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      Concurrent assessment of personal, indoor, and outdoor PM 2.5 and PM 1 levels and source contributions using novel low‐cost sensing devices

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          Abstract

          The intensity, frequency, duration, and contribution of distinct PM 2.5 sources in Asian households have seldom been assessed; these are evaluated in this work with concurrent personal, indoor, and outdoor PM 2.5 and PM 1 monitoring using novel low‐cost sensing (LCS) devices, AS‐LUNG. GRIMM‐comparable observations were acquired by the corrected AS‐LUNG readings, with R 2 up to 0.998. Twenty‐six non‐smoking healthy adults were recruited in Taiwan in 2018 for 7‐day personal, home indoor, and home outdoor PM monitoring. The results showed 5‐min PM 2.5 and PM 1 exposures of 11.2 ± 10.9 and 10.5 ± 9.8 µg/m 3, respectively. Cooking occurred most frequently; cooking with and without solid fuel contributed to high PM 2.5 increments of 76.5 and 183.8 µg/m 3 (1 min), respectively. Incense burning had the highest mean PM 2.5 indoor/outdoor (1.44 ± 1.44) ratios at home and on average the highest 5‐min PM 2.5 increments (15.0 µg/m 3) to indoor levels, among all single sources. Certain events accounted for 14.0%‐39.6% of subjects’ daily exposures. With the high resolution of AS‐LUNG data and detailed time‐activity diaries, the impacts of sources and ventilations were assessed in detail.

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          Global, regional, and national comparative risk assessment of 79 behavioural, environmental and occupational, and metabolic risks or clusters of risks, 1990–2015: a systematic analysis for the Global Burden of Disease Study 2015

          Summary Background The Global Burden of Diseases, Injuries, and Risk Factors Study 2015 provides an up-to-date synthesis of the evidence for risk factor exposure and the attributable burden of disease. By providing national and subnational assessments spanning the past 25 years, this study can inform debates on the importance of addressing risks in context. Methods We used the comparative risk assessment framework developed for previous iterations of the Global Burden of Disease Study to estimate attributable deaths, disability-adjusted life-years (DALYs), and trends in exposure by age group, sex, year, and geography for 79 behavioural, environmental and occupational, and metabolic risks or clusters of risks from 1990 to 2015. This study included 388 risk-outcome pairs that met World Cancer Research Fund-defined criteria for convincing or probable evidence. We extracted relative risk and exposure estimates from randomised controlled trials, cohorts, pooled cohorts, household surveys, census data, satellite data, and other sources. We used statistical models to pool data, adjust for bias, and incorporate covariates. We developed a metric that allows comparisons of exposure across risk factors—the summary exposure value. Using the counterfactual scenario of theoretical minimum risk level, we estimated the portion of deaths and DALYs that could be attributed to a given risk. We decomposed trends in attributable burden into contributions from population growth, population age structure, risk exposure, and risk-deleted cause-specific DALY rates. We characterised risk exposure in relation to a Socio-demographic Index (SDI). Findings Between 1990 and 2015, global exposure to unsafe sanitation, household air pollution, childhood underweight, childhood stunting, and smoking each decreased by more than 25%. Global exposure for several occupational risks, high body-mass index (BMI), and drug use increased by more than 25% over the same period. All risks jointly evaluated in 2015 accounted for 57·8% (95% CI 56·6–58·8) of global deaths and 41·2% (39·8–42·8) of DALYs. In 2015, the ten largest contributors to global DALYs among Level 3 risks were high systolic blood pressure (211·8 million [192·7 million to 231·1 million] global DALYs), smoking (148·6 million [134·2 million to 163·1 million]), high fasting plasma glucose (143·1 million [125·1 million to 163·5 million]), high BMI (120·1 million [83·8 million to 158·4 million]), childhood undernutrition (113·3 million [103·9 million to 123·4 million]), ambient particulate matter (103·1 million [90·8 million to 115·1 million]), high total cholesterol (88·7 million [74·6 million to 105·7 million]), household air pollution (85·6 million [66·7 million to 106·1 million]), alcohol use (85·0 million [77·2 million to 93·0 million]), and diets high in sodium (83·0 million [49·3 million to 127·5 million]). From 1990 to 2015, attributable DALYs declined for micronutrient deficiencies, childhood undernutrition, unsafe sanitation and water, and household air pollution; reductions in risk-deleted DALY rates rather than reductions in exposure drove these declines. Rising exposure contributed to notable increases in attributable DALYs from high BMI, high fasting plasma glucose, occupational carcinogens, and drug use. Environmental risks and childhood undernutrition declined steadily with SDI; low physical activity, high BMI, and high fasting plasma glucose increased with SDI. In 119 countries, metabolic risks, such as high BMI and fasting plasma glucose, contributed the most attributable DALYs in 2015. Regionally, smoking still ranked among the leading five risk factors for attributable DALYs in 109 countries; childhood underweight and unsafe sex remained primary drivers of early death and disability in much of sub-Saharan Africa. Interpretation Declines in some key environmental risks have contributed to declines in critical infectious diseases. Some risks appear to be invariant to SDI. Increasing risks, including high BMI, high fasting plasma glucose, drug use, and some occupational exposures, contribute to rising burden from some conditions, but also provide opportunities for intervention. Some highly preventable risks, such as smoking, remain major causes of attributable DALYs, even as exposure is declining. Public policy makers need to pay attention to the risks that are increasingly major contributors to global burden. Funding Bill & Melinda Gates Foundation.
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            The National Human Activity Pattern Survey (NHAPS): a resource for assessing exposure to environmental pollutants.

            Because human activities impact the timing, location, and degree of pollutant exposure, they play a key role in explaining exposure variation. This fact has motivated the collection of activity pattern data for their specific use in exposure assessments. The largest of these recent efforts is the National Human Activity Pattern Survey (NHAPS), a 2-year probability-based telephone survey (n=9386) of exposure-related human activities in the United States (U.S.) sponsored by the U.S. Environmental Protection Agency (EPA). The primary purpose of NHAPS was to provide comprehensive and current exposure information over broad geographical and temporal scales, particularly for use in probabilistic population exposure models. NHAPS was conducted on a virtually daily basis from late September 1992 through September 1994 by the University of Maryland's Survey Research Center using a computer-assisted telephone interview instrument (CATI) to collect 24-h retrospective diaries and answers to a number of personal and exposure-related questions from each respondent. The resulting diary records contain beginning and ending times for each distinct combination of location and activity occurring on the diary day (i.e., each microenvironment). Between 340 and 1713 respondents of all ages were interviewed in each of the 10 EPA regions across the 48 contiguous states. Interviews were completed in 63% of the households contacted. NHAPS respondents reported spending an average of 87% of their time in enclosed buildings and about 6% of their time in enclosed vehicles. These proportions are fairly constant across the various regions of the U.S. and Canada and for the California population between the late 1980s, when the California Air Resources Board (CARB) sponsored a state-wide activity pattern study, and the mid-1990s, when NHAPS was conducted. However, the number of people exposed to environmental tobacco smoke (ETS) in California seems to have decreased over the same time period, where exposure is determined by the reported time spent with a smoker. In both California and the entire nation, the most time spent exposed to ETS was reported to take place in residential locations.
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              Solid Fuel Use for Household Cooking: Country and Regional Estimates for 1980–2010

              Background: Exposure to household air pollution from cooking with solid fuels in simple stoves is a major health risk. Modeling reliable estimates of solid fuel use is needed for monitoring trends and informing policy. Objectives: In order to revise the disease burden attributed to household air pollution for the Global Burden of Disease 2010 project and for international reporting purposes, we estimated annual trends in the world population using solid fuels. Methods: We developed a multilevel model based on national survey data on primary cooking fuel. Results: The proportion of households relying mainly on solid fuels for cooking has decreased from 62% (95% CI: 58, 66%) to 41% (95% CI: 37, 44%) between 1980 and 2010. Yet because of population growth, the actual number of persons exposed has remained stable at around 2.8 billion during three decades. Solid fuel use is most prevalent in Africa and Southeast Asia where > 60% of households cook with solid fuels. In other regions, primary solid fuel use ranges from 46% in the Western Pacific, to 35% in the Eastern Mediterranean and < 20% in the Americas and Europe. Conclusion: Multilevel modeling is a suitable technique for deriving reliable solid-fuel use estimates. Worldwide, the proportion of households cooking mainly with solid fuels is decreasing. The absolute number of persons using solid fuels, however, has remained steady globally and is increasing in some regions. Surveys require enhancement to better capture the health implications of new technologies and multiple fuel use.
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                Author and article information

                Contributors
                sclung@rcec.sinica.edu.tw
                Journal
                Indoor Air
                Indoor Air
                10.1111/(ISSN)1600-0668
                INA
                Indoor Air
                John Wiley and Sons Inc. (Hoboken )
                0905-6947
                1600-0668
                31 December 2020
                May 2021
                : 31
                : 3 ( doiID: 10.1111/ina.v31.3 )
                : 755-768
                Affiliations
                [ 1 ] Research Center for Environmental Changes Academia Sinica Taipei Taiwan
                [ 2 ] Department of Atmospheric Sciences National Taiwan University Taipei Taiwan
                [ 3 ] Institute of Environmental and Occupational Health Sciences National Taiwan University Taipei Taiwan
                Author notes
                [*] [* ] Correspondence

                Shih‐Chun Candice Lung, Research Center for Environmental Changes, Academia Sinica, No. 128, Sec. 2, Academia Road, Nangang, Taipei 11529, Taiwan.

                Email: sclung@ 123456rcec.sinica.edu.tw

                Author information
                https://orcid.org/0000-0002-4227-0469
                https://orcid.org/0000-0002-2417-1504
                https://orcid.org/0000-0002-6307-0538
                https://orcid.org/0000-0003-2898-418X
                https://orcid.org/0000-0003-2755-1542
                https://orcid.org/0000-0002-7160-2952
                https://orcid.org/0000-0002-5835-910X
                Article
                INA12763
                10.1111/ina.12763
                8247015
                33047373
                4d4463ac-1c79-4822-a66e-5b10a4ec2aa1
                © 2020 The Authors. Indoor Air published by John Wiley & Sons Ltd

                This is an open access article under the terms of the http://creativecommons.org/licenses/by-nc-nd/4.0/ License, which permits use and distribution in any medium, provided the original work is properly cited, the use is non‐commercial and no modifications or adaptations are made.

                History
                : 22 September 2020
                : 17 June 2020
                : 30 September 2020
                Page count
                Figures: 3, Tables: 4, Pages: 14, Words: 10839
                Funding
                Funded by: Academia Sinica , open-funder-registry 10.13039/501100001869;
                Award ID: AS‐104‐SS‐A02
                Award ID: AS‐SS‐107‐03
                Award ID: Project No. 022324
                Funded by: Ministry of Science and Technology, Taiwan , open-funder-registry 10.13039/501100004663;
                Award ID: Project No. 108‐2111‐M‐001‐014
                Categories
                Original Article
                Original Articles
                Custom metadata
                2.0
                May 2021
                Converter:WILEY_ML3GV2_TO_JATSPMC version:6.0.2 mode:remove_FC converted:01.07.2021

                Health & Social care
                asian pm exposure sources,exposure behavior,i/o ratio,indoor particles,low‐cost sensors,pm sensing device

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