the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Regional to global distributions, trends, and drivers of biogenic volatile organic compound emission from 2001 to 2020
Abstract. Biogenic volatile organic compounds (BVOCs) are important precursors to ozone and secondary organic aerosols in the atmosphere, affecting air quality, clouds and climate. However, the trend of BVOC emissions and driving factors for the emission changes in different geographic regions over the past two decades has remained unclear. Here, regional to global changes in BVOC emissions during 2001–2020 are simulated using the latest Model of Emission of Gases and Aerosols from Nature (MEGANv3.2) with the input of time-varying satellite-retrieved vegetation and reanalysis meteorology data. Comparison of model simulations with the site observations shows that the model can reasonably reproduce the magnitude of isoprene and monoterpene emission fluxes. The spatial distribution of the modeled isoprene emissions is generally comparable to the satellite retrievals. The estimated annual average global BVOC emissions are 835.4 Tg yr-1 with the emissions from isoprene, monoterpenes, sesquiterpenes, and other BVOC comprised of 347.7, 184.8, 23.3, and 279.6 Tg yr-1, respectively. We find that the decrease in global isoprene emissions (-0.07 % yr-1) caused by increase in CO2 concentrations (-0.20 % yr-1) is stronger than that caused by changes in vegetation (-0.03 % yr-1) and meteorological factors (0.15 % yr-1). However, regional disparities are large. Isoprene emissions increase significantly in Europe, East Asia, and South Asia (0.37-0.66 % yr-1). The increasing trend is contributed by half from increased leaf area index (LAI) (maximum over 0.02 m2 m-2 yr-1) and tree cover. Changes in meteorological factors contribute to another half, with elevated temperature dominating in Europe and increased soil moisture dominating in East and South Asia. In contrast, in South America and Southeast Asia, shifts in vegetation type associated with the BVOC emission capacity, which partly results from the deforestation and agricultural expansion, decrease the BVOC emission and offset nearly half of the emission increase caused by changes in meteorological factors. Overall, isoprene emission increases by 0.35 % yr-1 and 0.25 % yr-1 in South America and Southeast Asia, respectively. In Central Africa, a decrease in temperature dominates the negative emission trend (-0.74 % yr-1). Global monoterpene emissions show a significantly increasing trend (0.34 % yr-1, 0.6 Tg yr-1) compared to that of isoprene (-0.07 % yr-1, -0.2 Tg yr-1), especially in strong greening hotspots. This is mainly because the monoterpene emissions are more sensitive to changes in LAI and are not subject to the inhibition effect of CO2. The findings highlight the important roles of vegetation cover and biomass, temperature, and soil moisture in modulating the temporal variations of global BVOC emissions in past two decades.
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Notice on discussion status
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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Preprint
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Supplement
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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.
- Preprint
(5153 KB) - Metadata XML
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Supplement
(1721 KB) - BibTeX
- EndNote
- Final revised paper
Journal article(s) based on this preprint
Interactive discussion
Status: closed
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RC1: 'Comment on egusphere-2023-1830', Anonymous Referee #1, 13 Sep 2023
BVOCs are important precursors to ozone and secondary organic aerosols in the atmosphere. In this manuscript, the authors focused on a comprehensive analysis of trends in BVOC emissions from 2001-2020 on a regional to global scales and identified the contribution of various driving factors to these trends. The manuscript is well written, and I suggested the acceptance after addressing the comments below.
- The authors used a newer version of MEGAN. Could the authors elaborate the major advancement compared to previous versions such as MEGAN 2.1?
- Are the observations only in 2013? The seasonal variations of isoprene flux in MEGAN appears to be very small, which seems to be quite different from the observations. Any explanations?
- Line 274: These discrepancies are mainly ascribed to the differences in vegetation emission factors between the two versions of MEGAN. Could the authors add some explanations the emission factors from which vegetation are more accurate?
- Line 367: Could the authors explain why for monoterpene emissions, only the effects of vegetation and meteorological factors are considered?
Citation: https://doi.org/10.5194/egusphere-2023-1830-RC1 - AC1: 'Reply on RC1', Hao Wang, 10 Oct 2023
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RC2: 'Comment on egusphere-2023-1830', Anonymous Referee #2, 18 Sep 2023
This is a study of great relevance to the atmospheric pollution modeling community. The trends presented and the sensitivity of MEGAN 3.2 to various parameters and its geographical distribution are of great interest to all of us who model both emissions and air quality. It provides interesting insights into how BVOC emissions can change at specific regions and highlights the significant impact of land-use changes and global warming.
I would like to ask the authors if they have reviewed or analyzed the uncertainty associated with the new emission factors used in MEGAN. Have they utilized those with the highest confidence index (denoted as 'J' in the code)? Or do they consider it worthwhile to address these factors or their spatial distribution in the future? Are these emission factors the default values in MEGAN for tree, shrub, grass, and crop categories?
Was there any anomaly in the reference year of 2001 that could potentially bias the study in specific regions? Did the authors find any unexpected anomalies that they did not anticipate?
Possible issues I have detected:
- In line 70, based on my reading of the rest of the manuscript, shouldn't the range '0.04-0.33% yr-1' be negative?
- Please review the use of capitalization for the acronyms 'LAI' and 'VCF' in both the text and figure captions.
- In line 545, it should be corrected with “activity factors”.
Citation: https://doi.org/10.5194/egusphere-2023-1830-RC2 - AC2: 'Reply on RC2', Hao Wang, 10 Oct 2023
Interactive discussion
Status: closed
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RC1: 'Comment on egusphere-2023-1830', Anonymous Referee #1, 13 Sep 2023
BVOCs are important precursors to ozone and secondary organic aerosols in the atmosphere. In this manuscript, the authors focused on a comprehensive analysis of trends in BVOC emissions from 2001-2020 on a regional to global scales and identified the contribution of various driving factors to these trends. The manuscript is well written, and I suggested the acceptance after addressing the comments below.
- The authors used a newer version of MEGAN. Could the authors elaborate the major advancement compared to previous versions such as MEGAN 2.1?
- Are the observations only in 2013? The seasonal variations of isoprene flux in MEGAN appears to be very small, which seems to be quite different from the observations. Any explanations?
- Line 274: These discrepancies are mainly ascribed to the differences in vegetation emission factors between the two versions of MEGAN. Could the authors add some explanations the emission factors from which vegetation are more accurate?
- Line 367: Could the authors explain why for monoterpene emissions, only the effects of vegetation and meteorological factors are considered?
Citation: https://doi.org/10.5194/egusphere-2023-1830-RC1 - AC1: 'Reply on RC1', Hao Wang, 10 Oct 2023
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RC2: 'Comment on egusphere-2023-1830', Anonymous Referee #2, 18 Sep 2023
This is a study of great relevance to the atmospheric pollution modeling community. The trends presented and the sensitivity of MEGAN 3.2 to various parameters and its geographical distribution are of great interest to all of us who model both emissions and air quality. It provides interesting insights into how BVOC emissions can change at specific regions and highlights the significant impact of land-use changes and global warming.
I would like to ask the authors if they have reviewed or analyzed the uncertainty associated with the new emission factors used in MEGAN. Have they utilized those with the highest confidence index (denoted as 'J' in the code)? Or do they consider it worthwhile to address these factors or their spatial distribution in the future? Are these emission factors the default values in MEGAN for tree, shrub, grass, and crop categories?
Was there any anomaly in the reference year of 2001 that could potentially bias the study in specific regions? Did the authors find any unexpected anomalies that they did not anticipate?
Possible issues I have detected:
- In line 70, based on my reading of the rest of the manuscript, shouldn't the range '0.04-0.33% yr-1' be negative?
- Please review the use of capitalization for the acronyms 'LAI' and 'VCF' in both the text and figure captions.
- In line 545, it should be corrected with “activity factors”.
Citation: https://doi.org/10.5194/egusphere-2023-1830-RC2 - AC2: 'Reply on RC2', Hao Wang, 10 Oct 2023
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Xiaohong Liu
Chenglai Wu
Guangxing Lin
The requested preprint has a corresponding peer-reviewed final revised paper. You are encouraged to refer to the final revised version.
- Preprint
(5153 KB) - Metadata XML
-
Supplement
(1721 KB) - BibTeX
- EndNote
- Final revised paper