Improved catalog of NO<sub><i>x</i></sub> point source  emissions (version 2)

Beirle, Steffen; Borger, Christian; Jost, Adrian; Wagner, Thomas

doi:10.5194/essd-15-3051-2023

Cited by 15 publications

(12 citation statements)

References 25 publications

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“…For the detected point sources, the NOx to NO2 ratio of 1.38 was used and a 15 km radius considered for emission quantification. Analyzing our results with data available from other studies from other parts of the world (Beirle et al, 2023), NOx emissions from CCI BCS and CT PP (0.238±0.151 kg/s) are comparable with emissions from the Samra Combined Cycle Gas Turbine Power Plant in Jordan (0.239±0.063 kg/s), the Ladyzhyn power station in Ladyzhyn, Vinnytsia, Ukraine (0.239±0.036 kg/s), the Anuppur Thermal Power Project in Jethari, Jaithari, Annupur, Madhya Pradesh, India (0.236±0.071 kg/s) and the Agios Dimitrios power station in Kozani, Greece (0.236± 0.052kg/s).…”

Section: Mobile Mini-doas Measurementsmentioning

confidence: 93%

“…2, while Figure 3 shows SO2 columns quantified during the same measurement. A recent study published by Beirle et al, (2023) reports NOx emissions released to the atmosphere between 2018 and 2021 from point sources (such as power plants) using TROPOspheric Monitoring Instrument (TROPOMI) measurements of NO2 to derive them. For the detected point sources, the NOx to NO2 ratio of 1.38 was used and a 15 km radius considered for emission quantification.…”

Section: Mobile Mini-doas Measurementsmentioning

confidence: 99%

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Emissions to the atmosphere by power plants in Baja California Sur, Mexico

Rivera-Cárdenas,

Barrera-Huertas,

Valenzuela

et al. 2024

Renew. energ. biomass sustain

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Sulfur dioxide (SO2) and nitrogen dioxide (NO2) emissions to the atmosphere released by three power plants located in Baja California Sur, Mexico, were quantified using mini-DOAS instruments. In La Paz municipality, the Punta Prieta Power Plant released 65.67±77.80 tons/day of SO2 and 6.66±12.57 tons/day of NO2, while the Internal Combustion Power Plant Baja California Sur released 44.72±5.37 tons/day of SO2 and 8.27±1.72 tons/day of NO2. In the municipality of Comondú, the Internal Combustion Power Plant Agustín Olachea released 18.17±8.00 tons/day of SO2 and 0.67±0.32 tons/day of NO2. Comparisons of our measurements with emissions inventories and annual operating reports for the Punta Prieta Power Plant are in good agreement, however, we found differences for the Internal Combustion Power Plant Baja California Sur and the Internal Combustion Power Plant Agustín Olachea. Our analyses show that the Punta Prieta Power Plant has increased its SO2 and NO2 emissions between 2013 and 2022. The Internal Combustion Power Plant Baja California Sur has increased its SO2 emissions, while NO2 emissions have declined between 2013 and 2022. The Internal Combustion Power Plant Agustín Olachea has been decreasing its SO2 and NO2 emissions between 2010 and 2022, albeit in 2018, there was a considerable increase of NO2 emissions.

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Section: Mobile Mini-doas Measurementsmentioning

confidence: 93%

Section: Mobile Mini-doas Measurementsmentioning

confidence: 99%

Emissions to the atmosphere by power plants in Baja California Sur, Mexico

Rivera-Cárdenas,

Barrera-Huertas,

Valenzuela

et al. 2024

Renew. energ. biomass sustain

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“…In this sense, performing intercomparisons against existing satellite-derived point source catalogues (e.g. Beirle et al, 2023;Fioletov et al, 2023) could also help to better constrain bottom-up emissions from co-emitted species.…”

Section: Future Perspectivementioning

confidence: 99%

A global catalogue of CO₂ emissions and co-emitted species from power plants, including high-resolution vertical and temporal profiles

Guevara,

Enciso,

Tena

et al. 2024

Earth Syst. Sci. Data

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Abstract. We present a high-resolution global emission catalogue of CO2 and co-emitted species (NOx, SO2, CO, CH4) from thermal power plants for the year 2018. The construction of the database follows a bottom-up approach, which combines plant-specific information with national energy consumption statistics and fuel-dependent emission factors for CO2 and emission ratios for co-emitted species (e.g. the amount of NOx emitted relative to CO2: NOx/CO2). The resulting catalogue contains annual emission information for more than 16 000 individual facilities at their exact geographical locations. Each facility is linked to a country- and fuel-dependent temporal profile (i.e. monthly, day of the week and hourly) and a plant-level vertical profile, which were derived from national electricity generation statistics and plume rise calculations that combine stack parameters with meteorological information. The combination of the aforementioned information allows us to derive high-resolution spatial and temporal emissions for modelling purposes. Estimated annual emissions were compared against independent plant- and country-level inventories, including Carbon Monitoring for Action (CARMA), the Global Infrastructure emission Database (GID) and the Emissions Database for Global Atmospheric Research (EDGAR), as well as officially reported emission data. Overall good agreement is observed between datasets when comparing the CO2 emissions. The main discrepancies are related to the non-inclusion of auto-producer or heat-only facilities in certain countries due to a lack of data. Larger inconsistencies are obtained when comparing emissions from co-emitted species due to uncertainties in the fuel-, country- and region-dependent emission ratios and gap-filling procedures. The temporal distribution of emissions obtained in this work was compared against traditional sector-dependent profiles that are widely used in modelling efforts. This highlighted important differences and the need to consider country dependencies when temporally distributing emissions. The resulting catalogue (https://doi.org/10.24380/0a9o-v7xe, Guevara et al., 2023) is developed in the framework of the Prototype System for a Copernicus CO2 service (CoCO2) European Union (EU)-funded project to support the development of the Copernicus CO2 Monitoring and Verification Support capacity (CO2MVS).

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“…Examples of the NO2 source apportionment can be seen in Figure 2. The method was first applied over Riyadh, Germany and South Africa to estimate NOx emissions from large point sources 15,25 . Due to TROPOMI's higher spatial resolution compared with OMI, the flux divergence method can identify emissions within individual urban areas 26,[37][38][39] .…”

Section: Wrf-camx Simulationmentioning

confidence: 99%

“…This is typically done with a remote sensing instrument -in orbit [13][14][15] or on an aircraft [16][17][18] . Analyses have been conducted for global megacities [19][20][21][22][23] and power plants 24,25 using the Tropospheric Monitoring Instrument (TROPOMI) and a complementary satellite instrument, the Ozone Monitoring Instrument (OMI). The emission rates are inferred by analyzing the concentration maps over a large region and incorporating the lifetime (chemical and dispersion lifetime) of the pollutant to back-calculate the emission rate at the source.…”

Section: Introductionmentioning

confidence: 99%

Identifying Sources of NOx emissions from Aircraft through Source Apportionment and Regression Models

Goldberg,

de Foy,

Nawaz

et al. 2024

Preprint

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Air quality managers in areas exceeding air pollution standards are motivated to understand where there are further opportunities to reduce NOx emissions to improve ozone and PM2.5 air quality. In this project, we use a combination of aircraft remote sensing (i.e., GCAS), source apportionment models (i.e., CAMx), and regression models to investigate NOx emissions from individual source-sectors in Houston, TX. In prior work, GCAS column NO2 was shown to be close to the “truth” in validating column NO2 in model simulations. Column NO2 from CAMx was substantially low biased compared to Pandora (–20%) and GCAS measurements (–31%), suggesting an underestimate of local NOx emissions. We applied a flux divergence method to the GCAS and CAMx data to distinguish the linear shape of major highways and identify NO2 underestimates at highway locations. Using a multiple linear regression model, we isolated on-road, railyard, and “other” NOx emissions as the likeliest cause of this low bias, and simultaneously identified a potential overestimate of shipping NOx emissions. We modified on-road and shipping NOX emissions in a new CAMx simulation and increased the background NO2, and better agreement was found with GCAS measurements: bias improved from –31% to –10% and r2 improved from 0.78 to 0.80. This study outlines how remote sensing data, including fine spatial information from newer instruments such as TEMPO, can be used in concert with chemical transport models to provide actionable information for air quality managers to identify further opportunities to reduce NOx emissions.

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Improved catalog of NO_x point source emissions (version 2)

Cited by 15 publications

References 25 publications

Emissions to the atmosphere by power plants in Baja California Sur, Mexico

Emissions to the atmosphere by power plants in Baja California Sur, Mexico

A global catalogue of CO₂ emissions and co-emitted species from power plants, including high-resolution vertical and temporal profiles

Identifying Sources of NOx emissions from Aircraft through Source Apportionment and Regression Models

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Improved catalog of NOx point source emissions (version 2)

Cited by 15 publications

References 25 publications

Emissions to the atmosphere by power plants in Baja California Sur, Mexico

Emissions to the atmosphere by power plants in Baja California Sur, Mexico

A global catalogue of CO2 emissions and co-emitted species from power plants, including high-resolution vertical and temporal profiles

Identifying Sources of NOx emissions from Aircraft through Source Apportionment and Regression Models

Contact Info

Product

Resources

About

Improved catalog of NO_x point source emissions (version 2)

A global catalogue of CO₂ emissions and co-emitted species from power plants, including high-resolution vertical and temporal profiles