| 1. |
- Li, Wenjing, et al.
(författare)
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Spatial variation in the effects of air pollution on cardiovascular mortality in Beijing, China
- 2019
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Ingår i: Environmental Science and Pollution Research. - : Springer. - 0944-1344 .- 1614-7499.
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Tidskriftsartikel (refereegranskat)abstract
- Due to lack of data from multiple air quality monitoring stations, studies about spatial association between concentrations of ambient pollutants and mortality in China are rare. To investigate the spatial variation of association between concentrations of particulate matter less than 10 μm in aerodynamic diameter (PM10) and nitrogen dioxide (NO2) and cardiovascular mortality in Beijing, China, we collected data including daily deaths, concentrations of PM10 and NO2, and meteorological factors from January 1, 2009, to December 31, 2010, in all 16 districts of Beijing. Generalized additive model (GAM) and generalized additive mixed model (GAMM) were used to examine the citywide and district-specific effects of PM10 and NO2 on cardiovascular mortality. The citywide effect derived from GAMM was lower than that derived from GAM and the strongest effects were identified for 2-day moving average lag 0–1. For every 10 μg/m3 increases in concentrations of PM10 and NO2, the corresponding daily cardiovascular mortality increases in 0.31% (95%CI 0.15%, 0.46%) and 1.63% (95%CI 1.11%, 2.13%), respectively. The death risk associated with air pollutants varied across different geographic districts in Beijing. We found spatially varied adverse effects of air pollution on cardiovascular deaths in Beijing. But there was insufficient evidence to show the significant spatial heterogeneity in mortality effects of PM10 and NO2 in this study.
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| 2. |
- Li, Wenjing, et al.
(författare)
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The spatial variation in the effects of air pollution on cardiovascular mortality in Beijing, China
- 2018
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Ingår i: Journal of Exposure Science and Environmental Epidemiology. - : Nature Publishing Group. - 1559-0631 .- 1559-064X. ; 28:3, s. 297-304
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Tidskriftsartikel (refereegranskat)abstract
- Owing to lack of data from multiple air quality monitoring stations, studies about spatial association between concentrations of ambient pollutants and mortality in China are rare. To investigate the spatial variation of association between concentrations of particulate matter less than 10 mu m in aerodynamic diameter (PM10), nitrogen dioxide (NO2) and carbon monoxide (CO) and cardiovascular mortality in Beijing, China, we collected data including daily deaths, concentrations of PM10, NO2 and CO, and meteorological factors from 1 January 2009 to 31 December 2010 in all 16 districts of Beijing. Generalized additive model (GAM) and generalized additive mixed model (GAMM) were used to examine the citywide and district-specific effects of PM10, NO2 and CO on cardiovascular mortality. The citywide effect derived from GAMM was lower than that derived from GAM, and the strongest effects were identified for 2-day moving average lag 0-1. The interquartile increases in concentrations of PM10, NO2 and CO were associated with 2.46 (95% confidence interval (CI), 1.22-3.72), 4.11 (95% CI, 2.82-5.42) and 2.23 (95% CI, 1.14-3.33) percentage increases in daily cardiovascular mortality by GAMM, respectively. The relative risk of each district compared with reference district was generally statistically significant. The death risk associated with air pollutants varies across different geographic districts in Beijing. The data indicate that the risk is high in suburban areas and rural counties. We found significant and spatially varied adverse effects of air pollution on cardiovascular deaths across the rural and urban areas in Beijing.
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| 3. |
- Luo, Kai, et al.
(författare)
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Acute Effects of Nitrogen Dioxide on Cardiovascular Mortality in Beijing : An Exploration of Spatial Heterogeneity and the District-specific Predictors
- 2016
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Ingår i: Scientific Reports. - London, United Kingdom : Nature Publishing Group. - 2045-2322. ; 6:2
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Tidskriftsartikel (refereegranskat)abstract
- The exploration of spatial variation and predictors of the effects of nitrogen dioxide (NO2) on fatal health outcomes is still sparse. In a multilevel case-crossover study in Beijing, China, we used mixed Cox proportional hazard model to examine the citywide effects and conditional logistic regression to evaluate the district-specific effects of NO2 on cardiovascular mortality. District-specific predictors that could be related to the spatial pattern of NO2 effects were examined by robust regression models. We found that a 10 μg/m(3) increase in daily mean NO2 concentration was associated with a 1.89% [95% confidence interval (CI): 1.33-2.45%], 2.07% (95% CI: 1.23-2.91%) and 1.95% (95% CI: 1.16-2.72%) increase in daily total cardiovascular (lag03), cerebrovascular (lag03) and ischemic heart disease (lag02) mortality, respectively. For spatial variation of NO2 effects across 16 districts, significant effects were only observed in 5, 4 and 2 districts for the above three outcomes, respectively. Generally, NO2 was likely having greater adverse effects on districts with larger population, higher consumption of coal and more civilian vehicles. Our results suggested independent and spatially varied effects of NO2 on total and subcategory cardiovascular mortalities. The identification of districts with higher risk can provide important insights for reducing NO2 related health hazards.
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| 4. |
- Luo, Kai, et al.
(författare)
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Ambient Fine Particulate Matter Exposure and Risk of Cardiovascular Mortality : Adjustment of the Meteorological Factors
- 2016
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Ingår i: International Journal of Environmental Research and Public Health. - Basel : MDPI AG. - 1661-7827 .- 1660-4601. ; 13:11
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Tidskriftsartikel (refereegranskat)abstract
- Few studies have explicitly explored the impacts of the extensive adjustment (with a lag period of more than one week) of temperature and humidity on the association between ambient fine particulate matter (PM2.5) and cardiovascular mortality. In a time stratified case-crossover study, we used a distributed lag nonlinear model to assess the impacts of extensive adjustments of temperature and humidity for longer lag periods (for 7, 14, 21, 28 and 40 days) on effects of PM2.5 on total cardiovascular mortality and mortality of cerebrovascular and ischemic heart disease and corresponding exposure-response relationships in Beijing, China, between 2008 and 2011. Compared with results only controlled for temperature and humidity for 2 days, the estimated effects of PM2.5 were smaller and magnitudes of exposure-response curves were decreased when longer lag periods of temperature and relative humidity were included for adjustments, but these changes varied across subpopulation, with marked decreases occurring in males and the elderly who are more susceptible to PM2.5-related mortalities. Our findings suggest that the adjustment of meteorological factors using lag periods shorter than one week may lead to overestimated effects of PM2.5. The associations of PM2.5 with cardiovascular mortality in susceptible populations were more sensitive to further adjustments for temperature and relative humidity.
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| 5. |
- Fang, Xin, et al.
(författare)
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Bayesian model averaging method for evaluating associations between air pollution and respiratory mortality : a time-series study
- 2016
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Ingår i: BMJ Open. - London, England : BMJ Publishing Group Ltd. - 2044-6055. ; 6:8
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Tidskriftsartikel (refereegranskat)abstract
- Objective: To demonstrate an application of Bayesian model averaging (BMA) with generalised additive mixed models (GAMM) and provide a novel modelling technique to assess the association between inhalable coarse particles (PM10) and respiratory mortality in time-series studies.Design: A time-series study using regional death registry between 2009 and 2010.Setting: 8 districts in a large metropolitan area in Northern China.Participants: 9559 permanent residents of the 8 districts who died of respiratory diseases between 2009 and 2010.Main outcome measures: Per cent increase in daily respiratory mortality rate (MR) per interquartile range (IQR) increase of PM10 concentration and corresponding 95% confidence interval (CI) in single-pollutant and multipollutant (including NOx, CO) models.Results: The Bayesian model averaged GAMM (GAMM+ BMA) and the optimal GAMM of PM10, multipollutants and principal components (PCs) of multipollutants showed comparable results for the effect of PM10 on daily respiratory MR, that is, one IQR increase in PM10 concentration corresponded to 1.38% vs 1.39%, 1.81% vs 1.83% and 0.87% vs 0.88% increase, respectively, in daily respiratory MR. However, GAMM+ BMA gave slightly but noticeable wider CIs for the single-pollutant model (-1.09 to 4.28 vs -1.08 to 3.93) and the PCs-based model (-2.23 to 4.07 vs -2.03 vs 3.88). The CIs of the multiple-pollutant model from two methods are similar, that is, -1.12 to 4.85 versus -1.11 versus 4.83.Conclusions: The BMA method may represent a useful tool for modelling uncertainty in time-series studies when evaluating the effect of air pollution on fatal health outcomes.
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| 6. |
- He, Yan, et al.
(författare)
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Discovering Optimal Triplets for Assessing the Uncertainties of Satellite-Derived Evapotranspiration Products
- 2023
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Ingår i: Remote Sensing. - 2072-4292. ; 15:13
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Tidskriftsartikel (refereegranskat)abstract
- Information relating to errors in evapotranspiration (ET) products, including satellite-derived ET products, is critical to their application but often challenging to obtain, with a limited number of flux towers available for the sufficient validation of measurements. Triple collocation (TC) methods can assess the inherent uncertainties of the above ET products using just three independent variables as a triplet input. However, both the severity with which the variables in the triplet violate the assumptions of zero error correlations and the corresponding impact on the error estimation are unknown. This study proposed a cross-correlation analysis approach to discover the optimal triplet of satellite-derived ET products with regard to providing the most reliable error estimation. All possible triple collocation solutions for the same product were first evaluated by the extended triple collocation (ETC), among which the optimum was selected based on the correlation between ETC-based and in-situ-based error metrics, and correspondingly, a statistic experiment based on ranked triplets demonstrated how the optimal triplet was valid for all pixels of the product. Six popular products (MOD16, PML_V2, GLASS, SSEBop, ERA5, and GLEAM) that were produced between 2003 to 2018 and which cover China’s mainland were chosen for the experiment, in which the error estimates were compared with measurements from 23 in-situ flux towers. The findings suggest that (1) there exists an optimal triplet in which a product as an input of TC with other collocating inputs together violate TC assumptions the least; (2) the error characteristics of the six ET products varied significantly across China, with GLASS performing the best (median error: 0.1 mm/day), followed by GLEAM, ERA5, and MOD16 (median errors below 0.2 mm/day), while PML_V2 and SSEBop had slightly higher median errors (0.24 mm/day and 0.27 mm/day, respectively); and (3) removing seasonal variations in ET signals has a substantial impact on enhancing the accuracy of error estimations.
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| 7. |
- Shah, Suraj, et al.
(författare)
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Evaluating the added value of multi-variable calibration of SWAT with remotely sensed evapotranspiration data for improving hydrological modeling
- 2021
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Ingår i: Journal of Hydrology. - : Elsevier BV. - 0022-1694. ; 603
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Tidskriftsartikel (refereegranskat)abstract
- Hydrological processes in a watershed consist of multiple sub-processes (such as plant growth, evapotranspiration, water yield, and soil–water balance) that have complex interactions. The common practice of calibrating hydrological models against only a single variable (e.g., streamflow) can lead to parameter uncertainty (also known as equifinality), resulting in significant uncertainties in the representation and simulation of sub-processes. As multi-variable calibration can be a potential solution to this issue, we tested the integration of spatially and temporally gridded remotely sensed evapotranspiration (RS-ET) data with the Soil and Water Assessment Tool (SWAT) hydrological model. This approach was intended to reduce equifinality by enhancing related hydrological sub-processes in both space and time rather than improving the evaluation metrics at the streamflow outlet. We further introduced the principle of repeated measure design in the calibration process, where the SWAT was calibrated under two different schemes: Scheme1 (using only streamflow data) and Scheme2 (using both RS-ET and streamflow data). The model's performance was evaluated using the concept of stability at multiple spatial scales (basin outlet, sub-basins, and hydrological response units) and aspects (different model outputs and most sensitive calibrated parameters). The significance of the difference between the stabilities produced by the two schemes was estimated using the Mann–Whitney U test. Testing this approach in Meichuan Basin (China) showed that Scheme2 substantially reduced equifinality for calibrated parameters and model outputs compared to Scheme1. In addition, the model solutions and outputs for Scheme2 were significantly different from Scheme1. Our results demonstrate the added value of using increasingly available open-access RS-ET data for improving hydrological model calibration.
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