Jan Theunis

Correlation analysis of noise and ultrafine particle counts in a street canyon

Ultrafine particles (UFP, diameter<100 nm) are very likely to negatively affect human health, as underlined by some epidemiological studies. Unfortunately, further investigation and monitoring are hindered by the high cost involved in measuring these UFP. Therefore we investigated the possibility to correlate UFP counts with data coming from low-cost sensors, most notably noise sensors. Analyses are based on an experiment where UFP counts, noise levels, traffic counts, nitrogen oxide (NO, NO(2) and their combination NO(x)) concentrations, and meteorological data were collected simultaneously in a street canyon with a traffic intensity of 3200 vehicles/day, over a 3-week period during summer. Previous reports that NO(x) concentrations could be used as a proxy to UFP monitoring were verified in our setup. Traffic intensity or noise level data were found to correlate with UFP to a lesser degree than NO(x) did. This can be explained by the important influence of meteorological conditions (mainly wind and humidity), influencing UFP dynamics. Although correlations remain moderate, sound levels are more correlated to UFP in the 20-30 nm range. The particles in this size range have indeed rather short atmospheric residence times, and are thus more closely short-term traffic-related. Finally, the UFP estimates were significantly improved by grouping data with similar relative humidity and wind conditions. By doing this, we were able to devise noise indicators that correlate moderately with total particle counts, reaching a Spearman correlation of R=0.62. Prediction with noise indicators is even comparable to the more-expensive-to-measure NO(x) for the smallest UFP, showing the potential of using microphones to estimate UFP counts.

The Aeroflex: A Bicycle for Mobile Air Quality Measurements

Fixed air quality stations have limitations when used to assess peoples real life exposure to air pollutants. Their spatial coverage is too limited to capture the spatial variability in, e.g., an urban or industrial environment. Complementary mobile air quality measurements can be used as an additional tool to fill this void. In this publication we present the Aeroflex, a bicycle for mobile air quality monitoring. The Aeroflex is equipped with compact air quality measurement devices to monitor ultrafine particle number counts, particulate mass and black carbon concentrations at a high resolution (up to 1 second). Each measurement is automatically linked to its geographical location and time of acquisition using GPS and Internet time. Furthermore, the Aeroflex is equipped with automated data transmission, data pre-processing and data visualization. The Aeroflex is designed with adaptability, reliability and user friendliness in mind. Over the past years, the Aeroflex has been successfully used for high resolution air quality mapping, exposure assessment and hot spot identification.

Prediction of ultrafine particle number concentrations in urban environments by means of Gaussian process regression based on measurements of oxides of nitrogen

Gaussian process regression is used to predict ultrafine particle (UFP) number concentrations. We infer their number concentrations based on the concentrations of NO, NO2, CO and O3 at half hour and 5?min resolution. Because UFP number concentrations follow from a dynamic process, we have used a non-stationary kernel based on the addition of a linear and a rational quadratic kernel. Simultaneous measurements of UFP and gaseous pollutants were carried out during one month at three sampling locations situated within a 1?km2 area in a Belgian city, Antwerp. The method proposed provides accurate predictions when using NO and NO2 as covariates and less accurate predictions when using CO and O3. We have also evaluated the models for different training periods and we have found that a training period of at least seven days is suitable to let the models learn the UFP number concentration dynamics in different typologies of traffic. Prediction of UFP number concentrations using Gaussian process regression.Simultaneous measurement at three urban sites of NO/NO2 and UFP.NO and NO2 are the inputs of the model; UFP is the target variable.Similar model performance at three urban sites at 5 and 30?min resolution.

Participatory Patterns in an International Air Quality Monitoring Initiative.

The issue of sustainability is at the top of the political and societal agenda, being considered of extreme importance and urgency. Human individual action impacts the environment both locally (e.g., local air/water quality, noise disturbance) and globally (e.g., climate change, resource use). Urban environments represent a crucial example, with an increasing realization that the most effective way of producing a change is involving the citizens themselves in monitoring campaigns (a citizen science bottom-up approach). This is possible by developing novel technologies and IT infrastructures enabling large citizen participation. Here, in the wider framework of one of the first such projects, we show results from an international competition where citizens were involved in mobile air pollution monitoring using low cost sensing devices, combined with a web-based game to monitor perceived levels of pollution. Measures of shift in perceptions over the course of the campaign are provided, together with insights into participatory patterns emerging from this study. Interesting effects related to inertia and to direct involvement in measurement activities rather than indirect information exposure are also highlighted, indicating that direct involvement can enhance learning and environmental awareness. In the future, this could result in better adoption of policies towards decreasing pollution.

Participatory Air Quality Monitoring in Urban Environments: Reconciling Technological Challenges and Participation

There is a clear scope and added value for participatory air quality monitoring to complement the measurements from official air quality monitoring stations. However, the actually available monitoring tools do not yet allow widespread do-it-yourself approaches. Meanwhile targeted monitoring campaigns can already be implemented with existing devices. To do so there is need for creative ways of collaboration between scientists, citizens and authorities. In this chapter we present a framework for participatory air quality monitoring which starts from the need to clearly define which research questions have to be answered. Setting up a participatory monitoring campaign is further framed by the available sensors, the level of participation and efforts involved and the need for proper data processing and interpretation. The complexity of air quality research asks for a community science approach in which citizen scientists and regular scientists work closely together to answer specific research questions. Two examples highlight the potential and some of the challenges faced by participatory air quality monitoring approaches.

Endothelial function in patients with chronic obstructive pulmonary disease: a systematic review of studies using flow mediated dilatation

ABSTRACT Background: Cardiovascular disease is an important cause of morbidity and mortality in chronic obstructive pulmonary disease (COPD). Endothelial function may be involved in the pathogenesis of cardiovascular disease. In contrast to the attention given to pulmonary endothelial dysfunction, little is known about peripheral vascular changes in COPD. Therefore, we reviewed the literature on peripheral endothelial function in COPD. Methods: Databases were screened for studies using ultrasound-based flow-mediated dilation (FMD), the reference method for assessing peripheral endothelial function, in stable COPD patients. Pooled effect sizes were calculated using random effects model. Results: 17 studies were identified, with a total of 1228 participants (724 COPD patients; 504 controls). Pooled analysis demonstrated an impaired endothelial-dependent FMD (−3.22%; 95% confidence interval (CI) −4.74 to −1.69; p < 0.001; I2 = 96%) and endothelial-independent FMD (−2.86%; 95%CI −5.63 to −0.09; p = 0.04; I2 = 83%) in COPD patients when compared with smoking and non-smoking controls. Conclusion: This review provides evidence for impaired peripheral endothelial function in COPD. Since impaired endothelial function may contribute to cardiovascular morbidity, a more comprehensive cardiovascular phenotyping is considered important in COPD to address cardiovascular risk. A high frequency of cardiovascular comorbidity is observed in COPD patients, and therefore well-controlled, larger studies that investigate endothelial function in COPD patients are recommended.

Oxygen saturation measurements in telemonitoring of patients with COPD: a systematic review

ABSTRACT Introduction: Telemonitoring applications are expected to become a key component in future healthcare. Despite the frequent use of SpO2 measurements in telemonitoring of patients with chronic obstructive pulmonary disease (COPD), no profound overview is available about these measurements. Areas covered: A systematic search identified 71 articles that performed SpO2 measurements in COPD telemonitoring. The results indicate that long-term follow-up of COPD patients using daily SpO2 spot checks is practically feasible. Very few studies specified protocols for performing these measurements. In many studies, deviating SpO2 values were used to raise alerts that led to immediate action from healthcare professionals. However, little information was available about the exact implementation and performance of these alerts. Therefore, no firm conclusions can be drawn about the real value of SpO2 measurements. Future research could optimize performance of alerts using individualized, time-dependent thresholds or predictive algorithms to account for individual differences and SpO2 baseline changes. Additionally, the value of performing continuous measurements should be examined. Expert commentary: Standardization of the measurements, data science techniques and advancing technology can still boost performance of telemonitoring applications. All these opportunities should be thoroughly explored to assess the real value of SpO2 in COPD telemonitoring.

Participatory Sensing, Opinions and Collective Awareness

This book introduces and reviews recent advances in the field in a comprehensive and non-technical way by focusing on the potential of emerging citizen-science and social-computation frameworks, coupled with the latest theoretical and modeling tools developed by physicists, mathematicians, computer and social scientists to analyse, interpret and visualize complex data sets. There is overwhelming evidence that the current organisation of our economies and societies is seriously damaging biological ecosystems and human living conditions in the short term, with potentially catastrophic effects in the long term. The need to re-organise the daily activities with the greatest impact energy consumption, transport, housing towards a more efficient and sustainable development model has recently been raised in the public debate on several global, environmental issues. Above all, this requires the mismatch between global, societal and individual needs to be addressed. Recent advances in Information and Communication Technologies (ICT) can trigger important transitions at the individual and collective level to achieve this aim. Based on the findings of the collaborative research network EveryAware the following developments among the emerging ICT technologies are discussed in depth in this volume: Participatory sensing where ICT development is pushed to the level where it can support informed action at the hyperlocal scale, providing capabilities for environmental monitoring, data aggregation and mining, as well as information presentation and sharing. Web gaming, social computing and internet-mediated collaboration where the Web will continue to acquire the status of an infrastructure for social computing, allowing users cognitive abilities to be coordinated in online communities, and steering the collective action towards predefined goals. Collective awareness and decision-making where the access to both personal and community data, collected by users, processed with suitable analysis tools, and re-presented in an appropriate format by usable communication interfaces leads to a bottom-up development of collective social strategies.

Peripheral endothelial function is positively associated with maximal aerobic capacity in patients with chronic obstructive pulmonary disease

BACKGROUND Patients with COPD are frequently diagnosed with cardiovascular disease. Peripheral endothelial dysfunction is an underlying mechanism and can be used as an early marker of cardiovascular impairment. To date, little is known on the association between peripheral endothelial dysfunction, cardiovascular risk factors and measurements of exercise capacity in patients with COPD. Therefore, we aimed to determine the relation between endothelial function and patient characteristics, cardiovascular risk factors and (micro)vascular and functional performance in patient with CODP. METHODS Clinical and demographic data of patients with COPD were measured during routine pre-rehabilitation assessment. Cardiovascular risk factors, including blood pressure, ankle brachial index, arterial stiffness and retinal vessel widths were obtained. Peripheral endothelial function was measured using the EndoPAT-2000. Functional performance was assessed using cardiopulmonary exercise test, constant work rate test and six-minute walk test. RESULTS 40 patients with COPD completed the study protocol (65% males; mean age: 62.8 ± 7.3 years; mean FEV1: 45.8 ± 17.5 %pred). Peripheral endothelial dysfunction was observed in 55% of the patients. Patients with peripheral endothelial dysfunction had significantly worse aerobic exercise capacity and higher prevalence of cardiovascular risk factors. Stepwise multivariate regression models identified sex, systolic blood pressure and maximal aerobic capacity as independent correlates of peripheral endothelial function. After correction for sex, age and systolic blood pressure, there was a significant partial correlation between peripheral endothelial function and maximal aerobic capacity (R = 0.51, p = 0.004). CONCLUSION Peripheral endothelial function was positively associated with maximal aerobic capacity, when correcting for sex, age and systolic blood pressure. Establishing peripheral endothelial dysfunction as a determinant of impaired aerobic capacity in COPD can be valuable for developing interventions aiming to improve aerobic capacity, and in turn cardiovascular health.

Development and evaluation of land use regression models for black carbon based on bicycle and pedestrian measurements in the urban environment

Land use regression (LUR) modelling is increasingly used in epidemiological studies to predict air pollution exposure. The use of stationary measurements at a limited number of locations to build a LUR model, however, can lead to an overestimation of its predictive abilities. We use opportunistic mobile monitoring to gather data at a high spatial resolution to build LUR models to predict annual average concentrations of black carbon (BC). The models explain a significant part of the variance in BC concentrations. However, the overall predictive performance remains low, due to input uncertainty and lack of predictive variables that can properly capture the complex characteristics of local concentrations. We stress the importance of using an appropriate cross-validation scheme to estimate the predictive performance of the model. By using independent data for the validation and excluding those data also during variable selection in the model building procedure, overly optimistic performance estimates are avoided. Land use regression models are built based on opportunistic mobile measurements.No significant difference between different regression techniques.Distinction between cross-validation with and without a full rebuild of the model.Importance of an appropriate cross-validation scheme to estimate the performance.LUR models explain a significant part of the variance, but overall predictive performance is low.