Estimating local CH4 emissions in the Upper Silesian Coal Basin using inverse modelling

2021 ◽  
Author(s):  
Sebastian Wolff ◽  
Friedemann Reum ◽  
Christoph Kiemle ◽  
Gerhard Ehret ◽  
Mathieu Quatrevalet ◽  
...  

<p>Methane (CH<sub>4</sub>) is the second most important anthropogenic greenhouse gas (GHG) with respect to radiative forcing. Since pre-industrial times, the globally averaged CH<sub>4</sub> concentration in the atmosphere has risen by a factor of 2.5. A large fraction of global anthropogenic CH<sub>4</sub> emissions originates from localized point sources, e.g. coal mine ventilation shafts. International treaties foresee GHG emission reductions, entailing independent monitoring and verification support capacities. Considering the spatially widespread distribution of point sources, remote sensing approaches are favourable, in order to enable rapid survey of larger areas. In this respect, active remote sensing by airborne lidar is promising, such as provided by the integrated-path differential-absorption lidar CHARM-F operated by DLR. Installed onboard the German research aircraft HALO, CHARM-F serves as a demonstrator for future satellite missions, e.g. MERLIN. CHARM-F simultaneously measures weighted vertical column mixing ratios of CO<sub>2</sub> and CH<sub>4</sub> below the aircraft. In spring 2018, during the CoMet field campaign, measurements were taken in the Upper Silesian Coal Basin (USCB) in Poland. The USCB is considered to be a European hotspot of CH<sub>4</sub> emissions, covering an area of approximately 50 km × 50 km. Due to the high number of coal mines and density of ventilation shafts in the USCB, individual CH<sub>4</sub> exhaust plumes can overlap. This makes simple approaches to determine the emission rates of single shafts, i.e. the cross-sectional flux method, difficult. Therefore, we use an inverse modelling approach to obtain an estimate of the individual emission rates. Specifically, we employ the Weather Research and Forecast Model (WRF) coupled to the CarbonTracker Data Assimilation Shell (CTDAS), an Ensemble Kalman Filter. CTDAS-WRF propagates an ensemble realization of the a priori CH<sub>4</sub> emissions forward in space and time, samples the simulated CH<sub>4</sub> concentrations along the measurement’s flight path, and scales the a priori emission rates to optimally fit the measured values, while remaining tied to the prior. Hereby, we obtain a regularized a posteriori best emission estimate for the individual ventilation shafts. Here, we report on the results of this inverse modelling approach, including individual and aggregated emission estimates, their uncertainties, and to which extent the data are able to constrain individual emitters independently.</p>

2021 ◽  
Author(s):  
Sebastian Wolff ◽  
Gerhard Ehret ◽  
Christoph Kiemle ◽  
Axel Amediek ◽  
Mathieu Quatrevalet ◽  
...  

<p>A large fraction of global anthropogenic greenhouse gas emissions originates from localized point sources. International climate treaties foresee their independent monitoring. Given the high number of point sources and their global spatial distribution, local monitoring is challenging, whereas a global satellite-based observing system is advantageous. In this perspective, a promising measurement approach is active remote sensing by airborne lidar, such as provided by the integrated-path differential-absorption lidar CHARM-F. Installed onboard the German research aircraft HALO, CHARM-F serves as a demonstrator for future satellite missions, e.g. MERLIN. CHARM-F simultaneously measures weighted vertical column mixing ratios of CO<sub>2</sub> and CH<sub>4</sub> below the aircraft. In spring 2018, during the CoMet field campaign, measurements were taken at the largest European point sources of anthropogenic CO<sub>2</sub> and CH<sub>4</sub> emissions, i.e. coal-fired power plants and ventilation shafts of coal mines. The measurement flights aimed to transect isolated exhaust plumes, in order to derive the corresponding emission rates from the resulting enhancement in concentration, along the plume crossing. For the first time, multiple measurements of power plant emissions were made using airborne lidar. On average, we find that our measurements are consistent with reported numbers, but observe high discrepancies between successive plume crossings of up to 50 %. As an explanation for these high discrepancies, we assess the influence of inhomogeneity in the exhaust plume, caused by atmospheric turbulence. This assessment is based on the Weather Research and Forecasting Model (WRF). We find a pronounced diurnal cycle of plume inhomogeneity associated with local turbulence, predominately driven by midday solar irradiance. Our results reveal that periods of high turbulence, specifically during midday and afternoon, should be avoided whenever possible. Since lidar is intrinsically independent of sun light, measurements can be performed under conditions of weak turbulence, such as at night or in the early morning.</p>


2021 ◽  
Vol 14 (4) ◽  
pp. 2717-2736
Author(s):  
Sebastian Wolff ◽  
Gerhard Ehret ◽  
Christoph Kiemle ◽  
Axel Amediek ◽  
Mathieu Quatrevalet ◽  
...  

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.


2019 ◽  
Vol 65 (3-4) ◽  
pp. 191-197 ◽  
Author(s):  
Ivan Sačkov ◽  
Ľubomír Scheer ◽  
Tomáš Bucha

Abstract In this study, the individual tree detection approach (ITD) was used to estimate forest stand variables, such as mean height, mean diameter, and total volume. Specifically, we applied the multisource-based method implemented in reFLex software (National Forest Centre, Slovakia) which uses all the information contained in the original point cloud and a priori information. For the accuracy assessment, four reference forest stands with different types of species mixture and the area of 7.5 ha were selected and measured. Furthermore, independent measurements of 1 372 trees were made for the construction of allometric models. The author’s ITD-based method provided slightly more accurate estimations for stands with substantial or moderate dominance of coniferous trees. However, no statistically significant effect of species mix on the overall accuracy was confirmed (p < 0.05). The root mean square error did not exceed 1.9 m for mean height, 3.0 cm for mean diameter, and 12.88 m3 ha−1 for total volume.


2020 ◽  
Author(s):  
Sebastian Wolff ◽  
Gerhard Ehret ◽  
Christoph Kiemle ◽  
Axel Amediek ◽  
Mathieu Quatrevalet ◽  
...  

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 high amount of point sources and their global spatial distribution, a mobile measurement approach with fast spatial coverage is needed. Active remote sensing measurements by airborne lidar show much promise in this respect. The integrated-path differential-absorption lidar CHARM–F is installed onboard an aircraft, in order to detect weighted vertical columns of CO2 mixing ratios, 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 mixings ratios, emission rates can be derived in terms of the cross–sectional flux method. On average, we find our results roughly corresponding to reported annual emission rates, but observe significant variations between individual overflights ranging up to a factor of 2. We suppose that these variations are mostly driven by turbulence. This hypothesis is supported 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.


2020 ◽  
Author(s):  
John Douros ◽  
Henk Eskes ◽  
Pepijn Veefkind

&lt;pre class=&quot;moz-quote-pre&quot;&gt;In our contribution we present comparisons between TROPOMI observations of NO2 (nitrogen dioxide) and the CAMS regional forecasts and analyses for Europe. The Sentinel-5P TROPOMI instrument, launched in October 2017, provides unique observations of atmospheric trace gases at a high resolution of about 5 km, resolving individual point sources, medium-scale towns, roads and shipping routes. The datasets have a global daily coverage, but these datasets are especially well suited to test high-resolution regional-scale air quality models and provide valuable input for emission inversion systems. In Europe, the Copernicus Atmosphere Monitoring Service (CAMS) has implemented a regional air quality forecasting capability for Europe based on an ensemble of 7-9 European models, available at a resolution of 0.1x0.1 degree. &lt;br /&gt;We discuss the different ways of making these comparisons, and present the quantitative results for summer and winter months and individual days. The models generally capture the fine-scale daily and averaged features observed by TROPOMI in much detail. We show that replacing the global 1x1 degree a-priori information in the retrieval by the regional 0.1x0.1 degree profiles of CAMS leads to significant changes (increases at hotspot emission locations) in the TROPOMI retrieved tropospheric column. Apart from comparing with the ensemble model, we also present the results for the individual CAMS models. &lt;/pre&gt;


Sign in / Sign up

Export Citation Format

Share Document