment, a total of 23 varieties of seven grass species (Kentucky bluegrass (Poa pratensis L.), Red Fescue (Festuca rubra L.), Perennial Ryegrass (Lolium perenne L.), Meadow Fescue (Festuca pratensis Huds.), Timothy (Phleum pratense L.), Common Bent (Agrostis capillaris L.), Sheep Fescue (Festuca ovina L.), which had not yet been evaluated in terms of energy utilization, were tested. Proximate analysis showed the average ash content was in the range of 5.73–8.31%, the content of volatile matter in the range of 70.99–82.29% and the content of fixed carbon in the range of 5.96–17.19%. Higher heating value and lower heating value of grasses ranged from 16,548 kJ∙kg−1–18,616 kJ∙kg−1, 15,428 kJ∙kg−1–17453 kJ∙kg−1, respectively. The Sheep Fescue turned out to be the most useful species for combustion. It has been shown that there may be statistically significant differences in the parameters determining their combustion suitability between the various varieties of a given species of grass. Therefore the major finding of this work shows that it is necessary to need to know theparameters of a given variety is necessary to optimize the combustion process and maintain the full energy efficiency of the system (especially lower heating value).

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Section: Introductionmentioning

confidence: 90%

Section: Introductionmentioning

confidence: 99%

Determination of Energy Parameters and Their Variability between Varieties of Fodder and Turf Grasses

et al. 2022

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“…In Europe, it occupies more than a third of agricultural land, and as an ecosystem, it is characterised by its unique ecological value [1]. Grassland differs in terms of management, yield, environmental and biodiversity value and intensification measures specific to different grassland types [2]. It ranges from extensively managed semi-natural grassland with low intensity of use and high biodiversity value to intensively managed, monocultural and low biodiversity value grassland [1][2][3].…”

Section: Introductionmentioning

confidence: 99%

“…Grassland differs in terms of management, yield, environmental and biodiversity value and intensification measures specific to different grassland types [2]. It ranges from extensively managed semi-natural grassland with low intensity of use and high biodiversity value to intensively managed, monocultural and low biodiversity value grassland [1][2][3]. The degree of intensification, i.e., manure and fertiliser inputs, grazing pressure, cutting frequency and grassland renewal, determines the productivity of grassland but can also be considered a proxy for its biodiversity value [1].…”

Section: Introductionmentioning

confidence: 99%

Grassland Use Intensity Classification Using Intra-Annual Sentinel-1 and -2 Time Series and Environmental Variables

et al. 2022

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Detailed spatial data on grassland use intensity is needed in several European policy areas for various applications, e.g., agricultural management, supporting nature conservation programs, improving biodiversity strategies, etc. Multisensory remote sensing is an efficient tool to collect information on grassland parameters. However, there is still a lack of studies on how to process, combine, and implement large radar and optical image datasets in a joint observation framework to map grassland types on large heterogeneous study areas. In our study, we assessed the usefulness of 2521 Sentinel-1 and 586 Sentinel-2 satellite images and topographic data for mapping grassland use intensity. We focused on the distinction between intensively and extensively managed permanent grassland in a large heterogeneous study area in Slovenia. We provided dense Satellite Image Time Series (SITS) for 2017, 2018 and 2019 to identify important differences, e.g., management practices, between the two grassland types analysed. We also investigated the effectiveness of combining two different remote-sensing products, the optical Normalised Difference Vegetation Index (NDVI) and radar coherence. Grassland types were distinguished using an object-based approach and the Random Forest classification. With the use of SITS only, the models achieved poor performance in the case of cloudy years (2018). However, the performance improved with additional features (environmental variables). The feature selection method based on Mean Decrease Accuracy (MDA) provided a deeper insight into the high-dimensional multisensory SITS. It helped select the most relevant features (acquisition dates, environmental variables) that distinguish between intensive and extensive grassland types. The addition of environmental variables improved the overall classification accuracy by 7–15%, while the feature selection additionally improved the final overall classification accuracy (using all available features) by 2–3%. Although the reference dataset was limited (1259 training samples), the final overall classification accuracy was above 88% in all years analysed. The results show that the proposed Random Forest classification using combined multisensor data and environmental variables can provide better and more stable information on grasslands than single optical or radar data SITS on large heterogeneous areas. Therefore, a combined approach is recommended to distinguish different grassland types.

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“…Meerbeek et al [3] explored the biomass potential for bioenergy in the landscape beyond forests and agricultural land: gardens, roadsides, sports fields, conservation areas, etc., and stated that a large amount of biomass that is created by their regular management should not be considered as waste, but as a sustainable bioenergy resource. Wicke et al [4] quantified the bioenergy potential from intensifying grasslands in Europe. The production potential of straw harvested over agricultural consumption in Poland and its use for energy purposes were evaluated by Gradziuk et al [5].…”

Section: Introductionmentioning

confidence: 99%

Using Timber as a Renewable Resource for Energy Production in Sustainable Forest Management

Banaś

Utnik-Banaś

2022

Energies

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Using timber from multifunctional forests for energy production can be economically viable and environmentally friendly when it is consistent with the principles of sustainable management; otherwise, it could be harmful from both an ecological and commercial point of view. The objective of this paper was to present the overall balance of timber biomass from felled trees in multifunctional forests and assess what kind and how much of this biomass can be used for energy purposes. The research material consisted of data on forest resources and the volume of timber removal in Polish State Forests in 2016–2020. The biomass of branches and stumps of felled trees was determined using biomass expansion factors (BEFs). The results obtained in this study indicated that industrial timber, energy wood, and biomass left in the forest as a source of deadwood are 67%, 20%, and 13% of the total woody biomass, respectively. The Polish State Forest’s potential for energy wood is estimated at 6.18 million tonnes of biomass annually. Total available energy produced from woody biomass amounted to 104.8 PJ y−1.

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Bioenergy Potential and Greenhouse Gas Emissions from Intensifying European Temporary Grasslands

Cited by 6 publications

References 50 publications

Determination of Energy Parameters and Their Variability between Varieties of Fodder and Turf Grasses

Determination of Energy Parameters and Their Variability between Varieties of Fodder and Turf Grasses

Grassland Use Intensity Classification Using Intra-Annual Sentinel-1 and -2 Time Series and Environmental Variables

Using Timber as a Renewable Resource for Energy Production in Sustainable Forest Management

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