Will climate change make Chinese people more comfortable? A scenario analysis based on the weather preference index

Abstract

Assessing the climate change impact (CCI) on weather conditions is important for addressing climate change and promoting sustainable development. This study used a weather preference index (WPI) as an indicator to evaluate the CCI on weather conditions in China under different scenarios from 2025 to 2100. First, we analyzed the change in the WPI in China from 1971 to 2013. Then, we estimated the trends in the WPI in China from 2025 to 2100 under different representative concentration pathways (RCPs) based on global climate models. We found that China’s weather conditions improved from 1971 to 2013, as the national average WPI increased from 1.34 to 1.59 with a change rate of 0.03 per decade (0.03/10 a). Under all climate change scenarios, the weather conditions in China will deteriorate. The change rates of the WPI will be −0.19/10 a ∼ − 0.01/10 a. The number of people experiencing deteriorated weather conditions will be 0.71 billion ∼ 1.22 billion, accounting for 53.28% ∼ 91.58% of the total population in China. We also found that the area of the regions with deteriorated weather conditions under all three climate change scenarios will be 2.34 million km2, accounting for 24.31% of China’s total land area. At the same time, as the emissions concentrations increase from RCP2.6 to RCP8.5, the area of the regions with severely deteriorated weather conditions in China will increase from 0 to 3.27 million km2. Therefore, we suggest that China needs to implement effective measures to address climate change in the future and focus on the mitigation of and adaptation to climate change in regions with deteriorated weather conditions.

Impact of urban expansion on grain production in the Japan Sea Rim region

“…First, we used the average value of MODIS NPP for 2000-2020 as the benchmark, and assumed that the NPP of each grid was constant to assess the impact originating from urban expansion, which could ignore the fact that the NPP of each grid was actually changing. Second, we simulated the impact of future urban expansion on grain production but did not consider the possible impact of future climate change on grain production (He et al, 2015;Fang et al, 2020). Third, we did not consider relevant policies, such as land management policies for protecting croplands and corresponding policies for food security, when assessing the impacts of urban expansion on grain production.…”

Investigating Drought Events and Their Consequences in Wildfires: An Application in China

“…It relies on two key assumptions: (1) precipitation variability is significantly greater than that of other variables (e.g., temperature and PET), and (2) the other variables exhibit stationarity, meaning they have no temporal trend [19]. However, it is worth noting that the climate in China has not only experienced a higher rate of warming in recent decades compared to the global trend [20,21], but it is also projected to worsen under future emission scenarios [22]. To address the combined effects of precipitation and temperature variability in drought assessment, the Standardized Precipitation Evapotranspiration Index (SPEI) is utilized.…”

Changes in the Geographical Distributions of Global Human Settlements

“…Therefore, research on the distribution of human settlements and their relationships with the environment and social economy is particularly important. The majority of related studies generally focus on the spatiotemporal variation characteristics of human settlement areas (Cohen et al, 2004;Angel et al, 2011;Gong et al, 2019); the environmental problems caused by the expansion of human settlements (Mcdonald et al, 2008;Wittemyer et al, 2008;Seto et al, 2011;Hutyra et al, 2011;Seto et al, 2012;Haddad et al, 2015;Ibisch et al, 2017); natural disasters impacting human settlements near the sea (Nicholls et al, 1996;Small et al, 2003;Abel et al, 2011;Strauss et al, 2012;Addo et al, 2013;Haer et al, 2013;Hauer et al, 2016;Hauer et al, 2019;Antonioli et al, 2020;Baisero et al, 2020); the influence of climate on the distribution of human settlements (Gray et al, 2012;Hunter et al, 2013;Nawrotzki et al, 2015;Egan et al, 2016;Leyk et al, 2017;Fang et al, 2020); and the prediction and analysis of human settlement areas (Angel et al, 2011;Seto et al, 2012).…”