Making a life in the physical sciences

As a practicing physical chemist, I argue that the challenges faced by the physical sciences have more parallels with organization science than it might first appear. While the physical sciences do represent a strong paradigm endeavor, many of the same issues that were raised in the article “Making a life in the field of organizational science” arise in physical sciences. An essential difference between the physical sciences and organization science is the essentially capital intensive nature of our research. Ironically, the constant pursuit of the requisite research dollars leads to substantial similarity between the fields. The state of academic physical sciences is analyzed in this context informed by the current state of research funding in the United States. Copyright © 2008 John Wiley & Sons, Ltd.     

Relating Background NO2 Concentrations in Air to Air Mass History Using Non-Parametric Regression Methods: Application at Two Background Sites in Ireland

The concentration of nitrogen dioxide (NO₂) in background air varies temporally and spatially and is influenced by meteorological and anthropogenic factors. Background concentrations used in local air quality modelling studies have a significant effect on the accuracy of the overall result and when based on short-term monitoring data, variation in concentrations with air mass history is often unaccounted for. The current paper presents a powerful tool for the quantification and separation of local and regional air mass effects on background air quality. The origin of and the regions traversed by an air mass prior to reaching a receptor has been modelled using HYsplit-4. Trajectories (between 12 and 96?h duration) were defined based on the frequency with which they passed into 16 predefined compass quadrants and each represented as a vector. Using this vector as the predictor variable and the background concentration as the response variable, non-parametric regression using a Gaussian kernel function was carried out. A graphical output indicated the trajectory direction of maximum NO₂ concentration, while allowing distinction to be made between spurious and true peaks. In all cases, air mass history was found to have a statistically significant effect on NO₂ concentrations. Incorporating emissions data into the analysis local and regional effects were separated and quantified. It was found that emissions in the UK and Europe have a significant effect on background NO₂ concentrations in Ireland and in some instances supersede domestic emissions. The methods can be used to identify source regions, separate local and regional effects and improve predictions of background concentrations based on limited monitoring data. In particular, the results highlight the importance of considering air mass history when assessing background concentration levels for use in local air quality modelling studies.     

Characterisation of Particulate Matter Sampled during a Study of Children's Personal Exposure to Airborne Particulate Matter in a UK Urban Environment

The personal exposure of children aged 9 – 11 years to particulate matter (PM₁₀ and PM_2.5) was carried out between January and September 1997 in the London Borough of Barnet. Personal sampling along with home, garden and classroom microenvironmental monitoring was completed for all ten children. Each child was monitored for five days during winter, spring and summer. All children completed daily time activity diaries to provide information on any potential activities that could influence their exposure to particulate matter. Each evening a household activity questionnaire was also completed by the parents. Personal Environmental Monitors were used to sample personal exposure to PM₁₀ and PM_2.5. Harvard Impactors were used for the microenvironmental sampling of both size fractions. The children's mean personal exposure concentrations for PM₁₀ during winter, spring and summer were 72, 54 and 35 µg/m³ respectively and for PM_2.5 22, 17 and 18 µg/m³ respectively. In order to determine the potential sources of particulate matter, analysis of the Teflon filters has been undertaken. The physical characteristics of the particles have been identified using Scanning Electron Microscopy. The relationships between personal exposure concentrations and the different microenvironments will be discussed.     

Automated riverine landscape characterization: GIS-based tools for watershed-scale research, assessment, and management

River systems consist of hydrogeomorphic patches (HPs) that emerge at multiple spatiotemporal scales. Functional process zones (FPZs) are HPs that exist at the river valley scale and are important strata for framing whole-watershed research questions and management plans. Hierarchical classification procedures aid in HP identification by grouping sections of river based on their hydrogeomorphic character; however, collecting data required for such procedures with field-based methods is often impractical. We developed a set of GIS-based tools that facilitate rapid, low cost riverine landscape characterization and FPZ classification. Our tools, termed RESonate, consist of a custom toolbox designed for ESRI ArcGIS®. RESonate automatically extracts 13 hydrogeomorphic variables from readily available geospatial datasets and datasets derived from modeling procedures. An advanced 2D flood model, FLDPLN, designed for MATLAB® is used to determine valley morphology by systematically flooding river networks. When used in conjunction with other modeling procedures, RESonate and FLDPLN can assess the character of large river networks quickly and at very low costs. Here we describe tool and model functions in addition to their benefits, limitations, and applications.