Similarly to the emissions of other measured conifer tree species, the terpenoid emissions of L. sibirica (Paper I) and L. cajanderi (Paper II) were dominated by monoterpenes (about 60−90% of the total). Substantial sesquiterpene emissions (about 10%) were detected fromL. sibirica. Substantial emissions of linalool emission were detected forL.
cajanderi, especially in June. In case of L. sibirica, the most emitted monoterpene was sabinene followed by ∆3-carene, α- and β-pinene. The monoterpene emission spectra ofL.
cajanderi were similar to the emission spectra of other conifer tree speciesP. abiesandP.
sylvestris as it was dominated by ∆3-carene, α- and β-pinene. The monoterpene emission potentials using the pool algorithm with constant β were 5.2−21, 1.5−2.2 and 0.46−19 µg gdw-1 h-1 forL. sibiricaand the two L. cajanderitrees A and B, respectively. In case ofL.
cajanderi, the emission potentials were of the same magnitude as those reported for other boreal tree species, while the emission potentials ofL. sibiricawere higher than those of other boreal trees. Also relatively high sesquiterpene emission potential of 0.40−1.8 was found forL. sibirica.
When interpreting our emission measurements of theLarix species, one should keep in mind that emissions of only oneL. sibirica and twoL. cajanderi trees were measured, and based on our results we cannot conclude anything about the intra species variation on the emissions. Besides, the young age of the L. sibirica sapling may have influenced the emission spectra. According to the study on twoL. cajanderi trees, it seems that there can be substantial variation in the magnitude of the emission rates. Also the emission spectra of different individual trees can vary substantially as shown by Bäck et al. (2012).
Considering that all the trees studied by Bäck et al. (2012) were growing in the same place, one could expect large intra-species variation in the emissions of the same tree species growing in different locations. Thus, while our results give good first estimates on the emissions ofLarix species, more measurements are still needed.
Paper III presents our method for PTR-MS calibration and VMR calculation, and it showed that when PTR-MS is used for long-term ambient measurement, it needs to be calibrated regularly with a standard VOC mixture in order to maintain the accuracy of the measurements. As in most cases, it is not possible to calibrate PTR-MS for all the compounds one wants to measure; we, therefore, presented a way to determine an instrument specific relative transmission curve, which can be used for calculating VMRs of compounds that are not calibrated. This automatic and straightforward method enables consistent data analysis, which is important when long-term measurements are carried out.
When ambient concentrations of methanol, acetaldehyde, acetone, benzene and toluene were measured simultaneously with two PTR-MS and two GC-MS instruments at SMEAR II (Paper V), a robust correlation was found for benzene and acetone measurements between all instrument pairs. The mean correlation coefficient was 0.88 and the slope values were reasonably close to unity for both compounds. For acetaldehyde and toluene, the correlation was only moderate, with average correlation coefficients of 0.50 and 0.62, respectively. In case of acetaldehyde, we could not find any clear reason for the weak correlation. Toluene concentrations were below the detection limits of the PTR-MS instruments for a considerable amount of the time, which biased the compared
concentrations towards higher values and additionally reduced the amount of data points used in the analysis. Despite a very strong correlation between the methanol measurements of different instruments (meanR = 0.90), the slope values were far from unity, with an RMS difference of 0.87 from the 1:1 line. Thus, all instruments captured the methanol concentrations well, but one should regard the quantitative concentration with caution. It is important to keep in mind that, when the deviation of the correlation slopes from unity originates from uncertainty in the instrument sensitivity, the emission measurements of these compounds also have similar uncertainty. This applies to e.g. eddy covariance, surface layer gradient and chamber techniques. The results of this study show that when performing long-term ambient measurements, occasional comparison measurements are needed in order to validate the measured concentration, even if regular calibration is performed.
A negative aerosol-climate effect, which is driven by the increase of BVOC emissions due to climate warming, was hypothesized inPaper V. This cooling feedback may affect the outcomes of anthropogenic emission restriction policies, by potentially decreasing the expected climate warming impact due to decreased anthropogenic emissions. Based on our analysis the minimum level of theB100 is set by the formation of biogenic SOA. Thus, even if the emissions of both aerosol particles and their precursors are reduced by regulation, part of the aerosol cooling effect will remain. This is especially true in the boreal zone. In order to fully understand the strength of the cooling, better understanding on the sources and formation processes of both biogenic and anthropogenic aerosol particles is needed. It is particularly important to know by how much the BVOC emissions will increase.
Additional studies on the temperature dependence ofN100 are needed, especially in tropics, subtropics and isoprene-rich environments. It should also be kept in mind that increasing BVOC emissions may have warming climate effects as well, for example via extending the methane lifetime and thus strengthening the warming greenhouse effect.
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