科研成果 by Year: 2006

A significant fraction of the fine particulate matter in Hong Kong is made up of organic carbon. In order to quantitatively assess the contributions of various sources to carbonaceous aerosol in Hong Kong, a chemical mass balance (CMB) receptor model in combination with organic tracers was employed. Organic tracers including n-alkanes, polycyclic aromatic hydrocarbons (PAHs), steranes, hopanes, resin acids, cholesterol, levoglucosan, and picene in PM2.5 collected from three air monitoring sites located at roadside, urban, and rural areas in Hong Kong are quantified using gas chromatography-mass spectrometry (GC/MS) in the present study. Analyses of some overlapping species from two separate laboratories will be compared for the first time. Spatial and seasonal source contributions to organic carbon (OC) in PM2.5 from up to nine air pollution sources are assessed, including diesel engine exhaust, gasoline engine exhaust, meat cooking, cigarette smoke, biomass burning, road dust, vegetative detritus, coal combustion, and natural gas combustion. Diesel engine exhaust dominated fine organic carbon in Hong Kong (57 ± 13% at urban sites and 25 ± 2% at the rural site). Other sources that play an important role are meat cooking and biomass burning, which can account for as much as 14% of fine organic carbon. The primary sources identified by this technique explained 49%, 79%, and 94% of the measured fine organic carbon mass concentration at the rural, the urban, and the roadside sites, respectively. The unexplained fine OC is likely due to secondary organic aerosol formation.

本文主要对跨库集成检索系统Cross-Search的设计思想,系统结构及功能模块实现进行了较为全面的介绍,系统主要解决了对异构数据源的连接,统一格式转化及处理和并发检索等方面的问题,对多数据源的同步检索给出了较为理想的解决方案,并予以实现。

The data management and archiving activities of the Pacific 2001 Air Quality Study were handled by the Pacific 2001 Data Centre which was run by the National Atmospheric Chemistry (NAtChem) Database and Analysis Facility of Environment Canada. To ensure that the Pacific 2001 Air Quality Study data were archived in a common way, the NARSTO Data Exchange Standard (DES) was used as the mandatory format for the data files, partially because it allowed for the inclusion of metadata within the data files and partially because it provided the necessary flexibility for handling the many measurement types used in the study. Described in detail in the paper, the DES is now readily available to the scientific community. After each DES data file was submitted to the Data Centre, a read-and-verify program was run to check its conformity to the DES and to detect incorrect and problematic data. The errors detected by the read-and-verify program were automatically documented and an error report was sent to the data originators for data correction and resubmission. Statistical summaries and data plots were created for all data files and subsequently sent to the data originators for review and further error detection. Of the 125 data files submitted to the Data Centre, only 5 were error-free upon first submission. A test of 17 randomly selected files determined that all but two required at least four iterations of the submission-error checking-resubmission cycle in order to produce final error-free files. It was therefore concluded that both data originators and data centres alike should assume that errors exist in all submitted data files until proven differently by a set of automated error-checking programs. It was also concluded that data visualization plots and statistical summaries are highly effective tools for detecting errors in data files. Metadata associated with the measurement data were documented in Quality Assurance Project Plans that were archived in the Data Centre with the DES data files. (c) 2006 Elsevier Ltd. All rights reserved.