Air pollution sampling site selection is one of the most important and yet most vexing of the problems faced by those responsible for regional and urban air quality management and for the attainment and maintenance of national ambient air quality standards. Since one cannot hope to monitor air quality at all locations at all times, selection of sites to give a reliable and realistic picture of air quality becomes a major issue and at the same time a difficult task. The location (configuration) and the number of stations may be based on many factors, some of which may depend on limited resources, federal and state regulations and local conditions. The combination of these factors has made air quality surveys more complex; requiring comprehensive planning to ensure that the prescribed objectives can be attained in the shortest possible time and at the least cost. Furthermore, the choice and siting of the measuring network represents a factor of significant economic relevance for policymakers. In view of the fact that equipment, maintenance and operating personnel costs are increasing dramatically, the possibility of optimizing the monitoring design, is most attractive to the directors of air quality management programs. In this work a methodology that is able to design an optimal air quality monitoring network (AQMN) is described. The objective of the optimization is to provide maximum information about the presence and level of atmospheric contaminants in a given area and with a limited budget. A criterion for assessing the allocation of monitoring stations is developed by applying a utility function that can describe the spatial coverage of the network and its ability to detect violations of standards for multiple pollutants. A mathematical model based on the Multiple Cell Approach (MCA) was used to create monthly spatial distributions for the concentrations of the pollutants emitted from different emission sources. This data was used to train artificial neural networks (ANN) that were proven to be able to predict very well the pattern and violation scores at different potential locations. These neural networks were embedded within a mathematical programming model whose objective is to determine the best monitoring locations for a given budget. This resulted in a nonlinear program (NLP). The proposed model is applied to a network of existing refinery stacks and the locations of monitoring stations and their area coverage percentage are obtained.

Power quality has a great effect on the operation of system loads. To analyze its effects and the possible economic losses due to system disturbances, there is an immediate need of a power quality monitoring system. With an effective communication system, network disturbance data can be gathered and analyzed efficiently such that outage duration and its consequent losses can be reduced. This thesis presents communication network performance simulation results of different types of communication schemes used in a power quality monitoring system. Discrete event simulation method is used to study the end-to-end delay times of different communication architectures. Based on these simulation results, system designers can choose the best option to meet their data communication requirements in power quality monitoring.

Air quality was influenced by many factors, in South Taiwan, air pollutants transportation caused by monsoon or sea-land breeze that may caused high air pollution events. Air pollutant generated by human activity on daytime, then transported and accumulated at sea region by land breeze during the nighttime. Unfortunately, air pollutants that accumulated over sea on night may transport back to land by sea breeze on daytime. Besides, monsoon may carry air pollutants from other regions to South Taiwan and caused high air quality event. Till now, air quality influenced by sea-land breeze and monsoon were not verified in South Taiwan. This study investigated the temporal variation and spatial distribution of air pollutants in the atmosphere around the coastal region of South Taiwan. Ambient air pollutants were simultaneously monitored both inland and offshore. Inland monitoring was conducted at two sites associated with fourteen national air quality monitoring stations, while offshore monitoring was conducted at two sites both in an island and on the boat. A protocol of ambient air quality monitoring was conducted for forty-eight hours. Gaseous air pollutants (i.e. CO, SO2, NOX, THC, and O3) were continuously monitored instrumentally. Data obtained from both inland and offshore monitoring were applied to plot the concentration contour by a software SURFER. Hourly variation of air pollutant concentrations was further used to study the influences of sea-land breezes on the transportation of air pollutants around the coastal region of South Taiwan for different seasons. In August and November, 2006 and May, 2007, sea-land breeze was observed during sampling period and sea breeze arise from 9:00 A.M. to 24:00 P.M. The average wind velocity was 1~4 m/s during the sampling period. In January and March, 2007, prevail wind direction was north direction and northeast direction (270o~30o), that was influenced by northeast monsoon during the sampling period. The average wind velocity was 2~4 m/s. The results showed that distribution of air pollutants, including O3, NOX, THC, and CO influenced by sea-land breezes, particularly for ozone. Air pollutants transported to sea region during the nighttime, and transported back at daytime. This phenomenon cause air pollutants accumulated between Kao-Ping and sea region. In general, NOX generated by transportation and industrial process, thus high concentration of NOX appeared during traffic congestion period and at industry region, mainly Kaohsiung city and Linyuang industrial region. However, sea-land breeze effect upon transportation of air pollutants wasn¡¦t obvious for SO2. High SO2 concentration appeared at Linyuang industrial region and Siaogang at daytime, and transported to region along the coast. During northeastern monsoon season, northeast winds obstructed by Central Mountain Range cause air pollutants accumulated at Kao-Ping region. High NOX concentration appeared at Kaohsiung City and Linyuang industrial region. SO2 accumulated at Siaogang and Linyuang during the nighttime might be caused by high atmospheric pressure system and blew air pollutants to Linbian. CO was accumulated at Siaogang at daytime and transported to Donggang, while THC was accumulated at Donggang whole day.

This research identified and evaluated possible uses of environmental monitoring data collected and reported by industrial facilities under the Clean Water Act requirements and determined whether the current regulatory system supported any of those uses. Federal policies and state-level policies in the United States, Florida, and California were evaluated in order to determine whether the current regulatory system supported any of the identified uses. Monitoring programs and currently available monitoring data were evaluated from Hillsborough County, Florida, and Los Angeles County, California, from the perspective of 1) the current implementation of the monitoring program, and 2) perfect implementation under full compliance with the monitoring program. Four possible uses for monitoring data were identified by this research: (1) identification of high polluting facilities within a given jurisdiction, (2) assessment of pollutant load to receiving waterbodies, (3) documentat ion of improvement over time in the amount of pollutants discharged from a given industrial facility, (4) self-evaluation purposes, such as identifying on-site pollutant sources, adapting pollution prevention efforts, and evaluating the monitoring protocol. The research conducted a telephone survey and evaluated industrial facilities' reported analytical monitoring data. Telephone questionnaires were administered to 63 industrial facilities, and analytical monitoring data were obtained from industrial facilities in Hillsborough County, Florida and Los Angeles County California. The representativeness, sampling frequency and variation in the industrial facilities' analytical monitoring data do not assist in the identification of high polluting facilities within a given jurisdiction nor provide for documentation of facilities' improvements. Pollutant loads to receiving watebodies can not be assessed through the use of industrial facilities' analytical monitoring data because of the sampl e measurement, variation, and sample frequency of the data. Therefore, these uses can not be supported under current implementation/current data submitted or under perfect compliance. However, the telephone survey revealed facility operators are attempting to use the results from monitoring for self evaluation purposes.

No description available.

American Water Resources Association Symposium Proceedings / Reprinted from Establishment of Water Quality Monitoring Programs / Edited By: Lorne G. Everett and Kenneth D. Schmidt / June 12-14, 1978 / San Francisco, California / Traditional techniques for monitoring the mass flux of pollutants in the vadose zone involve obtaining point samples of solute, either by core sampling of solids, followed by laboratory extraction, or by installation of suction probes. An alternative sampling technique, discussed in this paper, is to sample perched ground water within the vadose zone. Large amounts of water may be pumped for sampling purposes from wells drilled into productive, perched ground -water bodies. Alternatively, cascading water from perched regions may be sampled in wells with perforations above the water table. Analytical results of samples from such wells are more representative of regional conditions than small point samples. Case studies are presented on sampling from perched ground water underlying a point source (an oxidation pond), a line source (an ephemeral stream), and a diffuse source (irrigation return flow).

In the agri-food industry, carbon dioxide sensors can be used for process control, monitoring quality, and assessing safety. A carbon dioxide sensor was developed using poly aniline boronic acid (PABA) conducting polymer as the electrically conductive region of the sensor for use in the agri-food industry and was demonstrated for use in detecting incipient or ongoing spoilage in stored grain. The developed sensor dynamically detected up to 2455 ppm CO2 concentration levels. The performance of the sensor in measurements of low concentrations of dissolved CO2 was characterized using standard solutions of NAHCO3. The dynamic range for the detection of H2CO3 was 4.91X10-4 to 9.81X10-3 mol L-1. The dc resistance values decreased with increasing CO2 concentration indicating an increase of conductivity due to increase in the amount of protonation. The developed CO2 sensor was evaluated for the influence of temperature (by storing it at – 20°C and 0°C as well as at operating temperatures of +10°C to 55°C) and relative humidity (from 20 to 70%). Temperature dependence of sensor's resistance values were observed possibly due to the change in conduction mechanism at different temperatures. The variation in the resistance with humidity was curvi-linear and repeatable, indicating that humidity has a less pronounced effect on the sensor’s performance. The sensor’s response to changes in CO2 concentrations at various humidity and temperature levels was stable indicating that the sensor can detect CO2 levels under fluctuating environmental conditions. The response of the PABA film to CO2 concentration was not affected by the presence of alcohols and ketones, proving that the developed CO2 sensor is not cross-sensitive to these compounds which may be present in spoiling grain. The sensor packaging components were selected and built in such a way to avoid contamination of the sensing material and the substrate by undesirable components including grain dust and chaff. The developed conducting polymer CO2 sensor exhibited dynamic performance in its response, recovery times, sensitivity, selectivity, stability and response slope when exposed to various CO2 levels inside simulated grain bulk conditions.

In a semi-arid country like South Africa, the availability and quality of water has always played an important part in determining not only where people can live, but also their quality of life. The supply of water is also becoming a restriction to the socio-economic development of the country, in terms of both the quality and quantity of what is available. Thus different monitoring techniques should be put in place to help inform the process of conserving this precious commodity and to improve the quality of what is already available. Water quality monitoring has traditionally been by the means of physico-chemical analysis; this has more recently been augmented with the use of biomonitoring techniques. However, since the biota commonly used to indicate aquatic conditions are not always present in wetlands; this study tested the use of diatoms as bio-indicators in wetlands. Diatom samples were collected from thirteen wetlands in the Western Cape Province, and cells from these communities were enumerated and diatom ?based indices were calculated using version 3.1 of OMNIDIA. These indices were useful for indicating water quality conditions when compared to the measured physico-chemical parameters. In addition, most diatom species found were common to those found in riverine environments, making the transfer of ecological optima possible. The objective of the study was to provide a preliminary diatom-based index for wetlands, however, given the relatively small study area and the strong bias towards coastal wetlands it was deemed inadvisable to construct such an index, instead several indices are recommended for interim use until further research that more comprehensively covers wetlands in South Africa has been conducted. It is thus the recommendation of this study that more data is collected for comparison to other wetlands and that in the interim, indices such as SPI be applied for routine biomonitoring of these environments. / Thesis (M.Sc. (Botany))--North-West University, Potchefstroom Campus, 2010.

In the agri-food industry, carbon dioxide sensors can be used for process control, monitoring quality, and assessing safety. A carbon dioxide sensor was developed using poly aniline boronic acid (PABA) conducting polymer as the electrically conductive region of the sensor for use in the agri-food industry and was demonstrated for use in detecting incipient or ongoing spoilage in stored grain. The developed sensor dynamically detected up to 2455 ppm CO2 concentration levels. The performance of the sensor in measurements of low concentrations of dissolved CO2 was characterized using standard solutions of NAHCO3. The dynamic range for the detection of H2CO3 was 4.91X10-4 to 9.81X10-3 mol L-1. The dc resistance values decreased with increasing CO2 concentration indicating an increase of conductivity due to increase in the amount of protonation. The developed CO2 sensor was evaluated for the influence of temperature (by storing it at – 20°C and 0°C as well as at operating temperatures of +10°C to 55°C) and relative humidity (from 20 to 70%). Temperature dependence of sensor's resistance values were observed possibly due to the change in conduction mechanism at different temperatures. The variation in the resistance with humidity was curvi-linear and repeatable, indicating that humidity has a less pronounced effect on the sensor’s performance. The sensor’s response to changes in CO2 concentrations at various humidity and temperature levels was stable indicating that the sensor can detect CO2 levels under fluctuating environmental conditions. The response of the PABA film to CO2 concentration was not affected by the presence of alcohols and ketones, proving that the developed CO2 sensor is not cross-sensitive to these compounds which may be present in spoiling grain. The sensor packaging components were selected and built in such a way to avoid contamination of the sensing material and the substrate by undesirable components including grain dust and chaff. The developed conducting polymer CO2 sensor exhibited dynamic performance in its response, recovery times, sensitivity, selectivity, stability and response slope when exposed to various CO2 levels inside simulated grain bulk conditions.

In a semi-arid country like South Africa, the availability and quality of water has always played an important part in determining not only where people can live, but also their quality of life. The supply of water is also becoming a restriction to the socio-economic development of the country, in terms of both the quality and quantity of what is available. Thus different monitoring techniques should be put in place to help inform the process of conserving this precious commodity and to improve the quality of what is already available. Water quality monitoring has traditionally been by the means of physico-chemical analysis; this has more recently been augmented with the use of biomonitoring techniques. However, since the biota commonly used to indicate aquatic conditions are not always present in wetlands; this study tested the use of diatoms as bio-indicators in wetlands. Diatom samples were collected from thirteen wetlands in the Western Cape Province, and cells from these communities were enumerated and diatom ?based indices were calculated using version 3.1 of OMNIDIA. These indices were useful for indicating water quality conditions when compared to the measured physico-chemical parameters. In addition, most diatom species found were common to those found in riverine environments, making the transfer of ecological optima possible. The objective of the study was to provide a preliminary diatom-based index for wetlands, however, given the relatively small study area and the strong bias towards coastal wetlands it was deemed inadvisable to construct such an index, instead several indices are recommended for interim use until further research that more comprehensively covers wetlands in South Africa has been conducted. It is thus the recommendation of this study that more data is collected for comparison to other wetlands and that in the interim, indices such as SPI be applied for routine biomonitoring of these environments. / Thesis (M.Sc. (Botany))--North-West University, Potchefstroom Campus, 2010.