Fossil versus contemporary sources of fine elemental and organic carbonaceous particulate matter during the DAURE campaign in Northeast Spain

We present results from the international field campaign DAURE (Detn. of the sources of atm. Aerosols in Urban and Rural Environments in the Western Mediterranean), with the objective of apportioning the sources of fine carbonaceous aerosols. Submicron fine particulate matter (PM1) samples were collected during Feb.-March 2009 and July 2009 at an urban background site in Barcelona (BCN) and at a forested regional background site in Montseny (MSY). We present radiocarbon (14C) anal. for elemental and org. carbon (EC and OC) and source apportionment for these data. We combine the results with those from component anal. of aerosol mass spectrometer (AMS) measurements, and compare to levoglucosan-based ests. of biomass burning OC, source apportionment of filter data with inorg. compn. + EC + OC, submicron bulk potassium (K) concns., and gaseous acetonitrile concns. At BCN, 87 % and 91 % of the EC on av., in winter and summer, resp., had a fossil origin, whereas at MSY these fractions were 66 % and 79 %. The contribution of fossil sources to org. carbon (OC) at BCN was 40 % and 48 %, in winter and summer, resp., and 31 % and 25 % at MSY. The combination of results obtained using the 14C technique, AMS data, and the correlations between fossil OC and fossil EC imply that the fossil OC at Barcelona is ∼47 % primary whereas at MSY the fossil OC is mainly secondary (∼85 %). Day-to-day variation in total carbonaceous aerosol loading and the relative contributions of different sources predominantly depended on the meteorol. transport conditions. The estd. biogenic secondary OC at MSY only increased by ∼40 % compared to the order-of-magnitude increase obsd. for biogenic volatile org. compds. (VOCs) between winter and summer, which highlights the uncertainties in the estn. of that component. Biomass burning contributions estd. using the 14C technique ranged from similar to slightly higher than when estd. using other techniques, and the different estns. were highly or moderately correlated. Differences can be explained by the contribution of secondary org. matter (not included in the primary biomass burning source ests.), and/or by an over-estn. of the biomass burning OC contribution by the 14C technique if the estd. biomass burning EC/OC ratio used for the calcns. is too high for this region. Acetonitrile concns. correlate well with the biomass burning EC detd. by 14C. K is a noisy tracer for biomass burning. [on SciFinder(R)]

Constraining global methane emissions and uptake by ecosystems

Natural methane (CH4) emissions from wet ecosystems are an important part of today's global CH4 budget. Climate affects the exchange of CH4 between ecosystems and the atmosphere by influencing CH4 production, oxidation, and transport in the soil. The net CH4 exchange depends on ecosystem hydrology, soil and vegetation characteristics. Here, the LPJ-WHyMe global dynamical vegetation model is used to simulate global net CH4 emissions for different ecosystems: northern peatlands (45°–90° N), naturally inundated wetlands (60° S–45° N), rice agriculture and wet mineral soils. Mineral soils are a potential CH4 sink, but can also be a source with the direction of the net exchange depending on soil moisture content. The geographical and seasonal distributions are evaluated against multi-dimensional atmospheric inversions for 2003–2005, using two independent four-dimensional variational assimilation systems. The atmospheric inversions are constrained by the atmospheric CH4 observations of the SCIAMACHY satellite instrument and global surface networks. Compared to LPJ-WHyMe the inversions result in a~significant reduction in the emissions from northern peatlands and suggest that LPJ-WHyMe maximum annual emissions peak about one month late. The inversions do not put strong constraints on the division of sources between inundated wetlands and wet mineral soils in the tropics. Based on the inversion results we diagnose model parameters in LPJ-WHyMe and simulate the surface exchange of CH4 over the period 1990–2008. Over the whole period we infer an increase of global ecosystem CH4 emissions of +1.11 Tg CH4 yr−1, not considering potential additional changes in wetland extent. The increase in simulated CH4 emissions is attributed to enhanced soil respiration resulting from the observed rise in land temperature and in atmospheric carbon dioxide that were used as input. The long-term decline of the atmospheric CH4 growth rate from 1990 to 2006 cannot be fully explained with the simulated ecosystem emissions. However, these emissions show an increasing trend of +3.62 Tg CH4 yr−1 over 2005–2008 which can partly explain the renewed increase in atmospheric CH4 concentration during recent years.

Gasoline emissions dominate over diesel in formation of secondary organic aerosol mass

Although laboratory experiments have shown that organic compounds in both gasoline fuel and diesel engine exhaust can form secondary organic aerosol (SOA), the fractional contribution from gasoline and diesel exhaust emissions to ambient SOA in urban environments is poorly known. Here we use airborne and ground-based measurements of organic aerosol (OA) in the Los Angeles (LA) Basin, California made during May and June 2010 to assess the amount of SOA formed from diesel emissions. Diesel emissions in the LA Basin vary between weekdays and weekends, with 54% lower diesel emissions on weekends. Despite this difference in source contributions, in air masses with similar degrees of photochemical processing, formation of OA is the same on weekends and weekdays, within the measurement uncertainties. This result indicates that the contribution from diesel emissions to SOA formation is zero within our uncertainties. Therefore, substantial reductions of SOA mass on local to global scales will be achieved by reducing gasoline vehicle emissions.

Extended frequency range hearing thresholds and otoacoustic emissions in acute acoustic trauma

We sought to evaluate the relative value of pure tone audiometry (PTA), extended high-frequency audiometry (EFA) and transiently evoked otoacoustic emissions (OAE) and distortion products when monitoring acute acoustic trauma (AAT).

Analysis and Prediction of Transient Opacity Spikes Using Dimensional Modeling

Dimensional modeling, GT-Power in particular, has been used for two related purposes-to quantify and understand the inaccuracies of transient engine flow estimates that cause transient smoke spikes and to improve empirical models of opacity or particulate matter used for engine calibration. It has been proposed by dimensional modeling that exhaust gas recirculation flow rate was significantly underestimated and volumetric efficiency was overestimated by the electronic control module during the turbocharger lag period of an electronically controlled heavy duty diesel engine. Factoring in cylinder-to-cylinder variation, it has been shown that the electronic control module estimated fuel-Oxygen ratio was lower than actual by up to 35% during the turbocharger lag period but within 2% of actual elsewhere, thus hindering fuel-Oxygen ratio limit-based smoke control. The dimensional modeling of transient flow was enabled with a new method of simulating transient data in which the manifold pressures and exhaust gas recirculation system flow resistance, characterized as a function of exhaust gas recirculation valve position at each measured transient data point, were replicated by quasi-static or transient simulation to predict engine flows. Dimensional modeling was also used to transform the engine operating parameter model input space to a more fundamental lower dimensional space so that a nearest neighbor approach could be used to predict smoke emissions. This new approach, intended for engine calibration and control modeling, was termed the "nonparametric reduced dimensionality" approach. It was used to predict federal test procedure cumulative particulate matter within 7% of measured value, based solely on steady-state training data. Very little correlation between the model inputs in the transformed space was observed as compared to the engine operating parameter space. This more uniform, smaller, shrunken model input space might explain how the nonparametric reduced dimensionality approach model could successfully predict federal test procedure emissions when roughly 40% of all transient points were classified as outliers as per the steady-state training data.