Characterization of volatile organic compounds at a roadside environment in Hong Kong: An investigation of influences after air pollution control strategies

Vehicular emission is one of the important anthropogenic pollution sources for volatile organic compounds (VOCs). Four characterization campaigns were conducted at a representative urban roadside environment in Hong Kong between May 2011 and February 2012. Carbon monoxide (CO) and VOCs including methane (CH4), non-methane hydrocarbons (NMHCs), halocarbons, and alkyl nitrates were quantified. Both mixing ratios and compositions of the target VOCs show ignorable seasonal variations. Except CO, liquefied petroleum gas (LPG) tracers of propane, i-butane and n-butane are the three most abundant VOCs, which increased significantly as compared with the data measured at the same location in 2003. Meanwhile, the mixing ratios of diesel- and gasoline tracers such as ethyne, alkenes, aromatics, halogenated, and nitrated hydrocarbons decreased by at least of 37%. The application of advanced multivariate receptor modeling technique of positive matrix factorization (PMF) evidenced that the LPG fuel consumption is the largest pollution source, accounting for 60 ± 5% of the total quantified VOCs at the roadside location. The sum of ozone formation potential (OFP) for the target VOCs was 300.9 μg-O3 m-3, which was 47% lower than the value of 567.3 μg-O3 m-3 measured in 2003. The utilization of LPG as fuel in public transport (i.e., taxis and mini-buses) contributed 51% of the sum of OFP, significantly higher than the contributions from gasoline- (16%) and diesel-fueled (12%) engine emissions. Our results demonstrated the effectiveness of the switch from diesel to LPG-fueled engine for taxis and mini-buses implemented by the Hong Kong Special Administrative Region (HKSAR) Government between the recent ten years, in additional to the execution of substitution to LPG-fueled engine and restrictions of the vehicular emissions in compliance with the updated European emission standards

Oropharyngeal mucositis-specific quality-of-life measure in patients with cancer therapy.

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Assessing photochemical ozone formation in the Pearl River Delta with a photochemical trajectory model

A photochemical trajectory model (PTM), coupled with the Master Chemical Mechanism (MCM) describing the degradation of 139 volatile organic compounds (VOCs) in the troposphere, was developed and used for the first time to simulate the formation of photochemical pollutants at Wangqingsha (WQS), Guangzhou during photochemical pollution episodes between 12 and 17 November, 2007. The simulated diurnal variations and mixing ratios of ozone were in good agreement with observed data (R2=0.80, P<0.05), indicating that the photochemical trajectory model - an integration of boundary layer trajectories, precursor emissions and chemical processing - provides a reasonable description of ozone formation in the Pearl River Delta (PRD) region. Calculated photochemical ozone creation potential (POCP) indices for the region indicated that alkanes and oxygenated organic compounds had relatively low reactivity, while alkenes and aromatics presented high reactivity, as seen in other airsheds in Europe. Analysis of the emission inventory found that the sum of 60 of the 139 VOC species accounted for 92% of the total POCP-weighted emission. The 60 VOC species include C2-C6 alkenes, C6-C8 aromatics, biogenic VOCs, and so on. The results indicated that regional scale ozone formation in the PRD region can be mainly attributed to a relatively small number of VOC species, namely isoprene, ethene, m-xylene, and toluene, etc. A further investigation of the relative contribution of the main emission source categories to ozone formation suggested that mobile sources were the largest contributor to regional O3 formation (40%), followed by biogenic sources (29%), VOC product-related sources (23%), industry (6%), biomass burning (1%), and power plants (1%). The findings obtained in this study would advance our knowledge of air quality in the PRD region, and provide useful information to local government on effective control of photochemical smog in the region. © 2010 Elsevier Ltd

A computational framework to emulate the human perspective in flow cytometric data analysis

Background: In recent years, intense research efforts have focused on developing methods for automated flow cytometric data analysis. However, while designing such applications, little or no attention has been paid to the human perspective that is absolutely central to the manual gating process of identifying and characterizing cell populations. In particular, the assumption of many common techniques that cell populations could be modeled reliably with pre-specified distributions may not hold true in real-life samples, which can have populations of arbitrary shapes and considerable inter-sample variation. <p/>Results: To address this, we developed a new framework flowScape for emulating certain key aspects of the human perspective in analyzing flow data, which we implemented in multiple steps. First, flowScape begins with creating a mathematically rigorous map of the high-dimensional flow data landscape based on dense and sparse regions defined by relative concentrations of events around modes. In the second step, these modal clusters are connected with a global hierarchical structure. This representation allows flowScape to perform ridgeline analysis for both traversing the landscape and isolating cell populations at different levels of resolution. Finally, we extended manual gating with a new capacity for constructing templates that can identify target populations in terms of their relative parameters, as opposed to the more commonly used absolute or physical parameters. This allows flowScape to apply such templates in batch mode for detecting the corresponding populations in a flexible, sample-specific manner. We also demonstrated different applications of our framework to flow data analysis and show its superiority over other analytical methods. <p/>Conclusions: The human perspective, built on top of intuition and experience, is a very important component of flow cytometric data analysis. By emulating some of its approaches and extending these with automation and rigor, flowScape provides a flexible and robust framework for computational cytomics

3D time series analysis of cell shape using Laplacian approaches

Background: Fundamental cellular processes such as cell movement, division or food uptake critically depend on cells being able to change shape. Fast acquisition of three-dimensional image time series has now become possible, but we lack efficient tools for analysing shape deformations in order to understand the real three-dimensional nature of shape changes. Results: We present a framework for 3D+time cell shape analysis. The main contribution is three-fold: First, we develop a fast, automatic random walker method for cell segmentation. Second, a novel topology fixing method is proposed to fix segmented binary volumes without spherical topology. Third, we show that algorithms used for each individual step of the analysis pipeline (cell segmentation, topology fixing, spherical parameterization, and shape representation) are closely related to the Laplacian operator. The framework is applied to the shape analysis of neutrophil cells. Conclusions: The method we propose for cell segmentation is faster than the traditional random walker method or the level set method, and performs better on 3D time-series of neutrophil cells, which are comparatively noisy as stacks have to be acquired fast enough to account for cell motion. Our method for topology fixing outperforms the tools provided by SPHARM-MAT and SPHARM-PDM in terms of their successful fixing rates. The different tasks in the presented pipeline for 3D+time shape analysis of cells can be solved using Laplacian approaches, opening the possibility of eventually combining individual steps in order to speed up computations