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Characteristics, sources and formation of aerosol oxalate in an Eastern Asia megacity and its implication to haze pollution

A total of 238 samples of PM2.5 and TSP were analyzed to study the characteristics, sources, and formation pathways of aerosol oxalate in Shanghai in four seasons of 2007. The concentrations of oxalate were 0.07–0.41 μg m−3 in PM2.5 and 0.10–0.48 μg m−3 in TSP, respectively. Oxalate displayed a seasonal variation of autumn>summer>winter>spring in both PM2.5 and TSP and was dominantly present in PM2.5 in all samples. Correlation between oxalate and K+ and high ratio of oxalate/K+ suggested that biomass burning was a secondary source of aerosol oxalate in Shanghai, in addition to urban VOCs sources (vehicular and industrial emissions), especially in autumn. Secondary formation accounted for the majority of aerosol oxalate in Shanghai, which was supported by the high correlation of oxalate with nss-SO42−, K+ and NO3−, proceeding from different mechanisms. Relatively high ambient RH together with high cloud cover was found benefiting the secondary formation of aerosol oxalate. The in-cloud process (aqueous-phase oxidation) was proposed to be likely the major formation pathway of aerosol oxalate in Shanghai, which was supported by the high correlation of oxalate with nss-SO42− and K+ , dominant residence of oxalate in droplet mode and result of favorable meteorological condition analysis. High correlation of oxalate and NO3− reflected the OH radical involved oxidation chemistry of the two species in the atmosphere and also suggested that gas-particle surface reactions and evaporation-condensation process were both possible secondary formation pathways of aerosol oxalate in coarser particle mode (>1.0 μm). Aerosol oxalate contributed to the haze pollution and visibility degradation of the local environment. As a major water-soluble organic compound in aerosols, concentration of oxalate showed a distinct negative correlation to the atmospheric visibility, which implied that aerosol organic compounds could play an important role in air quality in Shanghai.
Carbonaceous species in PM2.5 at a pair of rural/urban sites in Beijing, 2005–2008

One-week integrated PM2.5 samples were collected over four years (2005–2008) at a pair of sites, one rural and one urban site, in the area of Beijing, China. Weekly organic and elemental carbon (OC and EC) concentrations from these samples were measured to investigate their atmospheric concentrations, temporal variation patterns and the factors influencing these aspects. A slightly systematic decrease in annual mean concentration of OC and an opposite trend for EC at both sites was observed. Since OC accounted for about 70 % of total carbon (TC, i.e. OC + EC) the total carbonaceous mass experienced a slight decline on a yearly basis over the study period. Its fraction of PM2.5 mass at the urban site in 2008 was significantly lower than observed 10 years earlier (1999), indicating that the relative importance of carbonaceous species in PM2.5 has decreased. In urban Beijing clear seasonal variations (by factors of 1.35 ~ 3.0) were shown in both OC and EC with higher weekly concentrations and fluctuations in winter and much lower values in summer and spring. The minimum seasonal urban excesses of OC (3.0 μg m−3) and EC (1.3 μg m−3) occurred in the summer of 2008, which were only one-ninth and one-seventh of their corresponding maximum values, respectively. This reduction in the urban-difference, coupled with more positive stable carbon isotope values of EC at the urban site in that summer relative to the preceding summers, supports that the special clean air campaign for the 2008 Summer Olympic Games very likely had noticeable impact on the ambient concentrations of carbonaceous aerosols in the Beijing area, particularly on the local urban scale. Less consistent seasonal patterns in OC and EC, their scattered correlation, and higher mass ratios of OC to EC (OC/EC) at the rural site indicate more complex and variable major sources regarding aerosol formation in the rural area. These emission sources include biomass burning during the harvest seasons, widely used high-polluting family stoves and small boilers for cooking and heating with high OC/EC ratios, and a greater relative quantity of secondary organic aerosols.
Forest-atmosphere exchange of ozone: sensitivity to very reactive biogenic VOC emissions and implications for in-canopy photochemistry

Understanding the fate of ozone within and above forested environments is vital to assessing the anthropogenic impact on ecosystems and air quality at the urban-rural interface. Observed forest-atmosphere exchange of ozone is often much faster than explicable by stomatal uptake alone, suggesting the presence of additional ozone sinks within the canopy. Using the Chemistry of Atmosphere-Forest Exchange (CAFE) model in conjunction with summer noontime observations from the 2007 Biosphere Effects on Aerosols and Photochemistry Experiment (BEARPEX-2007), we explore the viability and implications of the hypothesis that ozonolysis of very reactive but yet unidentified biogenic volatile organic compounds (BVOC) can influence the forest-atmosphere exchange of ozone. Non-stomatal processes typically generate 67 % of the observed ozone flux, but reactions of ozone with measured BVOC, including monoterpenes and sesquiterpenes, can account for only 2 % of this flux during the selected timeframe. By incorporating additional emissions and chemistry of a proxy for very reactive VOC (VRVOC) that undergo rapid ozonolysis, we demonstrate that an in-canopy chemical ozone sink of ~2 × 108 molec cm−3 s−1 can close the ozone flux budget. Even in such a case, the 65 min chemical lifetime of ozone is much longer than the canopy residence time of ~2 min, highlighting that chemistry can influence reactive trace gas exchange even when it is "slow" relative to vertical mixing. This level of VRVOC ozonolysis could enhance OH and RO2 production by as much as 1 pptv s−1 and substantially alter their respective vertical profiles depending on the actual product yields. Reaction products would also contribute significantly to the oxidized VOC budget and, by extension, secondary organic aerosol mass. Given the potentially significant ramifications of a chemical ozone flux for both in-canopy chemistry and estimates of ozone deposition, future efforts should focus on quantifying both ozone reactivity and non-stomatal (e.g. cuticular) deposition within the forest.
Satellite- and ground-based CO total column observations over 2010 Russian fires: accuracy of top-down estimates based on thermal IR satellite data

CO total column data are presented from three space sounders and two ground-based spectrometers in Moscow and its suburbs during the forest and peat fires that occurred in Central Russia in July–August 2010. Also presented are ground-based in situ CO measurements. The Moscow area was strongly impacted by the CO plume from these fires. Concurrent satellite- and ground-based observations were used to quantify the errors of CO top-down emission estimates. On certain days, CO total columns retrieved from the data of the space-based sounders were 2–3 times less than those obtained from the ground-based sun-tracking spectrometers. The depth of the polluted layer over Moscow was estimated using total column measurements compared with CO volume mixing ratios in the surface layer and on the TV tower and found to be around 360 m. The missing CO that is the average difference between the CO total column accurately determined by the ground spectrometers and that retrieved by AIRS, MOPITT, and IASI was determined for the Moscow area between 1.6 and 3.3 × 1018 molec cm−2. These values were extrapolated onto the entire plume; subsequently, the CO burden (total mass) over Russia during the fire event was corrected. A top-down estimate of the total emitted CO, obtained by a simple mass balance model increased by 40–100 % for different sensors due to this correction. Final assessments of total CO emitted by Russian wildfires obtained from different sounders are between 34 and 40 Tg CO during July–August 2010.
Technical Note: Comparing the effectiveness of recent algorithms to fill and smooth incomplete and noisy time series

Geophysical time series often feature missing data or data acquired at irregular times. Procedures are needed to either resample these series at systematic time intervals or to generate reasonable estimates at specified times in order to meet specific user requirements or to facilitate subsequent analyses. Interpolation methods have long been used to address this problem, taking into account the fact that available measurements also include errors of measurement or uncertainties. This paper inspects some of the currently used approaches to fill gaps and smooth time series (smoothing splines, Singular Spectrum Analysis and Lomb-Scargle) by comparing their performance in either reconstructing the original record or in minimizing the Mean Absolute Error (MAE), Mean Bias Error (MBE), chi-squared test statistics and autocorrelation of residuals between the underlying model and the available data, using both artificially-generated series or well-known publicly available records. Some methods make no assumption on the type of variability in the data while others hypothesize the presence of at least some dominant frequencies. It will be seen that each method exhibits advantages and drawbacks, and that the choice of an approach largely depends on the properties of the underlying time series and the objective of the research.
Lake breezes in the southern Great Lakes region and their influence during BAQS-Met 2007

Meteorological observations from the BAQS-Met field experiment during the summer months of 2007 were integrated and manually analyzed in order to identify and characterize lake breezes in the southern Great Lakes region of North America, and assess their potential impact on air quality. Lake breezes occurred frequently, with one or more lake breezes identified on 90 % of study days. They affected all parts of the study region, including southwestern Ontario and nearby portions of southeast Lower Michigan and northern Ohio, with lake-breeze fronts occasionally penetrating from 100 km to over 200 km inland. Occurrence rates and penetration distances were found to be higher than previously reported in the literature. This comprehensive depiction of observed lake breezes allows an improved understanding of their influence on the transport, dispersion, and production of pollutants in this region. The observational analyses were compared with output from subsequent runs of a high-resolution numerical weather prediction model. The model accurately predicted lake breeze occurrence and type in a variety of synoptic wind regimes, but selected cases showed substantial differences in the detailed timing and location of lake-breeze fronts, and with the initiation of deep moist convection. Knowledge of such strengths and weaknesses aids in the interpretation of results from air quality models driven by this meteorological model.
A novel calibration approach of MODIS AOD data to predict PM2.5 concentrations

Epidemiological studies investigating the human health effects of PM2.5 are susceptible to exposure measurement errors, a form of bias in exposure estimates, since they rely on data from a limited number of PM2.5 monitors within their study area. Satellite data can be used to expand spatial coverage, potentially enhancing our ability to estimate location- or subject-specific exposures to PM2.5, but some have reported poor predictive power. A new methodology was developed to calibrate aerosol optical depth (AOD) data obtained from the Moderate Resolution Imaging Spectroradiometer (MODIS). Subsequently, this method was used to predict ground daily PM2.5 concentrations in the New England region. 2003 MODIS AOD data corresponding to the New England region were retrieved, and PM2.5 concentrations measured at 26 US Environmental Protection Agency (EPA) PM2.5 monitoring sites were used to calibrate the AOD data. A mixed effects model which allows day-to-day variability in daily PM2.5-AOD relationships was used to predict location-specific PM2.5 levels. PM2.5 concentrations measured at the monitoring sites were compared to those predicted for the corresponding grid cells. Both cross-sectional and longitudinal comparisons between the observed and predicted concentrations suggested that the proposed new calibration approach renders MODIS AOD data a potentially useful predictor of PM2.5 concentrations. Furthermore, the estimated PM2.5 levels within the study domain were examined in relation to air pollution sources. Our approach made it possible to investigate the spatial patterns of PM2.5 concentrations within the study domain.
Spatial distributions and seasonal cycles of aerosols in India and China seen in global climate-aerosol model

A climate-aerosol model is employed to study spatial and temporal variability of aerosol properties over India and China for recent (year 2006) and future conditions (year 2020) under different emission pathways. We present results for aerosol mass concentration in different size classes and optical properties for the five different aerosol species treated by the model. Aerosol mass concentration and optical depth have significant contributions from both anthropogenic and natural aerosols. Different species have maxima in different regions, with the highest anthropogenic aerosol concentrations found in Kolkata and elsewhere in the Ganges basin in India and on the northern part of the east coast and in the Sichuan basin in China. In India, natural aerosols have a maximum in the summer due to higher wind speeds, whereas anthropogenic aerosols have a maximum in the winter due to less efficient wet removal. Surface concentrations also tend to be higher in winter due to the additional reason of lower average boundary layer height. In China, seasonal cycles are weaker with natural aerosols having a maximum in the spring and sulfate contribution to the aerosol optical depth (AOD) being higher in the latter half of the year. MODIS AOD spatial distributions are reproduced well by the model, except for the Ganges valley with high absorption and for the Thar desert with high dust concentrations. Seasonal cycles compare qualitatively well with MODIS measurements.
Ozone data assimilation with GEOS-Chem: a comparison between 3-D-Var, 4-D-Var, and suboptimal Kalman filter approaches

Chemistry transport models determine the evolving chemical state of the atmosphere by solving the fundamental equations that govern physical and chemical transformations subject to initial conditions of the atmospheric state and surface boundary conditions, e.g., surface emissions. The development of data assimilation techniques synthesize model predictions with measurements in a rigorous mathematical framework that provides observational constraints on these conditions. Two families of data assimilation methods are currently widely used: variational and Kalman filter (KF). The variational approach is based on control theory and formulates data assimilation as a minimization problem of a cost functional that measures the model-observations mismatch. The Kalman filter approach is rooted in statistical estimation theory and provides the analysis covariance together with the best state estimate. Suboptimal Kalman filters employ different approximations of the covariances in order to make the computations feasible with large models. Each family of methods has both merits and drawbacks. This paper compares several data assimilation methods used for global chemical data assimilation. Specifically, we evaluate data assimilation approaches for improving estimates of the summertime global tropospheric ozone distribution in August 2006 based on ozone observations from the NASA Tropospheric Emission Spectrometer and the GEOS-Chem chemistry transport model. The resulting analyses are compared against independent ozonesonde measurements to assess the effectiveness of each assimilation method. All assimilation methods provide notable improvements over the free model simulations, which differ from the ozonesonde measurements by about 20 % (below 200 hPa). Four dimensional variational data assimilation with window lengths between five days and two weeks is the most accurate method, with mean differences between analysis profiles and ozonesonde measurements of 1–5 %. Two sequential assimilation approaches (three dimensional variational and suboptimal KF), although derived from different theoretical considerations, provide similar ozone estimates, with relative differences of 5–10 % between the analyses and ozonesonde measurements. Adjoint sensitivity analysis techniques are used to explore the role of of uncertainties in ozone precursors and their emissions on the distribution of tropospheric ozone. A novel technique is introduced that projects 3-D-Variational increments back to an equivalent initial condition, which facilitates comparison with 4-D variational techniques.
Methane flux, vertical gradient and mixing ratio measurements in a tropical forest

Measurements of CH4 mixing ratio, vertical gradients and turbulent fluxes were carried out in a tropical forest (Reserva Biológica Cuieiras), about 60 km north of Manaus, Brazil. The methane mixing ratio and flux measurements were performed at a height of 53 m (canopy height 35 m). In addition, vertical CH4 gradients were measured within the canopy using custom made air samplers at levels of 2, 16 and 36 m above ground. The methane gradients within the canopy reveal that there is a continuous methane source at the surface. No clear evidence for aerobic methane emission from the canopy was found. The methane fluxes above the canopy are small but consistently upwards with a maximum early in the morning. The measured fluxes are in agreement with the observed CH4 gradient in the canopy. In the morning hours, a strong canopy venting peak is observed for both CH4 and CO2, but for CO2 this peak is then superimposed by photosynthetic uptake, whereas the peak lasts longer for CH4. Monthly averaged diurnal cycles of the CH4 mixing ratio show a decrease during daytime and increase during nighttime. The magnitude of the difference in CH4 mixing ratio between day and night gradually increases throughout the wet season. The fluxes required to explain the nighttime increase are in agreement with the nighttime fluxes measured above the canopy, which implies that the CH4 increase in the nighttime boundary layer originates from local sources.