Air pollution levels measured at traffic hot spots : Brisbane urban corridor study

Air pollution levels were monitored continuously over a period of 4 weeks at four sampling sites along a busy urban corridor in Brisbane. The selected sites were representative of industrial and residential types of urban environment affected by vehicular traffic emissions. The concentration levels of submicrometer particle number, PM2.5, PM10, CO, and NOx were measured 5-10 meters from the road. Meteorological parameters and traffic flow rates were also monitored. The data were analysed in terms of the relationship between monitored pollutants and existing ambient air quality standards. The results indicate that the concentration levels of all pollutants exceeded the ambient air background levels, in certain cases by up to an order of magnitude. While the 24-hr average concentration levels did not exceed the standard, estimates for the annual averages were close to, or even higher than the annual standard levels.

New criteria for evaluating methods of identifying hot spots

Identification of hot spots, also known as the sites with promise, black spots, accident-prone locations, or priority investigation locations, is an important and routine activity for improving the overall safety of roadway networks. Extensive literature focuses on methods for hot spot identification (HSID). A subset of this considerable literature is dedicated to conducting performance assessments of various HSID methods. A central issue in comparing HSID methods is the development and selection of quantitative and qualitative performance measures or criteria. The authors contend that currently employed HSID assessment criteria—namely false positives and false negatives—are necessary but not sufficient, and additional criteria are needed to exploit the ordinal nature of site ranking data. With the intent to equip road safety professionals and researchers with more useful tools to compare the performances of various HSID methods and to improve the level of HSID assessments, this paper proposes four quantitative HSID evaluation tests that are, to the authors’ knowledge, new and unique. These tests evaluate different aspects of HSID method performance, including reliability of results, ranking consistency, and false identification consistency and reliability. It is intended that road safety professionals apply these different evaluation tests in addition to existing tests to compare the performances of various HSID methods, and then select the most appropriate HSID method to screen road networks to identify sites that require further analysis. This work demonstrates four new criteria using 3 years of Arizona road section accident data and four commonly applied HSID methods [accident frequency ranking, accident rate ranking, accident reduction potential, and empirical Bayes (EB)]. The EB HSID method reveals itself as the superior method in most of the evaluation tests. In contrast, identifying hot spots using accident rate rankings performs the least well among the tests. The accident frequency and accident reduction potential methods perform similarly, with slight differences explained. The authors believe that the four new evaluation tests offer insight into HSID performance heretofore unavailable to analysts and researchers.

Identifying large truck hot spots using crash counts and PDOEs

Large trucks are involved in a disproportionately small fraction of the total crashes but a disproportionately large fraction of fatal crashes. Large truck crashes often result in significant congestion due to their large physical dimensions and from difficulties in clearing crash scenes. Consequently, preventing large truck crashes is critical to improving highway safety and operations. This study identifies high risk sites (hot spots) for large truck crashes in Arizona and examines potential risk factors related to the design and operation of the high risk sites. High risk sites were identified using both state of the practice methods (accident reduction potential using negative binomial regression with long crash histories) and a newly proposed method using Property Damage Only Equivalents (PDOE). The hot spots identified via the count model generally exhibited low fatalities and major injuries but large minor injuries and PDOs, while the opposite trend was observed using the PDOE methodology. The hot spots based on the count model exhibited large AADTs, whereas those based on the PDOE showed relatively small AADTs but large fractions of trucks and high posted speed limits. Documented site investigations of hot spots revealed numerous potential risk factors, including weaving activities near freeway junctions and ramps, absence of acceleration lanes near on-ramps, small shoulders to accommodate large trucks, narrow lane widths, inadequate signage, and poor lighting conditions within a tunnel.

Empirical evaluation of alternative approaches in identifying crash hot spots

This study proposes a framework of a model-based hot spot identification method by applying full Bayes (FB) technique. In comparison with the state-of-the-art approach [i.e., empirical Bayes method (EB)], the advantage of the FB method is the capability to seamlessly integrate prior information and all available data into posterior distributions on which various ranking criteria could be based. With intersection crash data collected in Singapore, an empirical analysis was conducted to evaluate the following six approaches for hot spot identification: (a) naive ranking using raw crash data, (b) standard EB ranking, (c) FB ranking using a Poisson-gamma model, (d) FB ranking using a Poisson-lognormal model, (e) FB ranking using a hierarchical Poisson model, and (f) FB ranking using a hierarchical Poisson (AR-1) model. The results show that (a) when using the expected crash rate-related decision parameters, all model-based approaches perform significantly better in safety ranking than does the naive ranking method, and (b) the FB approach using hierarchical models significantly outperforms the standard EB approach in correctly identifying hazardous sites.

Reconstructing the history of maize streak virus strain a dispersal to reveal diversification hot spots and its origin in southern Africa

Maize streak virus strain A (MSV-A), the causal agent of maize streak disease, is today one of the most serious biotic threats to African food security. Determining where MSV-A originated and how it spread transcontinentally could yield valuable insights into its historical emergence as a crop pathogen. Similarly, determining where the major extant MSV-A lineages arose could identify geographical hot spots of MSV evolution. Here, we use model-based phylogeographic analyses of 353 fully sequenced MSV-A isolates to reconstruct a plausible history of MSV-A movements over the past 150 years. We show that since the probable emergence of MSV-A in southern Africa around 1863, the virus spread transcontinentally at an average rate of 32.5 km/year (95% highest probability density interval, 15.6 to 51.6 km/year). Using distinctive patterns of nucleotide variation caused by 20 unique intra-MSV-A recombination events, we tentatively classified the MSV-A isolates into 24 easily discernible lineages. Despite many of these lineages displaying distinct geographical distributions, it is apparent that almost all have emerged within the past 4 decades from either southern or east-central Africa. Collectively, our results suggest that regular analysis of MSV-A genomes within these diversification hot spots could be used to monitor the emergence of future MSV-A lineages that could affect maize cultivation in Africa. © 2011, American Society for Microbiology.

Sustainability of public health interventions to reduce the risk of dioxin exposure at severe dioxin hot spots in Vietnam

Severe dioxin contamination at Bien Hoa and Da Nang airbases, Vietnam is of international concern. Public Health risk reduction programs were implemented in Bien Hoa in 2007-2009 and in Da Nang in 2009-2011. In 2009 and 2011 we reported the encouraging results of these interventions in improving the knowledge, attitude and practices (KAP) of local residents in reducing the dioxin exposure risk through foods. In 2013 we revisited these dioxin hot spots, aimed to evaluate whether the results of the intervention were maintained and to identify factors affecting the sustainability of the programs. To assess this, 16 in-depth interviews, six focus group discussions, and pre and post intervention KAP surveys were undertaken. 800 respondents from six intervention wards and 200 respondents from Buu Long Ward (the control site) were randomly selected to participate in the surveys. The results showed that as of 2013, the programs were rated as "moderately sustained" with a score of 3.3 out of 5.0 (cut off points 2.5 to <3.5) for Bien Hoa, and "well sustained" with a score of 3.8 out of 5.0 (cut off points 3.5 to <4.5) for Da Nang. Most formal intervention program activities had ceased and dioxin risk communication activities were no longer integrated into local routine health education programs. However, the main outcomes were maintained and were better than that in the control ward. Migration, lack of official guidance from City People's Committees and local authorities as well as the politically sensitive nature of dioxin issues were the main challenges for the sustainability of the programs.

Environmental health risk assessment of dioxin in foods and the sustainability of public health interventions at severe dioxin hot spots in Vietnam

This study assessed environmental health risk from dioxin in foods and sustainability of risk reduction programs at two heavily contaminated former military sites in Vietnam. The study involved 1000 household surveys, analysis of food samples and in-depth discussions with residents and officials. The findings indicate that more than 40 years after the war, local residents still experience high exposure to dioxin if they consume local high risk foods. Public health intervention programs were rated moderately to well sustained. Internal migration, and lack of clear, official guidance and sensitivity regarding dioxin issues were the main challenges for sustainability of prevention programs.

Environmental health risk assessment of dioxin in foods at the two most severe dioxin hot spots in Vietnam

Background Bien Hoa and Da Nang airbases were bulk storages for Agent Orange during the Vietnam War and currently are the two most severe dioxin hot spots. Objectives This study assesses the health risk of exposure to dioxin through foods for local residents living in seven wards surrounding these airbases. Methods This study follows the Australian Environmental Health Risk Assessment Framework to assess the health risk of exposure to dioxin in foods. Forty-six pooled samples of commonly consumed local foods were collected and analyzed for dioxin/furans. A food frequency and Knowledge–Attitude–Practice survey was also undertaken at 1000 local households, various stakeholders were involved and related publications were reviewed. Results Total dioxin/furan concentrations in samples of local “high-risk” foods (e.g. free range chicken meat and eggs, ducks, freshwater fish, snail and beef) ranged from 3.8 pg TEQ/g to 95 pg TEQ/g, while in “low-risk” foods (e.g. caged chicken meat and eggs, seafoods, pork, leafy vegetables, fruits, and rice) concentrations ranged from 0.03 pg TEQ/g to 6.1 pg TEQ/g. Estimated daily intake of dioxin if people who did not consume local high risk foods ranged from 3.2 pg TEQ/kg bw/day to 6.2 pg TEQ/kg bw/day (Bien Hoa) and from 1.2 pg TEQ/kg bw/day to 4.3 pg TEQ/kg bw/day (Da Nang). Consumption of local high risk foods resulted in extremely high dioxin daily intakes (60.4–102.8 pg TEQ/kg bw/day in Bien Hoa; 27.0–148.0 pg TEQ/kg bw/day in Da Nang). Conclusions Consumption of local “high-risk” foods increases dioxin daily intakes far above the WHO recommended TDI (1–4 pg TEQ/kg bw/day). Practicing appropriate preventive measures is necessary to significantly reduce exposure and health risk.

Los Hot Spots: ¿Una alternativa para reducir los niveles de delincuencia en Bogotá?

El interés de esta monografía es analizar la incidencia de la estrategia de seguridad ciudadana de los Hot Spots en los niveles de delincuencia de Bogotá durante el periodo de la Alcaldía de Samuel Moreno 2009-2011, tomando como casos de estudio la Avenida 19 y la Zona Rosa (Chicó El Lago). Esta investigación se realiza desde los conceptos teórico-prácticos que ha arrojado el modelo de Hot Spot tras su aplicación en 18 ciudades del mundo, y que sirven como herramienta para analizar las transformaciones del delito en las zonas de estudio. De esta manera se avanza hacia el resultado que permite identificar los factores que impidieron que el modelo de Hot Spots se formulara y ejecutara efectivamente y por lo tanto no disminuyera los niveles de delincuencia en Bogotá.

Extinction processes in hot spots of avian biodiversity and the targeting of pre-emptive conservation action

Hot spots of endemism are regarded as important global sites for conservation as they are rich in threatened endemic species and currently experiencing extensive habitat loss. Targeting pre-emptive conservation action to sites that are currently relatively intact but which would be vulnerable to particular human activities if they occurred in the future is, however, also valuable but has received less attention. Here, we address this issue by using data on Endemic Bird Areas (EBAs). First, we identify the ecological factors that affect extinction risk in the face of particular human activities, and then use these insights to identify EBAs that should be priorities for pre-emptive conservation action. Threatened endemic species in EBAs are significantly more likely to be habitat specialists or relatively large-bodied than non-threatened species, when compared across avian families. Increasing habitat loss causes a significant increase in extinction risk among habitat specialists, but we found no evidence to suggest that the presence of alien species/human exploitation causes a significant increase in extinction risk among large-bodied species. This suggests that these particular human activities are contributing to high extinction risk among habitat specialists, but not among large-bodied species. Based on these analyses, we identify 39 EBAs containing 570 species (24% of the total in EBAs) that are not currently threatened with severe habitat loss, but would be ecologically vulnerable to future habitat loss should it occur. We show that these sites tend to be poorly represented in existing priority setting exercises involving hot spots, suggesting that vulnerability must be explicitly included within these exercises if such sites are to be adequately protected.

Cortical hot spots and labyrinths: why cortical neuromodulation for episodic migraine with aura should be personalized

Stimulation protocols for medical devices should be rationally designed. For episodic migraine with aura we outline model-based design strategies toward preventive and acute therapies using stereotactic cortical neuromodulation. To this end, we regard a localized spreading depression (SD) wave segment as a central element in migraine pathophysiology. To describe nucleation and propagation features of the SD wave segment, we define the new concepts of cortical hot spots and labyrinths, respectively. In particular, we firstly focus exclusively on curvature-induced dynamical properties by studying a generic reaction-diffusion model of SD on the folded cortical surface. This surface is described with increasing level of details, including finally personalized simulations using patient's magnetic resonance imaging (MRI) scanner readings. At this stage, the only relevant factor that can modulate nucleation and propagation paths is the Gaussian curvature, which has the advantage of being rather readily accessible by MRI. We conclude with discussing further anatomical factors, such as areal, laminar, and cellular heterogeneity, that in addition to and in relation to Gaussian curvature determine the generalized concept of cortical hot spots and labyrinths as target structures for neuromodulation. Our numerical simulations suggest that these target structures are like fingerprints, they are individual features of each migraine sufferer. The goal in the future will be to provide individualized neural tissue simulations. These simulations should predict the clinical data and therefore can also serve as a test bed for exploring stereotactic cortical neuromodulation.

Norepinephrine ignites local hot spots of neuronal excitation: how arousal amplifies selectivity in perception and memory

Arousal sometimes enhances and sometimes impairs perception and memory. In our Glutamate Amplifies Noradrenergic Effects (GANE) model, glutamate at active synapses interacts with norepinephrine released by the locus coeruleus to create local ‘hot spots’ of activity that enable the selective effects of arousal. This hot spot mechanism allows local cortical regions to self-regulate norepinephrine release based on current activation levels. In turn, hot spots bias global energetic delivery and functional network connectivity to enhance processing of high priority representations and impair processing of lower priority representations.

Hot spots, hot moments, and spatio-temporal controls on soil CO2 efflux in a water-limited ecosystem

Soil CO2 efflux is the primary source of CO2 emissions from terrestrial ecosystems to the atmosphere. The rates of this flux vary in time and space producing hot moments (sudden temporal high fluxes) and hot spots (spatially defined high fluxes), but these high reaction rates are rarely studied in conjunction with each other. We studied temporal and spatial variation of soil CO2 efflux in a water-limited Mediterranean ecosystem in Baja California, Mexico. Soil CO2 efflux increased 522% during a hot moment after rewetting of soils following dry summer months. Monthly precipitation was the primary driver of the seasonal trend of soil CO2 efflux (including the hot moment) and through changes in soil volumetric water content (VWC) it influenced the relationship between CO2 efflux and soil temperature. Geostatistical analyses showed that the spatial dependence of soil CO2 efflux changed between two contrasting seasons (dry and wet). During the dry season high soil VWC was associated with high soil CO2 efflux, and during the wet season the emergence of a hot spot of soil CO2 efflux was associated with higher root biomass and leaf area index. These results suggest that sampling designs should accommodate for changes in spatial dependence of measured variables. The spatio-temporal relationships identified in this study are arguably different from temperate ecosystems where the majority of soil CO2 efflux research has been done. This study provides evidence of the complexity of the mechanisms controlling the spatio-temporal variability of soil CO2 efflux in water-limited ecosystems. (C) 2014 Elsevier Ltd. All rights reserved.