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We introduce the new Global Ozone Monitoring Experiment-2 (GOME-2) daily and monthly level-3 product of total column ozone (O 3), total and tropospheric column nitrogen dioxide (NO 2), total column water vapour, total column bromine oxide (BrO), total column formaldehyde (HCHO), and total column sulfur dioxide (SO 2) (daily products 10.15770/EUM_SAF_AC_0048, ; monthly products 10.15770/EUM_SAF_AC_0049,). The GOME-2 level-3 products aim to provide easily translatable and user-friendly data sets to the scientific community for scientific progress as well as to satisfy public interest. The purpose of this paper is to present the theoretical basis as well as the verification and validation of the GOME-2 daily and monthly level-3 products. The GOME-2 level-3 products are produced using the overlapping area-weighting method. Details of the gridding algorithm are presented. The spatial resolution of the GOME-2 level-3 products is selected based on the sensitivity study. The consistency of the resulting level-3 products among three GOME-2 sensors is investigated through time series of global averages, zonal averages, and bias. The accuracy of the products is validated by comparison to ground-based observations. The verification and validation results show that the GOME-2 level-3 products are consistent with the level-2 data. Small discrepancies are found among three GOME-2 sensors, which are mainly caused by the differences in the instrument characteristic and level-2 processor. The comparison of GOME-2 level-3 products to ground-based observations in general shows very good agreement, indicating that the products are consistent and fulfil the requirements to serve the scientific community and general public. [ABSTRACT FROM AUTHOR]

MAX-DOAS and direct sun NO2 vertical column network data are used to investigate the accuracy of tropospheric NO2 column measurements of the GOME-2 instrument on the MetOP-A satellite platform and the OMI instrument on Aura. The study is based on 23 MAX-DOAS and 16 direct sun instruments at stations distributed worldwide. A method to quantify and correct for horizontal dilution effects in heterogeneous NO2 field conditions is proposed. After systematic application of this correction to urban sites, satellite measurements are found to present smaller biases compared to ground-based reference data in almost all cases. We investigate the seasonal dependence of the validation results, as well as the impact of using different approaches to select satellite ground pixels in coincidence with ground-based data. In optimal comparison conditions (satellite pixels containing the station) the median bias between satellite tropospheric NO2 column measurements and the ensemble of MAX-DOAS and direct sun measurements is found to be significant and equal to −36 % for GOME-2A and −20 % for OMI. These biases are further reduced to −24 % and −8 % respectively, after application of the dilution correction. Comparisons with the QA4ECV satellite product for both GOME-2A and OMI is also performed, showing less scatter but also a slightly larger median tropospheric NO2 column bias with respect to the ensemble of MAX-DOAS and direct sun measurements. [ABSTRACT FROM AUTHOR]

To determine the sources of particulate matter less than 2.5 μm (PM2.5 in different ambient atmospheres (urban, roadside, industrial, and rural sites), the chemical components of PM2.5 such as ions (Cl-, NO3-, SO42-, NH4+, Na+, K+, Ca2+, and Mg2+), carbonaceous species, and elements (Al, As, Ba, Cd, Cu, Fe, Mn, Ni, Pb, Se, V, and Zn) were measured. The average mass concentrations of PM2.5 at the urban, roadside, industrial, and rural sites were 31.5 ± 14.8, 31.6 ± 22.3, 31.4 ± 16.0, and 25.8 ± 12.4 μg/m3, respectively. Except for secondary ammonium sulfate and ammonium nitrate, the model results showed that the traffic source (i.e., the sum of gasoline and diesel vehicle sources) was the most dominant source of PM2.5 (17.1%) followed by biomass burning (13.8%) at the urban site. The major primary sources of PM2.5 were consistent with the site characteristics (diesel vehicle source at the roadside site, coal-fired plants at the industrial site, and biomass burning at the rural site). Seasonal data from the urban site suggested that ammonium sulfate and ammonium nitrate were the most dominant sources of PM2.5 during all seasons. Further, the contribution of road dust source to PM2.5 increased during spring and fall seasons. We conclude that the determination of the major PM2.5 sources is useful for establishing efficient control strategies for PM2.5 in different regions and seasons. [ABSTRACT FROM AUTHOR]