Glen R. Cass

Indian Ocean Experiment: An integrated analysis of the climate forcing and effects of the great Indo-Asian haze

Every year, from December to April, anthropogenic haze spreads over most of the North Indian Ocean, and South and Southeast Asia. The Indian Ocean Experiment (INDOEX) documented this Indo-Asian haze at scales ranging from individual particles to its contribution to the regional climate forcing. This study integrates the multiplatform observations (satellites, aircraft, ships, surface stations, and balloons) with one- and four-dimensional models to derive the regional aerosol forcing resulting from the direct, the semidirect and the two indirect effects. The haze particles consisted of several inorganic and carbonaceous species, including absorbing black carbon clusters, fly ash, and mineral dust. The most striking result was the large loading of aerosols over most of the South Asian region and the North Indian Ocean. The January to March 1999 visible optical depths were about 0.5 over most of the continent and reached values as large as 0.2 over the equatorial Indian ocean due to long-range transport. The aerosol layer extended as high as 3 km. Black carbon contributed about 14% to the fine particle mass and 11% to the visible optical depth. The single-scattering albedo estimated by several independent methods was consistently around 0.9 both inland and over the open ocean. Anthropogenic sources contributed as much as 80% (±10%) to the aerosol loading and the optical depth. The in situ data, which clearly support the existence of the first indirect effect (increased aerosol concentration producing more cloud drops with smaller effective radii), are used to develop a composite indirect effect scheme. The Indo-Asian aerosols impact the radiative forcing through a complex set of heating (positive forcing) and cooling (negative forcing) processes. Clouds and black carbon emerge as the major players. The dominant factor, however, is the large negative forcing (-20±4 W m^(−2)) at the surface and the comparably large atmospheric heating. Regionally, the absorbing haze decreased the surface solar radiation by an amount comparable to 50% of the total ocean heat flux and nearly doubled the lower tropospheric solar heating. We demonstrate with a general circulation model how this additional heating significantly perturbs the tropical rainfall patterns and the hydrological cycle with implications to global climate.

Characterization of organic aerosols emitted from the combustion of biomass indigenous to South Asia

[1] Throughout South Asia biomass is commonly used as a fuel source for cooking and heating homes. The smoke from domestic use of these fuels is expected to be a major source of atmospheric particulate matter in the region and needs to be characterized for input in regional source apportionment models and global climate models. Biomass fuel samples including coconut leaves, rice straw, jackfruit branches, dried cowdung patties, and biomass briquettes manufactured from compressed biomass material were obtained from Bangladesh. The fuel samples were burned in a wood stove to collect and characterize the particulate matter emissions. The bulk chemical composition including total organic and elemental carbon, sulfate, nitrate, ammonium and chloride ions, and bulk elements such as potassium and sodium did not show conclusive differences among the biomass samples tested. Unique features, however, exist in the detailed organic characterization of the combustion smoke from the different sources. The organic compound fingerprints of the particulate matter are shown to be distinct from one another and distinct from North American wood fuels. Fecal stanols including 5b-stigmastanol, coprostanol, and cholestanol are found to be good molecular markers for the combustion of cowdung. Additionally, the patterns of methoxyphenols and plant sterols provide a unique signature for each biomass sample and are conducive as source apportionment tracers. INDEX TERMS: 0305 Atmospheric Composition and Structure: Aerosols and particles (0345, 4801); 0345 Atmospheric Composition and Structure: Pollution—urban and regional (0305); 0399 Atmospheric Composition and Structure: General or miscellaneous; 1699 Global Change: General or miscellaneous; KEYWORDS: biomass aerosol, molecular marker, organic

INDOEX aerosol: A comparison and summary of chemical, microphysical, and optical properties observed from land, ship, and aircraft

converged on values of about 3.8 ± 0.3 m 2 g � 1 , providing a firm constraint upon the description and modeling of haze optical properties. MSE values trended lower with more dilute haze but became more variable in clean air or regions of low concentrations. This cross-platform comparison resolved a number of measurement differences but also revealed that regional characterization from different platforms results in differences linked to variability in time and space. This emphasizes the need to combine such efforts with coordinated satellite and modeling studies able to characterize large-scale regional structure and variability. These comparisons also indicate that ‘‘closure’’ between chemical, microphysical, and optical properties across platforms to better than about 20% will require significant improvements in techniques, calibration procedures, and comparison efforts. INDEX TERMS: 0305 Atmospheric Composition and Structure: Aerosols and particles (0345, 4801); 0345 Atmospheric Composition and Structure: Pollution—urban and regional (0305); 0394 Atmospheric Composition and Structure: Instruments and techniques; KEYWORDS: INDOEX, data comparison, optical properties, chemistry, microphysics, size distributions

Speciation of ambient fine organic carbon particles and source apportionment of PM2.5 in Indian cities

Fine particle organic carbon in Delhi, Mumbai, Kolkata, and Chandigarh is speciated to quantify sources contributing to fine particle pollution. Gas chromatography/mass spectrometry of 29 particle-phase organic compounds, including n-alkanes, polycyclic aromatic hydrocarbons (PAHs), hopanes, steranes, and levoglucosan along with quantification of silicon, aluminum, and elemental carbon are used in a molecular-marker based source apportionment model to quantify the primary source contributions to the PM2.5 mass concentrations for four seasons in three sites and for the summer in Chandigarh. Five primary sources are identified and quantified: diesel engine exhaust, gasoline engine exhaust, road dust, coal combustion, and biomass combustion. Important trends in the seasonal and spatial patterns of the impact of these five sources are observed. On average, primary emissions from fossil fuel combustion (coal, diesel, and gasoline) are responsible for about 25-33% of PM2.5 mass in Delhi, 21-36% in Mumbai, 37-57% in Kolkata, and 28% in Chandigarh. These figures can be compared to the biomass combustion contributions to ambient PM2.5 of 7-20% for Delhi, 7-20% for Mumbai, 13-18% for Kolkata, and 8% for Chandigarh. These measurements provide important information about the seasonal and spatial distribution of fine particle phase organic compounds in Indian cities as well as quantifying sourcemorexa0» contributions leading to the fine particle air pollution in those cities.«xa0less

Source Apportionment of Daily Fine Particulate Matter at Jefferson Street, Atlanta, GA, during Summer and Winter

Abstract The primary emission source contributions to fine organic carbon (OC) and fine particulate matter (PM2.5) mass concentrations on a daily basis in Atlanta, GA, are quantified for a summer (July 3 to August 4, 2001) and a winter (January 2–31, 2002) month. Thirty-one organic compounds in PM2.5 were identified and quantified by gas chromatography/mass spectrometry. These organic tracers, along with elemental carbon, aluminum, and silicon, were used in a chemical mass balance (CMB) receptor model. CMB source apportionment results revealed that major contributors to identified fine OC concentrations include meat cooking (7–68%; average: 36%), gasoline exhaust (7–45%; average: 21%), and diesel exhaust (6– 41%; average: 20%) for the summer month, and wood combustion (0–77%; average: 50%); gasoline exhaust (14–69%; average: 33%), meat cooking (1–14%; average: 5%), and diesel exhaust (0–13%; average: 4%) for the winter month. Primary sources, as well as secondary ions, including sulfate, nitrate, and ammonium, accounted for 86 ± 13% and 112 ± 15% of the measured PM2.5 mass in summer and winter, respectively.

Secondary organic aerosol 3. Urban/regional scale model of size- and composition-resolved aerosols

The California Institute of Technology (CIT) three-dimensional urban/regional atmospheric model is used to perform comprehensive gas- and aerosol-phase simulations of the 8 September 1993 smog episode in the South Coast Air Basin of California (SoCAB) using the atmospheric chemical mechanism of part 1 [Griffin et al., 2002] and the thermodynamic module of part 2 [Pun et al., 2002]. This paper focuses primarily on simulations of secondary organic aerosol (SOA) and determination of the species and processes that lead to this SOA. Meteorological data and a gas and particulate emissions inventory for this episode were supplied directly by the South Coast Air Quality Management District. A summer 1993 atmospheric sampling campaign provides data against which the performance of the model is evaluated. Predictions indicate that SOA formation in the SoCAB is dominated by partitioning of hydrophobic secondary products of the oxidation of anthropogenic organics. The biogenic contribution to total SOA increases in the more rural eastern portions of the region, as does the fraction of hydrophilic SOA, the latter reflecting the increasing degree of oxidation of SOA species with atmospheric residence time.

Organic compounds in biomass smoke from residential wood combustion: Emissions characterization at a continental scale

Wood smoke in the atmosphere often accounts for 20–30% of the ambient fine-particle concentrations. In communities where wood is burned for home heating, wood smoke can at times contribute the majority of the atmospheric fine-particle burden. Chemical mass balance receptor models that use organic compounds as tracers can be used to determine the contributions of different emission sources, including wood smoke, to atmospheric fine-particle samples. In order for organic chemical tracer techniques to be applied to communities across the United States, differences in wood smoke composition that arise from differences in the type of wood burned in various regions must be understood. A continental-scale accounting of particulate organic compound emissions from residential wood combustion has been constructed which helps to quantify the regional differences in wood smoke composition that exist between different parts of the United States. Data from a series of source tests conducted on 22 North American wood species have been used to assemble a national inventory of emissions for more than 250 individual organic compounds that are released from wood combustion in fireplaces and wood stoves in the United States. The emission rates of important wood smoke markers, such as levoglucosan, certain substituted syringols and guaiacols, and phytosterols vary greatly with wood type and combustor type. These differences at the level of individual wood type and combustion conditions translate into regional differences in the aggregate composition of ambient wood smoke. By weighting the source test results in proportion to the availability of firewood from specific tree species and the quantities of wood burned in each locale, it is possible to investigate systematic differences that exist between wood smokes from different regions of North America. The relative abundance of 10 major wood smoke components averaged over the emissions inventory in different regions of the United States is computed and then used to illustrate the extent to which wood smoke composition differs from region to region in North America.

An evaluation of the thermodynamic equilibrium assumption for fine particulate composition: Nitrate and ammonium during the 1999 Atlanta Supersite Experiment

[1]xa0Data obtained during the 1999 Atlanta Supersite Experiment are used to test the validity of the assumption of thermodynamic equilibrium between fine particulate (PM2.5) nitrate (NO3−) and ammonium (NH4+) and gas-phase nitric acid (HNO3(g)) and ammonia (NH3(g)). Equilibrium is tested by first calculating the equilibrium concentrations of HNO3(g) and NH3(g) implied by the PM2.5 inorganic composition (i.e, Na+, NH4+, Cl−, NO3−, and SO42−), temperature, and relative humidity observed at the site. These calculated equilibrium concentrations are then compared to the corresponding observed gas-phase concentrations. The observed PM2.5 composition is based on the 5-min averaged measurements of the Georgia Tech PILS [Weber et al., 2001], while the observed HNO3(g) and NH3(g) concentrations are based on the measurements of Edgerton et al. [2000a] and Slanina et al. [2001], respectively. The equilibrium gas-phase concentrations are calculated using the ISORROPIA model of Nenes et al. [1998]. Out of the entire Atlanta Supersite database, we were able to identify 272 five-minute intervals with overlapping measurements of PM2.5 composition, HNO3(g) and NH3(g). Initial calculations using these 272 data points suggest an absence of thermodynamic equilibrium with the calculated equilibrium NH3(g) generally less than its observed concentration and predicted HNO3(g) generally greater than the observed concentration. However, relatively small downward adjustments in the measured PM2.5 SO42− (or apparent acidity) bring the calculated and measured NH3(g) and HNO3(g) into agreement. Moreover, with the exception of 31 of the 272 data points with either anomalously low observed concentrations of SO42− or NH3(g), there is a close correspondence between the SO42− (or acidity) correction needed for HNO3 and that needed for NH3 (slope of 1.04, intercept of ∼0, and r2 = 0.96). The average relative corrections required for equilibrium with HNO3 and NH3 are −14.1% and −13.7%, respectively; significantly larger than the estimated uncertainty arising from random errors in the measurement. One interpretation of our results is that thermodynamic equilibrium does in fact apply to the inorganic PM2.5 composition during the Atlanta Supersite Experiment and either (1) the PM2.5 SO42− concentration measured by the PILS was systematically overestimated by ∼15% or (2) the PM2.5 PILS systematically underestimated the concentration of the alkaline components by ∼15%; and/or 3. The ISORROPIA model systematically underestimated the pH of the PM2.5 encountered during the experiment.

Aerosol optical properties during INDOEX based on measured aerosol particle size and composition

The light scattering and light absorption as a function of wavelength and relative humidity due to aerosols measured at the Kaashidhoo Climate Observatory in the Republic of the Maldives during the INDOEX field campaign has been calculated. Using size-segregated measurements of aerosol chemical composition, calculated light scattering and absorption has been evaluated against measurements of light scattering and absorption. Light scattering coefficients are predicted to within a few percent over relative humidities of 20–90%. Single scattering albedos calculated from the measured elemental carbon size distributions and concentrations in conjunction with other aerosol species have a relative error of 4.0% when compared to measured values. The single scattering albedo for the aerosols measured during INDOEX is both predicted and observed to be about 0.86 at an ambient relative humidity of 80%. These results demonstrate that the light scattering, light absorption, and hence climate forcing due to aerosols over the Indian Ocean are consistent with the chemical and physical properties of the aerosol at that location.

Source apportionment of gasoline and diesel by multivariate calibration based on single particle mass spectral data

The mass apportionment of gasoline and diesel particles in ambient aerosol samples is a difficult problem because both sources exhibit very similar chemical composition. However, individual particle analysis could provide additional information and help achieve source apportionment with good accuracy. Aerosol time-of-flight mass spectrometry (ATOFMS) has proven to be a powerful technique capable of simultaneously determining both the size and chemical composition of single particles in real time. Thus, samples of gasoline and diesel particles were analyzed by ATOFMS for their single particle information. In addition to the aerodynamic diameter from which the individual particle mass can be estimated, positive and negative mass spectra were obtained for each particle. A novel data analysis approach based on the combination of an adaptive resonance theory-based neural network (ART-2a), and a multivariate calibration method, partial least squares (PLS), has been developed to apportion the mass contributions of gasoline and diesel sources to mixture samples. The ART-2a neural network was used first to classify the particle-by-particle mass spectral data. The source profile for each source (gasoline/diesel) was obtained in terms of the mass fractions of the classified particle types. Next, PLS was applied to build a model relating the mass fractions of different particle classes and the mass contributions of the two sources to mixture samples. Artificial mixture samples obtained by randomly mixing some particles from the two source samples have been used to examine the feasibility of the proposed method. Satisfactory predictions for the mass contributions of gasoline and diesel exhaust to the mixture samples have been obtained. A recently proposed formula for prediction error variance is successfully modified to quantify the uncertainty in the PLS predictions. This study exemplifies the potential promise of multivariate calibration as applied to the aerosol source apportionment problem.