Current model capabilities for simulating black carbon and sulfate concentrations in the Arctic atmosphere: a multi-model evaluation using a comprehensive measurement data set

The concentrations of sulfate, black carbon (BC) and other aerosols in the Arctic are characterized by high values in late winter and spring (so-called Arctic Haze) and low values in summer. Models have long been struggling to capture this seasonality and especially the high concentrations associated with Arctic Haze. In this study, we evaluate sulfate and BC concentrations from eleven different models driven with the same emission inventory against a comprehensive pan-Arctic measurement data set over a time period of 2 years (2008–2009). The set of models consisted of one Lagrangian particle dispersion model, four chemistry transport models (CTMs), one atmospheric chemistry-weather forecast model and five chemistry climate models (CCMs), of which two were nudged to meteorological analyses and three were running freely. The measurement data set consisted of surface measurements of equivalent BC (eBC) from five stations (Alert, Barrow, Pallas, Tiksi and Zeppelin), elemental carbon (EC) from Station Nord and Alert and aircraft measurements of refractory BC (rBC) from six different campaigns. We find that the models generally captured the measured eBC or rBC and sulfate concentrations quite well, compared to previous comparisons. However, the aerosol seasonality at the surface is still too weak in most models. Concentrations of eBC and sulfate averaged over three surface sites are underestimated in winter/spring in all but one model (model means for January–March underestimated by 59 and 37 % for BC and sulfate, respectively), whereas concentrations in summer are overestimated in the model mean (by 88 and 44 % for July–September), but with overestimates as well as underestimates present in individual models. The most pronounced eBC underestimates, not included in the above multi-site average, are found for the station Tiksi in Siberia where the measured annual mean eBC concentration is 3 times higher than the average annual mean for all other stations. This suggests an underestimate of BC sources in Russia in the emission inventory used. Based on the campaign data, biomass burning was identified as another cause of the modeling problems. For sulfate, very large differences were found in the model ensemble, with an apparent anti-correlation between modeled surface concentrations and total atmospheric columns. There is a strong correlation between observed sulfate and eBC concentrations with consistent sulfate/eBC slopes found for all Arctic stations, indicating that the sources contributing to sulfate and BC are similar throughout the Arctic and that the aerosols are internally mixed and undergo similar removal. However, only three models reproduced this finding, whereas sulfate and BC are weakly correlated in the other models. Overall, no class of models (e.g., CTMs, CCMs) performed better than the others and differences are independent of model resolution

A cross-sectional observational study of the nutritional intake of UK primary school children from deprived and non-deprived backgrounds: implications for school breakfast schemes

BACKGROUND: This study examined the nutritional intake of 9-11 year old children in Wales, UK, to assess the rationale for, and potential of, school breakfast initiatives. It also examined the possible unintended consequence of over consumption. METHODS: The study employed a cross-sectional observational design within a randomized controlled trial of a free school breakfast programme. A total of 111 primary schools were randomly assigned to an intervention condition (in which a free school breakfast programme was implemented) or a control condition (in which implementation of the scheme was delayed). Sub-samples of children completed multiple-pass 24-hr dietary recall interviews at baseline (n = 581), and 12 months later (n = 582). Deprivation was assessed for each child in terms of whether or not they were entitled to free school meals. RESULTS: Prior to the introduction of the programme, rates of breakfast skipping were low and there was little evidence of widespread nutritional deficiency. However, there was a subset of children who consumed inadequate levels of a range of vitamins and minerals and 29 % of children ate very little for breakfast (less than 100 kcal). Children that ate larger breakfasts, had higher daily intakes of all nutrients that were examined. Children from deprived backgrounds consumed significantly lower levels of several vitamins and minerals at breakfast. Following the introduction of the breakfast scheme in intervention schools, there was little difference in the nutritional quality of school versus home breakfasts (n = 35 and 211 respectively). Where children ate breakfast at both school and home (n = 33), their overall energy intake was higher, but not significantly so. CONCLUSIONS: Although the overall diet of this group of children was generally good prior to the breakfast scheme, the results suggest that such schemes could be beneficial for a subset of children who are poorly nourished and for those children who consume very little for breakfast. TRIAL REGISTRATION: Current Controlled Trials ISRCTN18336527

Wildfires in northern Eurasia affect the budget of black carbon in the Arctic – a 12-year retrospective synopsis (2002–2013)

International audienceIn recent decades much attention has been given to the Arctic environment, where climate change is happening rapidly. Black carbon (BC) has been shown to be a major component of Arctic pollution that also affects the ra-diative balance. In the present study, we focused on how vegetation fires that occurred in northern Eurasia during the period of 2002-2013 influenced the budget of BC in the Arctic. For simulating the transport of fire emissions from northern Eurasia to the Arctic, we adopted BC fire emission estimates developed independently by GFED3 (Global Fire Emissions Database) and FEI-NE (Fire Emission Inventory-northern Eurasia). Both datasets were based on fire locations and burned areas detected by MODIS (Moderate resolution Imaging Spectroradiometer) instruments on NASA's (National Aeronautics and Space Administration) Terra and Aqua satellites. Anthropogenic sources of BC were adopted from the MACCity (Monitoring Atmospheric Composition and Climate and megacity Zoom for the Environment) emission inventory. During the 12-year period, an average area of 250 000 km 2 yr −1 was burned in northern Eurasia (FEI-NE) and the global emissions of BC ranged between 8.0 and 9.5 Tg yr −1 (FEI-NE+MACCity). For the BC emitted in the Northern Hemisphere (based on FEI-NE+MACCity), about 70 % originated from anthropogenic sources and the rest from biomass burning (BB). Using the FEI-NE+MACCity inventory, we found that 102 ± 29 kt yr −1 BC was deposited in the Arctic (defined here as the area north of 67 • N) during the 12 years simulated, which was twice as much as when using the MACCity inventory (56 ± 8 kt yr −1). The annual mass of BC deposited in the Arctic from all sources (FEI-NE in northern Eurasia, MACCity elsewhere) is significantly higher by about 37 % in 2009 (78 vs. 57 kt yr −1) to 181 % in 2012 (153 vs. 54 kt yr −1), compared to the BC deposited using just the MACCity emission inventory. Deposition of BC in the Arctic from BB sources in the Northern Hemisphere thus represents 68 % of the BC deposited from all BC sources (the remaining being due to anthropogenic sources). Northern Eurasian vegetation fires (FEI-NE) contributed 85 % (79-91 %) to the BC deposited over the Arctic from all BB sources in the Northern Hemisphere. Published by Copernicus Publications on behalf of the European Geosciences Union. 7588 N. Evangeliou et al.: Wildfires in northern Eurasia affect the budget of black carbon in the Arctic We estimate that about 46 % of the BC deposited over the Arctic from vegetation fires in northern Eurasia originated from Siberia, 6 % from Kazakhstan, 5 % from Europe, and about 1 % from Mongolia. The remaining 42 % originated from other areas in northern Eurasia. About 42 % of the BC released from northern Eurasian vegetation fires was deposited over the Arctic (annual average: 17 %) during spring and summer

Current model capabilities for simulating black carbon and sulfate concentrations in the Arctic atmosphere: a multi-model evaluation using a comprehensive measurement data set

The concentrations of sulfate, black carbon (BC) and other aerosols in the Arctic are characterized by high values in late winter and spring (so-called Arctic Haze) and low values in summer. Models have long been struggling to capture this seasonality and especially the high concentrations associated with Arctic Haze. In this study, we evaluate sulfate and BC concentrations from eleven different models driven with the same emission inventory against a comprehensive pan-Arctic measurement data set over a time period of 2 years (2008–2009). The set of models consisted of one Lagrangian particle dispersion model, four chemistry transport models (CTMs), one atmospheric chemistry-weather forecast model and five chemistry climate models (CCMs), of which two were nudged to meteorological analyses and three were running freely. The measurement data set consisted of surface measurements of equivalent BC (eBC) from five stations (Alert, Barrow, Pallas, Tiksi and Zeppelin), elemental carbon (EC) from Station Nord and Alert and aircraft measurements of refractory BC (rBC) from six different campaigns. We find that the models generally captured the measured eBC or rBC and sulfate concentrations quite well, compared to previous comparisons. However, the aerosol seasonality at the surface is still too weak in most models. Concentrations of eBC and sulfate averaged over three surface sites are underestimated in winter/spring in all but one model (model means for January–March underestimated by 59 and 37% for BC and sulfate, respectively), whereas concentrations in summer are overestimated in the model mean (by 88 and 44% for July–September), but with overestimates as well as underestimates present in individual models. The most pronounced eBC underestimates, not included in the above multi-site average, are found for the station Tiksi in Siberia where the measured annual mean eBC concentration is 3 times higher than the average annual mean for all other stations. This suggests an underestimate of BC sources in Russia in the emission inventory used. Based on the campaign data, biomass burning was identified as another cause of the modeling problems. For sulfate, very large differences were found in the model ensemble, with an apparent anticorrelation between modeled surface concentrations and total atmospheric columns. There is a strong correlation between observed sulfate and eBC concentrations with consistent sulfate/eBC slopes found for all Arctic stations, indicating that the sources contributing to sulfate and BC are similar throughout the Arctic and that the aerosols are internally mixed and undergo similar removal. However, only three models reproduced this finding, whereas sulfate and BC are weakly correlated in the other models. Overall, no class of models (e.g., CTMs, CCMs) performed better than the others and differences are independent of model resolution