A Variance Estimator for Constrained Estimates of Change in Relative Categorical Frequencies

Consistent estimators of change and state becomes an issue when sample data come from a mix of permanent and temporary observation units. A joint maximum likelihood estimator of state and change creates estimates of state that depend on antecedent viz. posterior survey results and may differ from estimates of state derived from a single-date analysis of the sample data. A constrained estimator of change in relative categorical frequencies that eliminates this potential inconsistency is proposed and a model based estimator of their sampling variance is developed. The performance of the constrained estimator is quantified against six criteria and a joint maximum likelihood estimator in simulated sampling from 15 populations with three combinations of permanent and temporary samples, four to six categorical class attributes, and constant size between sampling dates. Bias of the constrained estimators was negligible but larger than for joint maximum likelihood estimators. Mean absolute deviations and variances of constrained estimators were generally at par with the joint estimators. Constrained estimators of root mean square errors and achieved coverage of nominal confidence intervals of constrained estimators were occasionally better. A generalized variance function for the constrained estimates of change is provided as a computational shortcut.     

Development of monitoring technology for airborne particulate matter

Particulate matter suspended in the air has adverse effects onhuman health. Its level of concentration is an important parameter in evaluating the degree of hazard it poses to the atmosphere. Conventional methods used in measuring particulatematter are often filter-based, which indicates some disadvantagesbecause such a base requires labor and time. In this study, to achieve real-time measurements, a new electrical method was developed for measuring PM10 and PM2.5 concentrations. The basicprinciple is to electrically charge particles passing through thePM inlet using a corona charger and measure the currents createdby charged particles to obtain the number concentration of particulate matter. A new type inlet based on the particle cupimpactor configuration was designed and its performance was evaluated. A unipolar diffusion charger was developed and thecharger's efficiency was determined experimentally in terms ofPn, which represents the penetration through the charger,P, times the average charge number acquired by a particle,n, for different particle sizes. The correlation was constructed between the PM10 (or the PM2.5) mass concentrationsand the electrical currents due to particles, which were chargedby the diffusion charger.     

Analysis of pollutant levels in central Hong Kong applying neural network method with particle swarm optimization

Air pollution has emerged as an imminent issue in modernsociety. Prediction of pollutant levels is an importantresearch topic in atmospheric environment today. For fulfillingsuch prediction, the use of neural network (NN), and inparticular the multi-layer perceptrons, has presented to be acost-effective technique superior to traditional statisticalmethods. But their training, usually with back-propagation (BP)algorithm or other gradient algorithms, is often with certaindrawbacks, such as: 1) very slow convergence, and 2) easilygetting stuck in a local minimum. In this paper, a newlydeveloped method, particle swarm optimization (PSO) model, isadopted to train perceptrons, to predict pollutant levels, andas a result, a PSO-based neural network approach is presented. The approach is demonstrated to be feasible and effective bypredicting some real air-quality problems.     

Multi-objective, decision-based assessment of a water quality monitoring network in a river system

Water quality monitoring network design has historically tended to use experience, intuition and subjective judgement in locating monitoring stations. Better design procedures to optimize monitoring systems need to simultaneously identify significant planning objectives and consider a number of social, economic and environmental constraints. The consideration of multiple objectives may require further decision analysis to determine the preference weights associated with the objectives to aid in the decision-making process. This may require the application of an optimization study to extract such information from decision makers or experts and to evaluate the overall effectiveness of locating strategies. This paper assesses the optimal expansion and relocation strategies of a water quality monitoring network using a two-stage analysis. The first stage focuses on the information retrieval of preference weights with respect to the designated planning objectives. With the aid of a pre-emptive goal programming model, data analysis is applied to obtain the essential information from the questionnaire outputs. The second stage then utilizes a weighted multi-objective optimization approach to search for the optimal locating strategies of the monitoring stations in the river basin. Practical implementation is illustrated by a case study in the Kao-Ping River Basin, south Taiwan.     

Optimal and suboptimal control of anaerobic digesters

Anaerobic digester failure due to entry of inhibitors or sudden changes in the feed substrate concentration may be encompassed beneficially by applying optimal control theory. An almost proportional relationship between the dilution rate and the methane production rate leads to a simple suboptimal control law with only minor loss in performance, after the occurrence of the above mentioned events.     

Global and Regional Distribution of Carbon Monoxide from MOPITT: Seasonal Distribution at 700 hPa

The Measurement of Pollution in the Troposphere (MOPITT) instrument is an eight-channel gas correlation radiometer, which was launched on the Earth Observing System (EOS) Terra satellite in 1999. Carbon monoxide (CO) is one of the important trace gases because its concentration in the troposphere directly influences the concentrations of tropospheric hydroxyl (OH), which controls the lifetimes of tropospheric trace gases. CO traces the transport of global and regional pollutants from industrial activities and large scale biomass burning. The global and regional distributions of CO were analyzed using the MOPITT data for East Asia, which were compared with the ozone distributions. In general, seasonal CO variations are characterized by a peak in the spring, which decrease in the summer. This work also revealed that the seasonal cycles for CO are at a maximum in the spring and a minimum in the summer, with average concentrations ranging from 118 to 170 ppbv. The monthly average for CO shows a similar profile to that for O3. This fact clearly indicates that the high concentration of CO in the spring is possibly due to one of two causes: the photochemical production of CO in the troposphere, or the transport of the CO into East Asia. The seasonal cycles for CO and O3 in East Asia are extensively influenced by the seasonal exchanges of different air mass types due to the Asian monsoon. The continental air masses contain high concentrations of O3 and CO, due to the higher continental background concentrations, and sometimes to the contribution from regional pollution. In summer this transport pattern is reversed, where the Pacific marine air masses that prevail over Korea bring low concentrations of CO and O3, which tend to give the apparent summer minimums.     

Organophosphate flame retardants and plasticisers in wastewater treatment plants

Previous studies have revealed that chlorinated and non-chlorinated organophosphorous flame retardants and plasticisers are important contaminants in German surface waters and it has been demonstrated that wastewater treatment plants contribute to the emission of these substances. In this study temporal development as well as elimination efficiency were determined in two wastewater treatment plants (STP) in the Ruhr/Rhine area at different stages of the wastewater treatment process. The samples were analysed for the non-chlorinated organophosphate esters tri-n-butylphosphate (TnBP), tri-iso-butylphosphate (TiBP), tris-(butoxyethyl)-phosphate (TBEP) and triphenylphosphate (TPP) and the chlorinated organophosphate esters tris-(2-chloro, 1-methylethyl)-phosphate (TCPP), tris-(2-chloro-, 1-chloromethylethyl)-phosphate (TDCP) and tris-(2-chloroethyl)-phosphate (TCEP). The study showed that there were significant differences in the elimination of chlorinated and non-chlorinated organophosphorous flame retardants. The elimination rates ranged from 57-86% for TiBP, TnBP and TBEP at both STP's. No elimination of the chlorinated flame retardants TCPP, TDCP and TCEP was observed in any of the sampled STPs. At both STPs the first treatment steps and the final filtration did not contribute to the elimination of the non-chlorinated organophosphorous flame retardants while the aeration step did. At both STPs the efficiency of the cleaning process concerning the flame retardants was comparable. Thus the type of construction of the STP was not relevant for the elimination of these substances. Additionally a strong day-to-day variation was observed, while in one STP a temporal trend for TCPP during the week was found.     

Selection and Calibration of Numerical Modeling in Flow and Water Quality

Numerical modeling is frequently used in coastal engineering research and application. One possible issue associated with using this method however, is that initial outcomes might differ from expectation. Modeling manipulation addresses this issue by changing the initial parameters which in turn affects the final output results. The advancement of modeling techniques in recent years has seen a gradual but steady accruement of knowledge regarding the relationship between input parameters and possible outputs, which has resulted in improved accuracy and efficiency methods. The advancements within this field have predominantly occurred on an individual basis and as such lack standardisation. An expert numerical modeler may use this knowledge subconsciously, yet may not know how to convey it to the model users. This paper has been written to introduce a systematic intelligent coding schema designed to organise current coastal engineering modeling manipulation knowledge into a standardised format. This system is relevant to the development of appropriate strategies for improved accuracy and efficiency as well as model modification to simulate specific real phenomena in prototype application cases.     

Effects of meteorological conditions on PM10 concentrations - A study in Macau

Review on the annual PM₁₀ concentrations over a 10-year period shows that Macau is subjected to severe fine particulate pollution. Investigations of its variation in monthly and daily time scales with the local meteorological records reveal further details. It is found that a distinct feature of the Asian monsoon climates, the changes of wind direction, mainly controls the general trend of PM₁₀ concentration in a year. The monsoon driven winter north-easterly winds bring upon Macau dry and particle enriched air masses leading to a higher concentration in that period while the summer south-westerly winds transport humid and cleaner air to the region leading to a lower PM₁₀ value. This distinct seasonal feature is further enhanced by the lower rainfall volume and frequency as well as mixing height in winter and their higher counterparts in summer. It is also found that the development of tropical cyclones near Macau could also impose episode like PM₁₀ concentration spikes due to the pre-typhoon induced stagnant air motion followed by the swing of wind direction to the northerly.     

Linking Land Cover and Water Quality in New York City’S Water Supply Watersheds

The Catskill/Delaware reservoirs supply 90% of New York City’s drinking water. The City has implemented a series of watershed protection measures, including land acquisition, aimed at preserving water quality in the Catskill/Delaware watersheds. The objective of this study was to examine how relationships between landscape and surface water measurements change between years. Thirty-two drainage areas delineated from surface water sample points (total nitrogen, total phosphorus, and fecal coliform bacteria concentrations) were used in step-wise regression analyses to test landscape and surface-water quality relationships. Two measurements of land use, percent agriculture and percent urban development, were positively related to water quality and consistently present in all regression models. Together these two land uses explained 25 to 75% of the regression model variation. However, the contribution of agriculture to water quality condition showed a decreasing trend with time as overall agricultural land cover decreased. Results from this study demonstrate that relationships between land cover and surface water concentrations of total nitrogen, total phosphorus, and fecal coliform bacteria counts over a large area can be evaluated using a relatively simple geographic information system method. Land managers may find this method useful for targeting resources in relation to a particular water quality concern, focusing best management efforts, and maximizing benefits to water quality with minimal costs.The United States Environmental Protection Agency through its Office of Research and Development funded and managed the research described here. It has been subjected to Agency’s administrative review and approved for publication as an EPA document.