Time-based source apportionment of air pollutants for Hong Kong

2007 ◽  
Author(s):  
Chi On Lo
2006 ◽  
Vol 6 (4) ◽  
pp. 6467-6496 ◽  
Author(s):  
J. C. F. Lo ◽  
A. K. H. Lau ◽  
Z. B. Yuan ◽  
J. C. H. Fung ◽  
F. Chen

Abstract. This paper describes a simple but practical methodology to identify the contribution of primary and secondary air pollutants from the local/regional emission sources to Hong Kong, a highly urbanized city with complex terrain and coastlines. The meteorological model MM5 coupled with a three-dimensional, mutli-particle trajectory model is used to identify salient aspects of regional air pollutant transport characteristics during some typical meteorological conditions over the Pearl River Delta (PRD) region. Several weighting factors are determined for calculating the air mass/pollutant trajectory and are used to evaluate the local and regional contribution of primary pollutants over the PRD to Hong Kong pollution. The relationships between emission inventories, physical paths and chemical transformation rates of the pollutants, and observational measurements are formulated. The local and regional contributions of secondary pollutants are obtained by this conceptual module under different weather scenarios. Our results demonstrate that major pollution sources over Hong Kong come from regional transport. In calm-weather situations, 78% of the respirable suspended particulates (RSP) totals in Hong Kong are contributed by regional transport, and 49% are contributed by the power plants within the PRD. In normal-day situations, 71% of the RSP are contributed by regional transport, and 45% are contributed by the power plants.


2018 ◽  
Vol 214 ◽  
pp. 1-9 ◽  
Author(s):  
Xiaxia Zhang ◽  
Zibing Yuan ◽  
Wenshi Li ◽  
Alexis K.H. Lau ◽  
Jian Zhen Yu ◽  
...  

2015 ◽  
Vol 122 ◽  
pp. 892-899 ◽  
Author(s):  
Zhiyuan Li ◽  
Zibing Yuan ◽  
Ying Li ◽  
Alexis K.H. Lau ◽  
Peter K.K. Louie

2002 ◽  
Vol 27 (8) ◽  
pp. 617-630 ◽  
Author(s):  
C.K Chau ◽  
E.Y Tu ◽  
D.W.T Chan ◽  
J Burnett

2019 ◽  
Author(s):  
Pragati Rai ◽  
Markus Furger ◽  
Jay Slowik ◽  
Francesco Canonaco ◽  
Roman Fröhlich ◽  
...  

Abstract. Trace element measurements in PM10 were performed with 1 h time resolution at a rural freeway site during summer 2015 in Switzerland using the Xact multi-metals monitor. On average the Xact 625 elements (without accounting for oxygen and other associated elements) make up about 20 % of the total PM10 mass (14.6 µg m−3). Subsequently, a source apportionment by positive matrix factorization (PMF) implemented via the Source Finder software (SoFi Pro) was applied. Eight different sources were identified (notable elements in brackets) for PM10: fireworks-I (K, S, Ba, Cl), fireworks-II (K), sea salt (Cl), secondary sulfate (S), background dust (Si, Ti), road dust (Ca), traffic-related (Fe) and industrial (Zn, Pb). The major components were secondary sulfate and traffic-related followed by background dust and road dust factors, explaining 21 %, 20 %, 18 % and 16 % of the analysed PM10 elemental mass, respectively, with the factor mass not corrected for oxygen content. Further, there are minor contributions (on the order of a few percent) of sea salt and industrial sources. The regionally influenced secondary sulfate factor experiences negligible resuspension, and concentrations are similar throughout the day. The significant loads of the traffic-related and road dust factors with strong diurnal variations highlight the continuing importance of vehicle-related air pollutants at this site. Enhanced control of PMF using SoFi Pro allowed for a successful apportionment of transient sources such as the two firework factors and sea salt, which remained mixed when analysed by unconstrained PMF.


Particuology ◽  
2015 ◽  
Vol 18 ◽  
pp. 96-104 ◽  
Author(s):  
Yan Cheng ◽  
Shuncheng Lee ◽  
Zhaolin Gu ◽  
Kinfai Ho ◽  
Yunwei Zhang ◽  
...  

2020 ◽  
Author(s):  
Zhiyuan Li ◽  
Steve Hung Lam Yim ◽  
Kin-Fai Ho

<p>Land use regression (LUR) models estimate air pollutant concentrations for areas without air quality measurements, which provides valuable information for exposure assessment and epidemiological studies. In the present study, we developed LUR models for ambient air pollutants in Hong Kong, China, a typical high-density and high-rise city. Air quality measurements at sixteen air quality monitoring stations, operated by the Hong Kong Environmental Protection Department, were collected. Moreover, five categories of predictor variables, including population distribution, traffic emissions, land use variables, urban/building morphology, and meteorological parameters, were employed to establish the LUR models of various air pollutants. Then the spatial distribution of air pollutant concentrations at 1 km × 1 km grid cells were plotted. Taking fine particle (PM2.5) as an example, the developed LUR model explained 89% of variability of PM2.5 concentrations, with a leave-one-out-cross-validation R2 of 0.64. LUR modelling results for other air pollutants will be presented. In addition, further improvements on the development of LUR models will be discussed. This study can help to assess long-term exposures to air pollutants for high-density and high-rise urban areas like Hong Kong.</p>


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