Schlagwort: afforestation

Science – Liang et al. (2025): Climate mitigation potential for targeted forestation after considering climate change, fires, and albedo

Shijing Liang, Alan D. Ziegler, Peter B. Reich, Kai Zhu, Dashan Wang, Xin Jiang, Deliang Chen, Philippe Ciais and Zhenzhong Zeng IN: Science Advances, doi.org/10.1126/sciadv.adn7915

The carbon sequestration potential of afforestation and reforestation remains uncertain in satellite-based assessments, particularly when accounting for dynamic climate conditions, vegetation-climate feedback, fire-dominated disturbance, and the trade-offs associated with surface albedo changes. Leveraging a coupled Earth system model, the authors estimated the global forestation mitigation during 2021–2100 under a sustainable shared socioeconomic pathway.

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Yan et al. (2025): Afforestation boosted gross primary productivity of China: evidence from remote sensing

Wei Yan, Hesong Wang, Chao Jiang, Osbert Jianxin Sun, Jianmin Chu, Anzhi Zhang IN: Journal of Forestry Research, 36, https://doi.org/10.1007/s11676-025-01828-9

Over recent decades, China has launched a series of long-running and large-scale ambitious forestation projects. However, there is still a lack of year-to-year evaluation on the effects of afforestation on carbon sequestration. Satellite remote sensing provides continuous observations of vegetation dynamics and land use and land cover change, is becoming a practical tool to evaluate the changes of vegetation productivity driven by afforestation. Here, a spatially-explicit analysis was conducted by combining Moderate Resolution Imaging Spectroradiometer (MODIS) land cover and three up-to-date remote sensing gross primary productivity (GPP) datasets of China.

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Upeksha et al. (2025): Costs and benefits of afforestation with renewable electricity-based desalination: Case study for Egypt

Upeksha Caldera, Andreas Mühlbauer, Mai ElSayed, Arman Aghahosseiini, Christian Breyer IN: Smart Energy, 17, https://doi.org/10.1016/j.segy.2025.100174

Aim of this research is to show how Egypt can make use of its plentiful renewable resources, available land area, and access to the sea, to establish cost-effective afforestation irrigated with renewable energy-based seawater desalination for land degradation mitigation.

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Pongratz et al. (2024): The state of carbon dioxide removal through afforestation and reforestation

Julia Pongratz, Clemens Schwingshackl, Thomas Gasser, Andrea Castanho, Giacomo Grassi IN: Proceedings of the 11th International Carbon Dioxide Conference

Here the authors present new estimates of CDR by A/R based on multiple bookkeeping models (those also used in GCP’s 2023 global carbon budget). They compare these with estimates of A/R and forest management based on the NGHGIs after correcting for natural fluxes. CDR through A/R amounts to 1,860 MtCO2 (1,160-2,230 MtCO2; full range across models) per year globally, averaged over 2013-2022. CDR in managed forests based on NGHGIs is 2000 MtCO2 per year over the same period.

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Egerer et al. (2024): How to measure the efficiency of bioenergy crops compared to forestation

Sabine Egerer, Stefanie Falk, Dorothea Mayer, Tobias Nützel, Wolfgang A. Obermeier, Julia Pongratz IN: Biogeosciences, 21, https://doi.org/10.5194/bg-21-5005-2024

In this study, the authors introduce different measures of efficiency to evaluate the carbon removal potential of afforestation and reforestation (AR) and bioenergy with carbon capture and storage (BECCS) under the low-emission scenario SSP1-2.6 and in the same area. They define efficiency as the potential to sequester carbon in the biosphere in a specific area or store carbon in geological reservoirs or woody products within a certain time. In addition to carbon capture and storage (CCS), they consider the effects of fossil fuel substitution (FFS) through the usage of bioenergy for energy production, which increases the efficiency through avoided CO2 emissions. These efficiency measures reflect perspectives regarding climate mitigation, carbon sequestration, land availability, spatiotemporal dynamics, and the technological progress in FFS and CCS. They use the land component JSBACH3.2 of the Max Planck Institute Earth System Model (MPI-ESM) to calculate the carbon sequestration potential in the biosphere using an updated representation of second-generation bioenergy plants such as Miscanthus.

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Egerer et al. (2024): How to measure the efficiency of bioenergy crops compared to forestation

Sabine Egerer, Stefanie Falk, Dorothea Mayer, Tobias Nützel, Wolfgang A. Obermeier, Julia Pongratz IN: Biogeosciences, https://doi.org/10.5194/bg-21-5005-2024

In our study, the authors introduce different measures of efficiency to evaluate the carbon removal potential of afforestation and reforestation (AR) and bioenergy with carbon capture and storage (BECCS) under the low-emission scenario SSP1-2.6 and in the same area. They define efficiency as the potential to sequester carbon in the biosphere in a specific area or store carbon in geological reservoirs or woody products within a certain time. In addition to carbon capture and storage (CCS), we consider the effects of fossil fuel substitution (FFS) through the usage of bioenergy for energy production, which increases the efficiency through avoided CO2 emissions.

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Nature – Kristensen et al. (2024): Tree planting is no climate solution at northern high latitudes

Jeppe Å. Kristensen, Laura Barbero-Palacios, Isabel C. Barrio, Ida B. D. Jacobsen, Jeffrey T. Kerby, Efrén López-Blanco, Yadvinder Malhi, Mathilde Le Moullec, Carsten W. Mueller, Eric Post, Katrine Raundrup, Marc Macias-Fauria IN: Nature Geoscience, 17, https://doi.org/10.1038/s41561-024-01573-4

Planting trees has become a popular solution for climate change mitigation, owing to the ability of trees to accumulate carbon in biomass and thereby reduce anthropogenic atmospheric CO2 enrichment. As conditions for tree growth expand with global warming, tree-planting projects have been introduced in regions of the highest northern latitudes. However, several lines of evidence suggest that high-latitude tree planting is counterproductive to climate change mitigation.

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Nature – Li al. (2024): Increased precipitation has not enhanced the carbon sequestration of afforestation in Northwest China

Xintao Li, Ke Xia, Taixia Wu, Shudong Wang, Hongzhao Tang, Chenchao Xiao, Hongwu Tang, Nan Xu, Dongzhen Jia IN: Communications Earth & Environment, 5, https://doi.org/10.1038/s43247-024-01733-9

Concerns have been raised about the sustainability of large-scale afforestation in semi-arid regions due to potential water constraints. Using multi-source remote sensing data, this study investigated whether increased humidity in the semi-arid regions of northwest China could sustain the continued expansion of afforestation efforts

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Wu et al. (2024): Prospects for the potential carbon sink effects of afforestation to enhance weathering in China

Weihua Wu, Werner Nel, Junfeng Ji, Jun Chen IN: Journal of Asian Earth Sciences, 276, https://doi.org/10.1016/j.jseaes.2024.106370

Previously, afforestation as a carbon sink was primarily evaluated in terms of the biomass carbon pool and soil organic carbon pool. Plants play a significant role in enhancing the chemical weathering of rocks and minerals, which can lead to more CO2 consumption. However, role of plants in enhancing chemical weathering and contributing to CO2 removal has not been considered when calculating the artificial sink. This paper reviews relevant studies on the carbon sinks from weathering and forest biomass in China and synthesizes the research on how plants affecting weathering in natural ecosystems.

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Nature – Yao et al. (2024): Carbon sequestration potential of tree planting in China

Ling Yao, Tang Liu,Jun Qin, Hou Jiang, Lin Yang, Pete Smith, Xi Chen, Chenghu Zhou, Shilong Piao IN: Nature Communications, 15, https://doi.org/10.1038/s41467-024-52785-6

China’s large-scale tree planting programs are critical for achieving its carbon neutrality by 2060, but determining where and how to plant trees for maximum carbon sequestration has not been rigorously assessed. Here, the authors developed a comprehensive machine learning framework that integrates diverse environmental variables to quantify tree growth suitability and its relationship with tree numbers. Then, their correlations with biomass carbon stocks were robustly established. Carbon sink potentials were mapped in distinct tree-planting scenarios.

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