Measurements of OVOC fluxes by eddy covariance using a proton-transfer-reaction mass spectrometer – method development at a coastal site

We present here vertical fluxes of oxygenated volatile organic compounds (OVOCs) measured with eddy covariance (EC) during the period of March to July 2012 near the southwest coast of the United Kingdom. The performance of the proton-transfer-reaction mass spectrometer (PTR-MS) for flux measurement is characterized, with additional considerations given to the homogeneity and stationarity assumptions required by EC. Observed mixing ratios and fluxes of OVOCs (specifically methanol, acetaldehyde, and acetone) vary significantly with time of day and wind direction. Higher mixing ratios and fluxes of acetaldehyde and acetone are found in the daytime and from the direction of a forested park, most likely due to light-driven emissions from terrestrial plants. Methanol mixing ratio and flux do not demonstrate consistent diel variability, suggesting sources in addition to plants. We estimate air-sea exchange and photochemical rates of these compounds, which are compared to measured vertical fluxes. For acetaldehyde, the mean (1 sigma) mixing ratio of 0.13 (0.02) ppb at night may be maintained by oceanic emission, while photochemical destruction out-paces production during the day. Air-sea exchange and photochemistry are probably net sinks of methanol and acetone in this region. Their nighttime mixing ratios of 0.46 (0.20) and 0.39 (0.08) ppb appear to be affected more by terrestrial emissions and long-distance transport, respectively.

The REFLEX project: Comparing different algorithms and implementations for the inversion of a terrestrial ecosystem model against eddy covariance data

We describe a model-data fusion (MDF) inter-comparison project (REFLEX), which compared various algorithms for estimating carbon (C) model parameters consistent with both measured carbon fluxes and states and a simple C model. Participants were provided with the model and with both synthetic net ecosystem exchange (NEE) of CO2 and leaf area index (LAI) data, generated from the model with added noise, and observed NEE and LAI data from two eddy covariance sites. Participants endeavoured to estimate model parameters and states consistent with the model for all cases over the two years for which data were provided, and generate predictions for one additional year without observations. Nine participants contributed results using Metropolis algorithms, Kalman filters and a genetic algorithm. For the synthetic data case, parameter estimates compared well with the true values. The results of the analyses indicated that parameters linked directly to gross primary production (GPP) and ecosystem respiration, such as those related to foliage allocation and turnover, or temperature sensitivity of heterotrophic respiration, were best constrained and characterised. Poorly estimated parameters were those related to the allocation to and turnover of fine root/wood pools. Estimates of confidence intervals varied among algorithms, but several algorithms successfully located the true values of annual fluxes from synthetic experiments within relatively narrow 90% confidence intervals, achieving >80% success rate and mean NEE confidence intervals <110 gC m−2 year−1 for the synthetic case. Annual C flux estimates generated by participants generally agreed with gap-filling approaches using half-hourly data. The estimation of ecosystem respiration and GPP through MDF agreed well with outputs from partitioning studies using half-hourly data. Confidence limits on annual NEE increased by an average of 88% in the prediction year compared to the previous year, when data were available. Confidence intervals on annual NEE increased by 30% when observed data were used instead of synthetic data, reflecting and quantifying the addition of model error. Finally, our analyses indicated that incorporating additional constraints, using data on C pools (wood, soil and fine roots) would help to reduce uncertainties for model parameters poorly served by eddy covariance data.

Identification of micro-scale anthropogenic CO2, heat and moisture sources – processing eddy covariance fluxes for a dense urban environment

Anthropogenic emissions of heat and exhaust gases play an important role in the atmospheric boundary layer, altering air quality, greenhouse gas concentrations and the transport of heat and moisture at various scales. This is particularly evident in urban areas where emission sources are integrated in the highly heterogeneous urban canopy layer and directly linked to human activities which exhibit significant temporal variability. It is common practice to use eddy covariance observations to estimate turbulent surface fluxes of latent heat, sensible heat and carbon dioxide, which can be attributed to a local scale source area. This study provides a method to assess the influence of micro-scale anthropogenic emissions on heat, moisture and carbon dioxide exchange in a highly urbanized environment for two sites in central London, UK. A new algorithm for the Identification of Micro-scale Anthropogenic Sources (IMAS) is presented, with two aims. Firstly, IMAS filters out the influence of micro-scale emissions and allows for the analysis of the turbulent fluxes representative of the local scale source area. Secondly, it is used to give a first order estimate of anthropogenic heat flux and carbon dioxide flux representative of the building scale. The algorithm is evaluated using directional and temporal analysis. The algorithm is then used at a second site which was not incorporated in its development. The spatial and temporal local scale patterns, as well as micro-scale fluxes, appear physically reasonable and can be incorporated in the analysis of long-term eddy covariance measurements at the sites in central London. In addition to the new IMAS-technique, further steps in quality control and quality assurance used for the flux processing are presented. The methods and results have implications for urban flux measurements in dense urbanised settings with significant sources of heat and greenhouse gases.

Multi-season eddy covariance observations of energy, water and carbon fluxes over a suburban area in Swindon, UK

Eddy covariance measurements of the turbulent sensible heat, latent heat and carbon dioxide fluxes for 12 months (2011–2012) are reported for the first time for a suburban area in the UK. The results from Swindon are comparable to suburban studies of similar surface cover elsewhere but reveal large seasonal variability. Energy partitioning favours turbulent sensible heat during summer (midday Bowen ratio 1.4–1.6) and latent heat in winter (0.05–0.7). A significant proportion of energy is stored (and released) by the urban fabric and the estimated anthropogenic heat flux is small but non-negligible (0.5–0.9 MJ m−2 day−1). The sensible heat flux is negative at night and for much of winter daytimes, reflecting the suburban nature of the site (44% vegetation) and relatively low built fraction (16%). Latent heat fluxes appear to be water limited during a dry spring in both 2011 and 2012, when the response of the surface to moisture availability can be seen on a daily timescale. Energy and other factors are more relevant controls at other times; at night the wind speed is important. On average, surface conductance follows a smooth, asymmetrical diurnal course peaking at around 6–9 mm s−1, but values are larger and highly variable in wet conditions. The combination of natural (vegetative) and anthropogenic (emission) processes is most evident in the temporal variation of the carbon flux: significant photosynthetic uptake is seen during summer, whilst traffic and building emissions explain peak release in winter (9.5 g C m−2 day−1). The area is a net source of CO2 annually. Analysis by wind direction highlights the role of urban vegetation in promoting evapotranspiration and offsetting CO2 emissions, especially when contrasted against peak traffic emissions from sectors with more roads. Given the extent of suburban land use, these results have important implications for understanding urban energy, water and carbon dynamics.

Multi-scale sensible heat fluxes in the urban environment from large aperture scintillometry and eddy covariance

Sensible heat fluxes (QH) are determined using scintillometry and eddy covariance over a suburban area. Two large aperture scintillometers provide spatially integrated fluxes across path lengths of 2.8 km and 5.5 km over Swindon, UK. The shorter scintillometer path spans newly built residential areas and has an approximate source area of 2-4 km2, whilst the long path extends from the rural outskirts to the town centre and has a source area of around 5-10 km2. These large-scale heat fluxes are compared with local-scale eddy covariance measurements. Clear seasonal trends are revealed by the long duration of this dataset and variability in monthly QH is related to the meteorological conditions. At shorter time scales the response of QH to solar radiation often gives rise to close agreement between the measurements, but during times of rapidly changing cloud cover spatial differences in the net radiation (Q*) coincide with greater differences between heat fluxes. For clear days QH lags Q*, thus the ratio of QH to Q* increases throughout the day. In summer the observed energy partitioning is related to the vegetation fraction through use of a footprint model. The results demonstrate the value of scintillometry for integrating surface heterogeneity and offer improved understanding of the influence of anthropogenic materials on surface-atmosphere interactions.

Daytime CO2 urban surface fluxes from airborne measurements, eddy-covariance observations and emissions inventory in Greater London

Airborne measurements within the urban mixing layer (360 m) over Greater London are used to quantify CO2 emissions at the meso-scale. Daytime CO2 fluxes, calculated by the Integrative Mass Boundary Layer (IMBL) method, ranged from 46 to 104 μmol CO2 m−2 s−1 for four days in October 2011. The day-to-day variability of IMBL fluxes is at the same order of magnitude as for surface eddy-covariance fluxes observed in central London. Compared to fluxes derived from emissions inventory, the IMBL method gives both lower (by −37%) and higher (by 19%) estimates. The sources of uncertainty of applying the IMBL method in urban areas are discussed and guidance for future studies is given.

Methodical study of nitrous oxide eddy covariance measurements using quantum cascade laser spectrometery over a Swiss forest

Nitrous oxide fluxes were measured at the Lägeren CarboEurope IP flux site over the multi-species mixed forest dominated by European beech and Norway spruce. Measurements were carried out during a four-week period in October–November 2005 during leaf senescence. Fluxes were measured with a standard ultrasonic anemometer in combination with a quantum cascade laser absorption spectrometer that measured N2O, CO2, and H2O mixing ratios simultaneously at 5 Hz time resolution. To distinguish insignificant fluxes from significant ones it is proposed to use a new approach based on the significance of the correlation coefficient between vertical wind speed and mixing ratio fluctuations. This procedure eliminated roughly 56% of our half-hourly fluxes. Based on the remaining, quality checked N2O fluxes we quantified the mean efflux at 0.8±0.4 μmol m−2 h−1 (mean ± standard error). Most of the contribution to the N2O flux occurred during a 6.5-h period starting 4.5 h before each precipitation event. No relation with precipitation amount could be found. Visibility data representing fog density and duration at the site indicate that wetting of the canopy may have as strong an effect on N2O effluxes as does below-ground microbial activity. It is speculated that above-ground N2O production from the senescing leaves at high moisture (fog, drizzle, onset of precipitation event) may be responsible for part of the measured flux.