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Current estimates of the terrestrial carbon fluxes in Asia show large uncertainties particularly in the boreal and mid-latitudes and in China. In this paper, we present an updated carbon flux estimate for Asia ("Asia" refers to lands as far west as the Urals and is divided into boreal Eurasia, temperate Eurasia and tropical Asia based on TransCom regions) by introducing aircraft CO<sub>2</sub> measurements from the CONTRAIL (Comprehensive Observation Network for Trace gases by Airline) program into an inversion modeling system based on the CarbonTracker framework. We estimated the averaged annual total Asian terrestrial land CO<sub>2</sub> sink was about −1.56 Pg C yr<sup>−1</sup> over the period 2006–2010, which offsets about one-third of the fossil fuel emission from Asia (+4.15 Pg C yr<sup>−1</sup>). The uncertainty of the terrestrial uptake estimate was derived from a set of sensitivity tests and ranged from −1.07 to −1.80 Pg C yr<sup>−1</sup>, comparable to the formal Gaussian error of ±1.18 Pg C yr<sup>−1</sup> (1-sigma). The largest sink was found in forests, predominantly in coniferous forests (−0.64 ± 0.70 Pg C yr<sup>−1</sup>) and mixed forests (−0.14 ± 0.27 Pg C yr<sup>−1</sup>); and the second and third large carbon sinks were found in grass/shrub lands and croplands, accounting for −0.44 ± 0.48 Pg C yr<sup>−1</sup> and −0.20 ± 0.48 Pg C yr<sup>−1</sup>, respectively. The carbon fluxes per ecosystem type have large a priori Gaussian uncertainties, and the reduction of uncertainty based on assimilation of sparse observations over Asia is modest (8.7–25.5%) for most individual ecosystems. The ecosystem flux adjustments follow the detailed a priori spatial patterns by design, which further increases the reliance on the a priori biosphere exchange model. The peak-to-peak amplitude of inter-annual variability (IAV) was 0.57 Pg C yr<sup>−1</sup> ranging from −1.71 Pg C yr<sup>−1</sup> to −2.28 Pg C yr<sup>−1</sup>. The IAV analysis reveals that the Asian CO<sub>2</sub> sink was sensitive to climate variations, with the lowest uptake in 2010 concurrent with a summer flood and autumn drought and the largest CO<sub>2</sub> sink in 2009 owing to favorable temperature and plentiful precipitation conditions. We also found the inclusion of the CONTRAIL data in the inversion modeling system reduced the uncertainty by 11% over the whole Asian region, with a large reduction in the southeast of boreal Eurasia, southeast of temperate Eurasia and most tropical Asian areas.
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The chemical and physical properties of secondary organic aerosol (SOA) formed by the photochemical degradation of biogenic and anthropogenic volatile organic compounds (VOC) are as yet still poorly constrained. The evolution of the complex refractive index (RI) of SOA, formed from purely biogenic VOC and mixtures of biogenic and anthropogenic VOC, was studied over a diurnal cycle in the SAPHIR photochemical outdoor chamber in Jülich, Germany. The correlation of RI with SOA chemical and physical properties such as oxidation level and volatility was examined. The RI was retrieved by a newly developed broadband cavity-enhanced spectrometer for aerosol optical extinction measurements in the UV spectral region (360 to 420 nm). Chemical composition and volatility of the particles were monitored by a high-resolution time-of-flight aerosol mass spectrometer, and a volatility tandem differential mobility analyzer. SOA was formed by ozonolysis of either (i) a mixture of biogenic VOC (α-pinene and limonene), (ii) biogenic VOC mixture with subsequent addition of an anthropogenic VOC (<i>p</i>-xylene-d<sub>10</sub>), or (iii) a mixture of biogenic and anthropogenic VOC. The SOA aged by ozone/OH reactions up to 29.5 h was found to be non-absorbing in all cases. The SOA with <i>p</i>-xylene-d<sub>10</sub> showed an increase of the scattering component of the RI correlated with an increase of the O / C ratio and with an increase in the SOA density. There was a greater increase in the scattering component of the RI when the SOA was produced from the mixture of biogenic VOCs and anthropogenic VOC than from the sequential addition of the VOCs after approximately the same ageing time. The increase of the scattering component was inversely correlated with the SOA volatility. Two RI retrievals determined for the pure biogenic SOA showed a constant RI for up to 5 h of ageing. Mass spectral characterization shows the three types of the SOA formed in this study have a significant amount of semivolatile components. The influence of anthropogenic VOCs on the oxygenated organic aerosol as well as the atmospheric implications are discussed.
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We use secondary organic aerosol (SOA) production data from an ensemble of unburned fuels measured in a smog chamber to test various SOA formation models. The evaluation considered data from 11 different fuels including gasoline, multiple diesels, and various jet fuels. The fuels are complex mixtures of species; they span a wide range of volatility and molecular structure to provide a challenging test for the SOA models. We evaluated three different versions of the SOA model used in the Community Multiscale Air Quality (CMAQ) model. The simplest and most widely used version of that model only accounts for the volatile species (species with less than or equal to 12 carbons) in the fuels. It had very little skill in predicting the observed SOA formation (<i>R</i><sup>2</sup> = 0.04, fractional error = 108%). Incorporating all of the lower-volatility fuel species (species with more than 12 carbons) into the standard CMAQ SOA model did not improve model performance significantly. Both versions of the CMAQ SOA model over-predicted SOA formation from a synthetic jet fuel and under-predicted SOA formation from diesels because of an overly simplistic representation of the SOA formation from alkanes that did not account for the effects of molecular size and structure. An extended version of the CMAQ SOA model that accounted for all organics and the influence of molecular size and structure of alkanes reproduced the experimental data. This underscores the importance of accounting for all low-volatility organics and information on alkane molecular size and structure in SOA models. We also investigated fitting an SOA model based solely on the volatility of the precursor mixture to the experimental data. This model could describe the observed SOA formation with relatively few free parameters, demonstrating the importance of precursor volatility for SOA formation. The exceptions were exotic fuels such as synthetic jet fuel that expose the central assumption of the volatility-dependent model that most emissions consist of complex mixtures with similar distribution of molecular classes. Despite its shortcomings, SOA formation as a function of volatility may be sufficient for modeling SOA formation in chemical transport models.
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We use the NASA Goddard Earth Observing System (GEOS) Chemistry Climate Model (GEOSCCM) to quantify the contribution of the two most important brominated very short lived substances (VSLSs), bromoform (CHBr<sub>3</sub>) and dibromomethane (CH<sub>2</sub>Br<sub>2</sub>), to stratospheric bromine and its sensitivity to convection strength. Model simulations suggest that the most active transport of VSLSs from the marine boundary layer through the tropopause occurs over the tropical Indian Ocean, the tropical western Pacific, and off the Pacific coast of Mexico. Together, convective lofting of CHBr<sub>3</sub> and CH<sub>2</sub>Br<sub>2</sub> and their degradation products supplies ~8 ppt total bromine to the base of the tropical tropopause layer (TTL, ~150 hPa), similar to the amount of VSLS organic bromine available in the marine boundary layer (~7.8–8.4 ppt) in the active convective lofting regions mentioned above. Of the total ~8 ppt VSLS bromine that enters the base of the TTL at ~150 hPa, half is in the form of organic source gases and half in the form of inorganic product gases. Only a small portion (<10%) of the VSLS-originated bromine is removed via wet scavenging in the TTL before reaching the lower stratosphere. On average, globally, CHBr<sub>3</sub> and CH<sub>2</sub>Br<sub>2</sub> together contribute ~7.7 pptv to the present-day inorganic bromine in the stratosphere. However, varying model deep-convection strength between maximum (strongest) and minimum (weakest) convection conditions can introduce a ~2.6 pptv uncertainty in the contribution of VSLSs to inorganic bromine in the stratosphere (Br<sub>y</sub><sup>VSLS</sup>). Contrary to conventional wisdom, the minimum convection condition leads to a larger Br<sub>y</sub><sup>VSLS</sup> as the reduced scavenging in soluble product gases, and thus a significant increase in product gas injection (2–3 ppt), greatly exceeds the relatively minor decrease in source gas injection (a few 10ths ppt).
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While the field of atmospheric organic aerosol scientific research has experienced thorough and insightful progress over the last half century, this progress has been accompanied by the evolution of a communicative and detailed yet, at times, complex and inconsistent language. The menagerie of detailed classification that now exists to describe organic compounds in our atmosphere reflects the wealth of observational techniques now at our disposal as well as the rich information provided by state-of-the-science instrumentation. However, the nomenclature in place to communicate these scientific gains is growing disjointed to the point that effective communication within the scientific community and to the public may be sacrificed. We propose standardizing a naming convention for organic aerosol classification that is relevant to laboratory studies, ambient observations, atmospheric models, and various stakeholders for air-quality problems. Because a critical aspect of this effort is to directly translate the essence of complex physico-chemical phenomena to a much broader, policy-oriented audience, we recommend a framework that maximizes comprehension among scientists and non-scientists alike. For example, to classify volatility, it relies on straightforward alphabetic terms (e.g., semivolatile, SV; intermediate volatility, IV; etc.) rather than possibly ambiguous numeric indices. This framework classifies organic material as primary or secondary pollutants and distinguishes among fundamental features important for science and policy questions including emission source, chemical phase, and volatility. Also useful is the addition of an alphabetic suffix identifying the volatility of the organic material or its precursor for when emission occurred. With this framework, we hope to introduce into the community a consistent connection between common notation for the general public and detailed nomenclature for highly specialized discussion. In so doing, we try to maintain consistency with historical, familiar naming schemes, unify much of the scattered nomenclature presented in recent literature, reduce the barrier of comprehension to outside audiences, and construct a scaffold into which insights from future scientific discoveries can be incorporated.
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Reactive iodine compounds play a significant role in the atmospheric chemistry of the oceanic boundary layer by influencing the oxidising capacity through catalytically removing O<sub>3</sub> and altering the HO<sub>x</sub> and NO<sub>x</sub> balance. The sea-to-air flux of iodine over the open ocean is therefore an important quantity in assessing these impacts on a global scale. This paper examines the effect of a number of relevant environmental parameters, including water temperature, salinity and organic compounds, on the magnitude of the HOI and I<sub>2</sub> fluxes produced from the uptake of O<sub>3</sub> and its reaction with iodide ions in aqueous solution. The results of these laboratory experiments and those reported previously (Carpenter et al., 2013), along with sea surface iodide concentrations measured or inferred from measurements of dissolved total iodine and iodate reported in the literature, were then used to produce parameterised expressions for the HOI and I<sub>2</sub> fluxes as a function of wind speed, sea-surface temperature and O<sub>3</sub>. These expressions were used in the Tropospheric HAlogen chemistry MOdel (THAMO) to compare with MAX-DOAS measurements of iodine monoxide (IO) performed during the HaloCAST-P cruise in the eastern Pacific ocean (Mahajan et al., 2012). The modelled IO agrees reasonably with the field observations, although significant discrepancies are found during a period of low wind speeds (< 3 m s<sup>−1</sup>), when the model overpredicts IO by up to a factor of 3. The inorganic iodine flux contributions to IO are found to be comparable to, or even greater than, the contribution of organo-iodine compounds and therefore its inclusion in atmospheric models is important to improve predictions of the influence of halogen chemistry in the marine boundary layer.
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Global warming is associated with large increases in surface air temperature in Siberia. Here, we apply the isotope-enabled atmospheric general circulation model ECHAM5-wiso to explore the potential of water isotope measurements at a recently opened monitoring station in Kourovka (57.04° N, 59.55° E) in order to successfully trace climate change in western Siberia. Our model is constrained to atmospheric reanalysis fields for the period 1957–2013 to facilitate the comparison with observations of δD in total column water vapour from the GOSAT satellite, and with precipitation δ<sup>18</sup>O measurements from 15 Russian stations of the Global Network of Isotopes in Precipitation. The model captures the observed Russian climate within reasonable error margins, and displays the observed isotopic gradients associated with increasing continentality and decreasing meridional temperatures. The model also reproduces the observed seasonal cycle of δ<sup>18</sup>O, which parallels the seasonal cycle of temperature and ranges from −25 ‰ in winter to −5 ‰ in summer. Investigating West Siberian climate and precipitation δ<sup>18</sup>O variability during the last 50 years, we find long-term increasing trends in temperature and δ<sup>18</sup>O, while precipitation trends are uncertain. During the last 50 years, winter temperatures have increased by 1.7 °C. The simulated long-term increase of precipitation δ<sup>18</sup>O is at the detection limit (<1 ‰ per 50 years) but significant. West Siberian climate is characterized by strong interannual variability, which in winter is strongly related to the North Atlantic Oscillation. In winter, regional temperature is the predominant factor controlling δ<sup>18</sup>O variations on interannual to decadal timescales with a slope of about 0.5 ‰ °C<sup>−1</sup>. In summer, the interannual variability of δ<sup>18</sup>O can be attributed to short-term, regional-scale processes such as evaporation and convective precipitation. This finding suggests that precipitation δ<sup>18</sup>O has the potential to reveal hydrometeorological regime shifts in western Siberia which are otherwise difficult to identify. Focusing on Kourovka, the simulated evolution of temperature, δ<sup>18</sup>O and, to a smaller extent, precipitation during the last 50 years is synchronous with model results averaged over all of western Siberia, suggesting that this site will be representative to monitor future isotopic changes in the entire region.
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Belgium is one of the areas within Europe experiencing the highest levels of air pollution. A high-resolution (3 km) modelling experiment is employed to provide guidance to policymakers about expected air quality changes in the near future (2026–2035). The regional air quality model AURORA (Air quality modelling in Urban Regions using an Optimal Resolution Approach), driven by output from a regional climate model, is used to simulate several 10-year time slices to investigate the impact of climatic changes and different emission scenarios on near-surface O<sub>3</sub> concentrations, one of the key indices for air quality. Evaluation of the model against measurements from 34 observation stations shows that the AURORA model is capable of reproducing 10-year mean concentrations, daily cycles and spatial patterns. The results for the Representative Concentration Pathways (RCP)4.5 emission scenario indicate that the mean surface O<sub>3</sub> concentrations are expected to increase significantly in the near future due to less O<sub>3</sub> titration by reduced NO<sub>x</sub> emissions. Applying an alternative emission scenario for Europe is found to have only a minor impact on the overall concentrations, which are dominated by the background changes. Climate change alone has a much smaller effect on the near-surface O<sub>3</sub> concentrations over Belgium than the projected emission changes. The very high horizontal resolution that is used in this study results in much improved spatial correlations and simulated peak concentrations compared to a standard 25 km simulation. An analysis of the number of peak episodes during summer revealed that the emission reductions in RCP4.5 result in a 25% decrease of these peak episodes.
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The ground-based radiometer GROMOS, stationed in Bern (47.95° N, 7.44° E), Switzerland, has a unique data set: it obtains ozone profiles from November 1994 to present with a time resolution of 30 min and equivalent quality during night- and daytime. Here, we derive a monthly climatology of the daily ozone cycle from 17 years of GROMOS observation. We present the diurnal ozone variation of the stratosphere and mesosphere. Characterizing the diurnal cycle of stratospheric ozone is important for correct trend estimates of the ozone layer derived from satellite observations. The diurnal ozone cycle from GROMOS is compared to two models: the Whole Atmosphere Community Climate Model (WACCM) and the Hamburg Model of Neutral and Ionized Atmosphere (HAMMONIA). Generally, observation and models show a good agreement: in the lower mesosphere, daytime ozone is for both GROMOS and models around 25% less than midnight ozone. In the stratosphere, ozone reaches its maximum in the afternoon showing values several percent larger than the midnight value. Further, GROMOS and models indicate a seasonal behaviour of the diurnal ozone variations in the stratosphere with a larger afternoon maximum during daytime in summer than in winter. Using the 17 years of ozone profiles from GROMOS, we find strong interannual variations in the diurnal ozone cycle for both the stratosphere and the mesosphere. Interannual variability in temperature, atmospheric circulation and composition may explain the observed interannual variability of the diurnal ozone cycle above Bern.
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Understanding the sources of volatile organic compounds (VOCs) is essential for ground-level ozone and secondary organic aerosol (SOA) abatement measures. We made VOC measurements at 27 sites and online observations at an urban site in Beijing from July 2009 to January 2012. Based on these measurement data, we determined the spatial and temporal distribution of VOCs, estimated their annual emission strengths based on their emission ratios relative to carbon monoxide (CO), and quantified the relative contributions of various sources using the chemical mass balance (CMB) model. These results from ambient measurements were compared with existing emission inventories to evaluate the spatial distribution, species-specific emissions, and source structure of VOCs in Beijing. The measured VOC distributions revealed a hotspot in the southern suburban area of Beijing, whereas current emission inventories suggested that VOC emissions were concentrated in downtown areas. Compared with results derived from ambient measurements, the annual inventoried emissions of oxygenated VOC (OVOC) species and C2–C4 alkanes may be underestimated, while the emissions of styrene and 1,3-butadiene may be overestimated by current inventories. Source apportionment using the CMB model identified vehicular exhaust as the most important VOC source, with the relative contribution of 49%, in good agreement with the 40–51% estimated by emission inventories. The relative contribution of paint and solvent utilization obtained from the CMB model was 14%, significantly lower than the value of 32% reported by one existing inventory. Meanwhile, the relative contribution of liquefied petroleum gas (LPG) usage calculated using the CMB model was 6%, whereas LPG usage contribution was not reported by current emission inventories. These results suggested that VOC emission strengths in southern suburban area of Beijing, annual emissions of C2–C4 alkanes, OVOCs and some alkenes, and the contributions of solvent and paint utilization and LPG usage in current inventories all require significant revisions.
