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The transitory nature of the atmospheric boundary layer (ABL) a few hours before and after the time of sunset has been studied comprehensively over a tropical station, Gadanki (13.45° N, 79.18° E), using a suite of in situ and remote sensing devices. This study addresses the following fundamental and important issues related to the afternoon transition (AT): which state variable first identifies the AT? Which variable best identifies the AT? Does the start time of the AT vary with season and height? If so, which physical mechanism is responsible for the observed height variation in the start time of the transition? <br><br> At the surface, the transition is first seen in temperature (<i>T</i>) and wind variance (σ<sup>2</sup><sub>WS</sub>), ~ 100 min prior to the time of local sunset, then in the vertical temperature gradient and finally in water vapor mixing ratio variations. Aloft, both signal-to-noise ratio (SNR) and spectral width (σ) show the AT nearly at the same time. The <i>T</i> at the surface and SNR aloft are found to be the best indicators of transition. Their distributions for the start time of the AT with reference to time of sunset are narrow and consistent in both total and seasonal plots. The start time of the transition shows some seasonal variation, with delayed transitions occurring mostly in the rainy and humid season of the northeast monsoon. Interestingly, in contrast to the general perception, the signature of the transition is first seen in the profiler data, then in the sodar data, and finally in the surface data. This suggests that the transition follows a top-to-bottom evolution. It indicates that other processes, like entrainment, could also play a role in altering the structure of the ABL during the AT, when the sensible heat flux decreases progressively. These mechanisms are quantified using a unique high-resolution data set to understand their variation in light of the intriguing height dependency of the start time of the AT.
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While previous research helped to identify and prioritize the sources of error in air-quality modeling due to anthropogenic emissions and spatial scale effects, our knowledge is limited on how these uncertainties affect climate-forced air-quality assessments. Using as reference a 10-year model simulation over the greater Paris (France) area at 4 km resolution and anthropogenic emissions from a 1 km resolution bottom-up inventory, through several tests we estimate the sensitivity of modeled ozone and PM<sub>2.5</sub> concentrations to different potentially influential factors with a particular interest over the urban areas. These factors include the model horizontal and vertical resolution, the meteorological input from a climate model and its resolution, the use of a top-down emission inventory, the resolution of the emissions input and the post-processing coefficients used to derive the temporal, vertical and chemical split of emissions. We show that urban ozone displays moderate sensitivity to the resolution of emissions (~ 8 %), the post-processing method (6.5 %) and the horizontal resolution of the air-quality model (~ 5 %), while annual PM<sub>2.5</sub> levels are particularly sensitive to changes in their primary emissions (~ 32 %) and the resolution of the emission inventory (~ 24 %). The air-quality model horizontal and vertical resolution have little effect on model predictions for the specific study domain. In the case of modeled ozone concentrations, the implementation of refined input data results in a consistent decrease (from 2.5 up to 8.3 %), mainly due to inhibition of the titration rate by nitrogen oxides. Such consistency is not observed for PM<sub>2.5</sub>. In contrast this consistency is not observed for PM<sub>2.5</sub>. In addition we use the results of these sensitivities to explain and quantify the discrepancy between a coarse (~ 50 km) and a fine (4 km) resolution simulation over the urban area. We show that the ozone bias of the coarse run (+9 ppb) is reduced by ~ 40 % by adopting a higher resolution emission inventory, by 25 % by using a post-processing technique based on the local inventory (same improvement is obtained by increasing model horizontal resolution) and by 10 % by adopting the annual emission totals of the local inventory. The bias of PM<sub>2.5</sub> concentrations follows a more complex pattern, with the positive values associated with the coarse run (+3.6 μg m<sup>−3</sup>), increasing or decreasing depending on the type of the refinement. We conclude that in the case of fine particles, the coarse simulation cannot selectively incorporate local-scale features in order to reduce its error.
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We estimate black carbon (BC) emissions in the western United States for July–September 2006 by inverting surface BC concentrations from the Interagency Monitoring of Protected Visual Environments (IMPROVE) network using a global chemical transport model (GEOS-Chem) and its adjoint. Our best estimate of the BC emissions is 49.9 Gg at 2° × 2.5° (a factor of 2.1 increase) and 47.3 Gg at 0.5° × 0.667° (1.9 times increase). Model results now capture the observed major fire episodes with substantial bias reductions (~ 35 % at 2° × 2.5° and ~ 15 % at 0.5° × 0.667°). The emissions are ~ 20–50 % larger than those from our earlier analytical inversions (Mao et al., 2014). The discrepancy is especially drastic in the partitioning of anthropogenic versus biomass burning emissions. The August biomass burning BC emissions are 4.6–6.5 Gg and anthropogenic BC emissions 8.6–12.8 Gg, varying with the model resolution, error specifications, and subsets of observations used. On average both anthropogenic and biomass burning emissions in the adjoint inversions increase 2-fold relative to the respective {a priori} emissions, in distinct contrast to the halving of the anthropogenic and tripling of the biomass burning emissions in the analytical inversions. We attribute these discrepancies to the inability of the adjoint inversion system, with limited spatiotemporal coverage of the IMPROVE observations, to effectively distinguish collocated anthropogenic and biomass burning emissions on model grid scales. This calls for concurrent measurements of other tracers of biomass burning and fossil fuel combustion (e.g., carbon monoxide and carbon isotopes). We find that the adjoint inversion system as is has sufficient information content to constrain the total emissions of BC on the model grid scales.
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This study analyzes in situ airborne measurements from the 2008 Stratosphere–Troposphere Analyses of Regional Transport (START08) experiment to characterize gravity waves in the extratropical upper troposphere and lower stratosphere (ExUTLS). The focus is on the second research flight (RF02), which took place on 21–22 April 2008. This was the first airborne mission dedicated to probing gravity waves associated with strong upper-tropospheric jet–front systems. Based on spectral and wavelet analyses of the in situ observations, along with a diagnosis of the polarization relationships, clear signals of mesoscale variations with wavelengths ~ 50–500 km are found in almost every segment of the 8 h flight, which took place mostly in the lower stratosphere. The aircraft sampled a wide range of background conditions including the region near the jet core, the jet exit and over the Rocky Mountains with clear evidence of vertically propagating gravity waves of along-track wavelength between 100 and 120 km. The power spectra of the horizontal velocity components and potential temperature for the scale approximately between ~ 8 and ~ 256 km display an approximate −5/3 power law in agreement with past studies on aircraft measurements, while the fluctuations roll over to a −3 power law for the scale approximately between ~ 0.5 and ~ 8 km (except when this part of the spectrum is activated, as recorded clearly by one of the flight segments). However, at least part of the high-frequency signals with sampled periods of ~ 20–~ 60 s and wavelengths of ~ 5–~ 15 km might be due to intrinsic observational errors in the aircraft measurements, even though the possibilities that these fluctuations may be due to other physical phenomena (e.g., nonlinear dynamics, shear instability and/or turbulence) cannot be completely ruled out.
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Detection of climate change requires a network of stable ground-based long-term measurements. Building upon earlier work, we first explore requirements of such measurements (such as maximum random uncertainty and sampling frequency) to ensure a minimum random uncertainty in monthly mean temperatures and to ensure effective detection of trends. In agreement with previous work we find that only for individual measurement random uncertainties > 0.2 K does the measurement random uncertainty start to contribute significantly to the random uncertainty in the monthly mean. For trend analysis, we find that the quality of the trend determination is only compromised when the measurement random uncertainty exceeds 2 K and measurements are made just once or twice a month. <br><br> In the second part of the study we provide guidance on how to most effectively design a measurement network. To this end we developed a method to objectively identify the optimal location of sites for detecting projected trends in upper-air temperatures and total column ozone in the shortest possible time. This is done by first estimating the spatial distribution of the minimum length of time during which measurements have to be made in order to detect projected trends in temperature and ozone. This quantity is calculated from the unforced variance in the signal and the degree of autocorrelation, both estimated from historical data sets and assumed not to change in the future, and the projected trends as estimated from chemistry–climate models. The optimal site locations are then selected by an iterative procedure based on the minimum time required to detect a trend and a minimal distance between different measurement sites. While the optimal sites identified here result from our use of only one of a wide range of objective strategies, these results provide additional incentives for initiating measurement programmes at these sites or, if already in operation, to continue to be supported.
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Long-term measurements of aerosol optical depths (AODs) at 440 nm and Ångström exponents (AE) between 440 and 870 nm made for CARSNET were compiled into a climatology of aerosol optical properties for China. Quality-assured monthly mean AODs are presented for 50 sites representing remote, rural, and urban areas. AODs were 0.14, 0.34, 0.42, 0.54, and 0.74 at remote stations, rural/desert regions, the Loess Plateau, central and eastern China, and urban sites, respectively, and the corresponding AE values were 0.97, 0.55, 0.82, 1.19, and 1.05. AODs increased from north to south, with low values (< 0.20) over the Tibetan Plateau and northwestern China and high AODs (> 0.60) in central and eastern China where industrial emissions and anthropogenic activities were likely sources. AODs were 0.20–0.40 in semi-arid and arid regions and some background areas in northern and northeastern China. AEs were > 1.20 over the southern reaches of the Yangtze River and at clean sites in northeastern China. In the northwestern deserts and industrial parts of northeast China, AEs were lower (< 0.80) compared with central and eastern regions. Dust events in spring, hygroscopic particle growth during summer, and biomass burning contribute the high AODs, especially in northern and eastern China. The AODs show decreasing trends from 2006 to 2009 but increased ~ 0.03 per year from 2009 to 2013.
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Atmospheric particulate matter (PM) was fractionated in six aerodynamic sizes, > 7.2, 7.2–3, 3–1.5, 1.5–1, 1–0.5 and < 0.5 μm, using a cascade impactor. These fractions were collected at urban and rural sites during warm and cold seasons. Organic tracer compounds, such as levoglucosan, isoprene, pinene oxidation products, polycyclic aromatic hydrocarbons and quinones, were analyzed by gas chromatography coupled with mass spectrometry. These analyses showed that the composition in the smallest size fractions (< 0.5 μm) was more uniform than in the larger sizes (7.2> PM > 0.5 μm). Thus, markers of photochemically synthesized organic compounds or combustion sources, either biomass burning or traffic emissions, were predominantly observed in the fraction < 0.5 μm, whereas the larger particles were composed of mixed sources from combustion processes, vegetation emissions, soil resuspension, road dust, urban lifestyle activities and photochemically synthesized organic compounds. <br><br> Important seasonal differences were observed at the rural site. In the < 0.5 μm fraction these were related to a strong predominance of biomass burning in the cold period and photochemically transformed biogenic organic compounds in the warm period. In the 7.2 > PM > 0.5 μm fractions the differences involved predominantly soil-sourced compounds in the warm period and mixed combustion sources, photochemical products and vegetation emissions in the cold. Multivariate curve resolution/alternating least squares showed that these organic aerosols essentially originated from six source components. Four of them reflected primary emissions related to either natural products, e.g., vegetation emissions and upwhirled soil dust, or anthropogenic contributions, e.g., combustion products and compounds related to urban lifestyle activities like vehicular exhaust and tobacco smoking. Two secondary organic aerosol components were identified. They accumulated in the smallest (< 0.5 μm) or in the larger fractions (> 0.5 μm) and involved strong or mild photochemical transformations of vegetation precursor molecules, respectively. Toxicologically relevant information was also disclosed with the present approach. Thus, the strong predominance of biomass burning residues at the rural site during the cold period involved atmospheric concentrations of polycyclic aromatic hydrocarbons that were 3 times higher than at the urban sites and benzo[a]pyrene concentrations above legal recommendations.
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Nearly all general circulation models significantly fail to reproduce the observed behaviour of the southern wintertime polar vortex. It has been suggested that these biases result from an underestimation of gravity wave drag on the atmosphere at latitudes near 60° S, especially around the "hot spot" of intense gravity wave fluxes above the mountainous Southern Andes and Antarctic peninsula. Here, we use Global Positioning System radio occultation (GPS-RO) data from the COSMIC satellite constellation to determine the properties of gravity waves in the hot spot and beyond. We show considerable southward propagation to latitudes near 60° S of waves apparently generated over the southern Andes. We propose that this propagation may account for much of the wave drag missing from the models. Furthermore, there is a long leeward region of increased gravity wave energy that sweeps eastwards from the mountains over the Southern Ocean. Despite its striking nature, the source of this region has historically proved difficult to determine. Our observations suggest that this region includes both waves generated locally and orographic waves advected downwind from the hot spot. We describe and use a new wavelet-based analysis technique for the quantitative identification of individual waves from COSMIC temperature profiles. This analysis reveals different geographical regimes of wave amplitude and short-timescale variability in the wave field over the Southern Ocean. Finally, we use the increased numbers of closely spaced pairs of profiles from the deployment phase of the COSMIC constellation in 2006 to make estimates of gravity wave horizontal wavelengths. We show that, given sufficient observations, GPS-RO can produce physically reasonable estimates of stratospheric gravity wave momentum flux in the hot spot that are consistent with measurements made by other techniques. We discuss our results in the context of previous satellite and modelling studies and explain how they advance our understanding of the nature and origins of waves in the southern stratosphere.
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Concentrations and fluxes of seven volatile organic compounds (VOCs) were measured between August and December 2012 at a rooftop site in central London as part of the ClearfLo project (Clean Air for London). VOC concentrations were quantified using a proton transfer reaction mass spectrometer (PTR-MS) and fluxes were calculated using a virtual disjunct eddy covariance technique. The median VOC fluxes, including aromatics, oxygenated compounds and isoprene, ranged from 0.07 to 0.33 mg m<sup>−2</sup> h<sup>−1</sup>. Median mixing ratios were 7.3 ppb for methanol and < 1 ppb for the other compounds. Strong relationships were observed between the fluxes and concentrations of some VOCs with traffic density and between the fluxes and concentrations of isoprene and oxygenated compounds with photosynthetically active radiation (PAR) and temperature. An estimated 50–90 % of the fluxes of aromatic VOCs were attributable to traffic activity, which showed little seasonal variation, suggesting that boundary layer effects or possibly advected pollution may be the primary causes of increased concentrations of aromatics in winter. Isoprene, methanol and acetaldehyde fluxes and concentrations in August and September showed high correlations with PAR and temperature, when fluxes and concentrations were largest suggesting that biogenic sources contributed to their fluxes. Modelled biogenic isoprene fluxes from urban vegetation using the Guenther et al. (1995) algorithm agreed well with measured fluxes in August and September. Comparisons of estimated annual benzene emissions from both the London and the National Atmospheric Emissions Inventories agreed well with measured benzene fluxes. Flux footprint analysis indicated emission sources were localised and that boundary layer dynamics and source strengths were responsible for temporal and spatial VOC flux and concentration variability during the measurement period.
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We measured a large suite of gas- and particle-phase multi-functional organic compounds with a Filter Inlet for Gases and AEROsols (FIGAERO) coupled to a high-resolution time-of-flight chemical ionization mass spectrometer (HR-ToF-CIMS) developed at the University of Washington. The instrument was deployed on environmental simulation chambers to study monoterpene oxidation as a secondary organic aerosol (SOA) source. We focus here on results from experiments utilizing an ionization method most selective towards acids (acetate negative ion proton transfer), but our conclusions are based on more general physical and chemical properties of the SOA. Hundreds of compounds were observed in both gas and particle phases, the latter being detected by temperature-programmed thermal desorption of collected particles. Particulate organic compounds detected by the FIGAERO–HR-ToF-CIMS are highly correlated with, and explain at least 25–50 % of, the organic aerosol mass measured by an Aerodyne aerosol mass spectrometer (AMS). Reproducible multi-modal structures in the thermograms for individual compounds of a given elemental composition reveal a significant SOA mass contribution from high molecular weight organics and/or oligomers (i.e., multi-phase accretion reaction products). Approximately 50 % of the HR-ToF-CIMS particle-phase mass is associated with compounds having effective vapor pressures 4 or more orders of magnitude lower than commonly measured monoterpene oxidation products. The relative importance of these accretion-type and other extremely low volatility products appears to vary with photochemical conditions. We present a desorption-temperature-based framework for apportionment of thermogram signals into volatility bins. The volatility-based apportionment greatly improves agreement between measured and modeled gas-particle partitioning for select major and minor components of the SOA, consistent with thermal decomposition during desorption causing the conversion of lower volatility components into the detected higher volatility compounds.
