The quantification of CO 2 emissions from cities using atmospheric measurements requires accurate knowledge of the atmospheric transport. Complex urban terrains significantly modify surface roughness, augment surface energy budgets, and create heat islands, all of which lead to lower horizontal winds and enhanced convection over urban areas. The question remains whether these processes should be included in atmospheric transport models that are used for city scale CO 2 inversion, and whether they need to be tailored on a city basis. In this study, we use the WRF model over Paris to address the following research question: does WRF runs at a 3 km resolution, including urban effects and the assimilation of local weather data, perform better than ECMWF forecasts that give fields at 16 km resolution? The analysis of model performances focuses on three variables: air temperature, wind and the planetary boundary layer (PBL) height. The results show that the use of objective analysis and nudging tools are required to obtain good agreements between WRF simulated fields with observations. Surface temperature is well reproduced by both WRF and ECMWF forecasts, with correlation coefficients with hourly observations larger than 0.92 and MBEs within 1°C over one month. Wind speed correlations with hourly observations are similar for WRF (range 0.76~0.85 across stations) and ECMWF (0.79~0.84), but the associated RMSEs and MBEs are better for ECMWF. Conversely, WRF outperforms ECMWF forecasts for its description of wind direction, horizontal and vertical gradients. Sensitivity tests with different WRF physics schemes show that the wind speed and the PBL height are strongly influenced by PBL schemes. The marginal advantage of WRF over ECMWF for the desired application is sufficient to motive additional testing with prescribed CO 2 flux maps for comparing modeled CO 2 concentrations with available observations in an urban environment.

Wind erosion of soils burned by wildfire contributes substantial particulate matter (PM) in the form of dust to the atmosphere, but the magnitude of this dust source is largely unknown. It is important to accurately quantify dust emissions because they can impact human health, degrade visibility, exacerbate dust-on-snow issues (including snowmelt timing, snow chemistry, and avalanche danger), and affect ecological and biogeochemical cycles, precipitation regimes, and the Earth’s radiation budget. We used a novel modeling approach in which local-scale winds were used to drive a high-resolution dust emission model parameterized for burned soils to provide a first estimate of post-fire PM emissions. The dust emission model was parameterized with dust flux measurements from a 2010 fire scar. Here we present a case study to demonstrate the ability of the modeling framework to capture the onset and dynamics of a post-fire dust event and then use the modeling framework to estimate PM emissions from burn scars left by wildfires in U.S. western sagebrush landscapes during 2012. Modeled emissions from 1.2 million ha of burned soil totaled 32.1 Tg (11.7–352 Tg) of dust as PM 10 and 12.8 Tg (4.68–141 Tg) as PM 2.5 . Despite the relatively large uncertainties in these estimates and a number of underlying assumptions, these first estimates of annual post-fire dust emissions suggest that post-fire PM emissions could substantially increase current annual PM estimates in the U.S. National Emissions Inventory during high fire activity years. Given the potential for post-fire scars to be a large source of PM, further on-site PM flux measurements are needed to improve emission parameterizations and constrain these first estimates.

A record spanning ten years of non-methane hydrocarbon (NMHC) data from the Pico Mountain Observatory (PMO), Pico Island, Azores, Portugal, was analyzed for seasonal NMHC behavior, atmospheric processing, and trends, focusing on ethane and propane. The location of this site in the central North Atlantic, at an elevation of 2225 m asl, allows these data to be used to investigate the background conditions and pollution transport events occurring in the lower free North Atlantic troposphere. The quantity ln([propane]/[ethane]) was used as an indicator of both photochemical processing and a marker for the occurrence of pollution transport events detected at the station. The Pico data were compared with three other continuous NMHC data sets from sites bordering the North Atlantic, i.e. the Global Atmospheric Watch (GAW) stations at Summit, Greenland, Hohenpeisssenberg, Germany, and Cape Verde, using ln([propane]/[ethane]) results as an indicator for the degree of photochemical processing (‘aging’) seen in the data. Comparisons of these three data sets showed some significant differences in the seasonal background and range of observed values. The statistical distribution of binned monthly data was determined, and individual sample events were then scaled to the monthly median observed value. Back trajectories, determined by the HYSPLIT model were used to investigate the geographic origin of the observed trace gases as a function of the degree of photochemical processing. Results show that PMO samples have been subjected to a diversity of air transport and aging, from highly processed air to freshly emitted air throughout the year, and in particular during summer months. The predominant air transport is from North America, with only occasional influence from continental areas located east and southeast (Europe and Africa). The available record was found to be too variable and still too short to allow deciphering NMHC trends from the data. Ethane and propane measurements at the PMO were compared with the MOZART-4 atmospheric chemistry and transport model at the appropriate time and location. The model was found to yield good agreement in the description of the lower range of atmospheric mole fractions observed, of the seasonal cycle, and the regional oxidation chemistry. However, ethane and propane enhancements in transport events were underestimated, indicating that after the ≥ 3 days of synoptic transport to PMO the spatial extent of plumes frequently is smaller than the 2.8°x2.8° (∼300 km) model grid resolution.

Winter maximum daily 8-hour average (MDA8) ozone concentrations in the Upper Green River Basin, Wyoming (UGRBWY) and the Uintah Basin, Utah (UBUT) have frequently exceeded 100 ppb in January, February and March, in the past few years. Such levels are well above the U.S. air quality standard of 75 ppb. In these two remote basins in the Rockies, local ozone precursor emissions result from intense oil and gas extraction activities that release methane, volatile organic compounds (VOCs), and nitrogen oxides (NO x ) to the atmosphere. These emissions become trapped beneath a stable and shallow (∼50–200 m) boundary layer maintained in low wind conditions. Wintertime surface ozone formation conditions are more likely in the UBUT than in the UGRBWY as the topography of the UBUT is an enclosed basin whereas the UGRBWY is open on its southern perimeter thus allowing for more air turnover. With snow-covered ground, high ozone events regularly begin in mid-December and last into early March in the UBUT whereas they usually do not begin in earnest until about a month later in the UGRBWY and may persist until mid-March. Winters without snow cover and the accompanying cold pool meteorological conditions do not experience high ozone events in either basin. For nine years with ozone observations in the UGRBWY (2005–2013) and four in the UBUT (2010–2013), all years with adequate (≥6 inches) and persistent snow cover, experienced days with ozone values ≥75 ppb except in 2012 in the UGRBWY when persistent high wind (>5 m/s) conditions were prevalent. Year to year differences in the occurrences of high ozone episodes appear to be driven primarily by differing meteorological conditions rather than by variations in ozone precursor levels.