Temporal changes in extreme high temperature, heat waves and relevant disasters in Nanjing metropolitan region, China

Liu, Guilin; Zhang, Luocheng; He, Bin; Xuan, Jin; Qian, Zhang; Razafindrabe, Bam H. N.; You, Hongjian

doi:10.1007/s11069-014-1556-y

Cited by 37 publications

(14 citation statements)

References 36 publications

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“…As the EHF_HWD significantly increased in Romania over the 55‐year period considered, this could have a serious impact on human health and mortality. Moreover, it was found that the maximum duration of a HW had a major impact on water quality, which can induce indirect effects on human health and ecosystems (D'Ippoliti et al, ; Liu et al, ; Kim et al, ).…”

Section: Resultsmentioning

confidence: 99%

“…Even though there is no simple relationship between air temperature and morbidity and mortality, high correlation between certain extreme temperatures and mortality has been demonstrated worldwide (Knowlton et al, 2009;Barnett et al, 2012). HWs cause more deaths all over the world than any other natural hazards (Unkaševic and Tošic, 2009;D'Ippoliti et al, 2010;Peterson et al, 2013;Shaposhnikov et al, 2014;Liu et al, 2015;Nairn and Fawcett, 2015;Kim et al, 2016;Chen et al, 2017). Some previous studies showed an increase in the number of deaths during HWs: between 3.0 and 7.8% in the United States of America (Medina-Ramón and Schwartz, 2007;Anderson and Bell, 2009;Peng et al, 2011), 21.8% in the Mediterranean areas (D'Ippoliti et al, 2010), 16.5% in Spain , 5% in China (Ma et al, 2015).…”

Section: Introductionmentioning

confidence: 99%

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Recent changes in heat waves and cold waves detected based on excess heat factor and excess cold factor in Romania

Piticar

Croitoru

Ciupertea

et al. 2017

Intl Journal of Climatology

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In this paper, we investigated changes in heat and cold waves in Romania over the period 1961–2015 by employing a new and superior approach. It consists in using excess heat factor to identify heat waves and excess cold factor to identify cold waves. Five indices were calculated and then analysed for both heat waves and cold waves resulting in a set of ten indices. Indices for heat waves were analysed for the extended summer season (May–September), whereas those for cold waves were assessed for the extended winter (November–March). The intensity threshold was set to be equal or above the 90th percentile for heat waves, and equal or below the 10th percentile for cold waves, while the duration threshold for both heat and cold waves was of at least three consecutive days. For a better comparison with other studies conducted worldwide, and to get more information from the data sets, the percentile thresholds for heat and cold waves identification were calculated based on three reference periods: 1961–1990, 1971–2000, and 1981–2010. Trends were calculated using ordinary least square method, whereas statistical significance was assessed by the t‐test. The main results indicated that changes are more substantial in the case of indices calculated based on excess heat factor compared to those based on excess cold factor, suggesting that the warming process is more reflected in heat waves rather than in cold waves. Thus, heat waves became more frequent, longer, and more intense, while cold waves became less frequent, but more intense. When the reference period for percentile threshold calculation was changed from the earliest to the most recent ones, the frequency of increasing and significant increasing trends decreased for some of the heat wave indices, while for the cold wave indices the significant downward trends increased.

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Section: Resultsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Recent changes in heat waves and cold waves detected based on excess heat factor and excess cold factor in Romania

Piticar

Croitoru

Ciupertea

et al. 2017

Intl Journal of Climatology

View full text Add to dashboard Cite

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“…As electricity is the primary energy source for indoor temperature conditioning, for which air-conditioners and electric fans are used, this would in turn lead to a higher demand for electricity. Since temperature fluctuation could cause diverse consequences on electricity through multiple social and economic characters and different temperature patterns may present different regional estimates (Bessec and Fouquau 2008, Fan et al 2014, Hekkenberg et al 2009, Istiaque and Khan 2018, Jovanović et al 2015, Liu et al 2014, Miller et al 2008, Sun et al 2017. However, many questions remain to be explored in China.…”

Section: Introductionmentioning

confidence: 99%

Climate impacts: temperature and electricity consumption

Zhang

Liao

2019

Nat Hazards

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One of the aspects of climate change is temperature rise. Temperature rise or fluctuations affect human economic activities and electricity consumption. This paper estimates the changes in electricity consumption due to temperature fluctuation at the county scale in rural China. By using the statistics of counties from 2006 to 2015 in a fixed-effect panel model, the results indicate that a one-degree temperature increase in summer days may lead to 0.015% more electricity consumption per capita, and this correlation may be weaker as income increases. Moreover, a one-degree temperature decrease in winter days may lead to 0.002% more electricity consumption. The northern region may consume 0.021% more electricity than the southern region when facing the same temperature drop. Overall, the effect of temperature on electricity consumption is modest, particularly for a drop in temperature, but the usage of other types of energy may increase to adapt to the cold.

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“…The existing literature has used various temperature indicators, i.e., mean temperature, maximum temperature, minimum temperature, and diurnal temperature range Lee 2014;Liu et al 2015) to mitigate the effects of climate change on public health in short-and long-term trends world widely. An increased health risk is observed for the heating days (Huang et al 2012).…”

Section: Introductionmentioning

confidence: 99%

Assessing the possible impacts of temperature change on air quality and public health in Beijing, 2008–2012

et al. 2015

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Understanding the impact of temperature fluctuations on air quality and public health has gained popularity among environmental and epidemiological researchers. Potentially, increase and decrease in temperature between neighboring days have increased the environmental and health risk worldwide. Based on ordinary least-squares method, this paper aims to examine the impact of temperature fluctuations on air quality index (AQI) and respiratory health outcomes (RHOs) during 2008-2012 in Beijing. Our results show that a drop of more than 3°C results in the increased impact on AQI and RHO in the heating period. At the same time, a raise of more than 3°C results in the similar increased impact on AQI in the whole study period and heating period. Furthermore, for a raise of more than 3°C, a larger impact on RHO is observed in the heating period compared with the whole study period. Additionally, an increase in temperature also results in the increased influence of health risk on females during the heating period. Our results suggest that the air quality and public health in Beijing are significantly influenced by decrease and increase in temperature in the heating period.

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Temporal changes in extreme high temperature, heat waves and relevant disasters in Nanjing metropolitan region, China

Cited by 37 publications

References 36 publications

Recent changes in heat waves and cold waves detected based on excess heat factor and excess cold factor in Romania

Recent changes in heat waves and cold waves detected based on excess heat factor and excess cold factor in Romania

Climate impacts: temperature and electricity consumption

Assessing the possible impacts of temperature change on air quality and public health in Beijing, 2008–2012

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