ALBERT

Description: Decreasing sea ice and increasing marine navigability in northern latitudes have changed Arctic ship traffic patterns in recent years and are predicted to increase annual ship traffic in the Arctic in the future. Development of effective regulations to manage environmental impacts of shipping requires an understanding of ship emissions and atmospheric processing in the Arctic environment. As part of the summer 2014 NETCARE (Network on Climate and Aerosols) campaign, the plume dispersion and gas and particle emission factors of emissions originating from the Canadian Coast Guard Amundsen icebreaker operating near Resolute Bay, NU, Canada have been investigated. The Amundsen burnt distillate fuel with 1.5 wt % sulfur. Emissions were studied via plume intercepts using aircraft measurements, an analytical plume dispersion model, and using the FLEXPART-WRF Lagrangian particle dispersion model. The first plume intercepts by research aircraft were carried out on 19 July 2014 during the operation of the Amundsen in the open water. The second and third plume intercept measurements were carried out on 20 and 21 July 2014 when the Amundsen had reached the ice edge and operated under icebreaking conditions. Typical of Arctic marine navigation, the engine load was low compared to cruising conditions for all of the plume intercepts. The measured species included mixing ratios of CO2, NOx, CO, SO2, particle number concentration (CN), refractory Black Carbon (rBC), and Cloud Condensation Nuclei (CCN). The results were compared to similar experimental studies in mid latitudes. Plume expansion rates (γ) were calculated using the analytical model and found to be γ = 0.75 ± 0.80, 0.93 ± 0.37, and 1.19 ± 0.39 for plumes 1, 2, and 3, respectively. These rates are smaller than prior studies conducted at mid latitudes, likely due to polar boundary layer dynamics, including reduced turbulent mixing compared to mid latitudes. All emission factors were in agreement with prior observations at low engine loads in mid latitudes. Icebreaking increased the NOx emission factor from EFNOx = 22.3 ± 8.0 to 57.8 ± 11.0 and 65.8 ± 4.0 g kg–diesel−1 for plumes 1, 2, and 3, likely due to change in combustion temperatures. The CO emission factor was EFCO = 6.4 ± 11.7, 6.8 ± 2.2 and 5.0 ± 1.0 g kg–diesel−1 for plumes 1, 2, and 3. The rBC emission factor was EFrBC = 0.20 ± 0.04 and 0.25 ± 0.12 g kg–diesel−1 for plumes 1 and 2. The CN emission factor was reduced while icebreaking from EFCPC = 1.96 ± 0.41 to 0.43 ± 0.11 and 0.47 ± 0.04 × 1016 kg–diesel−1 for plumes 1, 2, and 3. At 0.6 % supersaturation, the CCN emission factor was lower than observations in mid latitudes at low engine loads with EFCCN = 1.63 ± 0.41 to 1.06 ± 0.32 and 0.28 ± 0.07 × 1014 kg–diesel−1 for plumes 1, 2, and 3.

Description: The ability of seven state-of-the-art chemistry–aerosol models to reproduce distributions of tropospheric ozone and its precursors, as well as aerosols over eastern Asia in summer 2008, is evaluated. The study focuses on the performance of models used to assess impacts of pollutants on climate and air quality as part of the EU ECLIPSE project. Models, run using the same ECLIPSE emissions, are compared over different spatial scales to in situ surface, vertical profiles and satellite data. Several rather clear biases are found between model results and observations, including overestimation of ozone at rural locations downwind of the main emission regions in China, as well as downwind over the Pacific. Several models produce too much ozone over polluted regions, which is then transported downwind. Analysis points to different factors related to the ability of models to simulate VOC-limited regimes over polluted regions and NOx limited regimes downwind. This may also be linked to biases compared to satellite NO2, indicating overestimation of NO2 over and to the north of the northern China Plain emission region. On the other hand, model NO2 is too low to the south and west of this region and over South Korea/Japan. Overestimation of ozone is linked to systematic underestimation of CO particularly at rural sites and downwind of the main Chinese emission regions. This is likely to be due to enhanced destruction of CO by OH. Overestimation of Asian ozone and its transport downwind implies that radiative forcing from this source may be overestimated. Model-observation discrepancies over Beijing do not appear to be due to emission controls linked to the Olympic Games in summer 2008.With regard to aerosols, most models reproduce the satellite-derived AOD patterns over eastern China. Our study nevertheless reveals an overestimation of ECLIPSE model mean surface BC and sulphate aerosols in urban China in summer 2008. The effect of the short-term emission mitigation in Beijing is too weak to explain the differences between the models. Our results rather point to an overestimation of SO2 emissions, in particular, close to the surface in Chinese urban areas. However, we also identify a clear underestimation of aerosol concentrations over northern India, suggesting that the rapid recent growth of emissions in India, as well as their spatial extension, is underestimated in emission inventories. Model deficiencies in the representation of pollution accumulation due to the Indian monsoon may also be playing a role. Comparison with vertical aerosol lidar measurements highlights a general underestimation of scattering aerosols in the boundary layer associated with overestimation in the free troposphere pointing to modelled aerosol lifetimes that are too long. This is likely linked to too strong vertical transport and/or insufficient deposition efficiency during transport or export from the boundary layer, rather than chemical processing (in the case of sulphate aerosols). Underestimation of sulphate in the boundary layer implies potentially large errors in simulated aerosol–cloud interactions, via impacts on boundary-layer clouds.This evaluation has important implications for accurate assessment of air pollutants on regional air quality and global climate based on global model calculations. Ideally, models should be run at higher resolution over source regions to better simulate urban–rural pollutant gradients and/or chemical regimes, and also to better resolve pollutant processing and loss by wet deposition as well as vertical transport. Discrepancies in vertical distributions require further quantification and improvement since these are a key factor in the determination of radiative forcing from short-lived pollutants.