Observation and simulation of ethane at 23 FTIR sites

Ethane is the most abundant non-methane hydrocarbon (NMHC) in the Earthatmosphere. Its main sources are of anthropogenic origin, with globally62% from leakage during production and transport of natural gas, 20%from biofuel combustion and 18% from biomass burning. In the Southernhemisphere, anthropogenic emissions are lower which makes biomassburning emissions a more significant source. The main removal process isoxidation by the hydroxyl radical (OH), leading to a mean atmosphericlifetime of 2 months. Until recently, a prolonged decrease of itsabundance has been documented, at rates of -1 to -2.7%/yr, with globalemissions dropping from 14 to 11 Tg/yr over 1984-2010 owing tosuccessful measures reducing fugitive emissions from its fossil fuelsources. However, subsequent investigations have reported on an upturnin the ethane trend, characterized by a sharp rise from about 2009onwards. The ethane increase is attributed to the oil and natural gasproduction boom in North America, although significant changes in OHcould also be at play. In the present contribution, we report the trendof ethane at 23 ground-based Fourier Transform Infrared (FTIR) sitesspanning the 80ºN to 79ºS latitude range. Over 2010-2015, asignificant ethane rise of 3-5%/yr is determined for most sites in theNorthern Hemisphere, while for the Southern hemisphere the rates ofchanges are not significant at the 2-sigma uncertainty level . Dedicatedmodel simulations by EMAC (ECHAM5/MESSy Atmospheric Chemistry;1.8×1.8 degrees) implementing various emission scenarios areincluded in order to support data interpretation. The usualunderestimation of the NMHCs emissions in the main inventories isconfirmed here for RCP85 (Representative Concentration Pathway Databasev8.5). Scaling them by 1.5 is needed to capture the background levels ofatmospheric ethane. Moreover, additional and significant emissions ( 7Tg over 2009-2015) are needed to capture the ethane rise in the Northernhemisphere. Attributing them to the oil and gas sector and locating themin North America allows EMAC to produce adequate trends in the Northernhemisphere, but not in the Southern hemisphere, where they areoverestimated. Possible causes for this difference are discussed

Observation and simulation of ethane at 22 FTIR sites

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Ground-based validation of the Copernicus Sentinel-5p TROPOMI NO₂ measurements with the NDACC ZSL-DOAS, MAX-DOAS and Pandonia global networks

This paper reports on consolidated ground-based validation results of the atmospheric NO2 data produced operationally since April 2018 by the TROPOMI instrument on board of the ESA/EU Copernicus Sentinel-5 Precursor (S5p) satellite. Tropospheric, stratospheric, and total NO2 column data from S5p are compared to correlative measurements collected from, respectively, 19 Multi-Axis DOAS (MAX-DOAS), 26 NDACC Zenith-Scattered-Light DOAS (ZSL-DOAS), and 25 PGN/Pandora instruments distributed globally. The validation methodology gives special care to minimizing mismatch errors due to imperfect spatio-temporal co-location of the satellite and correlative data, e.g., by using tailored observation operators to account for differences in smoothing and in sampling of atmospheric structures and variability, and photochemical modelling to reduce diurnal cycle effects. Compared to the ground-based measurements, S5p data show, on an average: (i) a negative bias for the tropospheric column data, of typically −23 to −37 % in clean to slightly polluted conditions, but reaching values as high as −51 % over highly polluted areas; (ii) a slight negative bias for the stratospheric column data, of about −0.2 Pmolec/cm2, i.e. approx. −2 % in summer to −15 % in winter; and (iii) a bias ranging from zero to −50 % for the total column data, found to depend on the amplitude of the total NO2 column, with small to slightly positive bias values for columns below 6 Pmolec/cm2 and negative values above. The dispersion between S5p and correlative measurements contains mostly random components, which remain within mission requirements for the stratospheric column data (0.5 Pmolec/cm2), but exceed those for the tropospheric column data (0.7 Pmolec/cm2). While a part of the biases and dispersion may be due to representativeness differences, it is known that errors in the S5p tropospheric columns exist due to shortcomings in the (horizontally coarse) a-priori profile representation in the TM5-MP chemistry transport model used in the S5p retrieval, and to a lesser extent, to the treatment of cloud effects. Although considerable differences (up to 2 Pmolec/cm2 and more) are observed at single ground-pixel level, the near-real-time (NRTI) and off-line (OFFL) versions of the S5p NO2 operational data processor provide similar NO2 column values and validation results when globally averaged, with the NRTI values being on average 0.79 % larger than the OFFL values

Observation and simulation of ethane at 22 FTIR sites

info:eu-repo/semantics/nonPublishe

Ground-based validation of the Copernicus Sentinel-5p TROPOMI NO₂ measurements with the NDACC ZSL-DOAS, MAX-DOAS and Pandonia global networks

International audienceThis paper reports on consolidated ground-based validation results of the atmospheric NO2 data produced operationally since April 2018 by the TROPOMI instrument on board of the ESA/EU Copernicus Sentinel-5 Precursor (S5p) satellite. Tropospheric, stratospheric, and total NO2 column data from S5p are compared to correlative measurements collected from, respectively, 19 Multi-Axis DOAS (MAX-DOAS), 26 NDACC Zenith-Scattered-Light DOAS (ZSL-DOAS), and 25 PGN/Pandora instruments distributed globally. The validation methodology gives special care to minimizing mismatch errors due to imperfect spatio-temporal co-location of the satellite and correlative data, e.g., by using tailored observation operators to account for differences in smoothing and in sampling of atmospheric structures and variability, and photochemical modelling to reduce diurnal cycle effects. Compared to the ground-based measurements, S5p data show, on an average: (i) a negative bias for the tropospheric column data, of typically −23 to −37 % in clean to slightly polluted conditions, but reaching values as high as −51 % over highly polluted areas; (ii) a slight negative bias for the stratospheric column data, of about −0.2 Pmolec/cm2, i.e. approx. −2 % in summer to −15 % in winter; and (iii) a bias ranging from zero to −50 % for the total column data, found to depend on the amplitude of the total NO2 column, with small to slightly positive bias values for columns below 6 Pmolec/cm2 and negative values above. The dispersion between S5p and correlative measurements contains mostly random components, which remain within mission requirements for the stratospheric column data (0.5 Pmolec/cm2), but exceed those for the tropospheric column data (0.7 Pmolec/cm2). While a part of the biases and dispersion may be due to representativeness differences, it is known that errors in the S5p tropospheric columns exist due to shortcomings in the (horizontally coarse) a-priori profile representation in the TM5-MP chemistry transport model used in the S5p retrieval, and to a lesser extent, to the treatment of cloud effects. Although considerable differences (up to 2 Pmolec/cm2 and more) are observed at single ground-pixel level, the near-real-time (NRTI) and off-line (OFFL) versions of the S5p NO2 operational data processor provide similar NO2 column values and validation results when globally averaged, with the NRTI values being on average 0.79 % larger than the OFFL values

Elemental Characterization of Ambient Particulate Matter for a Globally Distributed Monitoring Network: Methodology and Implications

Global ground-level measurements of elements in ambient particulate matter (PM) can provide valuable information to understand the distribution of dust and trace elements, assess health impacts, and investigate emission sources. We use X-ray fluorescence spectroscopy to characterize the elemental composition of PM samples collected from 27 globally distributed sites in the Surface PARTiculate mAtter Network (SPARTAN) over 2019–2023. Consistent protocols are applied to collect all samples and analyze them at one central laboratory, which facilitates comparison across different sites. Multiple quality assurance measures are performed, including applying reference materials that resemble typical PM samples, acceptance testing, and routine quality control. Method detection limits and uncertainties are estimated. Concentrations of dust and trace element oxides (TEO) are determined from the elemental dataset. In addition to sites in arid regions, a moderately high mean dust concentration (6 μg/m3) in PM2.5 is also found in Dhaka (Bangladesh) along with a high average TEO level (6 μg/m3). High carcinogenic risk (>1 cancer case per 100000 adults) from airborne arsenic is observed in Dhaka (Bangladesh), Kanpur (India), and Hanoi (Vietnam). Industries of informal lead-acid battery and e-waste recycling as well as coal-fired brick kilns likely contribute to the elevated trace element concentrations found in Dhaka