the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
| 18 Jun 2024
Constraining Light Dependency in Modeled Emissions Through Comparison to Observed BVOC Concentrations in a Southeastern US Forest
Abstract. Climate change will bring about changes in meteorological and ecological factors that are currently used in global-scale models to calculate biogenic emissions. By comparing long-term datasets of biogenic compounds to modeled emissions, this work seeks to improve understanding of these models and their driving factors. We compare speciated BVOC measurements at the Virginia Forest Research Laboratory located in Fluvanna County, VA, USA for the 2020 year with emissions estimated by MEGANv3.2. The emissions were subjected to oxidation in a 0-D box-model (F0AM v4.3) to generate timeseries of modeled concentrations. We find that default light-dependent fractions (LDFs) in the emissions model do not accurately represent observed temporal variability of regional observations. Some monoterpenes with a default light dependence are better represented using light-independent emissions throughout the year (LDFα-pinene=0, as opposed to 0.6), while others are best represented using a seasonally or temporally dependent light dependence. For example, limonene has the highest correlation between modeled and measured concentrations using LDF=0 for January through April and roughly 0.74–0.97 in the summer months, in contrast to the default value of 0.4. The monoterpenes β-thujene, sabinene, and γ-terpinene similarly have an LDF that varies throughout the year, with light-dependent behavior in summer, while camphene and α-fenchene follow light-independent behavior throughout the year. Simulations of most compounds are consistently underpredicted in the winter months compared to observed concentrations. In contrast, day-to-day variability in the concentrations during summer months are relatively well captured using the coupled emissions-chemistry model constrained by regional concentrations of NOx and O3.
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The requested preprint has a corresponding peer-reviewed final revised paper. You are encouraged to refer to the final revised version.
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Journal article(s) based on this preprint
Interactive discussion
Status: closed
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RC1: 'Comment on egusphere-2024-1715', Anonymous Referee #1, 10 Jul 2024
Review of “Constraining light dependency in modeled emissions through comparison to observed BVOC concentrations in a southeastern US forest” by Panji et al
Panji et al present a study of methods to improve agreement between modeled and observed biogenic VOC concentrations. The measurements are 1 year’s data from Virginia Forest Research Laboratory focussed on isoprene, a-pinene, limonene and sabinene. A chemical box model is used to predict BVOC mixing ratios, using MEGAN to provide the biogenic emissions. The authors find that using MEGAN in default mode underpredicts monoterpene mixing ratios. Interestingly, their observations show that limonene has a different diurnal pattern than expected in summer. The expected diurnal cycle is exhibited by their a-pinene mixing ratio measurements. These measurements peak at night because of the fast OH chemistry during the daytime, reacts a-pinene into other products. Panji et al use the light dependence functions to improve the modeled to observed comparisons, finding that the function varies by compound and with the season.
I like how the study is progressing a one-size-fits all adjustment of the light dependence functions towards species and seasonally varying adjustments. I think the manuscript fits the ACP journal scope. I have one query and a couple of clarification comments before acceptance for publication.
My main confusion is about how the competing actions of limonene emissions and OH chemistry during the day act to keep limonene in (or out of) the air. My understanding is that the reaction of limonene with OH is faster than a-pinene with OH. Is the conclusion here that there is no OH left to quench the daytime limonene at this site, and can this be re-produced in the model?
line 172. I think the statement should read ‘independent’ instead of ‘dependent’? Otherwise it’s a strange statement. If they’re highly light dependent then there will be no emissions during the night. If they’re entirely light independent then the main driver is temperature which usually peaks during the day.
Line 195. Figure 4 is quite large but doesn’t really get talked about. Unless the new paragraph starting at line 196 is about fig 4? It isn’t clear. The new section at line 205 jumps to figure 5.
Line 215. It’s worth mentioning that the correlation coefficient for limonene nearly reaches 1.0 between june to august.
Figure 6. Please label the plots with a) and b) as in fig 5.
Citation: https://doi.org/10.5194/egusphere-2024-1715-RC1 -
RC2: 'Comment on egusphere-2024-1715', Anonymous Referee #2, 24 Jul 2024
Review of the manuscript
Constraining Light Dependency in Modeled Emissions Through Comparison to Observed BVOC Concentrations in a Southeastern US Forest
The submitted manuscript from Panji et al. presents comparison of modeled and measured concentrations of BVOC species, with special focus on monoterpenes, at the Virginia Forest Research Laboratory site (VFRL). The study focuses on the dependence of BVOC emissions on light and therefore proper setting of the light dependence factor (LDF) of individual BVOC compounds in the emission model. To be able to compare the measured concentrations with modeled values, the 0-dimension box model was applied. The authors compare performance of the emission model (MEGANv3.2) through the box model concentrations with MEGAN default LDF values, LDFs obtained from measurements at the VFRL site and LDF values best correlating with the observed concentrations. The paper investigates annual as well as time-varying (monthly) LDF values. The paper suggests new LDF values for selected monoterpene species.
The paper is well written and comprehensively structured. It falls well within the scope of ACP. I suggest accepting the paper for publication after addressing the following questions and minor comments.
Missing measurements of NOx and O3 at the VFRL site at the time of BVOC sampling were substituted by either measurement from previous years or by measurements from 15-53 miles distant stations. Though I understand the need to deal with lack of data, I think these assumptions need at least more discussion of the impact on results. The ozone stations are relatively far away from VFRL with cities such as Charlottesville or Richmond close by that can impact the O3 levels. Do the authors have some evidence that NOx and O3 levels do not have much inter-annual variability at these locations? The NOx and O3 data are crucial for calculation of BVOC concentrations from emissions, therefore can have a substantial impact on the final model to observation comparison.
Apart from LDF values and their seasonal changes, there are other parameters of the emission model that can (partially) explain the discrepancy of the modeled and measured results throughout the year. E.g. emission factors. Though not often used that way, EF can also very during the annual cycle (Helmig et al., 2013; https://doi.org/10.1016/j.chemosphere.2013.04.058). The EF intra-annual changes could be another factor that explains a different BVOC concentrations during winter and summer months. Could the authors include this in the discussion?
Can the authors please share their opinion (and include it in the paper ‘Discussion’ or ‘Conclusion’ section) on why the modeled concentrations are “consistently underpredicted in the winter months”? Actually, the modeled concentrations of limonene and sabinene are underpredicted also in July (Figs. 7 and 9).
The authors point out well that the LDF values play an important role in the BVOC models and their precise setting is important in order to obtain sensible emission results. Can the authors please elaborate if the LDF values obtained from the measurements at VFRL can be upscaled from this local site to global representation? If the authors think their values could be used for other studies as well, it would be extremely useful if they could add a Table summarising LDF values per species and per month that they recommend to use according to their study. This would be a very good benefit for other emission modelers.
Minor comments:
L73: please replace (McGlynn et al., 2021) by McGlynn et al. (2021)
L81: please replace “at Chan et al. (2011)” by “in Chan et al. (2011)”.
L90: please replace “vegetation” by “vegetation type j”
L159: Please make clear what is AMDAR – dataset of observed boundary layer heights?
L162: please describe which airports are IAD and RDU
L194: (4) should be (Figure 4)?
L195: the sentence ‘Although there are no isoprene emissions …’ does not make sense to me. There are no isoprene emissions shown in Figure 3. Furthermore, Figure 4 actually shows the opposite, i.e. almost zero night-time isoprene concentrations in observations. Should ‘observed’ be replaced by ‘modeled’?
L214: The following statement applies to limonene only, or not? “with a peak in light dependence during the summer and less light-dependence during the rest of the year”.
The description of results on Figure 6 is not very clear. Did you interpolate (with 0.01 value step) the modeled emissions or concentration values? Do I understand correctly, that for each month you calculated correlation between observed and modeled values and for a particular month you selected the LDF value that has the highest correlation (and this correlation value is the one shown in the plot)? If yes, please explain better in the text.
L224: “3 monoterpenes: isoprene, α-pinene, β- 225 pinene, and limonene.” Please remove isoprene.
p13: Caption of Fig 8 – please review the last sentence.
Supp. material:
- Fig S4 does not show results for January. Please edit the caption.
- Please review the caption of Figure S6. The last sentence does not make sense to me.
- Caption of Table S5 – emphi should be specific font of i?
- Caption of Fig S6 – please review the last sentence.
- AC1: 'Comment on egusphere-2024-1715', Namrata Shanmukh Panji, 12 Sep 2024
Interactive discussion
Status: closed
-
RC1: 'Comment on egusphere-2024-1715', Anonymous Referee #1, 10 Jul 2024
Review of “Constraining light dependency in modeled emissions through comparison to observed BVOC concentrations in a southeastern US forest” by Panji et al
Panji et al present a study of methods to improve agreement between modeled and observed biogenic VOC concentrations. The measurements are 1 year’s data from Virginia Forest Research Laboratory focussed on isoprene, a-pinene, limonene and sabinene. A chemical box model is used to predict BVOC mixing ratios, using MEGAN to provide the biogenic emissions. The authors find that using MEGAN in default mode underpredicts monoterpene mixing ratios. Interestingly, their observations show that limonene has a different diurnal pattern than expected in summer. The expected diurnal cycle is exhibited by their a-pinene mixing ratio measurements. These measurements peak at night because of the fast OH chemistry during the daytime, reacts a-pinene into other products. Panji et al use the light dependence functions to improve the modeled to observed comparisons, finding that the function varies by compound and with the season.
I like how the study is progressing a one-size-fits all adjustment of the light dependence functions towards species and seasonally varying adjustments. I think the manuscript fits the ACP journal scope. I have one query and a couple of clarification comments before acceptance for publication.
My main confusion is about how the competing actions of limonene emissions and OH chemistry during the day act to keep limonene in (or out of) the air. My understanding is that the reaction of limonene with OH is faster than a-pinene with OH. Is the conclusion here that there is no OH left to quench the daytime limonene at this site, and can this be re-produced in the model?
line 172. I think the statement should read ‘independent’ instead of ‘dependent’? Otherwise it’s a strange statement. If they’re highly light dependent then there will be no emissions during the night. If they’re entirely light independent then the main driver is temperature which usually peaks during the day.
Line 195. Figure 4 is quite large but doesn’t really get talked about. Unless the new paragraph starting at line 196 is about fig 4? It isn’t clear. The new section at line 205 jumps to figure 5.
Line 215. It’s worth mentioning that the correlation coefficient for limonene nearly reaches 1.0 between june to august.
Figure 6. Please label the plots with a) and b) as in fig 5.
Citation: https://doi.org/10.5194/egusphere-2024-1715-RC1 -
RC2: 'Comment on egusphere-2024-1715', Anonymous Referee #2, 24 Jul 2024
Review of the manuscript
Constraining Light Dependency in Modeled Emissions Through Comparison to Observed BVOC Concentrations in a Southeastern US Forest
The submitted manuscript from Panji et al. presents comparison of modeled and measured concentrations of BVOC species, with special focus on monoterpenes, at the Virginia Forest Research Laboratory site (VFRL). The study focuses on the dependence of BVOC emissions on light and therefore proper setting of the light dependence factor (LDF) of individual BVOC compounds in the emission model. To be able to compare the measured concentrations with modeled values, the 0-dimension box model was applied. The authors compare performance of the emission model (MEGANv3.2) through the box model concentrations with MEGAN default LDF values, LDFs obtained from measurements at the VFRL site and LDF values best correlating with the observed concentrations. The paper investigates annual as well as time-varying (monthly) LDF values. The paper suggests new LDF values for selected monoterpene species.
The paper is well written and comprehensively structured. It falls well within the scope of ACP. I suggest accepting the paper for publication after addressing the following questions and minor comments.
Missing measurements of NOx and O3 at the VFRL site at the time of BVOC sampling were substituted by either measurement from previous years or by measurements from 15-53 miles distant stations. Though I understand the need to deal with lack of data, I think these assumptions need at least more discussion of the impact on results. The ozone stations are relatively far away from VFRL with cities such as Charlottesville or Richmond close by that can impact the O3 levels. Do the authors have some evidence that NOx and O3 levels do not have much inter-annual variability at these locations? The NOx and O3 data are crucial for calculation of BVOC concentrations from emissions, therefore can have a substantial impact on the final model to observation comparison.
Apart from LDF values and their seasonal changes, there are other parameters of the emission model that can (partially) explain the discrepancy of the modeled and measured results throughout the year. E.g. emission factors. Though not often used that way, EF can also very during the annual cycle (Helmig et al., 2013; https://doi.org/10.1016/j.chemosphere.2013.04.058). The EF intra-annual changes could be another factor that explains a different BVOC concentrations during winter and summer months. Could the authors include this in the discussion?
Can the authors please share their opinion (and include it in the paper ‘Discussion’ or ‘Conclusion’ section) on why the modeled concentrations are “consistently underpredicted in the winter months”? Actually, the modeled concentrations of limonene and sabinene are underpredicted also in July (Figs. 7 and 9).
The authors point out well that the LDF values play an important role in the BVOC models and their precise setting is important in order to obtain sensible emission results. Can the authors please elaborate if the LDF values obtained from the measurements at VFRL can be upscaled from this local site to global representation? If the authors think their values could be used for other studies as well, it would be extremely useful if they could add a Table summarising LDF values per species and per month that they recommend to use according to their study. This would be a very good benefit for other emission modelers.
Minor comments:
L73: please replace (McGlynn et al., 2021) by McGlynn et al. (2021)
L81: please replace “at Chan et al. (2011)” by “in Chan et al. (2011)”.
L90: please replace “vegetation” by “vegetation type j”
L159: Please make clear what is AMDAR – dataset of observed boundary layer heights?
L162: please describe which airports are IAD and RDU
L194: (4) should be (Figure 4)?
L195: the sentence ‘Although there are no isoprene emissions …’ does not make sense to me. There are no isoprene emissions shown in Figure 3. Furthermore, Figure 4 actually shows the opposite, i.e. almost zero night-time isoprene concentrations in observations. Should ‘observed’ be replaced by ‘modeled’?
L214: The following statement applies to limonene only, or not? “with a peak in light dependence during the summer and less light-dependence during the rest of the year”.
The description of results on Figure 6 is not very clear. Did you interpolate (with 0.01 value step) the modeled emissions or concentration values? Do I understand correctly, that for each month you calculated correlation between observed and modeled values and for a particular month you selected the LDF value that has the highest correlation (and this correlation value is the one shown in the plot)? If yes, please explain better in the text.
L224: “3 monoterpenes: isoprene, α-pinene, β- 225 pinene, and limonene.” Please remove isoprene.
p13: Caption of Fig 8 – please review the last sentence.
Supp. material:
- Fig S4 does not show results for January. Please edit the caption.
- Please review the caption of Figure S6. The last sentence does not make sense to me.
- Caption of Table S5 – emphi should be specific font of i?
- Caption of Fig S6 – please review the last sentence.
- AC1: 'Comment on egusphere-2024-1715', Namrata Shanmukh Panji, 12 Sep 2024
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Namrata Shanmukh Panji
Deborah F. McGlynn
Laura E. R. Barry
Todd M. Scanlon
Manuel T. Lerdau
Sally E. Pusede
The requested preprint has a corresponding peer-reviewed final revised paper. You are encouraged to refer to the final revised version.
- Preprint
(17213 KB) - Metadata XML
-
Supplement
(18355 KB) - BibTeX
- EndNote
- Final revised paper