Mathematical models for accurate prediction of atmospheric visibility with particular reference to the seasonal and environmental patterns in Hong Kong

Atmospheric visibility impairment has gained increasing concern as it is associated with the existence of a number of aerosols as well as common air pollutants and produces unfavorable conditions for observation, dispersion, and transportation. This study analyzed the atmospheric visibility data measured in urban and suburban Hong Kong (two selected stations) with respect to time-matched mass concentrations of common air pollutants including nitrogen dioxide (NO(2)), nitrogen monoxide (NO), respirable suspended particulates (PM(10)), sulfur dioxide (SO(2)), carbon monoxide (CO), and meteorological parameters including air temperature, relative humidity, and wind speed. No significant difference in atmospheric visibility was reported between the two measurement locations (p > or = 0.6, t test); and good atmospheric visibility was observed more frequently in summer and autumn than in winter and spring (p < 0.01, t test). It was also found that atmospheric visibility increased with temperature but decreased with the concentrations of SO(2), CO, PM(10), NO, and NO(2). The results showed that atmospheric visibility was season dependent and would have significant correlations with temperature, the mass concentrations of PM(10) and NO(2), and the air pollution index API (correlation coefficients mid R: R mid R: > or = 0.7, p < or = 0.0001, t test). Mathematical expressions catering to the seasonal variations of atmospheric visibility were thus proposed. By comparison, the proposed visibility prediction models were more accurate than some existing regional models. In addition to improving visibility prediction accuracy, this study would be useful for understanding the context of low atmospheric visibility, exploring possible remedial measures, and evaluating the impact of air pollution and atmospheric visibility impairment in this region.     

Compensation effect during the pyrolysis of tyres and bamboo

Pyrolysis parameters (e.g. pre-exponential factor A, and activation energy E) of two waste materials, namely, tyre rubber and bamboo scaffolding, based on the Arrhenius equation were obtained from weight loss data via thermogravimetry at different heating rates. The compensation effect, which suggests that the linear variation in the pre-exponential factor and the activation energy, was observed for these materials. This can be attributed to the variety of active sites over the reactant surface in the course of decomposition. The calculated data from several revised, first-order models were compared with similar models in the literature. It has been shown that both literature and our calculated data exhibit high linearity in terms of ln A and E, revealing that the latter agree well with other researchers’ work.     

Influence of indoor air quality (IAQ) objectives on air-conditioned offices in Hong Kong

It is costly to sample all air pollutants of a general community. Air sampling should be conducted based on a practical assessment strategy and monitoring plan. In Hong Kong, the Environmental Protection Department (HKEPD) launched an Indoor Air Quality (IAQ) certification scheme to grade workplace IAQ as 'Excellent' or 'Good' by measuring the levels of nine common indoor air pollutants, namely carbon dioxide (CO(2)), carbon monoxide (CO), respirable suspended particulates (RSP), nitrogen dioxide (NO(2)), ozone (O(3)), formaldehyde (HCHO), total volatile organic compounds (TVOC), radon (Rn), and airborne bacteria count (ABC). Although average office IAQ performance has been improved since the implementation of this certification scheme, there are still resource issues and technical difficulties. To streamline the assessment of office IAQ performance, this study proposes a simple index of IAQ benchmarks formulated in compliance with the HKEPD requirements. In particular, three of the nine listed common air pollutants were selected as the 'representatives' for the overall satisfactory IAQ. Together with the assessment results of 422 Hong Kong air-conditioned offices, the index was evaluated in terms of test sensitivity, specificity and predictive values. Proved to be feasible to describe the IAQ of some air-conditioned offices, this IAQ index would be a useful tool for policymakers, building owners and professionals to quantify IAQ performance in offices and to make decisions on resources and manpower management for efficient mitigation actions.     

Production of activated carbons from waste tire--process design and economical analysis

The process design and economic analysis of process plants to produce activated carbons from waste tires and coal have been performed. The potential range of products from each process has been considered, namely for waste tire--pyro-gas, active carbon, carbon black and pyro-oil; for coal--pyro-gas and active carbons. Sensitivity analyses have been carried out on the main process factors; these are product price, production capacity, total production cost, capital investment and the tipping fee. Net present values for the two plants at various discount factors have been determined and the internal rates of return have been determined as 27.4% and 18.9% for the waste tire plant and the coal plant, respectively.     

An approach to assessing the probability of unsatisfactory radon in air-conditioned offices of Hong Kong

In order to maintain an acceptable Indoor Air Quality (IAQ), policies, strategies and guidelines have been developed worldwide and exposure concentrations of the indoor radon have been specified. Mapping indoor radon levels for a region could be done with intensive measurements on a large number of samples. To obtain the most accurate estimate of the levels with the uncertainties specified, a statistical model has been developed in this study to predict the fractions of samples in a region having an average radon level above the action levels of 150Bqm(-3) and 200Bqm(-3). The model was based on a transformation of the variation from a small sample set of data to a population geometric distribution via an estimator, known as the 'sample correction factor'. Using a dataset from a cross-sectional measurement of indoor radon levels in 216 Hong Kong offices, where the mean was 37.2Bqm(-3) and the 68% range was from 17.3Bqm(-3) to 80.3Bqm(-3), the 'sample correction factor' was evaluated and tested by the Monte-Carlo simulations. The model estimates of the fractions above the indoor radon action levels 150Bqm(-3) and 200Bqm(-3) (1.2-7.7% and 0.4-4.1% for a sample size of 20, 2.8-5.1% and 0.8-2.4% for a sample size of 60) were demonstrated to be consistent with those determined from the dataset (3.5% and 1.4%). With the 'sample correction factor' thus quantified, it will be possible to provide the required data for the policymakers making appropriate decisions on resources and manpower management.     

Identifying and mapping local bycatch hotspots of loggerhead sea turtles using a GIS-based method: implications for conservation

Fisheries bycatch of marine megafauna is a worldwide conservation issue. In this study, we propose a method for generating reliable maps of sea turtle bycatch hotspots. Based on a well-defined area of fishing effort determined from the longline sets monitored in 2007 and 2010, we calculated the fishing area with the highest turtle bycatch density for both years. Our results show that it is important to consider all the components of fishing effort (area, number of hooks and soak time) in order to standardize the bycatch events, and thus the spatial density of the captures can be considered an index of abundance and aggregation of the species. Moreover, the high-resolution level of the analyses was useful for investigating the cumulative effect of the longline sets, which often overlap, and made it possible to correctly map the capture density and the intensity of the fishing effort at any given location.     

Reflectance properties and physiological responses of Salicornia virginica to heavy metal and petroleum contamination

Wetland ecosystems of California are located in highly populated areas and subject to high levels of contamination. Monitoring of wetlands to assess degrees of pollution damage requires periodic retrieval of information over large areas, which can be effectively accomplished by rapidly evolving remote sensing technologies. The biophysical principles of remote sensing of vegetation under stress need to be understood in order to correctly interpret the information obtained at the scale of canopies. To determine the potential to remotely characterize and monitor pollution, plants of Salicornia virginica, a major component of wetland communities in California, were treated with two metals and two crude oil types to study their sensitivity to pollutants and how this impacted their reflectance characteristics. Several growth and physiological parameters, as well as shoot reflectance were measured and correlated with symptoms and contamination levels. Significant differences between treatments were found in at least some of the measured parameters in all pollutants. Reflectance was sensitive to early stress levels only for cadmium and the lightweight petroleum. Pollutants that differ in their way of action also had different plant reflectance signatures. The high degree of correlation between reflectance features and stress indicators highlights the potential of using remote sensing to assess the type and degree of pollution damage.