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Wan Chai, China

Yuan Z.,U.S. National Center for Atmospheric Research | Yadav V.,Washington University in St. Louis | Turner J.R.,Washington University in St. Louis | Louie P.K.K.,Revenue Tower | And 2 more authors.
Atmospheric Environment | Year: 2013

Despite extensive emission control measures targeting motor vehicles and to a lesser extent other sources, annual-average PM10 mass concentrations in Hong Kong have remained relatively constant for the past several years and for some air quality metrics, such as the frequency of poor visibility days, conditions have degraded. The underlying drivers for these long-term trends were examined by performing source apportionment on eleven years (1998-2008) of data for seven monitoring sites in the Hong Kong PM10 chemical speciation network. Nine factors were resolved using Positive Matrix Factorization. These factors were assigned to emission source categories that were classified as local (operationally defined as within the Hong Kong Special Administrative Region) or non-local based on temporal and spatial patterns in the source contribution estimates. This data-driven analysis provides strong evidence that local controls on motor vehicle emissions have been effective in reducing motor vehicle-related ambient PM10 burdens with annual-average contributions at neighborhood- and larger-scale monitoring stations decreasing by ~6μgm-3 over the eleven year period. However, this improvement has been offset by an increase in annual-average contributions from non-local contributions, especially secondary sulfate and nitrate, of ~8μgm-3 over the same time period. As a result, non-local source contributions to urban-scale PM10 have increased from 58% in 1998 to 70% in 2008. Most of the motor vehicle-related decrease and non-local source driven increase occurred over the period 1998-2004 with more modest changes thereafter. Non-local contributions increased most dramatically for secondary sulfate and secondary nitrate factors and thus combustion-related control strategies, including but not limited to power plants, are needed for sources located in the Pearl River Delta and more distant regions to improve air quality conditions in Hong Kong. PMF-resolved source contribution estimates were also used to examine differential contributions of emission source categories during high PM episodes compared to study-average behavior. While contributions from all source categories increased to some extent on high PM days, the increases were disproportionately high for the non-local sources. Thus, controls on emission sources located outside the Hong Kong Special Administrative Region will be needed to effectively decrease the frequency and severity of high PM episodes. © 2012 Elsevier Ltd. Source


Li Z.,Hong Kong University of Science and Technology | Yuan Z.,U.S. National Center for Atmospheric Research | Li Y.,Hong Kong University of Science and Technology | Lau A.K.H.,Hong Kong University of Science and Technology | And 2 more authors.
Atmospheric Environment | Year: 2015

Atmospheric particulate matter (PM) pollution is a major public health concern in Hong Kong. In this study, the spatiotemporal variations of health risks from ambient PM10 from seven air quality monitoring stations between 2000 and 2011 were analyzed. Positive matrix factorization (PMF) was adopted to identify major source categories of ambient PM10 and quantify their contributions. Afterwards, a point-estimated risk model was used to identify the inhalation cancer and non-cancer risks of PM10 sources. The long-term trends of the health risks from classified local and non-local sources were explored. Furthermore, the reason for the increase of health risks during high PM10 days was discussed. Results show that vehicle exhaust source was the dominant inhalation cancer risk (ICR) contributor (72%), whereas trace metals and vehicle exhaust sources contributed approximately 27% and 21% of PM10 inhalation non-cancer risk (INCR), respectively. The identified local sources accounted for approximately 80% of the ICR in Hong Kong, while contribution percentages of the non-local and local sources for INCR are comparable. The clear increase of ICR at high PM days was mainly attributed to the increase of contributions from coal combustion/biomass burning and secondary sulfate, while the increase of INCR at high PM days was attributed to the increase of contributions from the sources coal combustion/biomass burning, secondary nitrate, and trace metals. This study highlights the importance of health risk-based source apportionment in air quality management with protecting human health as the ultimate target. © 2015 Elsevier Ltd. Source


Li Z.,Hong Kong University of Science and Technology | Yuan Z.,U.S. National Center for Atmospheric Research | Li Y.,Hong Kong University of Science and Technology | Lau A.K.H.,Hong Kong University of Science and Technology | And 2 more authors.
Atmospheric Environment | Year: 2015

Atmospheric particulate matter (PM) pollution is a major public health concern in Hong Kong. In this study, the spatiotemporal variations of health risks from ambient PM10 from seven air quality monitoring stations between 2000 and 2011 were analyzed. Positive matrix factorization (PMF) was adopted to identify major source categories of ambient PM10 and quantify their contributions. Afterwards, a point-estimated risk model was used to identify the inhalation cancer and non-cancer risks of PM10 sources. The long-term trends of the health risks from classified local and non-local sources were explored. Furthermore, the reason for the increase of health risks during high PM10 days was discussed. Results show that vehicle exhaust source was the dominant inhalation cancer risk (ICR) contributor (72%), whereas trace metals and vehicle exhaust sources contributed approximately 27% and 21% of PM10 inhalation non-cancer risk (INCR), respectively. The identified local sources accounted for approximately 80% of the ICR in Hong Kong, while contribution percentages of the non-local and local sources for INCR are comparable. The clear increase of ICR at high PM days was mainly attributed to the increase of contributions from coal combustion/biomass burning and secondary sulfate, while the increase of INCR at high PM days was attributed to the increase of contributions from the sources coal combustion/biomass burning, secondary nitrate, and trace metals. This study highlights the importance of health risk-based source apportionment in air quality management with protecting human health as the ultimate target. © 2015 Elsevier Ltd. Source


Lau A.K.H.,U.S. National Center for Atmospheric Research | Lau A.K.H.,Hong Kong University of Science and Technology | Yuan Z.,U.S. National Center for Atmospheric Research | Yuan Z.,Hong Kong University of Science and Technology | And 2 more authors.
Science of the Total Environment | Year: 2010

Volatile organic compounds (VOCs) were measured at four stations with different environments in Hong Kong (HK) during two sampling campaigns. Positive matrix factorization was applied to characterize major VOC sources in HK. Nine sources were identified, and the spatial and seasonal variations of their contributions were derived. The most significant local VOC sources are vehicle and marine vessel exhausts or liquefied petroleum gas (LPG) at different stations. Vehicle- and marine vessel-related sources accounted for 2.9-12.7. ppbv in 2002-2003 and increased to 4.3-15.2. ppbv in 2006-2007. Different from the emission inventory, solvent-related sources only contributed 11- 19% at both sampling campaigns. Therefore, emission control from transport sector should be prioritized to alleviate ambient local VOC levels. Additionally, the contribution of aged VOC, which roughly represents contributions from regional and super-regional transport, also showed moderate increase during the four years, indicating cooperation with environmental authorities in the Pearl River Delta and beyond should be strengthened.All the anthropogenic sources contribute most to Yuen Long and least to Tap Mun. However, Tap Mun exhibited different trends in comparison with the other three stations, especially for sources of vehicle and marine vessel exhausts, LPG and paint solvents. When the local source contributions were incorporated with wind data to derive the directional dependences of sources, we may conclude that the rapid development of Yantian Container Terminal, the associated emissions from marine vessels around the Terminal and the on-site activities were likely responsible for the distinct VOC features at Tap Mun. The current impact from the Terminal is mainly concentrated in the northeastern corner of HK; however, it has the potential threat to other locations if the Terminal continues to expand in such a rapid speed in the coming years. More stringent VOC control measures on activities related to the operation of the Terminal is therefore highly recommended. © 2010 Elsevier B.V. Source


Yadav V.,University of Washington | Turner J.,University of Washington | Yuan Z.,Hong Kong University of Science and Technology | Lau A.,Hong Kong University of Science and Technology | Louie P.,Revenue Tower
Air and Waste Management Association - Air Quality Measurement Methods and Technology Conference 2012 | Year: 2012

Eleven years of collocated data collected at two sites in the Hong Kong PM10 speciation network were used to assess measurement precision and generate error structures for source apportionment modeling. Overall, the data quality was deemed to be very good. The PM10 collocated data relationships suggest that additional significant figures could be retained in the data set for some of the species. An analysis should be conducted to determine the appropriate number of significant figures. This refinement would improve the ability to assess measurement uncertainty using the collocated data and might improve the data quality. For PM10, laboratory blanks are routinely analyzed but field blanks are currently not being collected. It would be very helpful to routinely collect field blanks data so the limit of quantification (LOQ) could be assessed. The field blanks LOQs are expected to be higher than would be estimated from the laboratory blanks because there can be additional contamination of the filters during transport and handling. LOQ might provide a better estimate than the laboratory MDL or effective MDL when assessing species detectability which is an important data pre-conditioning step for source apportionment modeling. (Table Presented). Source

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