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Observed variations of the atmospheric greenhouse gas methane (CH<sub>4</sub>) over the past two decades remain the subject of debate. These variations reflect changes in emission, uptake, and atmospheric chemistry and transport. We isolate changes in the seasonal cycle of atmospheric CH<sub>4</sub> using a wavelet transform. We report a previously undocumented persistent decrease in the peak-to-peak amplitude of the seasonal cycle of atmospheric CH<sub>4</sub> at six out of seven high northern latitude sites over the past two to three decades. The observed amplitude changes are statistically significant for sites at Barrow, Alaska and Ocean Station M, Norway, which we find are the most sensitive of our sites to high northern latitude wetland emissions. We find using a series of numerical experiments using the TM5 atmospheric chemistry transport model that increasing wetland emissions and/or decreasing fossil fuel emissions can explain these observed changes, but no significant role for trends in meteorology and tropical wetlands. We also find no evidence in past studies to support a significant role for variations in the hydroxyl radical sink of atmospheric CH<sub>4</sub>. Using the TM5 model we find that changes in fossil fuel emissions of CH<sub>4</sub>, described by a conservative state-of-the-science bottom-up emission inventory, are not sufficient to reconcile observed changes in atmospheric CH<sub>4</sub> at these sites. The remainder of the observed trend in amplitude, by process of elimination, must be due to an increase in high northern latitude wetland emissions, corresponding to an annual increase of at least 0.7 %/yr (equivalent to 5 Tg CH<sub>4</sub>/yr over 30 years).
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This paper studies the seasonal variation of surface and column CO at three different sites (Paris, Jungfraujoch and Wollongong), with an emphasis on establishing a link between the CO vertical distribution and the nature of CO emission sources. We find the first evidence of a time lag between surface and free tropospheric CO seasonal variations in the Northern Hemisphere. The CO seasonal variability obtained from the total columns and free tropospheric partial columns shows a maximum around March–April and a minimum around September–October in the Northern Hemisphere (Paris and Jungfraujoch). In the Southern Hemisphere (Wollongong) this seasonal variability is shifted by about 6 months. Satellite observations by the IASI–MetOp (Infrared Atmospheric Sounding Interferometer) and MOPITT (Measurements Of Pollution In The Troposphere) instruments confirm this seasonality. Ground-based FTIR (Fourier transform infrared) measurements provide useful complementary information due to good sensitivity in the boundary layer. In situ surface measurements of CO volume mixing ratios at the Paris and Jungfraujoch sites reveal a time lag of the near-surface seasonal variability of about 2 months with respect to the total column variability at the same sites. The chemical transport model GEOS-Chem (Goddard Earth Observing System chemical transport model) is employed to interpret our observations. GEOS-Chem sensitivity runs identify the emission sources influencing the seasonal variation of CO. At both Paris and Jungfraujoch, the surface seasonality is mainly driven by anthropogenic emissions, while the total column seasonality is also controlled by air masses transported from distant sources. At Wollongong, where the CO seasonality is mainly affected by biomass burning, no time shift is observed between surface measurements and total column data.
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In this study a novel framework for inverse modelling of cloud condensation nuclei (CCN) spectra is developed using Köhler theory. The framework is established by using model-generated synthetic measurements as calibration data for a parametric sensitivity analysis. Assessment of the relative importance of aerosol physicochemical parameters, while accounting for bulk–surface partitioning of surface-active organic species, is carried out over a range of atmospherically relevant supersaturations. By introducing an objective function that provides a scalar metric for diagnosing the deviation of modelled CCN concentrations from synthetic observations, objective function response surfaces are presented as a function of model input parameters. Crucially, for the chosen calibration data, aerosol–CCN spectrum closure is confirmed as a well-posed inverse modelling exercise for a subset of the parameters explored herein. The response surface analysis indicates that the appointment of appropriate calibration data is particularly important. To perform an inverse aerosol–CCN closure analysis and constrain parametric uncertainties, it is shown that a high-resolution CCN spectrum definition of the calibration data is required where single-valued definitions may be expected to fail.<br><br> Using Köhler theory to model CCN concentrations requires knowledge of many physicochemical parameters, some of which are difficult to measure in situ on the scale of interest and introduce a considerable amount of parametric uncertainty to model predictions. For all partitioning schemes and environments modelled, model output showed significant sensitivity to perturbations in aerosol log-normal parameters describing the accumulation mode, surface tension, organic : inorganic mass ratio, insoluble fraction, and solution ideality. Many response surfaces pertaining to these parameters contain well-defined minima and are therefore good candidates for calibration using a Monte Carlo Markov Chain (MCMC) approach to constraining parametric uncertainties.<br><br>A complete treatment of bulk–surface partitioning is shown to predict CCN spectra similar to those calculated using classical Köhler theory with the surface tension of a pure water drop, as found in previous studies. In addition, model sensitivity to perturbations in the partitioning parameters was found to be negligible. As a result, this study supports previously held recommendations that complex surfactant effects might be neglected, and the continued use of classical Köhler theory in global climate models (GCMs) is recommended to avoid an additional computational burden. The framework developed is suitable for application to many additional composition-dependent processes that might impact CCN activation potential. However, the focus of this study is to demonstrate the efficacy of the applied sensitivity analysis to identify important parameters in those processes and will be extended to facilitate a global sensitivity analysis and inverse aerosol–CCN closure analysis.
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Measurements of atmospheric peroxides were made during Wangdu Campaign 2014 at Wangdu, a rural site in the North China Plain (NCP) in summer 2014. The predominant peroxides were detected to be hydrogen peroxide (H<sub>2</sub>O<sub>2</sub>), methyl hydroperoxide (MHP) and peroxyacetic acid (PAA). The observed H<sub>2</sub>O<sub>2</sub> reached up to 11.3 ppbv, which was the highest value compared with previous observations in China at summer time. A box model simulation based on the Master Chemical Mechanism and constrained by the simultaneous observations of physical parameters and chemical species was performed to explore the chemical budget of atmospheric peroxides. Photochemical oxidation of alkenes was found to be the major secondary formation pathway of atmospheric peroxides, while contributions from alkanes and aromatics were of minor importance. The comparison of modeled and measured peroxide concentrations revealed an underestimation during biomass burning events and an overestimation on haze days, which were ascribed to the direct production of peroxides from biomass burning and the heterogeneous uptake of peroxides by aerosols, respectively. The strengths of the primary emissions from biomass burning were on the same order of the known secondary production rates of atmospheric peroxides during the biomass burning events. The heterogeneous process on aerosol particles was suggested to be the predominant sink for atmospheric peroxides. The atmospheric lifetime of peroxides on haze days in summer in the NCP was about 2–3 h, which is in good agreement with the laboratory studies. Further comprehensive investigations are necessary to better understand the impact of biomass burning and heterogeneous uptake on the concentration of peroxides in the atmosphere.
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We report the formation of aliphatic organosulfates (OSs) in secondary organic aerosol (SOA) from the photooxidation of C<sub>10</sub>–C<sub>12</sub> alkanes. The results complement those from our laboratories reporting the formation of OSs and sulfonates from gas-phase oxidation of polycyclic aromatic hydrocarbons (PAHs). Both studies strongly support the formation of OSs from the gas-phase oxidation of anthropogenic precursors, as hypothesized on the basis of recent field studies in which aromatic and aliphatic OSs were detected in fine aerosol collected from several major urban locations. In this study, dodecane, cyclodecane and decalin, considered to be important SOA precursors in urban areas, were photochemically oxidized in an outdoor smog chamber in the presence of either non-acidified or acidified ammonium sulfate seed aerosol. Effects of acidity and relative humidity on OS formation were examined. Aerosols collected from all experiments were characterized by ultra performance liquid chromatography coupled to electrospray ionization high-resolution quadrupole time-of-flight mass spectrometry (UPLC/ESI-HR-QTOFMS). Most of the OSs identified could be explained by formation of gaseous epoxide precursors with subsequent acid-catalyzed reactive uptake onto sulfate aerosol and/or heterogeneous reactions of hydroperoxides. The OSs identified here were also observed and quantified in fine urban aerosol samples collected in Lahore, Pakistan, and Pasadena, CA, USA. Several OSs identified from the photooxidation of decalin and cyclodecane are isobars of known monoterpene organosulfates, and thus care must be taken in the analysis of alkane-derived organosulfates in urban aerosol.
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Methyl ethyl ketone (MEK) enters the atmosphere following direct emission from vegetation and anthropogenic activities, as well as being produced by the gas-phase oxidation of volatile organic compounds (VOCs) such as <i>n</i>-butane. This study presents the first overview of ambient MEK measurements at six different locations, characteristic of forested, urban and marine environments. In order to understand better the occurrence and behaviour of MEK in the atmosphere, we analyse diel cycles of MEK mixing ratios, vertical profiles, ecosystem flux data, and HYSPLIT back trajectories, and compare with co-measured VOCs. MEK measurements were primarily conducted with proton-transfer-reaction mass spectrometer (PTR-MS) instruments. Results from the sites under biogenic influence demonstrate that vegetation is an important source of MEK. The diel cycle of MEK follows that of ambient temperature and the forest structure plays an important role in air mixing. At such sites, a high correlation of MEK with acetone was observed (e.g. <i>r</i><sup>2</sup> = 0.96 for the SMEAR Estonia site in a remote hemiboreal forest in Tartumaa, Estonia, and <i>r</i><sup>2</sup> = 0.89 at the ATTO pristine tropical rainforest site in central Amazonia). Under polluted conditions, we observed strongly enhanced MEK mixing ratios. Overall, the MEK mixing ratios and flux data presented here indicate that both biogenic and anthropogenic sources contribute to its occurrence in the global atmosphere.
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The Nepal Ambient Monitoring and Source Testing Experiment (NAMaSTE) campaign took place in and around the Kathmandu Valley and in the Indo-Gangetic Plain (IGP) of southern Nepal during April 2015. The source characterization phase targeted numerous important but undersampled (and often inefficient) combustion sources that are widespread in the developing world such as cooking with a variety of stoves and solid fuels, brick kilns, open burning of municipal solid waste (a.k.a. trash or garbage burning), crop residue burning, generators, irrigation pumps, and motorcycles. NAMaSTE produced the first, or rare, measurements of aerosol optical properties, aerosol mass, and detailed trace gas chemistry for the emissions from many of the sources. This paper reports the trace gas and aerosol measurements obtained by Fourier transform infrared (FTIR) spectroscopy, whole-air sampling (WAS), and photoacoustic extinctiometers (PAX; 405 and 870 nm) based on field work with a moveable lab sampling authentic sources. The primary aerosol optical properties reported include emission factors (EFs) for scattering and absorption coefficients (EF <i>B</i><sub>scat</sub>, EF <i>B</i><sub>abs</sub>, in m<sup>2</sup> kg<sup>−1</sup> fuel burned), single scattering albedos (SSAs), and absorption Ångström exponents (AAEs). From these data we estimate black and brown carbon (BC, BrC) emission factors (g kg<sup>−1</sup> fuel burned). The trace gas measurements provide EFs (g kg<sup>−1</sup>) for CO<sub>2</sub>, CO, CH<sub>4</sub>, selected non-methane hydrocarbons up to C<sub>10</sub>, a large suite of oxygenated organic compounds, NH<sub>3</sub>, HCN, NO<sub><i>x</i></sub>, SO<sub>2</sub>, HCl, HF, etc. (up to ∼ 80 gases in all). <br><br> The emissions varied significantly by source, and light absorption by both BrC and BC was important for many sources. The AAE for dung-fuel cooking fires (4.63 ± 0.68) was significantly higher than for wood-fuel cooking fires (3.01 ± 0.10). Dung-fuel cooking fires also emitted high levels of NH<sub>3</sub> (3.00 ± 1.33 g kg<sup>−1</sup>), organic acids (7.66 ± 6.90 g kg<sup>−1</sup>), and HCN (2.01 ± 1.25 g kg<sup>−1</sup>), where the latter could contribute to satellite observations of high levels of HCN in the lower stratosphere above the Asian monsoon. HCN was also emitted in significant quantities by several non-biomass burning sources. BTEX compounds (benzene, toluene, ethylbenzene, xylenes) were major emissions from both dung- (∼ 4.5 g kg<sup>−1</sup>) and wood-fuel (∼ 1.5 g kg<sup>−1</sup>) cooking fires, and a simple method to estimate indoor exposure to the many measured important air toxics is described. Biogas emerged as the cleanest cooking technology of approximately a dozen stove–fuel combinations measured. Crop residue burning produced relatively high emissions of oxygenated organic compounds (∼ 12 g kg<sup>−1</sup>) and SO<sub>2</sub> (2.54 ± 1.09 g kg<sup>−1</sup>). Two brick kilns co-firing different amounts of biomass with coal as the primary fuel produced contrasting results. A zigzag kiln burning mostly coal at high efficiency produced larger amounts of BC, HF, HCl, and NO<sub><i>x</i></sub>, with the halogenated emissions likely coming from the clay. The clamp kiln (with relatively more biomass fuel) produced much greater quantities of most individual organic gases, about twice as much BrC, and significantly more known and likely organic aerosol precursors. Both kilns were significant SO<sub>2</sub> sources with their emission factors averaging 12.8 ± 0.2 g kg<sup>−1</sup>. Mixed-garbage burning produced significantly more BC (3.3 ± 3.88 g kg<sup>−1</sup>) and BTEX (∼ 4.5 g kg<sup>−1</sup>) emissions than in previous measurements. For all fossil fuel sources, diesel burned more efficiently than gasoline but produced larger NO<sub><i>x</i></sub> and aerosol emission factors. Among the least efficient sources sampled were gasoline-fueled motorcycles during start-up and idling for which the CO EF was on the order of ∼ 700 g kg<sup>−1</sup> – or about 10 times that of a typical biomass fire. Minor motorcycle servicing led to minimal if any reduction in gaseous pollutants but reduced particulate emissions, as detailed in a companion paper (Jayarathne et al., 2016). A small gasoline-powered generator and an “insect repellent fire” were also among the sources with the highest emission factors for pollutants. These measurements begin to address the critical data gap for these important, undersampled sources, but due to their diversity and abundance, more work is needed.
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We use the GLOMAP global aerosol model evaluated against observations of surface particulate matter (PM<sub>2.5</sub>) and aerosol optical depth (AOD) to better understand the impacts of biomass burning on tropical aerosol over the period 2003 to 2011. Previous studies report a large underestimation of AOD over regions impacted by tropical biomass burning, scaling particulate emissions from fire by up to a factor of 6 to enable the models to simulate observed AOD. To explore the uncertainty in emissions we use three satellite-derived fire emission datasets (GFED3, GFAS1 and FINN1). In these datasets the tropics account for 66–84 % of global particulate emissions from fire. With all emission datasets GLOMAP underestimates dry season PM<sub>2.5</sub> concentrations in regions of high fire activity in South America and underestimates AOD over South America, Africa and Southeast Asia. When we assume an upper estimate of aerosol hygroscopicity, underestimation of AOD over tropical regions impacted by biomass burning is reduced relative to previous studies. Where coincident observations of surface PM<sub>2.5</sub> and AOD are available we find a greater model underestimation of AOD than PM<sub>2.5</sub>, even when we assume an upper estimate of aerosol hygroscopicity. Increasing particulate emissions to improve simulation of AOD can therefore lead to overestimation of surface PM<sub>2.5</sub> concentrations. We find that scaling FINN1 emissions by a factor of 1.5 prevents underestimation of AOD and surface PM<sub>2.5</sub> in most tropical locations except Africa. GFAS1 requires emission scaling factor of 3.4 in most locations with the exception of equatorial Asia where a scaling factor of 1.5 is adequate. Scaling GFED3 emissions by a factor of 1.5 is sufficient in active deforestation regions of South America and equatorial Asia, but a larger scaling factor is required elsewhere. The model with GFED3 emissions poorly simulates observed seasonal variability in surface PM<sub>2.5</sub> and AOD in regions where small fires dominate, providing independent evidence that GFED3 underestimates particulate emissions from small fires. Seasonal variability in both PM<sub>2.5</sub> and AOD is better simulated by the model using FINN1 emissions. Detailed observations of aerosol properties over biomass burning regions are required to better constrain particulate emissions from fires.
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A dataset of 54 daily Italian downward surface solar radiation (SSR) records has been set up collecting data for the 1959–2013 period. Special emphasis is given to the quality control and the homogenization of the records in order to ensure the reliability of the resulting trends. This step has been shown as necessary due to the large differences obtained between the raw and homogenized dataset, especially during the first decades of the study period. In addition, SSR series under clear-sky conditions were obtained considering only the cloudless days from corresponding ground-based cloudiness observations. Subsequently, records were interpolated onto a regular grid and clustered into two regions, northern and southern Italy, which were averaged in order to get all-sky and clear-sky regional SSR records. Their temporal evolution is presented, and possible reasons for differences between all-sky and clear-sky conditions and between the two regions are discussed in order to determine to what extent SSR variability depends on aerosols or clouds. Specifically, the all-sky SSR records show a decrease until the mid-1980s (dimming period), and a following increase until the end of the series (brightening period) even though strength and persistence of tendencies are not the same in all seasons. Clear-sky records present stronger tendencies than all-sky records during the dimming period in all seasons and during the brightening period in winter and autumn. This suggests that, under all-sky conditions, the variations caused by the increase/decrease in the aerosol content have been partially masked by cloud cover variations, especially during the dimming period. Under clear sky the observed dimming is stronger in the south than in the north. This peculiarity could be a consequence of a significant contribution of mineral dust variations to the SSR variability.
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Mercury (Hg) emission from natural surfaces plays an important role in global Hg cycling. The present estimate of global natural emission has large uncertainty and remains unverified against field data, particularly for terrestrial surfaces. In this study, a mechanistic model is developed for estimating the emission of elemental mercury vapor (Hg<sup>0</sup>) from natural surfaces in China. The development implements recent advancements in the understanding of air–soil and air–foliage exchange of Hg<sup>0</sup> and redox chemistry in soil and on surfaces, incorporates the effects of soil characteristics and land use changes by agricultural activities, and is examined through a systematic set of sensitivity simulations. Using the model, the net exchange of Hg<sup>0</sup> between the atmosphere and natural surfaces of mainland China is estimated to be 465.1 Mg yr<sup>−1</sup>, including 565.5 Mg yr<sup>−1</sup> from soil surfaces, 9.0 Mg yr<sup>−1</sup> from water bodies, and −100.4 Mg yr<sup>−1</sup> from vegetation. The air–surface exchange is strongly dependent on the land use and meteorology, with 9 % of net emission from forest ecosystems; 50 % from shrubland, savanna, and grassland; 33 % from cropland; and 8 % from other land uses. Given the large agricultural land area in China, farming activities play an important role on the air–surface exchange over farmland. Particularly, rice field shift from a net sink (3.3 Mg uptake) during April–October (rice planting) to a net source when the farmland is not flooded (November–March). Summing up the emission from each land use, more than half of the total emission occurs in summer (51 %), followed by spring (28 %), autumn (13 %), and winter (8 %). Model verification is accomplished using observational data of air–soil/air–water fluxes and Hg deposition through litterfall for forest ecosystems in China and Monte Carlo simulations. In contrast to the earlier estimate by Shetty et al. (2008) that reported large emission from vegetative surfaces using an evapotranspiration approach, the estimate in this study shows natural emissions are primarily from grassland and dry cropland. Such an emission pattern may alter the current understanding of Hg emission outflow from China as reported by Lin et al. (2010b) because a substantial natural Hg emission occurs in West China.