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Since 1999, Environment and Climate Change Canada (ECCC) has been coordinating a multi-laboratory comparison of measurements of long-lived greenhouse gases in whole air samples collected at the Global Atmosphere Watch (GAW) Alert Observatory located in the Canadian High Arctic (82 ∘ 28 ′ N, 62 ∘ 30 ′ W). In this paper, we evaluate the measurement agreement of atmospheric CO 2 , CH 4 , N 2 O, SF 6 , and stable isotopes of CO 2 (δ13 C, δ18 O) between leading laboratories from seven independent international institutions. The measure of success is linked to target goals for network compatibility outlined by the World Meteorological Organization's (WMO) GAW greenhouse gas measurement community. Overall, based on ∼ 8000 discrete flask samples, we find that the co-located atmospheric CO 2 and CH 4 measurement records from Alert by CSIRO, MPI-BGC, SIO, UHEI-IUP, and ECCC versus NOAA (the designated reference laboratory) are generally consistent with the WMO compatibility goals of ± 0.1 ppm CO 2 and ± 2 ppb CH 4 over the 17-year period (1999–2016), although there are periods where differences exceed target levels and persist as systematic bias for months or years. Consistency with the WMO goals for N 2 O, SF 6 , and stable isotopes of CO 2 (δ13 C, δ18 O) has not been demonstrated. Additional analysis of co-located comparison measurements between CSIRO and SIO versus NOAA or INSTAAR (for the isotopes of CO 2) at other geographical sites suggests that the findings at Alert for CO 2 , CH 4 , N 2 O, and δ13 C–CO 2 could be extended across the CSIRO, SIO, and NOAA observing networks. The primary approach to estimate an overall measurement agreement level was carried out by pooling the differences of all individual laboratories versus the designated reference laboratory and determining the 95th percentile range of these data points. Using this approach over the entire data record, our best estimate of the measurement agreement range is -0.51 to + 0.53 ppm for CO 2 , -0.09 ‰ to + 0.07 ‰ for δ13 C, -0.50 ‰ to + 0.58 ‰ for δ18 O, -4.86 to + 6.16 ppb for CH 4 , -0.75 to + 1.20 ppb for N 2 O, and -0.14 to + 0.09 ppt for SF 6. A secondary approach of using the average of 2 standard deviations of the means for all flask samples taken in each individual sampling episode provided similar results. These upper and lower limits represent our best estimate of the measurement agreement at the 95 % confidence level for these individual laboratories, providing more confidence for using these datasets in various scientific applications (e.g., long-term trend analysis). [ABSTRACT FROM AUTHOR]

The use of the noble gas radon (222Rn) as a tracer for different research studies, for example observation-based estimation of greenhouse gas (GHG) fluxes, has led to the need of high-quality 222Rn activity concentration observations with high spatial and temporal resolution. So far a robust metrology chain for these measurements is not yet available. A portable direct atmospheric radon monitor (ARMON), based on electrostatic collection of 218Po , is now running at Spanish stations. This monitor has not yet been compared with other 222Rn and 222Rn progeny monitors commonly used at atmospheric stations. A 3-month intercomparison campaign of atmospheric 222Rn and 222Rn progeny monitors based on different measurement techniques was realized during the fall and winter of 2016–2017 to evaluate (i) calibration and correction factors between monitors necessary to harmonize the atmospheric radon observations and (ii) the dependence of each monitor's response in relation to the sampling height and meteorological and atmospheric aerosol conditions. Results of this study have shown the following. (i) All monitors were able to reproduce the atmospheric radon variability on a daily basis. (ii) Linear regression fits between the monitors exhibited slopes, representing the correction factors, between 0.62 and 1.17 and offsets ranging between -0.85 and -0.23 Bq m -3 when sampling 2 m above ground level (a.g.l.). Corresponding results at 100 m a.g.l. exhibited slopes of 0.94 and 1.03 with offsets of -0.13 and 0.01 Bq m -3 , respectively. (iii) No influence of atmospheric temperature and relative humidity on monitor responses was observed for unsaturated conditions at 100 m a.g.l., whereas slight influences (order of 10-2) of ambient temperature were observed at 2 m a.g.l. (iv) Changes in the ratio between 222Rn progeny and 222Rn monitor responses were observed under very low atmospheric aerosol concentrations. Results also show that the new ARMON could be useful at atmospheric radon monitoring stations with space restrictions or as a mobile reference instrument to calibrate in situ 222Rn progeny monitors and fixed radon monitors. In the near future a long-term comparison study between ARMON, HRM, and ANSTO monitors would be useful to better evaluate (i) the uncertainties of radon measurements in the range of a few hundred millibecquerels per cubic meter to a few becquerels per cubic meter and (ii) the response time correction of the ANSTO monitor for representing fast changes in the ambient radon concentrations. [ABSTRACT FROM AUTHOR]

The use of the noble gas radon (222Rn) as tracer for different research studies, for example observation-based estimation of greenhouse gas (GHG) fluxes, has led to the need of high-quality 222Rn activity concentration observations with high spatial and temporal resolution. So far a robust metrology chain for these measurements is not yet available. A 3-month inter-comparison campaign of atmospheric 222Rn- and 222Rn progeny monitors based on different measurement techniques was realized during the fall and winter of 2016-2017 to evaluate: i) calibration and correction factors between monitors necessary to harmonize the atmospheric radon observations; and ii) the dependence of each monitor's response in relation to the sampling height, meteorological and atmospheric aerosol conditions. Results of this study have shown that: i) all monitors were able to reproduce the atmospheric radon variability on daily basis; ii) linear regression fits between the monitors exhibited slopes between 0.62 and 1.17 and offsets ranging between -0.85 Bq m-3 and -0.23 Bq m-3 when sampling 2 m above ground level (a.g.l.). Corresponding results at 100 m a.g.l. exhibited slopes of 0.94 and 1.03 with offsets of -0.13 Bq m-3 and 0.01 Bq m-3, respectively; iii) no influence of atmospheric temperature and relative humidity on monitor responses was observed for unsaturated conditions; and iv) changes of the ratio between radon progeny and radon monitor responses were observed under very high atmospheric humidity and under very low atmospheric aerosol concentrations. However, a more statistically robust evaluation of these last influences based on a longer dataset should be conducted to improve the harmonization of the data. [ABSTRACT FROM AUTHOR]

CO2 emission estimates from urban areas can be obtained with a network of in situ instruments measuring atmospheric CO2 combined with high-resolution (inverse) transport modelling. Because the distribution of CO2 emissions is highly heterogeneous in space and variable in time in urban areas, gradients of atmospheric CO2 (here, dry air mole fractions) need to be measured by numerous instruments placed at multiple locations around and possibly within these urban areas. This calls for the development of lower-cost medium-precision sensors to allow a deployment at required densities. Medium precision is here set to be a random error (uncertainty) on hourly measurements of ±1 ppm or less, a precision requirement based on previous studies of network design in urban areas. Here we present tests of newly developed non-dispersive infrared (NDIR) sensors manufactured by Senseair AB performed in the laboratory and at actual field stations, the latter for CO2 dry air mole fractions in the Paris area. The lower-cost medium-precision sensors are shown to be sensitive to atmospheric pressure and temperature conditions. The sensors respond linearly to CO2 when measuring calibration tanks, but the regression slope between measured and assigned CO2 differs between individual sensors and changes with time. In addition to pressure and temperature variations, humidity impacts the measurement of CO2 , with all of these factors resulting in systematic errors. In the field, an empirical calibration strategy is proposed based on parallel measurements with the lower-cost medium-precision sensors and a high-precision instrument cavity ring-down instrument for 6 months. The empirical calibration method consists of using a multivariable regression approach, based on predictors of air temperature, pressure and humidity. This error model shows good performances to explain the observed drifts of the lower-cost medium-precision sensors on timescales of up to 1–2 months when trained against 1–2 weeks of high-precision instrument time series. Residual errors are contained within the ±1 ppm target, showing the feasibility of using networks of HPP3 instruments for urban CO2 networks. Provided that they could be regularly calibrated against one anchor reference high-precision instrument these sensors could thus collect the CO2 (dry air) mole fraction data required as for top-down CO2 flux estimates. [ABSTRACT FROM AUTHOR]

CO2 emission estimates from urban areas can be obtained with a network of in-situ instruments measuring atmospheric CO2 combined with high-resolution (inverse) transport modeling. The distribution of CO2 emissions being highly heterogeneous in space and variable in time in urban areas, gradients of atmospheric CO2 need to be measured by numerous instruments placed at multiple locations around and possibly within these urban areas, which calls for the development of lower-cost medium precision sensors to allow a deployment at required densities. Medium precision is here set to be a random error (uncertainty) on hourly measurements of ±1 ppm or less, a precision requirement based on previous studies of network design in urban areas. Here we present tests of a HPP commercial NDIR sensors manufactured by Senseair AB performed in the laboratory and at actual field stations, the latter for CO2 concentration in the Paris area. The lower-cost medium precision sensors are shown to be sensitive to atmospheric pressure and temperature conditions. The sensors respond linearly to CO2 when measuring calibration tanks, but the regression slope between measured and true CO2 differs between individual sensors and changes with time. In addition to pressure and temperature variations, humidity impacts the measurement of CO2, all causing systematic errors. In the field, an empirical calibration strategy is proposed based on parallel measurements with the lower-cost medium precision sensors and a high-precision instrument cavity ring-down instrument during 6 month. This empirical calibration method consists of using a multiple regression approach to create a model of the errors defined as the difference of CO2 measured by the lower-cost medium precision sensors relative to a calibrated high-precision instrument, based on predictors of air temperature, pressure and humidity. This error model shows good performances to explain the observed drifts of the lower-cost medium precision sensors on time scales of up to 1-2 months when trained against 1-2 weeks of high-precision instrument time series. Residual errors are contained within the ±1 ppm target, showing the feasibility to use networks of HPP instruments for urban CO2 networks, provided that they could be regularly calibrated against one anchor reference high-precision instrument. [ABSTRACT FROM AUTHOR]

Abstract. Providing timely information on urban Greenhouse-Gas (GHG) emissions and their trends to stakeholders relies on reliable measurements of atmospheric concentrations and the understanding of how local emissions and atmospheric transport influence these observations. Portable Fourier Transform Infra-Red (FTIR) spectrometers were deployed at 5 stations in the Paris metropolitan area to provide column-averaged concentrations of CO2 (XCO2) during a field campaign in spring of 2015. Here, we describe and analyze the variations of XCO2 observed at different sites and how they changed over time. We find that observations upwind and downwind of the city centre differ significantly in their XCO2 concentrations, while the overall variability of the daily cycle is similar, i.e., increasing during night-time with a strong decrease (typically 2–3ppm) during the afternoon. An atmospheric transport model framework (CHIMERE-CAMS) was used to simulate XCO2 and predict the same behaviour seen in the observations, which supports key findings, e.g. that even in a densely populated region like Paris (over 12 Million people), biospheric uptake of CO2 can be of major influence on daily XCO2 variations. Despite a general offset between modelled and observed XCO2, the model correctly predicts the impact of the meteorological parameters (e.g. wind direction and speed) on the concentration gradients between different stations. Looking at the local gradients of XCO2 for upwind and downwind station pairs, which is less sensitive to changes in XCO2 regional background conditions, we find the model-data agreement significantly better. Our modelling framework indicates that the local XCO2 gradient between the stations is dominated by the fossil fuel CO2 signal of the Paris metropolitan area. This highlights the usefulness of XCO2 observations to help optimise future urban GHG emission estimates. [ABSTRACT FROM AUTHOR]

The ClimaDat station at Gredos (GIC3) has been continuously measuring atmospheric (dry air) mixing ratios of carbon dioxide (CO2) and methane (CH4), as well as meteorological parameters, since November 2012. In this study we investigate the atmospheric variability of CH4 mixing ratios between 2013 and 2015 at GIC3 with the help of co-located observations of 222Rn concentrations, modelled 222Rn fluxes and modelled planetary boundary layer heights (PBLHs). Both daily and seasonal changes in atmospheric CH4 can be better understood with the help of atmospheric concentrations of 222Rn (and the corresponding fluxes). On a daily timescale, the variation in the PBLH is the main driver for 222Rn and CH4 variability while, on monthly timescales, their atmospheric variability seems to depend on emission changes. To understand (changing) CH4 emissions, nocturnal fluxes of CH4 were estimated using two methods: the radon tracer method (RTM) and a method based on the EDGARv4.2 bottom-up emission inventory, both using FLEXPARTv9.0.2 footprints. The mean value of RTM-based methane fluxes (FR_CH4) is 0.11 mg CH4 m-2 h-1 with a standard deviation of 0.09 or 0.29 mg CH4 m-2 h-1 with a standard deviation of 0.23 mg CH4 m-2 h-1 when using a rescaled 222Rn map (FR_CH4_rescale). For our observational period, the mean value of methane fluxes based on the bottom-up inventory (FE_CH4) is 0.33 mg CH4 m-2 h-1 with a standard deviation of 0.08 mg CH4 m-2 h-1. Monthly CH4 fluxes based on RTM (both FR_CH4 and FR_CH4_rescale) show a seasonality which is not observed for monthly FE_CH4 fluxes. During January-May, RTM-based CH4 fluxes present mean values 25 % lower than during June-December. This seasonal increase in methane fluxes calculated by RTM for the GIC3 area appears to coincide with the arrival of transhumant livestock at GIC3 in the second half of the year. [ABSTRACT FROM AUTHOR]

Many stakeholders are seeking methods to reduce carbon dioxide (CO2) emissions in urban areas, but reliable, high-resolution inventories are required to guide these efforts. We present the development of a high-resolution CO2 inventory available for the Greater Toronto Area and surrounding region in Southern Ontario, Canada (area of ~2.8 x 105 km², 26% of the province of Ontario). The new SOCE (Southern Ontario CO2 Emissions) inventory is available at the 2.5 x 2.5 km spatial and hourly temporal resolution and characterizes emissions from seven sectors: area, residential natural-gas combustion, commercial natural-gas combustion, point, marine, on-road, and off-road. To assess the accuracy of the SOCE inventory, we developed an observation--model framework using the GEM-MACH chemistry--transport model run on a high-resolution grid with 2.5 km grid spacing coupled to the Fossil Fuel Data Assimilation System (FFDAS) v2 inventories for anthropogenic CO2 emissions and the European Centre for Medium-Range Weather Forecasts (ECMWF) land carbon model C-TESSEL for biogenic fluxes. A run using FFDAS for the Southern Ontario region was compared to a run in which its emissions were replaced by the SOCE inventory. Simulated CO2 mixing ratios were compared against in situ measurements made at four sites in Southern Ontario -- Downsview, Hanlan's Point, Egbert and Turkey Point -- in 3 winter months, January-March 2016. Model simulations had better agreement with measurements when using the SOCE inventory emissions versus other inventories, quantified using a variety of statistics such as correlation coefficient, root-meansquare error, and mean bias. Furthermore, when run with the SOCE inventory, the model had improved ability to capture the typical diurnal pattern of CO2 mixing ratios, particularly at the Downsview, Hanlan's Point, and Egbert sites. In addition to improved model--measurement agreement, the SOCE inventory offers a sectoral breakdown of emissions, allowing estimation of average time-of-day and day-of-week contributions of different sectors. Our results show that at night, emissions from residential and commercial natural-gas combustion and other area sources can contribute > 80% of the CO2 enhancement, while during the day emissions from the on-road sector dominate, accounting for > 70% of the enhancement. [ABSTRACT FROM AUTHOR]

Atmospheric concentrations of the two main greenhouse gases (GHGs), carbon dioxide (CO2) and methane (CH4), are continuously measured since November 2012 at the Spanish rural station of Gredos (GIC3), within the climate network ClimaDat, together with atmospheric radon (222Rn) tracer and meteorological parameters. The atmospheric variability of CH4 concentrations measured from 2013 to 2015 at GIC3 has been analyzed in this study. It is interpreted in relation to the variability of measured 222Rn concentrations, modelled 222Rn fluxes and modelled heights of the planetary boundary layer (PBLH) in the same period. In addition, nocturnal fluxes of CH4 were estimated using two methods: the Radon Tracer Method (RTM) and one based on the EDGARv4.2 bottom-up emission inventory. Both previous methods have been applied using the same footprints, calculated with the atmospheric transport model FLEXPARTv6.2. Results show that daily and seasonal changes in atmospheric concentrations of 222Rn (and the corresponding fluxes) can help to understand the atmospheric CH4 variability. On daily basis, the variation in the PBLH mainly drives changes in 222Rn and CH4 concentrations while, on monthly basis, their atmospheric variability seems to depend on changes in their emissions. The median value of RTM based methane fluxes (FR_CH4) is 0.17 mg CH4m-2h-1 with an absolute deviation of 0.08 mg CH4m-2h-1. Median methane fluxes based on bottom-up inventory (FE_CH4) is of 0.32 mg CH4m-2h-1 with an absolute deviation of 0.06 mg CH4m-2h-1. Monthly FR_CH4 flux shows a seasonality which is not observed in the monthly FE_CH4 flux. During January-May FR_CH4 fluxes present a median value of 0.08 mg CH4m-2h-1 with an absolute deviation of 0.05 mg CH4m-2h-1 and a median value of 0.19 mg CH4m-2h-1 with an absolute deviation of 0.06 mg CH4m-2h-1 during June-December. This seasonal doubling of the median methane fluxes calculated by RTM at the GIC3 area seems to be mainly related to the alternate presence of transhumant livestock in the GIC3 area. The results obtained in this study highlight the benefit of applying independent RTM to improve the seasonality of the emission factors from bottom-up inventories. [ABSTRACT FROM AUTHOR]

Many stakeholders are seeking methods to reduce carbon dioxide (COO2) emissions in urban areas, however reliable, high-resolution inventories are required to guide these efforts. We present the development of a high-resolution COO2 inventory available for the Greater Toronto Area and surrounding region in southern Ontario, Canada (area of ∼ 2.8 × 105 km², 26 % of the province of Ontario). The new SOCE (Southern Ontario COO2 Emissions) inventory is available at the 2.5 × 2.5 km spatial and hourly temporal resolution and characterizes emissions from seven sectors: Area, Residential natural gas combustion, Commercial natural gas combustion, Point, Marine, On-road and Off-road. To assess the accuracy of the SOCE inventory, we developed an observation-model framework using the GEM-MACH chemistry-transport model run on a high-resolution grid with 2.5 km grid spacing coupled to the Fossil Fuel Data Assimilation System (FFDAS) v2 inventories for anthropogenic COO2 emissions and the European Center for Medium-Range Weather Forecasts (ECMWF) land carbon model C-TESSEL for biogenic fluxes. A run using FFDAS for the southern Ontario region was compared to a run in which its emissions were replaced by the SOCE inventory. Simulated COO2 mixing ratios were compared against in situ measurements made at four sites in southern Ontario, Downsview, Hanlan's Point, Egbert and Turkey Point, in three winter months, January–March, 2016. Model simulations had better agreement with measurements when using the SOCE inventory emissions versus other inventories, quantified using a variety of statistics such as Correlation Coefficient, root mean square error and mean bias. Furthermore, when run with the SOCE inventory, the model had improved ability to capture the typical diurnal pattern of COO2 mixing ratios, particularly at the Downsview, Hanlan's Point and Egbert sites. In addition to improved model-measurement agreement, the SOCE inventory offers a sectoral breakdown of emissions, allowing estimation of average time-of-day and day-of-week contributions of different sectors. Our results show that at night, emissions from Residential and Commercial natural gas combustion and other Area sources can contribute > 80 % of the COO2 enhancement while during the day emissions from the On-road sector dominate, accounting for > 70 % of the enhancement. [ABSTRACT FROM AUTHOR]

Due to increased demand for an understanding of CH4 emissions from industrial sites, the subject of cross sensitivities caused by absorption from multiple gases on δ13CH4 and C2H6 measured in the near-infrared spectral domain using CRDS has become increasingly important. Extensive laboratory tests are presented here, which characterize these cross sensitivities and propose corrections for the biases they induce. We found methane isotopic measurements to be subject to interference from elevated C2H6 concentrations resulting in heavier δ13CH4 by C23.5%° per ppm C2H6 = ppm CH4. Measured C2H6 is subject to absorption interference from a number of other trace gases, predominantly H2O (with an average linear sensitivity of 0.9 ppm C2H6 per % H2O in ambient conditions). Yet, this sensitivity was found to be discontinuous with a strong hysteresis effect and we suggest removing H2O from gas samples prior to analysis. The C2H6 calibration factor was calculated using a GC and measured as 0.5 (confirmed up to 5 ppm C2H6). Field tests at a natural gas compressor station demonstrated that the presence of C2H6 in gas emissions at an average level of 0.3 ppm shifted the isotopic signature by 2.5 °, whilst after calibration we find that the average C2H6 : CH4 ratio shifts by C0.06. These results indicate that, when using such a CRDS instrument in conditions of elevated C2H6 for CH4 source determination, it is imperative to account for the biases discussed within this study. [ABSTRACT FROM AUTHOR]

The increase of atmospheric methane (CH4) is the second largest contributor to the increased radiative forcing since the industrial revolution. Natural gas extraction and distribution is associated with CH4 leaks of uncertain magnitude that has spurred interest for developing new methods to measure them. Using a CRDS instrument we evaluate two methane identification methods commonly used to better constrain emission estimates from natural gas leaks, namely stable isotope analysis and the ethane: methane ratio (C2H6 : CH4). Recently it has come to light that CRDS measurements of δ13CH4 and C2H6 in the near infrared spectral domain are subject to cross sensitivities due to absorption from multiple gases. These sensitivities translate into biases in the retrieval of δ13CH4 and C2H6 concentrations in air samples, and should thus be accounted for during data processing. Here we present extensive laboratory tests using two CRDS instruments to characterize their cross sensitivities and propose corrections to calculate unbiased δ13CH4 and C2H6. Methane isotopic measurements were found to be subject to interference from elevated C2H6 concentrations (a secondary component in many natural gas types) resulting in heavier δ13CH4 by +23.5 ‰ per ppm C2H6 / ppm CH4. Measured C2H6 is subject to absorption interference from a number of other trace gases, the predominant being H2O (with an average linear sensitivity of 0.9 ppm C2H6 per % H2O in ambient conditions, meaning that the presence of H2O causes the inference of too high C2H6 mixing ratios if no correction is applied). Yet, this sensitivity was found to be discontinuous with a strong hysteresis effect. Throughout the range of C2H6 concentrations measured in this study (0-5 ppm C2H6), both CRDS instruments consistently measure concentrations double that reported by a GC, thus we have calculated a calibration factor of 0.5. To demonstrate the significance of the corrections we test the source identification methods on air measured at a natural gas compressor station. The presence of C2H6 in gas emissions at an average level of 0.3 ppm was found to shift the isotopic signature by 2.5 ‰. We find that after correction and calibration the average C2H6 : CH4 ratio shifts by +0.06. These results indicate that when using such a CRDS instrument in conditions of elevated C2H6 for CH4 source determination it is imperative to account for the biases discussed within this study. [ABSTRACT FROM AUTHOR]

Using Δ14C observations to infer the local concentration excess of CO2 due to the burning of fossil fuels (ΔFFCO2) is a promising technique to monitor anthropogenic CO2 emissions. A recent study showed that 14CO2 emissions from the nuclear industry can significantly alter the local atmospheric 14CO2 concentration and thus mask the Δ14C depletion due to ΔFFCO2. In this study, we investigate the relevance of this effect for the vicinity of Toronto, Canada, a hot spot of anthropogenic 14CO2 emissions. Comparing the measured emissions from local power plants to a global emission inventory highlighted significant deviations on interannual timescales. Although the previously assumed emission factor of 1.6 TBq(GWa)-1 agrees with the observed long-term average for all CANDU reactors of 1.50 ± 0.18 TBq(GWa)-1. This power-based parameterization neglects the different emission ratios for individual reactors, which range from 3.4 ± 0.82 to 0.65 ± 0.09 TBq(GWa)-1. This causes a mean difference of -14% in 14CO2 concentrations in our simulations at our observational site in Egbert, Canada. On an annual time basis, this additional 14CO2 masks the equivalent of 27-82% of the total annual FFCO2 offset. A pseudo-data experiment suggests that the interannual variability in the masked fraction may cause spurious trends in the ΔFFCO2 estimates of the order of 30% from 2006-2010. In addition, a comparison of the modeled Δ14C levels with our observational time series from 2008-2010 underlines that incorporating the best available 14CO2 emissions significantly increases the agreement. There were also short periods with significant observed Δ14C offsets, which were found to be linked with maintenance periods conducted on these nuclear reactors. [ABSTRACT FROM AUTHOR]