The science of the total environment

openair is an R package primarily developed for the analysis of air pollution measurement data but which is also of more general use in the atmospheric sciences. The package consists of many tools for importing and manipulating data, and undertaking a wide range of analyses to enhance understanding of air pollution data. In this paper we consider the development of the package with the purpose of showing how air pollution data can be analysed in more insightful ways. Examples are provided of importing data from UK air pollution networks, source identification and characterisation using bivariate polar plots, quantitative trend estimates and the use of functions for model evaluation purposes. We demonstrate how air pollution data can be analysed quickly and efficiently and in an interactive way, freeing time to consider the problem at hand. One of the central themes of openair is the use of conditioning plots and analyses, which greatly enhance inference possibilities. Finally, some consideration is given to future developments.

openair - An R package for air quality data analysis

Evaluation of waist circumference, waist-to-hip ratio, and the conicity index as screening tools for high trunk fat mass, as measured by dual-energy X-ray absorptiometry, in children aged 3–19 y

The development of models to assess air pollution exposures within cities for assignment to subjects in health studies has been identified as a priority area for future research. This paper reviews models for assessing intraurban exposure under six classes, including: (i) proximity-based assessments, (ii) statistical interpolation, (iii) land use regression models, (iv) line dispersion models, (v) integrated emission-meteorological models, and (vi) hybrid models combining personal or household exposure monitoring with one of the preceding methods. We enrich this review of the modelling procedures and results with applied examples from Hamilton, Canada. In addition, we qualitatively evaluate the models based on key criteria important to health effects assessment research. Hybrid models appear well suited to overcoming the problem of achieving population representative samples while understanding the role of exposure variation at the individual level. Remote sensing and activity-space analysis will complement refinements in pre-existing methods, and with expected advances, the field of exposure assessment may help to reduce scientific uncertainties that now impede policy intervention aimed at protecting public health.

A review and evaluation of intraurban air pollution exposure models

Metal-organic frameworks (MOFs) are typically highlighted for their potential application in gas storage, separations and catalysis. In contrast, the unique prospects these porous and crystalline materials offer for application in electronic devices, although actively developed, are often underexposed. This review highlights the research aimed at the implementation of MOFs as an integral part of solid-state microelectronics. Manufacturing these devices will critically depend on the compatibility of MOFs with existing fabrication protocols and predominant standards. Therefore, it is important to focus in parallel on a fundamental understanding of the distinguishing properties of MOFs and eliminating fabrication-related obstacles for integration. The latter implies a shift from the microcrystalline powder synthesis in chemistry labs, towards film deposition and processing in a cleanroom environment. Both the fundamental and applied aspects of this two-pronged approach are discussed. Critical directions for future research are proposed in an updated high-level roadmap to stimulate the next steps towards MOF-based microelectronics within the community.

/pdf/an-updated-roadmap-for-the-integration-of-metal-organic-4ryw3jm11n.pdf

An updated roadmap for the integration of metal–organic frameworks with electronic devices and chemical sensors

Several algorithms exist to implement a change between fixed-time signal plans. These are reviewed and the constraints influencing the process of change are examined. A comparison of actual networks reveals the daily and cyclical variations in flow which prevail in practice and within which the plan-changing process must be seen. Studies using TRANSYT are reported and finally 5 plan-change algorithms are assessed against an "ideal" plan-change, using Monte Carlo simulation techniques. The results suggest that significantly less delay (at the 5% level) and fewer stops are incurred when plan-changes are implemented at off-peak rather than at peak flows. The MODIFIED ABRUPT algorithm (commonly called CRASH), which is in common use, is found to generate no statistically significant (at the 5% level) additional stops or vehicular delay on main roads, irrespective of the level of flow at which the plan-change is made and whether the change is from off-peak to peak or vice versa. The variation in delay caused by implementing a plan-change with the MODIFIED ABRUPT method is found to be less than 2%. It is concluded that plan-changes should always be implemented during off-peak flow conditions and that the commonly used MODIFIED ABRUPT algorithm is the most satisfactory method under prevailing constraints. (Author)

Plan Change Algorithms for Traffic Control Systems

The UTMC philosophy is seeking to end the unsatisfactory position of incompatible systems and manufacturers' proprietary solutions by defining generic specifications and operational procedures for applications implemented throughout the UK. This study aimed to examine methods of integrating network monitoring, modelling and management. The research presented includes laboratory simulation and street trials implemented at the Leicester demonstration site. These laboratory simulation and street trials were designed to demonstrate that a system of traffic network models could be used off-line to develop traffic management measures to assist operators in responding to congestion caused by planned events. The methodology brings together several disparate software packages and UTC systems to monitor, model and manage traffic during the planned events. The Leicester study was based on 'special events', namely Saturday afternoon football matches at the Leicester City Football Club (LCFC) and Leicester Tigers Rugby Football Club.

Network monitoring, modelling and management to aid mitigate the impact of 'event' traffic

Novel wireless pervasive sensors network to improve the understanding of noise across urban areas”, proceeding

As vehicle technologies become ever more efficient and sophisticated, it is increasingly the case that the most inefficient and variable component in the modern passenger car is the driver With the support of a case study, this paper investigates variability in driver behavior, and seeks to both classify and quantify the effects Statistical cluster analysis techniques are utilized to group different types of driver behavior The paper then goes on to investigate the relationships between these clusters of behavior types, and metrics of environmental efficiency Finally, a range of intelligent transportation system (ITS) technologies are discussed which have the potential to influence driver behavior towards an environmental and resource optimum

Influencing Driver Behaviour for Environmental Benefit: The Role of ITS Technologies

Intelligent transportation systems (ITS) are fundamental to safe, efficient, control and management of people, vehicles and transport systems and plays an important role in addressing environmental impacts. Recent advances in intelligent pervasive technologies provide a wealth of static and dynamic data which complement legacy ITS systems. There is significant value-added in the integration of existing and emerging technologies especially if achieved across jurisdictional boundaries. However, there are considerable challenges to realize the rewards of integration particularly in real-time. This paper offers an e-science solution providing insight into the delivery of a real-time data management platform for both monitored and modeled sources.

/pdf/decision-support-for-intelligent-traffic-and-environment-2yylrrasm2.pdf

Margaret Bell

Papers

Plan Change Algorithms for Traffic Control Systems

Network monitoring, modelling and management to aid mitigate the impact of 'event' traffic

Novel wireless pervasive sensors network to improve the understanding of noise across urban areas”, proceeding

Influencing Driver Behaviour for Environmental Benefit: The Role of ITS Technologies

Decision Support for Intelligent Traffic and Environment Management