A Pilot Indoor-Outdoor Study of Organic Particulate Matter and Particulate Mutagenicity

Abstract

Many large metropolitan areas experience elevated concentrations of ground-level ozone pollution during the summertime “smog season”. Local environmental or health agencies often need to make daily air pollution forecasts for public advisories and for input into decisions regarding abatement measures and air quality management. Such forecasts are usually based on statistical relationships between weather conditions and ambient air pollution concentrations. Multivariate linear regression models have been widely used for this purpose, and well-specified regressions can provide reasonable results. However, pollution-weather relationships are typically complex and nonlinear—especially for ozone—properties that might be better captured by neural networks. This study investigates the potential for using neural networks to forecast ozone pollution, as compared to traditional regression models. Multiple regression models and neural networks are examined for a range of cities under different climate and ozone regimes, enabling a comparative study of the two approaches. Model comparison statistics indicate that neural network techniques are somewhat (but not dramatically) better than regression models for daily ozone prediction, and that all types of models are sensitive to different weather-ozone regimes and the role of persistence in aiding predictions.     

Formaldehyde Dose-Response in Healthy Nonsmokers

Industrial, commercial, and domestic levels of formaldehyde exposure range from <0.1 to >5.0 ppm. Irritation of the eyes and upper respiratory tract predominate, and bronchoconstriction is described in case reports. However, pulmonary function and irritant symptoms together have not been assessed over a range of HCHO concentrations in a controlled environment. We investigated dose response in both symptoms and pulmonary function associated with 3-h exposures to 0.0-3.0 ppm HCHO in a controlled environmental chamber. Ten subjects were randomly exposed to 0.0, 0.5, 1.0, and 2.0 ppm HCHO at rest plus 2.0 ppm HCHO with exercise and nine additional subjects were randomly exposed to 0.0,1.0,2.0, and 3.0 ppm HCHO at rest plus 2.0 ppm HCHO with exercise. Significant dose-response relationships in odor and eye irritation were observed (p < 0.05). Nasal flow resistance was increased at 3.0 ppm (p < 0.01), but not at 2.0 ppm HCHO. There were no significant decrements in pulmonary function (FVC, FEV₁, FEF_25-75%, SGaw) or increases in bronchial reactivity to methacholine (log PD_35SGaw) with exposure to 0.5-3.0 ppm HCHO at rest or to 2.0 ppm HCHO with exercise.     

Rotary Kiln Incineration III. An Indepth Study—Kiln Exit/Afterburner/Stack Train and Kiln Exit Pattern Factor Measurements During Liquid CCl4 Processing

Temperature and stable species concentration data are presented from various locations within a full-scale rotary kiln incinerator firing natural gas/carbon tetrachloride/air. The data are being collected as part of a cooperative program involving university, industry and government participation. The overall goal of the program is to develop a more sophisticated understanding of and a predictive capability for rotary kiln and afterburner performance as influenced by basic design and operational parameters. Non-uniformities in stable species and temperature exist for this particular kiln, at the kiln exit, under certain operating conditions. Flow perturbations from within the kiln were found to persist into the afterburner, but not into the stack. High destruction and removal efficiencies (DRE’s) were achieved under the operating conditions of these tests through adequate secondary combustion processing.     

Rotary Kiln Incineration IV. An Indepth Study— Kiln Exit,Transition and Afterburner Sampling During Liquid CCl4 Processing

Detailed temperature and stable species concentration data are presented from the kiln exit, transition section and afterburner of a full-scale incinerator facility firing natural gas/carbon tetrachloride/air. The data are collected as part of a cooperative program involving university, industry and government participation. The overall goal of the program is to develop an understanding and predictive capability for rotary kiln and afterburner performance as influenced by basic design and operational parameters. The data demonstrate that nonuniformities in stable species and temperature exist, under certain operating conditions, at the kiln exit in the vertical direction only. Measurements from the transition section indicate that non-uniformities may exist within this region under certain operating conditions. Flow perturbations from within the kiln can persist into the afterburner, although the degree of nonuniformity is substantially reduced compared to either the kiln or transition sections. High destruction and removal efficiencies were achieved under all operating conditions of these tests through a combination of kiln and secondary combustion processing.     

An Intelligent Emissions Controller for Fuel Lean Gas Reburn in Coal-Fired Power Plants

ABSTRACT

The application of artificial intelligence techniques for performance optimization of the fuel lean gas reburn (FLGR) system is investigated. A multilayer, feedforward artificial neural network is applied to model static nonlinear relationships between the distribution of injected natural gas into the upper region of the furnace of a coal-fired boiler and the corresponding oxides of nitrogen (NO_x) emissions exiting the furnace. Based on this model, optimal distributions of injected gas are determined such that the largest NO_x reduction is achieved for each value of total injected gas. This optimization is accomplished through the development of a new optimization method based on neural networks. This new optimal control algorithm, which can be used as an alternative generic tool for solving multidimensional nonlinear constrained optimization problems, is described and its results are successfully validated against an off-the-shelf tool for solving mathematical programming problems. Encouraging results obtained using plant data from one of Commonwealth Edison's coal-fired electric power plants demonstrate the feasibility of the overall approach.

Preliminary results show that the use of this intelligent controller will also enable the determination of the most cost-effective operating conditions of the FLGR system by considering, along with the optimal distribution of the injected gas, the cost differential between natural gas and coal and the open-market price of NO_x emission credits. Further study, however, is necessary, including the construction of a more comprehensive database, needed to develop high-fidelity process models and to add carbon monoxide (CO) emissions to the model of the gas reburn system.     

Second generation anticoagulant rodenticides in predatory birds: Probabilistic characterisation of toxic liver concentrations and implications for predatory bird populations in Canada

Second-generation anticoagulant rodenticides (SGARs) are widely used to control rodent pests but exposure and poisonings occur in non-target species, such as birds of prey. Liver residues are often analysed to detect exposure in birds found dead but their use to assess toxicity of SGARs is problematic. We analysed published data on hepatic rodenticide residues and associated symptoms of anticoagulant poisoning from 270 birds of prey using logistic regression to estimate the probability of toxicosis associated with different liver SGAR residues. We also evaluated exposure to SGARs on a national level in Canada by analysing 196 livers from great horned owls (Bubo virginianus) and red-tailed hawks (Buteo jamaicensis) found dead at locations across the country. Analysis of a broader sample of raptor species from Quebec also helped define the taxonomic breadth of contamination. Calculated probability curves suggest significant species differences in sensitivity to SGARs and significant likelihood of toxicosis below previously suggested concentrations of concern (<0.1mg/kg). Analysis of birds from Quebec showed that a broad range of raptor species are exposed to SGARs, indicating that generalised terrestrial food chains could be contaminated in the vicinity of the sampled areas. Of the two species for which we had samples from across Canada, great horned owls are exposed to SGARs to a greater extent than red-tailed hawks and the liver residue levels were also higher. Using our probability estimates of effect, we estimate that a minimum of 11% of the sampled great horned owl population is at risk of being directly killed by SGARs. This is the first time the potential mortality impact of SGARs on a raptor population has been estimated.     

Quantifying summed fullerene nC60 and related transformation products in water using LC LTQ Orbitrap MS and application to environmental samples

The application of engineered nanomaterials increases strongly. Development of analytical techniques and their application to environmental samples is essential for human and environmental risk assessment of the nanoparticles. The objective of this study was to develop a sensitive analytical method to quantify nC(60) in water, using accurate mass screening liquid chromatography-hybrid linear ion trap Orbitrap mass spectrometry. nC(60) can be transformed by oxidation, reduction and photochemical reaction. Therefore, the formation of some transformation products of nC(60) was studied as well. Finally, the developed analytical method was applied to surface water samples from several locations in the Netherlands. The developed method enabled to detect and quantify aqueous concentrations of the summed nC(60) and its transformation products as low as 5 ng/L. It was observed that nC(60) transformation products exceed quantities of the parent C(60). Despite the high sensitivity of the developed method, no nC(60) or transformation products were detected in an array of Dutch surface waters. This might be due to low emissions, losses in the aqueous phase by sedimentation, sorption or further transformation processes.     

Impact and cost of measures to reduce nutrient emissions from wastewater and storm water treatment in the German Elbe river basin

As a leading nutrient emitter, wastewater infrastructure harbors significant technical potentials to reduce the water-polluting emissions of phosphorus and nitrogen into the Elbe river basin. From the viewpoint of the central infrastructure, the effluent threshold value of urban wastewater treatment plants could be lowered further by advanced use of denitrification and membrane filtration, and storm water overflows of wastewater and contaminated rainwater from sewers could be treated in retention soil filters. In addition, small-scale wastewater treatment plants, infiltration and reducing or unsealing impervious surfaces could be used as decentralized elements of wastewater or storm water treatment. It can be shown that if the most advanced measures were applied in all wastewater-relevant areas, up to 60% of the phosphorus and 37% of the nitrogen emissions could be avoided. Alongside central wastewater treatment plants, small-scale treatment plants prove to be the most effective and cost-efficient option. To achieve an ecologically acceptable state of the Elbe, however, it may be necessary to employ more costly measures as well.     

Projecting Climate Change Effects on Forest Net Primary Productivity in Subtropical Louisiana,USA

This study projected responses of forest net primary productivity (NPP) to three climate change scenarios at a resolution of 5 km × 5 km across the state of Louisiana, USA. In addition, we assessed uncertainties associated with the NPP projection at the grid and state levels. Climate data of the scenarios were derived from Community Climate System Model outputs. Changes in annual NPP between 2000 and 2050 were projected with the forest ecosystem model PnET-II. Results showed that forest productivity would increase under climate change scenarios A1B and A2, but with scenario B1, it would peak during 2011–2020 and then decline. The projected average NPP under B1 over the years from 2000 to 2050 was significantly different from those under A1B and A2. Forest NPP appeared to be primarily a function of temperature, not precipitation. Uncertainties of the NPP projection were due to large spatial resolution of the climate variables. Overall, this study suggested that in order to project effects of climate change on forest ecosystem at regional level, modeling uncertainties could be reduced by increasing the spatial resolution of the climate projections.     

Hydrocarbon degradation, plant colonization and gene expression of alkane degradation genes by endophytic Enterobacter ludwigii strains

The genus Enterobacter comprises a range of beneficial plant-associated bacteria showing plant growth promotion. Enterobacter ludwigii belongs to the Enterobacter cloacae complex and has been reported to include human pathogens but also plant-associated strains with plant beneficial capacities. To assess the role of Enterobacter endophytes in hydrocarbon degradation, plant colonization, abundance and expression of CYP153 genes in different plant compartments, three plant species (Italian ryegrass, birdsfoot trefoil and alfalfa) were grown in sterile soil spiked with 1% diesel and inoculated with three endophytic E. ludwigii strains. Results showed that all strains were capable of hydrocarbon degradation and efficiently colonized the rhizosphere and plant interior. Two strains, ISI10-3 and BRI10-9, showed highest degradation rates of diesel fuel up to 68% and performed best in combination with Italian ryegrass and alfalfa. All strains expressed the CYP153 gene in all plant compartments, indicating an active role in degradation of diesel in association with plants.