COMPARISON OF STOCHASTIC AND DETERMINISTIC DYNAMIC PROGRAMMING FOR RESERVOIR OPERATING RULE GENERATION1

ABSTRACT: Two dynamic programming models — one deterministic and one stochastic — that may be used to generate reservoir operating rules are compared. The deterministic model (DPR) consists of an algorithm that cycles through three components: a dynamic program, a regression analysis, and a simulation. In this model, the correlation between the general operating rules, defined by the regression analysis and evaluated in the simulation, and the optimal deterministic operation defined by the dynamic program is increased through an iterative process. The stochastic dynamic program (SDP) describes streamflows with a discrete lag-one Markov process. To test the usefulness of both models in generating reservoir operating rules, real-time reservoir operation simulation models are constructed for three hydrologically different sites. The rules generated by DPR and SDP are then applied in the operation simulation model and their performance is evaluated. For the test cases, the DPR generated rules are more effective in the operation of medium to very large reservoirs and the SDP generated rules are more effective for the operation of small reservoirs.     

Particulate,Carbon Monoxide,and Acid Emission Factors for Residential Wood Burning Stoves

Emissions from residential wood burning stoves are of Increasing concern in many areas. This concern is due to the magnitude of the emissions and the toxic and chemical characteristics of the pollutants. Recent testing of standard and new technology woodstoves has provided data for developing a family of particulate and carbon monoxide emission factor curves. This testing has also provided data illustrating the acidity of woodstove emissions. The particulate and carbon monoxide curves relate the actual stove emissions to the stove size and operating parameters of burn rate, fuel loading, and fuel moisture. Curves relating stove types to the acidity of emissions have also been constructed.

Test data show actual emissions vary from 3 to 50 grams per kilogram for particles and from 50 to 300 grams per kilogram for carbon monoxide. Since woodstove emissions are the largest single category of particulate emissions in many areas, it Is essential that these emissions be quantified specifically for geographic regions, allowing meaningful impact analysis modeling to be accomplished. Emission factors for particles and carbon monoxide are presented from several stove sizes and burn rates.

The acidic nature of woodstove emissions has been clearly demonstrated. Tests indicate woodstove flue gas condensate solutions to be predominantly in the 2.8 to 4.2 pH range. Condensate solutions from conventional woodstoves exhibited the characteristic buffering capacity of carboxylic acids when titrations were performed with a strong base. The environmental impact of buffered acidic woodstove emissions is not currently well understood; however, it is possible with the data presented here to make semi-quantitative estimates of acid emissions from particulate and carbon monoxide emission factors and wood use inventories.     

Analysis of cloud and precipitation chemistry at Whiteface Mountain,NY

Federal and state programs over the past two decades have resulted in the reduction of emissions of precursors of acid rain. Concomitant with these changes, measured concentrations of acidity in precipitation and in watersheds have shown a downward trend or improvement. However, another pathway for these precursors is through cloud and fog events that often tend to occur at high-elevation regions affecting the fauna and flora as well. In this study we report on long-term measurements of cloud water and precipitation chemistry made from 1994 onwards at a high-elevation location, Whiteface Mountain NY, in the northeastern United States. Trends and inter-relationship between the ions were examined along with ambient SO₂ measurements and Adirondack lakes chemistry data.     

The Mutagenic Activity of Particulate Organic Matter Collected with a Dilution Sampler at Coal-Fired Power Plants

The Deep Creek Lake Study of 1983 provided an opportunity to obtain emission samples from coal-fired power plants with a dilution sampler for mutagenicity testing. Stack and ambient samples of particulate matter were collected with a dilution sampler at three coal-fired power plants in West Virginia. Samples were sequentially extracted with cyclohexane (CX), dichloromethane (DCM) and acetone (ACE) and tested for mutagenicity in the Ames Salmonella/microsome assay using TA98 (-S9). For the stack samples, the CX, DCM and ACE fractions constituted 1.0, 0.7 and 98.1 percent of the total extractable organic material (EOM), respectively, compared to 28.5, 7.4 and 64.1 percent for the ambient samples. In contrast, the mutagenic activity of the organic fractions was concentrated in the CX and DCM fractions.

The cyclohexane- and dichloromethane-soluble fractions of the stack samples from all locations exhibited mutagenicity when tested in the plate incorporation assay. No significant response was observed with the acetone fraction. When tested with Kado's modification of the preincubation assay, the acetone-soluble fraction did exhibit mutagenic activity comparable to that of the other fractions when expressed in units of revertants per milligram of particular matter. Chemical analyses of one of the acetone-soluble fractions indicated that half of the mass was sulfuric acid while the remainder consisted of C, H and O. More than 30 peaks were detected in the high pressure liquid chromatogram of this fraction.

Although little mutagenic activity was detected in the polar ACE fraction of the diluted stack emissions samples with this single bioassay, in view of the large mass of this fraction, further investigation of the chemical composition and genotoxic activity of this fraction would be prudent.     

PM2.5 chemical source profiles for vehicle exhaust, vegetative burning, geological material, and coal burning in Northwestern Colorado during 1995

PM_2.5 (particles with aerodynamic diameters less than 2.5 μm) chemical source profiles applicable to speciated emissions inventories and receptor model source apportionment are reported for geological material, motor vehicle exhaust, residential coal (RCC) and wood combustion (RWC), forest fires, geothermal hot springs; and coal-fired power generation units from northwestern Colorado during 1995. Fuels and combustion conditions are similar to those of other communities of the inland western US. Coal-fired power station profiles differed substantially between different units using similar coals, with the major difference being lack of selenium in emissions from the only unit that was equipped with a dry limestone sulfur dioxide (SO₂) scrubber. SO₂ abundances relative to fine particle mass emissions in power plant emissions were seven to nine times higher than hydrogen sulfide (H₂S) abundances from geothermal springs, and one to two orders of magnitude higher than SO₂ abundances in RCC emissions, implying that the SO₂ abundance is an important marker for primary particle contributions of non-aged coal-fired power station contributions. The sum of organic and elemental carbon ranged from 1% to 10% of fine particle mass in coal-fired power plant emissions, from 5% to 10% in geological material, >50% in forest fire emissions, >60% in RWC emissions, and >95% in RCC and vehicle exhaust emissions. Water-soluble potassium (K⁺) was most abundant in vegetative burning profiles. K⁺/K ratios ranged from 0.1 in geological material profiles to 0.9 in vegetative burning emissions, confirming previous observations that soluble potassium is a good marker for vegetative burning.     

PM2.5 chemical source profiles for vehicle exhaust, vegetative burning, geological material, and coal burning in Northwestern Colorado during 1995

PM_2.5 (particles with aerodynamic diameters less than 2.5 μm) chemical source profiles applicable to speciated emissions inventories and receptor model source apportionment are reported for geological material, motor vehicle exhaust, residential coal (RCC) and wood combustion (RWC), forest fires, geothermal hot springs; and coal-fired power generation units from northwestern Colorado during 1995. Fuels and combustion conditions are similar to those of other communities of the inland western US. Coal-fired power station profiles differed substantially between different units using similar coals, with the major difference being lack of selenium in emissions from the only unit that was equipped with a dry limestone sulfur dioxide (SO₂) scrubber. SO₂ abundances relative to fine particle mass emissions in power plant emissions were seven to nine times higher than hydrogen sulfide (H₂S) abundances from geothermal springs, and one to two orders of magnitude higher than SO₂ abundances in RCC emissions, implying that the SO₂ abundance is an important marker for primary particle contributions of non-aged coal-fired power station contributions. The sum of organic and elemental carbon ranged from 1% to 10% of fine particle mass in coal-fired power plant emissions, from 5% to 10% in geological material, >50% in forest fire emissions, >60% in RWC emissions, and >95% in RCC and vehicle exhaust emissions. Water-soluble potassium (K⁺) was most abundant in vegetative burning profiles. K⁺/K ratios ranged from 0.1 in geological material profiles to 0.9 in vegetative burning emissions, confirming previous observations that soluble potassium is a good marker for vegetative burning.     

Compositions of Particles from Selected Sources in Philadelphia for Receptor Modeling Applications

As a part of a receptor model study of the Philadelphia, PA atmosphere, particulate samples were collected from seven air pollution sources in the area: two oil-fired power plants, a coal-fired power plant, a fluidized catalytic cracker, a refuse incinerator, a secondary aluminum smelter and an antimony ore roaster. Samples were collected In two size fractions with a dilution source sampler connected to a modified dichotomous sampler. Masses of collected material were determined gravlmetrlcally. Samples were analyzed for elements by x-ray fluorescence followed by Instrumental neutron activation analysis of some samples. Other samples were analyzed by chemical methods for volatile and nonvolatile carbon, SO₄ ^2? and NH₄ ⁺. Data are presented for up to 46 elements and species on fine (<2.5-μm aerodynamic equivalent diameter) and coarse (2.5 μm < diam < 7-10 μm) particles from each source. Although the data were collected for use in Philadelphia, they should be of value for receptor modeling of other areas having similar sources. The most unexpected results were the large amounts of rare earth elements on particles from the catalytic cracker (e.g., 0.31 percent La In fine fraction) and the oil-fired power plants (120 and 420 ppm La in fine fraction). Substantial amounts of primary SO₄ ^2? are released from the oil-fired plants, the SO₄ ^2? concentrations accounting for 40-45 percent of the fine particulate mass.     

THE EFFECTS OF RISK AND RELIABILITY ON OPTIMAL RESERVOIR DESIGN1

A chance-constrained linear programming model, which utilizes multiple linear decision rules and is useful for river basin planning, is used to evaluate the effects of risk and reliability on optimal reservoir design. Streamflow forecasts or predictions can be explicitly included in the linear program. The risk associated with the predictions is included in the model through the use of cumulative distribution functions (CDF) of streamflows which are conditioned on the predictions. A multiple-purpose reservoir on the Gunpowder River in Maryland is used to illustrate the effectiveness of the model. In order to provide the decision makers with complete and useful information, trade-off curves relating minimum reservoir capacity (a surrogate for dam costs), water supply and flood control targets, and the reliability of achieving the targets are developed. The trade-off curves may enhance the decision maker's ability to select the best dam capacity, considering technological and financial constraints as well as the trade-offs between targets, risks, and costs.     

用大型底栖动物和ODP系统评价珠江的有机污染

采用大型底栖动物需氧有机体百分率ODP(oxygen demander percentage)法对广州珠江前航道、西航道和流溪河的下游段进行河流有机污染评价.结果显示:底栖动物需氧类群密度在三河段间分布确有显著性差异,并根据其ODP可以判断流溪河水质相对较好,水质级别为中国地表水环境质量标准(EQSSW)Ⅳ级,西航道和前航道水质级别都为Ⅴ级.通过测试,这一方法能成功地应用在珠江及流溪河,且该法可以较好地匹配于EQSSW五级评价系统,初步认为ODP系统可以成为一个较好的河流水质生物监测方法.图3表4参13