The impact of coal utilization in Texas under the National energy plan

The paper describes the results of a study of the impact of the National Energy on the trend towards increased utilization of coal and lignite in Texas with forecasts of increased coal and lignite utilization for the electric utility and industrial sectors. Environmental impacts of this increased coal and lignite use are projected in terms of increased air pollutant emissions and air quality impacts. Economic costs of compliance with alternative source emission regulations are also projected for the electric utility industry.Lignite consumption in Texas under the National Energy Plan is projected to increase from the present 13 million metric tons in 1976 to 57 million metric tons annually by 1985. Sub-bituminous coal consumption in Texas is projected to increase from 1 million metric per year in 1976 to 49 million metric tons per year in 1985. Bituminous coal consumption in Texas is expected to increase from less than one million metric tons per year in 1976 to about 3 million metric tons per year in 1985.Major increases in sulfur oxides emissions from coal and lignite combustion in Texas can be expected by 1985 of up to 1.5 × 10⁹ kg per year without controls and 0.2 × 10⁹ kg per year with controls. Increases in acid precipitation formation will result in north-east Texas from extensive lignite usage for electric power generation as a detriment to agriculture. The photochemical air pollution problem in the Houston area will probably worsen primarily because of increased nitrogen oxides and sulfur oxides emissions because of industrial coal combustion. Capital costs of air pollution controls in Texas for coal-fired utility boilers are estimated as up to U.S. $3.9 billion by 1985, with total operating costs of up to U.S. $1.2 billion per year.     

Spatiotemporal Associations of Reservoir Nutrient Characteristics and the Invasive,Harmful Alga Prymnesium parvum in West Texas

Golden alga (Prymnesium parvum) is a harmful alga that has caused ecological and economic harm in freshwater and marine systems worldwide. In inland systems of North America, toxic blooms have nearly eliminated fish populations in some systems. Modifying nutrient profiles through alterations to land or water use may be a viable alternative for golden alga control in reservoirs. The main objective of this study was to improve our understanding of the nutrient dynamics that influence golden alga bloom formation and toxicity in west Texas reservoirs. We examined eight sites in the Upper Colorado River basin, Texas: three impacted reservoirs that have experienced repeated golden alga blooms; two reference reservoirs where golden alga is present but nontoxic; and three confluence sites downstream of the impacted and reference sites. Total, inorganic, and organic nitrogen and phosphorus and their ratios were quantified monthly along with golden alga abundance and ichthyotoxicity between December 2010 and July 2011. Blooms persisted for several months at the impacted sites, which were characterized by high organic nitrogen and low inorganic nitrogen. At impacted sites, abundance was positively associated with inorganic phosphorus and bloom termination coincided with increases in inorganic nitrogen and decreases in inorganic phosphorus in late spring. Management of both inorganic and organic forms of nutrients may create conditions in reservoirs unfavorable to golden alga.     

Prediction of effluent concentration in a wastewater treatment plant using machine learning models

Of growing amount of food waste, the integrated food waste and waste water treatment was regarded as one of the efficient modeling method. However, the load of food waste to the conventional waste treatment process might lead to the high concentration of total nitrogen(T-N) impact on the effluent water quality. The objective of this study is to establish two machine learning models—artificial neural networks(ANNs) and support vector machines(SVMs), in order to predict 1-day interval T-N concentration of effluent from a wastewater treatment plant in Ulsan, Korea. Daily water quality data and meteorological data were used and the performance of both models was evaluated in terms of the coefficient of determination(R~2), Nash–Sutcliff efficiency(NSE), relative efficiency criteria(d rel). Additionally, Latin-Hypercube one-factor-at-a-time(LH-OAT) and a pattern search algorithm were applied to sensitivity analysis and model parameter optimization, respectively. Results showed that both models could be effectively applied to the 1-day interval prediction of T-N concentration of effluent. SVM model showed a higher prediction accuracy in the training stage and similar result in the validation stage.However, the sensitivity analysis demonstrated that the ANN model was a superior model for 1-day interval T-N concentration prediction in terms of the cause-and-effect relationship between T-N concentration and modeling input values to integrated food waste and waste water treatment. This study suggested the efficient and robust nonlinear time-series modeling method for an early prediction of the water quality of integrated food waste and waste water treatment process.     

Interaction effects of organic load and cycle time in an AsBr applied to a personal care industry wastewater treatment

A mechanically stirred anaerobic sequencing batch reactor (ASBR) containing granular biomass was applied to the treatment of a wastewater simulating the effluent from a personal care industry. The ASBR was operated with cycle lengths (t_C) of 8, 12 and 24 h and applied volumetric organic loads (AVOL) of 0.75, 0.50 and 0.25 gCOD/L.d, treating 2.0 L liquid medium per cycle. Stirring frequency was 150 rpm and the reactor was kept in an isothermal chamber at 30 °C. Increase in t_C resulted in efficiency increase at constant AVOL, reaching 77% at t_C of 24 h versus 69% at t_C of 8 h. However, efficiency decreased when AVOL decreased as a function of increasing t_C, due to the lack of substrate in the reaction medium. Moreover, replacing part of the wastewater by a chemically balanced synthetic one did not yield the expected effect and system efficiency dropped.