Analysis of air pollution data at a mixed source location using boosted regression trees

This paper explores the use of boosted regression trees to draw inferences concerning the source characteristics at a location of high source complexity. Models are developed for hourly concentrations of nitrogen oxides (NO_X) close to a large international airport. Model development is discussed and methods to quantify model uncertainties developed. It is shown that good explanatory models can be developed and further, allowing for interactions between model variables significantly improves the model fits compared with non-interacting models. Methods are used to determine which variables exert most influence over predicted concentrations and to explore the NO_X dependency for each. Model predictions are used to estimate aircraft take-off contributions to total concentrations of NO_X and determine how these predictions are affected by annual variations in meteorological conditions and runway use patterns. Furthermore, the results relating to the aircraft contributions to total NO_X concentration are compared with those from a more detailed independent field campaign. Finally, we find empirical evidence that plumes from larger aircraft disperse more rapidly from the point of release compared with smaller aircraft. The reasons for this behaviour and the implications are discussed.     

Ammonia emissions from a representative in-use fleet of light and medium-duty vehicles in the California South Coast Air Basin

We used Fourier Transform Infrared Spectroscopy (FTIR) to measure tailpipe ammonia emissions from a representative fleet of 41 light and medium-duty vehicles recruited in the California South Coast Air Basin. A total of 121 chassis dynamometer emissions tests were conducted on these vehicles and the test results were examined to determine the effects of several key variables on ammonia emissions. Variables included vehicle type, driving cycle, emissions technology, ammonia precursor emissions (i.e. CO and NOx) and odometer readings/model year as a proxy for catalyst age. The mean ammonia emissions factor was 46 mg km^?1 (σ = 48 mg km^?1) for the vehicle fleet. Average emission factors for specific vehicle groups are also reported in this study. Results of this study suggest vehicles with the highest ammonia emission rates possess the following characteristics: medium-duty vehicles, older emissions technologies, mid-range odometer readings, and higher CO emissions. In addition, vehicles subjected to aggressive driving conditions are likely to be higher ammonia emitters. Since the vehicles we studied were representative of recent model year vehicles and technologies in urban airsheds, the results of our study will be useful for developing ammonia emissions inventories in Los Angeles and other urban areas where California-certified vehicles are driven. However, efforts should also be made to continue emissions testing on in-use vehicles to ensure greater confidence in the ammonia emission factors reported here.     

An analysis of assessment outcomes from eight years' operation of the Australian border weed risk assessment system

The majority of Australian weeds are exotic plant species that were intentionally introduced for a variety of horticultural and agricultural purposes. A border weed risk assessment system (WRA) was implemented in 1997 in order to reduce the high economic costs and massive environmental damage associated with introducing serious weeds. We review the behaviour of this system with regard to eight years of data collected from the assessment of species proposed for importation or held within genetic resource centres in Australia. From a taxonomic perspective, species from the Chenopodiaceae and Poaceae were most likely to be rejected and those from the Arecaceae and Flacourtiaceae were most likely to be accepted. Dendrogram analysis and classification and regression tree (TREE) models were also used to analyse the data. The latter revealed that a small subset of the 35 variables assessed was highly associated with the outcome of the original assessment. The TREE model examining all of the data contained just five variables: unintentional human dispersal, congeneric weed, weed elsewhere, tolerates or benefits from mutilation, cultivation or fire, and reproduction by vegetative propagation. It gave the same outcome as the full WRA model for 71% of species. Weed elsewhere was not the first splitting variable in this model, indicating that the WRA has a capacity for capturing species that have no history of weediness. A reduced TREE model (in which human-mediated variables had been removed) contained four variables: broad climate suitability, reproduction in less or than equal to 1year, self-fertilisation, and tolerates and benefits from mutilation, cultivation or fire. It yielded the same outcome as the full WRA model for 65% of species. Data inconsistencies and the relative importance of questions are discussed, with some recommendations made for improving the use of the system.     

The influence of radiopharmaceutical isotope production on the global radioxenon background

Radioxenon isotopes play a major role in confirming whether or not an underground explosion was nuclear in nature. It is then of key importance to understand the sources of environmental radioxenon to be able to distinguish them from those of a nuclear explosion.     

Prediction of SVOC vegetation and atmospheric concentrations using calculated deposition velocities

A simple modeling concept was previously applied to study air-foliage exchange of both polybrominated diphenyl ethers (PBDEs) and polycyclic aromatic hydrocarbons (PAHs) using field measurements. In this paper, the predictive capabilities of this framework were tested using an independent set of data collected at the same sampling location for a different time period. Firstly, atmospheric (particle-bound and gaseous phase) PBDE and PAH concentrations were used to predict their accumulation in spruce needles. Conversely, we used PBDE and PAH concentrations in vegetation to predict their atmospheric concentrations. In both cases, calculated and measured values showed good agreement, providing evidence that the developed framework and our derived deposition velocities can be used as a predictive tool for these two different classes of semi-volatile organic compounds.     

TBT contamination of remote marine environments: ship groundings and ice-breakers as sources of organotins in the Great Barrier Reef and Antarctica

Remote marine environments such as many parts of the Great Barrier Reef (GBR) and the Antarctic are often assumed to be among the most pristine natural habitats. While distance protects them from many sources of pollution, recent studies have revealed extremely high concentrations of organotins in areas associated with shipping activities. Sediments at sites of ship groundings on the GBR have been found to contain up to 340,000 microg Sn kg(-1). Very high concentrations (up to 2290 microg Sn kg(-1)) have been detected in nearshore Antarctic sediments adjacent to channels cut through sea ice by ice-breaking vessels. In both cases, the bulk of the contamination is associated with flakes of antifouling paint abraded from vessel hulls, resulting in patchy but locally intense contamination of sediments. These particulates are likely to continue releasing organotins, rendering grounding sites and ice-breaking routes point-sources of contamination of surrounding environments. While the areas exposed to biologically-harmful concentrations of leached chemicals are likely to be limited in extent (1000-10,000 m(2)), deposition of antifouling paints constitutes a persistent ecological risk in otherwise pristine marine environments of high conservation value. The risk of contamination of GBR and Antarctic sediments by organotins needs to be considered against an important alternative risk: that less effective antifouling of ships hulls may increase the frequency of successful invasions by non-indigenous species. Additional options to minimise ecological risk include accident prevention and reducing organotin contamination from grounding sites through removal or treatment of contaminated sediments, as has been done at some sites in the GBR.     

Assessment Tools for Urban Catchments: Defining Observable Biological Potential1

Abstract: Urbanization represents a strong and increasingly more prevalent impact on stream quality worldwide. One of the characteristic effects of increased urbanization is a consistent decline in biological stream condition. The characterization of this biological degradation with increasing urbanization presents a number of advantages for the study and management of urban streams and catchments. In this paper, the limitation of biological condition with urbanization, called observed biological potential, is characterized. Using an urban intensity index and a biological index developed specifically for urban systems in the Baltimore, Maryland; Cleveland, Ohio; and San Jose, California regions, two principal techniques were compared (quantile regression and bin regression) to define observed biological potential along urban gradients. Quantile regression was selected as the preferable tool for describing observed biological potential given the consistency with which it can be applied and its statistical efficiency, however, bin quantile regression performed similarly. Having identified a numeric approximation of observed biological potential, two methods for identifying factors related to distance from potential as a way of identifying critical environmental factors affecting biological condition in urban areas were explored. The results of this work can be used for identifying benchmarks for urban stream biological condition, identifying limiting catchment characteristics, and prioritizing urban stream management efforts.