ALBERT

Description: The impacts of black carbon (BC) and particulate matter with aerodynamic diameters less than 2.5 µm (PM2.5) emissions from different source sectors (e.g., transportation, power, industry, residential, and biomass burning) and geographic source regions (e.g., Europe, North America, China, Russia, central Asia, south Asia, and the Middle East) to Arctic BC and PM2.5 concentrations are investigated through a series of annual sensitivity simulations using the Weather Research and Forecasting – sulfur transport and deposition model (WRF-STEM) modeling framework. The simulations are validated using observations at two Arctic sites (Alert and Barrow Atmospheric Baseline Observatory), the Interagency Monitoring of Protected Visual Environments (IMPROVE) surface sites over the US, and aircraft observations over the Arctic during spring and summer 2008. Emissions from power, industrial, and biomass burning sectors are found to be the main contributors to the Arctic PM2.5 surface concentration, with contributions of ∼ 30 %, ∼ 25 %, and ∼ 20 %, respectively. In contrast, the residential and transportation sectors are identified as the major contributors to Arctic BC, with contributions of ∼ 38 % and ∼ 30 %. Anthropogenic emissions are the most dominant contributors (∼ 88 %) to the BC surface concentration over the Arctic annually; however, the contribution from biomass burning is significant over the summer (up to ∼ 50 %). Among all geographical regions, Europe and China have the highest contributions to the BC surface concentrations, with contributions of ∼ 46 % and ∼ 25 %, respectively. Industrial and power emissions had the highest contributions to the Arctic sulfate (SO4) surface concentration, with annual contributions of ∼ 43 % and ∼ 41 %, respectively. Further sensitivity runs show that, among various economic sectors of all geographic regions, European and Chinese residential sectors contribute to ∼ 25 % and ∼ 14 % of the Arctic average surface BC concentration. Emissions from the Chinese industry sector and European power sector contribute ∼ 12 % and ∼ 18 % of the Arctic surface sulfate concentration. For Arctic PM2.5, the anthropogenic emissions contribute 〉 ∼ 75 % at the surface annually, with contributions of ∼ 25 % from Europe and ∼ 20 % from China; however, the contributions of biomass burning emissions are significant in particular during spring and summer. The contributions of each geographical region to the Arctic PM2.5 and BC vary significantly with altitude. The simulations show that the BC from China is transported to the Arctic in the midtroposphere, while BC from European emission sources are transported near the surface under 5 km, especially during winter.

Description: Recent increases in natural gas (NG) production through hydraulic fracturing have called the climate benefit of switching from coal-fired to natural gas-fired power plants into question. Higher than expected levels of methane, non-methane hydrocarbons (NMHC), and NOx have been observed in areas close to oil and NG operation facilities. Large uncertainties in the oil and NG operation emission inventories reduce the confidence level in the impact assessment of such activities on regional air quality and climate, as well as in the development of effective mitigation policies. In this work, we used ethane as the indicator of oil and NG emissions and explored the sensitivity of ethane to different physical parameterizations and simulation setups in the Weather Research and Forecasting with Chemistry (WRF-Chem) model using the US EPA National Emission Inventory (NEI-2011). We evaluated the impact of the following configurations and parameterizations on predicted ethane concentrations: planetary boundary layer (PBL) parameterizations, daily re-initialization of meteorological variables, meteorological initial and boundary conditions, and horizontal resolution. We assessed the uncertainties around oil and NG emissions using measurements from the FRAPPÉ and DISCOVER-AQ campaigns over the northern Front Range metropolitan area (NFRMA) in summer 2014. The sensitivity analysis shows up to 57.3 % variability in the normalized mean bias of the near-surface modeled ethane across the simulations, which highlights the important role of model configurations on the model performance and ultimately the assessment of emissions. Comparison between airborne measurements and the sensitivity simulations indicates that the model–measurement bias of ethane ranged from −14.9 to −8.2 ppb (NMB ranged from −80.5 % to −44 %) in regions close to oil and NG activities. Underprediction of ethane concentration in all sensitivity runs suggests an actual underestimation of the oil and NG emissions in the NEI-2011. An increase of oil and NG emissions in the simulations partially improved the model performance in capturing ethane and lumped alkanes (HC3) concentrations but did not impact the model performance in capturing benzene, toluene, and xylene; this is due to very low emission rates of the latter species from the oil and NG sector in NEI-2011.

Description: Recent increases in the Natural Gas (NG) production through hydraulic fracturing have called into question the climate benefit of switching from coal-fired to natural gas-fired power plants. Higher than expected levels of methane, Non-Methane Hydrocarbons (NMHC), and NOx have been observed in areas close to oil and NG operation facilities. Large uncertainties in the oil and NG operation emission inventories reduce the confidence level in the impact assessment of such activities on regional air quality and climate, as well as development of effective mitigation policies. In this work, we used ethane as the indicator of oil and NG emissions and explored the sensitivity of ethane to different physical parametrizations and simulation set-ups in the Weather Research and Forecasting with Chemistry (WRF-Chem) model using the U.S. EPA National Emission Inventory (NEI-2011). We evaluated the impact of the following configurations and parameterizations on predicted ethane concentrations: Planetary Boundary Layer (PBL) parametrizations, daily re-initialization of meteorological variables, meteorological initial and boundary conditions, and horizontal resolution. We assessed the uncertainties around oil and NG emissions by using measurements from the FRAPPÉ and DISCOVER-AQ campaigns over the Northern Front Range Metropolitan Area (NFRMA) in summer 2014. The sensitivity analysis shows up to 57.3% variability in normalized mean bias of the near-surface modeled ethane across the simulations, which highlights the important role of model configurations on the model performance and ultimately the assessment of emissions. Comparison between airborne measurements and the sensitivity simulations indicates that the model-measurement bias of ethane ranged from −14.9ppb to −8.2ppb (NMB ranged from −80.5% to −44%) in regions close to oil and NG activities. Under-prediction of ethane concentration in all sensitivity runs suggests an actual under-estimation of the oil and NG emissions in the NEI-2011. Increase of oil and NG emissions in the simulations partially improved the model performance in capturing ethane and lumped alkanes (HC3) concentrations but did not impact the model performance in capturing benzene, toluene, and xylene which is due to very low emission rates of these species from oil and NG sector in the NEI-2011.

Description: The impacts of BC and PM2.5 emissions from different source sectors (e.g. transportation, power, industry, residential, and biomass burning) and source regions (e.g. Europe, North America, China, Russia, Central Asia, South Asia, and the Middle East) to Arctic BC and PM2.5 concentrations are investigated using a series of sensitivity runs with WRF-STEM modeling framework. The simulations are validated using aircraft observations over the Arctic during spring and summer 2008. Emissions from power, industrial, and biomass burning sectors are found to be the main contributors to the Arctic PM2.5 with contributions of ~ 30 %, ~ 25 %, and ~ 20 % respectively. In contrast, the residential and transportation sectors are identified as the major contributors to Arctic BC with contributions of ~ 38 % and ~ 30 %. Anthropogenic emissions are the most dominant contributors (~ 88 %) to the BC surface concentration over the Arctic; however, the contribution from biomass burning is significant over the summer (up to ~ 50 %). Among all geographical regions, Europe and China have the highest contributions to the BC surface concentrations with contributions of ~ 46 % and ~ 25 % respectively. Further sensitivity runs show that among various economic sectors of all geographic regions, European and Chinese residential sector contribute up to ~ 25 % and ~ 14 % to the Arctic average surface BC concentration. For Arctic PM2.5, the anthropogenic emissions contribute 〉~ 75 % at the surface annually, with contributions of ~ 25 % from Europe and ~ 20 % from China; however, the contributions of biomass burning emissions are significant in particular during spring and summer. The contributions of each geographical region to the Arctic PM2.5 and BC vary significantly with altitude. The simulations show that the BC from China is transported to the Arctic in the mid-troposphere, while, BC from European emission sources are transported near the surface under 5 km, especially during winter.