Assessment of the Nested Grid Model Estimates for Driving Regional Visibility Models in the Southwestern United States

ABSTRACT

The Nested Grid Model (NGM) is a primitive-equation meteorological model that is routinely exercised over North America for forecasting purposes by the National Meteorological Center. While prognostic meteorological models are being increasingly used to drive air quality models, their use in conducting annual simulations requires significant resources. NGM estimates of wind fields and other meteorological variables provide an attractive alternative since they are typically archived and readily available for an entire year. Preliminary evaluation of NGM winds during the summer of 1992 for application to the region surrounding the Grand Canyon National Park showed serious shortcomings. The NGM winds along the borders between California, Arizona and Mexico tend to be northwesterly with a speed of about 6 m/sec, while the observed flow is predominantly southerly at about 2-5 m/sec. The mesoscale effect of a thermal low pressure area over the highly heated Southern California and western Arizona deserts does not appear to be represented by the NGM because of its coarse resolution and the use of sparse observations in that region. Tracer simulations and statistical evaluation against special high resolution observations of winds in the southwest United States clearly demonstrate the northwest bias in NGM winds and its adverse effect on predictions of an air quality model. The “enhanced” NGM winds, in which selected wind observations are incorporated in the NGM winds using a diagnostic meteorological model provide additional confirmation on the primary cause of the northwest bias. This study has demonstrated that in situations where limited resources prevent the use of prognostic meteorological models, previously archived coarse resolution wind fields in which additional observations are incorporated to correct known biases provide an attractive option.     

Efficacy of biochar in removal of organic pesticide,Bentazone from watershed systems

Abstract

Bentazone is one of the toxic insecticides used to control forest tent caterpillar moths, boll weevils, gypsy moths, and other types of moths in various field crops. We report the efficacy of biochar prepared from the Azardirachta Indica waste biomass as adsorbent for removal of Bentazone. Biochar material was prepared by pyrolysis process under limited oxygen conditions. Biochar material was characterized by proximate and ultimate analysis, SEM analysis, FTIR analysis and TG/DTA analyses. The Bentazone adsorption capacity by biochar from aqueous solutions was assessed. Effect of time, adsorbent dosage, insecticide concentration and pH on the adsorption characteristics of the biochar were evaluated. Adsorption parameters were obtained at equilibrium contact time of 150?min, with biochar dosage of 0.5?g at pH 8. From the optimization studies, desirability of 0.952 was obtained with response (adsorption uptake) of 79.40?mg/g, for initial concentration of insecticide (50?mg/L), adsorbent dosage (0.448?g), time 30.0?min and pH 2. The adsorption isotherm data for the removal of Bentazone fitted well with the Freundlich isotherm. This study indicates that the biochar produced from the bark of Azardirachta Indica biomass could be employed as a potential adsorbent for removal of synthetic organic pollutants from the water streams.     

Guidance for the performance evaluation of three-dimensional air quality modeling systems for particulate matter and visibility

Guidance for the performance evaluation of three-dimensional air quality modeling systems for particulate matter and visibility is presented. Four levels are considered: operational, diagnostic, mechanistic, and probabilistic evaluations. First, a comprehensive model evaluation should be conducted in at least two distinct geographical locations and for several meteorological episodes. Next, streamlined evaluations can be conducted for other similar applications if the comprehensive evaluation is deemed satisfactory. In all cases, the operational evaluation alone is insufficient, and some diagnostic evaluation must always be carried out. Recommendations are provided for designing field measurement programs that can provide the data needed for such model performance evaluations.     

Ozone formation in California's San Joaquin Valley: a critical assessment of modeling and data needs

Data from the 1990 San Joaquin Valley Air Quality Study/Atmospheric Utility Signatures, Predictions, and Experiments (SJVAQS/AUSPEX) field program in California's San Joaquin Valley (SJV) suggest that both urban and rural areas would have difficulty meeting an 8-hr average O3 standard of 80 ppb. A conceptual model of O3 formation and accumulation in the SJV is formulated based on the chemical, meteorological, and tracer data from SJVAQS/AUSPEX. Two major phenomena appear to lead to high O3 concentrations in the SJV: (1) transport of O3 and precursors from upwind areas (primarily the San Francisco Bay Area, but also the Sacramento Valley) into the SJV, affecting the northern part of the valley, and (2) emissions of precursors, mixing, transport (including long-range transport), and atmospheric reactions within the SJV responsible for regional and urban-scale (e.g., down-wind of Fresno and Bakersfield) distributions of O3. Using this conceptual model, we then conduct a critical evaluation of the meteorological model and air quality model. Areas of model improvements and data needed to understand and properly simulate O3 formation in the SJV are highlighted.     

Numerical and experimental investigation of state of health of Li-ion battery

ABSTRACT

Estimation of State of Health (SoH) of Lithium-ion (Li-ion) battery is essential to predict the lifespan of batteries of an electric vehicle (EV). The efficient prediction of battery health indicates to the effective and safe operation of EV. However, delivering an effective and accurate method for the estimation of SoH in the real condition is truly a challenging task. The present study proposed a holistic procedure of combining both experimental and numerical investigations to conduct the fundamental study on coupled mechanical-electrochemical behavior of Li-ion battery. The proposed investigation highlighted the effect of stress on the capacity of the battery, considering capacity fade as an equivalent parameter to its health for real-time estimation of SoH. Finally, a simple model of Artificial Neural Network (ANN) is provided, which shows the linear dependency of stress with the SoH. The results obtained from the ANN model are validated with a Linear Regression (LR) model for a better understanding of the inspection. The predicted value of mean Square Error (MSE) and R square error in the ANN training model are found to be 0.000309 and 0.849687, respectively. Whereas for the test model, these predicted values are found to be 0.000438 and 0.819347, respectively.     

Evaluation of the IMPROVE Equation for estimating aerosol light extinction

The [revised] IMPROVE Equation for estimating light extinction from aerosol chemical composition was evaluated considering new measurements at U.S. national parks. Compared with light scattering (Bsp) measured at seven IMPROVE sites with nephelometer data from 2003–2012, the [revised] IMPROVE Equation over- and underestimated Bsp in the lower and upper quintiles, respectively, of measured Bsp. Underestimation of the worst visibility cases (upper quintile) was reduced by assuming an organic mass (OM)/organic carbon (OC) ratio of 2.1 and hygroscopic growth of OM, based on results from previous field studies. This assumption, however, tended to overestimate low Bsp even more. Assuming that sulfate was present as ammonium bisulfate rather than as ammonium sulfate uniformly reduced estimated Bsp. The split-mode model of concentration- and size-dependent dry mass scattering efficiencies in the [revised] IMPROVE Equation does not eliminate systematic biases in estimated Bsp. While the new measurements of OM/OC and OM hygroscopicity should be incorporated into future iterations of the IMPROVE Equation, the problem is not well constrained due to a lack of routine measurements of sulfate neutralization and the water-soluble fraction of OM in the IMPROVE network.

Implications: Studies in U.S. national parks showed that aerosol organics contain more mass and absorb more water as a function of relative humidity than is currently assumed by the IMPROVE Equation for calculating chemical light extinction. Consideration of these results could significantly shift the apportionment of light extinction to water-soluble organic aerosols and therefore better inform pollution control strategies under the U.S. Environmental Protection Agency Regional Haze Rule.     

Effects of untreated hospital effluents on the accumulation of toxic metals in sediments of receiving system under tropical conditions: Case of South India and Democratic Republic of Congo

Physicochemical and ecotoxicological analyses have been performed to assess the quality of sediments receiving untreated hospital effluents from Indian and Democratic Republic of Congo (DRC) hospitals. The sediments were collected monthly and characterized for grain size, organic matter, total organic carbon, total carbon, nitrogen, phosphorus, toxic metals and ecotoxicity. The results highlight the high concentration of toxic metals from the Indian hospital effluent receiving systems, especially for Cr, Cu, As, Zn and Hg. On the other hand, the metal concentrations in the sediment receiving system from DRC are low (e.g. maximum Hg and Zn concentration were 0.46 and 48.84 mg kg⁻¹ respectively). Ostracods exposed to sediment samples H2 (September month sample) and H3 (June and September month samples) were found dead after 6 d of exposure whereas the higher mortality rate for Congo sediments was 23% but was accompanied with 33 ± 7% of growth inhibition. The results of this study show the variation of sediment composition on toxic metal levels as well as toxicity related to both, the type of hospitals and the sampling period. Additionally, hospital effluent disposal practices at the study sites can lead to the pollution of water resources and may generate risks for aquatic organisms and human health.     

Modelling the Removal of Gaseous Pollutants and Particulate Matters from the Atmosphere of a City by Rain: Effect of Cloud Density

In this paper, an original nonlinear mathematical model for the removal of gaseous pollutants and particulate matters from the atmosphere of an industrial city by rain is proposed and analyzed. It is assumed that five interacting phases in the atmosphere of the city exist, i.e., cloud droplets phase, raindrops phase, gaseous pollutants phase, particulate matters phase, and the phase of absorbed gaseous pollutants in raindrops. It is assumed further that these phases undergo nonlinear interactions in the atmosphere, while gaseous pollutant interacts with cloud droplets as well as with raindrops but particulate matters interact only with raindrops. The gravitational settling and reversible reaction processes have also been considered appropriately in the model. By analyzing the model, it is shown that both the gaseous pollutants and particulate matters may be removed from the atmosphere under certain conditions, provided the rates of formation of cloud droplets and raindrops are sufficiently large. It is noted that under unfavorable atmospheric conditions, rain does not occur and pollutants are not removed from the atmosphere.     

The Development of a Model to Examine Source-Receptor Relationships for Visibility on the Colorado Plateau

This paper describes the development and application of the Visibility and Haze in the Western Atmosphere (VISHWA) model to understand the source-receptor relationships that govern chemical species relevant to visibility degradation in the western United States. The model was developed as part of a project referred to as Visibility Assessment for Regional Emission Distributions (VARED), the objective of which is to estimate the contributions of various geographical regions, compounds, and emission

sources to light scattering and absorption by particles on the Colorado Plateau.

The VISHWA model is a modified version of a comprehensive Eulerian model, known as the Acid Deposition and Oxidant Model.1 The modifications were designed to obtain the computational efficiency required to simulate a one-year period at about 1/25th of real time, and at the same time incorporate mechanistic features relevant to realistic modeling of the fate and transport of visibility degrading species. The modifications included use of a condensed chemical mechanism; incorporation of reactions to simulate the formation of secondary organic particles; and use of a semi-Lagrangian advection scheme to preserve concentration peaks during advection.

The model was evaluated with 1992 air quality data from Project MOHAVE (Measurements of Haze and Visual Effects) intensive experiments. An important conclusion of this evaluation is that aqueous-phase oxidation of SO2 to sulfate in nonprecipitating clouds makes a significant contribution to observed sulfate levels during winter as well as summer. Model estimates of ambient sulfate

for the winter intensive were within a factor of 2 of the observations for 75% of the values. The corresponding statistic for the summer intensive was 90%. Model estimates of carbon were within a factor of 2 of the limited set of observations.