Project description:The World Health Organization has estimated that air pollution will be one of the most significant challenges related to the environment in the following years, and air quality monitoring and climate change mitigation actions have been promoted due to the Paris Agreement because of their impact on mortality risk. Thus, generating a methodology that supports experts in making decisions based on exposure data, identifying exposure-related activities, and proposing mitigation scenarios is essential. In this context, the emergence of Interactive Process Mining-a discipline that has progressed in the last years in healthcare-could help to develop a methodology based on human knowledge. For this reason, we propose a new methodology for a sequence-oriented sensitive analysis to identify the best activities and parameters to offer a mitigation policy. This methodology is innovative in the following points: i) we present in this paper the first application of Interactive Process Mining pollution personal exposure mitigation; ii) our solution reduces the computation cost and time of the traditional sensitive analysis; iii) the methodology is human-oriented in the sense that the process should be done with the environmental expert; and iv) our solution has been tested with synthetic data to explore the viability before the move to physical exposure measurements, taking the city of Valencia as the use case, and overcoming the difficulty of performing exposure measurements. This dataset has been generated with a model that considers the city of Valencia's demographic and epidemiological statistics. We have demonstrated that the assessments done using sequence-oriented sensitive analysis can identify target activities. The proposed scenarios can improve the initial KPIs-in the best scenario; we reduce the population exposure by 18% and the relative risk by 12%. Consequently, our proposal could be used with real data in future steps, becoming an innovative point for air pollution mitigation and environmental improvement.
Project description:BackgroundAlthough many studies demonstrated reduced mortality risk with higher greenness, few studies examined the modifying effect of greenness on air pollution-health associations. We evaluated residential greenness as an effect modifier of the association between long-term exposure to fine particles (PM2.5) and mortality.MethodsWe used data from all Medicare beneficiaries in North Carolina (NC) and Michigan (MI) (2001-2016). We estimated annual PM2.5 averages using ensemble prediction models. We estimated mortality risk per 1 μg/m3 increase using Cox proportional hazards modeling, controlling for demographics, Medicaid eligibility, and area-level covariates. We investigated health disparities by greenness using the Normalized Difference Vegetation Index with measures of urbanicity and socioeconomic status.ResultsPM2.5 was positively associated with mortality risk. Hazard ratios (HRs) were 1.12 (95% confidence interval (CI) = 1.12 to 1.13) for NC and 1.01 (95% CI = 1.00 to 1.01) for MI. HRs were higher for rural than urban areas. Within each category of urbanicity, HRs were generally higher in less green areas. For combined disparities, HRs were higher in low greenness or low SES areas, regardless of the other factor. HRs were lowest in high-greenness and high-SES areas for both states.ConclusionsIn our study, those in low SES and high-greenness areas had lower associations between PM2.5 and mortality than those in low SES and low greenness areas. Multiple aspects of disparity factors and their interactions may affect health disparities from air pollution exposures. Findings should be considered in light of uncertainties, such as our use of modeled PM2.5 data, and warrant further investigation.
Project description:Vegetation fires can release substantial quantities of fine particles (PM2.5), which are harmful to health. The fire smoke may be transported over long distances and can cause adverse health effects over wide areas.We aimed to assess annual mortality attributable to short-term exposures to vegetation fire-originated PM2.5 in different regions of Europe.PM2.5 emissions from vegetation fires in Europe in 2005 and 2008 were evaluated based on Moderate Resolution Imaging Spectroradiometer (MODIS) satellite data on fire radiative power. Atmospheric transport of the emissions was modeled using the System for Integrated modeLling of Atmospheric coMposition (SILAM) chemical transport model. Mortality impacts were estimated for 27 European countries based on a) modeled daily PM2.5 concentrations and b) population data, both presented in a 50 × 50 km2 spatial grid; c) an exposure-response function for short-term PM2.5 exposure and daily nonaccidental mortality; and d) country-level data for background mortality risk.In the 27 countries overall, an estimated 1,483 and 1,080 premature deaths were attributable to the vegetation fire-originated PM2.5 in 2005 and 2008, respectively. Estimated impacts were highest in southern and eastern Europe. However, all countries were affected by fire-originated PM2.5, and even the lower concentrations in western and northern Europe contributed substantially (~ 30%) to the overall estimate of attributable mortality.Our assessment suggests that air pollution caused by PM2.5 released from vegetation fires is a notable risk factor for public health in Europe. Moreover, the risk can be expected to increase in the future as climate change proceeds. This factor should be taken into consideration when evaluating the overall health and socioeconomic impacts of these fires. Citation: Kollanus V, Prank M, Gens A, Soares J, Vira J, Kukkonen J, Sofiev M, Salonen RO, Lanki T. 2017. Mortality due to vegetation fire-originated PM2.5 exposure in Europe-assessment for the years 2005 and 2008. Environ Health Perspect 125:30-37;?http://dx.doi.org/10.1289/EHP194.
Project description:This paper adopts the PM2.5 concentration data obtained from 1497 station-based monitoring sites, population and gross domestic product (GDP) census data, revealing population exposure and economic effects of PM2.5 in four typical urban agglomerations of China, i.e., Beijing-Tianjin-Hebei (BTH), the Yangtze River delta (YRD), the Pearl River delta (PRD), and Chengdu-Chongqing (CC). The Cokriging interpolation method was used to estimate the PM2.5 concentration from station-level to grid-level. Next, an evaluation was conducted mainly at the grid-level with a cell size of 1 × 1 km, assisted by the urban agglomeration scale. Criteria including the population-weighted mean, the cumulative percent distribution and the correlation coefficient were applied in our evaluation. The results showed that the spatial pattern of population exposure in BTH was consistent with that of PM2.5 concentration, as well as changes in elevation. The topography was also an important factor in the accumulation of PM2.5 in CC. Moreover, the most polluted urban agglomeration based on the population-weighted mean was BTH, while the least was PRD. In terms of the cumulative percent distribution, only 0.51% of the population who lived in the four urban agglomerations, and 2.33% of the GDP that was produced in the four urban agglomerations, were associated with an annual PM2.5 concentration smaller than the Chinese National Ambient Air Quality Standard of 35 µg/m³. This indicates that the majority of people live in the high air polluted areas, and economic development contributes to air pollution. Our results are supported by the high correlation between population exposure and the corresponding GDP in each urban agglomeration.
Project description:Smoking, sex, air pollution, lifestyle, and diet may act independently or in concert with each other to contribute to the different outcomes of lung cancer (LC). This study aims to explore their associations with the carcinogenesis of LC, which will be useful for formulating further preventive strategies. This retrospective, longitudinal follow-up cohort study was carried out by connecting to the MJ Health Database, Taiwan Cancer Registry database, and Taiwan cause of death database from 2000 to 2015. The studied subjects were persons attending the health check-ups, distributed throughout the main island of Taiwan. Cox proportional hazards regression models were used to investigate the risk factors associated with LC development and mortality after stratifying by smoking status, with a special emphasis on ambient two-year average PM2.5 exposure, using a satellite-based spatiotemporal model at a resolution of 1 km2, and on dietary habit including consumption of fruits and vegetables. After a median follow-up of 12.3 years, 736 people developed LC, and 401 people died of LC-related causes. For never smokers, the risk of developing LC (aHR: 1.32, 95%CI: 1.12-1.56) and dying from LC-related causes (aHR: 1.28, 95%CI: 1.01-1.63) rises significantly with every 10 μg/m3 increment of PM2.5 exposure, but not for ever smokers. Daily consumption of more than two servings of vegetables and fruits is associated with lowering LC risk in ever smokers (aHR: 0.68, 95%CI: 0.47-0.97), and preventing PM2.5 exposure is associated with lowering LC risk for never smokers.
Project description:The air quality in Beijing, especially its PM2.5 level, has become of increasing public concern because of its importance and sensitivity related to health risks. A set of monitored PM2.5 data from 31 stations, released for the first time by the Beijing Environmental Protection Bureau, covering 37 days during autumn 2012, was processed using spatial interpolation and overlay analysis. Following analyses of these data, a distribution map of cumulative exceedance days of PM2.5 and a temporal variation map of PM2.5 for Beijing have been drawn. Computational and analytical results show periodic and directional trends of PM2.5 spreading and congregating in space, which reveals the regulation of PM2.5 overexposure on a discontinuous medium-term scale. With regard to the cumulative effect of PM2.5 on the human body, the harm from lower intensity overexposure in the medium term, and higher overexposure in the short term, are both obvious. Therefore, data of population distribution were integrated into the aforementioned PM2.5 spatial spectrum map. A spatial statistical analysis revealed the patterns of PM2.5 gross exposure and exposure probability of residents in the Beijing urban area. The methods and conclusions of this research reveal relationships between long-term overexposure to PM2.5 and people living in high-exposure areas of Beijing, during the autumn of 2012.
Project description:We assessed the health risks of fine particulate matter (PM2.5) ambient air pollution and its trace elemental components in a rural South African community. Air pollution is the largest environmental cause of disease and disproportionately affects low- and middle-income countries. PM2.5 samples were previously collected, April 2017 to April 2018, and PM2.5 mass determined. The filters were analyzed for chemical composition. The United States Environmental Protection Agency's (US EPA) health risk assessment method was applied. Reference doses were calculated from the World Health Organization (WHO) guidelines, South African National Ambient Air Quality Standards (NAAQS), and US EPA reference concentrations. Despite relatively moderate levels of PM2.5 the health risks were substantial, especially for infants and children. The average annual PM2.5 concentration was 11 µg/m3, which is above WHO guidelines, but below South African NAAQS. Adults were exposed to health risks from PM2.5 during May to October, whereas infants and children were exposed to risk throughout the year. Particle-bound nickel posed both non-cancer and cancer risks. We conclude that PM2.5 poses health risks in Thohoyandou, despite levels being compliant with yearly South African NAAQS. The results indicate that air quality standards need to be tightened and PM2.5 levels lowered in South Africa.
Project description:Human exposure to fine particles can have significant harmful effects on the respiratory and cardiovascular system. To investigate daily exposure characteristics to PM2.5 with ambient concentrations in an urban environment, a personal exposure measurements were conducted for school children, office workers and at their residents, in the city of Taj 'Agra', India. In order to account for all the sources of particulate matter exposure, measurements on several different days during December 2013 to February 2014 were carried out. Personal environment monitors (PEM) and APM 550 were used to measure PM2.5 concentration. The research findings provide insight into possible sources and their interaction with human activities in modifying the human exposure levels.
Project description:Fine-particulate pollution is a major public health concern in China. Accurate assessment of the population exposed to PM2.5 requires high-resolution pollution and population information. This paper assesses China's potential population exposure to PM2.5, maps its spatiotemporal variability, and simulates the effects of the recent air pollution control policy. We relate satellite-based Aerosol Optical Depth (AOD) retrievals to ground-based PM2.5 observations. We employ block cokriging (BCK) to improve the spatial interpolation of PM2.5 distribution. We use the subdistrict level population data to estimate and map the potential population exposure to PM2.5 pollution in China at the subdistrict level, the smallest administrative unit with public demographic information. During 8 April 2013 and 7 April 2014, China's population-weighted annual average PM2.5 concentration was nearly 7 times the annual average level suggested by the World Health Organization (WHO). About 1322 million people, or 98.6% of the total population, were exposed to PM2.5 at levels above WHO's daily guideline for longer than half a year. If China can achieve its Action Plan on Prevention and Control of Air Pollution targets by 2017, the population exposed to PM2.5 above China's daily standard for longer than half a year will be reduced by 85%.
Project description:BACKGROUND AND PURPOSE:Acute exposure to particulate matter with aerodynamic diameter <2.5 μm (PM2.5) is associated with acute cardiovascular and cerebrovascular mortality. The aim of this study was to evaluate these associations with specific causes of cardiovascular and cerebrovascular mortality in Mexico City. METHODS:We obtained daily mortality records for Mexico City from 2004 to 2013 for cardiovascular and cerebrovascular causes in people ≥25 and ≥65 years old. Exposure to PM2.5 was assessed with daily estimates from a new hybrid spatiotemporal model using satellite measurements of aerosol optical depth PM2.5 and compared to ground level PM2.5 measurements with missing data estimated with generalized additive models PM2.5. We fitted Poisson regression models with distributed lags for all mortality outcomes. RESULTS:An increase of 10 µg/m3 in aerosol optical depth PM2.5 was associated with increased cardiovascular (1.22%; 95% confidence interval, 0.17-2.28) and cerebrovascular mortality (3.43%; 95% confidence interval, 0.10-6.28) for lag days 0 to 1 (lag 0-1). Stronger effects were identified for hemorrhagic stroke and people ≥65 years. Associations were slightly smaller using generalized additive models PM2.5. CONCLUSIONS:These results support the evidence that acute exposure to PM2.5 is associated with increased risk of specific cardiovascular and cerebrovascular mortality causes.