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

Background: The timely publication of findings in peer-reviewed journals is a primary goal of clinical research. In clinical trials, the processes leading to publication can be complex from choice and prioritization of analytic topics through to journal submission and revisions. As little literature exists on the publication process for multicenter trials, we describe the development, implementation, and effectiveness of such a process in a multicenter trial. Methods: The Hepatitis C Antiviral Long-Term Treatment against Cirrhosis (HALT-C) trial included a data coordinating center (DCC) and clinical centers that recruited and followed more than 1,000 patients. Publication guidelines were approved by the steering committee, and the publications committee monitored the publication process from selection of topics to publication. Results: A total of 73 manuscripts were published in 23 peer-reviewed journals. When manuscripts were closely tracked, the median time for analyses and drafting of manuscripts was 8 months. The median time for data analyses was 5 months and the median time for manuscript drafting was 3 months. The median time for publications committee review, submission, and journal acceptance was 7 months, and the median time from analytic start to journal acceptance was 18 months. Conclusions: Effective publication guidelines must be comprehensive, implemented early in a trial, and require active management by study investigators. Successful collaboration, such as in the HALT-C trial, can serve as a model for others involved in multidisciplinary and multicenter research programs. Trial registration: The HALT-C Trial was registered with clinicaltrials.gov (NCT00006164).

/pdf/processes-to-manage-analyses-and-publications-in-a-phase-iii-xz3q2il5kf.pdf

Processes to manage analyses and publications in a phase III multicenter randomized clinical trial

Environmental factors in future transport

This research devised and demonstrated a method to identify the uncertainties evident in transport infrastructure planning, focussing on the early decision making stages of the project lifecycle. The core of the method used a “Cross Impact” model, anchored in complexity theory to analyse expert opinions on the future for the project. Stakeholder interviews, based around an ideal scenario, were undertaken to elicit opinions about the proposed development, focusing on the decision making steps and environment en-route to the outcome. The interviews were then coded using qualitative data analysis techniques and the emerging variables analysed using the cross impact model. The findings from this case study were that executive leadership and collaboration between Local Authorities were the most influential determinants for progress, and that the prime causes of uncertainty were the extant economic and planning policies. Since the completion of this study, structural transport governance developments have occurred in the UK that have endorsed these findings. This paper focusses on coding of the stakeholder interviews and rationalising the variables which were either present in the scenario or introduced by the stakeholders.

https://eprints.ncl.ac.uk/file_store/production/264173/C8790E03-24BD-4826-9575-DAC5AA22D47D.pdf

Using Scenario-Based Elicitation in Analysis of Uncertainty in a Transport Infrastructure Project

Coming up for Air

Several attempts have been made worldwide to understand the gravity of the air pollution problem. Researchers and policy-makers have been trying to understand it through scientific, regulatory and non-regulatory options. This study reports on the applicability and performance of some well known air quality dispersion models like AERMOD and ISCST3 models for Indian conditions. The evaluation of these models has been carried out in Delhi, India using the historical air quality, meteorological and traffic data for the year 2007. The models have been evaluated using standard performance indicators like fractional bias, mean bias, normalized root mean square error, index of agreement and geometric mean bias.

Margaret Bell

Papers

Processes to manage analyses and publications in a phase III multicenter randomized clinical trial

Environmental factors in future transport

Using Scenario-Based Elicitation in Analysis of Uncertainty in a Transport Infrastructure Project

Coming up for Air

Performance evaluation of air quality dispersion models in Delhi, India