The stabilized methane–air counterflow flame into a plus-shaped chamber with platinum catalyst–coated walls: An emission estimation

Analysis of unsteady CH4/Air counterflow premixed flame into a newly designed plus-shaped channel is investigated in this study. The main objective is to explore the impact of platinum catalytic–coated walls of the combustion chamber on the flame characteristics and pollutant emissions. The OpenFOAM platform is used as a numerical simulation tool to investigate the effects of various equivalence ratios, from the range of lean to rich flames, and passing the reaction time on the counterflow flame characteristics and pollutant emissions of a plus-shaped chamber with the platinum catalyst–coated wall. Results show that the integrated temperature over the proposed geometry with platinum surfaces increases by 18% compared to the non-catalytic case. The numerical simulation revealed that presence of the platinum catalyst on the wall of the chamber has significant impact on reducing the pollutant emissions. This is evident as a 99.5% decrease on NO2 emission and a 58% reduction on CO2 formation are found.

Assessment of the Influence of Added Resistance on Ship Pollutant Emissions and Freight Throughput Using High-Fidelity Numerical Tools

The reduction of ship pollutants is a key issue in the international agenda. Emissions estimation is usually based on standard calculations that consider the different scenarios of ships. This work presents research on the influence of added resistance on ship emissions and freight throughput. First, a methodology to assess the added resistance influence is shown. The procedure is applied to a roll on-roll off ship under two load conditions. Analyses are computed to value wind- and wave-added resistances for different seasons. An investigation on ship pollutant emissions for a whole route is performed. Moreover, the influence of added resistance on the ship freight throughput is analyzed. Finally, some relevant information is concluded. For instance, a difference of up to 53% in pollutant emission estimation is observed if added resistance is considered. Additionally, the navigation in added resistance conditions could lead to a freight loss of 18% per operational year.

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 for anthropogenic methane (CH4) emissions in Europe. Here, we report on CH4 emission estimates for coal mine ventilation facilities in the USCB. Our estimates are driven by pair-wise upwind-downwind observations of the column-average dry-air mole fractions of CH4 (XCH4) 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 were deployed in the four cardinal directions around the USCB in approx. 50 km distance to 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 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 averaging kernels is essential to detected correlated estimates. Generally, our instantaneous emission estimates range between 80 and 133 kt CH4 a−1 for the south-eastern part of the USCB and between 414 and 790 kt CH4 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.

Methane Emission Estimation of Oil and Gas Sector: A Review of Measurement Technologies, Data Analysis Methods and Uncertainty Estimation

The emission estimation of the oil and gas sector, which involves field test measurements, data analysis, and uncertainty estimation, precedes effective emission mitigation actions. A systematic comparison and summary of these technologies and methods are necessary to instruct the technology selection and for uncertainty improvement, which is not found in existing literature. In this paper, we present a review of existing measuring technologies, matching data analysis methods, and newly developed probabilistic tools for uncertainty estimation and try to depict the process for emission estimation. Through a review, we find that objectives have a determinative effect on the selection of measurement technologies, matching data analysis methods, and uncertainty estimation methods. And from a systematic perspective, optical instruments may have greatly improved measurement accuracy and range, yet data analysis methods might be the main contributor of estimation uncertainty. We suggest that future studies on oil and gas methane emissions should focus on the analysis methods to narrow the uncertainty bond, and more research on uncertainty generation might also be required.

Bottom–Up Inventory of Residential Combustion Emissions in Poland for National Air Quality Modelling: Current Status and Perspectives

For many years, the Polish air quality modelling system was decentralized, which significantly hampered the appropriate development of methodologies, evaluations, and comparisons of modelling results. The major contributor to air pollution in Poland is the residential combustion sector. This paper demonstrates a novel methodology for residential emission estimation utilized for national air quality modelling and assessment. Our data were compared with EMEP and CAMS inventories, and despite some inequalities in country totals, spatial patterns were similar. We discuss the shortcomings of the presented method and draw conclusions for future improvements.

Estimating aerosol emission from SPEXone on the NASA PACE mission using an ensemble Kalman Smoother: Observing System Simulation Experiments (OSSEs)

We present a top-down approach for aerosol emission estimation from SPEXone polarimetric retrievals related to the aerosol amount, size, and absorption using a fixed-lag ensemble Kalman smoother (LETKS) in combination with the ECHAM-HAM model. We assess the system by performing Observing System Simulation Experiments (OSSEs), in order to evaluate the ability of the future multi-angle polarimeter instrument, SPEXone, as well as a satellite with near perfect global coverage. In our OSSEs, the Nature Run (NAT) is a simulation by the global climate aerosol model ECHAM-HAM with altered aerosol emissions. The Control (CTL) and the data assimilation (DAS) experiments are composed of an ensemble of ECHAM-HAM simulations, where the default aerosol emissions are perturbed with factors taken from a Gaussian distribution. Synthetic observations, specifically Aerosol Optical Depth at 550 nm (AOD550), Angstrom Exponent from 550 nm to 865 nm (AE550-865) and Single Scattering Albedo at 550 nm (SSA550) are assimilated in order to estimate the aerosol emission fluxes of desert dust (DU), sea salt (SS), organic carbon (OC), black carbon (BC) and sulphate (SO4), along with the emission fluxes of two SO4 precursor gases (SO2, DMS). The synthetic observations are sampled from the NAT according to two satellite observing systems, with different spatial coverages. The first is the sensor SPEXone, a hyperspectral multi-angle polarimeter with a narrow swath (~100 km), that will be a part of the NASA PACE mission. The second is an idealized sensor that can retrieve observations over the whole globe even under cloudy conditions. The prior emission global relative Mean Absolute Error (MAE) before the assimilation ranges from 33 % to 117 %. Depending on the species, the assimilated observations sampled using the idealized sensor, reduce this error to equal to or lower than 5 %. Despite its limited coverage, the SPEXone sampling bares similar results, with somewhat larger errors for DU and SS (both having a MAE equal to 11 %). Further, experiments show that doubling the measurement error, increases the global relative MAE to 22 % for DU and SS. The emission estimation of the other species is not affected as much by these changes. In addition, the role of biased meteorology on emission estimation was quantified by using two different datasets (ERA-5 and ERA-interim) to nudge the U and V wind components of the model. The results reveal that when the wind of DAS uses a different reanalysis dataset than the NAT the estimated SS emissions are negatively affected the most, while the estimated emissions of DU, OC, BC and SO2 are negatively affected to a smaller extent. If the DAS uses dust or sea salt emission parametrisations that are very different from the NAT, posterior emissions can still be successfully estimated but this experiment revealed that the source location is important for the estimation of dust emissions. This work suggests that the upcoming SPEXone sensor will provide observations related to aerosol amount, size and absorption with sufficient coverage and accuracy, in order to estimate aerosol emissions.