Projected changes in population exposure to extreme heat in China under a RCP8.5 scenario

doi:10.1007/s11442-018-1550-5

Abstract

Abstract:

Overall population exposure is measured by multiplying the annual average number of extremely hot days by the number of people exposed to the resultant heat. Extreme heat is also subdivided into high temperature (HT) and extremely high temperature (EHT) in cases where daily maximum temperature exceeds 35℃ and 40℃, respectively. Chinese population exposure to HT and EHT over four periods in the future (i.e., 2021-2040, 2041-2060, 2060-2081 and 2081-2100) were projected at the grid cell level in this study using daily maximum temperature based on an ensemble mean of 21 global climate models under the RCP8.5 scenario and with a population projection based on the A2r socio-economic scenario. The relative importance of population and climate as drivers of population exposure was evaluated at different spatial scales including national and meteorological geographical divisions. Results show that, compared with population exposure seen during 1981-2010, the base period, exposure to HT in China is likely to increase by 1.3, 2.0, 3.6, and 5.9 times, respectively, over the four periods, while concomitant exposure to EHT is likely to increase by 2.0, 8.3, 24.2, and 82.7 times, respectively. Data show that population exposure to HT is likely to increase significantly in Jianghuai region, Southwest China and Jianghan region, in particular in North China, Huanghuai region, South China and Jiangnan region. Population exposure to EHT is also likely to increase significantly in Southwest China and Jianghan region, especially in North China, Huanghuai, Jiangnan, and Jianghuai regions. Results reveal that climate is the most important factor driving the level of population exposure in Huanghuai, Jianghuai, Jianghan, and Jiangnan regions, as well as in South and Southwest China, followed by the interactive effect between population and climate. Data show that the climatic factor is also most significant at the national level, followed by the interactive effect between population and climate. The rate of contribution of climate to national-level projected changes in exposure is likely to decrease gradually from ca. 70% to ca. 60%, while the rate of contribution of concurrent changes in both population and climate is likely to increase gradually from ca. 20% to ca. 40% over the four future periods in this analysis.

Key words: RCP8.5 scenario, population exposure, high temperature, extremely high temperature, driving forces

Dapeng HUANG, Lei ZHANG, Ge GAO, Shao SUN. Projected changes in population exposure to extreme heat in China under a RCP8.5 scenario[J].Journal of Geographical Sciences, 2018, 28(10): 1371-1384.

Figures/Tables 10

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Model name / Country
ACCESS1-0 / Australia	CSIRO-MK3-6-0 / Australia	MIROC-ESM / Japan
BCC-CSM1-1 / China	GFDL-CM3 / USA	MIROC-ESM-CHEM / Japan
BNU-ESM / China	GFDL-ESM2G / USA	MIROC5 / Japan
CanESM2 / Canada	GFDL-ESM2M / USA	MPI-ESM-LR / Germany
CCSM4 / USA	INMCM4 / Russia	MPI-ESM-MR / Germany
CESM1-BGC / USA	IPSL-CM5A-LR / France	MRI-CGCM3 / Japan
CNRM-CM5 / France	IPSL-CM5A-MR / France	NorESM1-M / Norway

Change of population exposure	HT (≥35℃)			EHT (≥40℃)
Change of population exposure	Population factor	Climatic factor	Interactive effect between climate and population	Population factor	Climatic factor	Interactive effect between climate and population
Between 2021 and 2040 relative to 1981-2010	13.1	67.6	19.4	7.7	68.9	23.4
Between 2041 and 2060 relative to 2021-2040	2.9	67.6	29.5	0.9	67.1	32.1
Between 2061 and 2080 relative to 2041-2060	1.5	66.3	32.2	0.3	65.4	34.4
Between 2081 and 2100 relative to 2061-2080	1.8	58.4	39.9	0.1	59.9	40.0

Change in population exposure	Division	HT (≥35℃)			EHT (≥40℃)
Change in population exposure	Division	Population factor	Climatic factor	Interactive effect between climate and population	Population factor	Climatic factor	Interactive effect between climate and population
Between 2021 and 2040 relative to between 1981 and 2010	NC	30.1	40.0	29.9	19.0	45.6	35.5
	HH	13.5	63.4	23.1	8.6	66.9	24.5
	JHuai	11.1	68.3	20.6	3.4	75.7	20.9
	JHan	9.0	72.1	18.9	2.4	77.8	19.8
	JN	9.7	74.6	15.7	1.9	78.6	19.5
	SC	3.9	78.9	17.2	-12.7	152.6	-39.9
	SW	2.5	92.9	4.6	0.3	96.4	0.3
Between 2041 and 2060 relative to between 2021 and 2040	NC	8.7	39.7	51.7	2.6	43.5	53.9
	HH	2.8	62.3	34.9	0.5	65.8	33.7
	JHuai	2.0	67.9	30.1	0.3	71.7	28.0
	JHan	1.7	73.0	25.3	0.1	74.0	25.9
	JN	1.3	77.7	21.1	0.1	76.0	23.9
	SC	0.3	76.2	23.5	-0.4	125.1	-24.7
	SW	-2.5	106.5	-4.0	-0.4	107.6	-7.1
Between 2061 and 2080 relative to between 2041 and 2060	NC	4.7	36.6	58.7	0.7	40.0	59.2
	HH	14.6	58.8	39.8	0.1	63.2	36.6
	JHuai	1.1	64.3	34.6	0.1	67.6	32.3
	JHan	1.1	71.3	27.6	0.0	71.2	28.8
	JN	1.0	77.2	21.8	0.1	75.4	24.6
	SC	0.2	71.7	28.1	0.0	92.8	7.2
	SW	-0.9	108.0	-7.0	-0.1	106.7	-6.6
Between 2081 and 2100 relative to between 2061 and 2080	NC	3.6	31.8	64.6	0.3	35.3	64.4
	HH	1.7	48.7	49.6	0.1	56.2	43.7
	JHuai	1.5	54.3	44.2	0.1	61.3	38.6
	JHan	2.0	61.2	36.9	0.0	65.5	34.5
	JN	2.1	66.4	31.5	0.1	69.0	30.9
	SC	0.4	62.1	37.6	0.0	80.9	19.1
	SW	0.4	99.9	-0.3	0.0	100.6	-0.6