Ozone concentrations in excess of health‐based standards occur along the coastline of Lake Michigan. A complex pattern of ozone precursor emissions interfaces with a complex meteorological environment, presenting a challenge for air quality management and simulation. Precursors are transported into a shallow, stable boundary layer over the lake. This is followed by ozone formation and transport back onshore through a combination of synoptic and lake breeze winds. In this study, we use measurements during the Lake Michigan Ozone Study 2017 (LMOS) to quantitatively evaluate the Weather Research and Forecasting with Chemistry (WRF‐Chem) model at 4 km horizontal resolution for key features of high ozone episodes over Southern Lake Michigan, with a focus on meteorological performance. WRF‐Chem showed good performance and successful reproduction of meteorological fields and clouds. Lake breeze model skill was inconsistent, with both good and poor performance depending on site and day. The combination of Noah land surface model and High‐Resolution Rapid Refresh meteorology gave the best performance with the mean bias of −0.5 °C for temperature, −0.6 °C for dewpoint temperature, and −0.3 m/s for wind speed along the western coast of Lake Michigan during the daytime. For ozone, WRF‐Chem was biased low (−4.4 ppb mean bias for daytime ozone) and underestimated hourly peak ozone. In some cases, ozone bias can be attributed to transport and lake breeze errors. Average ozone concentration showed minor (<2 ppb) sensitivity to changes to meteorology initial and boundary conditions or the land surface model.

The Lake Michigan Ozone Study 2017 (LMOS 2017) was a collaborative multi-agency field study targeting ozone chemistry, meteorology, and air quality observations in the southern Lake Michigan area. The primary objective of LMOS 2017 was to provide measurements to improve air quality modeling of the complex meteorological and chemical environment in the region. LMOS 2017 science questions included spatiotemporal assessment of nitrogen oxides (NOx = NO + NO2) and volatile organic compounds (VOC) emission sources and their influence on ozone episodes, the role of lake breezes, contribution of new remote sensing tools such as GeoTASO, Pandora, and TEMPO to air quality management, and evaluation of photochemical grid models. The observing strategy included GeoTASO on board the NASA UC-12 capturing NO2 and formaldehyde columns, an in situ profiling aircraft, two ground-based coastal enhanced monitoring locations, continuous NO2 columns from coastal Pandora instruments, and an instrumented research vessel. Local photochemical ozone production was observed on 2 June, 9–12 June, and 14–16 June, providing insights on the processes relevant to state and federal air quality management. The LMOS 2017 aircraft mapped significant spatial and temporal variation of NO2 emissions as well as polluted layers with rapid ozone formation occurring in a shallow layer near the Lake Michigan surface. Meteorological characteristics of the lake breeze were observed in detail and measurements of ozone, NOx, nitric acid, hydrogen peroxide, VOC, oxygenated VOC (OVOC), and fine particulate matter (PM2.5) composition were conducted. This article summarizes the study design, directs readers to the campaign data repository, and presents a summary of findings.

Abstract. 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.