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.     

Flue gas treatability studies: a tool for techno-economic control of industrial air pollution

Air pollution problems in developing countries have gained larger fraction in the last decade especially due to non functioning and non implementation of effective air pollutioncontrol devices in industries. In industrial wastewater management, adequate treatability studies are conducted to arrive at a techno-economic treatment option. However no suchstudies were done for reducing air pollution or emission fromindustries until now in India. Little information was availableabout such studies in other countries. This article provides information about a novel technique known asflue gas treatability studies and to undertake such studies, a pilot scale system is installed in Air Pollution Control Divisionof M/s National Environmental Engineering research Institute, NEERI, Nagpur-20, India. This study is a tool for techno-economicselection of air pollution control systems specially for small/medium scale industrial emissions.     

Geochemical assessment of metal concentrations in sediment core of Korangi Creek along Karachi Coast, Pakistan

Sediment core from Korangi Creek, one of the polluted coastal locations along the Karachi Coast Pakistan, was collected to trace the history of marine pollution and to determine the impact of industrial activity in the area. Down core variation of metals such as Ca, K, Mg, Al, S, Ti, V, Cr, Mn, Fe, Ni, Cu and Zn was studied in the 72.0 cm core. Nuclear analytical techniques, proton induced X-rays emission (PIXE), was employed to ascertain the chemical composition in sediment core. Grain size analysis and sediment composition of cored samples indicated that Korangi creek sediments are clayey in nature. Correlation matrix revealed a strong association of Ni, Cu, Cr and Zn with Fe and Mn. To infer anthropogenic input, enrichment factor (EF), degree of contamination and pollution load index were calculated. EF showed severe enrichment in surface sediment for Ni, Cu, Cr and Zn, indicating increased industrial effluents discharge in recent years. The study suggests that heavy metal discharge in the area should be regulated. If the present trend of enrichment is allowed to continue unabated, it is most likely that the local food web complexes in the creek might be at highest risk.     

Validating an evidence-based, self-rated fall risk questionnaire (FRQ) for older adults

Background

Falls are a common, serious, and often unrecognized problem facing older adults. The objective of this study was to provide an initial clinical and statistical validation for a public health strategy of fall risk self-assessment by older adults using a Fall Risk Questionnaire (FRQ).

Methods

Adults age 65 + (n = 40) were recruited at a Los Angeles Veterans Affairs (VA) medical facility and at a local assisted living facility. Participants completed the FRQ self-assessment and results were compared to a “gold standard” of a clinical evaluation of risks using the American/British Geriatrics Society guidelines to assess independent predictors of falls: history of previous falls, fear of falling, gait/balance, muscle weakness, incontinence, sensation and proprioception, depression, vision, and medications. For the comparison, we used an iterative statistical approach, weighing items based on relative risk.

Results

There was strong agreement between the FRQ and clinical evaluation (kappa = .875, p < .0001). Individual item kappa values ranged from .305-.832. After dropping one FRQ item (vision risk) because of inadequate agreement with the clinical evaluation (kappa = .139, p = .321), the final FRQ had good concurrent validity.

Conclusions

The FRQ goes beyond existing screening tools in that it is based on both evidence and clinical acceptability and has been initially validated with clinical examination data. A larger validation with longitudinal follow-up should determine the actual strength of the FRQ in predicting future falls.     

Effects of significant damage of flame gap surfaces in flameproof electrical apparatus on flame gap efficiency

Electrical apparatus for use in the presence of explosive gas atmospheres has to be specially designed to prevent the apparatus from igniting the gas. Flameproof design is one of several options, and one requirement is then that any holes and slits in the enclosure wall be designed to prevent a possible gas explosion inside the enclosure from being transmitted to an explosive gas cloud outside it. Current standards (IEC) require that joint surfaces have a surface roughness of <6.3 μm. Any damaged joint surface has be restored to this quality. The present investigation has demonstrated that flame gap surfaces in flameproof electrical apparatuses can suffer considerable mechanical and corrosive damage before the flame gaps no longer function satisfactorily. In some cases very significant mechanical surface damage in fact improves the gap performance. This indicates that current high costs of repairing and replacing flameproof electrical apparatus in process plants offshore and onshore can be reduced considerably without any increase of the explosion risk.     

Forensic fingerprinting and source identification of the 2009 Sarnia (Ontario) oil spill

This paper presents a case study in which integrated forensic oil fingerprinting and data interpretation techniques were used to characterize the chemical compositions and determine the source of the 2009 Sarnia (Ontario) oil spill incident. The diagnostic fingerprinting techniques include determination of hydrocarbon groups and semi-quantitative product-type screening via gas chromatography (GC), analysis of oil-characteristic biomarkers and the extended suite of parent and alkylated PAH (polycyclic aromatic hydrocarbon) homologous series via gas chromatography-mass spectrometry (GC-MS), determination and comparison of a variety of diagnostic ratios of "source-specific marker" compounds, and determination of the weathering degree of the spilled oil, and whether the spilled oil hydrocarbons have been mixed with any other "background" chemicals (biogenic and/or pyrogenic hydrocarbons). The detailed chemical fingerprinting data and results reveal the following: (1) all four samples are mixtures of diesel and lubricating oil with varying percentages of diesel to lube oil. Both samples 1460 and 1462 are majority diesel-range oil mixed with a smaller portion of lube oil. Sample 1461 contains slightly less diesel-range oil. Sample 1463 is majority lubricating-range oil. (2) The diesel in the four diesel/lube oil mixture samples was most likely the same diesel and from the same source. (3) The spill sample 1460 and the suspected-source sample 1462 have nearly identical concentrations and distribution patterns of target analytes including TPHs, n-alkane, PAHs and biomarker compounds; and have nearly identical diagnostic ratios of target compounds as well. Furthermore, a perfect "positive match" correlation line (with all normalized ratio data points falling into the straight correlation line) is clearly demonstrated. It is concluded that the spill oil water sample 1460 (#1, from the water around the vessel enclosed by a boom) matches with the suspected source sample 1462 (#3, from the vessel engine room bilge pump). (4) From the n-alkane and PAH analysis, it appears that the oil in the spill sample 1460 is slightly more weathered in comparison with sample 1462. The minor differences in fingerprints of two samples were most likely caused by weathering effects. (5) Sample 1461 (#2, from the vessel engine room bilge) and sample 1463 (#4, from the vessel bilge waste collection tank) demonstrated significantly different fingerprints and diagnostic ratios of target compounds from that of spill sample 1460. This was caused most likely by percentages of diesel to lube oil in these two samples different from that in spill sample 1460.     

Spatial distributions and eco-partitioning of soil biogeochemical properties in the Everglades National Park

Large-scale ecosystem restoration efforts, such as those in the Florida Everglades, can be long-term and resource intensive. To gauge success, restoration efforts must have a means to evaluate positive or negative results of instituted activities. Edaphic properties across the Everglades landscape have been determined to be a valuable metric for such evaluation, and as such, a baseline condition from which to make future comparisons and track ecosystem response is necessary. The objectives of this work were to document this baseline condition in the southern most hydrologic unit of the Everglades, Everglades National Park (ENP), and to determine if significant eco-partitioning of soil attributes exists that would suggest the need to focus monitoring efforts in particular eco-types within the ENP landscape. A total of 342 sites were sampled via soil coring and parameters such as total phosphorus (TP), total nitrogen (TN), total carbon (TC), total calcium, total magnesium, and bulk density were measured at three depth increments in the soil profile (floc, 0-10 cm, and 10-20 cm). Geostatistical analysis and GIS applications were employed to interpolate site-specific biogeochemical properties of soils across the entire extent of the ENP. Spatial patterns and eco-type comparisons suggest TC and TN to be highest in Shark River Slough (SRS) and the mangrove interface (MI), following trends of greatest organic soil accumulation. However, TP patterns suggest greatest storages in MI, SRS, and western marl and wet prairies. Eco-partitioning of soil constituents suggest local drivers of geology and hydrology are significant in determining potential areas to focus monitoring for future change detection.