The Lagrangian particle dispersion model FLEXPART was originally designed for calculating long-range and mesoscale dispersion of air pollutants from point sources, such that occurring after an accident in a nuclear power plant. In the meantime, FLEXPART has evolved into a comprehensive tool for atmospheric transport modeling and analysis at different scales. A need for further multiscale modeling and analysis has encouraged new developments in FLEXPART. In this paper, we present a FLEXPART version that works with the Weather Research and Forecasting (WRF) mesoscale meteorological model. We explain how to run this new model and present special options and features that differ from those of the preceding versions. For instance, a novel turbulence scheme for the convective boundary layer has been included that considers both the skewness of turbulence in the vertical velocity as well as the vertical gradient in the air density. To our knowledge, FLEXPART is the first model for which such a scheme has been developed. On a more technical level, FLEXPART-WRF now offers effective parallelization, and details on computational performance are presented here. FLEXPART-WRF output can either be in binary or Network Common Data Form (NetCDF) format, both of which have efficient data compression. In addition, test case data and the source code are provided to the reader as a Supplement. This material and future developments will be accessible at http://www.flexpart.eu.Peer ReviewedPostprint (published version

Abstract. New pathways to form secondary organic aerosol (SOA) have been postulated recently. Glyoxal, the smallest dicarbonyl, is one of the proposed precursors. It has both anthropogenic and biogenic sources, and readily partitions into the aqueous phase of cloud droplets and deliquesced particles where it undergoes both reversible and irreversible chemistry. In this work we extend the regional scale chemistry transport model WRF-Chem to include detailed gas-phase chemistry of glyoxal formation as well as a state-of-the-science module describing its partitioning and reactions in the aerosol aqueous-phase. A comparison of several proposed mechanisms is performed to quantify the relative importance of different formation pathways and their regional variability. The CARES/CalNex campaigns over California in summer 2010 are used as case studies to evaluate the model against observations. A month-long simulation over the continental United States (US) enables us to extend our results to the continental scale. In all simulations over California, the Los Angeles (LA) basin was found to be the hot spot for SOA formation from glyoxal, which contributes between 1% and 15% of the model SOA depending on the mechanism used. Our results indicate that a mechanism based only on a reactive (surface limited) uptake coefficient leads to higher SOA yields from glyoxal compared to a more detailed description that considers aerosol phase state and chemical composition. In the more detailed simulations, surface uptake is found to give the highest SOA mass yields compared to a volume process and reversible formation. We find that the yields of the latter are limited by the availability of glyoxal in aerosol water, which is in turn controlled by an increase in the Henry's law constant depending on salt concentrations ("salting-in"). A time dependence in this increase prevents substantial partitioning of glyoxal into aerosol water at high salt concentrations. If this limitation is removed, volume pathways contribute > 20% of glyoxal-SOA mass, and the total mass formed (5.8% of total SOA in the LA basin) is about a third of the simple uptake coefficient formulation without consideration of aerosol phase state and composition. Results from the continental US simulation reveal the much larger potential to form glyoxal-SOA over the eastern continental US. Interestingly, the low concentrations of glyoxal-SOA over the western continental US are not due to the lack of a potential to form glyoxal-SOA here. Rather these small glyoxal-SOA concentrations reflect dry conditions and high salt concentrations, and the potential to form SOA mass here will strongly depend on the water associated with particles.

Abstract. We present top-down estimates of anthropogenic CO, NOx and CO2 surface fluxes at mesoscale using a Lagrangian model in combination with three different WRF model configurations, driven by data from aircraft flights during the CALNEX campaign in southern California in May–June 2010. The US EPA National Emission Inventory 2005 (NEI 2005) was the prior in the CO and NOx inversion calculations. The flux ratio inversion method, based on linear relationships between chemical species, was used to calculate the CO2 inventory without prior knowledge of CO2 surface fluxes. The inversion was applied to each flight to estimate the variability of single-flight-based flux estimates. In Los Angeles (LA) County, the uncertainties on CO and NOx fluxes were 10% and 15%, respectively. Compared with NEI 2005, the CO posterior emissions were lower by 43% in LA County and by 37% in the South Coast Air Basin (SoCAB). NOx posterior emissions were lower by 32% in LA County and by 27% in the SoCAB. NOx posterior emissions were 40% lower on weekends relative to weekdays. The CO2 posterior estimates were 183 Tg yr−1 in SoCAB. A flight during ITCT (Intercontinental Transport and Chemical Transformation) in 2002 was used to estimate emissions in the LA Basin in 2002. From 2002 to 2010, the CO and NOx posterior emissions decreased by 41% and 37%, respectively, in agreement with previous studies. Over the same time period, CO2 emissions increased by 10% in LA County but decreased by 4% in the SoCAB, a statistically insignificant change. Overall, the posterior estimates were in good agreement with the California Air Resources Board (CARB) inventory, with differences of 15% or less. However, the posterior spatial distribution in the basin was significantly different from CARB for NOx emissions. WRF-Chem mesoscale chemical-transport model simulations allowed an evaluation of differences in chemistry using different inventory assumptions, including NEI 2005, a gridded CARB inventory and the posterior inventories derived in this study. The biases in WRF-Chem ozone were reduced and correlations were increased using the posterior from this study compared with simulations with the two bottom-up inventories, suggesting that improving the spatial distribution of ozone precursor surface emissions is also important in mesoscale chemistry simulations.

Abstract. Petroleum and dairy operations are prominent sources of gas-phase organic compounds in California's San Joaquin Valley. It is essential to understand the emissions and air quality impacts of these relatively understudied sources, especially for oil/gas operations in light of increasing US production. Ground site measurements in Bakersfield and regional aircraft measurements of reactive gas-phase organic compounds and methane were part of the CalNex (California Research at the Nexus of Air Quality and Climate Change) project to determine the sources contributing to regional gas-phase organic carbon emissions. Using a combination of near-source and downwind data, we assess the composition and magnitude of emissions, and provide average source profiles. To examine the spatial distribution of emissions in the San Joaquin Valley, we developed a statistical modeling method using ground-based data and the FLEXPART-WRF transport and meteorological model. We present evidence for large sources of paraffinic hydrocarbons from petroleum operations and oxygenated compounds from dairy (and other cattle) operations. In addition to the small straight-chain alkanes typically associated with petroleum operations, we observed a wide range of branched and cyclic alkanes, most of which have limited previous in situ measurements or characterization in petroleum operation emissions. Observed dairy emissions were dominated by ethanol, methanol, acetic acid, and methane. Dairy operations were responsible for the vast majority of methane emissions in the San Joaquin Valley; observations of methane were well correlated with non-vehicular ethanol, and multiple assessments of the spatial distribution of emissions in the San Joaquin Valley highlight the dominance of dairy operations for methane emissions. The petroleum operations source profile was developed using the composition of non-methane hydrocarbons in unrefined natural gas associated with crude oil. The observed source profile is consistent with fugitive emissions of condensate during storage or processing of associated gas following extraction and methane separation. Aircraft observations of concentration hotspots near oil wells and dairies are consistent with the statistical source footprint determined via our FLEXPART-WRF-based modeling method and ground-based data. We quantitatively compared our observations at Bakersfield to the California Air Resources Board emission inventory and find consistency for relative emission rates of reactive organic gases between the aforementioned sources and motor vehicles in the region. We estimate that petroleum and dairy operations each comprised 22% of anthropogenic non-methane organic carbon at Bakersfield and were each responsible for 8–13% of potential precursors to ozone. Yet, their direct impacts as potential secondary organic aerosol (SOA) precursors were estimated to be minor for the source profiles observed in the San Joaquin Valley.

Abstract. Agriculture comprises a substantial, and increasing, fraction of land use in many regions of the world. Emissions from agricultural vegetation and other biogenic and anthropogenic sources react in the atmosphere to produce ozone and secondary organic aerosol, which comprises a substantial fraction of particulate matter (PM2.5). Using data from three measurement campaigns, we examine the magnitude and composition of reactive gas-phase organic carbon emissions from agricultural crops and their potential to impact regional air quality relative to anthropogenic emissions from motor vehicles in California's San Joaquin Valley, which is out of compliance with state and federal standards for tropospheric ozone PM2.5. Emission rates for a suite of terpenoid compounds were measured in a greenhouse for 25 representative crops from California in 2008. Ambient measurements of terpenoids and other biogenic compounds in the volatile and intermediate-volatility organic compound ranges were made in the urban area of Bakersfield and over an orange orchard in a rural area of the San Joaquin Valley during two 2010 seasons: summer and spring flowering. We combined measurements from the orchard site with ozone modeling methods to assess the net effect of the orange trees on regional ozone. When accounting for both emissions of reactive precursors and the deposition of ozone to the orchard, the orange trees are a net source of ozone in the springtime during flowering, and relatively neutral for most of the summer until the fall, when it becomes a sink. Flowering was a major emission event and caused a large increase in emissions including a suite of compounds that had not been measured in the atmosphere before. Such biogenic emission events need to be better parameterized in models as they have significant potential to impact regional air quality since emissions increase by several factors to over an order of magnitude. In regions like the San Joaquin Valley, the mass of biogenic emissions from agricultural crops during the summer (without flowering) and the potential ozone and secondary organic aerosol formation from these emissions are on the same order as anthropogenic emissions from motor vehicles and must be considered in air quality models and secondary pollution control strategies.

We present top-down estimates of anthropogenic CO, NO_x and CO₂ surface fluxes at mesoscale using a Lagrangian model in combination with three different WRF model configurations, driven by data from aircraft flights during the CALNEX campaign in southern California in May–June 2010. The US EPA National Emission Inventory 2005 (NEI 2005) was the prior in the CO and NO_x inversion calculations. The flux ratio inversion method, based on linear relationships between chemical species, was used to calculate the CO₂ inventory without prior knowledge of CO₂ surface fluxes. The inversion was applied to each flight to estimate the variability of single-flight-based flux estimates. In Los Angeles (LA) County, the uncertainties on CO and NO_x fluxes were 10% and 15%, respectively. Compared with NEI 2005, the CO posterior emissions were lower by 43% ± 6% in LA County and by 37% ± 10% in the South Coast Air Basin (SoCAB). NO_x posterior emissions were lower by 32% ± 10% in LA County and by 27% ± 15% in the SoCAB. NO_x posterior emissions were 40% lower on weekends relative to weekdays. The CO₂ posterior estimates were 183 ± 18 Tg yr⁻¹ in SoCAB. A flight during ITCT in 2002 was used to estimate emissions in the LA Basin in 2002. From 2002 to 2010, the CO and NO_x posterior emissions decreased by 41% and 37%, respectively, in agreement with previous studies. Over the same time period, CO₂ emissions increased by 10% ± 14% in LA County but decreased by 4% ± 10% in the SoCAB, a statistically insignificant change. Overall, the posterior estimates were in good agreement with the California Air Resources Board (CARB) inventory, with differences of 15% or less. However, the posterior spatial distribution in the basin was significantly different from CARB for NO_x emissions. WRF-Chem mesoscale chemical-transport model simulations allowed an evaluation of differences in chemistry using different inventory assumptions, including NEI 2005, CARB 2010 and the posterior inventories derived in this study. The biases in WRF-Chem ozone were reduced and correlations were increased using the posterior from this study compared with simulations with the two bottom-up inventories, showing that improving the spatial distribution of ozone precursor surface emissions is also important in mesoscale chemistry forecasts

International audienceLagrangian particle dispersion models require meteorological fields as input. Uncertainty in the driving meteorology is one of the major uncertainties in the results. The propagation of uncertainty through the system is not simple, and it has not been thoroughly explored. Here, we take an ensemble approach. Six different configurations of the Weather Research and Forecast (WRF) model drive otherwise identical simulations with FLEXPART-WRF for 49 days over eastern North America. The ensemble spreads of wind speed, mixing height, and tracer concentration are presented. Uncertainty of tracer concentrations due solely to meteorological uncertainty is 30–40 %. Spatial and temporal averaging reduces the uncertainty marginally. Tracer age uncertainty due solely to meteorological uncertainty is 15–20 %. These are lower bounds on the uncertainty, because a number of processes are not accounted for in the analysis

Abstract. We present a source apportionment study of a near-continuous 2-year dataset of volatile organic compounds (VOCs), recorded between October 2017 and November 2019 with a quadrupole-based high-sensitivity proton-transfer-reaction mass-spectrometry (hs-PTR-MS) instrument deployed at the Maïdo observatory (21.1∘ S, 55.4∘ E, 2160 m altitude). The observatory is located on La Réunion island in the southwest Indian Ocean. We discuss seasonal and diel profiles of six key VOC species unequivocally linked to specific sources – acetonitrile (CH3CN), isoprene (C5H8), isoprene oxidation products (Iox), benzene (C6H6), C8-aromatic compounds (C8H10), and dimethyl sulfide (DMS). The data are analyzed using the positive matrix factorization (PMF) method and back-trajectory calculations based on the Lagrangian mesoscale transport model FLEXPART-AROME to identify the impact of different sources on air masses sampled at the observatory. As opposed to the biomass burning tracer CH3CN, which does not exhibit a typical diel pattern consistently throughout the dataset, we identify pronounced diel profiles with a daytime maximum for the biogenic (C5H8 and Iox) and anthropogenic (C6H6, C8H10) tracers. The marine tracer DMS generally displays a daytime maximum except for the austral winter when the difference between daytime and nighttime mixing ratios vanishes. Four factors were identified by the PMF: background/biomass burning, anthropogenic, primary biogenic, and secondary biogenic. Despite human activity being concentrated in a few coastal areas, the PMF results indicate that the anthropogenic source factor is the dominant contributor to the VOC load (38 %), followed by the background/biomass burning source factor originating in the free troposphere (33 %), and by the primary (15 %) and secondary biogenic (14 %) source factors. FLEXPART-AROME simulations showed that the observatory was most sensitive to anthropogenic emissions west of Maïdo while the strongest biogenic contributions coincided with air masses passing over the northeastern part of La Réunion. At night, the observatory is often located in the free troposphere, while during the day, the measurements are influenced by mesoscale sources. Interquartile ranges of nighttime 30 min average mixing ratios of methanol (CH3OH), CH3CN, acetaldehyde (CH3CHO), formic acid (HCOOH), acetone (CH3COCH3), acetic acid (CH3COOH), and methyl ethyl ketone (MEK), representative for the atmospheric composition of the free troposphere, were found to be 525–887, 79–110, 61–101, 172–335, 259–379, 64–164, and 11–21 pptv, respectively.