scholarly journals Characterization of a commercial lower-cost medium-precision non-dispersive infrared sensor for atmospheric CO<sub>2</sub> monitoring in urban areas

2019 ◽  
Vol 12 (5) ◽  
pp. 2665-2677 ◽  
Author(s):  
Emmanuel Arzoumanian ◽  
Felix R. Vogel ◽  
Ana Bastos ◽  
Bakhram Gaynullin ◽  
Olivier Laurent ◽  
...  
Keyword(s):  
High Precision ◽  
Urban Areas ◽  
Lower Cost ◽  
Co2 Flux ◽  
Atmospheric Co2 ◽  
Precision Instrument ◽  
Transport Modelling ◽  
Dry Air ◽  
Empirical Calibration ◽  
Paris Area

Abstract. 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.

scholarly journals Characterization of lower-cost medium precision atmospheric CO<sub>2</sub> monitoring systems for urban areas using commercial NDIR sensors

2018 ◽  
Author(s):  
Emmanuel Arzoumanian ◽  
Felix R. Vogel ◽  
Ana Bastos ◽  
Bakhram Gaynullin ◽  
Olivier Laurent ◽  
...  
Keyword(s):  
High Precision ◽  
Urban Areas ◽  
Lower Cost ◽  
Co2 Concentration ◽  
Calibration Method ◽  
Atmospheric Co2 ◽  
Precision Instrument ◽  
Empirical Calibration ◽  
Paris Area ◽  
The Difference

Abstract. 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.

scholarly journals Maintaining consistent traceability in high precision isotope measurements of CO<sub>2</sub>: verifying atmospheric trends of δ<sup>13</sup>C

2012 ◽  
Vol 5 (3) ◽  
pp. 4003-4040 ◽  
Author(s):  
L. Huang ◽  
A. Chivulescu ◽  
D. Ernst ◽  
W. Zhang ◽  
Y.-S. Lee
Keyword(s):  
High Precision ◽  
Mean Value ◽  
Rate Of Change ◽  
Atmospheric Co2 ◽  
Precision Measurements ◽  
Total Change ◽  
History Of ◽  
Ambient Measurements ◽  
Isotope Measurements ◽  
Δ13c And Δ18o

Abstract. Maintaining consistent traceability of high precision measurements of CO2 isotopes is critical in being able to observe accurate atmospheric trends of δ13C (CO2). Although a number of laboratories/organizations around the world have been involved in baseline measurements of atmospheric CO2 isotopes for several decades, the reports on their traceability measures are rare. In this paper, a principle and an approach for the traceability maintenance of high precision isotope measurements (δ13C and δ18O) in atmospheric CO2 is described. The uncertainties of the traceability have been estimated based on the history of annual calibrations over the last 10 yr. The overall uncertainties of CO2 isotope measurements for individual ambient samples carried out by our program at Environment Canada are estimated (excluding the uncertainty associated with the sampling). The values are 0.02‰ and 0.05‰ in δ13C and δ18O, respectively, close to the WMO targets for data compatibility. The annual rate of change in δ13C of the primary anchor used in our program (which is the laboratory standard linking ambient measurements back to the primary VPDB scale) is close to zero (−0.0016 ± 0.0012‰ per year) over the period of 10 yr (2001–2011). The average annual decreasing rate of δ13C in air CO2 measurements at Alert over the period from 1999 to 2010 has been confirmed and verified, which is −0.025 ± 0.003‰ per year. The total change of δ13C in the annual mean value during this period is ∼−0.27‰. The concept of "Big Delta" is introduced and its role in maintaining traceability of the isotope measurements is described and discussed extensively. Finally, the challenges and a strategy for maintaining traceability are also discussed and suggested.

scholarly journals The potential for regional-scale bias in top-down CO<sub>2</sub> flux estimates due to atmospheric transport errors

2014 ◽  
Vol 14 (16) ◽  
pp. 23681-23709
Author(s):  
S. M. Miller ◽  
I. Fung ◽  
J. Liu ◽  
M. N. Hayek ◽  
A. E. Andrews
Keyword(s):  
Boundary Layer ◽  
Atmospheric Transport ◽  
Regional Scale ◽  
Co2 Flux ◽  
Atmospheric Co2 ◽  
Co2 Fluxes ◽  
Atmospheric Measurements ◽  
Meteorological Model ◽  
Co2 Transport

Abstract. Estimates of CO2 fluxes that are based on atmospheric data rely upon a meteorological model to simulate atmospheric CO2 transport. These models provide a quantitative link between surface fluxes of CO2 and atmospheric measurements taken downwind. Therefore, any errors in the meteorological model can propagate into atmospheric CO2 transport and ultimately bias the estimated CO2 fluxes. These errors, however, have traditionally been difficult to characterize. To examine the effects of CO2 transport errors on estimated CO2 fluxes, we use a global meteorological model-data assimilation system known as "CAM–LETKF" to quantify two aspects of the transport errors: error variances (standard deviations) and temporal error correlations. Furthermore, we develop two case studies. In the first case study, we examine the extent to which CO2 transport uncertainties can bias CO2 flux estimates. In particular, we use a common flux estimate known as CarbonTracker to discover the minimum hypothetical bias that can be detected above the CO2 transport uncertainties. In the second case study, we then investigate which meteorological conditions may contribute to month-long biases in modeled atmospheric transport. We estimate 6 hourly CO2 transport uncertainties in the model surface layer that range from 0.15 to 9.6 ppm (standard deviation), depending on location, and we estimate an average error decorrelation time of ∼2.3 days at existing CO2 observation sites. As a consequence of these uncertainties, we find that CarbonTracker CO2 fluxes would need to be biased by at least 29%, on average, before that bias were detectable at existing non-marine atmospheric CO2 observation sites. Furthermore, we find that persistent, bias-type errors in atmospheric transport are associated with consistent low net radiation, low energy boundary layer conditions. The meteorological model is not necessarily more uncertain in these conditions. Rather, the extent to which meteorological uncertainties manifest as persistent atmospheric transport biases appears to depend, at least in part, on the energy and stability of the boundary layer. Existing CO2 flux studies may be more likely to estimate inaccurate regional fluxes under those conditions.

scholarly journals Estimating surface CO<sub>2</sub> fluxes from space-borne CO<sub>2</sub> dry air mole fraction observations using an ensemble Kalman Filter

2009 ◽  
Vol 9 (8) ◽  
pp. 2619-2633 ◽  
Author(s):  
L. Feng ◽  
P. I. Palmer ◽  
H. Bösch ◽  
S. Dance
Keyword(s):  
Kalman Filter ◽  
Mole Fraction ◽  
Ensemble Kalman Filter ◽  
Transport Model ◽  
Co2 Flux ◽  
Surface Flux ◽  
Surface Fluxes ◽  
Co2 Fluxes ◽  
Dry Air ◽  
Geographical Regions

Abstract. We have developed an ensemble Kalman Filter (EnKF) to estimate 8-day regional surface fluxes of CO2 from space-borne CO2 dry-air mole fraction observations (XCO2) and evaluate the approach using a series of synthetic experiments, in preparation for data from the NASA Orbiting Carbon Observatory (OCO). The 32-day duty cycle of OCO alternates every 16 days between nadir and glint measurements of backscattered solar radiation at short-wave infrared wavelengths. The EnKF uses an ensemble of states to represent the error covariances to estimate 8-day CO2 surface fluxes over 144 geographical regions. We use a 12×8-day lag window, recognising that XCO2 measurements include surface flux information from prior time windows. The observation operator that relates surface CO2 fluxes to atmospheric distributions of XCO2 includes: a) the GEOS-Chem transport model that relates surface fluxes to global 3-D distributions of CO2 concentrations, which are sampled at the time and location of OCO measurements that are cloud-free and have aerosol optical depths <0.3; and b) scene-dependent averaging kernels that relate the CO2 profiles to XCO2, accounting for differences between nadir and glint measurements, and the associated scene-dependent observation errors. We show that OCO XCO2 measurements significantly reduce the uncertainties of surface CO2 flux estimates. Glint measurements are generally better at constraining ocean CO2 flux estimates. Nadir XCO2 measurements over the terrestrial tropics are sparse throughout the year because of either clouds or smoke. Glint measurements provide the most effective constraint for estimating tropical terrestrial CO2 fluxes by accurately sampling fresh continental outflow over neighbouring oceans. We also present results from sensitivity experiments that investigate how flux estimates change with 1) bias and unbiased errors, 2) alternative duty cycles, 3) measurement density and correlations, 4) the spatial resolution of estimated flux estimates, and 5) reducing the length of the lag window and the size of the ensemble. At the revision stage of this manuscript, the OCO instrument failed to reach its orbit after it was launched on 24 February 2009. The EnKF formulation presented here is also applicable to GOSAT measurements of CO2 and CH4.

scholarly journals Time-lapse gravity and levelling surveys reveal mass loss and ongoing subsidence in the urban subrosion-prone area of Bad Frankenhausen, Germany

Solid Earth ◽  
2019 ◽  
Vol 10 (3) ◽  
pp. 599-619 ◽  
Author(s):  
Martin Kobe ◽  
Gerald Gabriel ◽  
Adelheid Weise ◽  
Detlef Vogel
Keyword(s):  
Mass Loss ◽  
Soil Water ◽  
High Precision ◽  
Urban Areas ◽  
Quantitative Estimation ◽  
Monitoring Network ◽  
Time Lapse ◽  
Ground Subsidence ◽  
Special Focus ◽  
Precision Time

Abstract. We present results of sophisticated, high-precision time-lapse gravity monitoring that was conducted over 4 years in Bad Frankenhausen (Germany). To our knowledge, this is the first successful attempt to monitor subrosion-induced mass changes in urban areas with repeated gravimetry. The method provides an approach to estimate the mass of dissolved rocks in the subsurface. Subrosion, i.e. leaching and transfer of soluble rocks, occurs worldwide. Mainly in urban areas, any resulting ground subsidence can cause severe damage, especially if catastrophic events, i.e. collapse sinkholes, occur. Monitoring strategies typically make use of established geodetic methods, such as levelling, and therefore focus on the associated deformation processes. In this study, we combine levelling and highly precise time-lapse gravity observations. Our investigation area is the urban area of Bad Frankenhausen in central Germany, which is prone to subrosion, as many subsidence and sinkhole features on the surface reveal. The city and the surrounding areas are underlain by soluble Permian deposits, which are continuously dissolved by meteoric water and groundwater in a strongly fractured environment. Between 2014 and 2018, a total of 17 high-precision time-lapse gravimetry and 18 levelling campaigns were carried out in quarterly intervals within a local monitoring network. This network covers historical sinkhole areas but also areas that are considered to be stable. Our results reveal ongoing subsidence of up to 30.4 mm a−1 locally, with distinct spatiotemporal variations. Furthermore, we observe a significant time-variable gravity decrease on the order of 8 µGal over 4 years at several measurement points. In the processing workflow, after the application of all required corrections and least squares adjustment to our gravity observations, a significant effect of varying soil water content on the adjusted gravity differences was figured out. Therefore, we place special focus on the correlation of these observations and the correction of the adjusted gravity differences for soil water variations using the Global Land Data Assimilation System (GLDAS) Noah model to separate these effects from subrosion-induced gravity changes. Our investigations demonstrate the feasibility of high-precision time-lapse gravity monitoring in urban areas for sinkhole investigations. Although the observed rates of gravity decrease of 1–2 µGal a−1 are small, we suggest that it is significantly associated with subterranean mass loss due to subrosion processes. We discuss limitations and implications of our approach, as well as give a first quantitative estimation of mass transfer at different depths and for different densities of dissolved rocks.

Challenges in Linking Atmospheric CO2 Concentrations to Fluxes at Local and Regional Scales

1992 ◽  
Vol 40 (5) ◽  
pp. 697 ◽  
Author(s):  
MR Raupach ◽  
OT Denmead ◽  
FX Dunin
Keyword(s):  
Boundary Layer ◽  
Planetary Boundary Layer ◽  
Co2 Flux ◽  
Co2 Concentration ◽  
Atmospheric Co2 ◽  
Wheat Crop ◽  
Turbulent Transfer ◽  
Near Surface ◽  
Scalar Dispersion ◽  
Source Sink

We describe relationships between atmospheric CO2 concentration variations and CO2 source-sink distributions, at two important scales between the single plant and the whole earth: the vegetation canopy and the atmospheric planetary boundary layer. For both these scales, it is shown how knowledge of turbulence and scalar dispersion can be applied to infer CO2 source-sink distributions or fluxes from concentration measurements. At the canopy scale, the turbulent transfer of CO2 and other scalars is non-diffusive close to any point source or sink in the canopy, but diffusive at greater distances. This distinction leads to a physically tenable description of turbulent transfer, and thence to an 'inverse method' for finding the vertical profiles of sources and sinks in the canopy from measured concentration profiles. The method is tested with data from a wheat crop. At the scale of the planetary boundary layer, we consider the daily CO2 concentration drawdown (the depression of the near-surface CO2 concentration below the free-atmosphere value) of typically 20-40 ppm. This is determined by both the regionally averaged CO2 uptake at the surface and the growth of the daytime convective boundary layer (CBL). It is shown that, for a column of air which fills the CBL and is moved across the landscape by the mean wind, the net cumulative surface CO2 flux (in mol m-2) is given to a good approximation by h(t)[Cm(t) - C+]/V, where h(t) is CBL depth, Cm(t) the CO2 concentration in the CBL column in mol mol-1, C+ the concentration above the CBL, V the molar volume and time t is measured from the time at which Cm = C+ in the morning, typically about 0800 hours local time. The resulting CO2 flux estimates are regionally averaged over the trajectory followed by the column. This 'CBL budget method' for inferring surface fluxes is compared with direct measurements of CO2 fluxes, with satisfactory results. The technique has application to scalars other than CO2.

scholarly journals A high precision manometric system for absolute calibrations of CO2in dry air

1997 ◽  
Vol 102 (D5) ◽  
pp. 5885-5894 ◽  
Author(s):  
Cong Long Zhao ◽  
Pieter P. Tans ◽  
Kirk W. Thoning
Keyword(s):  
High Precision ◽  
Dry Air

scholarly journals Assessment of vertically-resolved PM<sub>10</sub> from mobile lidar observations

2009 ◽  
Vol 9 (21) ◽  
pp. 8617-8638 ◽  
Author(s):  
J.-C. Raut ◽  
P. Chazette
Keyword(s):  
Cross Sections ◽  
Urban Areas ◽  
Spatiotemporal Variability ◽  
Paris Area ◽  
Surface Measurements ◽  
Surface Network ◽  
Set Up ◽  
Outlying Regions ◽  
Lidar Observations ◽  
Mass Concentrations

Abstract. We investigate in this study the vertical PM10 distributions from mobile measurements carried out from locations along the Paris Peripherique (highly trafficked beltway around Paris), examine distinctions in terms of aerosol concentrations between the outlying regions of Paris and the inner city and eventually discuss the influence of aerosol sources, meteorology, and dynamics on the retrieved PM10 distributions. To achieve these purposes, we combine in situ surface measurements with active remote sensing observations obtained from a great number of research programs in Paris area since 1999. Two approaches, devoted to the conversion of vertical profiles of lidar-derived extinction coefficients into PM10, have been set up. A very good agreement is found between the theoretical and empirical methods with a discrepancy of 3%. Hence, specific extinction cross-sections at 355 nm are provided with a reasonable relative uncertainty lower than 12% for urban (4.5 m2 g−1) and periurban (5.9 m2 g−1) aersols, lower than 26% for rural (7.1 m2 g−1) aerosols, biomass burning (2.6 m2 g−1) and dust (1.1 m2 g−1) aerosols The high spatial and temporal resolutions of the mobile lidar (respectively 1.5 m and 1 min) enable to follow the spatiotemporal variability of various layers trapping aerosols in the troposphere. Appropriate specific extinction cross-sections are applied in each layer detected in the vertical heterogeneities from the lidar profiles. The standard deviation (rms) between lidar-derived PM10 at 200 m above ground and surface network stations measurements was ~14μg m−3. This difference is particularly ascribed to a decorrelation of mass concentrations in the first meters of the boundary layer, as highlighted through multiangular lidar observations. Lidar signals can be used to follow mass concentrations with an uncertainty lower than 25% above urban areas and provide useful information on PM10 peak forecasting that affect air quality.

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