biogenic volatile organic compoud emissions in some...
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Biogenic volatile organic compound emissions in grassland and forests in China
(I) and Variations of trace gases and particulate matter at Xinglong station (II)
Bai Jianhui1, Guenther Alex2,3, Turnipseed Andrew2
, Duhl Tiffany2, Greenberg James2, Wan Xiaowei1, van der A Ronald4, Yu Shuquan5
, Wang Bin5, Hao Nan6, Wang PuCai1 1. LAGEO, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing 100029 2. National Center for Atmospheric Research, Boulder, CO 80307, USA 3. Now at Pacific Northwest National Laboratory, Richland WA 99352, USA and Washington State University, Pullman WA
99164, USA 4. KNMI, Utrechtseweg 297, 3731GA De Bilt, The Netherlands. 5.School of Forestry & Bio-technology Zhejiang Agriculture and Forestry University，Hangzhou 311300. 6. German Aerospace Center (DLR), 82234, Wessling, Germany.
1. Introduction BVOC emissions (I)
BVOCs play important roles in: O3 photochemistry the formation of secondary organic aerosols (SOA,PM2.5) the Carbon budget BVOCs’ oxidation influences OH radicals and O3 BVOCs take part in chemical and photochemical reactions in the atmosphere, consume solar UV and visible radiation directly and/or indirectly
BVOC emission studies in some ecosystems in China are summarized, so as to understand their emission characteristics. More studies are needed in the future.
1) Changbai Mountain temperate forest (42o24’N,128o6’E, 738m
asl), jilin province, in 2010 and 2011 growing seasons REA (Relaxed Eddy Accumulation) technique Dominant trees:
Pinus koraiensis, Tilia amurensis, Quercus mongolica, Fraxinus mandshurica, Acer mono. Dominant Shrubs:
Deutzia amurensis, Acer pseudosieboldiarum, A. Tegmentosum, Corylus mandshurica.
2) Subtropical bamboo forest at Taihuyuan (30o18’N, 119o34’E) in
Linan city, Zhejing province, from July 2012 to January 2013. REA technique Dominant species: Phyllostachysviolascens or Lei bamboo
2. BVOC flux measurements in some ecosystems in China 2.1 Site description
3) Inner Mongolia grassland (43o26’- 44o08’N,116o04’ - 117o05’E) Ecosystem Research Station, CAS, in 2002 and 2003 growing seasons. Chamber method: 90cm×90cm×35cm Dominant species: A. chinense, Achnatherum sibiricum, S. grandis, Carex appendiculata, K. cristata, C. squarrosa, A. senescens, and A. tenuissimum.
4) Qianyanzhou subtropical forest (26o44’N, 115o03’E) in Taihe county, Jiangxi province from Jan., 2013 to Dec., 2015.
REA technique
Dominant species :
Pinus elliottii, Pinus massoniana · ·
· ·
Changbai Mountain temperate forest Qianyanzhou subtropical forest
LinAn subtropical bamboo forest
O3 analyzer
Solar radiation system
• Measuring time period: Growing seasons (e.g., 28 June to 25 August, 2010 in Changbai
temperate forest). • Air sample collections: 1) diurnal variation:6,9,12,15,18; 2) day-day variation: around noon • Sample analysis: The sampled cartridges were analyzed by GC-FID and GC-MS. Flux calculation: F = bσw(Cup-Cdown) (1) b: a proportionality factor; σw: standard deviation of the vertical
wind speed; Cup-Cdown : concentration difference between the updraft and downdraft cartridges over a period of 30 min.
2.3 Measurement of Solar radiation
2.2 Observation and analysis of BVOCs
Global solar radiation (Q): 270-3200 nm Direct radiation (D): 270-3200 nm Scattered radiation (S): Q - D PAR (photosynthetically active radiation): 400-700 nm (Licor)
1) Main VOC species in Changbai temperate forest: isoprene, αpinene,βpinene, camphene, sabinene, myrcene, carene, limonene, ocimene, terpinene, cymene, terpinolene, tricyclene.
The mean isoprene emission flux (mgm-2h-1) was 0.889, mean total monoterpene emission flux was 0.143 in 2011 summer.
2.4 Measuring results
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Fig.1 Isoprene emission flux, PAR,T in 2011 summer at a temperate forest in China
2) Main VOC species in a subtropical Lei bamboo forest The mean isoprene emission flux was 0.95 mgm-2h-1(maximum-10.32), the total monoterpene emission flux was 0.012 mgm-2h-1 from 7 July, 2012 to 19 Jan., 2013. α-pinene (-0.34 - 0.12), longifolene (-0.01-0.03), α-cadrene (-0.004 - 0.001) mgm-2h-1
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Fig. 2 The measured emission fluxes of isoprene at a subtropical Lei bamboo forest in China
3. Empirical models and their simulations 3.1 Empirical models of isoprene and monoterpene emissions PAR/cosZ = A1’e-k1Etm + A2’e-kwm + A3’e-S/Q + A0’ (2) (1) e-k1Etm: PAR attenuation by isoprene/monoterpene through OH radical during the photochemical reactions. (2) e-K2Wm: PAR absorption and/or utilization by gases, liquids, particles (GLPs) trough OH radicals. (3) e-S/D: Total scattering effects by GLPs in the atmosphere. Ai’ are empirical coefficients (i=1,2,3,0). Isoprene and monoterpene emission flux can be calculated by: e-k1Etm = A1PAR/cosZ + A2e-kwm + A3e-S/Q + A0 (3)
Fig. 3 Observed and calculated (‘obs’and ‘cal’, respectively) isoprene emission fluxes in Changbai temperate forest
Fig. 4 Observed and calculated mean "diurnal variation" of isoprene for 2010 and 2011 growing seasons in Changbai temperate forest
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• Isoprene model can capture most diurnal variation patterns of isoprene
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Fig. 5 Isoprene simulations by using empirical models (3-Factor, 2-Factor ), MEGAN model (Iso 3F, Iso 2F, Iso M) and measured emissions (Iso obs) in 2011 growing season in Changbai temperate forest. • Mean hourly emissions in 2010 and 2011 growing seasons: 1.71 and 1.55 mgm-2h-1 for isoprene, 0.48 and 0.47 mgm-2h-1 for monoterpenes.
3.2 Simulation results：hourly emission
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Fig. 6 Monthly mean diurnal variations of isoprene emission in 2011 growing season in Changbai Mountain temperate forest
3.2 Simulation results: monthly mean diurnal variation
• Total emission in growing season:
isoprene=1239.1, MT=340.4 (2011); isoprene=1283.5, MT=349.7 mgm-2 (2010)
The emission decreases of isoprene and monoterpenes (MT) from 2010 to 2011 associated with the temperature decreasing by -6.6% and water vapor decreasing by -7.6%, PAR increasing by 8.5% and S/Q increasing by 3.8%.
• Similar simulations of isoprene and monoterpene emissions were obtained in subtropical bamboo forest as Changbai Mountain temperate forest.
3.4 Isoprene emission model in the Inner Mongolia grassland
e-k1Et/m = -0.12 PAR +0.07 e-k2wm -0.003e-S/D +0.96 (4)
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Fig. 7 The calculated and measured emission fluxes of isoprene in 2002 and 2003 in the Inner Mongolia grassland
• Simulation result: the relative biases of 65% estimated emissions were within 50% of measured fluxes.
• BVOC emissions at standard conditions
Sites Isoprene mg m-2
Monoterpenes mg m-2
Time period
Inner Mongolia grassland
0.48
June - Aug., 2002
Changbai temperate forest
2.50 0.40 June, 2010 - Sep., 2011
LinAn subtropical bamboo forast
4.28 0.13 July, 2013 – Jan., 2014
3.5 BVOC emissions in different ecosystems (normalized to standard conditions)
Based on isoprene emission model, isoprene emission normalized to standard conditions (light=1500μmolm-2s-1, temperature=30℃) for June to August, 2002 was 482.8 μgm-2h-1 (in average), ranged from 413.6 to 539.4 μgm-2h-1. It is close to 500 μgm-2h-1 calculated by algorithms of Guenther et al. (2006).
Table 1 BVOC emission factors of different ecosystems at standard conditions
4. GC-FID system/technique for BVOC analysis (collaborated with James Greenberg, NCAR, USA)
y = 23.717xR2 = 0.9829
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Fig. 8 Concentration*Volume vs area using heptane as a standard gas, Response factor=23.717
4.1 Response factor was determined by analyzing heptane and diluting it from 10.4 ppm to different concentrations
4.2 Good reproducibility was obtained by analyzing isoprene and monoterpene mixtures
Run 1
Run 2
Isoprene α- pinene
β-pinene
camphene
limonene
Fig. 9 Gas chromatogram of BVOCs
Species Retention Time
Peak Area Run 1
Peak Area Run 2
Ratio of peak area Run2/Run1
Isoprene 5.557 66792 66222 0.991 α-pinene 14.143 51676.1 51395.7 0.995 camphene 14.574 60780 60633.1 0.998 β-pinene 15.115 62743.7 62623.8 0.998 limonene 15.955 118999 120311 1.011
• Reproducibility of identified BVOCs by using GC-FID
• BVOC emissions emitted form Qianyanzhou subtropical plantations limonene
Isoprene
• Higher limonene emission than isoprene.
• Dominant trees: pinus elliottii, Pinus massoniana.
Table 2. Retention time, peak areas of BVOCs and their ratios for 2 runs
Fig. 10 Gas chromatogram of BVOCs in Qianyanzhou forest
5. Routine observations of trace gases, solar radiation, meteorological parameters, particles, AOD
1) Trace gases – (O3, NO, NO2, SO2), solar radiation (including solar global radiation, solar direct and scattered radiation, UV, PAR, etc.), meteorological parameters, particles (PM2.5), AOD were carried out at some sites in China.
These sites include Xinglong station and Xianghe station in Hebei province. Changbai Mountaians forest in Jilin province, Linan bamboon forest in Zhejiang province, Qianyanzhou forest in Jiangxi province. 2) Some surface measurements of trace gases and particles were provided for the validation
of models. Good results were achieved.
Qianyanzhou station Qianyanzhou station Xinglong station
•Measurements of trace gases and particulate meter (NOx, SO2, O3, PM2.5) were carried out from 2005 to 2014 at Xinglong.
Instruments: O3(49C), NOx(42CTL), SO2(43C) - TE company PM2.5 - RP1400; Visibility- SVS1, EnviroTech sensor company •With the fast development of industry, traffic, economy and agriculture, air pollution is becoming more and more serious issue in Beijing and in North China, and should be solved. Therefore, it is necessary to investigate current situation and long-term variation of air quality at an atmospheric background site over this region.
Long-term variations of trace gases and particulate matter at Xinglong station (II) Xinglong Station: 40o24’N,117o30’E, 940 m, ~ 150 km away from Beijing city. an atmospheric background station in North China
Fig.1 Location of Xinglong station
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Fig. 2 Monthly concentrations of trace gases (NO,NO2,SO2,O3) at Xinglong station from May 2005 to January 2015 • Variation trends per year: NO2: - 3.37%; SO2: - 0.78%; O3: +1.71%
1. Long-term variations of NOX, SO2 and O3 at Xinglong station
Fig. 3 Annual mean concentrations of particulate mater（PM2.5）at Xinglong station from 2009 to 2015 • PM2.5 indicated an increase trend at the rate of 0.91% per year.
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3. Mechanism analysis: why NO2 and SO2 decrease, PM2.5 increase? AVOCs+BVOCs + OH + other GLPs (NO2,SO2…) → New GLPs（O3, PAN, PM2.5…） • To control air pollution in Beijing and North China, we should 1) control all source emissions of anthropogenic volatile organic
compounds (AVOCs) primarily 2) control all source emissions of NOx and SO2, so as to decrease
the reactants taking part in the chemical and photochemical reactions in the atmosphere and the formation of secondary pollutants, e.g., O3 and PM2.5.
Fig. 4 The car number and planting area in Beijing region from 1978 to 2014 0.0E+00
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Fig. 4 Monthly average of O3×NO2×SO2 and monthly concentrations of PM2.5 and O3 at Xinglong station from May 2005 to January 2015 • There were similar variations of monthly PM2.5 and O3×NO2×SO2; • It is essential to control the emissions of main pollutants (including
primary and secondary pollutants) in controlling PM2.5 pollution. • O3 photochemical pollution should be controlled, especially in summer.
4. Relations of O3×NO2×SO2 and PM2.5 at Xinglong station
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• List of Publications •Bai Jianhui, 2014. Isoprene and its energy role in the atmospheric photochemical processes, Advances in Geosciences, 4, 319-334.
•Bai Jianhui. 2015. Estimation of the isoprene emission from the Inner Mongolia grassland, Atmospheric Pollution Research, 6, 406-414, doi: 10.5094/APR.2015.045.
•Bai Jianhui, Alex Guenther, Andrew Turnipseed, Tiffany Duhl, 2015. Seasonal and interannual variations in whole–ecosystem isoprene and monoterpene emissions from a temperate mixed forest in Northern China. Atmospheric Pollution Research. 6.
•Bai Jianhui. 2015. Study on Solar Spectral Radiation and Calculating Method of Photosynthetically Active Radiation at Baikal Lake. Advances in Geosciences, 33-42. DOI:10.12677/AG.2015.52005.
•Bai Jianhui,Wu Yimei,Chai Wenhai,Wang Pucai,Wang Gengchen. Long-term variation of trace gases and particulate mater at an atmospheric background station in North China. Advances in Geosciences (Accepted).
•Bai Jianhui, Andrew Turnipseed, Tiffany Duhl, Nan Hao. Biogenic volatile compound emissions from a temperate forest, China: model simulation. Journal of Atmospheric Chemistry (Accepted).
Conclusions
1) BVOC emission studies were carried out in some ecosystems in China
2) BVOC emission fluxes were obtained
3) Empirical emission models of BVOCs were developed, the simulated BVOC emissions were in agreement with the observations and MEGAN model.
4) Long-term variations of trace gases and particulate mater in recent 10 years at Xinglong station were analyzed, we propose suggestions to control particulate mater and O3 pollution.
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