Wilfrid Bach

Fireworks pollution and health

This paper discusses the adverse health effects of air and noise pollution caused by fireworks episodes on Oahu, Hawaii. During such episodes the level of suspended particulates can increase by an average of 300 percent above pre‐fireworks levels. The 24‐hour Hawaii air quality standard can be exceeded by 170 percent. Significantly the lung‐penetrating paxticles of < 4.7 μm may increase by 700 percent due to fireworks smoke. Noise levels can reach 117 dBA exceeding all noise codes. An increase of 113 percent in treated respiratory illness during a fireworks episode was statistically significant, but an 8 percent decline in pulmonary function was not.

Solar irradiation and atmospheric pollution

SummaryThis report contains the results from 30-minute observations of UV (0.29 to 0.38 μm) and total solar irradiation, (0.3 to 3.0 μm) made on the rooftop of a medium size building in downtown Cincinnati. The one year data are obtained from a pyranometer and a UV radiometer used in conjunction with integrators and printout devices. UV and total direct solar irradiation data are analyzed in order to detect possible weekly pollution cycles. It is found that the average difference between weekday and Sunday values in Cincinnati is 3.6% and 29.2% for total direct and UV irradiation, respectively. Chi-square tests indicate significance of these differences at the 5% and 0.5% levels. Ratios of UV and total solar irradiation are presented as indices of atmospheric opacity and compared with turbidity coefficients. It is shown that the ratios vary relatively little irrespective of whether the atmosphere seems to be polluted or clean. Apparently the particle size distribution in a polluted atmosphere is no different from that in clean air. It is suggested that the small decrease in the ratio of UV to total solar irradiation for a polluted atmosphere may be due to selective absorption by gaseous pollutants. UV irradiation curves are used to analyze processes leading to fumigation and photochemical smog formation. Calculation of theoretical UV irradiation curves allows the exact assessment of the magnitude of UV attenuation due to pollutants. This attenuation ranges from 30% in clean to over 80% in smoggy atmospheres.ZusammenfassungDie Arbeit enthält die Ergebnisse von auf dem Dach eines mittelgroßen Gebäudes in der Stadt Cincinnati durchgeführten halbstündigen Beobachtungen von UV (0,29 bis 0,38 μm) und der Globalstrahlung (0,3 bis 3,0 μm). Die in einem Jahr mit einem Pyranometer und einem UV-Radiometer gewonnenen Beobachtungsdaten werden im Hinblick auf einen möglichen Wochenzyklus der Luftverunreinigung analysiert. Es ergab sich, daß die durchschnittlichen Unterschiede zwischen Werktags- und Sonntagswerten bei der Globalstrahlung 3,6% und bei der UV-Strahlung 29,2% betragen. χ2-Tests bestätigen die Signifikanz dieser Differenzen im 5%- und im 0.5%-Niveau. Die Werte des Verhältnisses von UV-zur Gesamtstrahlung werden als Indizes für die atmosphärische Trübung angegeben und mit Trübungskoeffizienten verglichen. Es wird gezeigt, daß diese Verhältniszahlen relativ nur wenig variieren, unabhängig davon, ob die Atmosphäre verunreinigt oder rein erscheint. Offenbar ist die Verteilung der Teilchengrößen in verunreinigter Luft nicht verschieden von der in reiner Luft. Es wird angenommen, daß die geringfügige Abnahme des Verhältnisses von UV- zu Globalstrahlung in verunreinigter Luft auf eine selektive Absorption durch gasförmige Verunreinigung zurückzuführen ist. Die Kurven der Tagesgänge der UV-Strahlung werden zur Analyse der Vorgänge verwendet, die zur Fumigation und photochemischen Smogbildung führen. Die Berechnung der theoretischen Tagesgänge der UV-Strahlung ermöglicht eine genaue Abschätzung der Größe der Schwächung der UV-Strahlung durch die Luftverunreinigungen. Diese Schwächung schwankt zwischen 30% in klarer und über 80% in Smogluft.

Simulation of the Environmental Impact of an Airport on the Surrounding Air Quality

It is the purpose of this study to demonstrate the procedure involved in simulating those average and maximum pollutant concentrations at or around an airport which fall under the control of the Clean Air Act. The information is useful, when planning new or expanding existing airports, when estimating the impact of airports on the surrounding air quality, and when assessing the effectiveness of control procedures. Simulation of airport air quality requires the accurate assessment of the temporal and spatial emission patterns. This involves the tabulation of air traffic density by type and engine, make and model of aircraft, and engine mode number; the use of fuel by different aircraft; the pollutant emission rates by engine model and operational mode; the allocation of emissions rates to the respective runways, turn-off points, taxiways, and parking areas, and the time each aircraft spent in the different operational modes. The resulting emission pattern for the Honolulu International Airport reflections scheduled and unscheduled commercial and military jet and piston aircraft and nonaircraft operations. Using this and the appropriate meteorological information average and maximum surface concentrations were calculated and compared with local ambient air quality standards. The calculation of concentrations is based on a newly developed diffusion model incorporating harmonic mean wind speeds for every degree of wind direction as determined by a Parzen maximum likelihood interpolation technique, and the assumption of log-normal concentration distributions. It is shown that for some pollutants the air quality standards are substantially exceeded, and it is concluded that airports may have a considerable adverse impact on their surrounding air quality.

Fitting a Circular Distribution to a Histogram

Abstract In meteorology, wind directions are often recorded to the nearest of 16 points of the compass. When studying the diffusion of air pollutants downwind from a source, it is often desirable to have much higher resolution—on the order of 1°. To obtain such high resolution, one is essentially faced with fitting a continuous distribution to a histogram. The basic problem is one of interpolating between observed directions. On a circle, a natural first approach is to use harmonic analysis; however, this can produce negative densities. One solution to this problem is similar to the techniques of spectrum estimation, using a window function to obtain a smooth, non-negative density.