Speciated PM10 Emission Inventory for Delhi, India

Emission inventories can serve as a basis for air quality management programs. The focus has been mainly on building inventories for criteria pollutants including particulate matter (PM). Control efforts in developing countries are mostly limited to total suspended particles (TSP) and/or PM10. Since the adverse effects of PM10 depend on its chemical composition, it is important to control emissions of toxic species. The first step is to identify key pollution sources and estimate quantities of various chemical species in emissions. This paper presents a speciated PM10 emission inventory for Delhi, the capital and one of the most polluted cities in India. An established PM10 inventory for Delhi in conjunction with source profiles was used to estimate emissions of major PM10 components including organic and elemental carbon (OC and EC, respectively), sulphates (SO42-), and nitrates (NO3-), as well as selected toxic trace metals (i.e., Pb, Ni, V, As, and Hg), some of which are subject to India&#39;s National Ambient Air Quality Standards (NAAQS). For the base year of 2007, emission estimates for PM10 mass, OC, EC, SO42-, and NO3- are 140, 22, 6.4, 2.8, and 2.1 tonnes/day (TPD; 1 tonne = 1000 kg), respectively. Emissions of Pb, Ni, V, As, and Hg are estimated to be 203, 43, 37, 26, and 9.4 kg/day, respectively. This inventory underestimated Pb and Hg emissions because sources of PM10 from unorganized secondary lead smelters are not specifically identified and gas-to-particle conversion of Hg is not accounted for.</p

Carbonaceous and Ionic Components of Atmospheric Fine Particles in Beijing and Their Impact on Atmospheric Visibility

Ground-based observation of fine particulate matter (PM2.5) in Beijing was carried out continuously in 2006. The carbonaceous and ionic components, as well as their distribution characteristics and seasonal variation, were obtained. The annual mean mass concentration of PM2.5 was 176.6 +/- 100.3 mu g/m(3). Long-range transport dust and local dust raised by strong wind during the spring made a considerable contribution to PM2.5 mass concentration. There was significant seasonal variation in carbonaceous and water-soluble ionic components associated with diverse emission sources, varying meteorological conditions during different seasons, and different mechanisms of formation for secondary aerosol ions. Comparing studies under different synoptic conditions suggested that PM2.5 pollution was mainly caused by transportation of particulates from remote sources, whereas hazy synoptic conditions are caused by local pollution. PM2.5 and visibility were negatively correlated, and the relationship between the concentrations of NH4+, SO42-, and NO3- with PM2.5 concentration during winter can be described using power function fitting.</p

Chemical Composition of Indoor and Outdoor Atmospheric Particles at Emperor Qin's Terra-cotta Museum, Xi'an, China

Indoor particles and microclimate were measured in summer (August 2004) and winter (January 2005) periods inside and outside Emperor Qin&#39;s Terra-Cotta Museum in Xi&#39;an, China. Indoor temperature ranged from 21.9 degrees C to 32.4 degrees C in summer and from 0 degrees C to 5.3 degrees C in winter. Relative humidity varied from 56% to 80% in summer and from 48% to 78% in winter. The number concentrations of particles were lower (0.3-1.0 mu m) in summer, and were higher (1.0-7.0 mu m) in winter. The average indoor PM(2.5) and TSP concentrations were 108.4 +/- 30.3 mu g/m(3) and 172.4 +/- 46.5 mu g/m(3) in summer and were 242.3 +/- 189.0 mu g/m(3) and 312.5 +/- 112.8 mu g/m(3) in winter, respectively. Sulfate, organic matter, and geological material dominated indoor PM(2.5), followed by ammonium, nitrate, and elemental carbon. Several milligram of sulfate particles can deposited in the museum per square meter each year based on the dry deposition estimate. High concentrations of acidic particles suspended inside the museum and their depositions have high risk for the erosion of the terra-cotta figures.</p

Comparison of Elemental Carbon in Lake Sediments Measured by Three Different Methods and 150-Year Pollution History in Eastern China

Concentrations of elemental carbon (EC) were measured in a 150 yr sediment record collected from Lake Chaohu in Anhui Province, eastern China, using three different thermal analytical methods: IMPROVE_A thermal optical reflectance (TOR), STN_thermal optical transmittance (TOT), and chemothermal oxidation (CTO). Distribution patterns for EC concentrations are different among the three methods, most likely due to the operational definition of EC and different temperature treatments prescribed for each method. However, similar profiles were found for high-temperature EC fractions among different methods. Historical soot(ToR) (high-temperature EC fractions measured by the IMPROVE_A TOR method) from Lake Chaohu exhibited stable low concentrations prior to the late 1970s and a sharp increase thereafter, corresponding well with the rapid industrialization of China in the last three decades. This may suggest that high-temperature thermal protocols are suitable for differentiating between soot and other carbon fractions. A similar soot(ToR) record was also obtained from Lake Taihu (similar to 200 km away), suggesting a regional source of soot. The ratio of char(ToR) (low-temperature EC fraction measured by the IMPROVE_A TOR method, after correction for pyrolysis) to sootToR in Lake Chaohu shows an overall decreasing trend, consistent with gradual changes in fuel use from wood burning to increasing fossil fuel combustions. Average higher char(ToR)/soot(ToR) was observed in Lake Taihu than in Lake Chaohu in the past 150 years, consistent with the longer and more extensive industrialization around the Taihu region.</p

Impacts of aerosol compositions on visibility impairment in Xi'an, China

Daily particle light scattering coefficient, PM2.5 mass and chemical composition were measured in Xi&#39;an from February to December 2009. Visibility was strongly affected by anthropogenic air pollution sources, resulting in an average visual range (VR) of 6.4 &plusmn; 4.5 km. The threshold PM2.5 mass concentration, corresponding to VR &lt;10 km, was &sim;88 &mu;g m&minus;3. The revised IMPROVE equation was applied to estimate chemical extinction (bext), which on average was &sim;15% lower than measured bext. PM2.5 ammonium sulfate was the largest contributor, accounting for &sim;40% of bext, followed by organic matter (&sim;24%), ammonium nitrate (&sim;23%), and elemental carbon (&sim;9%), with minor contributions from soil dust (&sim;3%), and NO2 (&sim;1%). High secondary inorganic aerosol contributions (i.e., SO42&minus; and NO3&minus;) were the main contributors for VR &lt;5 km. A Positive Matrix Factorization (PMF) solution to the Chemical Mass Balance (CMB) receptor model showed that coal combustion was the dominant factor, accounting for &sim;52% of the dry particle light scattering coefficient, followed by the engine exhaust factor (&sim;31%). Other factors included biomass burning (&sim;12%) and fugitive dust (&sim;5%).</p

Aerosol and Air Toxics Exposure in El Paso, Texas: A Pilot Study

The Paso del Norte (PdN) region is one of the largest metropolitan areas along the U.S.-Mexico border. Different emission regulations between the two countries, particularly with respect to on-road vehicle and domestic burning, have impacted the regional concentration and human exposure of air toxics (e. g., metals, polycyclic aromatic hydrocarbons [PAHs], and carbonyls). Comprehensive air quality measurements were conducted using a mobile monitoring system at two urban-scale sites within El Paso, Texas in December 2008 as a pilot study to understand aerosol and air toxics exposure and sources in the PdN region. The measurements show clear diurnal variations due to traffic emissions and a major pollution episode likely caused by both motor vehicles and domestic burning. Wind analysis further confirms the importance of cross-border transport on elevated pollutant concentrations at the monitoring sites. The traffic-dominated periods are characterized by high fractions of black carbon, particle-bound PAHs (p-PAHs), and carbonyls in comparison with dust-related periods. During the particular pollution episode, high levels of elemental chlorine and vinyl chloride were observed that might relate to unregulated domestic burning of polyvinyl chloride (PVC) products. Although most pollution indicators show a substantial improvement in air quality over the last decade, short-term exposure to some p-PAHs, e.g., benzo[a] pyrene, is still close to the health effects screening level. Bi-national efforts are required to further reduce air toxics emissions.</p

Winter and Summer Characteristics of Airborne Particles Inside Emperor Qin's Terra-Cotta Museum, China: A Study by Scanning Electron Microscopy-Energy Dispersive X-Ray Spectrometry

Day- and nighttime total suspended particulate matter was collected inside and outside Emperor Qin&#39;s Terra-Cotta Museum in winter and summer 2008. The purpose was to characterize the winter and summer differences of indoor airborne particles in two display halls with different architectural and ventilation conditions, namely the Exhibition Hall and Pit No. 1. The morphology and elemental composition of two season samples were investigated using scanning electron microscopy and energy dispersive X-ray spectrometry. It is found that the particle size, particle mass concentration, and particle type were associated with the visitor numbers in the Exhibition Hall and with the natural ventilation in Pit No. 1 in both winter and summer. Evident winter and summer changes in the composition and physicochemical properties of the indoor suspended particulate matters were related to the source emission and the meteorological conditions. Particle mass concentrations in both halls were higher in winter than in summer. In winter, the size of the most abundant particles at the three sites were all between 0.5 and 1.0 mu m, whereas in summer the peaks were all located at less than 0.5 mu m. The fraction of sulfur-containing particles was 2-7 times higher in winter than in summer. In addition to the potential soiling hazard, the formation and deposition of sulfur-containing particles in winter may lead to the chemical and physical weathering of the surfaces of the terra-cotta statues.</p

PM2.5 and PM10-2.5 chemical composition and source apportionmentnear a Hong Kong roadway

Twenty-four-hour PM2.5 and PM10 samples were collected simultaneously at a highly trafficked roadside site in Hong Kong every sixth day from October 2004 to September 2005. The mass concentrations of PM2.5, PM10-2.5 (defined as PM10 &minus; PM2.5), organic carbon (OC), elemental carbon (EC), water-soluble ions, and up to 25 elements were determined. Investigation of the chemical compositions and potential sources revealed distinct differences between PM2.5 and PM10-2.5. The annual average mass concentrations were 55.5 &plusmn; 25.5 and 25.9 &plusmn; 15.7 g/m3 for PM2.5 and PM10-2.5, respectively. EC, OM (OM = OC &times; 1.4), and ammonium sulfate comprised over &sim;82% of PM2.5, accounting for &sim;29%, &sim;27%, and &sim;25%, respectively, of the PM2.5 mass. Low OC/EC ratios (less than 1) for PM2.5 suggested that fresh diesel-engine exhaust was a major contributor. Seven sources were resolved for PM2.5 by positive matrix factorization (PMF) model, including vehicle emissions (&sim;29%), secondary inorganic aerosols (&sim;27%), waste incinerator/biomass burning (&sim;23%), residual oil combustion (&sim;10%), marine aerosols (&sim;6%), industrial exhaust (&sim;4%), and resuspended road dust (&sim;1%). EC and OM comprised only &sim;19% of PM10-2.5. The average OC/EC ratio of PM10-2.5 was 7.8 &plusmn; 14.2, suggesting that sources other than vehicular exhaust were important contributors. The sources for PM10-2.5 determined by the PMF model included &sim;20% traffic-generated resuspension (e.g., tire dust/brake linear/petrol evaporation), &sim;17% locally resuspended road dust, &sim;17% marine aerosols, &sim;12% secondary aerosols/field burning, and &sim;11% vehicle emissions.</p