Investigation into the use of satellite data in aiding characterization of particulate air quality in the Atlanta, Georgia metropolitan area

Poor air quality episodes occur often in metropolitan Atlanta, GA. The primary focus of this research is to assess the capability of satellites as a tool in characterizing air quality in Atlanta. Results indicate that intracity PM2.5 (particulate matter < or = 2.5 microm in aerodynamic diameter) concentrations show similar patterns as other U.S. urban areas, with the highest concentrations occurring within the city. PM2.5 and MODIS (Moderate Resolution Imaging Spectroradiometer) aerosol optical depth (AOD) have higher values in the summer than spring, yet MODIS AOD doubles in the summer unlike PM2.5. Most (80%) of the Ozone Monitoring Instrument aerosol index (AI) is below 0.5 with little differences between spring and summer. Using this value as a constraint of the carbonaceous aerosol signal in the urban area, aerosol transport events such as wildfire smoke associated with higher positive AI values can be identified. The results indicate that MODIS AOD is well correlated with PM2.5 on a yearly and seasonal basis with correlation coefficients as high as 0.8 for Terra and 0.7 for Aqua. A possible alternative view of the PM2.5 and AOD relationship is seen through the use of AOD thresholds. These probabilistic thresholds provide a means to describe the air quality index (AQI) through the use of multiyear AOD records for a specific area. The National Ambient Air Quality Standards (NAAQS) are used to classify the AOD into different AQI codes and probabilistically determine thresholds of AOD that represent most of a specific AQI category. For example, 80% of cases of moderate AQI days have AOD values between 0.5 and 0.6. The development of AOD thresholds provides a useful tool for evaluating air quality from the use of satellites in regions where there are sparse ground-based measurements of PM2.5.     

Evaluation of Four Live-Sorting Methods for Use in Rapid Biological Assessments Using Macroinvertebrates

Rapid bioassessment (RBA) techniques for evaluating river health are now commonplace and there is much debate on the best methods that should be used. One of the important features of RBA is subsampling of large qualitative or semi-quantitative samples to reduce the costs associated with handling and identifying animals. In Australia, the Australian River Assessment System (known as “AusRivAS”) has been widely used since 1994 to monitor and assess river health. To test the efficacy of AusRivAS protocols, four live-sorting protocols, the standard Australian River Assessment Scheme (AusRivAS) and three suggested improvements, were evaluated in three habitat types and in clear and turbid rivers. The suggested improvements included using magnification during the live-sort process, separate sorting of coarse and fine fractions and increasing the amount of time or animals collected. There was no statistically significant difference between any of the trialed live-sort protocols in terms of the number of taxa collected compared to the number remaining, the community composition, the abundances of individual families collected, or the AusRivAS Observed/Expected taxa ratios. The lack of differences between the live-sort protocols suggests that technicians using the current standard AusRivAS protocols are able to effectively obtain a representative subsample of animals from the whole kick or sweep net qualitative sample. This has the advantage of cost savings because no retraining will be required, field procedures will remain uncomplicated and previous river health assessments will remain valid.     

Short-Term Forecasting of Nitrogen Dioxide (NO<Subscript>2</Subscript>) Levels Using a Hybrid Statistical and Air Mass History Modelling Approach

A novel hybrid model has been developed to support the provision of real-time air quality forecasts. Statistical techniques have been applied in parallel with air mass history modelling to provide an efficient and accurate forecasting system with the ability to identify high NO₂ events, which tend to be the episodes of most significance in Ireland. Air mass history modelling and k-means clustering are used to identify air mass types that lead to high NO₂ levels in Ireland. Trajectory matching techniques allow data associated with these air masses to be partitioned during model development. Non-parametric regression (NPR) has been applied to describe nonlinear variations in concentration levels with wind speed, direction and season and produce a set of linearized factors which, together with other meteorological variables, are employed as inputs to a multiple linear regression. The model uses an innovative integrated approach to combine the NPR with the air mass history modelling results. On validation, a correlation coefficient of 0.75 was obtained, and 91 % of daily maximum (hourly averaged) NO₂ predictions were within a factor of two of the measured value. High pollution events were well captured, as indicated by strong agreement between measured and modelled high percentile values. The model requires only simple input data, does not require an emission inventory and utilises very low computational resources. It represents an accurate and efficient means of producing real-time air quality forecasts and, when used in combination with forecaster experience, is a useful tool for identifying periods of poor air quality 24 h in advance. The hybrid approach outlined in this paper can easily be applied to produce high-quality forecasts of both NO₂ and additional pollutants at new locations/countries where historical monitoring data are available.     

Modeling Phosphate Influence on Arsenate Reduction Kinetics by a Freshwater Cyanobacterium

Arsenic speciation in natural surface-water systems can be highly impacted through biological processes that result in non-thermodynamically predicted species to dominate the system. In laboratory experiments, arsenate reduction by a freshwater cyanobacterium exhibited saturation kinetics increasingly inhibited by elevating solution phosphate concentrations. Approximately 100% arsenate reduction occurred by days 4, 7, and 10 in the low (0.35 μm), middle (3.5 μm), and high (35 μm) phosphate treatments, respectively, with maximum arsenate reduction rates ranged from 0.013 μmol As g C⁻¹ day⁻¹ in the high-phosphate treatment to 0.398 μmol As g C⁻¹ day⁻¹ in the low-phosphate treatment. Saturation kinetic models were utilized to evaluate the impact of cell growth and arsenate-phosphate uptake competition on arsenate reduction rates by the cyanobacterium. Results showed reduced arsenicals dominate arsenic speciation once growth reached steady state, indicating reduced arsenicals may dominate natural systems, even when considering conservatively high, abiotic arsenic reoxidation.     

Feasibility of detection and quantification of gas-phase carbonyls in indoor environments using PFBHA derivatization and solid-phase microextraction (SPME)

Solid-phase microextraction (SPME) was evaluated for the detection and quantification of the gas-phase carbonyls: citronellal, glyoxal, methylglyoxal, and beta-ionone. Prepared air samples containing the carbonyl compounds were collected at a flow rate of 2.8 L min(-1) in an impinger containing a 25% reagent water/75% methanol collection liquid. The aqueous samples were then derivatized with O-(2,3,4,5,6-pentafluorobenzyl)hydroxylamine hydrochloride (PFBHA), extracted with a PDMS/DVB coated SPME fiber, and analyzed by GC-MS. Detection limits with a sample air volume of 76 L were calculated to be 0.03 ppbv, 0.34 ppbv, 0.12 ppbv, and 0.28 ppbv for citronellal, glyoxal, methylglyoxal, and beta-ionone, respectively.     

Societal implications of nanotechnology: occupational perspectives

Nanotechnology-infused products have begun to enter the market in spite of the fact that many sectors of society are still debating whether or not exposure to such products will result in detrimental side effects. Due to a lack of regulation of nanoproducts, it is difficult to track these products to assess how they interact with humans and the environment. Acknowledging this limitation, several studies are starting to investigate situations where individuals are exposed to nanoparticles in the workplace; it is to be noted that manufacturing of materials is the first stage in the product life cycle where exposure may occur. This paper reviews and discusses the potential societal implications associated with the manufacturing of nanoparticles: health concerns, workers’ perceptions, rights, ethics, and the role of policy and regulation. Scenarios are presented, possible implications are discussed, and recommendations are given for appropriate action. Finding the right solution to the identified implications represents a critical challenge. In summary, it is imperative that all stakeholders including industry, academia, government entities, and the public adopt a proactive attitude to ensure that nanotechnology matures in a sustainable manner.     

Measurement of organic compound emission using small test chambers

Organic compounds emitted from a variety of indoor materials have been measured using small (166 L) environmental test chambers. The paper discusses: a) factors to be considered in small chamber testing; b) parameters to be controlled; c) the types of results obtained. The following types of materials have been tested: adhesives, caulks, pressed wood products, floor waxes, paints, and solid insecticides. Selected data are presented. For each material, chamber concentrations of organic compounds have been determined for a range of environmental conditions (e.g., air exchange rate, temperature and relative humidity). Emission rates for individual organic compounds, as well as total measured organics, were calculated. The effects of environmental variables on emission rates have been evaluated. Models are used to evaluate the effect of chamber walls and concentration on emission rates.