Analysis of cloud and precipitation chemistry at Whiteface Mountain,NY

Federal and state programs over the past two decades have resulted in the reduction of emissions of precursors of acid rain. Concomitant with these changes, measured concentrations of acidity in precipitation and in watersheds have shown a downward trend or improvement. However, another pathway for these precursors is through cloud and fog events that often tend to occur at high-elevation regions affecting the fauna and flora as well. In this study we report on long-term measurements of cloud water and precipitation chemistry made from 1994 onwards at a high-elevation location, Whiteface Mountain NY, in the northeastern United States. Trends and inter-relationship between the ions were examined along with ambient SO₂ measurements and Adirondack lakes chemistry data.     

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.     

Further studies on the uptake of persistent organic pollutants (POPs) by polyurethane foam disk passive air samplers

Passive air samplers (PAS) can be used to monitor semi-volatile organic compounds in the atmosphere. Polyurethane foam (PUF) disks are a popular sampling medium because they have a high retention capacity for such compounds. This paper reports a highly time-resolved uptake study, to derive uptake rate data under field conditions, and investigate the effects of using different foam densities on the uptake rate. PUF disks were deployed alongside an active sampler, for periods of up to 12 weeks. The uptake rates were measured for a range of gas- and particle-bound persistent organic pollutants (polychlorinated biphenyls (PCBs) and polybrominated diphenyl ethers (PBDEs)), of different properties, to explore whether gas–particle partitioning affected uptake rate. Uptake rates for two different densities of foam (0.021 and 0.035 g cm^?3) were not statistically significantly different from each other. Uptake rates of light PCBs averaged ～6.5 m³ day^?1, somewhat higher than in previous studies; higher wind speeds and lower temperatures in this study are the likely reason for this difference. The study showed: i) the uptake rate of the compound with lowest K_OA considered in this study (PCB-28/31) declined in the later weeks, indicating an approach to equilibrium; ii) uptake rates of lighter BDEs and heavier PCBs (compounds of intermediate K_OA in this study) remain similar throughout the study period, indicating that they are not approaching equilibrium during the 12-week-study; iii) uptake rates were typically: ～8 m³ day^?1 for PCB-52; ～9.5 m³ day^?1 for PCB-95; ～11 m³ day^?1 for BDE-28 and ～2 m³ day^?1 BDE-99. The latter compound has an important particle-bound component and this lowers the sampling rate compared to predicted uptake rates for compounds which are in the gas phase only. It is shown that knowledge of gas–particle partitioning is needed to correct for this effect, and to improve predicted uptake rates.     

Atmospheric chemistry of perfluorobutenes (CF3CFCFCF3 and CF3CF2CFCF2): Kinetics and mechanisms of reactions with OH radicals and chlorine atoms,IR spectra,global warming potentials,and oxidation to perfluorocarboxylic acids

Relative rate techniques were used to determine k(Cl + CF₃CFCFCF₃) = (7.27 ± 0.88) × 10^?12, k(Cl + CF₃CF₂CFCF₂) = (1.79 ± 0.41) × 10^?11, k(OH + CF₃CFCFCF₃) = (4.82 ± 1.15) × 10^?13, and k(OH + CF₃CF₂CFCF₂) = (1.94 ± 0.27) × 10^?12 cm³ molecule^?1 s^?1 in 700 Torr of air or N₂ diluent at 296 K. The chlorine atom- and OH radical-initiated oxidation of CF₃CFCFCF₃ in 700 Torr of air gives CF₃C(O)F in molar yields of 196 ± 11 and 218 ± 20%, respectively. Chlorine atom-initiated oxidation of CF₃CF₂CFCF₂ gives molar yields of 97 ± 9% CF₃CF₂C(O)F and 97 ± 9% COF₂. OH radical-initiated oxidation of CF₃CF₂CFCF₂ gives molar yields of 110 ± 15% CF₃CF₂C(O)F and 99 ± 8% COF₂. The atmospheric fate of CF₃CF₂C(O)F and CF₃C(O)F is hydrolysis to give CF₃CF₂C(O)OH and CF₃C(O)OH. The atmospheric lifetimes of CF₃CFCFCF₃ and CF₃CF₂CFCF₂ are determined by reaction with OH radicals and are approximately 24 and 6 days, respectively. The contribution of CF₃CFCFCF₃ and CF₃CF₂CFCF₂ to radiative forcing of climate change will be negligible.     

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.     

Evaluation of the aggressive potential of marine chloride and sulfate salts on mortars applied as renders in the Metropolitan Region of Salvador--Bahia, Brazil

In recent years, growing interest has focused on determining the performance of materials and evaluating the service life of structures exposed to various environmental forces. In this context, the determination of the aggressive potential of marine salts on mortars used as external renders is critical. The present study aimed to evaluate the spatial distribution of marine salts relative to distance from the sea. This was done by monitoring the deposition rate of chlorides and sulfates in wet candle sensors, located at nine stations scattered around the Metropolitan Region of Salvador, state of Bahia, Brazil. The study also determined the effectiveness of water-soluble salts at penetrating three different types of mortars of varying cement content via deposition and diffusion. The methodology employed enabled an evaluation of the efficiency of the monitoring sensors' measurement of the aggressiveness potential of local marine aerosol, and determination of the comparative performance of the three mortars tested, from the standpoint of resistance to salt penetration. The type and amount of salts captured both in solution and in powder samples extracted from the mortars were determined by ion chromatography. The analysis of the various types of mortars tested indicated which types are more resistant to the aggressive potential of the region's marine aerosol and the distance from the shore where local buildings are liable to be most strongly affected.     

Approximating the distribution of recreational visits from on-site survey data

While convenient and often used, on-site surveys are biased by the fact that users who visit the site more often are proportionately more likely to be sampled. This so-called avidity or size biased sampling results in over-estimating the visitation patterns of the average user. This analysis develops a rule of thumb method that may easily be applied by recreation site managers to visitation data collected on-site in order to infer behavior of the average user of the site. The key assumption that drives the derivation is that the visitation data of users is logarithmically distributed. To evaluate the methodology, we analyze several data sets of recreational users assuming that they reflect the populations of users and from these construct hypothetical on-site samples.     

The reliability of experts' opinions in constructing a composite environmental index: The case of ESI 2005

The complexity of the environment demands a well-constructed composite environmental index (CEI) to provide a useful tool to draw attention to environmental conditions and trends for policy purposes. Among the common difficulties in constructing a proper CEI are uncertainties due to the selection of the most representative underlying variables or indicators. A degree of uncertainty accompanies experts' judgments, and to deal with vague, subjective or inconsistent information, logic other than classic is required. This study analyzes a procedure that uses different experts' opinions in constructing a CEI, with the use of paraconsistent annotated logic. For this, a sensitivity analysis of the Environmental Sustainability Index (ESI 2005) was used as an example to assess the reliability of experts' opinions. The uncertainty due to the disagreement in experts' opinions clearly indicates that the forms we presently use to measure and monitor the actual environment are insufficient, that is, there is a lack of a “science of sustainability”.     

Predicting land cover using GIS, Bayesian and evolutionary algorithm methods

Modelling land cover change from existing land cover maps is a vital requirement for anyone wishing to understand how the landscape may change in the future. In order to test any land cover change model, existing data must be used. However, often it is not known which data should be applied to the problem, or whether relationships exist within and between complex datasets. Here we have developed and tested a model that applied evolutionary processes to Bayesian networks. The model was developed and tested on a dataset containing land cover information and environmental data, in order to show that decisions about which datasets should be used could be made automatically. Bayesian networks are amenable to evolutionary methods as they can be easily described using a binary string to which crossover and mutation operations can be applied. The method, developed to allow comparison with standard Bayesian network development software, was proved capable of carrying out a rapid and effective search of the space of possible networks in order to find an optimal or near-optimal solution for the selection of datasets that have causal links with one another. Comparison of land cover mapping in the North-East of Scotland was made with a commercial Bayesian software package, with the evolutionary method being shown to provide greater flexibility in its ability to adapt to incorporate/utilise available evidence/knowledge and develop effective and accurate network structures, at the cost of requiring additional computer programming skills. The dataset used to develop the models included GIS-based data taken from the Land Cover for Scotland 1988 (LCS88), Land Capability for Forestry (LCF), Land Capability for Agriculture (LCA), the soil map of Scotland and additional climatic variables.