Prediction of Traffic Noise: A Screening Technique

Abstract

Traffic noise is ubiquitous in many communities and is an important environmental concern, especially for persons located near major roadways. Several different methods are available to estimate noise levels resulting from roadway traffic. These include computational, graphical, and computer modeling techniques.

The prediction methodology presented here is a simplified technique that can be used for estimating noise resulting from traffic and for screening traffic noise impacts. This Traffic Noise Screening (TNS) approach consists of a series of traffic noise level prediction graphs developed for different roadway configurations. The graphs are based on the results from using the Federal Highway Administration (FHWA) STAMINA2.0 computerized noise prediction model for various scenarios. Data inputs to the TNS approach include roadway geometries, traffic volumes, vehicle travel speed, and centerline distance to the receptors.

The TNS graphs allow easy estimation of traffic noise levels for use in predicting traffic-related noise impacts. This TNS approach is not intended as a substitute for detailed modeling, such as with STAMINA2.0, but as a screening tool to aid in determining when detailed modeling may be necessary. If screening results indicate that noise estimates are significant, or if the scenario is rather complex, then additional, more detailed modeling can be performed.     

A Comparison of Nonlinear Regression and Neural Network Models for Ground-Level Ozone Forecasting

ABSTRACT

A hybrid nonlinear regression (NLR) model and a neural network (NN) model, each designed to forecast next-day maximum 1-hr average ground-level O₃ concentrations in Louisville, KY, were compared for two O₃ seasons—1998 and 1999. The model predictions were compared for the forecast mode, using forecasted meteorological data as input, and for the hindcast mode, using observed meteorological data as input. The two models performed nearly the same in the forecast mode. For the two seasons combined, the mean absolute forecast error was 12.5 ppb for the NLR model and 12.3 ppb for the NN model. The detection rate of 120 ppb threshold exceedances was 42% for each model in the forecast mode. In the hindcast mode, the NLR model performed marginally better than the NN     

The Development of a Charging/Collecting Device for High Resistivity Dust Using Cooled Electrodes

A charging/collecting device for high-resistivity fly ash has been developed which controls back ionization by cooling the collector electrode internally with water. The device consists of parallel 6.0 cm pipes with corona wires suspended between the pipes. The pipes provide a simple means of interfacing with a cooling water system and also minimizing the collector area needing to be cooled. By cooling the pipes with 38°C (100°F) water, back ionization is eliminated and average field strengths of 7 kV/cm can be achieved with fly ash having a resistivity > 10¹² ω-cm. Results of tests on an actual flue gas stream and plans for future testing are described. Initial tests using heated instead of cooled electrodes are described as well as other tests that lead to the present design. The results of tests with the heated electrode show the kind of improvements in performance that can be obtained when resistivity is controlled in only a small collection area.     

The Onset of Electrical Breakdown in Dust Layers: II. Effective Dielectric Constant and Local Field Enhancement

Part I of this work has shown that electrical breakdown in dust layers obeys Paschen's Law, but occurs at applied field values which appear too small to initiate the breakdown. In this paper we will show how an effective dielectric constant characterizing the dust layer can be determined from ac dielectric measurements and the theory of Debye. When combined with an expression for the enhanced local electric field in the void spaces between particles in the layer, field strengths which are large enough to initiate electrical breakdown in the layer are predicted at relatively low values of applied field. The effect of temperature and dust layer thickness on the onset of electrical breakdown within the dust layer can also be explained by the dependence of the effective dielectric constant on these parameters.     

Urinary dialkyl phosphate levels before and after first season chlorpyrifos spraying amongst farm workers in the Western Cape,South Africa

The study investigated urinary levels of dialkyl phosphates resulting from pesticide exposure amongst 40 farm workers. Workers were tested (urinary dialkyl phosphate levels, anthropometry, short exposure questionnaire) before and after the first day of seasonal chlorpyrifos spraying. Median baseline urinary dialkyl phosphates was high amongst both non-applicators (1587.5 μg/g creatinine, n = 8) and applicators (365.6 μg/g creatinine, n = 9). There was not much evidence of an increase in post-spray dialkyl phosphates levels from pre-spray levels amongst both applicators and non-applicators. Hours mixing, spraying, driving a tractor and hours worked by non-applicators were not significantly associated with an increase in post-spray dialkyl phosphate levels, adjusting for age, height, weight, gender, use of empty pesticide containers and self-reported kidney problems. Past applicator status was weakly positively associated with pre-spray dialkyl phosphate levels adjusting for age, height, weight, and gender, self-reported kidney problems, smoking and alcohol (β= 1019.5, p = 0.307, R²= 0.28). The high dialkyl phosphate levels call for an epidemiological investigation into the health effects of organophosphorous pesticides.     

Assessment of the bioavailability of cadmium in Jamaican soils

Extraordinary geogenic concentrations of cadmium (Cd) have been reported for some Jamaican soils. However, the bioavailability of the metal in these soils remains unknown. Here, the bioavailability of Cd in selected Jamaican soils was investigated through the determination of total and sequentially extractable concentrations in paired soil–plant (yam; Dioscorea sp.) samples (n?=?24), using neutron activation analysis and atomic absorption spectroscopy as primary analytical techniques. Our results indicate that total soil Cd varied widely (2.2–148.7 mg kg^?1), and on average, total extractable Cd accounted for ~55 % of the total soil Cd. The exchangeable and oxidizable species averaged 1.5 and 6.4 % of the total Cd, respectively, and, based on Spearman analysis, are the best predictors of yam Cd. There is also good evidence to suggest that variation in the bioavailability of the metal is in part controlled by the geochemical characteristics of the soils analyzed and is best explained by pH, cation exchange capacity (CEC) and organic matter content (% LOI).     

GENERALIZED WATERSHED LOADING FUNCTIONS FOR STREAM FLOW NUTRIENTS1

ABSTRACT: Loading functions are proposed as a general model for estimating monthly nitrogen and phosphorus fluxes in stream flow. The functions have a simple mathematical structure, describe a wide range of rural and urban nonpoint sources, and couple surface runoff and ground water discharge. Rural runoff loads are computed from daily runoff and erosion and monthly sediment yield calculations. Urban runoff loads are based on daily nutrient accumulation rates and exponential wash off functions. Ground water discharge is determined by lumped parameter unsaturated and saturated zone soil moisture balances. Default values for model chemical parameters were estimated from literature values. Validation studies over a three-year period for an 850 km² watershed showed that the loading functions explained at least 90 percent of the observed monthly variation in dissolved and total nitrogen and phosphorus fluxes in stream flow. Errors in model predictions of mean monthly fluxes were: dissolved phosphorus - 4 percent; total phosphorus - 2 percent; dissolved nitrogen - 18 percent; and total nitrogen - 28 percent. These results were obtained without model calibration.