the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Simulating impacts on UK air quality from net-zero forest planting scenarios
Mathew R. Heal
Edward J. Carnell
Stephen Bathgate
Julia Drewer
James I. L. Morison
Massimo Vieno
Abstract. The UK proposes additional bioenergy plantations and afforestation as part of measures to meet net-zero greenhouse gas emissions, but species and locations are not yet decided. Different tree species emit varying amounts of isoprene and monoterpene volatile organic compounds that are precursors to ozone and secondary organic aerosol (SOA) formation, the latter of which is a component of PM2.5. The forest canopy also acts as a depositional sink for air pollutants. All these processes are meteorologically influenced. We present here a first step at coupling information on tree species planting suitability and other planting constraints with data on UK-specific BVOC emission rates and tree canopy data to simulate via the WRF-EMEP4UK high spatial resolution atmospheric chemistry transport model the impact on UK air quality of four potential scenarios. Our ‘maximum planting’ scenarios are based on planting areas where yields are predicted to be ≥50 % of the maximum from the Ecological Site Classification Decision Support System (ESC-DSS) for Eucalyptus gunnii, hybrid aspen (Populus tremula), Italian alder (Alnus cordata) and Sitka spruce (Picea sitchensis). The additional areas of forest in our scenarios are 2.0 to 2.7 times current suggestions for new bioenergy and afforestation landcover in the UK. Our planting scenarios increase UK annual mean surface ozone concentrations by 1.0 ppb or 3 % relative to the baseline landcover for the highest BVOC emitting species (e.g., E. gunni). Increases in ozone reach 2 ppb in summer when BVOC emissions are greatest. In contrast, all the additional planting scenarios lead to reductions in UK annual mean PM2.5 – ranging from -0.2 µg m-3 (-3 %) for Sitka spruce to -0.5 µg m-3 (-7 %) for aspen – revealing that PM2.5 deposition to the additional forest canopy area more than offsets additional SOA formation. Relative decreases in annual mean PM2.5 are greater than the relative increases in annual mean ozone. Reductions in PM2.5 are least in summer, coinciding with the period of maximum monoterpene emissions. Although only a first step in evaluating the impact of increased forest plantation on UK air quality, our study demonstrates the need for locally relevant data on landcover suitability, emissions and meteorology in model simulations.
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Gemma Purser et al.
Status: final response (author comments only)
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RC1: 'Comment on acp-2022-782', Anonymous Referee #1, 13 Mar 2023
This manuscript describes model simulations of the air quality impacts of four UK afforestation scenarios. The authors have improved on previous studies by using more detailed data on landcover suitability (placing limits on the potential area available for plantations), emission factors based on UK measurements of the specific species and a high resolution chemistry and transport model (WRF-EMEP4UK). These upgrades have the potential to result in a more accurate simulation. The manuscript has detailed methods and results sections and there is some discussion of the results including a brief comparison to previous studies. The current manuscript does not discuss the accuracy of these results which may mislead readers into assuming that these simulations are accurate representations when they have not shown this to be the case. The following three main points should be addressed before this manuscript is published:
Main points
1. The authors conclude that their simulations “demonstrate the need to use locally relevant data and atmospheric chemistry transport models to assess the impact of additional forest planting on surface atmospheric composition” but do not provide any evidence that this simulation is more accurate than any other simulation. Demonstrating that their improvements significantly improve the ability to model these scenarios requires comparing with alternative simulations and showing that they are more accurate.
2. The authors conclude that widespread planting of trees will slightly increase UK ozone and decrease PM2.5 but there is no assessment of the uncertainty of these simulations. For example, if their BVOC emissions change is underestimated and/or the particle deposition rate changes are overestimated then not only would there be error in the magnitude of the change in PM but even the sign of the change could be wrong. The manuscript needs a comprehensive description (as quantitative as possible) of the uncertainties associated with each component of the model system (BVOC emission, ozone and particle uptake, chemical transformation, etc) and a discussion of how the uncertainties might influence these results. In particular, this should address whether the uncertainties are so large that it is not currently possible to accurately predict whether widescale UK tree planting will have a positive or negative health impact.
As an example, the BVOC emission factors used for their model simulations are based on measurements of trees growing in the UK which should be more representative. But what is the uncertainty of these enclosure measurements? Have the emission rates been assessed by above canopy flux measurements? This is especially important for monoterpene emissions which are well known to be disturbed by the process of enclosing the vegetation for measurements. How valid is the assumption that light, temperature and biomass density are the only important controlling factors? Many studies have shown that these BVOC emissions are highly sensitive to stresses which can influence both the emission factor measurements and the model extrapolation. Other processes, such as the particle deposition rates, may be even more uncertain and the total uncertainty is likely quite high. A finding that these model simulations are highly uncertain does not suggest that they are not a valuable activity but will emphasize the need to reduce these uncertainties before any robust conclusions can be made.
3. The manuscript would benefit from additional simulations to investigate model sensitivity and quantify the impact of the identified uncertainties. It would also be informative to have simulations where only emissions or uptake is changed to better understand the results. For example, this could be used to determine the relative contributions of increased tree particle uptake vs lower agricultural BVOC emissions in determining the reductions in PM2.5 mentioned in lines 764 -766.
Specific points:
Line 403: exsisting => existing
Line 608-613: aspen is a higher per biomass emitter but is the area average emission (biomass X emission factor) of aspen and spruce about the same?
Line 613-622: it is surprising that a relatively small amount of monoterpenes would offset the ozone impacts of a much larger amount of isoprene. Some explanation should be provided of how this could be the case. For example, is it the difference in ozone formation potentials assumed by the model?
Line 646 : “than the loss than through” delete second “than”
Table 2. Specify the standard conditions for emission factors. Also, why is the monoterpene emission factor for deciduous woodland so high?
Citation: https://doi.org/10.5194/acp-2022-782-RC1 -
RC2: 'Comment on acp-2022-782', Anonymous Referee #2, 05 Apr 2023
In their paper “Simulating impacts on UK air quality from net-zero forest planting scenarios” the authors address a very timely and policy relevant issue for the UK. The authors present a first step towards a more complete understanding of the wider impacts of large-scale afforestation for carbon sequestration and bioenergy production in the UK.
The paper is certainly within the scope of ACP and my recommendation is that the paper is published, subject to correction / clarification on the following minor issues:
Section 2.3.1 (lines 251 – 255): Could you clarify the model setup, is it running for the whole European domain but nested at 5 x 5 km resolution over the UK online? What is the resolution for the rest of the domain?
Section 2.3.1 (lines 273 – 276): As the emission of BVOCs, dry deposition of gases and aerosols, and formation of SOA, are all important processes in this study it would be very useful to summarise here the approach taken (rather than just refer the reader to Simpson et al 2012). In particular, it will help with the later Results / Discussion to specify how SOA is formed i.e., via a fixed yield from oxidation of BVOCs? Do isoprene and monoterpenes both contribute to SOA? is a volatility basis set approach applied or does SOA condense irreversibly onto existing aerosol?
Section 2.3.2 (lines 297 – 298): The yield data is at 250 m x 250 m whereas the model land cover is at 5 km x 5 km, could you add a note here to clarify how the conversion is made? The underlying planting data takes into account the constraints from the Lovett et al 2014 study, are those constraints lost when scaled up to 5 km x 5 km or is just a % of a gridcell used?
Table 2: it would be useful to reiterate in the caption that the first four rows are based on field experiments from your previous study and the last four are based on the model algorithm used in EMEP
Figures 9, 11 and 13 are a little confusing. Showing the scenarios as a difference from the baseline makes sense but having the baseline concentrations on the same plot gives the (incorrect) impression that e.g. the baseline O3 is higher than all scenarios between Jan and April. One option would be to show the baseline seasonal cycles of O3, SOA and PM2.5 on their own Figure and have the scenarios on their own Figure each for O3, SOA and PM2.5?
Citation: https://doi.org/10.5194/acp-2022-782-RC2
Gemma Purser et al.
Gemma Purser et al.
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