Estimation of Smog Effects in the Hydrocarbon-Nitric Oxide System

Hydrocarbon components (propylene, simulated auto exhaust, or authentic auto exhaust) were irradiated in the presence of nitric oxide in large chambers instrumented for measurements of numerous variables. Eye irritation was measured using a selected panel of human subjects. The various dependent variables are presented as functions of the reactant concentrations by means of contour diagrams derived by computer treatment. The effect of “hydrocarbon” and nitric oxide levels on smog effects are discussed; the observed relationships between end effects and reaction rates are considered. The study simulated the effects of varying degrees of vehicular emissions control over one or both reactants and has a bearing on the establishment of vehicle emission standards in California.     

Condensed Sulfur Trioxide—Particulate or Vapor?

Sulfuric acid from condensed sulfur trioxide (SO₃) has been found in the filtering medium used in the EPA/APCO, WP-50, and high-volume sampling methods. The amount of sulfuric acid ranged from 1 8 to 78% of the total particulate matter found when sampling emissions from oil-fired boilers. These levels were high enough to determine whether a unit is in compliance with regulations. A question is raised as to whether condensed sulfur trioxide should be included in particulate measurements or eliminated after analyzing the filter medium.     

A Numerical Modeling Technique for Estimating Sulfur Dioxide Dry Deposition Due to Local Source Emissions

This paper describes a methodology for estimating the effect of local source emissions on dry deposition of sulfur dioxide in regions of complex terrain. Airflow in complex terrain is simulated by a time-dependent dynamical model for the meteorological fields. The results of the dynamical model are used to drive a semi-stochastic Lagrangian dispersion model in order to evaluate concentrations resulting from local source emissions. The Lagrangian dispersion model is coupled with a dry deposition treatment which includes the effects of both surface properties and micrometeoroiogical factors on deposition.

A sample application is discussed for a source in the Shenandoah Valley. The largest concentrations and deposition rates were obtained shortly after sunrise, during the transition from the nocturnal to the daytime flow regime. These results suggest that dry deposition may be episodic.     

The measurement of place attachment: Personal,community, and environmental connections

Place attachment has been researched extensively in the social and behavioural sciences over the past two decades. However, it is challenging for researchers to assimilate the mixed messages presented in the place attachment literature and to understand the multiple place attachment terms. In this study, a four-dimensional model of rural landholder attachments to their natural resource management region was conceptually and empirically developed with the aim of developing an integrated approach to the measurement of place attachment that clearly distinguishes between different elements of place scholarship. A 29-item place attachment scale with the dimensions of place identity, place dependence, nature bonding, and social bonding was tested on a random sample of rural landholders in the Adelaide and Mount Lofty Ranges in South Australia (N = 320). The majority of respondents were male (69.3%) and the average age was 59 years. The scale was reduced to 20-items and then administered simultaneously and in the same response format to rural landholders in two other areas of South Australia: the Northern and Yorke region (N = 664) and South Australian Murray-Darling Basin region (N = 659). In both studies, the majority of respondents were male (85%) and the average age was 55 years. Exploratory factor and reliability analyses of Adelaide and Mount Lofty Ranges and Northern and Yorke datasets produced a five-dimensional model of place attachment with high reliabilities. Social bonding divided into the constructs of family bonding and friend bonding. The refined five-dimensional model was then examined for convergent validity, with moderate but significant correlations found between individual attachment constructs and dependent variables expected to be related to the construct, such as place identity and length of residence, and nature bonding and time currently spent in nature. We used confirmatory factor analysis to test the goodness-of-fit of the South Australian Murray-Darling Basin (SAMDB) dataset to the proposed five-dimensional model and then compared its fit to the traditional two-dimensional model of place identity and place dependence. The five-dimensional model provided moderate fit for the SAMDB data. We conclude with a discussion of the validity and reliability of the five-dimensional model and its future role in place attachment research.     

Ammonia assessment from agriculture: U.S. status and needs

Recent studies suggest that human activities accelerate the production of reactive nitrogen on a global scale. Increased nitrogen emissions may lead to environmental impacts including photochemical air pollution, reduced visibility, changes in biodiversity, and stratospheric ozone depletion. In the last 50 yr, emissions of ammonia (NH3), which is the most abundant form of reduced reactive nitrogen in the atmosphere, have significantly increased as a result of intensive agricultural management and greater livestock production in many developed countries. These agricultural production practices are increasingly subject to governmental regulations intended to protect air resources. It is therefore important that an accurate and robust agricultural emission factors database exist to provide valid scientific support of these regulations. This paper highlights some of the recent work that was presented at the 2006 Workshop on Agricultural Air Quality in Washington, D.C. regarding NH3 emissions estimates and emission factors from agricultural sources in the U.S. and Europe. In addition, several best management practices are explored as the scientific community attempts to maximize the beneficial use of reactive nitrogen while simultaneously minimizing negative environmental impacts.     

Fuzzy input–output model for optimizing eco-industrial supply chains under water footprint constraints

Global water stress is expected to increase due to population growth, economic development and climate change. Because of this trend, there is an increased interest in the water intensity of industrial activities conducted via the product supply chain or within specified geographical boundaries or regions, both at the enterprise- or regulatory-level. The total water footprint of economic activities should be evaluated in consideration of local water resource consumption, virtual water trade and resource availability. As individual entities seek to protect their respective interests, the challenge is to optimize inter-regional trade of goods with the consideration of the interests of participants in the network. This work presents a fuzzy input–output model for optimizing supply chains under water footprint constraints. Two case studies, involving tile manufacturing and biofuel production, are considered to demonstrate the use of the model.     

GROUND WATER IN PERSPECTIVE1

ABSTRACT. Owing to their enormous capacity, ground-water reservoirs are at least equal in importance to the ground water itself. As regulators of water movement in the hydrological cycle, these reservoirs surpass all lakes combined, natural and manmade. While many aquifers are not well understood, data on many others are adequate for long-range broad-scale planning. An example is the basalt aquifer of the Snake River Plain in Idaho. However, the area has managerial problems which concern the time, the place and the feasibility of manipulations of water. All continents of the world contain great aquifers. For every huge aquifer, however, hundreds of smaller ones occur, and even these contain astonishing amounts of water. Aquifers in the Ohio River Basin of the United States are good examples. Management of total water resources is a difficult problem at many places. But many problems could be met and many water shortages alleviated or eliminated by use of aquifers, not merely as sources of water, but as reservoirs for management of water.     

Measuring terrestrial movement behavior using passive integrated transponder (PIT) tags: effects of tag size on detection, movement, survival, and growth

Movement behaviors have broad ecological and evolutionary implications, affecting individual fitness, metapopulation dynamics, the distribution and abundance of species, as well as gene flow and thus adaptation and speciation. However, movement behaviors such as dispersal, station keeping, and ranging are poorly understood in many taxa due to the incompatibility of traditional tracking methods with long-term observations. This is particularly true for small-bodied life history stages and species. While the introduction of smaller passive integrated transponder (PIT) tags and the development of PIT telemetry have removed some barriers, the trade-offs between different tag sizes are unknown. Through a series of experiments, we tested for effects of PIT tag size on detection, movement, tag retention, growth, and survival of a juvenile amphibian. We found no effect of PIT tag size on initial movement distance, survival, or growth; and all individuals retained their tag for the course of the experiment. Detection and recapture rates, however, were increased with PIT tag size. The orientation of the tag relative to the vertical axis of the antenna also affected the size of the detection field, which was 15.78–43.90 % smaller when the antenna was moved perpendicular rather than parallel to the long axis of the tag. We conclude that PIT telemetry is a suitable technique for marking previously untraceable species or life history stages and may offer insight into the behaviors of these individuals. Investigations using multiple PIT tag sizes should include this in statistical analyses to account for tag size biased detection differences.