Interpretation of Meteorological Pollutant Roses in Areas Subject to Nocturnal Drainage Winds

The composition of aerosol particle products formed from the photochemical reaction of terpenes with NO_x and the chemical reaction of terpenes with ozone was determined using direct insertion probe/high resolution mass spectrometry. Samples of the aerosol particles generated from these gas phase reactions were collected on stainless steel disks using a specially-designed impactor. The samples were analyzed using computer-controlled high resolution mass spectrometry. The photochemical reaction of limonene with NO_x produced more than 30 reaction products in the aerosol phase. The major products identified included aldehydes, alcohols, acids, peroxides, and nitrate esters of alcohols, acids, and peroxides. In addition, there was evidence of dimeric and possibly trimeric reaction products. The composition of aerosol particle products formed from the dark reaction of ozone with limonene was determined and found similar to those products generated in the photochemical reaction, excluding the nitrated species. Aerosol concentrations were monitored using nephelometry which indicated a conversion of terpene to aerosol of 50% or greater for both the limonene and terpinolene reaction systems. The results show that direct insertion probe high resolution mass spectrometric technique has the capability for determining the composition of very polar and high molecular weight materials in aerosol particles. The composition of terpene aerosol particle products and the mass spectral data obtained from their analysis can be used in further studies to determine the importance of terpene aerosol particle formation in ambient air.     

The Formation of Mg3Ca(S04)4 during the Sulfation Reaction of Dolomite

Abstract

Inspection and maintenance programs for motor vehicles in the United States increasingly use loaded mode mass emissions testing (IM240). A method was developed to predict mass emission rates and mass emission changes, particularly from repair benefits, using a low-cost, portable four-gas non-dispersive infrared (NDIR) vehicle exhaust gas analyzer. A single vehicle was tested several times with the analyzer while on the dynamometer and undergoing successive repairs. Excellent correlations for CO and HC were observed. Five vehicles were measured using an on-road driving loop before and after emissions-related repairs, while another three vehicles were tested with no repairs performed. The on-road concentration data used to guide the repair process were converted to grams per gallon; when divided by estimated miles per gallon, this gave grams per mile emissions for comparison to IM240. Correlation coefficients (r²) of 0.87 for CO and 0.76 for HC were achieved for the 13 tests. The linear correlations between IM240 and emissions measured by this method would allow repair facilities to perform a relatively inexpensive test for diagnostic purposes and to estimate repair effectiveness without the need for a dynamometer.     

A Wind Tunnel Study of Gaseous Pollutants in City Street Canyons

Steady state mean concentrations of tracer gas were measured in a 400:1 scale model of an idealized city with variable geometry placed within a wind tunnel at various orientations to the mean flow for a free stream velocity of 6.8 ft/sec. The tracer gas was released from two parallel line sources to simulate lanes of traffic in an effort to quantify the persistence of pollution as well as the mean values realized at street levels. An aerodynamically rough turbulent boundary layer of neutral thermal stratification was employed to simulate the atmosphere. Values of concentration measured in the model city were converted to prototype concentrations in ppm and compared to National Ambient Air Quality Standards. It was shown that single isolated structures may cause favorable mixing of pollution downwind but very high concentrations exist in the immediate leeward vicinity of the building. Two favorable geometries for city blocks tested were found to reduce pedestrian exposure to pollution both near heavy traffic congestion and downwind. It was concluded that the pollutant dilution was controlled by the mean flow rather than by turbulent diffusion and that the lateral spread of the plume was slight as one proceeded downwind of the line source. The combination of favorable geometry and higher dilution velocities may bring pollution levels down to existing Air Quality Standards. The body of information presented in this paper should interest city planners and air quality monitoring personnel, as well as those researchers attempting to study and model flow in city street canyons. It provides order of magnitude estimates on pedestrian and office worker exposure to pollutants under a wide range of conditions.     

Mathematical models for accurate prediction of atmospheric visibility with particular reference to the seasonal and environmental patterns in Hong Kong

Atmospheric visibility impairment has gained increasing concern as it is associated with the existence of a number of aerosols as well as common air pollutants and produces unfavorable conditions for observation, dispersion, and transportation. This study analyzed the atmospheric visibility data measured in urban and suburban Hong Kong (two selected stations) with respect to time-matched mass concentrations of common air pollutants including nitrogen dioxide (NO(2)), nitrogen monoxide (NO), respirable suspended particulates (PM(10)), sulfur dioxide (SO(2)), carbon monoxide (CO), and meteorological parameters including air temperature, relative humidity, and wind speed. No significant difference in atmospheric visibility was reported between the two measurement locations (p > or = 0.6, t test); and good atmospheric visibility was observed more frequently in summer and autumn than in winter and spring (p < 0.01, t test). It was also found that atmospheric visibility increased with temperature but decreased with the concentrations of SO(2), CO, PM(10), NO, and NO(2). The results showed that atmospheric visibility was season dependent and would have significant correlations with temperature, the mass concentrations of PM(10) and NO(2), and the air pollution index API (correlation coefficients mid R: R mid R: > or = 0.7, p < or = 0.0001, t test). Mathematical expressions catering to the seasonal variations of atmospheric visibility were thus proposed. By comparison, the proposed visibility prediction models were more accurate than some existing regional models. In addition to improving visibility prediction accuracy, this study would be useful for understanding the context of low atmospheric visibility, exploring possible remedial measures, and evaluating the impact of air pollution and atmospheric visibility impairment in this region.     

Identification of soil heavy metal sources from anthropogenic activities and pollution assessment of Fuyang County, China

Understanding regional variations of soil heavy metals and their anthropogenic influence are very important for environmental planning. In this study, 286 surface soil samples were collected in Fuyang county, and the 'total' metals for copper (Cu), zinc (Zn), lead (Pb), cadmium (Cd) and nickel (Ni) were measured in 2005. Statistic analysis showed that Cu, Zn, Pb and Cd had been added by exterior factors, and Ni was mainly controlled by natural factors. The combination of multivariate statistical and geostatistical analysis successfully grouped three groups (Cu, Zn and Pb; Cd; and Ni) of heavy metals from different sources. Through pollution evaluation, it was found that 15.76% of the study area for Cu, Zn and Pb, and 46.14% for Cd suffered from moderate or severe pollution. Further spatial analysis identified the limestone mining activities, paper mills, cement factory and metallurgic activities were the main sources for the concentration of Cu, Zn, Pb and Cd in soils, and soil Ni was mainly determined by the parent materials.     

Predicting the biological condition of streams: use of geospatial indicators of natural and anthropogenic characteristics of watersheds

We developed and evaluated empirical models to predict biological condition of wadeable streams in a large portion of the eastern USA, with the ultimate goal of prediction for unsampled basins. Previous work had classified (i.e., altered vs. unaltered) the biological condition of 920 streams based on a biological assessment of macroinvertebrate assemblages. Predictor variables were limited to widely available geospatial data, which included land cover, topography, climate, soils, societal infrastructure, and potential hydrologic modification. We compared the accuracy of predictions of biological condition class based on models with continuous and binary responses. We also evaluated the relative importance of specific groups and individual predictor variables, as well as the relationships between the most important predictors and biological condition. Prediction accuracy and the relative importance of predictor variables were different for two subregions for which models were created. Predictive accuracy in the highlands region improved by including predictors that represented both natural and human activities. Riparian land cover and road-stream intersections were the most important predictors. In contrast, predictive accuracy in the lowlands region was best for models limited to predictors representing natural factors, including basin topography and soil properties. Partial dependence plots revealed complex and nonlinear relationships between specific predictors and the probability of biological alteration. We demonstrate a potential application of the model by predicting biological condition in 552 unsampled basins across an ecoregion in southeastern Wisconsin (USA). Estimates of the likelihood of biological condition of unsampled streams could be a valuable tool for screening large numbers of basins to focus targeted monitoring of potentially unaltered or altered stream segments.     

The impact of the tunnel exhausts in terms of heavy metals to the surrounding ecosystem

Samples of soil, plants, and lichens were analysed for heavy metal content (Cd, Cr, Cu, Ni, Pb, and Zn) in relation to different distances from the tunnel ventilation systems in order to evaluate the environmental pollution caused by car exhausts pollution from the Tauerntunnel and the Katschbergtunnel (Austria). Results show that the extent of heavy metal pollution is related to the type of tunnel ventilation system. The vertical ventilation system which ends in an exhaust air tower in the alpine pasture of Mosermandl 1,900 m above sea level contaminates soils and plants up to a distance of 750 m from the exhaust source. The dispersion of metals in front of the horizontal ventilation systems, which are located next to the tunnel portals, exhibits a rapid decrease with distance. Lichen transplants placed in front of the horizontal ventilation systems show very high metal accumulation, which gradually declines with the distance from the emitter source, therefore the lichen species Pseudevernia furfuracea can be used as a very efficient biomonitor for monitoring heavy metal pollution caused by tunnel exhausts over time. Data from former years (1986, 1988, 1990 and 1992) and from this present research suggest that the contamination of heavy metals at Mosermandl has decreased slightly in soil samples, except for Cu, but increased in plant samples, whereas a significant increase of Pb was observed.     

Non-intrusive characterization methods for wastewater-affected groundwater plumes discharging to an alpine lake

Streams and lakes in rocky environments are especially susceptible to nutrient loading from wastewater-affected groundwater plumes. However, the use of invasive techniques such as drilling wells, installing piezometers or seepage meters, to detect and characterize these plumes can be prohibitive. In this work, we report on the use of four non-intrusive methods for this purpose at a site in the Rocky Mountains. The methods included non-invasive geophysical surveys of subsurface electrical conductivity (EC), in-situ EC measurement of discharging groundwater at the lake-sediment interface, shoreline water sampling and nutrient analysis, and shoreline periphyton sampling and analysis of biomass and taxa relative abundance. The geophysical surveys were able to detect and delineate two high-EC plumes, with capacitively coupled ERI (OhmMapper) providing detailed two-dimensional images. In situ measurements at the suspected discharge locations confirmed the presence of high-EC water in the two plumes and corroborated their spatial extent. The nutrient and periphyton results showed that only one of the two high-EC plumes posed a current eutrophication threat, with elevated nitrogen and phosphorus levels, high localized periphyton biomass and major shifts in taxonomic composition to taxa that are commonly associated with anthropogenic nutrient loading. This study highlights the need to use non-intrusive methods in combination, with geophysical and water EC-based methods used for initial detection of wastewater-affected groundwater plumes, and nutrient or periphyton sampling used to characterize their ecological effects.     

Hyperspectral Characteristics of Canopy Components and Structure for Phenological Assessment of an Invasive Weed

Spectral reflectance values of four canopy components (stems, buds, opening flowers, and postflowers of yellow starthistle (Centaurea solstitialis)) were measured to describe their spectral characteristics. We then physically combined these canopy components to simulate the flowering stage indicated by accumulated flower ratios (AFR) 10%, 40%, 70%, and 90%, respectively. Spectral dissimilarity and spectral angles were calculated to quantitatively identify spectral differences among canopy components and characteristic patterns of these flowering stages. This study demonstrated the ability of hyperspectral data to characterize canopy components, and identify different flowering stages. Stems had a typical spectral profile of green vegetation, which produced a spectral dissimilarity with three reproduction organs (buds, opening flowers, and postflowers). Quantitative differences between simulated flower stages depended on spectral regions and phenological stages examined. Using full-range canopy spectra, the initial flowering stage could be separated from the early peak, peak, and late flowering stages by three spectral regions, i.e. the blue absorption (around 480 nm) and red absorption (around 650 nm) regions and NIR plateau from 730 nm to 950 nm. For airborne CASI data, only the red absorption region and NIR plateau could be used to identify the flowering stages in the field. This study also revealed that the peak flowering stage was more easily recognized than any of the other three stages.     

Energy-Based Land Use Predictors of Proximal Factors and Benthic Diatom Composition in Florida Freshwater Marshes

The Landscape Development Intensity index (LDI), which is based on non-renewable energy use and integrates diverse land use activities, was compared to other measures of LU (e.g., %agriculture, %urban) to determine its ability for predicting benthic diatom composition in freshwater marshes of peninsular Florida. In this study, 70 small, isolated herbaceous marshes located along a human disturbance gradient (generally agricultural) throughout peninsular Florida were sampled for benthic diatoms and soil and water physical/chemical parameters (i.e., TP, TKN, pH, specific conductance, etc.). Landscape measures of percent agriculture, percent urban, percent natural, and LDI index values were calculated for a 100 m buffer around each site. The strongest relationships using Mantel's r statistic, which ranges from −1 to 1, were found between benthic diatom composition, the combined soil and water variables, and LDI scores (r=0.51, P<0.0001). Although similar, soil and water variables alone (r=0.45, P<0.0001) or with percent agriculture or percent natural were not as strongly correlated (both Mantel's r=0.46, P<0.0001). Little urban land use was found in the areas surrounding the study wetlands. Diatom data were clustered using flexible beta into 2 groups, and stepwise discriminant analysis identified specific conductance, followed by LDI score, soil pH, water total phosphorus, and ammonia, as cluster-separating variables. The LDI explained slightly more of the variation in species composition than either percent agriculture or percent natural, perhaps because the LDI can combine disparate land uses into a single quantitative value. However, the ecological significance of the difference between land use metrics and diatom composition is controvertible, and additional tests including more varied land uses appear warranted.