the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
| 08 Jan 2025
Future Forests: estimating biogenic emissions from net-zero aligned afforestation pathways in the UK
Abstract. Woodlands sequester carbon dioxide from the atmosphere, which could help mitigate climate change. As part of efforts to reach net-zero greenhouse gas emissions by the year 2050, the UK’s Climate Change Committee (CCC) recommend increasing woodland cover from a UK average of 13 % to 17–19 %. Woodlands also have the potential to degrade air quality, due to the emission of biogenic volatile organic compounds (BVOCs) which are precursors to major atmospheric pollutants, ozone (O3) and particulate matter (PM). Here we make an estimate of the potential impact of afforestation in the UK on BVOC emissions, coupling information on tree species’ emissions potential, planting suitability and policy-informed land cover change. We quantify the potential emission of BVOCs from five afforestation experiments using the Model of Emissions of Gases and Aerosols from Nature (MEGAN) (v2.1) in the Community Land Model (CLM) (v4.5) for the year 2050. Experiments were designed to explore the impact of the variation in BVOC emissions potentials between and within plant functional types (PFTs) on estimates of BVOC emissions from UK land cover, to understand the scale of change associated with afforestation to 19 % woodland cover by the year 2050.
Our estimate of current annual UK emissions is 40 kt yr-1 for isoprene and 46 kt yr-1 for total monoterpenes. Broadleaf afforestation results in a change to UK isoprene emission of between -4 % and +131 %, and a change to total monoterpene emission of between +6 % and +52 %. Needleleaf afforestation leads to a change in UK isoprene emission of between -3 % and +20 %, and a change to total monoterpene emission of between +66 % and +95 %.
Our study highlights the potential for net-zero aligned afforestation to have substantial impacts on UK BVOC emissions, and therefore air quality, but also demonstrates routes to minimising these impacts through consideration of the emissions potentials of tree species planted.
Competing interests: Piers M Forster is the current chair of the Climate Change Committee. All other authors have no competing interests to declare.
Publisher's note: Copernicus Publications remains neutral with regard to jurisdictional claims made in the text, published maps, institutional affiliations, or any other geographical representation in this preprint. The responsibility to include appropriate place names lies with the authors.- Preprint
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Status: final response (author comments only)
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RC1: 'Comment on egusphere-2024-3895', Jing Tang, 07 Feb 2025
This manuscript presents the modelling results of the changes in BVOC emissions from UK afforestation. It is an interesting research topic considering the roles of BVOCs in atmospheric composition and net-zero emission actions. My main struggle with this paper is about the method design.
First, the authors chose to estimate BVOC emissions from CLM with the embedded MEGAN model. To fit into the CLM or climate data resolution, the model ran at very coarse spatial resolution; many higher resolution inputs (emission factor, leaf area index, etc) have to be averaged, or species distribution data have to be lumped, which can bring large uncertainties to the emission estimations. There are a lot of higher resolutions of climate data, which are sufficient to run the MEGAN model alone to get much higher-resolution estimations of emissions. I did not get the idea of choosing the CLM model, and there is no clear description of what variables from CLM (if any) were fed into the MEGAN. I don’t think making decisions based on these coarse resolution maps is so informative. With the coarse resolutions and grouped species, it is still unknown where to grow what species (due to grouped species) to increase or decrease certain BVOC emissions, and the resolution is way too coarse to estimate any air quality impacts.
Then, when converting grass to trees, the model should consider the removed emissions from grass as well.
Lastly, it is unclear why the authors chose to run for one future year, i.e., 2050 and even used the meteorological conditions from 2003. The authors' argument for selecting the meteorological condition from 2003 was based on comparing the maximum 1.5 m air temperature. This does not seem correct to me, considering that temperature is not the only factor influencing BVOC emissions. The year-to-year meteorological variations will undoubtedly affect your current estimations; it does not make sense to only look at 1-year outputs.
Citation: https://doi.org/10.5194/egusphere-2024-3895-RC1 -
RC2: 'Comment on egusphere-2024-3895', Anonymous Referee #2, 04 Mar 2025
The paper by Mooney et al. attempts to quantify future BVOC emissions from different afforestation pathways in the UK. The paper is within the scope of the journal and presents interesting results in terms of air quality implications. However, a number of technical issues need to be addressed prior to potential publication.
Uncertainty analysis. The authors discuss the effect of CO2 in inhibiting isoprene emissions in the future, but completely lack a proper sensitivity study to account for projected heat and drought waves on future BVOC emissions, which in my opinion is a much more relevant factor for future emission scenarios. It has been shown in many recent studies that the peak of isoprene (and possibly other light-dependent emissions) is not correctly represented with the standard CLM parameterisations based on Megan v2.1 (e.g. Jiang et al., 2018: doi: 10.1016/j.atmosenv.2018.01.026, Seco et al., 2015, doi: 10.1111/gcb.12980, Potosnak et al., 2014: doi: 10.1016/j.atmosenv.2013.11.055; Kaser et al, 2022: doi: 10.5194/acp-22-5603-2022; Otu-Larbi et al., 2019: doi: 10.1111/gcb.14963; Wang et al., 2024: doi: 10.1038/s41467-024-49960-0). In particular, heat waves can increase (or decrease) BVOC emissions, depending on their duration, and are an important factor not considered in this study. Failure to account for this effect is a major shortcoming and makes future BVOC projections particularly questionable. The authors should provide an uncertainty assessment by using different parameterisations in their sensitivity runs to estimate the effect on their future projections.
Line 127cc: To quantify emissions a number of datasets are used including ambient concentration data. It is not explained further how, and to what extent these observations are used to validate and/or test the model results.
Model setup: Can the authors be more concrete on the methodology to attribute species-specific emission potentials to PFTs for estimating the average emission potential using tree inventories for actual present day scenarios? The assumptions themselves may be valid, but they are simplifications with associated uncertainties. Quantifying these uncertainties is important to understand how much confidence to place in the conclusions.
Citation: https://doi.org/10.5194/egusphere-2024-3895-RC2
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