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The UV and humidity sensing properties of ZnO nanorods prepared by arc discharge have been studied. Scanning electron microscopy and photoluminescence spectroscopy were carried out to analyze the morphology and optical properties of the as-synthesized ZnO nanorods. Proton induced x-ray emission was used to probe the impurities in the ZnO nanorods. A large quantity of high purity ZnO nanorod structures were obtained with lengths of 0.5-1 microm. The diameters of the as-synthesized ZnO nanorods were found to be between 40 and 400 nm. The nanorods interlace with each other, forming 3D networks which make them suitable for sensing application. The addition of a polymeric film-forming agent (BASF LUVISKOL VA 64) improved the conductivity, as it facilitates the construction of conducting networks. Ultrasonication helped to separate the ZnO nanorods and disperse them evenly through the polymeric agent. Improved photoconductivity was measured for a ZnO nanorod sensor annealed in air at 200 degrees C for 30 min. The ZnO nanorod sensors showed a UV-sensitive photoconduction, where the photocurrent increased by nearly four orders of magnitude from 2.7 x 10(-10) to 1.0 x 10(-6) A at 18 V under 340 nm UV illumination. High humidity sensitivity and good stability were also measured. The resistance of the ZnO nanorod sensor decreased almost linearly with increasing relative humidity (RH). The resistance of the ZnO nanorods changed by approximately five orders of magnitude from 4.35 x 10(11) Omega in dry air (7% RH) to about 4.95 x 10(6) Omega in 95% RH air. It is experimentally demonstrated that ZnO nanorods obtained by the arc discharge method show excellent performance and promise for applications in both UV and humidity sensors.

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Despite intensive research over the past three decades, a generally accepted standard method to measure black carbon (BC) or elemental carbon (EC) still does not exist. Data on BC and EC concentrations are method specific and can differ widely. This work was motivated by the lack of any prior study that established the variability between these two measures of carbonaceous particulate matter. Measurements of BC and EC were performed at different locations across Asia and the South Pacific in both urban and suburban locations. Filter samples were collected during the winter of 2007 to the winter of 2010 and analyzed for both BC and EC. EC was measured using the Interagency Monitoring of Protected Visual Environments (IMPROVE_A) protocol. Black carbon was measured by the EELS reflectometer (Diffusion Systems, Ltd). Bangladesh had the highest correlation coefficient of 0.93. Bangkok, Thailand on the other hand had the lowest correlation coefficient of 0.34. A review of previously reported source apportionment of BC concentrations in these locations showed that New Zealand had the highest percentage (82%) of BC from biomass while Mongolia had the lowest percentage of 3.1%. The fraction of BC emissions from diesel vehicles was found predominant in Mumbai, India with values as high as 80%. Mongolia had the lowest emission of BC from diesel vehicle (5.4%) with coal-and biomass-combustion being the dominant sources.

In Bangladesh, the ambient air within Dhaka city is highly polluted by motor vehicle and brick kiln emissions. In addition, meteorological conditions during the winter cause increases in the fine particulate matter concentrations by factors of 4 to 5 fold compared to the rainy season. To understand the contribution of possible pollution sources, compositional data for both the coarse and fine fractions samples collected between May 2001 and March 2005 have been analyzed using Positive Matrix Factorization (PMF). The results were compared with the previous source apportionment results. Conditional Probability Function (CPF) plots were developed for each source using local wind data to explore the directionality of local sources. Back trajectory ensemble methods were used to identify potential source regions and pathways of transboundary transport of PM 2.2 apportioned sources. The Potential Source Contribution Function (PSCF) domain extended around the receptor site in Dhaka (23.77°N, 90.38°E) over the range from 1.5° to 42.5°N and 56.5° to 110.5°E. The PSCF results are compared to the conditional probability function (CPF) analyses that use 3 hour average local wind directional data to determine the likely directions for the sources. Both PSCF and CPF help to identify the potential source locations, but on different distance scales. These analyses demonstrate that coarse particles are dominated by local sources. However, local and regional source contributed to the elevated fine PM levels in Dhaka. Thus, regional control efforts will be required in addition to local initiatives to improve the air quality in mega cities in this region like Dhaka.