Changes in Power Plant NOx Emissions over Northwest Greece Using a Data Assimilation Technique

Abstract

In this work, we investigate the ability of a data assimilation technique and space-borne observations to quantify and monitor changes in nitrogen oxides (NOx) emissions over Northwestern Greece for the summers of 2018 and 2019. In this region, four lignite-burning power plants are located. The data assimilation technique, based on the Ensemble Kalman Filter method, is employed to combine space-borne atmospheric observations from the high spatial resolution Sentinel-5 Precursor (S5P) Tropospheric Monitoring Instrument (TROPOMI) and simulations using the LOTOS-EUROS Chemical Transport model. The Copernicus Atmosphere Monitoring Service-Regional European emissions (CAMS-REG, version 4.2) inventory based on the year 2015 is used as the a priori emissions in the simulations. Surface measurements of nitrogen dioxide (NO2) from air quality stations operating in the region are compared with the model surface NO2 output using either the a priori (base run) or the a posteriori (assimilated run) NOx emissions. Relative to the a priori emissions, the assimilation suggests a strong decrease in concentrations for the station located near the largest power plant, by 80% in 2019 and by 67% in 2018. Concerning the estimated annual a posteriori NOx emissions, it was found that, for the pixels hosting the two largest power plants, the assimilated run results in emissions decreased by ~40–50% for 2018 compared to 2015, whereas a larger decrease, of ~70% for both power plants, was found for 2019, after assimilating the space-born observations. For the same power plants, the European Pollutant Release and Transfer Register (E-PRTR) reports decreased emissions in 2018 and 2019 compared to 2015 (−35% and −38% in 2018, −62% and −72% in 2019), in good agreement with the estimated emissions. We further compare the a posteriori emissions to the reported energy production of the power plants during the summer of 2018 and 2019. Mean decreases of about −35% and−63% in NOx emissions are estimated for the two larger power plants in summer of 2018 and 2019, respectively, which are supported by similar decreases in the reported energy production of the power plants (~−30% and −70%, respectively).

A New Separation Methodology for the Maritime Sector Emissions over the Mediterranean and Black Sea Regions

“…This work can be extended to generate a top-down emission inventory using the TROPOMI observations and data assimilation based on the LOTOS-EUROS. This technique has already been demonstrated successfully over point NOx emission sources [37]. The clear separation of maritime traffic in well-defined lanes crossing the Mediterranean Seas demonstrated in this work will allow us to apply the same data assimilation technique to update marine pollution-related emissions.…”

“…More specifically, a recent analysis studying the sensitivity of the OMI observed NO 2 columns to anthropogenic emissions concluded that the contribution of the increasing shipping emissions in adjacent areas may mask a significant part of national emission reductions [35]. An evaluation of the model performance over Greece was recently conducted while, over high emitting locations such as power plants, the modelled columns were found to be highly spatially correlated (R = 0.95) with the TROPOMI tropospheric columns [36,37]. LOTOS-EUROS NO 2 simulations were also performed in order to quantify the effects of the lockdown due to the COVID-19 pandemic over Greece as observed by TROPOMI [27].…”

Comparison of S5P/TROPOMI Inferred NO₂ Surface Concentrations with in-situ Measurements over Central Europe

“…A model evaluation against ground-based measurements over two major Greek cities has shown that the modelled NO2 surface concentrations show a high spatial correlation of 0.86 and a moderate underestimation of about 10% [33]. When compared to industrial stations located near power plants in Greece, LOTOS-EUROS NO2 surface concentrations mean seasonal bias improves to 2 μg/m 3 from 10 μg/m 3 , after assimilating the space-borne TROPOMI NO2 observations [34]. The model has also been recently used to estimate changes in NO2 emissions due to the COVID-19 pandemic restrictive measures [26] and to study NO2 concentrations attributed to shipping activity in the Mediterranean and the Black Sea basin [35].…”

Estimating NOx LOTOS-EUROS CTM Emission Parameters over the Northwest of South America through 4DEnVar TROPOMI NO2 Assimilation

“…The model profile is convoluted with these averaging kernels, provided in the satellite download data product to simulate the retrieval for a correct model and satellite retrieval products comparison [48]. The averaging kernels are implemented to the model output at the time of the nearest satellite overpass, which is usually at 18:30 UTC [49]. A selection on the pixel quality flag (qa) was been applied, averaging over the pixels filtered for (qa) > 0.55.…”

“…Different works have studied the effect of assimilation of satellite retrieved NO 2 data on emissions or Surface concentrations in a global domain [57,60] pointing towards the ability to estimate emissions by assimilating satellite observations that are taken only once per day over one place concerning with the NO 2 atmospheric life time during different times of the year. On another side regional domain estimation studies like Skoulidou et al [49], Wang et al [61] orient our subsequent emission experiments toward the interest of persistent emission estimation capabilities.…”