We used daily maximum temperature data（1986–2100） from the COSMO-CLM（COnsortium for Small-scale MOdeling in CLimate Mode） regional climate model and the population statistics for China in 2010 to determine the fr...We used daily maximum temperature data（1986–2100） from the COSMO-CLM（COnsortium for Small-scale MOdeling in CLimate Mode） regional climate model and the population statistics for China in 2010 to determine the frequency, intensity, coverage, and population exposure of extreme maximum temperature events（EMTEs） with the intensity–area–duration method. Between 1986 and 2005（reference period）, the frequency, intensity, and coverage of EMTEs are 1330–1680 times yr^–1, 31.4–33.3℃, and 1.76–3.88 million km^2, respectively. The center of the most severe EMTEs is located in central China and 179.5–392.8 million people are exposed to EMTEs annually. Relative to 1986–2005, the frequency, intensity, and coverage of EMTEs increase by 1.13–6.84, 0.32–1.50, and15.98%–30.68%, respectively, under 1.5℃ warming; under 2.0℃ warming, the increases are 1.73–12.48, 0.64–2.76,and 31.96%–50.00%, respectively. It is possible that both the intensity and coverage of future EMTEs could exceed the most severe EMTEs currently observed. Two new centers of EMTEs are projected to develop under 1.5℃ warming, one in North China and the other in Southwest China. Under 2.0℃ warming, a fourth EMTE center is projected to develop in Northwest China. Under 1.5 and 2.0℃ warming, population exposure is projected to increase by 23.2%–39.2% and 26.6%–48%, respectively. From a regional perspective, population exposure is expected to increase most rapidly in Southwest China. A greater proportion of the population in North, Northeast, and Northwest China will be exposed to EMTEs under 2.0℃ warming. The results show that a warming world will lead to increases in the intensity, frequency, and coverage of EMTEs. Warming of 2.0℃ will lead to both more severe EMTEs and the exposure of more people to EMTEs. Given the probability of the increased occurrence of more severe EMTEs than in the past, it is vitally important to China that the global temperature increase is limited within 1.5℃.展开更多
PM_（2.5）, formally defined as particulate matter with diameter less than 2.5 μm, is one of most harmful air pollutants threatening human health. Numerous epidemiological studies have shown that both short-term and ...PM_（2.5）, formally defined as particulate matter with diameter less than 2.5 μm, is one of most harmful air pollutants threatening human health. Numerous epidemiological studies have shown that both short-term and long-term exposures to PM_（2.5） are strongly linked with respiratory diseases. In this study, various types of spatio-temporal data were collected and used to estimate the spatio-temporal variation of PM2.5 exposure in Beijing in 2014. The seasonal and daily variation of the population-weighted exposure level（PWEL） in 2014 was estimated and compared. The results show that the population exposure to ambient air pollution differs significantly in the four seasons, and the exposure levels in winter and spring are notably higher than the other seasons; the exposure level changes greatly from North to South, and each sub-district maintains similarity to neighboring sub-districts.展开更多
基金Supported by the National Natural Science Foundation of China(41571494,41661144027,and 41671211)
文摘We used daily maximum temperature data（1986–2100） from the COSMO-CLM（COnsortium for Small-scale MOdeling in CLimate Mode） regional climate model and the population statistics for China in 2010 to determine the frequency, intensity, coverage, and population exposure of extreme maximum temperature events（EMTEs） with the intensity–area–duration method. Between 1986 and 2005（reference period）, the frequency, intensity, and coverage of EMTEs are 1330–1680 times yr^–1, 31.4–33.3℃, and 1.76–3.88 million km^2, respectively. The center of the most severe EMTEs is located in central China and 179.5–392.8 million people are exposed to EMTEs annually. Relative to 1986–2005, the frequency, intensity, and coverage of EMTEs increase by 1.13–6.84, 0.32–1.50, and15.98%–30.68%, respectively, under 1.5℃ warming; under 2.0℃ warming, the increases are 1.73–12.48, 0.64–2.76,and 31.96%–50.00%, respectively. It is possible that both the intensity and coverage of future EMTEs could exceed the most severe EMTEs currently observed. Two new centers of EMTEs are projected to develop under 1.5℃ warming, one in North China and the other in Southwest China. Under 2.0℃ warming, a fourth EMTE center is projected to develop in Northwest China. Under 1.5 and 2.0℃ warming, population exposure is projected to increase by 23.2%–39.2% and 26.6%–48%, respectively. From a regional perspective, population exposure is expected to increase most rapidly in Southwest China. A greater proportion of the population in North, Northeast, and Northwest China will be exposed to EMTEs under 2.0℃ warming. The results show that a warming world will lead to increases in the intensity, frequency, and coverage of EMTEs. Warming of 2.0℃ will lead to both more severe EMTEs and the exposure of more people to EMTEs. Given the probability of the increased occurrence of more severe EMTEs than in the past, it is vitally important to China that the global temperature increase is limited within 1.5℃.
文摘PM_（2.5）, formally defined as particulate matter with diameter less than 2.5 μm, is one of most harmful air pollutants threatening human health. Numerous epidemiological studies have shown that both short-term and long-term exposures to PM_（2.5） are strongly linked with respiratory diseases. In this study, various types of spatio-temporal data were collected and used to estimate the spatio-temporal variation of PM2.5 exposure in Beijing in 2014. The seasonal and daily variation of the population-weighted exposure level（PWEL） in 2014 was estimated and compared. The results show that the population exposure to ambient air pollution differs significantly in the four seasons, and the exposure levels in winter and spring are notably higher than the other seasons; the exposure level changes greatly from North to South, and each sub-district maintains similarity to neighboring sub-districts.
