Using an inverse modelling approach with equifinality control to investigate the dominant controls on snowmelt nutrient export

2019 ◽  
Vol 33 (23) ◽  
pp. 2958-2977 ◽  
Author(s):  
Diogo Costa ◽  
John Pomeroy ◽  
Helen Baulch ◽  
Jane Elliott ◽  
Howard Wheater
Keyword(s):  
Inverse Modelling ◽  
Nutrient Export ◽  
Modelling Approach

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 ◽  
...  
Keyword(s):  
Remote Sensing ◽  
A Priori ◽  
Point Sources ◽  
Airborne Lidar ◽  
Inverse Modelling ◽  
Emission Rates ◽  
Coal Basin ◽  
Upper Silesian Coal Basin ◽  
The Individual ◽  
Modelling Approach

<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>

An inverse modelling approach for estimating vehicular emissions in urban coastal areas of the Messina Strait

2012 ◽  
Vol 50 (1/2/3/4) ◽  
pp. 274 ◽  
Author(s):  
Antonio Cantelli ◽  
Giovanni Leuzzi ◽  
Paolo Monti ◽  
Paolo Viotti
Keyword(s):  
Coastal Areas ◽  
Inverse Modelling ◽  
Vehicular Emissions ◽  
Messina Strait ◽  
Modelling Approach

scholarly journals Sensitivity analysis of methane emissions derived from SCIAMACHY observations through inverse modelling

2005 ◽  
Vol 5 (5) ◽  
pp. 9405-9445 ◽  
Author(s):  
J. F. Meirink ◽  
H. J. Eskes ◽  
A. P. H. Goede
Keyword(s):  
Inverse Modelling ◽  
Limiting Factor ◽  
Atmospheric Methane ◽  
Simulation Experiments ◽  
Cloud Parameters ◽  
Global Emission ◽  
Spatial Coverage ◽  
Methane Source ◽  
The Impact ◽  
Modelling Approach

Abstract. Satellite observations of trace gases in the atmosphere offer a promising method for global verification of emissions and improvement of global emission inventories. Here, an inverse modelling approach based on four-dimensional variational (4D-var) data assimilation is presented and applied to synthetic measurements of atmospheric methane. In this approach emissions and initial concentrations are optimised simultaneously, thus allowing inversions to be carried out on time scales of weeks to months, short compared with the lifetime of methane. Observing System Simulation Experiments (OSSEs) have been performed to demonstrate the feasibility of the method and to investigate the utility of SCIAMACHY observations for methane source estimation. The impact of a number of parameters on the error in the methane emission field retrieved has been analysed. These parameters include the measurement error, the error introduced by the presence of clouds, and the spatial resolution of the emission field. It is shown that 4D-var is an efficient method to deal with large amounts of satellite data and to retrieve emissions at high resolution. Some important conclusions regarding the SCIAMACHY measurements can be drawn: (i) the observations at their estimated precision of 1.5 to 2% will contribute considerably to uncertainty reduction in monthly, subcontinental (~500 km) methane source strengths; (ii) it is essential to take partly cloudy pixels into account in order to achieve sufficient spatial coverage; and (iii) the uncertainty in measured cloud parameters may at some point become the limiting factor, rather than the uncertainty in measured methane.

Assessing the effectiveness of analytical and numerical inverse modelling approach for slug tests interpretation

2021 ◽  
Vol 11 (3) ◽  
pp. 282
Author(s):  
Francesco Chidichimo ◽  
Michele De Biase ◽  
Carmine Fallico ◽  
Samuele De Bartolo ◽  
Mario Ianchello ◽  
...  
Keyword(s):  
Inverse Modelling ◽  
Slug Tests ◽  
Modelling Approach
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