Abstract. We describe the implementation of a biochemical model of isoprene emission that depends on the electron requirement for isoprene synthesis into the Farquhar–Ball–Berry leaf model of photosynthesis and stomatal conductance that is embedded within a global chemistry-climate simulation framework. The isoprene production is calculated as a function of electron transport-limited photosynthesis, intercellular and atmospheric carbon dioxide concentration, and canopy temperature. The vegetation biophysics module computes the photosynthetic uptake of carbon dioxide coupled with the transpiration of water vapor and the isoprene emission rate at the 30 min physical integration time step of the global chemistry-climate model. In the model, the rate of carbon assimilation provides the dominant control on isoprene emission variability over canopy temperature. A control simulation representative of the present-day climatic state that uses 8 plant functional types (PFTs), prescribed phenology and generic PFT-specific isoprene emission potentials (fraction of electrons available for isoprene synthesis) reproduces 50% of the variability across different ecosystems and seasons in a global database of 28 measured campaign-average fluxes. Compared to time-varying isoprene flux measurements at 9 select sites, the model authentically captures the observed variability in the 30 min average diurnal cycle (R2 = 64–96%) and simulates the flux magnitude to within a factor of 2. The control run yields a global isoprene source strength of 451 TgC yr−1 that increases by 30% in the artificial absence of plant water stress and by 55% for potential natural vegetation.
Abstract. All eddy-covariance flux measurements are associated with random uncertainties which are a combination of sampling error due to natural variability in turbulence and sensor noise. The former is the principal error for systems where the signal-to-noise ratio of the analyser is high, as is usually the case when measuring fluxes of heat, CO2 or H2O. Where signal is limited, which is often the case for measurements of other trace gases and aerosols, instrument uncertainties dominate. We are here applying a consistent approach based on auto- and cross-covariance functions to quantifying the total random flux error and the random error due to instrument noise separately. As with previous approaches, the random error quantification assumes that the time-lag between wind and concentration measurement is known. However, if combined with commonly used automated methods that identify the individual time-lag by looking for the maximum in the cross-covariance function of the two entities, analyser noise additionally leads to a systematic bias in the fluxes. Combining datasets from several analysers and using simulations we show that the method of time-lag determination becomes increasingly important as the magnitude of the instrument error approaches that of the sampling error. The flux bias can be particularly significant for disjunct data, whereas using a prescribed time-lag eliminates these effects (provided the time-lag does not fluctuate unduly over time). We also demonstrate that when sampling at higher elevations, where low frequency turbulence dominates and covariance peaks are broader, both the probability and magnitude of bias are magnified. We show that the statistical significance of noisy flux data can be increased (limit of detection can be decreased) by appropriate averaging of individual fluxes, but only if systematic biases are avoided by using a prescribed time-lag. Finally, we make recommendations for the analysis and reporting of data with low signal-to-noise and their associated errors.
Abstract. This paper reports the fluxes and mixing ratios of biogenically emitted volatile organic compounds (BVOCs) 4 m above a mixed oak and hornbeam forest in northern Italy. Fluxes of methanol, acetaldehyde, isoprene, methyl vinyl ketone + methacrolein, methyl ethyl ketone and monoterpenes were obtained using both a proton transfer reaction-mass spectrometer (PTR-MS) and a proton transfer reaction-time of flight-mass spectrometer (PTR-ToF-MS) together with the methods of virtual disjunct eddy covariance (PTR-MS) and eddy covariance (PTR-ToF-MS). Isoprene was the dominant emitted compound with a mean day-time flux of 1.9 mg m-2 h-1. Mixing ratios, recorded 4 m above the canopy, were dominated by methanol with a mean value of 6.2 ppbv over the 28 day measurement period. Comparison of isoprene fluxes calculated using the PTR-MS and PTR-ToF-MS showed very good agreement while comparison of the monoterpene fluxes suggested a slight over estimation of the flux by the PTR-MS. A basal isoprene emission rate for the forest of 1.7 mg m-2 h-1 was calculated using the MEGAN isoprene emissions algorithms (Guenther et al., 2006). A detailed tree species distribution map for the site enabled the leaf-level emissions of isoprene and monoterpenes recorded using GC-MS to be scaled up to produce a "bottom-up" canopy-scale flux. This was compared with the "top-down" canopy-scale flux obtained by measurements. For monoterpenes, the two estimates were closely correlated and this correlation improved when the plant species composition in the individual flux footprint was taken into account. However, the bottom-up approach significantly underestimated the isoprene flux, compared with the top-down measurements, suggesting that the leaf-level measurements were not representative of actual emission rates.
Odours can have a significant influence on the outcome of social interactions. However, we have yet to characterize the chemical signature of any specific social cue in human body odour, and we know little about how changes in the social context influence odour chemistry. Here, we argue that adoption of emerging analytical techniques from other disciplines, such as atmospheric chemistry, might become game-changing tools in this endeavour. First, we describe the use of online chemical ionization time-of-flight mass spectrometry to sensitively measure many hundreds of gas-phase volatile organic compounds in real time. By analysing ambient air emanating from undisturbed individuals or groups, the technique enables a continuous recording of an instantaneous odour change in response to external stimuli and changing the social context. This has considerable advantages over the traditional approach of periodic sampling for analysis by gas chromatography. We also discuss multivariate statistical approaches, such as positive matrix factorization, that can effectively sift through this complex datastream to identify linked groups of compounds that likely underpin functional chemosignals. In combination, these innovations offer new avenues for addressing outstanding questions concerning olfactory communication in humans and other species, as well as in related fields using odour, such as biometrics and disease diagnostics.This article is part of the Theo Murphy meeting issue ‘Chemical communication in humans’.
Full text of Abstract : Fluxes of volatile organic compounds were measured above tropical rainforest and oil palm plantation in the Malaysian state of Sabah on the island of Borneo. During April and July 2008 an Ionikon proton transfer reaction mass spectrometer (ptrms) was operated at the 100 m Global Atmospheric Watch (GAW) tower at Bukit Atur, at the edge of the Danum Valley conservation area. An ultrasonic anemometer and air inlet were mounted at 76 m, with the ptrms housed in a laboratory building at the foot of the tower, measuring fluxes over tropical rainforest (selectively logged in 1989) with a typical canopy height of 30 to 40 m. In addition, during the July period, a second ptrms was coupled to a lift system which automatically moved an inlet to sample in-canopy gradients inside the forest canopy, between 2 and 30 m. During May 2008, the ptrms was moved to an oil palm plantation, north of the town of Lahad Datu, were fluxes were measured at a height of 15 m above the 12 m tall canopy, together with concentrations and fluxes of ozone and aerosols. These measurements formed part of two major UK projects: OP3-Danum-2008 (Oxidant and Particle Production Processes above South East Asian Rainforest) was aimed at quantifying biogenic emissions and evaluating their impact on air chemistry and the production of photo-oxidants and biogenic secondary organic aerosol, while ACES (Aerosol Coupling in the Earth System) studies the role of primary biogenic emissions, in-canopy processes and the effect of land-use change on aerosols. Initial results indicate that fluxes of isoprene above forest averaged 1.4 mg m-2 s-1 which is somewhat smaller than previous measurements in Amazonia and than previous estimates derived from leaf- level measurements, reflecting uncertainties in the assumed plant species composition. Concentrations peaked at the top of the canopy during midday. With an average of 5.5 mg m-2s-1, isoprene fluxes above the oil palm plantation were four times larger. Average fluxes of total monoterpenes were 0.15 mg m-2 s-1 at the forest site and 0.85 mg m-2 s-1 above oil palm. Fluxes of isoprene oxidation products (MVK + MACR) were upwards above forest and downward above oil palm, indicating that the high measurement height on the GAW tower provided more time for chemical conversion. Particle number fluxes above forest showed periods of apparent emission during midday indicative of VOC emissions resulting in particle growth.
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