Optimization and Process Design Tools for Estimation of Weekly Exposure to Air Pollution Integrating Travel Patterns during Pregnancy

A growing number of international studies have highlighted that ambient air pollution exposures are related to different health outcomes. To do so, researchers need to estimate exposure levels to air pollution throughout everyday life. In the literature, the most commonly used estimate is based on home address only or taking into account, in addition, the work address. However, several studies have shown the importance of daily mobility in the estimate of exposure to air pollutants. In this context, we developed an R procedure that estimates individual exposures combining home addresses, several important places, and itineraries of the principal mobility during a week. It supplies researchers a useful tool to calculate individual daily exposition to air pollutants weighting by the time spent at each of the most frequented locations (work, shopping, residential address, etc.) and while commuting. This task requires the efficient calculation of travel time matrices or the examination of multimodal transport routes. This procedure is freely available from the Equit’Area project website: (https://www.equitarea.org). This procedure is structured in three parts: the first part is to create a network, the second allows to estimate main itineraries of the daily mobility and the last one tries to reconstitute the level of air pollution exposure. One main advantage of the tool is that the procedure can be used with different spatial scales and for any air pollutant.

On the potential of iPhone significant location data to characterize individual mobility for air pollution health studies

In many air pollution health studies,the time-activity pattern of individuals is often ignored largely due to lack of data.However,a better understanding of this location-based information is expected to decrease uncertainties in exposure estimation.Here,we showcase the potential of iPhone’s Significant Location(iSL)data in capturing the user’s historical time-activity patterns in order to estimate exposure to ambient air pollutants.In this study,one subject carried an iPhone in tandem with a reference GPS tracking device for one month.The GPS device recorded locations in 10 second intervals while the iSL recorded the time spent in locations the subject visited frequently.Using GPS data as a reference,we then evaluated the accuracy of iSL data in capturing the subject’s time-activity patterns and time-weighted air pollution concentration within the study time period.We found the iSL data accurately captured the time the subject spent in 16 microenvironments(i.e.locations the subject visited more than once),which was 93%of the time during the study period.The average error of time-weighted aerosol optical depth value,a surrogate of particle pollution,is only 0.012%.To explore the availability of iSL data among iPhone users,an online survey was conducted.Among the 349 surveyed participants,72%of them have iSL data available.Considering the popularity of iPhones,iSL data may be available for a significant portion of the general population.Our results suggest iSL data have great potential for characterizing historical time-activity patterns to improve air pollution exposure estimation.

Investigating the impact of air pollution on AMI and COPD hospital admissions in the coastal city of Qingdao,China

Air pollution has been widely associated with adverse effects on the respiratory and cardiovascular systems.We investigated the relationship between acute myocardial infarction(AMI),chronic obstructive pulmonary disease(COPD)and air pollution exposure in the coastal city of Qingdao,China.Air pollution in this region is characterized by inland and oceanic transportation sources in addition to local emission.We examined the influence of PM_(2.5),PM_(10),NO_(2),SO_(2),CO and O_(3) concentrations on hospital admissions for AMI and COPD from October 1,2014,to September 30,2018,in Qingdao using a Poisson generalized additive model(GAM).We found that PM_(2.5),PM_(10),NO_(2),SO_(2) and CO exhibited a significant short-term(lag 1 day)association with AMI in the singlepollutant model among older adults(>65 years old)and females,especially during the cold season(October to March).In contrast,only NO2 and SO2 had clear cumulative lag associations with COPD admission for females and those over 65 years old at lag 01 and lag 03,respectively.In the twopollutant model,the exposure-response relationship fitted by the two-pollutant model did not change significantly.Our findings indicated that there is an inflection point between the concentration of certain air pollutants and the hospital admissions of AMI and COPD even under the linear assumption,indicative of the benefits of reducing air pollution vary with pollution levels.This study has important implications for the development of policy for air pollution control in Qingdao and the public health benefits of reducing air pollution levels.