Responses of microbial populations in the rhizosphere to deposition of simulated acidic rain onto foliage and/or soil

Air pollutants or some chemicals applied to plant foliage can alter the ecology of the rhizosphere. Experiments were conducted to distinguish among possible foliage-mediated versus soil- or root-mediated effects of acid deposition on microorganism in the rhizosphere. Seedlings of a sorghum x sudangrass hybrid in pots of non-sterile soil-sand mix in a greenhouse were exposed to simulated rain solution adjusted with H2SO4 + HNO3 to pH 4.9, 4.2, 3.5 or 2.8. Solutions were applied as simulated rain to foliage and soil, foliage only (soil covered by plastic, and deionized water applied directly to the soil), or soil only (solution applied directly to the soil). Solutions were applied on 16 days during a 6-week period (1.5 cm deposition in 1 h per application). Plant shoot and root dry weights and population densities of selected types of bacteria, filamentous actinomycetes and fungi in the rhizosphere were quantified after exposures were completed. Deposition of simulated acidic rain onto foliage alone had no effect on plant biomass or microbial population densities in the rhizosphere (colony-forming units per gram of rhizosphere soil). However, plant growth was stimulated and all microbial populations in the rhizosphere increased 3- to 8-fold with increased solution acidity (relative to pH 4.9 solution) when solution penetrated the soil. Statistical analyses indicated that the acid dose-population response relationships for soil-only and foliage-and-soil applications were not different. Thus, no foliage-mediated effect of simulated acidic rain on rhizosphere ecology was detected.     

Investigating the chemical nature of humic-like substances (HULIS) in North American atmospheric aerosols by liquid chromatography tandem mass spectrometry

The high-molecular weight water-soluble organic compounds present in atmospheric aerosols underwent functional-group characterization using liquid chromatography tandem mass spectrometry (LC-MS/MS), with a focus on understanding the chemical structure and origins of humic-like substances (HULIS) in the atmosphere. Aerosol samples were obtained from several locations in North America at times when primary sources contributing to organic aerosol were well-characterized: Riverside, CA, Fresno, CA, urban and peripheral Mexico City, Atlanta, GA, and Bondville, IL. Chemical analysis targeted identification and quantification of functional groups, such as aliphatic, aromatic, and bulk carboxylic acids, organosulfates, and carbohydrate-like substances that comprise species with molecular weights (MW) 200–600 amu. Measured high-MW functional groups were compared to modeled primary sources with the purpose of identifying associations between aerosol sources, high-MW aerosol species, and HULIS. Mobile source emissions were linked to high-molecular weight carboxylic acids, especially aromatic acids, biomass burning was associated with carboxylic acids and carbohydrate-like substances, and secondary organic aerosol (SOA) correlated well with the total amount of HULIS measured, whereas organosulfates showed no correlation with aerosol sources and exhibited unique spatial trends. These results suggested the importance of motor vehicles, biomass burning, and SOA as important sources of precursors to HULIS. Structural characteristics of atmospheric HULIS were compared to terrestrial humic and fulvic acids and revealed striking similarities in chemical structure, with the exception of organosulfates which were unique to atmospheric HULIS.     

Exploring the Crowding–Satisfaction Relationship in Recreational Boating

Along with the growing boating population and the number of boats in use on limited inland waterways, boater expectations of setting density, safety perceptions, and the associated impacts on their experience (e.g., satisfaction) are becoming increasingly important. The primary purpose of this article was to explore a recreational boating crowding–satisfaction model derived from previous work using safety and enjoyment as mediating variables. We also tested our crowding–satisfaction model among day and overnight users. Our analysis revealed no significant difference between day and overnight users for any of the relationships tested in our model. Our final model indicated as respondents’ expectations for seeing people increased along with their feelings of being crowded, they were more inclined to consider the conditions on the lake as being unsafe. They were also more inclined to indicate that the number of people they had seen on the lake detracted from their boating experience. Respondents’ satisfaction was tied to their perceptions of crowding. Mediating variables illustrated that the relationship was conditioned by perceptions of safety and enjoyment. Analysis of the indirect effect observed in our study illustrate that when the number of people seen on the lake exceed respondents’ expectations, their perceptions of safety and enjoyment both decline, resulting in lower satisfaction. These findings have implications for managing recreational boating use on inland lake systems. Given the role played by expectations in our model, efforts to communicate with boaters about conditions on these waterways is important for helping them plan their boating experience and avoid situations they consider unsafe or unsatisfactory.     

Contribution of transition metals in the reactive oxygen species activity of PM emissions from retrofitted heavy-duty vehicles

We assessed the contribution of water-soluble transition metals to the reactive oxygen species (ROS) activity of diesel exhaust particles (DEPs) from four heavy-duty vehicles in five retrofitted configurations (V-SCRT, Z-SCRT, DPX, hybrid, and school bus). A heavy-duty truck without any control device served as the baseline vehicle. Particles were collected from all vehicle-configurations on a chassis dynamometer under three driving conditions: cruise (80 km h^?1), transient UDDS, and idle. A sensitive macrophage-based in vitro assay was used to determine the ROS activity of collected particles. The contribution of water-soluble transition metals in the measured activity was quantified by their removal using a Chelex^® complexation method. The study demonstrates that despite an increase in the intrinsic ROS activity (per mass basis) of exhaust PM with use of most control technologies, the overall ROS activity (expressed per km or per h) was substantially reduced for retrofitted configurations compared to the baseline vehicle. Chelex treatment of DEPs water extracts removed a substantial (≥70%) and fairly consistent fraction of the ROS activity, which ascertains the dominant role of water-soluble metals in PM-induced cellular oxidative stress. However, relatively lower removal of the activity in few vehicle-configurations (V-SCRT, DPX and school bus idle), despite a large aggregate metals removal, indicated that not all species were associated with the measured activity. A univariate regression analysis identified several transition metals (Fe, Cr, Co and Mn) as significantly correlated (R > 0.60; p < 0.05) with the ROS activity. Multivariate linear regression model incorporating Fe, Cr and Co explained 90% of variability in ROS levels, with Fe accounting for the highest (84%) fraction of the variance.     

Environmental Management of Human Waste Disposal for Recreational Boating Activities

/ A methodology to estimate the number of pump-out facilities and dump stations required to service human waste disposal for recreational power boating activities in Pennsylvania during the 1994 boating season is described. Study results suggest that a total of 39 additional pump-out stations and 13 dump stations may be required on seven major waterbodies: The Three Rivers Area, Lake Erie/Presque Isle Bay, Raystown Lake, the Susquehanna River, the Delaware River, Lake Wallenpaupack, and the Kinzua Reservoir. Suggestions for improving the methodology are provided. KEY WORDS: Human waste; Recreation; Power boating; Waste facilities; Waste disposal; Pennsylvania     

Effects of experimental protocol on global vegetation model accuracy: A comparison of simulated and observed vegetation patterns for Asia

Prognostic vegetation models have been widely used to study the interactions between environmental change and biological systems. This study examines the sensitivity of vegetation model simulations to: (i) the selection of input climatologies representing different time periods and their associated atmospheric CO₂ concentrations, (ii) the choice of observed vegetation data for evaluating the model results, and (iii) the methods used to compare simulated and observed vegetation. We use vegetation simulated for Asia by the equilibrium vegetation model BIOME4 as a typical example of vegetation model output. BIOME4 was run using 19 different climatologies and their associated atmospheric CO₂ concentrations. The Kappa statistic, Fuzzy Kappa statistic and a newly developed map-comparison method, the Nomad index, were used to quantify the agreement between the biomes simulated under each scenario and the observed vegetation from three different global land- and tree-cover data sets: the global Potential Natural Vegetation data set (PNV), the Global Land Cover Characteristics data set (GLCC), and the Global Land Cover Facility data set (GLCF). The results indicate that the 30-year mean climatology (and its associated atmospheric CO₂ concentration) for the time period immediately preceding the collection date of the observed vegetation data produce the most accurate vegetation simulations when compared with all three observed vegetation data sets. The study also indicates that the BIOME4-simulated vegetation for Asia more closely matches the PNV data than the other two observed vegetation data sets. Given the same observed data, the accuracy assessments of the BIOME4 simulations made using the Kappa, Fuzzy Kappa and Nomad index map-comparison methods agree well when the compared vegetation types consist of a large number of spatially continuous grid cells. The results of this analysis can assist model users in designing experimental protocols for simulating vegetation.     

Future Climate in the Yellowstone National Park Region and Its Potential Impact on Vegetation

Biotic responses to future changes in global climate are difficult to project for a particular region because the responses involve processes that operate at many spatial scales. This difficulty is exacerbated in mountainous regions, where future vegetation changes are often portrayed as simple upward displacements of vegetation zones in response to warming. We examine the scope of future responses that may occur in a mountainous area by illustrating the potential distributions of selected tree taxa in the region of Yellowstone National Park. The output of a coarse-resolution climate model that incorporated a doubling of carbon dioxide concentration in the atmosphere was interpolated onto a 5-minute grid of topographically adjusted climate data. The output was also used as input into statistical relationships between the occurrence of individual taxa and climate. The simulated vegetation changes include a combination of elevational and directional range adjustments. The range of high-elevation species decreases, and some species become regionally extirpated. The new communities have no analogue in the present-day vegetation because they mix low-elevation montane species currently in the region with extralocal species from the northern and central Rocky Mountains and Pacific Northwest. The projected climate changes within the Yellowstone region and the individualism displayed by species in their potential range adjustments are equal or greater than the changes seen in the paleoecologic record during previous warming intervals. Although the results support conservation strategies that include habitat connectivity, the magnitude of the changes may exceed the ability of species to adjust their ranges. The predicted patterns call into question the adequacy of current management objectives to cope with the scope of future changes.     

Making decisions about environmental management when conventional economic analysis cannot be used

A process is described for making comparative valuations of a wide range of environmental management activities when the combined social, economic, managerial, and political benefits of some (but not all) of these activities cannot be adequately described in economic terms and when budgetary constraints do not permit funding of all activities under consideration. The process accounts for subjective judgment and contains a formal rigorous decision strategy that takes the place of intuition when quantitative and qualitative values of environmental activities need to be evaluated.     

Source identification of personal exposure to fine particulate matter using organic tracers

Personal exposure to fine particulate matter (PM2.5) is due to both indoor and outdoor sources. Contributions of sources to personal exposure can be quite different from those observed at ambient sampling locations. The primary goal of this study was to investigate the effectiveness of using trace organic speciation data to help identify sources influencing PM2.5 exposure concentrations. Sixty-four 24-h PM2.5 samples were obtained on seven different subjects in and around Boulder, CO. The exposure samples were analyzed for PM2.5 mass, elemental and organic carbon, organic tracer compounds, water-soluble metals, ammonia, and nitrate. This study is the first to measure a broad distribution of organic tracer compounds in PM2.5 personal samples. PM2.5 mass exposure concentrations averaged 8.4 μg m^?3. Organic carbon was the dominant constituent of the PM2.5 mass. Forty-four organic species and 19 water-soluble metals were quantifiable in more than half of the samples. Fifty-four organic species and 16 water-soluble metals had measurement signal-to-noise ratios larger than two after blank subtraction.The dataset was analyzed by Principal Component Analysis (PCA) to determine the factors that account for the greatest variance. Eight significant factors were identified; each factor was matched to its likely source based primarily on the marker species that loaded the factor. The results were consistent with the expectation that multiple marker species for the same source loaded the same factor. Meat cooking was an important source of variability. The factor that represents meat cooking was highly correlated with organic carbon concentrations (r = 0.84). The correlation between ambient PM2.5 and PM2.5 exposure was relatively weak (r = 0.15). Time participants spent performing various activities was generally not well correlated with PCA factor scores, likely because activity duration does not measure emissions intensity. The PCA results demonstrate that organic tracers can aid in identifying factors that influence personal exposures to PM2.5.