scholarly journals Towards spaceborne monitoring of localized CO<sub>2</sub> emissions: an instrument concept and first performance assessment

2020 ◽  
Vol 13 (6) ◽  
pp. 2887-2904 ◽  
Author(s):  
Johan Strandgren ◽  
David Krutz ◽  
Jonas Wilzewski ◽  
Carsten Paproth ◽  
Ilse Sebastian ◽  
...  
Keyword(s):  
Performance Assessment ◽  
Co2 Emissions ◽  
Co2 Emission ◽  
Power Plants ◽  
Co2 Flux ◽  
Point Sources ◽  
Noise Model ◽  
Spectral Window ◽  
Instrument Noise ◽  
Noise Error

Abstract. The UNFCCC (United Nations Framework Convention on Climate Change) requires the nations of the world to report their carbon dioxide (CO2) emissions. The independent verification of these reported emissions is a cornerstone for advancing towards the emission accounting and reduction measures agreed upon in the Paris Agreement. In this paper, we present the concept and first performance assessment of a compact spaceborne imaging spectrometer with a spatial resolution of 50×50 m2 that could contribute to the “monitoring, verification and reporting” (MVR) of CO2 emissions worldwide. CO2 emissions from medium-sized power plants (1–10 Mt CO2 yr−1), currently not targeted by other spaceborne missions, represent a significant part of the global CO2 emission budget. In this paper we show that the proposed instrument concept is able to resolve emission plumes from such localized sources as a first step towards corresponding CO2 flux estimates. Through radiative transfer simulations, including a realistic instrument noise model and a global trial ensemble covering various geophysical scenarios, it is shown that an instrument noise error of 1.1 ppm (1σ) can be achieved for the retrieval of the column-averaged dry-air mole fraction of CO2 (XCO2). Despite a limited amount of information from a single spectral window and a relatively coarse spectral resolution, scattering by atmospheric aerosol and cirrus can be partly accounted for in the XCO2 retrieval, with deviations of at most 4.0 ppm from the true abundance for two-thirds of the scenes in the global trial ensemble. We further simulate the ability of the proposed instrument concept to observe CO2 plumes from single power plants in an urban area using high-resolution CO2 emission and surface albedo data for the city of Indianapolis. Given the preliminary instrument design and the corresponding instrument noise error, emission plumes from point sources with an emission rate down to the order of 0.3 Mt CO2 yr−1 can be resolved, i.e., well below the target source strength of 1 Mt CO2 yr−1. This leaves a significant margin for additional error sources, like scattering particles and complex meteorology, and shows the potential for subsequent CO2 flux estimates with the proposed instrument concept.

scholarly journals Towards space-borne monitoring of localized CO<sub>2</sub> emissions: an instrument concept and first performance assessment

2020 ◽  
Author(s):  
Johan Strandgren ◽  
David Krutz ◽  
Jonas Wilzewski ◽  
Carsten Paproth ◽  
Ilse Sebastian ◽  
...  
Keyword(s):  
Power Plant ◽  
Performance Assessment ◽  
Co2 Emissions ◽  
Co2 Emission ◽  
Power Plants ◽  
Point Sources ◽  
Source Strength ◽  
Spectral Window ◽  
Instrument Noise ◽  
Noise Error

Abstract. The UNFCCC (United Nations Framework Convention on Climate Change) requires the nations of the world to report their carbon dioxide (CO2) emissions. Independent verification of these reported emissions is a corner stone for advancing towards emission accounting and reduction measures agreed upon in the Paris agreement. In this paper, we present the concept and first performance assessment of a compact space-borne imaging spectrometer that could support the task of "monitoring, verification, reporting" (MVR) of CO2 emissions worldwide. With a single spectral window in the short-wave infrared spectral region and a spatial resolution of 50 x 50 m2, the goal is to reliably estimate the CO2 emissions from localized sources down to a source strength of approx. 1 MtCO2 yr-1, hence complementing other planned CO2 monitoring missions, like the planned European Carbon Constellation (CO2M). Resolving CO2 plumes also from medium-sized power plants (1–10 MtCO2 yr-1) is of key importance for independent quantification of CO2 emissions from the coal-fired power plant sector. Through radiative transfer simulations, including a realistic instrument noise model and a global trial ensemble covering various geophysical scenarios, it is shown that an instrument noise error of 1.1 ppm (1σ) can be achieved for the retrieval of the column-averaged dry-air mole fraction of CO2 (XCO2). Despite limited amount of information from a single spectral window and a relatively coarse spectral resolution, scattering by atmospheric aerosol and cirrus can be partly accounted for in the XCO2 retrieval, with deviations of at most 4.0 ppm from the true abundance for 68 % of the scenes in the global trial ensemble. We further simulate the ability of the proposed instrument concept to observe CO2 plumes from single power plants in an urban area using high-resolution CO2 emission and surface albedo data for the city of Indianapolis. Given the preliminary instrument design and the corresponding instrument noise error, emission plumes from point sources with an emission rate down to the order of 0.3 MtCO2 yr-1 can be resolved, i.e. well below the target source strength of 1 MtCO2 yr-1. Hence, the proposed instrument concept could be able to resolve and quantify the CO2 plumes from localized point sources responsible for approx. 90 % of the power plant CO2 emission budget, assuming global coverage through a fleet of sensors and favorable conditions with respect to illumination and particle scattering.

scholarly journals Towards space-borne monitoring of localized CO2 emissions: an instrument concept and first performance assessment

2020 ◽  
Author(s):  
Johan Strandgren ◽  
Jonas Wilzewski ◽  
David Krutz ◽  
Carsten Paproth ◽  
Ilse Sebastian ◽  
...  
Keyword(s):  
Performance Assessment ◽  
Co2 Emissions ◽  
Spectral Resolution ◽  
Power Plants ◽  
Point Sources ◽  
Noise Model ◽  
Source Strength ◽  
Spectral Window ◽  
Instrument Noise ◽  
Noise Error

&lt;p&gt;Independent verification of reported carbon dioxide (CO2) emissions is a corner stone for advancing towards emission accounting and reduction measures agreed upon in the Paris agreement. Here, we present the concept and first performance assessment of a compact space-borne imaging spectrometer that could support the task of &quot;monitoring, verification, reporting'' (MVR) of CO2 emissions worldwide. With a ground resolution of 50m x 50m, the goal is to estimate the CO2 emissions from localized sources down to a source strength of approx. 1 MtCO2/yr, hence complementing other planned CO2 monitoring missions, like the European Carbon Constellation (CO2M).&lt;/p&gt;&lt;p&gt;Such fine ground resolution requires a trade-off towards coarse spectral resolution in order to achieve sufficient noise performance. Since fine ground resolution also implies limited ground coverage, a fleet of satellites, each carrying such an instrument is envisioned, requiring a relatively low-cost and simple design, e.g. by restricting the spectrometer to a single spectral window. To demonstrate that column-averaged dry-air mole-fractions of CO2 (XCO2) can be reliably retrieved with a single spectral window and at the required coarse spectral resolution, we use degraded GOSAT short-wave infrared spectra of the CO2 bands near 1.6 and 2.0 &amp;#181;m, respectively.&lt;/p&gt;&lt;p&gt;Through radiative transfer simulations, including a realistic instrument noise model and a global trial ensemble covering various geophysical scenarios, it is further shown that an instrument noise error of 1.1 ppm (1sigma) can be achieved for the XCO2 retrieval. Despite the limited amount of information from a single spectral window and a relatively coarse spectral resolution, scattering by atmospheric aerosol and cirrus can be partly accounted for, with deviations of at most 4.0 ppm from the true abundance for 68 % of the scenes in the global trial ensemble.&lt;/p&gt;&lt;p&gt;Finally we simulate the ability of the proposed instrument concept to observe CO2 plumes from single power plants in an urban environment using high-resolution CO2 emission and surface albedo data for the city of Indianapolis. Given the preliminary instrument design and the corresponding instrument noise error, emission plumes from point sources with an emission rate down to the order of 0.3 MtCO2/yr can be resolved, i.e. well below the target source strength of 1 MtCO2/yr. Hence, some margin for additional error sources like scattering particles and complex meteorology exists.&lt;/p&gt;

scholarly journals Estimating CO2 Emissions from Large Scale Coal-Fired Power Plants Using OCO-2 Observations and Emission Inventories

Atmosphere ◽  
2021 ◽  
Vol 12 (7) ◽  
pp. 811
Author(s):  
Yaqin Hu ◽  
Yusheng Shi
Keyword(s):  
Power Plant ◽  
Co2 Emissions ◽  
Atmospheric Carbon Dioxide ◽  
Power Plants ◽  
Large Scale ◽  
Global Climate ◽  
Gaussian Model ◽  
Point Sources ◽  
Emission Inventories ◽  
Bottom Up

The concentration of atmospheric carbon dioxide (CO2) has increased rapidly worldwide, aggravating the global greenhouse effect, and coal-fired power plants are one of the biggest contributors of greenhouse gas emissions in China. However, efficient methods that can quantify CO2 emissions from individual coal-fired power plants with high accuracy are needed. In this study, we estimated the CO2 emissions of large-scale coal-fired power plants using Orbiting Carbon Observatory-2 (OCO-2) satellite data based on remote sensing inversions and bottom-up methods. First, we mapped the distribution of coal-fired power plants, displaying the total installed capacity, and identified two appropriate targets, the Waigaoqiao and Qinbei power plants in Shanghai and Henan, respectively. Then, an improved Gaussian plume model method was applied for CO2 emission estimations, with input parameters including the geographic coordinates of point sources, wind vectors from the atmospheric reanalysis of the global climate, and OCO-2 observations. The application of the Gaussian model was improved by using wind data with higher temporal and spatial resolutions, employing the physically based unit conversion method, and interpolating OCO-2 observations into different resolutions. Consequently, CO2 emissions were estimated to be 23.06 ± 2.82 (95% CI) Mt/yr using the Gaussian model and 16.28 Mt/yr using the bottom-up method for the Waigaoqiao Power Plant, and 14.58 ± 3.37 (95% CI) and 14.08 Mt/yr for the Qinbei Power Plant, respectively. These estimates were compared with three standard databases for validation: the Carbon Monitoring for Action database, the China coal-fired Power Plant Emissions Database, and the Carbon Brief database. The comparison found that previous emission inventories spanning different time frames might have overestimated the CO2 emissions of one of two Chinese power plants on the two days that the measurements were made. Our study contributes to quantifying CO2 emissions from point sources and helps in advancing satellite-based monitoring techniques of emission sources in the future; this helps in reducing errors due to human intervention in bottom-up statistical methods.

scholarly journals Joint inverse estimation of fossil fuel and biogenic CO2 fluxes in an urban environment: An observing system simulation experiment to assess the impact of multiple uncertainties

Elem Sci Anth ◽  
2018 ◽  
Vol 6 ◽  
Author(s):  
Kai Wu ◽  
Thomas Lauvaux ◽  
Kenneth J. Davis ◽  
Aijun Deng ◽  
Israel Lopez Coto ◽  
...  
Keyword(s):  
High Resolution ◽  
Urban Environment ◽  
Co2 Emissions ◽  
Fossil Fuel ◽  
Atmospheric Transport ◽  
System Simulation ◽  
Co2 Flux ◽  
Point Sources ◽  
Co2 Fluxes ◽  
The Impact

The Indianapolis Flux Experiment aims to utilize a variety of atmospheric measurements and a high-resolution inversion system to estimate the temporal and spatial variation of anthropogenic greenhouse gas emissions from an urban environment. We present a Bayesian inversion system solving for fossil fuel and biogenic CO2 fluxes over the city of Indianapolis, IN. Both components were described at 1 km resolution to represent point sources and fine-scale structures such as highways in the a priori fluxes. With a series of Observing System Simulation Experiments, we evaluate the sensitivity of inverse flux estimates to various measurement deployment strategies and errors. We also test the impacts of flux error structures, biogenic CO2 fluxes and atmospheric transport errors on estimating fossil fuel CO2 emissions and their uncertainties. The results indicate that high-accuracy and high-precision measurements produce significant improvement in fossil fuel CO2 flux estimates. Systematic measurement errors of 1 ppm produce significantly biased inverse solutions, degrading the accuracy of retrieved emissions by about 1 µmol m–2 s–1 compared to the spatially averaged anthropogenic CO2 emissions of 5 µmol m–2 s–1. The presence of biogenic CO2 fluxes (similar magnitude to the anthropogenic fluxes) limits our ability to correct for random and systematic emission errors. However, assimilating continuous fossil fuel CO2 measurements with 1 ppm random error in addition to total CO2 measurements can partially compensate for the interference from biogenic CO2 fluxes. Moreover, systematic and random flux errors can be further reduced by reducing model-data mismatch errors caused by atmospheric transport uncertainty. Finally, the precision of the inverse flux estimate is highly sensitive to the correlation length scale in the prior emission errors. This work suggests that improved fossil fuel CO2 measurement technology, and better understanding of both prior flux and atmospheric transport errors are essential to improve the accuracy and precision of high-resolution urban CO2 flux estimates.

scholarly journals What would dense atmospheric observation networks bring to the quantification of city CO<sub>2</sub> emissions?

2016 ◽  
Vol 16 (12) ◽  
pp. 7743-7771 ◽  
Author(s):  
Lin Wu ◽  
Grégoire Broquet ◽  
Philippe Ciais ◽  
Valentin Bellassen ◽  
Felix Vogel ◽  
...  
Keyword(s):  
Co2 Emissions ◽  
Metropolitan Area ◽  
Land Surface ◽  
Co2 Emission ◽  
Power Plants ◽  
Lower Cost ◽  
Residential Buildings ◽  
Inversion Method ◽  
Monitoring Tool ◽  
Model Framework

Abstract. Cities currently covering only a very small portion ( <  3 %) of the world's land surface directly release to the atmosphere about 44 % of global energy-related CO2, but they are associated with 71–76 % of CO2 emissions from global final energy use. Although many cities have set voluntary climate plans, their CO2 emissions are not evaluated by the monitoring, reporting, and verification (MRV) procedures that play a key role for market- or policy-based mitigation actions. Here we analyze the potential of a monitoring tool that could support the development of such procedures at the city scale. It is based on an atmospheric inversion method that exploits inventory data and continuous atmospheric CO2 concentration measurements from a network of stations within and around cities to estimate city CO2 emissions. This monitoring tool is configured for the quantification of the total and sectoral CO2 emissions in the Paris metropolitan area (∼  12 million inhabitants and 11.4 TgC emitted in 2010) during the month of January 2011. Its performances are evaluated in terms of uncertainty reduction based on observing system simulation experiments (OSSEs). They are analyzed as a function of the number of sampling sites (measuring at 25 m a.g.l.) and as a function of the network design. The instruments presently used to measure CO2 concentrations at research stations are expensive (typically ∼  EUR 50 k per sensor), which has limited the few current pilot city networks to around 10 sites. Larger theoretical networks are studied here to assess the potential benefit of hypothetical operational lower-cost sensors. The setup of our inversion system is based on a number of diagnostics and assumptions from previous city-scale inversion experiences with real data. We find that, given our assumptions underlying the configuration of the OSSEs, with 10 stations only the uncertainty for the total city CO2 emission during 1 month is significantly reduced by the inversion by ∼  42 %. It can be further reduced by extending the network, e.g., from 10 to 70 stations, which is promising for MRV applications in the Paris metropolitan area. With 70 stations, the uncertainties in the inverted emissions are reduced significantly over those obtained using 10 stations: by 32 % for commercial and residential buildings, by 33 % for road transport, by 18 % for the production of energy by power plants, and by 31 % for total emissions. These results indicate that such a high number of stations would be likely required for the monitoring of sectoral emissions in Paris using this observation–model framework. They demonstrate some high potential that atmospheric inversions can contribute to the monitoring and/or the verification of city CO2 emissions (baseline) and CO2 emission reductions (commitments) and the advantage that could be brought by the current developments of lower-cost medium precision (LCMP) sensors.

scholarly journals A global map of emission clumps for future monitoring of fossil fuel CO<sub>2</sub> emissions from space

2019 ◽  
Vol 11 (2) ◽  
pp. 687-703 ◽  
Author(s):  
Yilong Wang ◽  
Philippe Ciais ◽  
Grégoire Broquet ◽  
François-Marie Bréon ◽  
Tomohiro Oda ◽  
...  
Keyword(s):  
Co2 Emissions ◽  
Land Surface ◽  
Urban Areas ◽  
Power Plants ◽  
Fossil Fuel ◽  
Large Fraction ◽  
Point Sources ◽  
Bottom Up ◽  
Large Power ◽  
Data Product

Abstract. A large fraction of fossil fuel CO2 emissions emanate from “hotspots”, such as cities (where direct CO2 emissions related to fossil fuel combustion in transport, residential, commercial sectors, etc., excluding emissions from electricity-producing power plants, occur), isolated power plants, and manufacturing facilities, which cover a small fraction of the land surface. The coverage of all high-emitting cities and point sources across the globe by bottom-up inventories is far from complete, and for most of those covered, the uncertainties in CO2 emission estimates in bottom-up inventories are too large to allow continuous and rigorous assessment of emission changes (Gurney et al., 2019). Space-borne imagery of atmospheric CO2 has the potential to provide independent estimates of CO2 emissions from hotspots. But first, what a hotspot is needs to be defined for the purpose of satellite observations. The proposed space-borne imagers with global coverage planned for the coming decade have a pixel size on the order of a few square kilometers and a XCO2 accuracy and precision of <1 ppm for individual measurements of vertically integrated columns of dry-air mole fractions of CO2 (XCO2). This resolution and precision is insufficient to provide a cartography of emissions for each individual pixel. Rather, the integrated emission of diffuse emitting areas and intense point sources is sought. In this study, we characterize area and point fossil fuel CO2 emitting sources which generate coherent XCO2 plumes that may be observed from space. We characterize these emitting sources around the globe and they are referred to as “emission clumps” hereafter. An algorithm is proposed to identify emission clumps worldwide, based on the ODIAC global high-resolution 1 km fossil fuel emission data product. The clump algorithm selects the major urban areas from a GIS (geographic information system) file and two emission thresholds. The selected urban areas and a high emission threshold are used to identify clump cores such as inner city areas or large power plants. A low threshold and a random walker (RW) scheme are then used to aggregate all grid cells contiguous to cores in order to define a single clump. With our definition of the thresholds, which are appropriate for a space imagery with 0.5 ppm precision for a single XCO2 measurement, a total of 11 314 individual clumps, with 5088 area clumps, and 6226 point-source clumps (power plants) are identified. These clumps contribute 72 % of the global fossil fuel CO2 emissions according to the ODIAC inventory. The emission clumps is a new tool for comparing fossil fuel CO2 emissions from different inventories and objectively identifying emitting areas that have a potential to be detected by future global satellite imagery of XCO2. The emission clump data product is distributed from https://doi.org/10.6084/m9.figshare.7217726.v1.

scholarly journals A methodology to constrain carbon dioxide emissions from coal-fired power plants using satellite observations of co-emitted nitrogen dioxide

2020 ◽  
Vol 20 (1) ◽  
pp. 99-116 ◽  
Author(s):  
Fei Liu ◽  
Bryan N. Duncan ◽  
Nickolay A. Krotkov ◽  
Lok N. Lamsal ◽  
Steffen Beirle ◽  
...  
Keyword(s):  
Nitrogen Dioxide ◽  
Co2 Emissions ◽  
Co2 Emission ◽  
Power Plants ◽  
Operating Conditions ◽  
Satellite Observations ◽  
Nox Emissions ◽  
Bottom Up ◽  
Monitoring Instrument ◽  
The Us

Abstract. We present a method to infer CO2 emissions from individual power plants based on satellite observations of co-emitted nitrogen dioxide (NO2), which could serve as complementary verification of bottom-up inventories or be used to supplement these inventories. We demonstrate its utility on eight large and isolated US power plants, where accurate stack emission estimates of both gases are available for comparison. In the first step of our methodology, we infer nitrogen oxides (NOx) emissions from US power plants using Ozone Monitoring Instrument (OMI) NO2 tropospheric vertical column densities (VCDs) averaged over the ozone season (May–September) and a “top-down” approach that we previously developed. Second, we determine the relationship between NOx and CO2 emissions based on the direct stack emissions measurements reported by continuous emissions monitoring system (CEMS) programs, accounting for coal quality, boiler firing technology, NOx emission control device type, and any change in operating conditions. Third, we estimate CO2 emissions for power plants using the OMI-estimated NOx emissions and the CEMS NOx∕CO2 emission ratio. We find that the CO2 emissions estimated by our satellite-based method during 2005–2017 are in reasonable agreement with the US CEMS measurements, with a relative difference of 8 %±41 % (mean ± standard deviation). The broader implication of our methodology is that it has the potential to provide an additional constraint on CO2 emissions from power plants in regions of the world without reliable emissions accounting. We explore the feasibility by comparing the derived NOx∕CO2 emission ratios for the US with those from a bottom-up emission inventory for other countries and applying our methodology to a power plant in South Africa, where the satellite-based emission estimates show reasonable consistency with other independent estimates. Though our analysis is limited to a few power plants, we expect to be able to apply our method to more US (and world) power plants when multi-year data records become available from new OMI-like sensors with improved capabilities, such as the TROPOspheric Monitoring Instrument (TROPOMI), and upcoming geostationary satellites, such as the Tropospheric Emissions: Monitoring Pollution (TEMPO) instrument.

scholarly journals Detecting long-term changes in point source fossil CO<sub>2</sub> emissions with tree ring archives

2016 ◽  
Author(s):  
E. D. Keller ◽  
J. C. Turnbull ◽  
M. W. Norris
Keyword(s):  
Point Source ◽  
Co2 Emissions ◽  
Tree Ring ◽  
Power Plants ◽  
Transport Model ◽  
Atmospheric Transport ◽  
Model Simulation ◽  
Point Sources ◽  
Long Term Changes

Abstract. We examine the utility of tree ring 14C archives for detecting long term changes in fossil CO2 emissions from a point source. Trees assimilate carbon from the atmosphere during photosynthesis, in the process faithfully recording the average atmospheric 14C content in each new annual tree ring. Using 14C as a proxy for fossil CO2, we examine interannual variability over six years of fossil CO2 observations between 2004-05 and 2011-12 from two trees growing near the Kapuni Natural Gas Plant in rural Taranaki, New Zealand. We quantify the amount of variability that can be attributed to transport and meteorology by simulating constant point source fossil CO2 emissions over the observation period with the atmospheric transport model WindTrax. We compare model simulation results to observations and calculate the amount of change in emissions that we can detect with new observations over annual or multi-year time periods given both measurement uncertainty of 1ppm and the modelled variation in transport. In particular, we ask, what is the minimum amount of change in emissions that we can detect using this method, given a reference period of six years? We find that changes of 42% or more could be detected in a new sample from one year at the same observation location, or 22% in the case of four years of new samples. This threshold lowers and the method becomes more practical the more the size of the signal increases. For point sources 10 times larger than the Kapuni plant (a more typical size for power plants worldwide), it would be possible to detect sustaine d emissions changes on the order of 10% given suitable meteorology and observations.

scholarly journals Determination of the emission rates of CO<sub>2</sub> point sources with airborne lidar

2021 ◽  
Vol 14 (4) ◽  
pp. 2717-2736
Author(s):  
Sebastian Wolff ◽  
Gerhard Ehret ◽  
Christoph Kiemle ◽  
Axel Amediek ◽  
Mathieu Quatrevalet ◽  
...  
Keyword(s):  
Co2 Emissions ◽  
Power Plants ◽  
Point Sources ◽  
Airborne Lidar ◽  
Observation System ◽  
Emission Rates ◽  
Flux Method ◽  
Cross Sectional ◽  
Mixing Ratios ◽  
The Cross

Abstract. Anthropogenic point sources, such as coal-fired power plants, produce a major share of global CO2 emissions. International climate agreements demand their independent monitoring. Due to the large number of point sources and their global spatial distribution, the implementation of a satellite-based observation system is convenient. Airborne active remote sensing measurements demonstrate that the deployment of lidar is promising in this respect. The integrated path differential absorption lidar CHARM-F is installed on board an aircraft in order to detect weighted column-integrated dry-air mixing ratios of CO2 below the aircraft along its flight track. During the Carbon Dioxide and Methane Mission (CoMet) in spring 2018, airborne greenhouse gas measurements were performed, focusing on the major European sources of anthropogenic CO2 emissions, i.e., large coal-fired power plants. The flights were designed to transect isolated exhaust plumes. From the resulting enhancement in the CO2 mixing ratios, emission rates can be derived via the cross-sectional flux method. On average, our results roughly correspond to reported annual emission rates, with wind speed uncertainties being the major source of error. We observe significant variations between individual overflights, ranging up to a factor of 2. We hypothesize that these variations are mostly driven by turbulence. This is confirmed by a high-resolution large eddy simulation that enables us to give a qualitative assessment of the influence of plume inhomogeneity on the cross-sectional flux method. Our findings suggest avoiding periods of strong turbulence, e.g., midday and afternoon. More favorable measurement conditions prevail during nighttime and morning. Since lidars are intrinsically independent of sunlight, they have a significant advantage in this regard.

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