Abstract. A system for measuring the two-dimensional (2-D) spatial distribution of atmospheric CO 2 over complex industrial sites and urban areas on the order of 1 to 30 km 2 every few minutes with a spatial resolution as high as tens of meters has been developed and demonstrated over the past 3 years. The greenhouse gas (GHG) laser imaging tomography experiment (GreenLITE™) provides improved measurement capabilities for applications ranging from automated 24∕7 monitoring of ground carbon storage/sequestration (GCS) sites to long-duration real-time analyses of GHG sources and sinks in urban environments. GreenLITE combines a set of sensors based on an intensity modulated continuous wave approach with 2-D sparse tomographic reconstruction mechanisms to compute a 2-D map of CO 2 concentrations over the area of interest. GreenLITE systems have recently been deployed at a number of test facilities, including a 4000-h demonstration at a GCS site in Illinois and an urban deployment in Paris, France, from November 2015 to the present. This paper describes the GreenLITE concept and the associated measurement capabilities and provides proof of concept results and analyses of observations from both short-term tests as well as longer-term industrial and urban deployments. © The Authors. Published by SPIE under a Creative Commons Attribution 3.0 Unported License. Distribution or reproduction of this work in whole or in part requires full attribution of the original publication, including its DOI.
The quantification of CO2 emissions from cities using atmospheric measurements requires accurate knowledge of the atmospheric transport. Complex urban terrains significantly modify surface roughness, augment surface energy budgets, and create heat islands, all of which lead to lower horizontal winds and enhanced convection over urban areas. The question remains whether these processes should be included in atmospheric transport models that are used for city scale CO2 inversion, and whether they need to be tailored on a city basis. In this study, we use the WRF model over Paris to address the following research question: does WRF runs at a 3 km resolution, including urban effects and the assimilation of local weather data, perform better than ECMWF forecasts that give fields at 16 km resolution? The analysis of model performances focuses on three variables: air temperature, wind and the planetary boundary layer (PBL) height. The results show that the use of objective analysis and nudging tools are required to obtain good agreements between WRF simulated fields with observations. Surface temperature is well reproduced by both WRF and ECMWF forecasts, with correlation coefficients with hourly observations larger than 0.92 and MBEs within 1°C over one month. Wind speed correlations with hourly observations are similar for WRF (range 0.76~0.85 across stations) and ECMWF (0.79~0.84), but the associated RMSEs and MBEs are better for ECMWF. Conversely, WRF outperforms ECMWF forecasts for its description of wind direction, horizontal and vertical gradients. Sensitivity tests with different WRF physics schemes show that the wind speed and the PBL height are strongly influenced by PBL schemes. The marginal advantage of WRF over ECMWF for the desired application is sufficient to motive additional testing with prescribed CO2 flux maps for comparing modeled CO2 concentrations with available observations in an urban environment.
Abstract. This work assesses the impact of uncertainties in atmospheric state knowledge on retrievals of carbon dioxide column amounts (XCO 2 ) from laser differential absorption spectroscopy (LAS) measurements. LAS estimates of XCO 2 columns are normally derived not only from differential absorption observations but also from measured or prior knowledge of atmospheric state that includes temperature, moisture, and pressure along the viewing path. In the case of global space-based monitoring systems, it is often difficult if not impossible to provide collocated in situ measurements of atmospheric state for all observations, so retrievals often rely on collocated remote-sensed data or values derived from numerical weather prediction (NWP) models to describe the atmospheric state. A radiative transfer-based simulation framework, combined with representative global upper-air observations and matched NWP profiles, was used to assess the impact of model differences on estimates of column CO 2 and O 2 concentrations. These analyses focus on characterizing these errors for LAS measurements of CO 2 in the 1.57-μm region and of O 2 in the 1.27-μm region. The results provide a set of signal-to-noise metrics that characterize the errors in retrieved values associated with uncertainties in atmospheric state and provide a method for selecting optimal differential absorption line pairs to minimize the impact of these noise terms.
Abstract. In 2015, the Greenhouse gas Laser Imaging Tomography Experiment (GreenLITE™) measurement system was deployed for a long-duration experiment in the center of Paris, France. The system measures near-surface atmospheric CO2 concentrations integrated along 30 horizontal chords ranging in length from 2.3 to 5.2 km and covering an area of 25 km2 over the complex urban environment. In this study, we use this observing system together with six conventional in situ point measurements and the Weather Research and Forecasting model coupled with Chemistry (WRF-Chem) and two urban canopy schemes (Urban Canopy Model – UCM; Building Effect Parameterization – BEP) at a horizontal resolution of 1 km to analyze the temporal and spatial variations in CO2 concentrations within the city of Paris and its vicinity for the 1-year period spanning December 2015 to November 2016. Such an analysis aims at supporting the development of CO2 atmospheric inversion systems at the city scale. Results show that both urban canopy schemes in the WRF-Chem model are capable of reproducing the seasonal cycle and most of the synoptic variations in the atmospheric CO2 point measurements over the suburban areas as well as the general corresponding spatial differences in CO2 concentration that span the urban area. However, within the city, there are larger discrepancies between the observations and the model results with very distinct features during winter and summer. During winter, the GreenLITE™ measurements clearly demonstrate that one urban canopy scheme (BEP) provides a much better description of temporal variations and horizontal differences in CO2 concentrations than the other (UCM) does. During summer, much larger CO2 horizontal differences are indicated by the GreenLITE™ system than both the in situ measurements and the model results, with systematic east–west variations.
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