Impacts of physical parametrization on prediction of ethane concentrations for oil and gas emissions

Abstract. 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 FRAPPE 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 −14.9 ppb to −8.2 ppb (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.