Judith C. Chow

Chemically-speciated on-road PM2.5 motor vehicle emission factors in Hong Kong.

PM(2.5) (particle with an aerodynamic diameter less than 2.5microm) was measured in different microenvironments of Hong Kong (including one urban tunnel, one Hong Kong/Mainland boundary roadside site, two urban roadside sites, and one urban ambient site) in 2003. The concentrations of organic carbon (OC), elemental carbon (EC), water-soluble ions, and up to 40 elements (Na to U) were determined. The average PM(2.5) mass concentrations were 229+/-90, 129+/-95, 69+/-12, 49+/-18microg m(-3) in the urban tunnel, cross boundary roadside, urban roadside, and urban ambient environments, respectively. Carbonaceous particles (sum of organic material [OM] and EC) were the dominant constituents, on average, accounting for approximately 82% of PM(2.5) emissions in the tunnel, approximately 70% at the three roadside sites, and approximately 48% at the ambient site, respectively. The OC/EC ratios were 0.6+/-0.2 and 0.8+/-0.1 at the tunnel and roadside sites, respectively, suggesting carbonaceous aerosols were mainly from vehicle exhausts. Higher OC/EC ratio (1.9+/-0.7) occurred at the ambient site, indicating contributions from secondary organic aerosols. The PM(2.5) emission factor for on-road diesel-fueled vehicles in the urban area of Hong Kong was 257+/-31mg veh(-1) km(-1), with a composition of approximately 51% EC, approximately 26% OC, and approximately 9% SO(4)(=). The other inorganic ions and elements made up approximately 11% of the total PM(2.5) emissions. OC composed the largest fraction (approximately 51%) in gasoline and liquid petroleum gas (LPG) emissions, followed by EC (approximately 19%). Diesel engines showed higher emission rates than did gasoline and LPG engines for most pollutants, except for V, Br, Sb, and Ba.

Characteristics and source apportionment of PM1 emissions at a roadside station

The mass concentrations of PM(1) (particles less than 1.0 μm in aerodynamic diameter), organic carbon (OC), elemental carbon (EC), water-soluble ions, and up to 25 elements were reported for 24h aerosol samples collected every sixth day at a roadside sampling station in Hong Kong from October 2004 to September 2005. Annual average PM(1) mass concentration was 44.5 ± 19.5 μg m(-3). EC, OM (organic matter, OC × 1.2), and SO(4)(=) were the dominant components, accounting for ∼ 36%, ∼ 26%, and ∼ 24% of PM(1), respectively. Other components, i.e., NO(3)(-), NH(4)(+), geological material, trace elements and unidentified material, comprised the remaining ∼ 14%. Annual average OC/EC ratio (0.6 ± 0.3) was low, indicating that primary vehicle exhaust was the major source of carbonaceous aerosols. The seasonal variations of pollutants were due to gas-particle partitioning processes or a change in air mass rather than secondary aerosol produced locally. Vehicle exhaust, secondary aerosols, and waste incinerator/biomass burning were dominant air pollution sources, accounting for ∼ 38%, ∼ 22% and ∼ 16% of PM(1), respectively. Pollution episodes during summer (May-August) which were frequently accompanied by tropical storms or typhoons were dominated by vehicle emissions. During winter (November-February) pollution episodes coincided with northeasterly monsoons were characterized by secondary aerosols and incinerator/biomass burning emissions.

Receptor Models and Measurements for Identifying and Quantifying Air Pollution Sources

Abstract Air pollution sources have spatial, temporal, and chemical patterns from a large number of individual emitters that are superimposed at a large number of receptors. For suspended particulate matter, particle size is also relevant to the source and its zone of influence. Because the number of individual emitters far exceeds the number of components in these patterns than can be practically measured, it is necessary to group sources into categories or types that have similar patterns. This chapter describes several receptor models in common use, identifies source and receptor characteristics used in these models, specifies available measurement methods used to quantify those characteristics, and discusses some of the uncertainties and false source identifications to be avoided in a receptor-modeling study. The emphasis is on particulate matter pollution, supplemented with commonly measured gaseous components.