Observational constraints on methane emissions from Polish coal mines using a ground-based remote sensing network

Given its abundant coal mining activities, the Upper Silesian Coal Basin (USCB) in southern Poland is one of the largest sources of anthropogenic methane (CH$_{4}$) emissions in Europe. Here, we report on CH$_{4}$emission estimates for coal mine ventilation facilities in the USCB. Our estimates are driven by pairwise upwind–downwind observations of the column-average dry-air mole fractions of CH$_{4}$ (XCH$_{4}$) by a network of four portable, ground-based, sun-viewing Fourier transform spectrometers of the type EM27/SUN operated during the CoMet campaign in May–June 2018. The EM27/SUN instruments were deployed in the four cardinal directions around the USCB approximately 50 km from the center of the basin. We report on six case studies for which we inferred emissions by evaluating the mismatch between the observed downwind enhancements and simulations based on trajectory calculations releasing particles out of the ventilation shafts using the Lagrangian particle dispersion model FLEXPART. The latter was driven by wind fields calculated by WRF (Weather Research and Forecasting model) under assimilation of vertical wind profile measurements of three co-deployed wind lidars. For emission estimation, we use a Phillips–Tikhonov regularization scheme with the L-curve criterion. Diagnosed by the emissions averaging kernels, we find that, depending on the catchment area of the downwind measurements, our ad hoc network can resolve individual facilities or groups of ventilation facilities but that inspecting the emissions averaging kernels is essential to detect correlated estimates. Generally, our instantaneous emission estimates range between 80 and 133 kt CH$_{4}$ a$^{-1}$ for the southeastern part of the USCB and between 414 and 790 kt CH$_{4}$a$^{-1}$ for various larger parts of the basin, suggesting higher emissions than expected from the annual emissions reported by the E-PRTR (European Pollutant Release and Transfer Register). Uncertainties range between 23 % and 36 %, dominated by the error contribution from uncertain wind fields

High potential for CH4 emission mitigation from oil infrastructure in one of EU's major production regions

Ambitious methane (CH4) emission mitigation represents one of the most effective opportunities to slow the rate of global warming over the next decades. The oil and gas (O&G) sector is a significant source of methane emissions, with technically feasible and cost-effective emission mitigation options. Romania, a key O&G producer within the EU, with the second highest reported annual CH4 emissions from the energy sector in the year 2020 (Greenhouse Gas Inventory Data - Comparison by Category, 2022), can play an important role towards the EU's emission reduction targets. In this study, we quantify CH4 emissions from onshore oil production sites in Romania at source and facility level using a combination of ground- and drone-based measurement techniques. Measured emissions were characterized by heavily skewed distributions, with 10% of the sites accounting for more than 70% of total emissions. Integrating the results from all site-level quantifications with different approaches, we derive a central estimate of 5.4 kg h-1 per site of CH4 (3.6 %-8.4 %, 95% confidence interval) for oil production sites. This estimate represents the third highest when compared to measurementbased estimates of similar facilities from other production regions. Based on our results, we estimate a total of 120 kt CH4 yr-1 (range: 79-180 kt yr-1) from oil production sites in our studied areas in Romania. This is approximately 2.5 times higher than the reported emissions from the entire Romanian oil production sector for 2020. Based on the source-level characterization, up to three-quarters of the detected emissions from oil production sites are related to operational venting. Our results suggest that O&G production infrastructure in Romania holds a massive mitigation potential, specifically by implementing measures to capture the gas and minimize operational venting and leaks

Basic measurements of radiation at station Magurele (2021-05 et seq)

This is a compilation of all short-wave and long-wave radiation datasets from station Magurele that were and are published in the frame of BSRN. New data will be added regularly

Biomass burning aerosol over Romania using dispersion model and Calipso data

The purpose of the study is to analyze the seasonal variability, for the hot and cold seasons, of biomass burning aerosol observed over Romania using forward dispersion calculations based on FLEXPART model. The model was set up to use as input the MODIS fire data with a degree of confidence over 25% after transforming the emitted power in emission rate. The modelled aerosols in this setup was black carbon coated by organics. Distribution in the upper layers were compared to Calipso retrieval

Independent Retrieval of Aerosol Type From Lidar

This paper presents an algorithm for aerosol typing from multiwavelength lidar data, based on Artificial Neural Networks. The aerosol model used to simulate optical properties for the training of the network is described. The algorithm is tested on real observations from ESA-CALIPSO database

Independent Retrieval of Aerosol Type From Lidar

This paper presents an algorithm for aerosol typing from multiwavelength lidar data, based on Artificial Neural Networks. The aerosol model used to simulate optical properties for the training of the network is described. The algorithm is tested on real observations from ESA-CALIPSO database

Biomass burning aerosol over Romania using dispersion model and Calipso data

The purpose of the study is to analyze the seasonal variability, for the hot and cold seasons, of biomass burning aerosol observed over Romania using forward dispersion calculations based on FLEXPART model. The model was set up to use as input the MODIS fire data with a degree of confidence over 25% after transforming the emitted power in emission rate. The modelled aerosols in this setup was black carbon coated by organics. Distribution in the upper layers were compared to Calipso retrieval

Aerosol characterization from active and passive ground measurements and satellite data

One year records of AErosolROboticNEtwork (AERONET) sun photometer measurements were analyzed to investigate the seasonal and daily variations of columnar aerosol optical depth. Some irregularities of this time series are associated with aerosol intrusions. The aerosol layers indicated by these irregularities are identified and characterized using the extensive optical data from coincident CALIPSO satellite observations and ground based LIDAR

Multiyear Aerosol Study Based on Lidar&Sunphotometer Measurements in Romania

This observational study focused on three-years time-averaged data set (January 2012–2015). An investigation of long-term trends was performed on two different data sets derived from active and passive remote sensing measurements in Magurele, Romania. Measurements of sun photometer aerosol optical depth (AOD) at 500 nm and 340 nm show the mean values of 0.230 ±0 .118 and 0.398 ± 0.185, respectively. The lidar AOD at 532 and 355nm has a mean of 0.271 ±.0.164 and 0.472 ± 0.165 respectively. The highest seasonal mean value was measured by the lidar during the summer of 2014 while the lowest seasonal value was measured by the sunphotometer in February 2012. The origin of atmospheric aerosols has been analyzed using both backtajectories of Hysplit and Circulation Type Classification (CTCs) methods