Comment on egusphere-2022-278

A new method is presented to estimate urban hydroxyl radical (OH) concentrations using the downwind decay of the Tropospheric Monitoring Instrument (TROPOMI) derived nitrogen dioxide (NO2) / carbon monoxide (CO) ratio combined with Weather Research Forecast (WRF) simulations. Seasonal OH concentrations, nitrogen oxides (NOx) and CO emissions for summer (June to October, 2018) and winter (November, 2018 to March, 2019) are derived for Riyadh. WRF is able to spatially simulate NO2 and CO urban plumes over Riyadh as observed by TROPOMI. However, WRF-simulated NO2 plumes close to center of the city are overestimated by 25 % in summer and 40 to 50 % in winter compared to TROPOMI observations. WRF simulated CO plumes differ by 10 % with TROPOMI in both seasons. The differences between model and TROPOMI are used to optimize the OH concentration, NOx and CO emissions iteratively using a least squares method. For summer, both the NO2 / CO ratio optimization and the XNO2 optimization imply that the OH prior from the Copernicus Atmospheric Monitoring Service (CAMS) has to be increased by 32.03±4.0 % . The OH estimations from the NO2 / CO ratio and the XNO2 optimization differ by 10 %. Summer Emission Database for Global Atmospheric Research v4.3.2 (EDGAR) NOx and CO emissions over Riyadh need to be increased by 42.1±8.7 % and 100.8±9.5 %. For winter, the optimization method increases OH by ~52.0±5.3 %, while reducing NOx emission by 15.45± 3.4 % and doubling the CO emission. TROPOMI derived OH concentrations and pre-existing Exponentially Modified Gaussian function fit (EMG) method differ by 18 % in summer and 7.5 % in winter, confirming that urban OH concentrations can be reliably estimated using the TROPOMI-observed NO2 / CO ratio.

The natural gas high pressure direct injection (HPDI) engines have attracted attention due to their high combustion stability and thermal efficiency comparable to diesel. However, the nitrogen oxides (NOx) emissions from HPDI engines remain high. In this study, the coupling effects of the exhaust gas recirculation (EGR) and pilot diesel quantity were investigated on a four stroke HPDI engine by simulation. Three pilot diesel quantities and four EGR rates were involved, and the combustion and emission characteristics of the engine were compared and discussed. The results show that with increasing EGR rate, the maximum combustion pressure (Pmax) decreases with different pilot diesel quantity, and the crank angle corresponding to the maximum combustion pressure (CPmax), the crank angle corresponding to the maximum heat release rate (CHRRmax) and the crank angle corresponding to the 50% cumulative heat release (CA50) are all pushed back. NOx emissions decrease gradually with the increase of EGR rate, but soot, unburned hydrocarbon (HC) and carbon monoxide (CO) emissions and methane escape all increase and the indicated thermal efficiency (ITE) decreases. The traditional “trade-off” relationship between NOx and soot emissions still exists on HPDI engine and becomes more obvious as the quantity of pilot diesel increases. NOx and soot emissions can be well balanced at moderate EGR rate. Increasing the quantity of pilot diesel can partially offset the hysteresis effect of EGR on the combustion process. And when the EGR rate is controlled within 30%, increasing the quantity of pilot diesel is beneficial to reduce HC and CO emissions and methane escape. By increasing the quantity of pilot diesel coupled with a moderate level of EGR rate, it is possible to significantly reduce NOx emissions while maintaining the ITE, methane escape and unburned diesel, HC and CO emissions at the same level as without EGR. But soot emissions will increase substantially.

Inverse modeling can provide valuable insights into the sources of atmospheric tracers based on observations and a set of boundary conditions. However, biases in these boundary conditions can lead to biases in the optimized emissions. In this study, we present a series of global inversion experiments of carbon monoxide (CO) emissions using the TM5-4dvar inverse modeling suit constrained by satellite data from the TROPOspheric Monitoring Instrument (TROPOMI) and surface flask measurements from NOAA. These experiments are designed to systematically assess the impact of different boundary conditions, with a particular focus on hydroxyl radical (OH) distributions, a key determinant of both the sources and sinks of CO.Methyl chloroform (MCF) measurements are commonly used to constrain global atmospheric OH climatological fields. We find that our OH fields that are modeled with global atmospheric chemistry calculations are biased high. Despite this bias, these OH fields often provide more realistic lateral distributions than climatological OH fields, particularly in the tropical boundary layer. Another critical boundary condition for inverse modeling of CO is its secondary production from Volatile Organic Compounds (VOCs) and methane. Due to the challenges of directly measuring secondary CO production, model-based estimates are used instead.Our results show that combining modeled secondary CO production estimates with modeled OH fields leads to a closed budget, reducing aliasing across emission categories and enhancing confidence in the optimized anthropogenic and biomass burning emissions. Although the individual budget terms of both the secondary production and the chemical loss of CO may be overestimated, their combined effect yields realistic steady-state CO mixing ratios, as validated by TROPOMI CO observations. This study emphasizes the critical need for improved OH fields to accurately estimate CO emissions, and advances the understanding of potential biases in future inversions.

On-road vehicle emissions of carbon monoxide (CO), nitrogen oxides (NOx), and volatile organic compounds (VOCs) during 1995–2009 in the Atlanta Metropolitan Statistical Area were estimated using the Motor Vehicle Emission Simulator (MOVES) model and data from the National Emissions Inventories and the State of Georgia. Statistically significant downward trends (computed using the nonparametric Theil-Sen method) in annual on-road CO, NOx, and VOC emissions of 6.1%, 3.3%, and 6.0% per year, respectively, are noted during the 1995–2009 period despite an increase in total vehicle distance traveled. The CO and NOx emission trends are correlated with statistically significant downward trends in ambient air concentrations of CO and NOx in Atlanta ranging from 8.0% to 11.8% per year and from 5.8% to 8.7% per year, respectively, during similar time periods. Weather-adjusted summertime ozone concentrations in Atlanta exhibited a statistically significant declining trend of 2.3% per year during 2001–2009. Although this trend coexists with the declining trends in on-road NOx, VOC, and CO emissions, identifying the cause of the downward trend in ozone is complicated by reductions in multiple precursors from different source sectors.Implications:Large reductions in on-road vehicle emissions of CO and NOx in Atlanta from the late 1990s to 2009, despite an increase in total vehicle distance traveled, contributed to a significant improvement in air quality through decreases in ambient air concentrations of CO and NOx during this time period. Emissions reductions in motor vehicles and other source sectors resulted in these improvements and the observed declining trend in ozone concentrations over the past decade. Although these historical trends cannot be extrapolated to the future because pollutant concentration contributions due to on-road vehicle emissions will likely become an increasingly smaller fraction of the atmospheric total, they provide an indication of the benefits of past control measures.

Abstract. The Sentinel-5P TROPOspheric Monitoring Instrument (TROPOMI) instrument, launched in October 2017, provides unique observations of atmospheric trace gases at a high resolution of about 5 km, with near-daily global coverage, resolving individual sources like thermal powerplants, industrial complexes, fires, medium-scale towns, roads, and shipping routes. Even though Sentinel-5P (S5P) is a global mission, these datasets are especially well suited to test high-resolution regional-scale air quality (AQ) models and provide valuable input for emission inversion systems. In Europe, the Copernicus Atmosphere Monitoring Service (CAMS) has implemented an operational regional AQ forecasting capability based on an ensemble of several European models, available at a resolution of 0.1∘ × 0.1∘. In this paper, we present comparisons between TROPOMI observations of nitrogen dioxide (NO2) and the CAMS AQ forecasts and analyses of NO2. We discuss the different ways of making these comparisons and present quantitative results in the form of maps for individual days, summer and winter months, and a time series for European subregions and cities between May 2018 and March 2021. The CAMS regional products generally capture the fine-scale daily and averaged features observed by TROPOMI in much detail. In summer, the comparison shows a close agreement between TROPOMI and the CAMS ensemble NO2 tropospheric columns with a relative difference of up to 15 % for most European cities. In winter, however, we find a significant discrepancy in the column amounts over much of Europe, with relative differences up to 50 %. The possible causes for these differences are discussed, focusing on the possible impact of retrieval and modeling errors. Apart from comparisons with the CAMS ensemble, we also present results for comparisons with the individual CAMS models for selected months. Furthermore, we demonstrate the importance of the free tropospheric contribution to the estimation of the tropospheric column and thus include profile information from the CAMS configuration of the ECMWF's (European Centre for Medium-Range Weather Forecasts) global integrated model above 3 km altitude in the comparisons. We also show that replacing the global 1∘ × 1∘ a priori information in the retrieval by the regional 0.1∘ × 0.1∘ resolution profiles of CAMS leads to significant changes in the TROPOMI-retrieved tropospheric column, with typical increases at the emission hotspots up to 30 % and smaller increases or decreases elsewhere. As a spinoff, we present a new TROPOMI NO2 level 2 (L2) data product for Europe, based on the replacement of the original TM5-MP generated global a priori profile by the regional CAMS ensemble profile. This European NO2 product is compared with ground-based remote sensing measurements of six Pandora instruments of the Pandonia Global Network and nine Multi-AXis Differential Optical Absorption Spectroscopy (MAX-DOAS) instruments. As compared to the standard S5P tropospheric NO2 column data, the overall bias of the new product for all except two stations is 5 % to 12 % smaller, owing to a reduction in the multiplicative bias. Compared to the CAMS tropospheric NO2 columns, dispersion and correlation parameters with respect to the standard data are, however, superior.

Emission regulations are steadily becoming more stringent, compelling researchers to adopt extra precautions to minimize the release of pollutants into the environment. For this purpose, many methods are employed by researchers. Among these, Water-Emulsified Fuels (WEFs) stand out as an effective solution for obtaining decrement on nitrogen oxide (NOx) and Particulate Matter (PM) emissions, concurrently. In this study, emulsion fuels were prepared using diesel, sunflower biodiesel, distilled water, and surfactants (Span 80 + Tween 80). The fuels are denoted as D (diesel), DW5 (93% diesel + 5% water + 2% surfactants), DW10 (88% diesel + 10% water + 2% surfactants), B (biodiesel), BW5 (93% biodiesel + 5% water + 2% surfactants), and BW10 (88% biodiesel + 10% water + 2% surfactants). Test fuels were prepared by stirring the emulsion mixture at a speed of 1500 rpm using a magnetic stirrer at room temperature for one hour, and the fuel properties were then specified. Finally, performance and emission tests were performed on a turbocharged, water-cooled, 4-stroke, and 4-cylinder diesel engine. WEFs led to decreased engine torque and brake power values, along with lowered carbon monoxide (CO) and nitrogen oxide (NOx) emissions. DW5 and DW10 reduced engine torque by 6.27% and 9.82%, and brake power by 6.49% and 10.31%, respectively, compared to D. Similarly, BW5 and BW10 decreased engine torque by 4.63% and 8.12%, and brake power by 4.73% and 8.38%, respectively, compared to B. Additionally, DW5 and DW10 fuels reduced CO emissions by 1.61% and 2.85%, and NOx emissions by 8% and 12.61%, respectively. BW5 and BW10 fuels lowered CO emissions by 1.56% and 3.67%, and NOx emissions by 3.87% and 10.47%, respectively.

High-spatiotemporal-resolution inverse estimation of CO and NOx emission reductions during emission control periods with a modified ensemble Kalman filter

Combination of high cetane diesel fuel and post injection mode in a diesel engine: A path towards lower exhaust emissions

Abstract. Shipping is an important source of nitrogen oxide (NOx) emissions worldwide, contributing to air pollution and negatively affecting marine environments, ecosystems, and biodiversity. TROPOMI (TROPOspheric Monitoring Instrument) on board the Sentinel-5 Precursor (S5P) has significantly enhanced the ability to detect ship emissions from space due to its low measurement noise levels and high spatial resolution of 5.5×3.5 km2 at nadir. This study uses the TROPOMI tropospheric NO2 slant column density (tSCD) to identify global shipping routes qualitatively. Preprocessing techniques, including iterative high-pass and Fourier filtering, markedly improve the detection of shipping lanes, revealing previously undetectable routes. Our analysis examines the impact of high-pass-filter box sizes, demonstrating that smaller sizes enhance the visibility of narrow shipping features, whereas larger box sizes increase overall NO2 signals. Additionally, we investigate various flagging criteria that affect NO2 signal distribution, highlighting the critical importance of careful selection for accurate emission monitoring. Filtered TROPOMI NO2 tSCDs over oceans show a strong correlation with shipping activities, as confirmed by comparison with the CAMS-GLOB-SHIP (Copernicus Atmospheric Monitoring Service for Global Shipping) inventory, and also reveal unknown shipping routes in regions such as the Bering Sea. Furthermore, TROPOMI effectively captures NO2 emissions from offshore oil and gas platforms, with NO2 hotspots in the TROPOMI data aligning well with locations of offshore installations listed in the OSPAR (Oslo and Paris Commission) and BOEM (Bureau of Ocean Energy Management) inventories. Lastly, the filtered TROPOMI NO2 tropospheric vertical column densities (tVCDs) are compared with the high-pass-filtered NO2 tVCDs from the CAMS (Copernicus Atmospheric Monitoring Service) model, which has a coarse spatial resolution of 0.4°. While both datasets effectively identify global shipping lanes, the high-pass-filtered CAMS NO2 tVCDs are significantly higher than the filtered TROPOMI NO2 tVCDs in the North Atlantic and strongly depend on the masking threshold in the high-pass filtering method in the South Atlantic Ocean.

<div class="section abstract"><div class="htmlview paragraph">Reactivity Controlled Compression Ignition (RCCI) has demonstrated diesel-like or better brake thermal efficiency with significant reductions in nitrogen oxide (NO<sub>X</sub>) and particulate matter (PM) emissions. Hydrocarbon (HC) and carbon monoxide (CO) emission levels, on the other hand, are higher and similar to those of port-fuel-injected (PFI) gasoline engines. The higher HC and CO emissions combined with the lower exhaust temperatures during RCCI operation present a challenge for current exhaust aftertreatment technologies. The reduction of HC and CO emissions in a lean environment is typically achieved with an oxidation catalyst. In this work, several diesel oxidation catalysts (DOC) with different precious metal loadings were evaluated for effectiveness to control HC and CO emissions from RCCI combustion in a light-duty multi-cylinder engine operating on gasoline and diesel fuels. Each catalyst was evaluated under steady-state engine operation with temperatures ranging from 160 to 260°C. A shift to a higher light-off temperature was observed during the RCCI operation. In addition to the steady-state experiments, the performance of the DOCs were evaluated during multi-mode engine operation by switching from diesel-like combustion at higher exhaust temperature and low HC/CO emissions to RCCI combustion at lower temperature and higher HC/CO emissions. High CO and HC emissions from RCCI generated an exotherm temporary keeping the catalyst above the light-off temperature.</div></div>

<strong class="journal-contentHeaderColor">Abstract.</strong> Since 2017 the Tropospheric Monitoring Instrument (TROPOMI) onboard ESA&rsquo;s Copernicus Sentinel-5 satellite (S5-P) has provided the operational Carbon Monoxide (CO) data product with daily global coverage on a spatial resolution of 5.5 &times; 7 km² (7&times; 7 km² before August 2019). The European Centre for Medium-Range Weather Forecasts (ECMWF) plans to assimilate the retrieved total columns and the corresponding vertical sensitivities in the Copernicus Atmosphere Monitoring Service Integrated Forecasting System (CAMS-IFS) to improve forecasts of the atmospheric chemical composition. The TROPOMI data will primarily constrain the vertical integrated CO field (VCD) of CAMS-IFS but to a lesser extent also its vertical CO distribution as well. For clear-sky conditions, the vertical sensitivity of the TROPOMI CO data product is useful throughout the atmosphere but for cloudy scenes it varies due to cloud shielding and light scattering. To assess the profile information, we deploy a posteriori profile retrieval that combines individual TROPOMI CO column retrievals with different vertical sensitivities to obtain a vertical CO profile that is then a representative average for the chosen spatial and temporal domain. We demonstrate the approach on three CO pollution cases. For the so called &ldquo;Rabbit Foot Fire&rdquo; in Idaho on the 12 August 2018, we estimate a CO profile showing the pollution at an altitude of about 5 km in good agreement with airborne in-situ measurements of the Biomass Burning fluxes of trace gases and aerosols (BB-FLUX) field campaign. The distinct CO enhancement in a plume aloft, decoupled from the ground, is sensed by TROPOMI but is not present in the CAMS-IFS model. For a large-scale event, we analyzed the CO pollution from Siberian wildfires that took place from 14 to 18 August 2018. The TROPOMI data is estimating the height of the pollution plume over Canada at 7 km in agreement with CAMS-IFS. However, CAMS-IFS underestimates the enhanced CO vertical column densities sensed by TROPOMI within the plume by more than 100 ppb. Finally, we study the seasonal biomass burning in the Amazon. During the burning season (1&ndash;15 August 2019) the CO profile retrieved from the TROPOMI measurements agrees well with the one of CAMS-IFS with a similar vertical shape between ground and 14 km altitude. Hence, our results indicate that assimilating TROPOMI CO retrieval with different vertical sensitivities e.g., under clear-sky and cloudy conditions provide information about the vertical distribution of CO.

<strong class="journal-contentHeaderColor">Abstract.</strong> The Tropospheric Monitoring Instrument (TROPOMI) on the Copernicus Sentinel 5 Precursor (S5P) satellite, launched in October 2017, provides a wealth of atmospheric composition data, including total columns of carbon monoxide (TCCO) at high horizontal resolution (5.5 km <span class="inline-formula">×</span> 7 km). Near-real-time TROPOMI TCCO data have been monitored in the global data assimilation system of the Copernicus Atmosphere Monitoring Service (CAMS) since November 2018 to assess the quality of the data. The CAMS system already routinely assimilates TCCO data from the Measurement of Pollution in the Troposphere (MOPITT) instrument and the Infrared Atmospheric Sounding Interferometer (IASI) outside the polar regions. The assimilation of TROPOMI TCCO data in the CAMS system was tested for the period 6 July to 31 December 2021, i.e. after the TROPOMI algorithm update to version 02.02.00 in July 2021. By assimilating TROPOMI TCCO observations, the CAMS CO columns increase by on average 8 %, resulting in an improved fit to independent observations (IAGOS aircraft profiles and NDACC Fourier transform infrared (FTIR) tropospheric and total-column CO data) compared to a version of the CAMS system where only TCCO from MOPITT and IASI is assimilated. The largest absolute and relative changes from the assimilation of TROPOMI CO are found in the lower and middle troposphere, i.e. that part of the atmosphere that is not already well constrained by the assimilated TIR MOPITT and IASI data. The largest impact near the surface comes from clear-sky TROPOMI data over land, and additional vertical information comes from the retrievals of measurements in cloudy conditions. July and August 2021 saw record numbers of boreal wildfires over North America and Russia, leading to large amounts of CO being released into the atmosphere. The paper assesses the impact of TROPOMI CO assimilation on selected CO plumes more closely. While the CO column can be well constrained by the assimilation of TROPOMI CO data, and the fit to individual IAGOS CO profiles in the lower and middle troposphere is considerably improved, the TROPOMI CO columns do not provide further constraints on individual plumes that are transported across continents and oceans at altitudes above 500 hPa.

<strong class="journal-contentHeaderColor">Abstract.</strong> The Tropospheric Monitoring Instrument (TROPOMI) on the Copernicus Sentinel 5 Precursor (S5P) satellite, launched in October 2017, provides a wealth of atmospheric composition data, including total columns of carbon monoxide (TCCO) at high horizontal resolution (5.5 km <span class="inline-formula">×</span> 7 km). Near-real-time TROPOMI TCCO data have been monitored in the global data assimilation system of the Copernicus Atmosphere Monitoring Service (CAMS) since November 2018 to assess the quality of the data. The CAMS system already routinely assimilates TCCO data from the Measurement of Pollution in the Troposphere (MOPITT) instrument and the Infrared Atmospheric Sounding Interferometer (IASI) outside the polar regions. The assimilation of TROPOMI TCCO data in the CAMS system was tested for the period 6 July to 31 December 2021, i.e. after the TROPOMI algorithm update to version 02.02.00 in July 2021. By assimilating TROPOMI TCCO observations, the CAMS CO columns increase by on average 8 %, resulting in an improved fit to independent observations (IAGOS aircraft profiles and NDACC Fourier transform infrared (FTIR) tropospheric and total-column CO data) compared to a version of the CAMS system where only TCCO from MOPITT and IASI is assimilated. The largest absolute and relative changes from the assimilation of TROPOMI CO are found in the lower and middle troposphere, i.e. that part of the atmosphere that is not already well constrained by the assimilated TIR MOPITT and IASI data. The largest impact near the surface comes from clear-sky TROPOMI data over land, and additional vertical information comes from the retrievals of measurements in cloudy conditions. July and August 2021 saw record numbers of boreal wildfires over North America and Russia, leading to large amounts of CO being released into the atmosphere. The paper assesses the impact of TROPOMI CO assimilation on selected CO plumes more closely. While the CO column can be well constrained by the assimilation of TROPOMI CO data, and the fit to individual IAGOS CO profiles in the lower and middle troposphere is considerably improved, the TROPOMI CO columns do not provide further constraints on individual plumes that are transported across continents and oceans at altitudes above 500 hPa.

This study presents a three-dimensional simulation of wet combustion in the annular combustion chamber of a C30 microturbine using a hydrogen-methane fuel mixture. The research aims to minimize exhaust emissions, including nitrogen oxides (NOx) and carbon monoxide (CO), and reduce fuel consumption. A partially premixed combustion model has been utilized to accurately simulate the combustion process within the chamber. The impact of steam addition (wet combustion) is also analyzed. The simulation employs the k-ε Realizable turbulence model and probability density function (PDF) for chemical reactions. The fuel mixture is adjusted by adding hydrogen in increments of 10%, resulting in a final composition of 40% hydrogen and 60% methane. With hydrogen’s high heating value, the chamber temperature reaches 2376 K, significantly increasing NOx and CO emissions. To control the temperature and maintain turbine operating conditions, the fuel mass flow rate is reduced by 35%, ensuring a consistent turbine inlet temperature. At this temperature, CO and CO2 emissions decrease by 16% and 61%, respectively, while NOx emissions increase due to hydrogen’s flame characteristics. The introduction of humidity levels of 2.5%, 5%, 7.5%, and 10% in the inlet air reduces NOx emissions by 68% in the case where the fuel mixture contains 10% hydrogen, with this reduction occurring at 10% humidity. Additionally, a 48% reduction in CO emissions was observed when the fuel mixture contained 40% hydrogen, and this reduction also occurred at 10% humidity. Wet combustion also enhances temperature uniformity in the chamber. These findings highlight the potential of hydrogen-methane mixtures with wet combustion to enable low-emission, efficient microturbines, supporting sustainable energy goals.

Regulations on environmental effects due to such issues as nitrogen oxide (NOx) and carbon monoxide (CO) emissions from thermal power plants have become stricter[1]; hence the need for compliance with these regulations has been increasing. To meet this need, several technologies with respect to fuel combustion, exhaust gas treatment and operational control have been developed[2-4]. The technologies for the fuel combustion and the exhaust gas treatment include a low NOx burner and an air quality control system, and they are capable of reducing impact on the environment as physical and chemical implementation methods. The operational control technology for the thermal power plants is constantly required to receive changes in operational conditions. It is difficult to realize operational control which responds to combustion properties. To overcome this issue, the operational control must be able to reduce NOx and CO emissions flexibly in accordance with such changes. Robustness is also required in such control because the measured NOx and CO data often include noise. Therefore, a robust and flexible plant control system is strongly desired to reduce environmental effects from thermal power plants efficiently. Several studies have proposed plant control technologies to reduce the environmental effects[4-10]. These technologies are classified into two types of methods: model based and non-model based methods. The former methods include an optimization algorithm and a numerical model to estimate plant properties using neural networks (NNs)[11,12] and multivariable model predictive control[13]. The optimization algorithm searches for optimal control signals to reduce NOx and CO emissions using the numerical model. The latter methods have no models and they generates the optimal control signals by fuzzy logic[14]. A fuzzy logic controller outputs the optimal control signals for multivariable inputs using fuzzy rule bases. The fuzzy rule bases are based on a priori knowledge of plant control, and they can be tuned by parameters. These technologies require the measured plant data for initial tuning of the model properties and the parameters of rules when the technologies are installed in plants. It usually takes some time to collect enough plant data. In addition, the search for control