Eddy-covariance data with low signal-to-noise ratio:time-lag determination, uncertainties and limit of detection

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. Here, we are applying a consistent approach based on auto- and cross-covariance functions to quantify 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 data sets 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

Volatile organic compound fluxes and concentrations in London (ClearfLo)

Volatile organic compounds (VOCs) from anthropogenic sources such as fuel combustion or evaporative emissions can directly and indirectly affect human health. Some VOCs, such as benzene and 1,3- butadiene are carcinogens. These and other VOCs contribute to the formation of ozone (O3) and aerosol particles, which have effects on human health and the radiative balance of the atmosphere. Although in the UK VOC emissions are subject to control under European Commission Directive 2008/50/EC and emission reducing echnologies have been implemented, urban air pollution remains a concern. Urban air quality is likely to remain a priority since currently >50% of the global population live in urban areas with trends in urbanization and population migration predicted to increase. The ClearfLo project is a large multi-institutional consortium funded by the UK Natural Environment Research Council (NERC) and provides integrated measurements of meteorology, gas phase and particulate composition of the atmosphere over London. Both long term and IOP measurements were made at street and elevated locations at a range of sites across London and its surroundings during 2011 and 2012. Mixing ratios of a selection of nine VOCs were measured using a high sensitivity proton transfer reaction-mass spectrometer (PTR-MS) at a ground level urban background (North Kensington) and kerbside (Marylebone Road) site during the winter IOP. VOC fluxes were measured by virtually disjunct eddy covariance (vDEC) at an elevated urban site (King’s College Strand) in Aug-Dec 2012. Our results for the first IOP showed that most of the selected compound concentrations depended on traffic emissions, although there was a marked difference between the urban ackground and kerbside sites. We identified some temperature effects on VOC concentrations. We also present the first analyses of VOC flux measurements over London. Preliminary analyses indicate most compounds associated with vehicle emissions closely followed diurnal traffic counts. Fluxes of isoprene and methanol appear to be controlled by light intensity and temperature, consistent with a redominantly biogenic source of these compounds

Seasonal and diurnal trends in concentrations and fluxes of volatile organic compounds in central London

Concentrations and fluxes of seven volatile organic compounds (VOCs) were measured between August and December 2012 at a rooftop site in central London as part of the ClearfLo project (Clean Air for London). VOC concentrations were quantified using a proton transfer reaction mass spectrometer (PTR-MS) and fluxes were calculated using a virtual disjunct eddy covariance technique. The median VOC fluxes, including aromatics, oxygenated compounds and isoprene, ranged from 0.07 to 0.33 mgm&#x100000;^-2 h^-&#x100000;1. Median mixing ratios were 7.3 ppb for methanol and < 1 ppb for the other compounds. Strong relationships were observed between the fluxes and concentrations of some VOCs with traffic density and between the fluxes and concentrations ofisoprene and oxygenated compounds with photosynthetically active radiation (PAR) and temperature. An estimated 50–90% of the fluxes of aromatic VOCs were attributable to traffic activity, which showed little seasonal variation, suggesting that boundary layer effects or possibly advected pollutionmay be the primary causes of increased concentrations of aromatics in winter. Isoprene, methanol and acetaldehyde fluxes and concentrations in August and September showed high correlations with PAR and temperature, when fluxes andconcentrations were largest suggesting that biogenic sources contributed to their fluxes. Modelled biogenic isoprene fluxes from urban vegetation using the Guenther et al. (1995) algorithm agreed well with measured fluxes in August andSeptember. Comparisons of estimated annual benzene emissions from both the London and the National Atmospheric Emissions Inventories agreed well with measured benzene fluxes. Flux footprint analysis indicated emission sourceswere localised and that boundary layer dynamics and source strengths were responsible for temporal and spatial VOC flux and concentration variability during the measurement period

Modelling chemistry in the nocturnal boundary layer above tropical rainforest and a generalised effective nocturnal ozone deposition velocity for sub-ppbv NOx conditions

Measurements of atmospheric composition have been made over a remote rainforest landscape. A box model has previously been demonstrated to model the observed daytime chemistry well. However the box model is unable to explain the nocturnal measurements of relatively high [NO] and [O3], but relatively low observed [NO2]. It is shown that a one-dimensional (1-D) column model with simple O3 -NOx chemistry and a simple representation of vertical transport is able to explain the observed nocturnal concentrations and predict the likely vertical profiles of these species in the nocturnal boundary layer (NBL). Concentrations of tracers carried over from the end of the night can affect the atmospheric chemistry of the following day. To ascertain the anomaly introduced by using the box model to represent the NBL, vertically-averaged NBL concentrations at the end of the night are compared between the 1-D model and the box model. It is found that, under low to medium [NOx] conditions (NOx <1 ppbv), a simple parametrisation can be used to modify the box model deposition velocity of ozone, in order to achieve good agreement between the box and 1-D models for these end-of-night concentrations of NOx and O3. This parametrisation would could also be used in global climate-chemistry models with limited vertical resolution near the surface. Box-model results for the following day differ significantly if this effective nocturnal deposition velocity for ozone is implemented; for instance, there is a 9% increase in the following day’s peak ozone concentration. However under medium to high [NOx] conditions (NOx > 1 ppbv), the effect on the chemistry due to the vertical distribution of the species means no box model can adequately represent chemistry in the NBL without modifying reaction rate constants

Tall tower measurements of methane, carbon monoxide and carbon dioxide emissions in London, UK

London, with a population of 8.2 million, is the largest city in Europe. It is heavily built-up (typically 8% vegetation cover within the central boroughs) and boasts some of the busiest arteries in Europe despite efforts to reduce traffic in the city centre with the introduction of a congestion charging scheme in 2007. We report on over two years of continuous measurements atop a tall tower in the heart of London between October 2011 and present. Fluxes of methane (CH4), carbon monoxide (CO) and carbon dioxide (CO2) are measured by eddy-covariance from the top of the British Telecom (BT) tower in central London (51° 31’ 17.4” N, 0° 8’ 20.04” W). The eddy-covariance system consists of a Gill R3-50 ultrasonic anemometer located 192 m above street level , a Picarro G2301-f cavity ring-down spectrometer for the measurement of CH4, CO2 and water, and an Aero-Laser AL5002 carbon monoxide analyser. Air is sampled 0.3 m below the sensor head of the ultrasonic anemometer and pulled down 45 m of 12.7 mm OD Teflon tubing. CO2 emissions were found to be mainly controlled by fossil fuel combustion (e.g. traffic, commercial and domestic heating) and diurnal averages of CO2 fluxes are highly correlated to traffic. However changes in heating-related natural gas consumption and, to a lesser extent, photosynthetic activity in two large city centre green spaces (Hyde Park and Regent’s Park) explained the seasonal variability. Annual estimates of net exchange of CO2 (41 ktons m-2) obtained by eddy-covariance agreed well with up-scaled data from the UK National Atmospheric Emissions Inventory (NAEI). CO fluxes were correlated to both CO2 and CH4; the estimated net emissions of CO for 2013 were 156 ± 40 tons km-2 which is in reasonable agreement with the 2012 London Atmospheric Emissions Inventory (LAEI) value of 90 tons km-2 and with independent measurement-based estimates which report a range of 105 to 220 tons km-2 (Harrison et al., 2012; O’Shea et al., 2014). Methane emissions from central London exhibit diurnal trends both for concentrations and fluxes. Fluxes are strongly correlated to those of carbon dioxide and although flux ratios exhibit diurnal cycles they are relatively constant on an annual basis. The baseline for methane fluxes is thought to result from leaks in the natural gas distribution network at a rate of 30 tons km-2 yr-1. However, a two- to three-fold difference was found between inventory and measured total fluxes, which could indicate an underestimation of CH4 emissions from combustion sources by the inventory (e.g. road traffic, domestic and commercial heating). Central London methane emissions are estimated at 70 tons km-2 yr-1 and the global warming effect of CO2 was found to be 25 times greater than that of CH4 (100-year horizon). References: Harrison et al., 2012, Atmospheric Chemistry and Physics, 12(6), 3065-3114. O’Shea et al., 2014, Journal of Geophysical Research: Atmospheres, 119(8), 4940–4952

Process-based modelling of NH3 exchange with grazed grasslands

In this study the GAG model, a process-based ammonia (NH3) emission model for urine patches, was extended and applied for the field scale. The new model (GAG_field) was tested over two modelling periods, for which micrometeorological NH3 flux data were available. Acknowledging uncertainties in the measurements, the model was able to simulate the main features of the observed fluxes. The temporal evolution of the simulated NH3 exchange flux was found to be dominated by NH3 emission from the urine patches, offset by simultaneous NH3 deposition to areas of the field not affected by urine. The simulations show how NH3 fluxes over a grazed field in a given day can be affected by urine patches deposited several days earlier, linked to the interaction of volatilization processes with soil pH dynamics. Sensitivity analysis showed that GAG_field was more sensitive to soil buffering capacity (β), field capacity (θfc) and permanent wilting point (θpwp) than the patch-scale model. The reason for these different sensitivities is dual. Firstly, the difference originates from the different scales. Secondly, the difference can be explained by the different initial soil pH and physical properties, which determine the maximum volume of urine that can be stored in the NH3 source layer. It was found that in the case of urine patches with a higher initial soil pH and higher initial soil water content, the sensitivity of NH3 exchange to β was stronger. Also, in the case of a higher initial soil water content, NH3 exchange was more sensitive to the changes in θfc and θpwp. The sensitivity analysis showed that the nitrogen content of urine (cN) is associated with high uncertainty in the simulated fluxes. However, model experiments based on cN values randomized from an estimated statistical distribution indicated that this uncertainty is considerably smaller in practice

From sink to source: long-term (2002-2019) trends and anomalies in net ecosystem exchange of CO2 from a Scottish temperate peatland

A 'display' at the EGU General Assembly 2020. Peatlands North of 45˚ represent one of the largest terrestrial carbon (C) stores. They play an important role in the global C-cycle, and their ability to sequester carbon is controlled by multiple, often competing, factors including precipitation, temperature and phenology. Land-atmosphere exchange of carbon dioxide (CO2) is dynamic, and exhibits marked seasonal and inter-annual variations which can effect the overall carbon sink strength in both the short- and long-term. Due to increased incidences of climate anomalies in recent years, long-term datasets are essential to disambiguate natural variability in Net Ecosystem Exchange (NEE) from shorter-term fluctuations. This is particularly important at high latitudes (>45˚N) where the majority of global peatlands are found. With increasing pressure from stressors such as climate and land-use change, it has been predicted that with a ca. 3oC global temperature rise by 2100, UK peatlands could become a net source of C. NEE of CO2 has been measured using the eddy-covariance (EC) method at Auchencorth Moss (55°47’32 N, 3°14’35 W, 267 m a.s.l.), a temperate, lowland, ombrotrophic peatland in central Scotland, continuously since 2002. Alongside EC data, we present a range of meteorological parameters measured at site including soil temperature, total solar and photosynthetically active radiation (PAR), rainfall, and, since April 2007, half-hourly water table depth readings. The length of record and range of measurements make this dataset an important resource as one of the longest term records of CO2 fluxes from a temperate peatland. Although seasonal cycles of gross primary productivity (GPP) were highly variable between years, the site was a consistent CO2 sink for the period 2002-2012. However, net annual losses of CO2 have been recorded on several occasions since 2013. Whilst NEE tends to be positively correlated with the length of growing season, anomalies in winter weather also explain some of the variability in CO2 sink strength the following summer. Additionally, water table depth (WTD) plays a crucial role, affecting both GPP and ecosystem respiration (Reco). Relatively dry summers in recent years have contributed to shifting the balance between Reco and GPP: prolonged periods of low WTD were typically accompanied by an increase in Reco, and a decrease in GPP, hence weakening the overall CO2 sink strength. Extreme events such as drought periods and cold winter temperatures can have significant and complex effects on NEE, particularly when such meteorological anomalies co-occur. For example, a positive annual NEE occurred in 2003 when Europe experienced heatwave and summer drought. More recently, an unusually long spell of snow lasting until the end of March delayed the onset of the 2018 growing season by up to 1.5 months compared to previous years. This was followed by a prolonged dry spell in summer 2018, which weakened GPP, increased Reco and led to a net annual loss of 47.4 ton CO2-C km-2. It is clear that the role of Northern peatlands within the carbon cycle is being modified, driven by changes in climate at both local and global scales