Drivers of long-term variability in CO2 net ecosystem exchange in a temperate peatland

Land–atmosphere exchange of carbon dioxide (CO2) in peatlands exhibits marked seasonal and inter-annual variability, which subsequently affects the carbon (C) sink strength of catchments across multiple temporal scales. Long-term studies are needed to fully capture the natural variability and therefore identify the key hydrometeorological drivers in the net ecosystem exchange (NEE) of CO2. Since 2002, NEE has been measured continuously by eddy-covariance at Auchencorth Moss, a temperate lowland peatland in central Scotland. Hence this is one of the longest peatland NEE studies to date. For 11 years, the site was a consistent, yet variable, atmospheric CO2 sink ranging from −5.2 to −135.9 g CO2-C m−2 yr−1 (mean of −64.1 ± 33.6 g CO2-C m−2 yr−1). Inter-annual variability in NEE was positively correlated to the length of the growing season. Mean winter air temperature explained 87% of the inter-annual variability in the sink strength of the following summer, indicating an effect of winter climate on local phenology. Ecosystem respiration (Reco) was enhanced by drought, which also depressed gross primary productivity (GPP). The CO2 uptake rate during the growing season was comparable to three other sites with long-term NEE records; however, the emission rate during the dormant season was significantly higher. To summarise, the NEE of the peatland studied is modulated by two dominant factors: - phenology of the plant community, which is driven by winter air temperature and impacts photosynthetic potential and net CO2 uptake during the growing season (colder winters are linked to lower summer NEE), - water table level, which enhanced soil respiration and decreased GPP during dry spells. Although summer dry spells were sporadic during the study period, the positive effects of the current climatic trend towards milder winters on the site's CO2 sink strength could be offset by changes in precipitation patterns especially during the growing season

Spatial and temporal variability of urban fluxes of methane, carbon monoxide and carbon dioxide above London, UK

We report on more than 3 years of measurements of fluxes of methane (CH4), carbon monoxide (CO) and carbon dioxide (CO2) taken by eddy-covariance in central London, UK. Mean annual emissions of CO2 in the period 2012–2014 (39.1 ± 2.4 ktons km−2 yr−1) and CO (89 ± 16 tons km−2 yr−1 ) were consistent (within 1 and 5% respectively) with values from the London Atmospheric Emissions Inventory, but measured CH4 emissions (72 ± 3 tons km−2 yr−1) were over two-fold larger than the inventory value. Seasonal variability was large for CO with a winter to summer reduction of 69 %, and monthly fluxes were strongly anti-correlated with mean air temperature. The winter increment in CO emissions was attributed mainly to vehicle cold starts and reduced fuel combustion efficiency. CO2 fluxes were 33 % higher in winter than in summer and anti-correlated with mean air temperature, albeit to a lesser extent than for CO. This was attributed to an increased demand for natural gas for heating during the winter. CH4 fluxes exhibited moderate seasonality (21 % larger in winter), and a spatially variable linear anti-correlation with air temperature. Differences in resident population within the flux footprint explained up to 90 % of the spatial variability of the annual CO2 fluxes and up to 99 % for CH4. Furthermore, we suggest that biogenic sources of CH4, such as wastewater, which is unaccounted for by the atmospheric emissions inventories, make a substantial contribution to the overall bud- get and that commuting dynamics in and out of central business districts could explain some of the spatial and temporal variability of CO2 and CH4 emissions. To our knowledge,this study is unique given the length of the data sets presented, especially for CO and CH4 fluxes. This study offers an independent assessment of “bottom-up” emissions inventories and demonstrates that the urban sources of CO and CO2 are well characterized in London. This is however not the case for CH4 emissions which are heavily underestimated by the inventory approach. Our results and others point to opportunities in the UK and abroad to identify and quantify the “missing” sources of urban methane, revise the methodologies of the emission inventories and devise emission reduction strategies for this potent greenhouse gas

Turbulent flow at 190 m height above London during 2006-2008: A climatology and the applicability of similarity theory

Flow and turbulence above urban terrain is more complex than above rural terrain, due to the different momentum and heat transfer characteristics that are affected by the presence of buildings (e.g. pressure variations around buildings). The applicability of similarity theory (as developed over rural terrain) is tested using observations of flow from a sonic anemometer located at 190.3 m height in London, U.K. using about 6500 h of data. Turbulence statistics—dimensionless wind speed and temperature, standard deviations and correlation coefficients for momentum and heat transfer—were analysed in three ways. First, turbulence statistics were plotted as a function only of a local stability parameter z/Λ (where Λ is the local Obukhov length and z is the height above ground); the σ_i/u_* values (i = u, v, w) for neutral conditions are 2.3, 1.85 and 1.35 respectively, similar to canonical values. Second, analysis of urban mixed-layer formulations during daytime convective conditions over London was undertaken, showing that atmospheric turbulence at high altitude over large cities might not behave dissimilarly from that over rural terrain. Third, correlation coefficients for heat and momentum were analyzed with respect to local stability. The results give confidence in using the framework of local similarity for turbulence measured over London, and perhaps other cities. However, the following caveats for our data are worth noting: (i) the terrain is reasonably flat, (ii) building heights vary little over a large area, and (iii) the sensor height is above the mean roughness sublayer depth

Seasonal fluxes of carbon monoxide from an intensively grazed grassland in Scotland

Fluxes of carbon monoxide (CO) were measured using a fast-response quantum cascade laser absorption spectrometer and the eddy covariance method at a long-term intensively grazed grassland in southern Scotland. Measurements lasted 20 months from April 2016 to November 2017, during which normal agricultural activities continued. Observed fluxes followed a regular diurnal cycle, peaking at midday and returning to values near zero during the night, with occasional uptake observed. CO fluxes correlated well with the meteorological variables of solar radiation, soil temperature and soil moisture content. Using a general additive model (GAM) we were able to gap fill CO fluxes and estimate annual fluxes of 0.38 ± 0.046 and 0.35 ± 0.045 g C m−2 y−1g C m−2 y−1 for 2016 and 2017, respectively. If the CO fluxes reported in this study are representative of UK grasslands, then national annual emissions could be expected to be in the order of 61.91 (54.3–69.5) Gg, which equates to 3.8% (3.4–4.3%) of the current national inventory total

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

The impact of boundary layer height on air pollution concentrations in London – early results from the ClearfLo project.

The ClearfLo projects aims to understand the processes generating pollutants like ozone, NOx and particulate matter and their interaction with the urban atmospheric boundary layer. ClearfLo (www.clearflo.ac.uk) is a large multi-institution NERC-funded project that is establishing integrated measurements of the meteorology, composition and particulate loading of London’s urban atmosphere, complemented by an ambitious modeling programme. The project established a new long-term measurement infrastructure in London encompassing measurement capabilities at street level and at elevated sites. These measurements were accompanied by high resolution mod- eling with the UK Met Office Unified model and WRF. This combined measuring/modelling approach enables us to identify the seasonal cycle in the meteorology and composition, together with the controlling processes. Two intensive observation periods in January/February 2012 and during the Olympics in summer 2012 measured London’s atmosphere with higher level of detail. Data from these IOPs will enable us (i) to determine the vertical structure and evolution of the urban atmosphere (ii) to determine the chemical controls on ozone production, particularly the role of biogenic emissions and (iii) to determine the processes controlling the evolution of the size,distribution and composition of particulate matter. We present results from the wintertime IOP in London focusing on a wintertime pollution episode during January 2012. We compare measured concentrations from top of BT Tower in central London with rural background measurements and determine the processes leading to the urban increment in pollutant concentrations. Therefore, we combine high-resolution simulations with the Met Office Unified Model for London and mixing layer heights derived from lidar measurements with air quality measurements in central London in order to quantify the role the boundary layer depth plays for London’s concentrations

Atmospheric observations consistent with reported decline in the UK’s methane emissions, 2013 – 2020

Atmospheric measurements can be used as a tool to evaluate national greenhouse gas inventories through inverse modelling. Using 8 years of continuous methane (CH4) concentration data, this work assesses the United Kingdom's (UK) CH4 emissions over the period 2013–2020. Using two different inversion methods, we find mean emissions of 2.10 ± 0.09 and 2.12 ± 0.26 Tg yr−1 between 2013 and 2020, an overall trend of −0.05 ± 0.01 and −0.06 ± 0.04 Tg yr−2 and a 2 %–3 % decrease each year. This compares with the mean emissions of 2.23 Tg yr−1 and the trend of −0.03 Tg yr−2 (1 % annual decrease) reported in the UK's 2021 inventory between 2013 and 2019. We examine how sensitive these estimates are to various components of the inversion set-up, such as the measurement network configuration, the prior emissions estimate, the inversion method and the atmospheric transport model used. We find the decreasing trend to be due, primarily, to a reduction in emissions from England, which accounts for 70 % of the UK CH4 emissions. Comparisons during 2015 demonstrate consistency when different atmospheric transport models are used to map the relationship between sources and atmospheric observations at the aggregation level of the UK. The posterior annual national means and negative trend are found to be consistent across changes in network configuration. We show, using only two monitoring sites, that the same conclusions on mean UK emissions and negative trend would be reached as using the full six-site network, albeit with larger posterior uncertainties. However, emissions estimates from Scotland fail to converge on the same posterior under different inversion set-ups, highlighting a shortcoming of the current observation network in monitoring all of the UK. Although CH4 emissions in 2020 are estimated to have declined relative to previous years, this decrease is in line with the longer-term emissions trend and is not necessarily a response to national lockdowns

Evaluating methane inventories by isotopic analysis in the London region

A thorough understanding of methane sources is necessary to accomplish methane reduction targets. Urban environments, where a large variety of methane sources coexist, are one of the most complex areas to investigate. Methane sources are characterised by specific δ13C-CH4 signatures, so high precision stable isotope analysis of atmospheric methane can be used to give a better understanding of urban sources and their partition in a source mix. Diurnal measurements of methane and carbon dioxide mole fraction, and isotopic values at King’s College London, enabled assessment of the isotopic signal of the source mix in central London. Surveys with a mobile measurement system in the London region were also carried out for detection of methane plumes at near ground level, in order to evaluate the spatial allocation of sources suggested by the inventories. The measured isotopic signal in central London (−45.7 ±0.5‰) was more than 2‰ higher than the isotopic value calculated using emission inventories and updated δ13C-CH4 signatures. Besides, during the mobile surveys, many gas leaks were identified that are not included in the inventories. This suggests that a revision of the source distribution given by the emission inventories is needed

Overriding water table control on managed peatland greenhouse gas emissions

Global peatlands store more carbon than is naturally present in the atmosphere1,2. However, many peatlands are under pressure from drainage-based agriculture, plantation development and fire, with the equivalent of around 3% of all anthropogenic greenhouse gases emitted from drained peatland3–5. Efforts to curb such emissions are intensifying through the conservation of undrained peatlands and rewetting of drained systems6. Here we report CO2 eddy covariance data from 16 locations and CH4 data from 41 locations in the British Isles, and combine them with published data from sites across all major peatland biomes. We find that the mean annual effective water-table depth (WTDe; that is, the average depth of the aerated peat layer) overrides all other ecosystem- and management-related controls on greenhouse gas fluxes. We estimate that every 10 cm of reduction in WTDe could reduce the net warming impact of CO2 and CH4 emissions (100-year Global Warming Potentials) by at least 3 t CO2e ha-1 yr-1, until WTDe is < 30 cm. Raising water levels further would continue to have a net cooling effect until WTDe is < 10 cm. Our results suggest that greenhouse gas emissions from peatlands drained for agriculture could be greatly reduced without necessarily halting their productive use. Halving WTDe in all drained agricultural peatlands, for example, could reduce emissions by the equivalent of over 1% of global anthropogenic emissions

Studying the spatial variability of methane flux with five eddy covariance towers of varying height

In this study, the spatial representativeness of eddy covariance (EC) methane (CH4) measurements was examined by comparing parallel CH4 fluxes from three short (6 m) towers separated by a few kilometres and from two higher levels (20 m and 60 m) at one location. The measurement campaign was held on an intensively managed grassland on peat soil in the Netherlands. The land use and land cover types are to a large degree homogeneous in the area. The CH4 fluxes exhibited significant variability between the sites on 30-min scale. The spatial coefficient of variation (CVspa) between the three short towers was 56% and it was of similar magnitude as the temporal variability, unlike for the other fluxes (friction velocity, sensible heat flux) for which the temporal variability was considerably larger than the spatial variability. The CVspa decreased with temporal averaging, although less than what could be expected for a purely random process View the MathML source(1/N), and it was 14% for 26-day means of CH4 flux. This reflects the underlying heterogeneity of CH4 flux in the studied landscape at spatial scales ranging from 1 ha (flux footprint) to 10 km2 (area bounded by the short towers). This heterogeneity should be taken into account when interpreting and comparing EC measurements. On an annual scale, the flux spatial variability contributed up to 50% of the uncertainty in CH4 emissions. It was further tested whether EC flux measurements at higher levels could be used to acquire a more accurate estimate of the spatially integrated CH4 emissions. Contrarily to what was expected, flux intensity was found to both increase and decrease depending on measurement height. Using footprint modelling, 56% of the variation between 6 m and 60 m CH4 fluxes was attributed to emissions from local anthropogenic hotspots (farms). Furthermore, morning hours proved to be demanding for the tall tower EC where fluxes at 60 m were up to four-fold those at lower heights. These differences were connected with the onset of convective mixing during the morning period