FRINK Linked Data Fragments server

Matches in SemOpenAlex for { <https://semopenalex.org/work/W2891341107> ?p ?o ?g. }

• W2891341107 endingPage "403" @default.
• W2891341107 startingPage "392" @default.
• W2891341107 abstract "China is in a critical stage of ambient air quality management after global attention on pollution in its cities. Industrial development and urbanization have led to alarming levels of air pollution with serious health hazards in densely populated cities. The quantification of cause-specific PM2.5-related health impacts and corresponding economic loss estimation is crucial for control policies on ambient PM2.5 levels. Based on ground-level direct measurements of PM2.5 concentrations in 338 Chinese cities for the year 2016, this study estimates cause-specific mortality using integrated exposure-response (IER) model, non-linear power law (NLP) model and log-linear (LL) model followed by morbidity assessment using log-linear model. The willingness to pay (WTP) and cost of illness (COI) methods have been used for PM2.5-attributed economic loss assessment. In 2016 in China, the annual PM2.5 concentration ranged between 10 and 157 μg/m3 and 78.79% of the total population was exposed to >35 μg/m3 PM2.5 concentration. Subsequently, the national PM2.5-attributable mortality was 0.964 (95% CI: 0.447, 1.355) million (LL: 1.258 million and NPL: 0.770 million), about 9.98% of total reported deaths in China. Additionally, the total respiratory disease and cardiovascular disease-specific hospital admission morbidity were 0.605 million and 0.364 million. Estimated chronic bronchitis, asthma and emergency hospital admission morbidity were 0.986, 1.0 and 0.117 million respectively. Simultaneously, the PM2.5 exposure caused the economic loss of 101.39 billion US$, which is 0.91% of the national GDP in 2016. This study, for the first time, highlights the discrepancies associated with the three commonly used methodologies applied for cause-specific mortality assessment. Mortality and morbidity results of this study would provide a measurable assessment of 338 cities to the provincial and national policymakers of China for intensifying their efforts on air quality improvement." @default.
• W2891341107 created "2018-09-27" @default.
• W2891341107 creator A5004781570 @default.
• W2891341107 creator A5039675860 @default.
• W2891341107 creator A5056383254 @default.
• W2891341107 creator A5083529259 @default.
• W2891341107 date "2018-12-01" @default.
• W2891341107 modified "2023-10-18" @default.
• W2891341107 title "PM2.5-related health and economic loss assessment for 338 Chinese cities" @default.
• W2891341107 cites W1573077434 @default.
• W2891341107 cites W1601261108 @default.
• W2891341107 cites W1819362720 @default.
• W2891341107 cites W1862113676 @default.
• W2891341107 cites W1980841287 @default.
• W2891341107 cites W1987928674 @default.
• W2891341107 cites W2007596562 @default.
• W2891341107 cites W2010821940 @default.
• W2891341107 cites W2011799742 @default.
• W2891341107 cites W2020311755 @default.
• W2891341107 cites W2022660056 @default.
• W2891341107 cites W2024712407 @default.
• W2891341107 cites W2026841279 @default.
• W2891341107 cites W2062911553 @default.
• W2891341107 cites W2066015033 @default.
• W2891341107 cites W2066148159 @default.
• W2891341107 cites W2069977802 @default.
• W2891341107 cites W2077925494 @default.
• W2891341107 cites W2078709216 @default.
• W2891341107 cites W2081458748 @default.
• W2891341107 cites W2084046231 @default.
• W2891341107 cites W2095469231 @default.
• W2891341107 cites W2095640367 @default.
• W2891341107 cites W2103214555 @default.
• W2891341107 cites W2110052313 @default.
• W2891341107 cites W2121613218 @default.
• W2891341107 cites W2128049102 @default.
• W2891341107 cites W2139572631 @default.
• W2891341107 cites W2141180304 @default.
• W2891341107 cites W2141970008 @default.
• W2891341107 cites W2148822217 @default.
• W2891341107 cites W2152242123 @default.
• W2891341107 cites W2156784363 @default.
• W2891341107 cites W2178774870 @default.
• W2891341107 cites W2220793879 @default.
• W2891341107 cites W2292324066 @default.
• W2891341107 cites W2294362895 @default.
• W2891341107 cites W2294879709 @default.
• W2891341107 cites W2300151471 @default.
• W2891341107 cites W2325869058 @default.
• W2891341107 cites W2333275403 @default.
• W2891341107 cites W2419137754 @default.
• W2891341107 cites W2461336101 @default.
• W2891341107 cites W2461586262 @default.
• W2891341107 cites W2509366888 @default.
• W2891341107 cites W2518697674 @default.
• W2891341107 cites W2531171441 @default.
• W2891341107 cites W2531469489 @default.
• W2891341107 cites W2534063667 @default.
• W2891341107 cites W2554916010 @default.
• W2891341107 cites W2557850980 @default.
• W2891341107 cites W2566321408 @default.
• W2891341107 cites W2577441852 @default.
• W2891341107 cites W2581321420 @default.
• W2891341107 cites W2583446368 @default.
• W2891341107 cites W2599606803 @default.
• W2891341107 cites W2606710141 @default.
• W2891341107 cites W2607350314 @default.
• W2891341107 cites W2609970893 @default.
• W2891341107 cites W2610316289 @default.
• W2891341107 cites W2744846696 @default.
• W2891341107 cites W2745095037 @default.
• W2891341107 cites W2751395834 @default.
• W2891341107 cites W2753051611 @default.
• W2891341107 cites W2753663805 @default.
• W2891341107 cites W2765442061 @default.
• W2891341107 cites W2765800814 @default.
• W2891341107 cites W2766019201 @default.
• W2891341107 cites W2766329946 @default.
• W2891341107 cites W2766335895 @default.
• W2891341107 cites W2767117582 @default.
• W2891341107 cites W2767631445 @default.
• W2891341107 cites W2772868688 @default.
• W2891341107 cites W2775246189 @default.
• W2891341107 cites W2775279707 @default.
• W2891341107 cites W2775495561 @default.
• W2891341107 cites W2782578484 @default.
• W2891341107 cites W2783835530 @default.
• W2891341107 cites W2977289556 @default.
• W2891341107 cites W3025238321 @default.
• W2891341107 cites W4252807987 @default.
• W2891341107 doi "https://doi.org/10.1016/j.envint.2018.09.024" @default.
• W2891341107 hasPubMedId "https://pubmed.ncbi.nlm.nih.gov/30245362" @default.
• W2891341107 hasPublicationYear "2018" @default.
• W2891341107 type Work @default.
• W2891341107 sameAs 2891341107 @default.
• W2891341107 citedByCount "194" @default.
• W2891341107 countsByYear W28913411072019 @default.
• W2891341107 countsByYear W28913411072020 @default.

• next