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© Author(s) 2018. Accurate and consistent monitoring of anthropogenic combustion is imperative because of its significant health and environmental impacts, especially at city-to-regional scale. Here, we assess the performance of the Copernicus Atmosphere Monitoring Service (CAMS) global prediction system using measurements from aircraft, ground sites, and ships during the Korea-United States Air Quality (KORUS-AQ) field study in May to June 2016. Our evaluation focuses on CAMS CO and CO2 analyses as well as two higher-resolution forecasts (16 and 9km horizontal resolution) to assess their capability in predicting combustion signatures over east Asia. Our results show a slight overestimation of CAMS CO2 with a mean bias against airborne CO2 measurements of 2.2, 0.7, and 0.3ppmv for 16 and 9km CO2 forecasts, and analyses, respectively. The positive CO2 mean bias in the 16km forecast appears to be consistent across the vertical profile of the measurements. In contrast, we find a moderate underestimation of CAMS CO with an overall bias against airborne CO measurements of -19.2 (16km), -16.7 (9km), and -20.7ppbv (analysis). This negative CO mean bias is mostly seen below 750hPa for all three forecast/analysis configurations. Despite these biases, CAMS shows a remarkable agreement with observed enhancement ratios of CO with CO2 over the Seoul metropolitan area and over the West (Yellow) Sea, where east Asian outflows were sampled during the study period. More efficient combustion is observed over Seoul (dCO dCO2 Combining double low line 9ppbvppmv-1) compared to the West Sea (dCO dCO2 Combining double low line 28ppbvppmv-1). This "combustion signature contrast" is consistent with previous studies in these two regions. CAMS captured this difference in enhancement ratios (Seoul: 8-12ppbvppmv-1, the West Sea: ∼ 30ppbvppmv-1) regardless of forecast/analysis configurations. The correlation of CAMS CO bias with CO2 bias is relatively high over these two regions (Seoul: 0.64-0.9

© Author(s) 2018. Accurate and consistent monitoring of anthropogenic combustion is imperative because of its significant health and environmental impacts, especially at city-to-regional scale. Here, we assess the performance of the Copernicus Atmosphere Monitoring Service (CAMS) global prediction system using measurements from aircraft, ground sites, and ships during the Korea-United States Air Quality (KORUS-AQ) field study in May to June 2016. Our evaluation focuses on CAMS CO and CO2 analyses as well as two higher-resolution forecasts (16 and 9km horizontal resolution) to assess their capability in predicting combustion signatures over east Asia. Our results show a slight overestimation of CAMS CO2 with a mean bias against airborne CO2 measurements of 2.2, 0.7, and 0.3ppmv for 16 and 9km CO2 forecasts, and analyses, respectively. The positive CO2 mean bias in the 16km forecast appears to be consistent across the vertical profile of the measurements. In contrast, we find a moderate underestimation of CAMS CO with an overall bias against airborne CO measurements of -19.2 (16km), -16.7 (9km), and -20.7ppbv (analysis). This negative CO mean bias is mostly seen below 750hPa for all three forecast/analysis configurations. Despite these biases, CAMS shows a remarkable agreement with observed enhancement ratios of CO with CO2 over the Seoul metropolitan area and over the West (Yellow) Sea, where east Asian outflows were sampled during the study period. More efficient combustion is observed over Seoul (dCO dCO2 Combining double low line 9ppbvppmv-1) compared to the West Sea (dCO dCO2 Combining double low line 28ppbvppmv-1). This "combustion signature contrast" is consistent with previous studies in these two regions. CAMS captured this difference in enhancement ratios (Seoul: 8-12ppbvppmv-1, the West Sea: ∼ 30ppbvppmv-1) regardless of forecast/analysis configurations. The correlation of CAMS CO bias with CO2 bias is relatively high over these two regions (Seoul: 0.64-0.9

The air quality in the outflow from Fort Worth, TX was studied in June 2011 at a location surrounded by oil and gas development in the Barnett Shale. The objectives of this study were to understand the major sources of volatile organic compounds (VOCs) and organic aerosols and explore the potential influence each VOC source had on ozone and secondary organic aerosol formation. Measurements of VOCs were apportioned between six factors using Positive Matrix Factorization (PMF): Natural Gas (25 ± 2%; ±99% CL); Fugitive Emissions (15 ± 2%); Internal Combustion Engines (15 ± 2%); Biogenic Emissions (7 ± 1%); Industrial Emissions/Oxidation 1(8 ± 1%); and Oxidation 2 (18 ± 2%). Reactivity calculations suggest the Biogenic and Oxidation 2 factors were the most likely VOC sources to influence local ozone. However, enough OH reactivity was calculated for factors related to the oil and gas development that they could incrementally increase O3. Three organic aerosol (OA) types were identified with PMF applied to high-resolution time-of-flight aerosol mass spectrometry measurements: hydrocarbon-like OA (HOA; 11% of mass) and two classes of oxidized OA (semi- and less-volatile OOA, SV and LV; 45% and 44%, respectively). The HOA correlated with the Internal Combustion Engine VOC factor indicating that a large fraction of the HOA was emitted by gasoline and diesel motors. The SV-OOA correlated with the oxidized VOC factors during most of the study, whereas a correlation between LV-OOA and the oxidized VOC factors was only observed during part of the study. It is hypothesized that SV-OOA and the oxidized VOC factors correlated reasonably well because these factors likely were separated by at most only a few oxidation generations on the oxidation pathway of organic compounds.

The air quality in the outflow from Fort Worth, TX was studied in June 2011 at a location surrounded by oil and gas development in the Barnett Shale. The objectives of this study were to understand the major sources of volatile organic compounds (VOCs) and organic aerosols and explore the potential influence each VOC source had on ozone and secondary organic aerosol formation. Measurements of VOCs were apportioned between six factors using Positive Matrix Factorization (PMF): Natural Gas (25 ± 2%; ±99% CL); Fugitive Emissions (15 ± 2%); Internal Combustion Engines (15 ± 2%); Biogenic Emissions (7 ± 1%); Industrial Emissions/Oxidation 1(8 ± 1%); and Oxidation 2 (18 ± 2%). Reactivity calculations suggest the Biogenic and Oxidation 2 factors were the most likely VOC sources to influence local ozone. However, enough OH reactivity was calculated for factors related to the oil and gas development that they could incrementally increase O3. Three organic aerosol (OA) types were identified with PMF applied to high-resolution time-of-flight aerosol mass spectrometry measurements: hydrocarbon-like OA (HOA; 11% of mass) and two classes of oxidized OA (semi- and less-volatile OOA, SV and LV; 45% and 44%, respectively). The HOA correlated with the Internal Combustion Engine VOC factor indicating that a large fraction of the HOA was emitted by gasoline and diesel motors. The SV-OOA correlated with the oxidized VOC factors during most of the study, whereas a correlation between LV-OOA and the oxidized VOC factors was only observed during part of the study. It is hypothesized that SV-OOA and the oxidized VOC factors correlated reasonably well because these factors likely were separated by at most only a few oxidation generations on the oxidation pathway of organic compounds.