Hot topic detection in news blogs from the perspective of W2T

News blog hot topics are important for the information recommendation service and marketing. However, information overload and personalized management make the information arrangement more difficult. Moreover, what influences the formation and development of blog hot topics is seldom paid attention to. In order to correctly detect news blog hot topics, the paper first analyzes the development of topics in a new perspective based on W2T (Wisdom Web of Things) methodology. Namely, the characteristics of blog users, context of topic propagation and information granularity are unified to analyze the related problems. Some factors such as the user behavior pattern, network opinion and opinion leader are subsequently identified to be important for the development of topics. Then the topic model based on the view of event reports is constructed. At last, hot topics are identified by the duration, topic novelty, degree of topic growth and degree of user attention. The experimental results show that the proposed method is feasible and effective.

Tackling the health burden from household air pollution (HAP) : development and implementation of new WHO Guidelines

Household air pollution (HAP), arising mainly from the combustion of solid and other polluting fuels, is responsible for a very substantial public health burden, most recently estimated as causing 3.5 million premature deaths in 2010. These patterns of household fuel use have also important negative impacts on safety, prospects for poverty reduction and the environment, including climate change. Building on previous air quality guidelines, the WHO is developing new guidelines focused on household fuel combustion, covering cooking, heating and lighting, and although global, the key focus is low and middle income countries reflecting the distribution of disease burden. As discussed in this paper, currently in development, the guidelines will include reviews of a wide range of evidence including fuel use in homes, emissions from stoves and lighting, household air pollution and exposure levels experienced by populations, health risks, impacts of interventions on HAP and exposure, and also key factors influencing sustainable and equitable adoption of improved stoves and cleaner fuels. GRADE, the standard method used for guidelines evidence review may not be well suited to the variety and nature of evidence required for this project, and a modified approach is being developed and tested. Work on the guidelines is being carried out in close collaboration with the UN Foundation Global Alliance on Clean cookstoves, allowing alignment with specific tools including recently developed international voluntary standards for stoves, and the development of country action plans. Following publication, WHO plans to work closely with a number of countries to learn from implementation efforts, in order to further strengthen support and guidance. A case study on the situation and policy actions to date in Bhutan provide an illustration of the challenges and opportunities involved, and the timely importance of the new guidelines and associated research, evaluation and policy development agendas.

Editorial : forecasting urban air quality

Air pollution has significant impacts on both the environment and human health. Therefore, urban areas have received ever growing attention, because they not only have the highest concentrations of air pollutants, but they also have the highest human population. In modern societies, urban air quality (UAQ) is routinely evaluated and local authorities provide regular reports to the public about current UAQ levels. Both local and international authorities also recommended that some air pollutant concentrations remain below a certain level, with the aim of reducing emissions and improving the air quality, both in urban areas and on a more regional scale. In some countries, protocols aimed at reducing emissions have come in force as a result of international agreements.

Exponential integrators and a dual-scale model for wood drying

For the timber industry, the ability to simulate the drying of wood is invaluable for manufacturing high quality wood products. Mathematically, however, modelling the drying of a wet porous material, such as wood, is a diffcult task due to its heterogeneous and anisotropic nature, and the complex geometry of the underlying pore structure. The well{ developed macroscopic modelling approach involves writing down classical conservation equations at a length scale where physical quantities (e.g., porosity) can be interpreted as averaged values over a small volume (typically containing hundreds or thousands of pores). This averaging procedure produces balance equations that resemble those of a continuum with the exception that effective coeffcients appear in their deffnitions. Exponential integrators are numerical schemes for initial value problems involving a system of ordinary differential equations. These methods differ from popular Newton{Krylov implicit methods (i.e., those based on the backward differentiation formulae (BDF)) in that they do not require the solution of a system of nonlinear equations at each time step but rather they require computation of matrix{vector products involving the exponential of the Jacobian matrix. Although originally appearing in the 1960s, exponential integrators have recently experienced a resurgence in interest due to a greater undertaking of research in Krylov subspace methods for matrix function approximation. One of the simplest examples of an exponential integrator is the exponential Euler method (EEM), which requires, at each time step, approximation of φ(A)b, where φ(z) = (ez - 1)/z, A E Rnxn and b E Rn. For drying in porous media, the most comprehensive macroscopic formulation is TransPore [Perre and Turner, Chem. Eng. J., 86: 117-131, 2002], which features three coupled, nonlinear partial differential equations. The focus of the first part of this thesis is the use of the exponential Euler method (EEM) for performing the time integration of the macroscopic set of equations featured in TransPore. In particular, a new variable{ stepsize algorithm for EEM is presented within a Krylov subspace framework, which allows control of the error during the integration process. The performance of the new algorithm highlights the great potential of exponential integrators not only for drying applications but across all disciplines of transport phenomena. For example, when applied to well{ known benchmark problems involving single{phase liquid ow in heterogeneous soils, the proposed algorithm requires half the number of function evaluations than that required for an equivalent (sophisticated) Newton{Krylov BDF implementation. Furthermore for all drying configurations tested, the new algorithm always produces, in less computational time, a solution of higher accuracy than the existing backward Euler module featured in TransPore. Some new results relating to Krylov subspace approximation of '(A)b are also developed in this thesis. Most notably, an alternative derivation of the approximation error estimate of Hochbruck, Lubich and Selhofer [SIAM J. Sci. Comput., 19(5): 1552{1574, 1998] is provided, which reveals why it performs well in the error control procedure. Two of the main drawbacks of the macroscopic approach outlined above include the effective coefficients must be supplied to the model, and it fails for some drying configurations, where typical dual{scale mechanisms occur. In the second part of this thesis, a new dual{scale approach for simulating wood drying is proposed that couples the porous medium (macroscale) with the underlying pore structure (microscale). The proposed model is applied to the convective drying of softwood at low temperatures and is valid in the so{called hygroscopic range, where hygroscopically held liquid water is present in the solid phase and water exits only as vapour in the pores. Coupling between scales is achieved by imposing the macroscopic gradient on the microscopic field using suitably defined periodic boundary conditions, which allows the macroscopic ux to be defined as an average of the microscopic ux over the unit cell. This formulation provides a first step for moving from the macroscopic formulation featured in TransPore to a comprehensive dual{scale formulation capable of addressing any drying configuration. Simulation results reported for a sample of spruce highlight the potential and flexibility of the new dual{scale approach. In particular, for a given unit cell configuration it is not necessary to supply the effective coefficients prior to each simulation.

Effect of driving conditions and suspension parameters on dynamic load-sharing of longitudinal-connected air suspensions

The objective of this research was to investigate the effects of driving conditions and suspension parameters on dynamic load-sharing of longitudinal-connected air suspensions of a tri-axle semi-trailer. A novel nonlinear model of a multi-axle semi-trailer with longitudinal-connected air suspension was formulated based on fluid mechanics and thermodynamics and was validated through test results. The effects of driving conditions and suspension parameters on dynamic load-sharing and road-friendliness of the semi-trailer were analyzed. Simulation results indicate that the road-friendliness metric-DLC (dynamic load coefficient) is not always in accordance with the load-sharing metric-DLSC (dynamic load-sharing coefficient). The effect of employing larger air lines and connectors on the DLSC optimization ratio gives varying results as road roughness increases and as driving speed increases. When the vehicle load reduces, or the static pressure increases, the DLSC optimization ratio declines monotonically. The results also indicate that if the air line diameter is always assumed to be larger than the connector diameter, the influence of air line diameter on load-sharing is more significant than that of the connector.

Evaluating the effectiveness of heat warning systems : a systematic review of epidemiological evidence

Objectives To review the existing research on the effectiveness of heat warning systems (HWSs) in saving lives and reducing harm. Methods A systematic search of major databases was conducted, using “heat, heatwave, high temperature, hot temperature, OR hot climate” AND “warning system”. Results Fifteen articles were retrieved. Six studies asserted that fewer people died of excessive heat after HWS implementation. HWS was associated with reduction in ambulance use. One study estimated the benefits of HWS to be 468millionforsaving117livescomparedto210,000 costs of running the system. Eight studies showed that mere availability of HWS did not lead to behavioral changes. Perceived threat of heat dangers to self/others was the main factor related to heeding warnings and taking proper actions. However, costs and barriers associated with taking protective actions, such as costs of running air conditioners, were of significant concern particularly to the poor. Conclusions Research in this area is limited. Prospective designs applying health behavior theories should establish whether HWS can produce the health benefits they are purported to achieve by identifying the target vulnerable groups.

Extracting news blog hot topics based on the W2T methodology

Although topic detection and tracking techniques have made great progress, most of the researchers seldom pay more attention to the following two aspects. First, the construction of a topic model does not take the characteristics of different topics into consideration. Second, the factors that determine the formation and development of hot topics are not further analyzed. In order to correctly extract news blog hot topics, the paper views the above problems in a new perspective based on the W2T (Wisdom Web of Things) methodology, in which the characteristics of blog users, context of topic propagation and information granularity are investigated in a unified way. The motivations and features of blog users are first analyzed to understand the characteristics of news blog topics. Then the context of topic propagation is decomposed into the blog community, topic network and opinion network, respectively. Some important factors such as the user behavior pattern, opinion leader and network opinion are identified to track the development trends of news blog topics. Moreover, a blog hot topic detection algorithm is proposed, in which news blog hot topics are identified by measuring the duration, topic novelty, attention degree of users and topic growth. Experimental results show that the proposed method is feasible and effective. These results are also useful for further studying the formation mechanism of opinion leaders in blogspace.

Assessing the Impact of Sensor Accuracy and Sensor Choice on Air Traffic Conflict Risk Estimation using Risk-Ratio Concepts

One of the primary desired capabilities of any future air traffic separation management system is the ability to provide early conflict detection and resolution effectively and efficiently. In this paper, we consider the risk of conflict as a primary measurement to be used for early conflict detection. This paper focuses on developing a novel approach to assess the impact of different measurement uncertainty models on the estimated risk of conflict. The measurement uncertainty model can be used to represent different sensor accuracy and sensor choices. Our study demonstrates the value of modelling measurement uncertainty in the conflict risk estimation problem and presents techniques providing a means of assessing sensor requirements to achieve desired conflict detection performance.

Estimating the effects of ambient temperature on mortality : methodological challenges and proposed solutions

The health impacts of exposure to ambient temperature have been drawing increasing attention from the environmental health research community, government, society, industries, and the public. Case-crossover and time series models are most commonly used to examine the effects of ambient temperature on mortality. However, some key methodological issues remain to be addressed. For example, few studies have used spatiotemporal models to assess the effects of spatial temperatures on mortality. Few studies have used a case-crossover design to examine the delayed (distributed lag) and non-linear relationship between temperature and mortality. Also, little evidence is available on the effects of temperature changes on mortality, and on differences in heat-related mortality over time. This thesis aimed to address the following research questions: 1. How to combine case-crossover design and distributed lag non-linear models? 2. Is there any significant difference in effect estimates between time series and spatiotemporal models? 3. How to assess the effects of temperature changes between neighbouring days on mortality? 4. Is there any change in temperature effects on mortality over time? To combine the case-crossover design and distributed lag non-linear model, datasets including deaths, and weather conditions (minimum temperature, mean temperature, maximum temperature, and relative humidity), and air pollution were acquired from Tianjin China, for the years 2005 to 2007. I demonstrated how to combine the case-crossover design with a distributed lag non-linear model. This allows the case-crossover design to estimate the non-linear and delayed effects of temperature whilst controlling for seasonality. There was consistent U-shaped relationship between temperature and mortality. Cold effects were delayed by 3 days, and persisted for 10 days. Hot effects were acute and lasted for three days, and were followed by mortality displacement for non-accidental, cardiopulmonary, and cardiovascular deaths. Mean temperature was a better predictor of mortality (based on model fit) than maximum or minimum temperature. It is still unclear whether spatiotemporal models using spatial temperature exposure produce better estimates of mortality risk compared with time series models that use a single site’s temperature or averaged temperature from a network of sites. Daily mortality data were obtained from 163 locations across Brisbane city, Australia from 2000 to 2004. Ordinary kriging was used to interpolate spatial temperatures across the city based on 19 monitoring sites. A spatiotemporal model was used to examine the impact of spatial temperature on mortality. A time series model was used to assess the effects of single site’s temperature, and averaged temperature from 3 monitoring sites on mortality. Squared Pearson scaled residuals were used to check the model fit. The results of this study show that even though spatiotemporal models gave a better model fit than time series models, spatiotemporal and time series models gave similar effect estimates. Time series analyses using temperature recorded from a single monitoring site or average temperature of multiple sites were equally good at estimating the association between temperature and mortality as compared with a spatiotemporal model. A time series Poisson regression model was used to estimate the association between temperature change and mortality in summer in Brisbane, Australia during 1996–2004 and Los Angeles, United States during 1987–2000. Temperature change was calculated by the current day's mean temperature minus the previous day's mean. In Brisbane, a drop of more than 3 �C in temperature between days was associated with relative risks (RRs) of 1.16 (95% confidence interval (CI): 1.02, 1.31) for non-external mortality (NEM), 1.19 (95% CI: 1.00, 1.41) for NEM in females, and 1.44 (95% CI: 1.10, 1.89) for NEM aged 65.74 years. An increase of more than 3 �C was associated with RRs of 1.35 (95% CI: 1.03, 1.77) for cardiovascular mortality and 1.67 (95% CI: 1.15, 2.43) for people aged < 65 years. In Los Angeles, only a drop of more than 3 �C was significantly associated with RRs of 1.13 (95% CI: 1.05, 1.22) for total NEM, 1.25 (95% CI: 1.13, 1.39) for cardiovascular mortality, and 1.25 (95% CI: 1.14, 1.39) for people aged . 75 years. In both cities, there were joint effects of temperature change and mean temperature on NEM. A change in temperature of more than 3 �C, whether positive or negative, has an adverse impact on mortality even after controlling for mean temperature. I examined the variation in the effects of high temperatures on elderly mortality (age . 75 years) by year, city and region for 83 large US cities between 1987 and 2000. High temperature days were defined as two or more consecutive days with temperatures above the 90th percentile for each city during each warm season (May 1 to September 30). The mortality risk for high temperatures was decomposed into: a "main effect" due to high temperatures using a distributed lag non-linear function, and an "added effect" due to consecutive high temperature days. I pooled yearly effects across regions and overall effects at both regional and national levels. The effects of high temperature (both main and added effects) on elderly mortality varied greatly by year, city and region. The years with higher heat-related mortality were often followed by those with relatively lower mortality. Understanding this variability in the effects of high temperatures is important for the development of heat-warning systems. In conclusion, this thesis makes contribution in several aspects. Case-crossover design was combined with distribute lag non-linear model to assess the effects of temperature on mortality in Tianjin. This makes the case-crossover design flexibly estimate the non-linear and delayed effects of temperature. Both extreme cold and high temperatures increased the risk of mortality in Tianjin. Time series model using single site’s temperature or averaged temperature from some sites can be used to examine the effects of temperature on mortality. Temperature change (no matter significant temperature drop or great temperature increase) increases the risk of mortality. The high temperature effect on mortality is highly variable from year to year.

The effects of cold air (-110°C) and water (8°C) cryotherapy on knee skin temperature

Exposure to cold air, whole body cryotherapy (WBC), is a novel treatment employed by athletes. In WBC individuals dressed in minimal clothing are exposed to a temperature below -100°C for 2-4 min. The use of WBC has been advocated as a treatment for various knee injuries. PURPOSE: To compare the effects of two modalities of cryotherapy, -110°C WBC and 8°C cold water immersion (CWI) on knee skin temperature (Tsk). METHODS: With ethical approval and written informed consent 10 healthy active male participants (26.5±4.9 yr, 183.5±6.0 cm, 90.7±19.9 kg, 26.8±5.0 kg/m2, 23.0±9.3% body fat (measured by DXA), 7.6 ± 2.0 mm patellar skin fold; mean±SD) were exposed to 4 min of CWI and WBC. The treatment order was randomised in a controlled crossover design, with a minimum of 7 days between treatments. During WBC participants stood in a chamber (-60±3°C) for 20 s before entering the main chamber (-110°C±3°C) where they remained for 3 min and 40 s. For CWI participants were seated in a tank filled with cold water (8±0.3°C) and immersed to the level of the sternum for 4 min. Right knee Tsk was assessed via non-contact, infrared thermal imaging. A quadrilateral region of interest was created using inert markers placed 5 cm above and below the most superior and inferior aspect of the patella. Tsk within this quadrilateral was recorded pre, immediately post and every 10 min thereafter for 60 min. Tsk changes were examined using a two-way (treatment x time) repeated measures analyses of variance. In addition, a paired sample t-test was used to compare baseline Tsk before both treatments. RESULTS: Knee Tsk was similar before treatment (WBC: 29.9±0.7°C, CWI: 29.6±0.9°C, p>0.05). There was a significant main effect for treatment (p<0.05) and time (p<0.001). Compared to baseline, Tsk was significantly reduced (p<0.05) immediately post and at 10, 20, 30, 40, 50 and 60 min after both cooling modalities. Knee Tsk was lower (p<0.05) immediately after WBC (19.0±0.9°C) compared to CWI (20.5±0.6°C). However, from 10 to 60 min post, knee Tsk was lower (p<0.05) following the CWI treatment. CONCLUSION: WBC elicited a greater decrease in knee Tsk compared to CWI immediately after treatment. However, both modalities display different recovery patterns and Tsk after CWI was significantly lower than WBC at 10, 20, 30, 40, 50 and 60 min after treatment.

Extremely cold and hot temperatures increase the risk of ischaemic heart disease mortality : epidemiological evidence from China

Objective: To examine the effects of extremely cold and hot temperatures on ischaemic heart disease (IHD) mortality in five cities (Beijing, Tianjin, Shanghai, Wuhan and Guangzhou) in China; and to examine the time relationships between cold and hot temperatures and IHD mortality for each city. Design: A negative binomial regression model combined with a distributed lag non-linear model was used to examine city-specific temperature effects on IHD mortality up to 20 lag days. A meta-analysis was used to pool the cold effects and hot effects across the five cities. Patients: 16 559 IHD deaths were monitored by a sentinel surveillance system in five cities during 2004–2008. Results: The relationships between temperature and IHD mortality were non-linear in all five cities. The minimum-mortality temperatures in northern cities were lower than in southern cities. In Beijing, Tianjin and Guangzhou, the effects of extremely cold temperatures were delayed, while Shanghai and Wuhan had immediate cold effects. The effects of extremely hot temperatures appeared immediately in all the cities except Wuhan. Meta-analysis showed that IHD mortality increased 48% at the 1st percentile of temperature (extremely cold temperature) compared with the 10th percentile, while IHD mortality increased 18% at the 99th percentile of temperature (extremely hot temperature) compared with the 90th percentile. Conclusions: Results indicate that both extremely cold and hot temperatures increase IHD mortality in China. Each city has its characteristics of heat effects on IHD mortality. The policy for response to climate change should consider local climate–IHD mortality relationships.

Drying kinetics of two grape varieties of Italy

Two varieties of grapes, white grape and red grape grown in the Campania region of Italy were selected for the study of drying characteristics. Comparisons were made with treated and untreated grapes under constant drying condition of 50o C in a conventional drying system. This temperature was selected to represent farm drying conditions. Grapes were purchased from a local market from the same supplier to maintain the same size of grapes and same properties. An abrasive physical treatment was used as pretreatment. The drying curves were constructed and drying kinetics was calculated using several commonly available models. It was found that treated samples show better drying characteristics than untreated samples. The objective of this study is to obtain drying kinetics which can be used to optimize the drying operations in grape drying.

Drying condition effects on fluidization quality and fluidization velocity at initial and final stages of cubical particulates for pet food

In this research fluidization behavior of cubical Bovine intestine samples was studied. Bovine intestine samples were heat pump dried at atmospheric pressure and at emperatures below and above the material freezing points. Experiments were conducted to study fluidization characteristics and drying kinetics at different drying conditions. Bovine particles were characterized according to Geldart classification and minimum fluidization velocity was calculated using Ergun Equation and generalized equation for all drying conditions at the beginning of the trials and end of the trials. Walli’s model was used to categorize stability of the fluidization at the beginning and end of the drying for each trial. Walli’s values determined were positive at the beginning and end of all trials indicating stable fluidisation at the beginning and end for each drying condition.

Effects of air pollution exposure on adult bicycle commuters : an investigation of respiratory health, motorised traffic proximity and the utility of commute re-routing

Bicycle commuting has the potential to be an effective contributing solution to address some of modern society’s biggest issues, including cardiovascular disease, anthropogenic climate change and urban traffic congestion. However, individuals shifting from a passive to an active commute mode may be increasing their potential for air pollution exposure and the associated health risk. This project, consisting of three studies, was designed to investigate the health effects of bicycle commuters in relation to air pollution exposure, in a major city in Australia (Brisbane). The aims of the three studies were to: 1) examine the relationship of in-commute air pollution exposure perception, symptoms and risk management; 2) assess the efficacy of commute re-routing as a risk management strategy by determining the exposure potential profile of ultrafine particles along commute route alternatives of low and high proximity to motorised traffic; and, 3) evaluate the feasibility of implementing commute re-routing as a risk management strategy by monitoring ultrafine particle exposure and consequential physiological response from using commute route alternatives based on real-world circumstances; 3) investigate the potential of reducing exposure to ultrafine particles (UFP; < 0.1 µm) during bicycle commuting by lowering proximity to motorised traffic with real-time air pollution and acute inflammatory measurements in healthy individuals using their typical, and an alternative to their typical, bicycle commute route. The methods of the three studies included: 1) a questionnaire-based investigation with regular bicycle commuters in Brisbane, Australia. Participants (n = 153; age = 41 ± 11 yr; 28% female) reported the characteristics of their typical bicycle commute, along with exposure perception and acute respiratory symptoms, and amenability for using a respirator or re-routing their commute as risk management strategies; 2) inhaled particle counts measured along popular pre-identified bicycle commute route alterations of low (LOW) and high (HIGH) motorised traffic to the same inner-city destination at peak commute traffic times. During commute, real-time particle number concentration (PNC; mostly in the UFP range) and particle diameter (PD), heart and respiratory rate, geographical location, and meteorological variables were measured. To determine inhaled particle counts, ventilation rate was calculated from heart-rate-ventilation associations, produced from periodic exercise testing; 3) thirty-five healthy adults (mean ± SD: age = 39 ± 11 yr; 29% female) completed two return trips of their typical route (HIGH) and a pre-determined altered route of lower proximity to motorised traffic (LOW; determined by the proportion of on-road cycle paths). Particle number concentration (PNC) and diameter (PD) were monitored in real-time in-commute. Acute inflammatory indices of respiratory symptom incidence, lung function and spontaneous sputum (for inflammatory cell analyses) were collected immediately pre-commute, and one and three hours post-commute. The main results of the three studies are that: 1) healthy individuals reported a higher incidence of specific acute respiratory symptoms in- and post- (compared to pre-) commute (p < 0.05). The incidence of specific acute respiratory symptoms was significantly higher for participants with respiratory disorder history compared to healthy participants (p < 0.05). The incidence of in-commute offensive odour detection, and the perception of in-commute air pollution exposure, was significantly lower for participants with smoking history compared to healthy participants (p < 0.05). Females reported significantly higher incidence of in-commute air pollution exposure perception and other specific acute respiratory symptoms, and were more amenable to commute re-routing, compared to males (p < 0.05). Healthy individuals have indicated a higher incidence of acute respiratory symptoms in- and post- (compared to pre-) bicycle commuting, with female gender and respiratory disorder history indicating a comparably-higher susceptibility; 2) total mean PNC of LOW (compared to HIGH) was reduced (1.56 x e4 ± 0.38 x e4 versus 3.06 x e4 ± 0.53 x e4 ppcc; p = 0.012). Total estimated ventilation rate did not vary significantly between LOW and HIGH (43 ± 5 versus 46 ± 9 L•min; p = 0.136); however, due to total mean PNC, accumulated inhaled particle counts were 48% lower in LOW, compared to HIGH (7.6 x e8 ± 1.5 x e8 versus 14.6 x e8 ± 1.8 x e8; p = 0.003); 3) LOW resulted in a significant reduction in mean PNC (1.91 x e4 ± 0.93 x e4 ppcc vs. 2.95 x e4 ± 1.50 x e4 ppcc; p ≤ 0.001). Commute distance and duration were not significantly different between LOW and HIGH (12.8 ± 7.1 vs. 12.0 ± 6.9 km and 44 ± 17 vs. 42 ± 17 mins, respectively). Besides incidence of in-commute offensive odour detection (42 vs. 56 %; p = 0.019), incidence of dust and soot observation (33 vs. 47 %; p = 0.038) and nasopharyngeal irritation (31 vs. 41 %; p = 0.007), acute inflammatory indices were not significantly associated to in-commute PNC, nor were these indices reduced with LOW compared to HIGH. The main conclusions of the three studies are that: 1) the perception of air pollution exposure levels and the amenability to adopt exposure risk management strategies where applicable will aid the general population in shifting from passive, motorised transport modes to bicycle commuting; 2) for bicycle commuting at peak morning commute times, inhaled particle counts and therefore cardiopulmonary health risk may be substantially reduced by decreasing exposure to motorised traffic, which should be considered by both bicycle commuters and urban planners; 3) exposure to PNC, and the incidence of offensive odour and nasopharyngeal irritation, can be significantly reduced when utilising a strategy of lowering proximity to motorised traffic whilst bicycle commuting, without significantly increasing commute distance or duration, which may bring important benefits for both healthy and susceptible individuals. In summary, the findings from this project suggests that bicycle commuters can significantly lower their exposure to ultrafine particle emissions by varying their commute route to reduce proximity to motorised traffic and associated combustion emissions without necessarily affecting their time of commute. While the health endpoints assessed with healthy individuals were not indicative of acute health detriment, individuals with pre-disposing physiological-susceptibility may benefit considerably from this risk management strategy – a necessary research focus with the contemporary increased popularity of both promotion and participation in bicycle commuting.