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Emission factors of SO<sub>2</sub>, NO<sub><i>x</i></sub> and size-distributed particle numbers were measured for approximately 300 different ships in the Gulf of Finland and Neva Bay area during two campaigns in August/September 2011 and June/July 2012. The measurements were carried out from a harbor vessel and from an Mi-8 helicopter downwind of passing ships. Other measurements were carried out from shore sites near the island of Kronstadt and along the Neva River in the urban area of Saint Petersburg. Most ships were running at reduced speed (10 kn), i.e., not at their optimal load. Vessels for domestic and international shipping were monitored. It was seen that the distribution of the SO<sub>2</sub> emission factors is bi-modal, with averages of 4.6 and 18.2 g<sub>SO<sub>2</sub></sub> kg<sub>fuel</sub><sup>-1</sup> for the lower and the higher mode, respectively. The emission factors show compliance with the 1% fuel sulfur content Sulfur Emission Control Areas (SECA) limit for 90% of the vessels in 2011 and 97% in 2012. The distribution of the NO<sub><i>x</i></sub> emission factor is mono-modal, with an average of 58 g<sub>NO<sub><i>x</i></sub></sub> kg<sub>fuel</sub><sup>-1</sup>. The corresponding emission related to the generated power yields an average of 12.1 g<sub>NO<sub><i>x</i></sub></sub> kWh<sup>−1</sup>. The distribution of the emission factors for particulate number shows that nearly 90% of all particles in the 5.6 nm to 10 μm size range were below 70 nm in diameter. The distribution of the corresponding emission factors for the mass indicates two separated main modes, one for particles between 30 and 300 nm and the other for above 2 μm. The average particle emission factors were found to be in the range from 0.7 to 2.7 × 10<sup>16</sup> particles kg<sub>fuel</sub><sup>-1</sup> and 0.2 to 3.4 g<sub>PM</sub> kg<sub>fuel</sub><sup>-1</sup>, respectively. The NO<sub><i>x</i></sub> and particulate emissions are comparable with other studies. The measured emission factors were compared, for individual ships, to modeled ones using the Ship Traffic Emission Assessment Model (STEAM) of the Finnish Meteorological Institute. A reasonably good agreement for gaseous sulfur and nitrogen emissions can be seen for ships in international traffic, but significant deviations are found for inland vessels. Regarding particulate mass, the values of the modeled data are about 2–3 times higher than the measured results, which probably reflects the assumptions made in the modeled fuel sulfur content. The sulfur contents in the fuel retrieved from the measurements were lower than the previously used assumptions by the City of Saint Petersburg when carrying out atmospheric modeling, and using these measurements it was possible to better assess the impact of shipping on air quality.
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Ozone (O<sub>3</sub>) concentrations in the lower troposphere (LT) over Beijing have significantly increased over the past 2 decades as a result of rapid industrialization in China, with important implications for regional air quality and the photochemistry of the background troposphere. We characterize the vertical distribution of lower-tropospheric (0–6 km) O<sub>3</sub> over Beijing using observations from 16 ozonesonde soundings during a field campaign in April–May 2005 and MOZAIC (Measurement of Ozone and Water Vapor by Airbus In-Service Aircraft) over 13 days in the same period. We focus on the origin of LT O<sub>3</sub> enhancements observed over Beijing, particularly in May. We use a global 3-D chemistry and transport model (GEOS-Chem CTM; GEOS – Goddard Earth Observing System) driven by assimilated meteorological fields to examine the transport pathways for O<sub>3</sub> pollution and to quantify the sources contributing to O<sub>3</sub> and its enhancements in the springtime LT over Beijing. Output from the Global Modeling Initiative (GMI) CTM is also used. High O<sub>3</sub> concentrations (up to 94.7 ppbv) were frequently observed at the altitude of ~ 1.5–2 km. The CTMs captured the timing of the occurrences but significantly underestimated their magnitude. GEOS-Chem simulations and a case study showed that O<sub>3</sub> produced in the Asian troposphere (especially from Asian anthropogenic pollution) made major contributions to the observed O<sub>3</sub> enhancements. Contributions from anthropogenic pollution in the European and North American troposphere were reduced during these events, in contrast with days without O<sub>3</sub> enhancements when contributions from Europe and North America were substantial. The O<sub>3</sub> enhancements typically occurred under southerly wind and warmer conditions. It is suggested that an earlier onset of the Asian summer monsoon would cause more O<sub>3</sub> enhancement events in the LT over the North China Plain in late spring and early summer.
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Particle water and pH are predicted using meteorological observations (relative humidity (RH), temperature (<i>T</i>)), gas/particle composition, and thermodynamic modeling (ISORROPIA-II). A comprehensive uncertainty analysis is included, and the model is validated. We investigate mass concentrations of particle water and related particle pH for ambient fine-mode aerosols sampled in a relatively remote Alabama forest during the Southern Oxidant and Aerosol Study (SOAS) in summer and at various sites in the southeastern US during different seasons, as part of the Southeastern Center for Air Pollution and Epidemiology (SCAPE) study. Particle water and pH are closely linked; pH is a measure of the particle H<sup>+</sup> aqueous concentration and depends on both the presence of ions and amount of particle liquid water. Levels of particle water, in turn, are determined through water uptake by both the ionic species and organic compounds. Thermodynamic calculations based on measured ion concentrations can predict both pH and liquid water but may be biased since contributions of organic species to liquid water are not considered. In this study, contributions of both the inorganic and organic fractions to aerosol liquid water were considered, and predictions were in good agreement with measured liquid water based on differences in ambient and dry light scattering coefficients (prediction vs. measurement: slope = 0.91, intercept = 0.5 μg m<sup>−3</sup>, <i>R</i><sup>2</sup> = 0.75). ISORROPIA-II predictions were confirmed by good agreement between predicted and measured ammonia concentrations (slope = 1.07, intercept = −0.12 μg m<sup>−3</sup>, <i>R</i><sup>2</sup> = 0.76). Based on this study, organic species on average contributed 35% to the total water, with a substantially higher contribution (50%) at night. However, not including contributions of organic water had a minor effect on pH (changes pH by 0.15 to 0.23 units), suggesting that predicted pH without consideration of organic water could be sufficient for the purposes of aqueous secondary organic aerosol (SOA) chemistry. The mean pH predicted in the Alabama forest (SOAS) was 0.94 ± 0.59 (median 0.93). pH diurnal trends followed liquid water and were driven mainly by variability in RH; during SOAS nighttime pH was near 1.5, while daytime pH was near 0.5. pH ranged from 0.5 to 2 in summer and 1 to 3 in the winter at other sites. The systematically low pH levels in the southeast may have important ramifications, such as significantly influencing acid-catalyzed reactions, gas–aerosol partitioning, and mobilization of redox metals and minerals. Particle ion balances or molar ratios, often used to infer pH, do not consider the dissociation state of individual ions or particle liquid water levels and do not correlate with particle pH.
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Free-burning experimental fires were conducted in a wind tunnel to explore the role of ignition type and thus fire spread mode on the resulting emissions profile from combustion of fine (< 6 mm in diameter) Eucalyptus litter fuels. Fires were burnt spreading with the wind (heading fire), perpendicular to the wind (flanking fire) and against the wind (backing fire). Greenhouse gas compounds (i.e. CO<sub>2</sub>, CH<sub>4</sub> and N<sub>2</sub>O) and CO were quantified using off-axis integrated-cavity-output spectroscopy. Emissions factors calculated using a carbon mass balance technique (along with statistical testing) showed that most of the carbon was emitted as CO<sub>2</sub>, with heading fires emitting 17% more CO<sub>2</sub> than flanking and 9.5% more CO<sub>2</sub> than backing fires, and about twice as much CO as flanking and backing fires. Heading fires had less than half as much carbon remaining in combustion residues. Statistically significant differences in CH<sub>4</sub> and N<sub>2</sub>O emissions factors were not found with respect to fire spread mode. Emissions factors calculated per unit of dry fuel consumed showed that combustion phase (i.e. flaming or smouldering) had a statistically significant impact, with CO and N<sub>2</sub>O emissions increasing during smouldering combustion and CO<sub>2</sub> emissions decreasing. Findings on the equivalence of different emissions factor reporting methods are discussed along with the impact of our results for emissions accounting and potential sampling biases associated with our work. The primary implication of this study is that prescribed fire practices could be modified to mitigate greenhouse gas emissions from forests by judicial use of ignition methods to induce flanking and backing fires over heading fires.
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A new exhaust aerosol model CFD-TUTEAM (Tampere University of Technology Exhaust Aerosol Model for Computational Fluid Dynamics) was developed. It is based on modal aerosol dynamics modeling with log-normal assumption of particle distributions. The model has an Eulerian sub-model providing detailed spatial information within the computational domain and a computationally less expensive, but spatial-information-lacking, Lagrangian sub-model. Particle formation in a laboratory sampling system that includes a porous tube-type diluter and an aging chamber was modeled with CFD-TUTEAM. The simulation results imply that over 99% of new particles are formed in the aging chamber region because the nucleation rate remains at a high level in the aging chamber due to low dilution ratio and low nucleation exponents. The nucleation exponents for sulfuric acid in sulfuric-acid–water nucleation ranging from 0.25 to 1 appeared to fit best with measurement data, which are the same values as obtained from the slopes of the measured volatile nucleation mode number concentration vs. the measured raw exhaust sulfuric acid concentration. These nucleation exponents are very low compared to the nucleation exponents obtained from the classical nucleation theory of binary sulfuric-acid–water nucleation. The values of nucleation exponent lower than unity suggest that other compounds, such as hydrocarbons, might have a significant role in the nucleation process.
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Data assimilation is used in atmospheric chemistry models to improve air quality forecasts, construct re-analyses of three-dimensional chemical (including aerosol) concentrations and perform inverse modeling of input variables or model parameters (e.g., emissions). Coupled chemistry meteorology models (CCMM) are atmospheric chemistry models that simulate meteorological processes and chemical transformations jointly. They offer the possibility to assimilate both meteorological and chemical data; however, because CCMM are fairly recent, data assimilation in CCMM has been limited to date. We review here the current status of data assimilation in atmospheric chemistry models with a particular focus on future prospects for data assimilation in CCMM. We first review the methods available for data assimilation in atmospheric models, including variational methods, ensemble Kalman filters, and hybrid methods. Next, we review past applications that have included chemical data assimilation in chemical transport models (CTM) and in CCMM. Observational data sets available for chemical data assimilation are described, including surface data, surface-based remote sensing, airborne data, and satellite data. Several case studies of chemical data assimilation in CCMM are presented to highlight the benefits obtained by assimilating chemical data in CCMM. A case study of data assimilation to constrain emissions is also presented. There are few examples to date of joint meteorological and chemical data assimilation in CCMM and potential difficulties associated with data assimilation in CCMM are discussed. As the number of variables being assimilated increases, it is essential to characterize correctly the errors; in particular, the specification of error cross-correlations may be problematic. In some cases, offline diagnostics are necessary to ensure that data assimilation can truly improve model performance. However, the main challenge is likely to be the paucity of chemical data available for assimilation in CCMM.
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Dynamic flux chambers (DFCs) and micrometeorological (MM) methods are extensively deployed for gauging air–surface Hg<sup>0</sup> gas exchange. However, a systematic evaluation of the precision of the contemporary Hg<sup>0</sup> flux quantification methods is not available. In this study, the uncertainty in Hg<sup>0</sup> flux measured by the relaxed eddy accumulation (REA) method, the aerodynamic gradient method (AGM), the modified Bowen ratio (MBR) method, as well as DFC of traditional (TDFC) and novel (NDFC) designs, are assessed using a robust data set from two field intercomparison campaigns. <br><br> The absolute precision in Hg<sup>0</sup> concentration difference (Δ<i>C</i>) measurements is estimated at 0.064 ng m<sup>−3</sup> for the gradient-based MBR and AGM systems. For the REA system, the parameter is Hg<sup>0</sup> concentration (<i>C</i>) dependent at 0.069 + 0.022<i>C</i>. During the campaigns, 57 and 62 % of the individual vertical gradient measurements are found to be significantly different from 0, while for the REA technique, the percentage of significant observations is lower. For the chambers, non-significant fluxes are confined to a few night-time periods with varying ambient Hg$^{0}$ concentrations. Relative bias for DFC-derived fluxes is estimated to be ~ ±10, and ~ 85% of the flux bias is within ±2 ng m<sup>−2</sup> h<sup>−1</sup> in absolute terms. The DFC flux bias follows a diurnal cycle, which is largely affected by the forced temperature and irradiation bias in the chambers. Due to contrasting prevailing micrometeorological conditions, the relative uncertainty (median) in turbulent exchange parameters differs by nearly a factor of 2 between the campaigns, while that in Δ<i>C</i> measurement is fairly consistent. The estimated flux uncertainties for the triad of MM techniques are 16–27, 12–23 and 19–31% (interquartile range) for the AGM, MBR and REA methods, respectively. This study indicates that flux-gradient-based techniques (MBR and AGM) are preferable to REA in quantifying Hg<sup>0</sup> flux over ecosystems with low vegetation height. A limitation of all Hg<sup>0</sup> flux measurement systems investigated is their inability to obtain synchronous samples for the calculation of Δ<i>C</i>. This reduces the precision of flux quantification, particularly in the MM systems under non-stationarity of ambient Hg<sup>0</sup> concentration. For future applications, it is recommended to accomplish Δ<i>C</i> derivation from simultaneous collected samples.
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A sudden stratospheric warming (SSW) in early January 2013 caused the Arctic polar vortex to split and temperatures to rapidly rise above the threshold for chlorine activation. However, ozone in the lower stratospheric polar vortex from late December 2012 through early February 2013 reached the lowest values on record for that time of year. Analysis of Aura Microwave Limb Sounder (MLS) trace gas measurements and Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) polar stratospheric cloud (PSC) data shows that exceptional chemical ozone loss early in the 2012/13 Arctic winter resulted from a unique combination of meteorological conditions associated with the early-January 2013 SSW: unusually low temperatures in December 2012, offspring vortices within which air remained well isolated for nearly 1 month after the vortex split, and greater-than-usual vortex sunlight exposure throughout December 2012 and January 2013. Conditions in the two offspring vortices differed substantially, with the one overlying Canada having lower temperatures, lower nitric acid (HNO<sub>3</sub>), lower hydrogen chloride, more sunlight exposure/higher ClO in late January, and a later onset of chlorine deactivation than the one overlying Siberia. MLS HNO<sub>3</sub> and CALIPSO data indicate that PSC activity in December 2012 was more extensive and persistent than at that time in any other Arctic winter in the past decade. Chlorine monoxide (ClO, measured by MLS) rose earlier than previously observed and was the largest on record through mid-January 2013. Enhanced vortex ClO persisted until mid-February despite the cessation of PSC activity when the SSW started. Vortex HNO<sub>3</sub> remained depressed after PSCs had disappeared; passive transport calculations indicate vortex-averaged denitrification of about 4 parts per billion by volume. The estimated vortex-averaged chemical ozone loss, ~ 0.7–0.8 parts per million by volume near 500 K (~21 km), was the largest December/January loss in the MLS record from 2004/05 to 2014/15.
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We investigate 3-D mountain effects on solar flux distributions and their impact on surface hydrology over the western United States, specifically the Rocky Mountains and the Sierra Nevada, using the global CCSM4 (Community Climate System Model version 4; Community Atmosphere Model/Community Land Model – CAM4/CLM4) with a 0.23° × 0.31° resolution for simulations over 6 years. In a 3-D radiative transfer parameterization, we have updated surface topography data from a resolution of 1 km to 90 m to improve parameterization accuracy. In addition, we have also modified the upward-flux deviation (3-D–PP (plane-parallel)) adjustment to ensure that the energy balance at the surface is conserved in global climate simulations based on 3-D radiation parameterization. We show that deviations in the net surface fluxes are not only affected by 3-D mountains but also influenced by feedbacks of cloud and snow in association with the long-term simulations. Deviations in sensible heat and surface temperature generally follow the patterns of net surface solar flux. The monthly snow water equivalent (SWE) deviations show an increase in lower elevations due to reduced snowmelt, leading to a reduction in cumulative runoff. Over higher-elevation areas, negative SWE deviations are found because of increased solar radiation available at the surface. Simulated precipitation increases for lower elevations, while it decreases for higher elevations, with a minimum in April. Liquid runoff significantly decreases at higher elevations after April due to reduced SWE and precipitation.
