A Review of Urban Air Pollution Monitoring and Exposure Assessment Methods <s> Introduction <s> We recognized that many health outcomes are associated with air pollution, but in this project launched by the US EPA, the intent was to assess the role of exposure to ambient air pollutants as risk factors only for respiratory effects in children. The NHANES-III database is a valuable resource for assessing children’s respiratory health and certain risk factors, but lacks monitoring data to estimate subjects’ exposures to ambient air pollutants. Since the 1970s, EPA has regularly monitored levels of several ambient air pollutants across the country and these data may be used to estimate NHANES subject’s exposure to ambient air pollutants. The first stage of the project eventually evolved into assessing different estimation methods before adopting the estimates to evaluate respiratory health. Specifically, this paper describes an effort using EPA’s AIRS monitoring data to estimate ozone and PM10 levels at census block groups. We limited those block groups to counties visited by NHANES-III to make the project more manageable and apply four different interpolation methods to the monitoring data to derive air concentration levels. Then we examine method-specific differences in concentration levels and determine conditions under which different methods produce significantly different concentration values. We find that different interpolation methods do not produce dramatically different estimations in most parts of the US where monitor density was relatively low. However, in areas where monitor density was relatively high (i.e., California), we find substantial differences in exposure estimates across the interpolation methods. Our results offer some insights into terms of using the EPA monitoring data for the chosen spatial interpolation methods. Journal of Exposure Analysis and Environmental Epidemiology (2004) 14, 404–415. doi:10.1038/sj.jea.7500338 <s> BIB001 </s> A Review of Urban Air Pollution Monitoring and Exposure Assessment Methods <s> Introduction <s> Abstract This study addresses two objectives: (1) to develop a formal method of optimally locating a dense network of air pollution monitoring stations; and (2) to derive an exposure assessment model based on these monitoring data and related land use, population, and biophysical information. Previous studies have located monitors in an ad hoc fashion, favouring the placement of monitors in traffic “hot spots” or in areas deemed subjectively to be of interest. We apply our methodology in locating 100 nitrogen dioxide monitors in Toronto, Canada. Locations identified by the method represent land use, transportation infrastructure and the distribution of at-risk populations. Our exposure assessments derived from the monitoring program produce reasonable estimates at the intra-urban scale. The method for optimally locating monitors may have widespread applicability for the design of pollution monitoring networks, particularly for measuring traffic pollutants with fine-scale spatial variability. <s> BIB002 </s> A Review of Urban Air Pollution Monitoring and Exposure Assessment Methods <s> Introduction <s> Scientists and policymakers have shown growing interest in the health effects of chronic air pollution exposure. In this study, we use geostatistical techniques in combination with small-area data to address a central research question: "Does chronic exposure to particulate air pollution significantly associate with mortality when the effects of other social, demographic, and lifestyle confounders are taken into account?" Our analysis relies on age-standardized mortality ratios for census tracts (CTs) of Hamilton (average population of 3419 persons), social and demographic data from the 1991 Census of Canada, smoking variables extracted from secondary surveys, and total suspended particulate (TSP) data from 23 monitoring stations operated by the Ministry of the Environment. Air pollution data are interpolated with a geostatistical procedure known as "kriging". This method translates fixed-site pollution monitoring observations into a continuous surface, which was overlaid onto the population-weighted centroids of the CTs. Our results show substantively large and statistically significant health effects for women and men. Evaluated over the inter-quartile range of the data, we found the relative risk of premature mortality for TSP exposure to be 1.19 (95% CI: 1.13-1.26) for women and 1.30 (95% CI: 1.24-1.37) for men. We also tested associations with cardio-respiratory and cancer mortality. We found positive, significant associations between particulate exposure and these causes of death in most models. Inclusion of socioeconomic, demographic, and lifestyle reduced but did not eliminate the health effects of exposure to particulate air pollution. Overall our results suggest that intra-urban variations in particulate air pollution significantly associate with premature, all-cause, cardio-respiratory, and cancer mortality in small areas of Hamilton. <s> BIB003 </s> A Review of Urban Air Pollution Monitoring and Exposure Assessment Methods <s> Introduction <s> 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. <s> BIB004 </s> A Review of Urban Air Pollution Monitoring and Exposure Assessment Methods <s> Introduction <s> This paper provides the first review of the application of atmospheric models for particle dispersion. The different types of dispersion models available, from simple box type models to complex fluid dynamics models are outlined and the suitability of the different approaches to dispersion modelling within different environments, in regards to scale, complexity of the environment and concentration parameters is assessed. Finally, several major commercial and non-commercial particle dispersion packages are reviewed, detailing which processes are included and advantages and limitations of their use to modelling particle dispersion. The models reviewed included: Box models (AURORA, CPB and PBM), Gaussian models (CALINE4, HIWAY2, CAR-FMI, OSPM, CALPUFF, AEROPOL, AERMOD, UK-ADMS and SCREEN3), Lagrangian/Eulerian Models (GRAL, TAPM, ARIA Regional), CFD models (ARIA Local, MISKAM, MICRO-CALGRID) and models which include aerosol dynamics (GATOR, MONO32, UHMA, CIT, AERO, RPM, AEROFOR2, URM-1ATM, MADRID, CALGRID and UNI-AERO). <s> BIB005 </s> A Review of Urban Air Pollution Monitoring and Exposure Assessment Methods <s> Introduction <s> BACKGROUND ::: Fine particulate air pollution has been linked to cardiovascular disease, but previous studies have assessed only mortality and differences in exposure between cities. We examined the association of long-term exposure to particulate matter of less than 2.5 microm in aerodynamic diameter (PM2.5) with cardiovascular events. ::: ::: ::: METHODS ::: We studied 65,893 postmenopausal women without previous cardiovascular disease in 36 U.S. metropolitan areas from 1994 to 1998, with a median follow-up of 6 years. We assessed the women's exposure to air pollutants using the monitor located nearest to each woman's residence. Hazard ratios were estimated for the first cardiovascular event, adjusting for age, race or ethnic group, smoking status, educational level, household income, body-mass index, and presence or absence of diabetes, hypertension, or hypercholesterolemia. ::: ::: ::: RESULTS ::: A total of 1816 women had one or more fatal or nonfatal cardiovascular events, as confirmed by a review of medical records, including death from coronary heart disease or cerebrovascular disease, coronary revascularization, myocardial infarction, and stroke. In 2000, levels of PM2.5 exposure varied from 3.4 to 28.3 microg per cubic meter (mean, 13.5). Each increase of 10 microg per cubic meter was associated with a 24% increase in the risk of a cardiovascular event (hazard ratio, 1.24; 95% confidence interval [CI], 1.09 to 1.41) and a 76% increase in the risk of death from cardiovascular disease (hazard ratio, 1.76; 95% CI, 1.25 to 2.47). For cardiovascular events, the between-city effect appeared to be smaller than the within-city effect. The risk of cerebrovascular events was also associated with increased levels of PM2.5 (hazard ratio, 1.35; 95% CI, 1.08 to 1.68). ::: ::: ::: CONCLUSIONS ::: Long-term exposure to fine particulate air pollution is associated with the incidence of cardiovascular disease and death among postmenopausal women. Exposure differences within cities are associated with the risk of cardiovascular disease. <s> BIB006 </s> A Review of Urban Air Pollution Monitoring and Exposure Assessment Methods <s> Introduction <s> Land use regression (LUR) is a promising technique for predicting ambient air pollutant concentrations at high spatial resolution. We expand on previous work by modeling oxides of nitrogen and fine particulate matter in Vancouver, Canada, using two measures of traffic. Systematic review of historical data identified optimal sampling periods for NO and NO2. Integrated 14-day mean concentrations were measured with passive samplers at 116 sites in the spring and fall of 2003. Study estimates for annual mean NO and NO2 ranged from 5.4−98.7 and 4.8−28.0 ppb, respectively. Regulatory measurements ranged from 4.8−29.7 and 9.0−24.1 ppb and exhibited less spatial variability. Measurements of particle mass concentration (PM2.5) and light absorbance (ABS) were made at a subset of 25 sites during another campaign. Fifty-five variables describing each sampling site were generated in a Geographic Information System (GIS) and linear regression models for NO, NO2, PM2.5, and ABS were built with the most predictive covari... <s> BIB007 </s> A Review of Urban Air Pollution Monitoring and Exposure Assessment Methods <s> Introduction <s> Abstract Several recent studies associated long-term exposure to air pollution with increased mortality. An ongoing cohort study, the Netherlands Cohort Study on Diet and Cancer (NLCS), was used to study the association between long-term exposure to traffic-related air pollution and mortality. Following on a previous exposure assessment study in the NLCS, we improved the exposure assessment methods. Long-term exposure to nitrogen dioxide (NO2), nitrogen oxide (NO), black smoke (BS), and sulphur dioxide (SO2) was estimated. Exposure at each home address (N=21 868) was considered as a function of a regional, an urban and a local component. The regional component was estimated using inverse distance weighed interpolation of measurement data from regional background sites in a national monitoring network. Regression models with urban concentrations as dependent variables, and number of inhabitants in different buffers and land use variables, derived with a Geographic Information System (GIS), as predictor variables were used to estimate the urban component. The local component was assessed using a GIS and a digital road network with linked traffic intensities. Traffic intensity on the nearest road and on the nearest major road, and the sum of traffic intensity in a buffer of 100 m around each home address were assessed. Further, a quantitative estimate of the local component was estimated. The regression models to estimate the urban component explained 67%, 46%, 49% and 35% of the variances of NO2, NO, BS, and SO2 concentrations, respectively. Overall regression models which incorporated the regional, urban and local component explained 84%, 44%, 59% and 56% of the variability in concentrations for NO2, NO, BS and SO2, respectively. We were able to develop an exposure assessment model using GIS methods and traffic intensities that explained a large part of the variations in outdoor air pollution concentrations. <s> BIB008 </s> A Review of Urban Air Pollution Monitoring and Exposure Assessment Methods <s> Introduction <s> Epidemiologic studies of air pollution require accurate exposure assessments at unmonitored locations in order to minimize exposure misclassification. One approach gaining considerable interest is the land-use regression (LUR) model. Generally, the LUR model has been utilized to characterize air pollution exposure and health effects for individuals residing within urban areas. The objective of this article is to briefly summarize the history and application of LUR models to date outlining similarities and differences of the variables included in the model, model development, and model validation. There were 6 studies available for a total of 12 LUR models. Our findings indicated that among these studies, the four primary classes of variables used were road type, traffic count, elevation, and land cover. Of these four, traffic count was generally the most important. The model R2 explaining the variability in the exposure estimates for these LUR models ranged from .54 to .81. The number of air sampling sites generating the exposure estimates, however, was not correlated with the model R2 suggesting that the locations of the sampling sites may be of greater importance than the total number of sites. The primary conclusion of this study is that LUR models are an important tool for integrating traffic and geographic information to characterize variability in exposures. <s> BIB009 </s> A Review of Urban Air Pollution Monitoring and Exposure Assessment Methods <s> Introduction <s> BACKGROUND ::: Evidence suggests that air pollution exposure adversely affects pregnancy outcomes. Few studies have examined individual-level intraurban exposure contrasts. ::: ::: ::: OBJECTIVES ::: We evaluated the impacts of air pollution on small for gestational age (SGA) birth weight, low full-term birth weight (LBW), and preterm birth using spatiotemporal exposure metrics. ::: ::: ::: METHODS ::: With linked administrative data, we identified 70,249 singleton births (1999-2002) with complete covariate data (sex, ethnicity, parity, birth month and year, income, education) and maternal residential history in Vancouver, British Columbia, Canada. We estimated residential exposures by month of pregnancy using nearest and inverse-distance weighting (IDW) of study area monitors [carbon monoxide, nitrogen dioxide, nitric oxide, ozone, sulfur dioxide, and particulate matter < 2.5 (PM2.5) or < 10 (PM10) microm in aerodynamic diameter], temporally adjusted land use regression (LUR) models (NO, NO2, PM2.5, black carbon), and proximity to major roads. Using logistic regression, we estimated the risk of mean (entire pregnancy, first and last month of pregnancy, first and last 3 months) air pollution concentrations on SGA (< 10th percentile), term LBW (< 2,500 g), and preterm birth. ::: ::: ::: RESULTS ::: Residence within 50 m of highways was associated with a 22% (95% CI, 0.81-1.87) [corrected] increase in LBW. Exposure to all air pollutants except O3 was associated with SGA, with similar odds ratios (ORs) for LUR and monitoring estimates (e.g., LUR: OR = 1.02; 95% CI, 1.00-1.04; IDW: OR = 1.05; 95% CI, 1.03-1.08 per 10-microg/m3 increase in NO). For preterm births, associations were observed with PM2.5 for births < 37 weeks gestation (and for other pollutants at < 30 weeks). No consistent patterns suggested exposure windows of greater relevance. ::: ::: ::: CONCLUSION ::: Associations between traffic-related air pollution and birth outcomes were observed in a population-based cohort with relatively low ambient air pollution exposure. <s> BIB010 </s> A Review of Urban Air Pollution Monitoring and Exposure Assessment Methods <s> Introduction <s> BackgroundThere is a growing body of literature linking GIS-based measures of traffic density to asthma and other respiratory outcomes. However, no consensus exists on which traffic indicators best capture variability in different pollutants or within different settings. As part of a study on childhood asthma etiology, we examined variability in outdoor concentrations of multiple traffic-related air pollutants within urban communities, using a range of GIS-based predictors and land use regression techniques.MethodsWe measured fine particulate matter (PM2.5), nitrogen dioxide (NO2), and elemental carbon (EC) outside 44 homes representing a range of traffic densities and neighborhoods across Boston, Massachusetts and nearby communities. Multiple three to four-day average samples were collected at each home during winters and summers from 2003 to 2005. Traffic indicators were derived using Massachusetts Highway Department data and direct traffic counts. Multivariate regression analyses were performed separately for each pollutant, using traffic indicators, land use, meteorology, site characteristics, and central site concentrations.ResultsPM2.5 was strongly associated with the central site monitor (R2 = 0.68). Additional variability was explained by total roadway length within 100 m of the home, smoking or grilling near the monitor, and block-group population density (R2 = 0.76). EC showed greater spatial variability, especially during winter months, and was predicted by roadway length within 200 m of the home. The influence of traffic was greater under low wind speed conditions, and concentrations were lower during summer (R2 = 0.52). NO2 showed significant spatial variability, predicted by population density and roadway length within 50 m of the home, modified by site characteristics (obstruction), and with higher concentrations during summer (R2 = 0.56).ConclusionEach pollutant examined displayed somewhat different spatial patterns within urban neighborhoods, and were differently related to local traffic and meteorology. Our results indicate a need for multi-pollutant exposure modeling to disentangle causal agents in epidemiological studies, and further investigation of site-specific and meteorological modification of the traffic-concentration relationship in urban neighborhoods. <s> BIB011 </s> A Review of Urban Air Pollution Monitoring and Exposure Assessment Methods <s> Introduction <s> Evidence is increasing that long-term exposure to ambient air pollution is associated with deaths from cardiopulmonary diseases. In a 2002 pilot study, we reported clear indications that traffic-related air pollution, especially at the local scale, was related to cardiopulmonary mortality in a randomly selected subcohort of 5000 older adults participating in the ongoing Netherlands Cohort Study (NLCS) on diet and cancer. In the current study, referred to as NLCS-AIR, our objective was to obtain more precise estimates of the effects of traffic-related air pollution by analyzing associations with cause-specific mortality, as well as lung cancer incidence, in the full cohort of approximately 120,000 subjects. Cohort members were 55 to 69 years of age at enrollment in 1986. Follow-up was from 1987 through 1996 for mortality (17,674 deaths) and from late 1986 through 1997 for lung cancer incidence (2234 cases). Information about potential confounding variables and effect modifiers was available from the questionnaire that subjects completed at enrollment and from publicly available data (including neighborhood-scale information such as income distributions). The NLCS was designed for a case-cohort approach, which makes use of all the cases in the full cohort, while data for the random subcohort are used to estimate person-time experience in the study. Full information on confounders was available for the subjects in the random subcohort and for the emerging cases of mortality and lung cancer incidence during the follow-up period, and in NLCS-AIR we used the case-cohort approach to examine the relation between exposure to air pollution and cause-specific mortality and lung cancer. We also specified a standard Cox proportional hazards model within the full cohort, for which information on potential confounding variables was much more limited. Exposure to air pollution was estimated for the subjects' home addresses at baseline in 1986. Concentrations were estimated for black smoke (a simple marker for soot) and nitrogen dioxide (NO2) as indicators of traffic-related air pollution, as well as nitric oxide (NO), sulfur dioxide (SO2), and particulate matter with aerodynamic diameter 65 A-weighted decibels (dB(A); decibels with the sound pressure scale adjusted to conform with the frequency response of the human ear). Examination of sex, smoking status, educational level, and vegetable and fruit intake as possible effect modifiers showed that for overall black smoke concentrations, associations with mortality tended to be stronger in case-cohort subjects with lower levels of education and those with low fruit intake, but differences between strata were not statistically significant. For lung cancer incidence, we found essentially no relation to exposure to NO2, black smoke, PM2.5, SO2, or several traffic indicators. Associations of overall air pollution concentrations and traffic indicator variables with lung cancer incidence were, however, found in subjects who had never smoked, with an RR of 1.47 (95% CI, 1.01-2.16) for a 10-microg/m3 increase in overall black smoke concentration. In the current study, the mortality risks associated with both background air pollution and traffic exposure variables were much smaller than the estimate previously reported in the pilot study for risk of cardiopulmonary mortality associated with living near a major road (RR, 1.95; 95% CI, 1.09-3.51). The differences are most likely due to the extension of the follow-up period in the current study and to random error in the pilot study related to sampling from the full cohort. Though relative risks were generally small in the current study, long-term average concentrations of black smoke, NO2, and PM2.5 were related to mortality, and associations of black smoke and NO2 exposure with natural-cause and respiratory mortality were statistically significant. Traffic intensity near the home was also related to natural-cause mortality. The highest relative risks associated with background air pollution and traffic variables were for respiratory mortality, though the number of deaths was smaller than for the other mortality categories. <s> BIB012 </s> A Review of Urban Air Pollution Monitoring and Exposure Assessment Methods <s> Introduction <s> Background:Air pollution studies increasingly estimate individual-level exposures from area-based measurements by using exposure prediction methods such as nearest-monitor and kriging predictions. However, little is known about the properties of these methods for health effects estimation. This simu <s> BIB013 </s> A Review of Urban Air Pollution Monitoring and Exposure Assessment Methods <s> Introduction <s> BackgroundVariations in air pollution exposure within a community may be associated with asthma prevalence. However, studies conducted to date have produced inconsistent results, possibly due to errors in measurement of the exposures.MethodsA standardized asthma survey was administered to children in grades one and eight in Hamilton, Canada, in 1994–95 (N ~1467). Exposure to air pollution was estimated in four ways: (1) distance from roadways; (2) interpolated surfaces for ozone, sulfur dioxide, particulate matter and nitrous oxides from seven to nine governmental monitoring stations; (3) a kriged nitrogen dioxide (NO2) surface based on a network of 100 passive NO2 monitors; and (4) a land use regression (LUR) model derived from the same monitoring network. Logistic regressions were used to test associations between asthma and air pollution, controlling for variables including neighbourhood income, dwelling value, state of housing, a deprivation index and smoking.ResultsThere were no significant associations between any of the exposure estimates and asthma in the whole population, but large effects were detected the subgroup of children without hayfever (predominately in girls). The most robust effects were observed for the association of asthma without hayfever and NO2LUR OR = 1.86 (95%CI, 1.59–2.16) in all girls and OR = 2.98 (95%CI, 0.98–9.06) for older girls, over an interquartile range increase and controlling for confounders.ConclusionOur findings indicate that traffic-related pollutants, such as NO2, are associated with asthma without overt evidence of other atopic disorders among female children living in a medium-sized Canadian city. The effects were sensitive to the method of exposure estimation. More refined exposure models produced the most robust associations. <s> BIB014 </s> A Review of Urban Air Pollution Monitoring and Exposure Assessment Methods <s> Introduction <s> Poor air quality is a global health issue, causing serious problems like asthma, cancer, and heart disease around the world. Earlier this decade, the World Health Organization estimated that three million people die each year from the effects of air pollution [6]. Unfortunately, while variations in air quality are significant, today's air quality monitors are very sparsely deployed. To address this visibility gap, the Common Sense project is developing participatory sensing systems that allow individuals to measure their personal exposure, groups to aggregate their members' exposure, and activists to mobilize grassroots community action. <s> BIB015 </s> A Review of Urban Air Pollution Monitoring and Exposure Assessment Methods <s> Introduction <s> Abstract Cohort studies designed to estimate human health effects of exposures to urban pollutants require accurate determination of ambient concentrations in order to minimize exposure misclassification errors. However, it is often difficult to collect concentration information at each study subject location. In the absence of complete subject-specific measurements, land-use regression (LUR) models have frequently been used for estimating individual levels of exposures to ambient air pollution. The LUR models, however, have several limitations mainly dealing with extensive monitoring data needs and challenges involved in their broader applicability to other locations. In contrast, air quality models can provide high-resolution source–concentration linkages for multiple pollutants, but require detailed emissions and meteorological information. In this study, first we predicted air quality concentrations of PM2.5, NOx, and benzene in New Haven, CT using hybrid modeling techniques based on CMAQ and AERMOD model results. Next, we used these values as pseudo-observations to develop and evaluate the different LUR models built using alternative numbers of (training) sites (ranging from 25 to 285 locations out of the total 318 receptors). We then evaluated the fitted LUR models using various approaches, including: 1) internal “Leave-One-Out-Cross-Validation” (LOOCV) procedure within the “training” sites selected; and 2) “Hold-Out” evaluation procedure, where we set aside 33–293 tests sites as independent datasets for external model evaluation. LUR models appeared to perform well in the training datasets. However, when these LUR models were tested against independent hold out (test) datasets, their performance diminished considerably. Our results confirm the challenges facing the LUR community in attempting to fit empirical response surfaces to spatially- and temporally-varying pollution levels using LUR techniques that are site dependent. These results also illustrate the potential benefits of enhancing basic LUR models by utilizing air quality modeling tools or concepts in order to improve their reliability or transferability. <s> BIB016 </s> A Review of Urban Air Pollution Monitoring and Exposure Assessment Methods <s> Introduction <s> Worldwide, decision-makers and nongovernment organizations are increasing their use of citizen volunteers to enhance their ability to monitor and manage natural resources, track species at risk, and conserve protected areas. We reviewed the last 10 years of relevant citizen science literature for areas of consensus, divergence, and knowledge gaps. Different community-based monitoring (CBM) activities and governance structures were examined and contrasted. Literature was examined for evidence of common benefits, challenges, and recommendations for successful citizen science. Two major gaps were identified: (1) a need to compare and contrast the success (and the situations that induce success) of CBM programs which present sound evidence of citizen scientists influencing positive environmental changes in the local ecosystems they monitor and (2) more case studies showing use of CBM data by decision-makers or the barriers to linkages and how these might be overcome. If new research focuses on these gaps, and on the differences of opinions that exist, we will have a much better understanding of the social, economic, and ecological benefits of citizen science. <s> BIB017 </s> A Review of Urban Air Pollution Monitoring and Exposure Assessment Methods <s> Introduction <s> Increasing evidence links air pollution to the risk of cardiovascular disease. This study investigated the association between ischemic heart disease (IHD) prevalence and exposure to traffic-related air pollution (nitrogen dioxide [NO₂], fine particulate matter [PM₂.₅], and ozone [O₃]) in a population of susceptible subjects in Toronto. Local (NO₂) exposures were modeled using land use regression based on extensive field monitoring. Regional exposures (PM₂.₅, O₃) were modeled as confounders using inverse distance weighted interpolation based on government monitoring data. The study sample consisted of 2360 patients referred during 1992 to 1999 to a pulmonary clinic at the Toronto Western Hospital in Toronto, Ontario, Canada, to diagnose or manage a respiratory complaint. IHD status was determined by clinical database linkages (ICD-9-CM 412-414). The association between IHD and air pollutants was assessed with a modified Poisson regression resulting in relative risk estimates. Confounding was controlled with individual and neighborhood-level covariates. After adjusting for multiple covariates, NO₂ was significantly associated with increased IHD risk, relative risk (RR) = 1.33 (95% confidence interval [CI]: 1.2, 1.47). Subjects living near major roads and highways had a trend toward an elevated risk of IHD, RR = 1.08 (95% CI: 0.99, 1.18). Regional PM₂.₅ and O₃ were not associated with risk of IHD. <s> BIB018 </s> A Review of Urban Air Pollution Monitoring and Exposure Assessment Methods <s> Introduction <s> BACKGROUND ::: Ambient air pollution is suspected to cause lung cancer. We aimed to assess the association between long-term exposure to ambient air pollution and lung cancer incidence in European populations. ::: ::: ::: METHODS ::: This prospective analysis of data obtained by the European Study of Cohorts for Air Pollution Effects used data from 17 cohort studies based in nine European countries. Baseline addresses were geocoded and we assessed air pollution by land-use regression models for particulate matter (PM) with diameter of less than 10 μm (PM10), less than 2·5 μm (PM2·5), and between 2·5 and 10 μm (PMcoarse), soot (PM2·5absorbance), nitrogen oxides, and two traffic indicators. We used Cox regression models with adjustment for potential confounders for cohort-specific analyses and random effects models for meta-analyses. ::: ::: ::: FINDINGS ::: The 312 944 cohort members contributed 4 013 131 person-years at risk. During follow-up (mean 12·8 years), 2095 incident lung cancer cases were diagnosed. The meta-analyses showed a statistically significant association between risk for lung cancer and PM10 (hazard ratio [HR] 1·22 [95% CI 1·03-1·45] per 10 μg/m(3)). For PM2·5 the HR was 1·18 (0·96-1·46) per 5 μg/m(3). The same increments of PM10 and PM2·5 were associated with HRs for adenocarcinomas of the lung of 1·51 (1·10-2·08) and 1·55 (1·05-2·29), respectively. An increase in road traffic of 4000 vehicle-km per day within 100 m of the residence was associated with an HR for lung cancer of 1·09 (0·99-1·21). The results showed no association between lung cancer and nitrogen oxides concentration (HR 1·01 [0·95-1·07] per 20 μg/m(3)) or traffic intensity on the nearest street (HR 1·00 [0·97-1·04] per 5000 vehicles per day). ::: ::: ::: INTERPRETATION ::: Particulate matter air pollution contributes to lung cancer incidence in Europe. ::: ::: ::: FUNDING ::: European Community's Seventh Framework Programme. <s> BIB019 </s> A Review of Urban Air Pollution Monitoring and Exposure Assessment Methods <s> Introduction <s> The role of sustainable mobility and its impact on society and the environment is evident and recognized worldwide. Nevertheless, although there is a growing number of measures and projects that deal with sustainable mobility issues, it is not so easy to compare their results and, so far, there is no globally applicable set of tools and indicators that ensure holistic evaluation and facilitate replicability of the best practices. In this paper, based on the extensive literature review, we give a systematic overview of relevant and scientifically sound indicators that cover different aspects of sustainable mobility that are applicable in different social and economic contexts around the world. Overall, 22 sustainable mobility indicators have been selected and an overview of the applied measures described across the literature review has been presented. <s> BIB020 </s> A Review of Urban Air Pollution Monitoring and Exposure Assessment Methods <s> Introduction <s> It is estimated that each of us, on a daily basis, produces a bit more than 1 GB of digital content through our mobile phone and social networks activities, bank card payments, location-based positioning information, online activities, etc. However, the implementation of these large data amounts in city assets planning systems still remains a rather abstract idea for several reasons, including the fact that practical examples are still very strongly services-oriented, and are a largely unexplored and interdisciplinary field; hence, missing the cross-cutting dimension. In this paper, we describe the Policy 2.0 concept and integrate user generated content into Policy 2.0 platform for sustainable mobility planning. By means of a real-life example, we demonstrate the applicability of such a big data integration approach to smart cities planning process. Observed benefits range from improved timeliness of the data and reduced duration of the planning cycle to more informed and agile decision making, on both the citizens and the city planners end. The integration of big data into the planning process, at this stage, does not have uniform impact across all levels of decision making and planning process, therefore it should be performed gradually and with full awareness of existing limitations. <s> BIB021 </s> A Review of Urban Air Pollution Monitoring and Exposure Assessment Methods <s> Introduction <s> Sustainable mobility and smart mobility management play important roles in achieving smart cities’ goals. In this context we investigate the role of smartphones as mobility behavior sensors and evaluate the responsivity of different attitudinal profiles towards personalized route suggestion incentives delivered via mobile phones. The empirical results are based on mobile sensed data collected from more than 3400 people’s real life over a period of six months. The findings show which user profiles are most likely to accept such incentives and how likely they are to result in more sustainable mode choices. In addition we provide insights into tendencies towards accepting more sustainable route options for different trip purposes and illustrate smart city platform potential (for collection of mobility behavior data and delivery of incentives) as a tool for development of personalized mobility management campaigns and policies. <s> BIB022
The world energy consumption has increased rapidly due to economic growth, rising populations and industrialization over the last 50 years. This rise in energy consumption is primarily from increased use of fossil fuel. The burning of fossil fuel produces a huge amount of Carbon dioxide (CO 2 ), which is a greenhouse gas that contributes to global warming, causing the Earth surface temperature rise in response. More harmfully, it emits a number of air pollutants such as Carbon monoxide (CO), Sulfur dioxide (SO 2 ), Nitrogen oxides (NO x ) and Particulate matters (PM 2.5 and PM  ). Exposure to these air pollutants has both acute and chronic effects on human health, affecting a number of different systems and organs. These effects range from minor upper respiratory irritation to chronic respiratory and heart disease, lung cancer, acute respiratory infection and asthmatic attacks BIB019 . In addition, long-term exposures have also been linked with premature mortality and reduced life expectancy. For example, around 90% of human population in European cities are exposed to pollution levels exceeding World Health Organization (WHO) air quality guidelines levels and, as a consequence, it is estimated that the average life expectancy in the European Union is 8.6 months lower [2, 3] . The public should be aware of their air quality through pollution monitoring, eventually urging the local and international authorities to take actions on air pollution reduction such as traffic and industrial activity control, land use management, etc. For legislatory purposes, policymakers have been installing monitoring stations or systems across many cities BIB002 BIB003 . As a consequence, current systems measure air pollution at a very low spatial resolution, e.g., only 22 stations covering a 50 × 50 km 2 (113 km 2 per station) in Beijing, 14 stations covering 1572 km 2 (112 km 2 per station) in London, and 61 stations (221 km 2 per station) in Flanders, Belgium. Researchers have also placed pollution sensors to assess the personal exposure to air pollution in places of interest BIB021 BIB022 BIB020  , such as major roads with heavy traffic and industrial sites. Measurements obtained at these stations or locations can only reflect the air pollution level there or in small areas around there. To estimate these pollutant concentrations at the unmeasured areas using the available measurements, researchers have proposed a variety of methods, e.g., spatial averaging, nearest neighbor, Inverse Distance Weighting (IDW), Kriging, Land-Use Regression (LUR) modeling, dispersion modeling, neural networks, etc. Most studies select one single method to estimate the pollutant concentrations  BIB006 BIB010 BIB007 BIB018 BIB016 BIB011 , while some studies combine several methods together for pollution estimation at different scales BIB012 BIB008 . Some researchers not only assess the exposure to air pollution, but also study the relationship to specific health effects BIB012 BIB013 BIB014 . With the development of pollution sensing and Global Positioning System (GPS) technology in the last few decades, mobile sensing systems with integrated pollution sensors and GPS devices have been gradually applied in urban areas. This increases the density of pollutant measurements, which alleviates, but does not eliminate the measurement sparsity since the carriers of the mobile sensing systems mainly explore specific areas or cover city roads. For such purposes, researchers have adopted the methods developed for stationary monitoring data to estimate the air pollution at unexplored areas. Several general reviews about pollution exposure assessment have been done in the past decades. Jerrett et al. reviewed all available methods for intraurban exposure assessment BIB004 , including interpolation methods, LUR models, dispersion models, hybrid models and so on. Ryan and LeMasters reviewed six studies for a total of 12 LUR models, and summarized the geographic variables commonly used in LUR models BIB009 . Hoek et al. identified 25 LUR studies in their systematic review  . Holmes et al. gave a comprehensive review of dispersion modeling and its application in particle concentration estimation BIB005 . Wong et al. reviewed the studies of air pollution estimation using spatial interpolation methods BIB001 . All of these reviews focus on the air pollution studies using stationary monitoring data; however, to the best of our knowledge, there exists no overview on the research using mobile sensing data. The goal of this paper is to give an overview of the state of the art in air pollution monitoring, including monitoring data acquisition and pollution assessment methods, especially the adoption of these methods in mobile pollution monitoring. The latter seems particularly relevant in the scope of a growing number of citizen science initiatives that aim at implementing mobile sensing approaches for air quality monitoring in their communities BIB017 BIB015 . Furthermore, we give a detailed overview of derived air quality indicators to facilitate transferability of the best practices among different regions and campaigns.