Feasibility of Applying a Stable Isotopic Tracer for Direct Determination of Dry Particulate Deposition to Soybean Plants

ABSTRACT

A stable rare-earth isotopic tracer was used to measure the deposition of KNO₃ particles on soybean leaves by direct measurement of the tracer on the plant surfaces by thermal-ionization mass spectrometry. Submicrometer particles, made from a solution containing 3 |mg mL^-1 neodymium isotope (¹⁴⁸Nd, 87.9%) and 1,000 mg mL^-1 KNO₃, were dispersed with a two-fluid nozzle and released upwind of a soybean field. Total suspended- and size-fractionated-aerosol particles were collected on an open-face filter and in a micro-orifice impactor, respectively, at a distance of 40 m from the release point. Soybean leaves exposed to the plume were collected at distances ranging from 25 to 100 m. As little as 5.5 pg of the tracer (i.e., excess ¹⁴⁸Nd) was detected in soybean leaves at signal-to-noise ratios ranging from 7,500 to 240,000, in the presence of 200 to 2,700 pg of naturally occurring Nd. The dry-particle deposition velocity, determined from the ratio of the aerial concentration and directly deposited aerosol (geometric mass mean diameter, 0.20 mm) flux, and its corresponding analytical uncertainty were 0.30 cm sec^-1 and 2.5%, respectively.     

The Air Pollution Carrying Capacities of Selected Colorado Mountain Valley Ski Communities

Of all the recreational activities in Colorado, skiing most greatly creates population densities such as to cause noticeable basinwide air pollution. Skiing is big business in this State as skiers spend over $127 million/year at ski resorts. Skiing provides pleasure to thousands of people. Many realize the importance of clear and clean air to the continuing happiness of skiers and to the success of recreational communities.     

Prediction of household and commercial BMW generation according to socio-economic and other factors for the Dublin region

Both planning and design of integrated municipal solid waste management systems require accurate prediction of waste generation. This research predicted the quantity and distribution of biodegradable municipal waste (BMW) generation within a diverse ‘landscape’ of residential areas, as well as from a variety of commercial establishments (restaurants, hotels, hospitals, etc.) in the Dublin (Ireland) region. Socio-economic variables, housing types, and the sizes and main activities of commercial establishments were hypothesized as the key determinants contributing to the spatial variability of BMW generation. A geographical information system (GIS) ‘model’ of BMW generation was created using ArcMap, a component of ArcGIS 9. Statistical data including socio-economic status and household size were mapped on an electoral district basis. Historical research and data from scientific literature were used to assign BMW generation rates to residential and commercial establishments. These predictions were combined to give overall BMW estimates for the region, which can aid waste planning and policy decisions. This technique will also aid the design of future waste management strategies, leading to policy and practice alterations as a function of demographic changes and development. The household prediction technique gave a more accurate overall estimate of household waste generation than did the social class technique. Both techniques produced estimates that differed from the reported local authority data; however, given that local authority reported figures for the region are below the national average, with some of the waste generated from apartment complexes being reported as commercial waste, predictions arising from this research are believed to be closer to actual waste generation than a comparison to reported data would suggest. By changing the input data, this estimation tool can be adapted for use in other locations. Although focusing on waste in the Dublin region, this method of waste prediction can have significant potential benefits if a universal method can be found to apply it effectively.