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.     

Water and sediment quality of dry season pools in a dryland river system: the upper Leichhardt River, Queensland, Australia

This article presents the geochemical characteristics and physicochemical properties of water and sediment from twelve semi-permanent, dryland pools in the upper Leichhardt River catchment, north-west Queensland, Australia. The pools were examined to better understand the quality of sediments and temporary waters in a dryland system with a well-established metal contamination problem. Water and sediment sampling was conducted at the beginning of the hydroperiod in May and September 2007. Water samples were analyzed for major solute compositions (Ca, Na, K, Mg, Cl, SO(4), HCO(3)) and water-soluble (operationally defined as the <0.45 μm fraction) metals (Cd, Cu, Pb, Zn). Sediment samples were analyzed for total extractable and bioaccessible metals (As, Cd, Cu, Pb, Zn), elemental composition and grain morphology. At the time of sampling a number of pools contained water and sediment with elevated concentrations, compared to Australian regulatory guidelines, of Cu (maximum: water 28 μg L(-1); sediment 770 mg kg(-1)), Pb (maximum: water 3.4 μg L(-1); sediment 630 mg kg(-1)) and Zn (maximum: water 150 μg L(-1); sediment 780 mg kg(-1)). Concentrations of Cd and As in pools were relatively low and generally within Australian regulatory guideline values. Localized factors, such as the interaction of waters with anthropogenic contaminants from modern and historic mine wastes (i.e. residual smelter and slag materials), exert influence on the quality of pool waters. Although the pools of the upper Leichhardt River catchment are contaminated, they do not appear to be the primary repository of water and sediment associated metals when compared to materials in the remainder channel and floodplain. Nevertheless, a precautionary approach should be adopted to mitigating human exposure to contaminated environments, which might include the installation of appropriate warning signs by local health and environmental authorities.     

Monitoring of diazinon concentrations and loadings,and identification of geographic origins consequent to stormwater runoff from orchards in the Sacramento River watershed,U.S.A

Diazinon contamination of California's rivers has resulted in placing several rivers on the federal Clean Water Act § 303d list of impaired waterways. Impaired water body listing requiresthe development of Total Maximum Daily Loads (TMDL). Previous studies identified stormwater related diazinon pulses in California rivers. This study was conducted to monitor diazinonconcentrations in the Sacramento River watershed after rainfallevents, to ascertain whether pulses could be identified and, ifconcentrations of concern were observed, to estimate loadings anddetermine geographic origins of the insecticide. TMDL developmentrequires knowledge of contaminant sources, loadings, and geographic origins. Flow and diazinon concentrations peaked in the Sacramento River at Sacramento after the three largest stormsduring January and February 1994. Diazinon concentrations peakedconsequent to each of three storms. Diazinon concentrationsmeasured in the Sacramento River at Sacramento exceeded theCalifornia Department of Fish and Game acute and chroniccriteria for protection of aquatic life during January andFebruary for nine and nineteen days, respectively. Multipleexceedances were observed throughout the watershed. Diazinon loading and geographic origin differed with each of the three storms. The design of this study provides a useful template for others attempting to identify loadings and sources of contaminants in surface waters and to rectify aquatic ecosystemcontamination from various land use practices.     

Using improved neural network model to analyze RSP,NOx and NO2 levels in urban air in Mong Kok,Hong Kong

As the health impact of air pollutants existing in ambient addresses much attention in recent years, forecasting of airpollutant parameters becomes an important and popular topic inenvironmental science. Airborne pollution is a serious, and willbe a major problem in Hong Kong within the next few years. InHong Kong, Respirable Suspended Particulate (RSP) and NitrogenOxides NO_x and NO₂ are major air pollutants due to thedominant diesel fuel usage by public transportation and heavyvehicles. Hence, the investigation and prediction of the influence and the tendency of these pollutants are ofsignificance to public and the city image. The multi-layerperceptron (MLP) neural network is regarded as a reliable andcost-effective method to achieve such tasks. The works presentedhere involve developing an improved neural network model, whichcombines the principal component analysis (PCA) technique and theradial basis function (RBF) network, and forecasting thepollutant levels and tendencies based in the recorded data. Inthe study, the PCA is firstly used to reduce and orthogonalizethe original input variables (data), these treated variables arethen used as new input vectors in RBF neural network modelestablished for forecasting the pollutant tendencies. Comparingwith the general neural network models, the proposed modelpossesses simpler network architecture, faster training speed,and more satisfactory predicting performance. This improvedmodel is evaluated by using hourly time series of RSP, NO_x and NO₂ concentrations collected at Mong Kok Roadside Gaseous Monitory Station in Hong Kong during the year 2000. By comparing the predicted RSP, NO_x and NO₂ concentrationswith the actual data of these pollutants recorded at the monitorystation, the effectiveness of the proposed model has been proven.Therefore, in authors' opinion, the model presented in the paper is a potential tool in forecasting air quality parameters and hasadvantages over the traditional neural network methods.     

Sharing the geo-Referenced Results of Climate Change Impact Research

The Prairie Adaptation Research Collaborative (PARC) has implemented an Internet Map Server (IMS) at the PARC web site (www.parc.ca) to 1) disseminate the geo-referenced results of PARC sponsored research on climate change impacts and adaptation, and 2) address data, information and knowledge management within the PARC network of researchers and partners. PARC facilitates interdisciplinary research on adaptation to the impacts of climate change in the Canadian Prairie Provinces. The web site is intended as a platform for sharing information and encouraging discussion of climate change impacts and adaptation. The IMS enables scientists and stakeholders to apply simple climate change scenarios to geo-referenced biophysical and social data, and dynamically create maps that display the geographic distribution of potential impacts of climate change. With a limited capacity for spatial analysis, most geo-processing and the climate impact modeling is done offline within a GIS environment. The IMS will serve the output from climate impact models, such that the model results can be customized by the web site user and be most readily applied to the planning and analysis of adaptation strategies.     

Assessing the effects of severe rainstorm-induced mixing on a subtropical,subalpine lake

Severe rainstorms cause vertical mixing that modifies the internal dynamics (e.g., internal seiche, thermal structure, and velocity filed) in warm polymictic lakes. Yuan Yang Lake (YYL), a subtropical, subalpine, and seasonally stratified small lake in the north-central region of Taiwan, is normally affected by typhoons accompanied with strong wind and heavy rainfall during the summer and fall. In this study, we used the field data, statistical analysis, spectral analysis, and numerical modeling to investigate severe rainstorm-induced mixing in the lake. Statistical determination of the key meteorological and environmental conditions underlying the observed vertical mixing suggests that the vertical mixing, caused by heat loss during severe rainstorms, was likely larger than wind-induced mixing and that high inflow discharge strongly increased heat loss through advection heat. Spectral analysis revealed that internal seiches at the basin scale occurred under non-rainstorm meteorological conditions and that the internal seiches under the rainstorm were modified on the increase of the internal seiche frequencies. Based upon observed frequencies of the internal seiches, a two-dimensional model was simulated and then appropriate velocity patterns of the internal seiches were determined under non-rainstorm conditions. Moreover, the model implemented with inflow boundary condition was conducted for rainstorm events. The model results showed that the severe rainstorms promoted thermal destratification and changed vertical circulation of the basin-scale, internal seiche motion into riverine flow.     

Comparison of Two Manual Methods of Nitrogen Dioxide Determination in Ambient Air

Sodium arsenite (modified Jacobs and Hochheiser method; hereafter referred as SA), the most widely used manual monitoring method for determination of nitrogen dioxide (NO₂) in ambient air, particularly in developing countries has been evaluated and compared with US EPA recommended equivalent method of TGS-ANSA (hereafter referred as ANSA). NO₂ concentrations generated from laboratory test atmosphere were analyzed by these two methods and were compared statistically. Laboratory evaluations showed that SA method has high sensitivity to different sampling conditions, which normally vary during actual field monitoring. Hence, correction factors for absorption efficiency were estimated for SA and ANSA methods. Absorption efficiency of NO₂ in SA method was found to be much lower (64%) as against the reported value of 82% at the method recommended sampling conditions, whereas for ANSA method, it was found 1.0 as against the reported value of 0.93. After applying derived correction factors, both the methods produced almost similar concentration values of NO₂.     

Exposure and inhalation risk assessment in an aluminium cast-house

To date the exposure, absorption and respiratory health effects of cast-house workers have not been described since most studies performed in the aluminium industry are focused on exposure and health effects of potroom personnel. In the present study, we assessed the external exposure and the absorbed dose of metals in personnel from the aluminium cast house. This was combined with an evaluation of respiratory complaints and the lung function of the personnel. 30 workers from an aluminium casting plant participated and 17 individuals of the packaging and distribution departments were selected as controls. The exposure was assessed by the quantification of total inhalable fume with metal fraction and by the determination of urinary aluminium, chromium, beryllium, manganese and lead concentration. Carbon monoxide (CO), carbon dioxide (CO2), aldehydes and polyaromatic hydrocarbons and man-made mineral fibres concentration were assessed as well. In order to evaluate their respiratory status each participant filled out a questionnaire and their lung function was tested by forced spirometry. Total inhalable fume exposure was maximum 4.37 mg m(-3). Exposure to the combustion gases, man-made mineral fibres and metal fume was well below the exposure limits. Beryllium could not be detected in the urine. The values of aluminium, manganese and lead in the urine were all under the respective reference value. One individual had a urinary chromium excretion above the ACGIH defined biological exposure index (BEI) of 30 microg g(-1) creatinine. There was no significant difference in any of the categories of the respiratory questionnaire and in the results of the spirometry between cast house personnel and referents (Chi-square, all p > 0.05). Exposure in cast houses seem to be acceptable under these conditions. However, peak exposure to fumes cannot be excluded and the potential risk of chromium and beryllium exposure due to the recycling of aluminium requires further attention.     

Penetration of polar brominated DBPs through the activated carbon columns during total organic bromine analysis

Total organic bromine (TOBr) is a collective parameter representing all the brominated organic disinfection byproducts (DBPs) in water samples. TOBr can be measured using the adsorption-pyrolysis method according to Standard Method 5320B. This method involves that brominated organic DBPs are separated from inorganic halides and concentrated from aqueous solution by adsorption onto the activated carbon (AC). Previous studies have reported that some commonly known brominated DBPs can partially penetrate through the AC during this adsorption step. In this work, the penetration of polar brominated DBPs through AC and ozone-modified AC was explored with two simulated drinking water samples and one chlorinated wastewater effluent sample. Polar brominated DBPs were selectively detected with a novel precursor ion scan method using electrospray ionization-triple quadrupole mass spectrometry. The results show that 3.4% and 10.4% of polar brominated DBPs (in terms of total ion intensity) in the chlorinated Suwannee River fulvic acid and humic acid samples, respectively, penetrated through the AC, and 19.6% of polar brominated DBPs in the chlorinated secondary wastewater effluent sample penetrated through the AC. The ozone-modification of AC minimized the penetration of polar brominated DBPs during the TOBr analysis.