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Simultaneous monitoring of stable oxygen isotope composition in water vapour and precipitation over the central Tibetan Plateau

This study investigated daily δ18O variations of water vapour (δ18Ov) and precipitation (δ18Op) simultaneously at Nagqu on the central Tibetan Plateau for the first time. Data show that the δ18O tendencies of water vapour coincide strongly with those of associated precipitation. The δ18O values of precipitation affect those of water vapour not only on the same day, but also for the following several days. In comparison, the δ18O values of local water vapour may only partly contribute to those of precipitation. During the entire sampling period, the variations of δ18Ov and δ18Op at Nagqu did not appear dependent on temperature, but did seem significantly dependent on the joint contributions of relative humidity, pressure, and precipitation amount. In addition, the δ18O changes in water vapour and precipitation can be used to diagnose different moisture sources, especially the influences of the Indian monsoon and convection. Moreover, intense activities of the Indian monsoon and convection may cause the relative enrichment of δ18Op relative to δ18Ov at Nagqu (on the central Tibetan Plateau) to differ from that at other stations on the northern Tibetan Plateau. These results indicate that the effects of different moisture sources, including the Indian monsoon and convection currents, need be considered when attempting to interpret paleoclimatic records on the central Tibetan Plateau.
Constraining black carbon aerosol over Asia using OMI aerosol absorption optical depth and the adjoint of GEOS-Chem

Accurate estimates of the emissions and distribution of black carbon (BC) in the region referred to here as Southeastern Asia (70–150° E, 11° S–55° N) are critical to studies of the atmospheric environment and climate change. Analysis of modeled BC concentrations compared to in situ observations indicates levels are underestimated over most of Southeast Asia when using any of four different emission inventories. We thus attempt to reduce uncertainties in BC emissions and improve BC model simulations by developing top-down, spatially resolved, estimates of BC emissions through assimilation of OMI (Ozone Monitoring Instrument) observations of aerosol absorption optical depth (AAOD) with the GEOS-Chem (Goddard Earth Observing System – chemistry) model and its adjoint for April and October 2006. Overwhelming enhancements, up to 500 %, in anthropogenic BC emissions are shown after optimization over broad areas of Southeast Asia in April. In October, the optimization of anthropogenic emissions yields a slight reduction (1–5 %) over India and parts of southern China, while emissions increase by 10–50 % over eastern China. Observational data from in situ measurements and AERONET (Aerosol Robotic Network) observations are used to evaluate the BC inversions and assess the bias between OMI and AERONET AAOD. Low biases in BC concentrations are improved or corrected in most eastern and central sites over China after optimization, while the constrained model still underestimates concentrations in Indian sites in both April and October, possibly as a consequence of low prior emissions. Model resolution errors may contribute up to a factor of 2.5 to the underestimation of surface BC concentrations over northern India. We also compare the optimized results using different anthropogenic emission inventories and discuss the sensitivity of top-down constraints on anthropogenic emissions with respect to biomass burning emissions. In addition, the impacts of brown carbon, the formulation of the observation operator, and different a priori constraints on the optimization are investigated. Overall, despite these limitations and uncertainties, using OMI AAOD to constrain BC sources improves model representation of BC distributions, particularly over China.
Sensitivity estimations for cloud droplet formation in the vicinity of the high-alpine research station Jungfraujoch (3580 m a.s.l.)

Aerosol radiative forcing estimates suffer from large uncertainties as a result of insufficient understanding of aerosol–cloud interactions. The main source of these uncertainties is dynamical processes such as turbulence and entrainment but also key aerosol parameters such as aerosol number concentration and size distribution, and to a much lesser extent, the composition. From June to August 2011 a Cloud and Aerosol Characterization Experiment (CLACE2011) was performed at the high-alpine research station Jungfraujoch (Switzerland, 3580 m a.s.l.) focusing on the activation of aerosol to form liquid-phase clouds (in the cloud base temperature range of −8 to 5 °C). With a box model the sensitivity of the effective peak supersaturation (SSpeak), an important parameter for cloud activation, to key aerosol and dynamical parameters was investigated. The updraft velocity, which defines the cooling rate of an air parcel, was found to have the greatest influence on SSpeak. Small-scale variations in the cooling rate with large amplitudes can significantly alter CCN activation. Thus, an accurate knowledge of the air parcel history is required to estimate SSpeak. The results show that the cloud base updraft velocities estimated from the horizontal wind measurements made at the Jungfraujoch can be divided by a factor of approximately 4 to get the updraft velocity required for the model to reproduce the observed SSpeak. The aerosol number concentration and hygroscopic properties were found to be less important than the aerosol size in determining SSpeak. Furthermore turbulence is found to have a maximum influence when SSpeak is between approximately 0.2 and 0.4 %. Simulating the small-scale fluctuations with several amplitudes, frequencies and phases, revealed that independently of the amplitude, the effect of the frequency on SSpeak shows a maximum at 0.46 Hz (median over all phases) and at higher frequencies, the maximum SSpeak decreases again.
Comprehensive mapping and characteristic regimes of aerosol effects on the formation and evolution of pyro-convective clouds

A recent parcel model study (Reutter et al., 2009) showed three deterministic regimes of initial cloud droplet formation, characterized by different ratios of aerosol concentrations (NCN) to updraft velocities. This analysis, however, did not reveal how these regimes evolve during the subsequent cloud development. To address this issue, we employed the Active Tracer High Resolution Atmospheric Model (ATHAM) with full microphysics and extended the model simulation from the cloud base to the entire column of a single pyro-convective mixed-phase cloud. A series of 2-D simulations (over 1000) were performed over a wide range of NCN and dynamic conditions. The integrated concentration of hydrometeors over the full spatial and temporal scales was used to evaluate the aerosol and dynamic effects. The results show the following. (1) The three regimes for cloud condensation nuclei (CCN) activation in the parcel model (namely aerosol-limited, updraft-limited, and transitional regimes) still exist within our simulations, but net production of raindrops and frozen particles occurs mostly within the updraft-limited regime. (2) Generally, elevated aerosols enhance the formation of cloud droplets and frozen particles. The response of raindrops and precipitation to aerosols is more complex and can be either positive or negative as a function of aerosol concentrations. The most negative effect was found for values of NCN of ~ 1000 to 3000 cm−3. (3) The nonlinear properties of aerosol–cloud interactions challenge the conclusions drawn from limited case studies in terms of their representativeness, and ensemble studies over a wide range of aerosol concentrations and other influencing factors are strongly recommended for a more robust assessment of the aerosol effects.
Emissions of nitrogen oxides from US urban areas: estimation from Ozone Monitoring Instrument retrievals for 2005–2014

Satellite remote sensing of tropospheric nitrogen dioxide (NO2) can provide valuable information for estimating surface nitrogen oxides (NOx) emissions. Using an exponentially modified Gaussian (EMG) method and taking into account the effect of wind on observed NO2 distributions, we estimate 3-year moving-average emissions of summertime NOx from 35 US (United States) urban areas directly from NO2 retrievals of the Ozone Monitoring Instrument (OMI) during 2005–2014. Following conclusions of previous studies that the EMG method provides robust and accurate emission estimates under strong-wind conditions, we derive top-down NOx emissions from each urban area by applying the EMG method to OMI data with wind speeds greater than 3–5 m s−1. Meanwhile, we find that OMI NO2 observations under weak-wind conditions (i.e., < 3 m s−1) are qualitatively better correlated to the surface NOx source strength in comparison to all-wind OMI maps; therefore, we use them to calculate the satellite-observed NO2 burdens of urban areas and compare with NOx emission estimates. The EMG results show that OMI-derived NOx emissions are highly correlated (R > 0.93) with weak-wind OMI NO2 burdens as well as with bottom-up NOx emission estimates over 35 urban areas, implying a linear response of the OMI observations to surface emissions under weak-wind conditions. The simultaneous EMG-obtained effective NO2 lifetimes (~ 3.5 ± 1.3 h), however, are biased low in comparison to the summertime NO2 chemical lifetimes. In general, isolated urban areas with NOx emission intensities greater than ~ 2 Mg h−1 produce statistically significant weak-wind signals in 3-year average OMI data. From 2005 to 2014, we estimate that total OMI-derived NOx emissions over all selected US urban areas decreased by 49 %, consistent with reductions of 43, 47, 49, and 44 % in the total bottom-up NOx emissions, the sum of weak-wind OMI NO2 columns, the total weak-wind OMI NO2 burdens, and the averaged NO2 concentrations, respectively, reflecting the success of NOx control programs for both mobile sources and power plants. The decrease rates of these NOx-related quantities are found to be faster (i.e., −6.8 to −9.3 % yr−1) before 2010 and slower (i.e., −3.4 to −4.9 % yr−1) after 2010. For individual urban areas, we calculate the R values of pair-wise trends among the OMI-derived and bottom-up NOx emissions, the weak-wind OMI NO2 burdens, and ground-based NO2 measurements, and high correlations are found for all urban areas (median R= 0.8), particularly large ones (R up to 0.97). The results of the current work indicate that using the EMG method and considering the wind effect, the OMI data allow for the estimation of NOx emissions from urban areas and the direct constraint of emission trends with reasonable accuracy.
Investigating the observed sensitivities of air-quality extremes to meteorological drivers via quantile regression

Air pollution variability is strongly dependent on meteorology. However, quantifying the impacts of changes in regional climatology on pollution extremes can be difficult due to the many non-linear and competing meteorological influences on the production, transport, and removal of pollutant species. Furthermore, observed pollutant levels at many sites show sensitivities at the extremes that differ from those of the overall mean, indicating relationships that would be poorly characterized by simple linear regressions. To address this challenge, we apply quantile regression to observed daily ozone (O3) and fine particulate matter (PM2.5) levels and reanalysis meteorological fields in the USA over the past decade to specifically identify the meteorological sensitivities of higher pollutant levels. From an initial set of over 1700 possible meteorological indicators (including 28 meteorological variables with 63 different temporal options), we generate reduced sets of O3 and PM2.5 indicators for both summer and winter months, analyzing pollutant sensitivities to each for response quantiles ranging from 2 to 98 %. Primary covariates connected to high-quantile O3 levels include temperature and relative humidity in the summer, while winter O3 levels are most commonly associated with incoming radiation flux. Covariates associated with summer PM2.5 include temperature, wind speed, and tropospheric stability at many locations, while stability, humidity, and planetary boundary layer height are the key covariates most frequently associated with winter PM2.5. We find key differences in covariate sensitivities across regions and quantiles. For example, we find nationally averaged sensitivities of 95th percentile summer O3 to changes in maximum daily temperature of approximately 0.9 ppb °C−1, while the sensitivity of 50th percentile summer O3 (the annual median) is only 0.6 ppb °C−1. This gap points to differing sensitivities within various percentiles of the pollutant distribution, highlighting the need for statistical tools capable of identifying meteorological impacts across the entire response spectrum.
Model studies of volatile diesel exhaust particle formation: are organic vapours involved in nucleation and growth?

A high concentration of volatile nucleation mode particles (NUP) formed in the atmosphere when the exhaust cools and dilutes has hazardous health effects and it impairs the visibility in urban areas. Nucleation mechanisms in diesel exhaust are only poorly understood. We performed model studies using two sectional aerosol dynamics process models AEROFOR and MAFOR on the formation of particles in the exhaust of a diesel engine, equipped with an oxidative after-treatment system and running with low fuel sulfur content (FSC) fuel, under laboratory sampling conditions where the dilution system mimics real-world conditions. Different nucleation mechanisms were tested. Based on the measured gaseous sulfuric acid (GSA) and non-volatile core and soot particle number concentrations of the raw exhaust, the model simulations showed that the best agreement between model predictions and measurements in terms of particle number size distribution was obtained by barrier-free heteromolecular homogeneous nucleation between the GSA and a semi-volatile organic vapour combined with the homogeneous nucleation of GSA alone. Major growth of the particles was predicted to occur due to the similar organic vapour at concentrations of (1−2) × 1012 cm−3. The pre-existing core and soot mode concentrations had an opposite trend on the NUP formation, and the maximum NUP formation was predicted if a diesel particle filter (DPF) was used. On the other hand, the model predicted that the NUP formation ceased if the GSA concentration in the raw exhaust was less than 1010 cm−3, which was the case when biofuel was used.
Parameterizations for convective transport in various cloud-topped boundary layers

We investigate the representation of convective transport of atmospheric compounds by boundary layer clouds. We focus on three key parameterizations that, when combined, express this transport: the area fraction of transporting clouds, the upward velocity in the cloud cores and the chemical concentrations at cloud base. The first two parameterizations combined represent the kinematic mass flux by clouds. To investigate the key parameterizations under a wide range of conditions, we use large-eddy simulation model data for 10 meteorological situations, characterized by either shallow cumulus or stratocumulus clouds. The parameterizations have not been previously tested with such large data sets. In the analysis, we show that the parameterization of the area fraction of clouds currently used in mixed-layer models is affected by boundary layer dynamics. Therefore, we (i) simplify the independent variable used for this parameterization, Q1, by considering the variability in moisture rather than in the saturation deficit and update the parameters in the parameterization to account for this simplification. We (ii) next demonstrate that the independent variable has to be evaluated locally to capture cloud presence. Furthermore, we (iii) show that the area fraction of transporting clouds is not represented by the parameterization for the total cloud area fraction, as is currently assumed in literature. To capture cloud transport, a novel active cloud area fraction parameterization is proposed. Subsequently, the scaling of the upward velocity in cloud cores by the Deardorff convective velocity scale and the parameterization for the concentration of atmospheric reactants at cloud base from literature are verified and improved by analysing six shallow cumulus cases. For the latter, we additionally discuss how the parameterization is affected by wind conditions. This study contributes to a more accurate estimation of convective transport, which occurs at sub-grid scales.
Sources, seasonality, and trends of southeast US aerosol: an integrated analysis of surface, aircraft, and satellite observations with the GEOS-Chem chemical transport model

We use an ensemble of surface (EPA CSN, IMPROVE, SEARCH, AERONET), aircraft (SEAC4RS), and satellite (MODIS, MISR) observations over the southeast US during the summer–fall of 2013 to better understand aerosol sources in the region and the relationship between surface particulate matter (PM) and aerosol optical depth (AOD). The GEOS-Chem global chemical transport model (CTM) with 25 × 25 km2 resolution over North America is used as a common platform to interpret measurements of different aerosol variables made at different times and locations. Sulfate and organic aerosol (OA) are the main contributors to surface PM2.5 (mass concentration of PM finer than 2.5 μm aerodynamic diameter) and AOD over the southeast US. OA is simulated successfully with a simple parameterization, assuming irreversible uptake of low-volatility products of hydrocarbon oxidation. Biogenic isoprene and monoterpenes account for 60 % of OA, anthropogenic sources for 30 %, and open fires for 10 %. 60 % of total aerosol mass is in the mixed layer below 1.5 km, 25 % in the cloud convective layer at 1.5–3 km, and 15 % in the free troposphere above 3 km. This vertical profile is well captured by GEOS-Chem, arguing against a high-altitude source of OA. The extent of sulfate neutralization (f = [NH4+]/(2[SO42−] + [NO3−]) is only 0.5–0.7 mol mol−1 in the observations, despite an excess of ammonia present, which could reflect suppression of ammonia uptake by OA. This would explain the long-term decline of ammonium aerosol in the southeast US, paralleling that of sulfate. The vertical profile of aerosol extinction over the southeast US follows closely that of aerosol mass. GEOS-Chem reproduces observed total column aerosol mass over the southeast US within 6 %, column aerosol extinction within 16 %, and space-based AOD within 8–28 % (consistently biased low). The large AOD decline observed from summer to winter is driven by sharp declines in both sulfate and OA from August to October. These declines are due to shutdowns in both biogenic emissions and UV-driven photochemistry. Surface PM2.5 shows far less summer-to-winter decrease than AOD and we attribute this in part to the offsetting effect of weaker boundary layer ventilation. The SEAC4RS aircraft data demonstrate that AODs measured from space are consistent with surface PM2.5. This implies that satellites can be used reliably to infer surface PM2.5 over monthly timescales if a good CTM representation of the aerosol vertical profile is available.
Acetylene (C2H2) and hydrogen cyanide (HCN) from IASI satellite observations: global distributions, validation, and comparison with model

We present global distributions of C2H2 and hydrogen cyanide (HCN) total columns derived from the Infrared Atmospheric Sounding Interferometer (IASI) for the years 2008–2010. These distributions are obtained with a fast method allowing to retrieve C2H2 abundance globally with a 5 % precision and HCN abundance in the tropical (subtropical) belt with a 10 % (25 %) precision. IASI data are compared for validation purposes with ground-based Fourier transform infrared (FTIR) spectrometer measurements at four selected stations. We show that there is an overall agreement between the ground-based and space measurements with correlation coefficients for daily mean measurements ranging from 0.28 to 0.81, depending on the site. Global C2H2 and subtropical HCN abundances retrieved from IASI spectra show the expected seasonality linked to variations in the anthropogenic emissions and seasonal biomass burning activity, as well as exceptional events, and are in good agreement with previous spaceborne studies. Total columns simulated by the Model for Ozone and Related Chemical Tracers, version 4 (MOZART-4) are compared to the ground-based FTIR measurements at the four selected stations. The model is able to capture the seasonality in the two species in most of the cases, with correlation coefficients for daily mean measurements ranging from 0.50 to 0.86, depending on the site. IASI measurements are also compared to the distributions from MOZART-4. Seasonal cycles observed from satellite data are reasonably well reproduced by the model with correlation coefficients ranging from −0.31 to 0.93 for C2H2 daily means, and from 0.09 to 0.86 for HCN daily means, depending on the considered region. However, the anthropogenic (biomass burning) emissions used in the model seem to be overestimated (underestimated), and a negative global mean bias of 1 % (16 %) of the model relative to the satellite observations was found for C2H2 (HCN).