Editorial

9 pages, 222 KiB

Open AccessEditorial

Sustainability with Changing Climate and Extremes

by Shaofei Jin, Jia Yang and Xiaodong Yan

Sustainability 2022, 14(19), 11830; https://doi.org/10.3390/su141911830 - 20 Sep 2022

Viewed by 886

Climate change and extreme events are receiving increasingly more attention in the global sustainable development sphere [...] Full article

(This article belongs to the Special Issue Sustainability with Changing Climate and Extremes)

Research

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13 pages, 8306 KiB

Open AccessArticle

Impact of Extreme Heatwaves on Population Exposure in China Due to Additional Warming

by Leibin Wang, Robert V. Rohli, Qigen Lin, Shaofei Jin and Xiaodong Yan

Sustainability 2022, 14(18), 11458; https://doi.org/10.3390/su141811458 - 13 Sep 2022

Cited by 5 | Viewed by 1386

Abstract

Extreme heatwaves are among the most important climate-related disasters affecting public health. Assessing heatwave-related population exposures under different warming scenarios is critical for climate change adaptation. Here, the Coupled Model Intercomparison Project phase 6 (CMIP6) multi-model ensemble output results are applied over several [...] Read more.

Extreme heatwaves are among the most important climate-related disasters affecting public health. Assessing heatwave-related population exposures under different warming scenarios is critical for climate change adaptation. Here, the Coupled Model Intercomparison Project phase 6 (CMIP6) multi-model ensemble output results are applied over several warming periods in the Intergovernmental Panel on Climate Change AR6 report, to estimate China’s future heatwave population exposure under 1.5 °C and 2.0 °C warming scenarios. Our results show a significant increase in projected future annual heatwave days (HD) under both scenarios. With an additional temperature increase of 0.5 °C to 2.0 °C of warming, by mid-century an additional 20.15 percent increase in annual HD would occur, over 1.5 °C warming. If the climate warmed from 1.5 °C to 2.0 °C by mid-century, population exposure would increase by an additional 40.6 percent. Among the three influencing elements that cause the changes in population exposure related to heatwaves in China–climate, population, and interaction (e.g., as urbanization affects population redistribution)–climate plays the dominant role in different warming scenarios (relative contribution exceeds 70 percent). Therefore, considering the future heat risks, humanity benefits from a 0.5 °C reduction in warming, particularly in eastern China. This conclusion may provide helpful insights for developing mitigation strategies for climate change. Full article

(This article belongs to the Special Issue Sustainability with Changing Climate and Extremes)

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25 pages, 5662 KiB

Open AccessArticle

Future Drought and Flood Vulnerability and Risk Prediction of China’s Agroecosystem under Climate Change

by Jiangnan Li, Jieming Chou, Weixing Zhao, Yuan Xu, Yidan Hao and Yuanmeng Li

Sustainability 2022, 14(16), 10069; https://doi.org/10.3390/su141610069 - 14 Aug 2022

Cited by 7 | Viewed by 1993

Abstract

Droughts and floods cause serious damage to agricultural production and ecosystems, and system-based vulnerability and risk prediction are the main tools used to address droughts and floods. This paper takes the agroecosystem as the research object, uses the vulnerability model based on “sensitivity–exposure–adaptability” [...] Read more.

Droughts and floods cause serious damage to agricultural production and ecosystems, and system-based vulnerability and risk prediction are the main tools used to address droughts and floods. This paper takes the agroecosystem as the research object, uses the vulnerability model based on “sensitivity–exposure–adaptability” and “vulnerability-risk, source-risk receptor” drought and flood risk models, and establishes multi-index prediction systems covering climate change, population, agricultural technology, economy, ecology, and other factors. Using a combination of AHP and the entropy weighting method, we predict the vulnerability and risk of droughts and floods in China’s agroecosystem under the SSP1-2.6, SSP2-4.5, and SSP5-8.5 scenarios from 2020 to 2050. The results show that as the scenario changes from SSP1-2.6 to SSP5-8.5 in turn, drought and flood vulnerability intensify, and the drought or flood vulnerability area expands to southern China. At the same time, future drought and flood risk patterns present the characteristics of high risk in Northeast, North, Central, and Southwest China. Therefore, major grain-producing provinces such as Heilongjiang and Henan need to do a good job of preventing and responding to agroecosystem drought and flood risks by strengthening regional structural and nonstructural measures. Full article

(This article belongs to the Special Issue Sustainability with Changing Climate and Extremes)

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14 pages, 3531 KiB

Open AccessArticle

Spatiotemporal Evolution and Socioeconomic Impacts of Rainstorms and Droughts in Contiguous Poverty-Stricken Areas of China

by Aiwei Li, Shuyuan Gao, Miaoni Gao, Xueqing Wang, Hongling Zhang, Tong Jiang and Jing Yang

Sustainability 2022, 14(16), 9927; https://doi.org/10.3390/su14169927 - 11 Aug 2022

Cited by 1 | Viewed by 1305

Abstract

To consolidate the achievements in the elimination of absolute poverty in China and prevent rural populations from returning to poverty as a result of meteorological disasters, this study analyzed the spatiotemporal characteristics of rainstorms and droughts and their socioeconomic impacts on China’s contiguous [...] Read more.

To consolidate the achievements in the elimination of absolute poverty in China and prevent rural populations from returning to poverty as a result of meteorological disasters, this study analyzed the spatiotemporal characteristics of rainstorms and droughts and their socioeconomic impacts on China’s contiguous poverty-stricken areas (CPSAs) from 1984 to 2019. The annual number of rainstorms and drought days in CPSAs of China reached approximately 1.9 days/year and 44.6 days/year, respectively. It gradually decreased from southeast to northwest. Rainstorms showed a significant increasing trend of 0.075 days/decade, while there is no significant trend in drought days. Due to rainstorms and droughts, the average annual number of people affected and direct economic losses in CPSAs reached 34 million people/year and 29 billion Chinese yuan/year, accounting for 22.9% and 12.6% of China’s total amounts, respectively. The average annual loss rate due to disasters in this region reached 1.6%, which is 0.6% higher than the national level. Furthermore, the distinct features and socioeconomic impacts of rainstorms and droughts were identified on the southeastern and northwestern sides of the population density line (PDL) along Tengchong-Aihui in China. Droughts have often impacted the regions located along the PDL, while rainstorms and droughts have occurred more frequently in the regions to the southeast of the PDL than in the regions to the northwest of the PDL. As a result, the affected population and direct economic losses due to rainstorms and droughts in the regions to the southeast of the PDL were 8.8 and 9.2 times and 3.3 and 7.4 times higher, respectively, than those in the regions on the other side of the PDL. Although the losses were greater, the disaster resistance capabilities were significantly improved in these regions. In contrast, the regions to the northwest side of the PDL exhibited a significant increasing trend in losses with a relatively low disaster resistance capabilities. This study revealed that it is necessary to improve the capability of meteorological disaster prevention and reduction in China’s CPSAs, especially in the regions to the west of the PDL, which could further contribute to the realization of United Nations Sustainable Development Goals. Full article

(This article belongs to the Special Issue Sustainability with Changing Climate and Extremes)

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14 pages, 2713 KiB

Open AccessArticle

Human Resource Allocation in the State-Owned Forest Farm of China for the Changing Climate

by Xiaofang Deng, Junkui Li, Lijuan Su, Shan Zhao and Shaofei Jin

Sustainability 2022, 14(15), 9667; https://doi.org/10.3390/su14159667 - 05 Aug 2022

Cited by 3 | Viewed by 1137

Abstract

Global climate change has become a hot topic in today’s international political, economic, environmental and diplomatic arenas. China has implemented a series of strategies, measures and actions to cope with climate change, which has promoted industrial transformation and human resource adjustment in China’s [...] Read more.

Global climate change has become a hot topic in today’s international political, economic, environmental and diplomatic arenas. China has implemented a series of strategies, measures and actions to cope with climate change, which has promoted industrial transformation and human resource adjustment in China’s state-owned forest areas. However, little is known about the role of current human resource allocation in adaptation to climate change in the state-owned forest farm of China. To address these gaps, this study calculated the current situation of human resource structure and the contribution rate of three industries to the allocation of human resources and the evaluation model of coordinated fitness to the climate changes in key state-owned forest farms. The results show that: (1) The current situation of talent in key state-owned forest areas shows a shortage of total amount, a shortage of high-level and highly educated talents, and aging of talents. (2) The coefficient of structural deviation increased and the coefficient of structural-change synergy kept decreasing, indicating that the coordination between human resource allocation and industrial structure in key state-owned forest areas nowadays is only at the intermediate level of synergistic fitness. The paper highlights the trained-professional human resource and the industrial structure changes in the context of climate change as the main limited factors for the key state-owned forest farms of China. Increasing the education investment for climate change and the economic income for the employees are suggested to be promoted for policy makers in future. Full article

(This article belongs to the Special Issue Sustainability with Changing Climate and Extremes)

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18 pages, 5416 KiB

Open AccessArticle

Effects of Future Climate Change on Citrus Quality and Yield in China

by Shuangshuang Wang, Wenqiang Xie and Xiaodong Yan

Sustainability 2022, 14(15), 9366; https://doi.org/10.3390/su14159366 - 30 Jul 2022

Cited by 6 | Viewed by 2316

Abstract

As the world’s most widely cultivated fruit, citrus in China is increasingly suffering from ongoing climate change, which affects the sustainability of agricultural systems and social economy. In this study, we linked climate factors to citrus quality and yield and established projection models [...] Read more.

As the world’s most widely cultivated fruit, citrus in China is increasingly suffering from ongoing climate change, which affects the sustainability of agricultural systems and social economy. In this study, we linked climate factors to citrus quality and yield and established projection models to elucidate the impact of future climate change. Then, we used the ensemble mean of 19 Coupled Model Intercomparison Project 6 (CMIP6) models to project the 2021–2040 and 2041–2060 climate changes relative to the historical baseline 1995–2014 period under different shared socioeconomic pathways scenarios (SSP2-4.5, SSP5-8.5). The results show that the monthly mean diurnal temperature range in July had the greatest influence on quality, and monthly mean temperature in October, monthly mean relative humidity in October, monthly mean minimum temperature in November and monthly mean maximum temperature in September had the greatest influence on yield at the growth and ripening stages. Moreover, the quality and yield of citrus present different characteristics in terms of change in cultivation areas in the future. The quality of Sichuan, Zhejiang and Fujian Provinces in China will become significantly better, however, Hubei, Guangdong and Guangxi Provinces it will become worse. Surprisingly, yield will increase in all plantations due to future suitable climate conditions for citrus growth and ripening. Full article

(This article belongs to the Special Issue Sustainability with Changing Climate and Extremes)

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16 pages, 3914 KiB

Open AccessArticle

The Impact of Rainfall on Urban Human Mobility from Taxi GPS Data

by Peng Guo, Yanling Sun, Qiyi Chen, Junrong Li and Zifei Liu

Sustainability 2022, 14(15), 9355; https://doi.org/10.3390/su14159355 - 30 Jul 2022

Cited by 2 | Viewed by 1495

Abstract

Rainfall severely impacts human mobility in urban areas and creates significant challenges for traffic management and urban planning. There is an urgent need to understand the impact of rainfall on residents’ travels from multiple perspectives. Taxi GPS data contains a large amount of [...] Read more.

Rainfall severely impacts human mobility in urban areas and creates significant challenges for traffic management and urban planning. There is an urgent need to understand the impact of rainfall on residents’ travels from multiple perspectives. Taxi GPS data contains a large amount of spatiotemporal information about human activities and mobility in urban areas. For this study, we selected the central area of Zhuhai as the study area and used taxi data from August 2020 for the investigation. Firstly, we divided the taxi data into four scenarios, i.e., weekdays with and without rainfall and weekends with and without rainfall and analyzed and compared the trip characteristics for the different scenarios. Then, using the traffic analysis zone (TAZ) as the node and taxi flow between TAZs as edges, we constructed a network and compared the network indicators under the different scenarios. Finally, we used the Leiden algorithm to detect communities in different scenarios and compared the network indicators of the communities. The results showed that on days with rainfall, taxi flow and its spatial and temporal distribution pattern changed significantly, which affected transportation supply and demand. These findings may provide useful references for the formulation of urban transport policies that can adapt to different weather conditions. Full article

(This article belongs to the Special Issue Sustainability with Changing Climate and Extremes)

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16 pages, 3858 KiB

Open AccessArticle

Effects of Climate Change on the Climatic Production Potential of Potatoes in Inner Mongolia, China

by Li-Tao Yang, Jun-Fang Zhao, Xiang-Ping Jiang, Sheng Wang, Lin-Hui Li and Hong-Fei Xie

Sustainability 2022, 14(13), 7836; https://doi.org/10.3390/su14137836 - 27 Jun 2022

Cited by 4 | Viewed by 1677

Abstract

Understanding the impacts of regional climate change on crop production will benefit strategic decisions for future agricultural adaptation in China. In this study, the climatic production potential of potato over the past 61 years in Inner Mongolia was simulated based on long-term observed [...] Read more.

Understanding the impacts of regional climate change on crop production will benefit strategic decisions for future agricultural adaptation in China. In this study, the climatic production potential of potato over the past 61 years in Inner Mongolia was simulated based on long-term observed data and the step-by-step correction method. The results show that the annual average potential for potato climatic production in Inner Mongolia is 19,318 kg·hm⁻², fluctuating between the highest value (25,623 kg·hm⁻²) and the lowest value (15,354 kg·hm⁻²). Over the past 61 years, the climatic production potential exhibited an insignificant decreasing trend, with large interannual fluctuation, especially since 2000. The high-value areas of the climatic production potential were mainly located in the central and southern regions. The climatic production potential of potato in most areas showed a decreasing trend. The influence of radiation changes on the potato climatic production potential was not obvious in most areas. The effects of temperature changes on the climatic production potential of potato were mostly negative, and were most obvious in the central and western regions and in the southeastern region. The change in precipitation in most parts of western Inner Mongolia, Hohhot, Chifeng and eastern Xingan League had a positive effect on the climatic production potential of potato. However, the change in precipitation in southern Ulanchabu, eastern Chifeng, Hulunbuir and western and eastern regions had a negative effect on the climatic production potential of potato. The main limiting factor for the climatic production potential of potato in Inner Mongolia is precipitation. Our findings have important implications for local potato production to cope with ongoing climate change in China. Full article

(This article belongs to the Special Issue Sustainability with Changing Climate and Extremes)

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16 pages, 1987 KiB

Open AccessArticle

Inter- and Mixed Cropping of Different Varieties Improves High-Temperature Tolerance during Flowering of Summer Maize

by Shuyan Li, Junfang Zhao, Junling Li, Ruixin Shao, Hongping Li, Wensong Fang, Liting Hu and Tianxue Liu

Sustainability 2022, 14(12), 6993; https://doi.org/10.3390/su14126993 - 08 Jun 2022

Cited by 3 | Viewed by 1331

Abstract

Global warming increases the risk of high-temperature injury to maize. Inter- and mixed-cropping of maize varieties with different genotypes is one way to effectively alleviate the high-temperature injury during the flowering period. However, the mitigation effect of different varieties and intercropping modes on [...] Read more.

Global warming increases the risk of high-temperature injury to maize. Inter- and mixed-cropping of maize varieties with different genotypes is one way to effectively alleviate the high-temperature injury during the flowering period. However, the mitigation effect of different varieties and intercropping modes on high-temperature injury is still unclear. Based on previous years of field production, Denghai 605, which is more sensitive to high temperatures during the flowering period, was determined as the main test variety, and Zhengdan 958, Dedan 5, Weike 702, and Xianyu 335, which have great genotypic differences, were used as auxiliary varieties. The main test varieties and auxiliary varieties were intercropped and mixed cropped, respectively. Plant height, ear height, leaf area index, population light transmittance, ear characteristics, and yield were measured, and the land equivalent ratio (LER) was calculated. The plant height of Denghai 605 intercropped with Zhengdan 958 and Dedan 5 and mixed with Weike 702 and Xianyu 335 decreased significantly. The population light transmittance of the bottom or middle layer in Denghai 605 increased significantly when intercropped with other varieties. The grain number per ear increased significantly under inter- and mixed cropping with Zhengdan 958 and Weike 702. Except under intercropping with Dedan 5, the yield of Denghai 605 increased significantly, by 8.8–28.0%, under inter- and mixed cropping. Under intercropping with Zhengdan 958 and inter- and mixed cropping with Weike 702 and Xianyu 335, respectively, the group land equivalent ratio was greater than 1.1, indicating that under the combination of these varieties, inter- and mixed cropping effectively reduced the impact of high temperatures during flowering. Full article

(This article belongs to the Special Issue Sustainability with Changing Climate and Extremes)

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21 pages, 9364 KiB

Open AccessArticle

Spatial Zoning of Dry-Hot Wind Disasters in Shandong Province

by Nan Wang, Xiaoping Xue, Lijuan Zhang, Yue Chu, Meiyi Jiang, Yumeng Wang, Yiping Yang, Xihui Guo, Yufeng Zhao and Enbo Zhao

Sustainability 2022, 14(7), 3904; https://doi.org/10.3390/su14073904 - 25 Mar 2022

Cited by 3 | Viewed by 1645

Abstract

As a major agricultural province of China, Shandong province has long ranked first in agricultural growth value among all of the provinces; at the same time, it is also the province that is most affected by dry-hot wind. Therefore, it is of great [...] Read more.

As a major agricultural province of China, Shandong province has long ranked first in agricultural growth value among all of the provinces; at the same time, it is also the province that is most affected by dry-hot wind. Therefore, it is of great significance to study the spatial zoning of the risks of dry-hot wind in this province. Based on meteorological, slope, and altitude data, and the principle of disaster risk assessment, this study uses a weighted comprehensive evaluation method, analytic hierarchy process, and ARC-GIS spatial analysis to study the spatial zoning of the risks of dry-hot wind in Shandong province. The results show that the high-risk regions of dry-hot wind are concentrated in the north-central portion of the province, the medium-risk regions are in the peripheral areas, and the low-risk regions are located mainly in the west, southwest, and east. Exposure of disaster-bearing bodies is high in the south and low in the north, while vulnerability to disaster-bearing bodies is high in the west and low in the east. The more developed areas in the east show high disaster prevention and mitigation capability, whereas this is weak in the west. In summary, dry-hot wind risk in Shandong province varies significantly by area. The medium- and high-risk areas are mainly in the west and central portions of the province. Full article

(This article belongs to the Special Issue Sustainability with Changing Climate and Extremes)

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21 pages, 23091 KiB

Open AccessArticle

Peanut Drought Risk Zoning in Shandong Province, China

by Meiyi Jiang, Xiaoping Xue, Lijuan Zhang, Yuying Chen, Cheng Zhao, Haiyan Song and Nan Wang

Sustainability 2022, 14(6), 3322; https://doi.org/10.3390/su14063322 - 11 Mar 2022

Cited by 5 | Viewed by 2163

Abstract

Peanut growth in Shandong Province, a major peanut-producing area in China, is greatly affected by drought. The present study uses hierarchical analysis, weighted comprehensive evaluation, and ArcGIS spatial analysis to conduct spatial zoning of peanut drought risk in Shandong Province based on daily [...] Read more.

Peanut growth in Shandong Province, a major peanut-producing area in China, is greatly affected by drought. The present study uses hierarchical analysis, weighted comprehensive evaluation, and ArcGIS spatial analysis to conduct spatial zoning of peanut drought risk in Shandong Province based on daily precipitation data for the province acquired from 1991 to 2020, the per capita GDP, and the peanut planting area of Shandong Province, so as to quantify the disaster risk of peanut drought and formulate disaster prevention and resilience planning accordingly. The results show the high-drought-risk zone was mainly distributed in the northwestern part of Shandong Province and on the Jiaodong Peninsula, covering 32.4% of the province. Drought risk was concentrated on the Jiaodong Peninsula, covering 20.7% of the province. The high-vulnerability zone was mainly distributed in the cities of Yantai, Weihai, Linyi, and Rizhao, accounting for 26.8% of the total area. The low-disaster-prevention and low-mitigation-capacity zone was mainly distributed in the western part of Shandong Province, covering 38.7% of the province. Medium- and high-risk areas for drought affecting peanuts were widely distributed, while the overall comprehensive risk index was high, covering 76.2% of the province. Spatial analysis to conduct risk zoning and assessment of peanut drought in Shandong Province, so as to provide a basis for peanut drought disaster prevention and safe peanut production in Shandong Province. Full article

(This article belongs to the Special Issue Sustainability with Changing Climate and Extremes)

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17 pages, 3310 KiB

Open AccessArticle

Analysis of the Temporal and Spatial Distribution of Extreme Climate Indices in Central China

by Yan Li, Junfang Zhao, Rui Miao, Yan Huang, Xiaoqing Fan, Xiaoqing Liu, Xueqi Wang, Ye Wang and Yuyang Shen

Sustainability 2022, 14(4), 2329; https://doi.org/10.3390/su14042329 - 18 Feb 2022

Cited by 5 | Viewed by 1668

Abstract

Using the daily precipitation and temperature data of 101 meteorological stations in four provinces of central China (Henan, Hubei, Hunan, Jiangxi) from 1988 to 2017, we analyzed the temporal and spatial dynamics and periodicity of nine extreme climate indices in central China, using [...] Read more.

Using the daily precipitation and temperature data of 101 meteorological stations in four provinces of central China (Henan, Hubei, Hunan, Jiangxi) from 1988 to 2017, we analyzed the temporal and spatial dynamics and periodicity of nine extreme climate indices in central China, using the predefined methods for analyzing extreme climate events, such as a M-K test, a linear trend analysis, and a wavelet analysis. The extreme climate characteristics and changes in central China in the past 30 years were revealed. The results showed that the CSDI was significantly reduced linearly at a rate of −0.19 d/10a, and the WSDI and TXx increased significantly at rates of 0.25 d/10a and 0.30℃/10a, respectively. The CDD decreased significantly at a rate of −1.67 d/10a. The duration of extreme low-temperature and drought events in central China showed a gradual shortening, while the duration of extreme high-temperature events and the high-temperature values increased. The results of the abrupt climate change test showed that some extreme climate indices in central China had significant abrupt climate changes after 2000. Analyzing the cyclicality of each index, it was determined that the extreme climate index in central China had a significant cyclical change every 2–4 years, and the change was more notable after 2000. Analyzing the spatial distribution of the extreme climate indices, it was determined that Jiangxi had the longest duration of all high-temperature events, and was the largest and longest of events of extreme precipitation. It was also determined that the Jiangxi region was at greater risk of extreme climate events in central China. The results of this study can provide a scientific basis for climate change trends, local disaster prevention, and mitigation management in central China. Full article

(This article belongs to the Special Issue Sustainability with Changing Climate and Extremes)

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20 pages, 3319 KiB

Open AccessArticle

Fresh Air–Natural Microclimate Comfort Index: A New Tourism Climate Index Applied in Chinese Scenic Spots

by Xiaoyan Yang, Changshun Li, Muhammad Bilal and Shaofei Jin

Sustainability 2022, 14(3), 1911; https://doi.org/10.3390/su14031911 - 08 Feb 2022

Cited by 2 | Viewed by 1864

Abstract

Severe air pollution in China has caused significant tourism transformation for pursuing fresh air in microclimate tourism markets. Contemporary practices simply measure the air freshness of destinations and scenic spots using a single index, i.e., primarily negative oxygen ions (O₂⁻). [...] Read more.

Severe air pollution in China has caused significant tourism transformation for pursuing fresh air in microclimate tourism markets. Contemporary practices simply measure the air freshness of destinations and scenic spots using a single index, i.e., primarily negative oxygen ions (O₂⁻). This index cannot comprehensively reveal scenic spots’ air freshness degree and determine the dynamic interactions between air freshness and scenic spots’ tourism development, thus inducing an illusion of air freshness for the target scenic spots. Meanwhile, the current fresh air index primarily ignores connections with the microclimate index of scenic spots and cannot provide a multidimensional index for scenic spots to take advantage of both air and microclimate resources for diverse tourism products and service production. Therefore, this study proposes a multidimensional index, the fresh air–natural microclimate comfort index (FAI-NMCI), connecting the fresh air index with the natural microclimate comfort index of scenic spots together from transdisciplinary and multidisciplinary perspectives. This study utilizes FAI-NMCI to measure four scenic spots of Fujian Province, and reveals in-depth results of scenic spots’ air freshness and natural microclimate comfort degree together. The results demonstrate that the four scenic spots in Fujian province of China had different levels of air freshness degree and natural microclimate comfort degree in 2018. The natural scenic spots were mostly distributed in Healing Fresh, Very Fresh, and Super Fresh levels of FAI with the most comfortable and comfortable levels of NMCI. The cultural scenic spots were mostly distributed in Relatively Fresh and Healing Fresh levels of FAI with the most comfortable and comfortable levels of NMCI. Meanwhile, the FAI-NMCI of natural and cultural scenic spots also had significant differences within 24 Jieqi, which will promote dynamic and creative utilization of those resources in microclimate tourism development. Full article

(This article belongs to the Special Issue Sustainability with Changing Climate and Extremes)

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17 pages, 5394 KiB

Open AccessArticle

Evaluation and Projection of Diurnal Temperature Range in Maize Cultivation Areas in China Based on CMIP6 Models

by Wenqiang Xie, Shuangshuang Wang and Xiaodong Yan

Sustainability 2022, 14(3), 1660; https://doi.org/10.3390/su14031660 - 31 Jan 2022

Cited by 9 | Viewed by 2358

Abstract

The diurnal temperature range (DTR) is an important meteorological component affecting maize yield. The accuracy of climate models simulating DTR directly affects the projection of maize production. We evaluate the ability of 26 Coupled Model Intercomparison Project phase 6 (CMIP6) models to simulate [...] Read more.

The diurnal temperature range (DTR) is an important meteorological component affecting maize yield. The accuracy of climate models simulating DTR directly affects the projection of maize production. We evaluate the ability of 26 Coupled Model Intercomparison Project phase 6 (CMIP6) models to simulate DTR during 1961–2014 in maize cultivation areas with the observation (CN05.1), and project DTR under different shared socioeconomic pathway (SSP) scenarios. The root mean square error (

R M S E

), standard deviation (

S D

), Kling-Gupta efficiency (

K G E

) and comprehensive rating index (

C R I

) are used in the evaluation of the optimal model. The results show that CMIP6 models can generally reproduce the spatial distribution. The reproducibility of the annual average DTR in the maize cultivation areas is better than that in China but lower for the maize-growing season. The optimal model (EC-Earth3-Veg-LR) is used in the projection. Under the two SSPs, the DTR decreases compared with the historical period, especially in Northwest and North China. The DTR under SSP245 remains unchanged (annual) or increases slightly (growing season) during 2015–2050, while a significant decreasing trend is observed under SSP585. This highlights the importance of evaluating DTR in maize cultivation areas, which is helpful to further improve the accuracy of maize yield prediction. Full article

(This article belongs to the Special Issue Sustainability with Changing Climate and Extremes)

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15 pages, 10787 KiB

Open AccessArticle

Effect of Snow Cover on Spring Soil Moisture Content in Key Agricultural Areas of Northeast China

by Mingxi Pan, Fang Zhao, Jingyan Ma, Lijuan Zhang, Jinping Qu, Liling Xu and Yao Li

Sustainability 2022, 14(3), 1527; https://doi.org/10.3390/su14031527 - 28 Jan 2022

Cited by 5 | Viewed by 1479

Abstract

As an important source of soil moisture content during spring in high-latitude areas, snow cover affects the occurrence of spring drought and crop yield and quality. There has not been sufficient research on the effect of winter snow cover on spring soil moisture [...] Read more.

As an important source of soil moisture content during spring in high-latitude areas, snow cover affects the occurrence of spring drought and crop yield and quality. There has not been sufficient research on the effect of winter snow cover on spring soil moisture content. This paper focuses on the main agricultural areas of Northeast China—the Songnen Plain and the Sanjiang Plain. Using meteorological data of both spring soil moisture content and snow cover at 19 agricultural meteorological stations from 1983 to 2019, the effect of snow cover on spring soil moisture content in the Sanjiang Plain and Songnen Plain is studied by variance analysis, spatial analysis, and correlation analysis. The results show that: (1) Compared to the Sanjiang Plain, the Songnen Plain has a significantly lower content of soil moisture at the surface (0–10 cm) and deep layer (10–20 cm, 20–30 cm) during the entire spring and every month of spring (p < 0.05), and a greater interannual variation of soil moisture. (2) Snow cover has a significant effect on spring soil moisture in the Songnen Plain, but not as much as one in the Sanjiang Plain. For the Songnen Plain, snow-cover duration and the snow-cover onset date has a lasting influence on spring soil moisture until May, which can extend to as deep as 20–30 cm. As months go by, its influence on shallow-layer soil gradually wears off. Maximum snow depth and the snow-cover end date only influence the April surface soil. (3) Snow cover has a strong effect on soil moisture conservation in more arid areas. Delayed snow-cover onset date, earlier snow-cover end date, and significantly shortened snow-cover duration all contribute to a spring drought soil condition in the Songnen Plain. Full article

(This article belongs to the Special Issue Sustainability with Changing Climate and Extremes)

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16 pages, 3545 KiB

Open AccessArticle

Impact of Abnormal Climatic Events on the CPUE of Yellowfin Tuna Fishing in the Central and Western Pacific

by Weifeng Zhou, Huijuan Hu, Wei Fan and Shaofei Jin

Sustainability 2022, 14(3), 1217; https://doi.org/10.3390/su14031217 - 21 Jan 2022

Cited by 4 | Viewed by 1951

Abstract

To explore the impact of climate change on fishery resources, the temporal and spatial characteristics of the thermocline in the main yellowfin tuna purse-seine fishing grounds in the western and central Pacific Ocean during La Niña and El Niño years were studied using [...] Read more.

To explore the impact of climate change on fishery resources, the temporal and spatial characteristics of the thermocline in the main yellowfin tuna purse-seine fishing grounds in the western and central Pacific Ocean during La Niña and El Niño years were studied using the 2008–2017 Argo grid data (BOA_Argo) and the log data of commercial fishing vessels. A generalized additive model (GAM) was used to analyze the variables affecting yellowfin tuna fishing grounds. The results showed that in La Niña years, the catch per unit effort (CPUE) moved westward as the high-value zone of the upper boundary contracted westward to 145° E, and in the El Niño years this moved eastward to 165° E. Compared with normal years, the upper boundary depth difference of the thermocline on the east and west sides of the equatorial Pacific was larger in La Niña years, and the upper boundary depth of 80–130 m shifted westward. The thermocline strength was generally weaker in the west and stronger in the east. The thermocline had two band-like distribution structures with an axis at 15° N and 15° S. The CPUE was distributed from 120 m to 200 m. The CPUE distribution was dense when the temperature range of the upper boundary of the thermocline was 27.5–29.5 °C, and the intensity was 0.08–0.13 °C·m⁻¹. The upper-boundary temperature had the greatest impact on the CPUE. The eastward shift of the CPUE during El Niño and the westward shift during La Niña were associated with the optimal thermocline parameter values. The factor of year had a fluctuating effect on the CPUE, and the influence of the La Niña years was greater. The areas with high abundance were 5° N–5° S and 150° E–175° E. The results showed that the changes in the thermocline caused by abnormal climate events significantly affected the CPUE. Full article

(This article belongs to the Special Issue Sustainability with Changing Climate and Extremes)

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13 pages, 12767 KiB

Open AccessArticle

High-Resolution Regional Climate Modeling and Projection of Heatwave Events over the Yangtze River Basin

by Zhibo Gao and Xiaodong Yan

Sustainability 2022, 14(3), 1141; https://doi.org/10.3390/su14031141 - 20 Jan 2022

Cited by 4 | Viewed by 1671

Abstract

Heatwave events (HWEs) have strong impacts on human health, ecosystems, and sustainable social development. Using a gridded observation dataset and a high-resolution regional climate model (RCM), this study analyzed the characteristics of HWEs over the Yangtze River Basin (YRB) in eastern China during [...] Read more.

Heatwave events (HWEs) have strong impacts on human health, ecosystems, and sustainable social development. Using a gridded observation dataset and a high-resolution regional climate model (RCM), this study analyzed the characteristics of HWEs over the Yangtze River Basin (YRB) in eastern China during the historical period and projected the changes in HWEs over the YRB in the future. The daily maximum temperature (Tmax), long-lived (≥6 days) HWEs, and total (≥3 days) HWEs in the YRB all showed an obvious upward trend from 1981 to 2018, while the increase in short-lived (≥3 days and <6 days) HWEs was relatively moderate overall. The RCM of the Weather Research and Forecasting (WRF) model can simulate the characteristics of Tmax and HWEs in the historical period very well, and the projection results showed that Tmax, total HWEs, and long-lived HWEs will all increase obviously in both the SSP245 and SSP585 scenarios. Short-lived HWEs will also increase rapidly under SSP585, but they will rise slowly overall under SSP245. The changes in HWEs had distinct regional differences, and the intensity and coverage area of HWEs were greater under SSP585 overall. In the future, the increase in HWEs over the YRB region is likely to be associated with the enhancement of the western-Pacific subtropical high (WPSH) and South-Asian high (SAH), and this enhancement was also greater under SSP585. The results from the high-resolution simulation of the RCM can provide an important reference for disaster prevention and mitigation in the future. Full article

(This article belongs to the Special Issue Sustainability with Changing Climate and Extremes)

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14 pages, 2396 KiB

Open AccessArticle

Population Exposure Changes to One Heat Wave and the Influencing Factors Using Mobile Phone Data—A Case Study of Zhuhai City, China

by Junrong Li, Peng Guo, Yanling Sun, Zifei Liu, Xiakun Zhang and Xinrui Pei

Sustainability 2022, 14(2), 997; https://doi.org/10.3390/su14020997 - 17 Jan 2022

Cited by 2 | Viewed by 2192

Abstract

The frequent occurrence of extreme high temperature weather and heat waves has greatly affected human life. This paper analyzes population exposure and its influencing factors during a heat wave incident in Zhuhai from 6 to 12 September 2021 based on real-time mobile phone [...] Read more.

The frequent occurrence of extreme high temperature weather and heat waves has greatly affected human life. This paper analyzes population exposure and its influencing factors during a heat wave incident in Zhuhai from 6 to 12 September 2021 based on real-time mobile phone data and meteorological data. The results show that the most areas of Zhuhai are affected by high temperature during this heat wave incident. The hourly population exposure is directly proportional to hourly heat wave coverage. In terms of time dimension, the overall population exposure shows a trend of decreasing and then increasing. In terms of spatial dimensions, high population exposure is concentrated in areas such as primary and secondary schools, colleges and universities, office buildings, and residential areas. Low exposure is distributed in most of the mountainous areas along the southern coast. In addition, the leading factors that cause changes in population exposure in different periods of the heat wave cycle are different, which rely more on either climatic factors or population factors. Full article

(This article belongs to the Special Issue Sustainability with Changing Climate and Extremes)

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21 pages, 8217 KiB

Open AccessArticle

Spatial-Temporal Variation of Snow Black Carbon Concentration in Snow Cover in Northeast China from 2001 to 2016 Based on Remote Sensing

by Yanjiao Zheng, Lijuan Zhang, Wenliang Li, Fan Zhang and Xinyue Zhong

Sustainability 2022, 14(2), 959; https://doi.org/10.3390/su14020959 - 15 Jan 2022

Cited by 1 | Viewed by 1741

Abstract

The amount of black carbon (BC) on snow surface can significantly reduce snow surface albedo in the visible-light range and change the surface radiative forcing effect. Therefore, it is key to study regional and global climate changes to understand the BC concentration on [...] Read more.

The amount of black carbon (BC) on snow surface can significantly reduce snow surface albedo in the visible-light range and change the surface radiative forcing effect. Therefore, it is key to study regional and global climate changes to understand the BC concentration on snow. In this study, we simulated the BC concentration on the surface snow of northeast China using an asymptotic radiative transfer model. From 2001 to 2016, the BC concentration showed no significant increase, with an average increase of 82.104 ng/g compared with that in the early 21st century. The concentration of BC in December was the largest (1344.588 ng/g) and decreased in January and February (1248.619 ng/g and 983.635 ng/g, respectively). The high black carbon content centers were concentrated in the eastern and central regions with dense populations and concentrated industries, with a concentration above 1200 ng/g, while the BC concentration in the southwest region with less human activities was the lowest (below 850 ng/g), which indicates that human activities played an important role in snow BC pollution. Notably, Heilongjiang province has the highest concentration, which may be related to its atmospheric stability in winter. These findings suggest that the BC pollution in northeast China has been aggravated from 2001 to 2016. It is estimated that the snow surface albedo will decrease by 16.448% due to the BC pollution of snow in northeast China. The problem of radiative forcing caused by black carbon to snow reflectivity cannot be ignored. Full article

(This article belongs to the Special Issue Sustainability with Changing Climate and Extremes)

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14 pages, 3210 KiB

Open AccessEditor’s ChoiceArticle

Global Forest Types Based on Climatic and Vegetation Data

by Chen Xu, Xianliang Zhang, Rocío Hernandez-Clemente, Wei Lu and Rubén D. Manzanedo

Sustainability 2022, 14(2), 634; https://doi.org/10.3390/su14020634 - 07 Jan 2022

Cited by 3 | Viewed by 3995

Abstract

Forest types are generally identified using vegetation or land-use types. However, vegetation classifications less frequently consider the actual forest attributes within each type. To address this in an objective way across different regions and to link forest attributes with their climate, we aimed [...] Read more.

Forest types are generally identified using vegetation or land-use types. However, vegetation classifications less frequently consider the actual forest attributes within each type. To address this in an objective way across different regions and to link forest attributes with their climate, we aimed to improve the distribution of forest types to be more realistic and useful for biodiversity preservation, forest management, and ecological and forestry research. The forest types were classified using an unsupervised cluster analysis method by combining climate variables with normalized difference vegetation index (NDVI) data. Unforested regions were masked out to constrict our study to forest type distributions, using a 20% tree cover threshold. Descriptive names were given to the defined forest types based on annual temperature, precipitation, and NDVI values. Forest types had distinct climate and vegetation characteristics. Regions with similar NDVI values, but with different climate characteristics, which would be merged in previous classifications, could be clearly distinguished. However, small-range forest types, such as montane forests, were challenging to differentiate. At macroscale, the resulting forest types are largely consistent with land-cover types or vegetation types defined in previous studies. However, considering both potential and current vegetation data allowed us to create a more realistic type distribution that differentiates actual vegetation types and thus can be more informative for forest managers, conservationists, and forest ecologists. The newly generated forest type distribution is freely available to download and use for non-commercial purposes as a GeoTIFF file via doi: 10.13140/RG.2.2.19197.90082). Full article

(This article belongs to the Special Issue Sustainability with Changing Climate and Extremes)

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11 pages, 6585 KiB

Open AccessArticle

Quality Evaluation of the 0.01° Multi-Source Fusion Precipitation Product and Its Application in Extreme Precipitation Event

by Zheng Wang, Yang Pan, Junxia Gu, Yu Zhang and Jianrong Wang

Sustainability 2022, 14(2), 616; https://doi.org/10.3390/su14020616 - 06 Jan 2022

Cited by 1 | Viewed by 1129

Abstract

High-resolution and high-quality precipitation data play an important role in Numerical Weather Prediction Model testing, mountain flood geological disaster monitoring, hydrological monitoring and prediction and have become an urgent need for the development of modern meteorological business. The 0.01° multi-source fusion precipitation product [...] Read more.

High-resolution and high-quality precipitation data play an important role in Numerical Weather Prediction Model testing, mountain flood geological disaster monitoring, hydrological monitoring and prediction and have become an urgent need for the development of modern meteorological business. The 0.01° multi-source fusion precipitation product is the latest precipitation product developed by the National Meteorological Information Center to meet the above needs. Taking the hourly precipitation observation data of 2400 national automatic stations as the evaluation base, independent and non-independent test methods are used to evaluate the 0.01° multi-source fusion precipitation product in 2020. The product quality differences between the 0.01° precipitation product and the 0.05° precipitation product are compared, and their application in extreme precipitation events are analyzed. The results show that, in the independent test, the product quality of the 0.01° precipitation product and the 0.05° precipitation product are basically the same, which is better than that of each single input data source, and the product quality in winter and spring is slightly lower than that in summer, and both products have better quality in the east in China. The evaluation results of the 0.01° precipitation product in the non-independent test are far better than that of the 0.05° product. The root mean square error and the correlation coefficient of the 0.01° multi-source fusion precipitation product are 0.169 mm/h and 0.995, respectively. In the extreme precipitation case analysis, the 0.01° precipitation product, which is more consistent with the station observation values, effectively improves the problem that the extreme value of the 0.05° product is lower than that of station observation values and greatly improves the accuracy of the precipitation extreme value in the product. The 0.01° multi-source fusion precipitation product has better spatial continuity, a more detailed description of precipitation spatial distribution and a more accurate reflection of precipitation extreme values, which will better provide precipitation data support for refined meteorological services, major activity support, disaster prevention and reduction, etc. Full article

(This article belongs to the Special Issue Sustainability with Changing Climate and Extremes)

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12 pages, 11259 KiB

Open AccessArticle

Spatial Distribution of, and Variations in, Cold Regions in China from 1961 to 2019

by Yumeng Wang, Jingyan Ma, Lijuan Zhang, Yutao Huang, Xihui Guo, Yiping Yang, Enbo Zhao, Yufeng Zhao, Yue Chu, Meiyi Jiang and Nan Wang

Sustainability 2022, 14(1), 465; https://doi.org/10.3390/su14010465 - 02 Jan 2022

Cited by 1 | Viewed by 1273

Abstract

In this study, on the basis of the temperature data collected at 612 meteorological stations in China from 1961 to 2019, cold regions were defined using three indicators: an average temperature of <−3.0 °C during the coldest month; less than five months with [...] Read more.

In this study, on the basis of the temperature data collected at 612 meteorological stations in China from 1961 to 2019, cold regions were defined using three indicators: an average temperature of <−3.0 °C during the coldest month; less than five months with an average temperature of >10 °C; and an annual average temperature of ≤5 °C. Spatial interpolation, spatial superposition, a trend analysis, and a spatial similarity analysis were used to obtain the spatial distribution of the cold regions in China from 1961 to 2019. Then, the areas of the cold regions and the spatial change characteristics were analyzed. The results reveal that the average area of the cold regions in China from 1961 to 2019 was about 427.70 × 10⁴ km², accounting for about 44.5% of the total land area. The rate of change of the area of the cold regions from 1961 to 2019 was −14.272 × 10⁴ km²/10 a, exhibiting a very significant decreasing trend. On the basis of the changes between 1991–2019 and 1961–1990, the area of China’s cold regions decreased by 49.32 × 10⁴ km². The findings of this study provide references for studying changes in the natural environment due to climate change, as well as for studying changes on a global scale. Full article

(This article belongs to the Special Issue Sustainability with Changing Climate and Extremes)

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17 pages, 6967 KiB

Open AccessArticle

Impact of Model Resolution on the Simulation of Precipitation Extremes over China

by Neng Luo and Yan Guo

Sustainability 2022, 14(1), 25; https://doi.org/10.3390/su14010025 - 21 Dec 2021

Cited by 8 | Viewed by 2386

Abstract

Climate models tend to overestimate light precipitation and underestimate heavy precipitation due to low model resolution. This work investigated the impact of model resolution on simulating the precipitation extremes over China during 1995–2014, based on five models from Coupled Model Intercomparison Project 6 [...] Read more.

Climate models tend to overestimate light precipitation and underestimate heavy precipitation due to low model resolution. This work investigated the impact of model resolution on simulating the precipitation extremes over China during 1995–2014, based on five models from Coupled Model Intercomparison Project 6 (CMIP6), each having low- and high-resolution versions. Six extreme indices were employed: simple daily intensity index (SDII), wet days (WD), total precipitation (PRCPTOT), extreme precipitation amount (R95p), heavy precipitation days (R20mm), and consecutive dry days (CDD). Models with high resolution demonstrated better performance in reproducing the pattern of climatological precipitation extremes over China, especially in the western Sichuan Basin along the eastern side of the Tibetan Plateau (D1), South China (D2), and the Yangtze-Yellow River basins (D3). Decreased biases of precipitation exist in all high-resolution models over D1, with the largest decease in root mean square error (RMSE) being 48.4% in CNRM-CM6. The improvement could be attributed to fewer weak precipitation events (0 mm/day–10 mm/day) in high-resolution models in comparison with their counterparts with low resolutions. In addition, high-resolution models also show smaller biases over D2, which is associated with better capturing of the distribution of daily precipitation frequency and improvement of the simulation of the vertical distribution of moisture content. Full article

(This article belongs to the Special Issue Sustainability with Changing Climate and Extremes)

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21 pages, 32573 KiB

Open AccessArticle

Snow-Disaster Risk Zoning and Assessment in Heilongjiang Province

by Hao Li, Wenshuang Xi, Lijuan Zhang and Shuying Zang

Sustainability 2021, 13(24), 14010; https://doi.org/10.3390/su132414010 - 18 Dec 2021

Cited by 5 | Viewed by 3086

Abstract

Heilongjiang Province is located in the northeast region of China, with the country’s highest latitude. It has long and cold winters, and a temperate monsoon climate. Its unique geographic location and climatic conditions make it the second largest stable snow-covered region in China. [...] Read more.

Heilongjiang Province is located in the northeast region of China, with the country’s highest latitude. It has long and cold winters, and a temperate monsoon climate. Its unique geographic location and climatic conditions make it the second largest stable snow-covered region in China. The winter snow period starts in October and ends in April of the following year. Therefore, the long-term accumulation of snow causes road obstructions and low-temperature frost damage, which seriously affects local economic development and human safety. This study adopts snow parameters (e.g., snow depth and snow-cover period), natural environmental factors (e.g., elevation and slope), and socioeconomic factors (e.g., gross domestic product and light index). On the basis of the disaster risk assessment theory, we constructed a disaster risk index from four aspects (i.e., disaster risk, susceptibility, vulnerability, and disaster prevention and mitigation). Then, we performed snow-disaster risk zoning and an assessment in Heilongjiang Province. The main findings are as follows: the snow-disaster risk in the northern and eastern regions of Heilongjiang Province was high; the central and northern regions were highly sensitive to disasters; the main urban areas were highly vulnerable; and the economically developed regions had strong disaster prevention and mitigation capabilities. Overall, the spatial distribution of the snow-disaster risk followed a decreasing trend from east to west. High-risk areas were distributed in the east and northwest (covering 34.3% of the entire Heilongjiang Province area); medium-risk areas were distributed in the north and center (accounting for 45.2% of the entire Heilongjiang Province area); and low-risk areas were concentrated in the west (constituting 20.5% of the entire Heilongjiang Province area). Full article

(This article belongs to the Special Issue Sustainability with Changing Climate and Extremes)

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12 pages, 16920 KiB

Open AccessArticle

Understanding Climate Hazard Patterns and Urban Adaptation Measures in China

by Shao Sun, Zunya Wang, Chuanye Hu and Ge Gao

Sustainability 2021, 13(24), 13886; https://doi.org/10.3390/su132413886 - 15 Dec 2021

Cited by 6 | Viewed by 3919

Abstract

Climate-related risks pose a great threat to urban safety, infrastructure stability and socioeconomic sustainability. China is a country that crosses diverse geomorphic and climatic regions in the world and is frequently affected by various climate hazards. In this study, we propose a comprehensive [...] Read more.

Climate-related risks pose a great threat to urban safety, infrastructure stability and socioeconomic sustainability. China is a country that crosses diverse geomorphic and climatic regions in the world and is frequently affected by various climate hazards. In this study, we propose a comprehensive analysis on the spatial pattern of major climate hazards in China from 1991 to 2020, including rainstorms, droughts, heatwaves, coldwaves, typhoons, and snowstorms, and generate an integrated sketch map on multi-hazard zones. It is detectable that South of the Yangtze River is in danger of heatwaves, rainstorms, and typhoons, while the North China Plain is more likely to suffer droughts. Coldwaves, snowstorms, and freezing mainly affect Northeast China, Northwest China, and the Qinghai–Tibet Plateau. In the view of climate governance, cities are hotspots affected by intensified climate hazards in a warmer climate. There is an urgent need to incorporate a climate adaptation strategy into future city construction, so as to improve social resilience and mitigate climate impacts in rapid urbanization process. Specific adaptation measures have been developed from the perspectives of land-use planning, prevention standard, risk assessment, and emergency response to facilitate the understanding of climate resilience and urban sustainability. Full article

(This article belongs to the Special Issue Sustainability with Changing Climate and Extremes)

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16 pages, 2051 KiB

Open AccessArticle

The Effects of Land-Use Change/Conversion on Trade-Offs of Ecosystem Services in Three Precipitation Zones

by Qiang Feng, Siyan Dong and Baoling Duan

Sustainability 2021, 13(23), 13306; https://doi.org/10.3390/su132313306 - 01 Dec 2021

Cited by 6 | Viewed by 1529

Abstract

Revealing the spatial differentiation of ecosystem service (ES) trade-offs and their responses to land-use change along precipitation gradients are important issues in the Loess Plateau of China. We selected three watersheds called Dianshi (300 mm < MAP (mean annual precipitation) < 400 mm), [...] Read more.

Revealing the spatial differentiation of ecosystem service (ES) trade-offs and their responses to land-use change along precipitation gradients are important issues in the Loess Plateau of China. We selected three watersheds called Dianshi (300 mm < MAP (mean annual precipitation) < 400 mm), Ansai (400 mm < MAP < 500 mm), and Linzhen (500 mm < MAP < 600 mm). A new ES trade-off quantification index was proposed, and quantile regression, piecewise linear regression, and redundancy analysis were used. The results were as follows. (1) Carbon sequestration (TC) and soil conservation (SEC) increased, but water yield (WY) decreased in the three watersheds from 2000 to 2018. (2) The effect of forests on trade-offs was positive in three watersheds, the main effect of shrubs was also positive, but the negative effect appeared in the TC-WY trade-off in Ansai. Grassland exacerbated trade-offs in Dianshi, whereas it reduced trade-offs in Ansai and Linzhen. These effects exhibited respective trends with the quantile in the three watersheds. (3) There were threshold values that trade-offs responded to land-use changes, and we could design land-use conversion types to balance ESs. In general, the water consumption of grass cannot be ignored in Dianshi; shrubs and grass are suitable vegetation types, and forests need to be restricted in Ansai; more forests and shrubs can be supported in Linzen due to higher precipitation, but the current proportions of forests and shrubs are too high. Our research contributes to a better understanding of the response mechanisms of ES trade-offs to land-use changes. Full article

(This article belongs to the Special Issue Sustainability with Changing Climate and Extremes)

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15 pages, 13963 KiB

Open AccessArticle

Spatial-Temporal Characteristics of Arctic Summer Climate Comfort Level in the Context of Regional Tourism Resources from 1979 to 2019

by Yutao Huang, Xuezhen Zhang, Dan Zhang, Lijuan Zhang, Wenshuai Zhang, Chong Ren, Tao Pan, Zheng Chu and Yuying Chen

Sustainability 2021, 13(23), 13056; https://doi.org/10.3390/su132313056 - 25 Nov 2021

Cited by 5 | Viewed by 1501

Abstract

In the context of global warming, a key scientific question for the sustainable development of the Arctic tourism industry is whether the region’s climate is becoming more suitable for tourism. Based on the ERA5-HEAT (Human thErmAl comforT) dataset from the European Center for [...] Read more.

In the context of global warming, a key scientific question for the sustainable development of the Arctic tourism industry is whether the region’s climate is becoming more suitable for tourism. Based on the ERA5-HEAT (Human thErmAl comforT) dataset from the European Center for Medium-range Weather Forecasts (ECMWF), this study used statistical methods such as climatic tendency rate and RAPS to analyze the spatial-temporal changes in Arctic summer climate comfort zones from 1979 to 2019 and to explore the influence of changes in climate comfort on Arctic tourism. The results showed the following: (1) With the increase in the Arctic summer temperature, the universal thermal climate index (UTCI) rose significantly from 1979 to 2019 at a rate of 0.457 °C/10a. There was an abrupt change in 2001, when the climate comfort changed from “colder” to “cool”, and the climate comfort has remained cool over the past decade (2010–2019). (2) With the increase in Arctic summer temperatures, the area assessed as “comfortable” increased significantly from 1979 to 2019 at a rate of 2.114 × 10⁵ km²/10a. Compared with the comfortable area in the 1980s, the comfortable area increased by 6.353 × 10⁵ km² over the past 10 years and expanded to high-latitude and high-altitude areas, mainly in Kola Peninsula, Putorana Plateau, and Verkhoyansk Mountains in Russia, as well as the Brooks Mountains in Alaska. (3) With the increase in Arctic summer temperatures, the number of days rated comfortable on 30% of the grid increased significantly from 1979 to 2019 (maximum increase: 31 days). The spatial range of the area with a low level of comfortable days narrowed and the spatial range of the area with a high level of such days expanded. The area with 60–70 comfortable days increased the most (4.57 × 10⁵ km²). The results of this study suggest that global warming exerts a significant influence on the Arctic summer climate comfort level and provides favorable conditions for further development of regional tourism resources. Full article

(This article belongs to the Special Issue Sustainability with Changing Climate and Extremes)

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21 pages, 5115 KiB

Open AccessArticle

Assessment and Prediction of Climate Risks in Three Major Urban Agglomerations of Eastern China

by Jieming Chou, Mingyang Sun, Wenjie Dong, Weixing Zhao, Jiangnan Li, Yuanmeng Li and Jianyin Zhou

Sustainability 2021, 13(23), 13037; https://doi.org/10.3390/su132313037 - 25 Nov 2021

Cited by 4 | Viewed by 1939

Abstract

In the context of global climate change and urban expansion, extreme urban weather events occur frequently and cause significant social problems and economic losses. To study the climate risks associated with rapid urbanization in the global context of climate change, the vulnerability degree [...] Read more.

In the context of global climate change and urban expansion, extreme urban weather events occur frequently and cause significant social problems and economic losses. To study the climate risks associated with rapid urbanization in the global context of climate change, the vulnerability degree of urban agglomeration is constructed by the Grey Model (GM (1, 1)). Based on the sixth phase of the Coupled Model Intercomparison Project (CMIP6) data sets SSP1-2.6, SSP2-4.5, and SSP5-8.5, drought, heat wave, and flood hazards under different emission scenarios are calculated. The vulnerability degree of the urban agglomeration and the climate change hazard were input into the climate change risk assessment model to evaluate future climate change risk. The analysis results show regional differences, with the Beijing–Tianjin–Hebei urban agglomeration having good urban resilience, the Yangtze River Delta urban agglomeration having slightly higher overall risk, and the Pearl River Delta urban agglomeration having the highest relative risk overall. On the whole, the higher the emission intensity is, the greater the risk of climate change to each urban agglomeration under different emission scenarios. Full article

(This article belongs to the Special Issue Sustainability with Changing Climate and Extremes)

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15 pages, 3570 KiB

Open AccessArticle

The Study on Compound Drought and Heatwave Events in China Using Complex Networks

by Kaiwen Li, Ming Wang and Kai Liu

Sustainability 2021, 13(22), 12774; https://doi.org/10.3390/su132212774 - 18 Nov 2021

Cited by 5 | Viewed by 2322

Abstract

Compound extreme events can severely impact water security, food security, and social and economic development. Compared with single-hazard events, compound extreme events cause greater losses. Therefore, understanding the spatial and temporal variations in compound extreme events is important to prevent the risks they [...] Read more.

Compound extreme events can severely impact water security, food security, and social and economic development. Compared with single-hazard events, compound extreme events cause greater losses. Therefore, understanding the spatial and temporal variations in compound extreme events is important to prevent the risks they cause. Only a few studies have analyzed the spatial and temporal relations of compound extreme events from the perspective of a complex network. In this study, we define compound drought and heatwave events (CDHEs) using the monthly scale standard precipitation index (SPI), and the definition of a heatwave is based on daily maximum temperature. We evaluate the spatial and temporal variations in CDHEs in China from 1961 to 2018 and discuss the impact of maximum temperature and precipitation changes on the annual frequency and annual magnitude trends of CDHEs. Furthermore, a synchronization strength network is established using the event synchronization method, and the proposed synchronization strength index (SSI) is used to divide the network into eight communities to identify the propagation extent of CDHEs, where each community represents a region with high synchronization strength. Finally, we explore the impact of summer Atlantic multidecadal oscillation (AMO) and Pacific decadal oscillation (PDO) on CDHEs in different communities. The results show that, at a national scale, the mean frequency of CDHEs takes on a non-significant decreasing trend, and the mean magnitude of CDHEs takes on a non-significant increasing trend. The significant trends in the annual frequency and annual magnitude of CDHEs are attributed to maximum temperature and precipitation changes. AMO positively modulates the mean frequency and mean magnitude of CDHEs within community 1 and 2, and negatively modulates the mean magnitude of CDHEs within community 3. PDO negatively modulates the mean frequency and mean magnitude of CDHEs within community 4. AMO and PDO jointly modulate the mean magnitude of CDHEs within community 6 and 8. Overall, this study provides a new understanding of CDHEs to mitigate their severe effects. Full article

(This article belongs to the Special Issue Sustainability with Changing Climate and Extremes)

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19 pages, 6383 KiB

Open AccessArticle

Assessment of Seasonal Variability of Extreme Temperature in Mainland China under Climate Change

by Weixiong Yan, Junfang Zhao, Jianping Li and Yunxia Wang

Sustainability 2021, 13(22), 12462; https://doi.org/10.3390/su132212462 - 11 Nov 2021

Cited by 4 | Viewed by 1616

Abstract

Some studies have suggested that variations in the seasonal cycle of temperature and season onset could affect the efficiency in the use of radiation by plants, which would then affect yield. However, the study of the temporal variation in extreme climatic variables is [...] Read more.

Some studies have suggested that variations in the seasonal cycle of temperature and season onset could affect the efficiency in the use of radiation by plants, which would then affect yield. However, the study of the temporal variation in extreme climatic variables is not sufficient in China. Using seasonal trend analysis (STA), this article evaluates the distribution of extreme temperature seasonality trends in mainland China, describes the trends in the seasonal cycle, and detects changes in extreme temperature characterized by the number of hot days (HD) and frost days (FD), the frequency of warm days (TX90p), cold days (TX10p), warm nights (TN90p), and cold nights (TN10p). The results show a statistically significant positive trend in the annual average amplitudes of extreme temperatures. The amplitude and phase of the annual cycle experience less variation than that of the annual average amplitude for extreme temperatures. The phase of the annual cycle in maximum temperature mainly shows a significant negative trend, accounting for approximately 30% of the total area of China, which is distributed across the regions except for northeast and southwest. The amplitude of the annual cycle indicates that the minimum temperature underwent slightly greater variation than the maximum temperature, and its distribution has a spatial characteristic that is almost bounded by the 400 mm isohyet, increasing in the northwest and decreasing in the southeast. In terms of the extreme air temperature indices, HD, TX90p, and TN90p show an increasing trend, FD, TX10p, and TN10p show a decreasing trend. They are statistically significant (p < 0.05). This number of days also suggests that temperature has increased over mainland China in the past 42 years. Full article

(This article belongs to the Special Issue Sustainability with Changing Climate and Extremes)

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15 pages, 4598 KiB

Open AccessArticle

How the Updated Earth System Models Project Terrestrial Gross Primary Productivity in China under 1.5 and 2 °C Global Warming

by Chi Zhang, Shaohong Wu, Yu Deng and Jieming Chou

Sustainability 2021, 13(21), 11744; https://doi.org/10.3390/su132111744 - 24 Oct 2021

Viewed by 1568

Abstract

Three Earth system models (ESMs) from the Coupled Model Intercomparison Project phase 6 (CMIP6) were chosen to project ecosystem changes under 1.5 and 2 °C global warming targets in the Shared Socioeconomic Pathway 4.5 W m⁻² (SSP245) scenario. Annual terrestrial gross primary [...] Read more.

Three Earth system models (ESMs) from the Coupled Model Intercomparison Project phase 6 (CMIP6) were chosen to project ecosystem changes under 1.5 and 2 °C global warming targets in the Shared Socioeconomic Pathway 4.5 W m⁻² (SSP245) scenario. Annual terrestrial gross primary productivity (GPP) was taken as the representative ecological indicator of the ecosystem. Under 1.5 °C global warming, GPP in four climate zones—i.e., temperate continental; temperate monsoonal; subtropical–tropical monsoonal; high-cold Tibetan Plateau—showed a marked increase, the smallest magnitude of which was around 12.3%. The increase was greater under 2 °C of global warming, which suggests that from the perspective of ecosystem productivity, global warming poses no ecological risk in China. Specifically, in comparison with historical GPP (1986–2005), under 1.5 °C global warming GPP was projected to increase by 16.1–23.8% in the temperate continental zone, 12.3–16.1% in the temperate monsoonal zone, 12.5–14.7% in the subtropical–tropical monsoonal zone, and 20.0–37.0% on the Tibetan Plateau. Under 2 °C global warming, the projected GPP increase was 23.0–34.3% in the temperate continental zone, 21.2–24.4% in the temperate monsoonal zone, 16.1–28.4% in the subtropical–tropical monsoonal zone, and 28.4–63.0% on the Tibetan Plateau. The GPP increase contributed by climate change was further quantified and attributed. The ESM prediction from the Max Planck Institute suggested that the climate contribution could range from −12.8% in the temperate continental zone up to 61.1% on the Tibetan Plateau; however, the ESMs differed markedly regarding their climate contribution to GPP change. Although precipitation has a higher sensitivity coefficient, temperature generally plays a more important role in GPP change, primarily because of the larger relative change in temperature in comparison with that of precipitation. Full article

(This article belongs to the Special Issue Sustainability with Changing Climate and Extremes)

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11 pages, 7396 KiB

Open AccessArticle

Changes in the Frequency of Extreme Cooling Events in Winter over China and Their Relationship with Arctic Oscillation

by Shuaifeng Song and Xiaodong Yan

Sustainability 2021, 13(20), 11491; https://doi.org/10.3390/su132011491 - 18 Oct 2021

Cited by 5 | Viewed by 1472

Abstract

Extreme weather and climate events are becoming increasingly frequent and have gained an increasing amount of attention. Extreme cooling (EC) events are a major challenge to socioeconomic sustainability and human health. Based on meteorological stations and NCEP/NCAR reanalysis data, this study analyzed the [...] Read more.

Extreme weather and climate events are becoming increasingly frequent and have gained an increasing amount of attention. Extreme cooling (EC) events are a major challenge to socioeconomic sustainability and human health. Based on meteorological stations and NCEP/NCAR reanalysis data, this study analyzed the temporal and spatial distributions of EC events in winter in China by using the relative threshold and the relationship between EC events and the Arctic Oscillation (AO) index during the period of 1961–2017. The results show that the frequency of EC events in China decreased by 0.730 d in these 57 years, with a trend of −0.1 d/10 y. Northeast China had the highest frequency of EC events in winter, with an average of 4 d. In addition, EC events are significantly negatively correlated with the AO index in China, with a correlation coefficient of −0.5, and the AO index accounts for approximately 21% of the EC event variance. The strongest correlations are mainly located in Northwest China. Our research shows that significant changes in the mid–high latitude atmospheric circulation anomalies, which are associated with the AO, are responsible for EC events. These findings provide theoretical guidance for the prediction and simulation of EC events. Full article

(This article belongs to the Special Issue Sustainability with Changing Climate and Extremes)

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16 pages, 5363 KiB

Open AccessArticle

Locomotion of Slope Geohazards Responding to Climate Change in the Qinghai-Tibetan Plateau and Its Adjacent Regions

by Yiru Jia, Jifu Liu, Lanlan Guo, Zhifei Deng, Jiaoyang Li and Hao Zheng

Sustainability 2021, 13(19), 10488; https://doi.org/10.3390/su131910488 - 22 Sep 2021

Cited by 3 | Viewed by 2033

Abstract

Slope geohazards, which cause significant social, economic and environmental losses, have been increasing worldwide over the last few decades. Climate change-induced higher temperatures and shifted precipitation patterns enhance the slope geohazard risks. This study traced the spatial transference of slope geohazards in the [...] Read more.

Slope geohazards, which cause significant social, economic and environmental losses, have been increasing worldwide over the last few decades. Climate change-induced higher temperatures and shifted precipitation patterns enhance the slope geohazard risks. This study traced the spatial transference of slope geohazards in the Qinghai-Tibet Plateau (QTP) and investigated the potential climatic factors. The results show that 93% of slope geohazards occurred in seasonally frozen regions, 2.6% of which were located in permafrost regions, with an average altitude of 3818 m. The slope geohazards are mainly concentrated at 1493–1988 m. Over time, the altitude of the slope geohazards was gradually increased, and the mean altitude tended to spread from 1984 m to 2562 m by 2009, while the slope gradient varied only slightly. The number of slope geohazards increased with time and was most obvious in spring, especially in the areas above an altitude of 3000 m. The increase in temperature and precipitation in spring may be an important reason for this phenomenon, because the results suggest that the rate of air warming and precipitation at geohazard sites increased gradually. Based on the observation of the spatial location, altitude and temperature growth rate of slope geohazards, it is noted that new geohazard clusters (NGCs) appear in the study area, and there is still a possibility of migration under the future climate conditions. Based on future climate forecast data, we estimate that the low-, moderate- and high-sensitivity areas of the QTP will be mainly south of 30° N in 2030, will extend to the south of 33° N in 2060 and will continue to expand to the south of 35° N in 2099; we also estimate that the proportion of high-sensitivity areas will increase from 10.93% in 2030 to 14.17% in 2060 and 17.48% in 2099. Full article

(This article belongs to the Special Issue Sustainability with Changing Climate and Extremes)

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14 pages, 2801 KiB

Open AccessArticle

Integrated Assessments of Meteorological Hazards across the Qinghai-Tibet Plateau of China

by Shao Sun, Qiang Zhang, Yuanxin Xu and Ruyue Yuan

Sustainability 2021, 13(18), 10402; https://doi.org/10.3390/su131810402 - 17 Sep 2021

Cited by 8 | Viewed by 3872

Abstract

Recent decades have witnessed accelerated climate changes across the Qinghai-Tibet Plateau (QTP) and elevated socioeconomic exposure to meteorological hazards. The QTP is called the “the third pole”, exerting remarkable impact on environmental changes in its surrounding regions. While few reports are available for [...] Read more.

Recent decades have witnessed accelerated climate changes across the Qinghai-Tibet Plateau (QTP) and elevated socioeconomic exposure to meteorological hazards. The QTP is called the “the third pole”, exerting remarkable impact on environmental changes in its surrounding regions. While few reports are available for addressing multi-hazard risks over the QTP, we develop an integrated indicator system involving multiple meteorological hazards, i.e., droughts, rainstorms, snowstorms and hailstorms, investigating the spatiotemporal patterns of major hazards over the QTP. The hazard zones of droughts and rainstorms are identified in the southern Gangdise Mountains, the South Tibet Valley, the eastern Nyenchen-Tanglha Mountains, the Hengduan Mountains and West Sichuan Basin. Snowstorm hazard zones distribute in the Himalayas, the Bayan Har Mountains and the central Nyenchen-Tanglha Mountains, while hailstorm hazard zones cluster in central part of the QTP. Since the 21st century, intensified rainstorms are detectable in the densely populated cities of Xining and Lhasa and their adjacent areas, while amplified droughts are observed in grain production areas of the South Tibet Valley and the Hengduan Mountains. Snowstorm hazards show large interannual variations and an increase in pastoral areas, although the overall trend is declining slightly. The frequency of hailstorms gradually decreases in human settlements due to thermal and landscape effects. Mapping meteorological hazards regionalization could help to understand climate risks in the QTP, and provide scientific reference for human adaptation to climate changes in highly sensitive areas. Full article

(This article belongs to the Special Issue Sustainability with Changing Climate and Extremes)

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15 pages, 2190 KiB

Open AccessArticle

The Impact on Carbon Emissions of China with the Trade Situation versus the U.S.

by Jieming Chou, Fan Yang, Zhongxiu Wang and Wenjie Dong

Sustainability 2021, 13(18), 10324; https://doi.org/10.3390/su131810324 - 15 Sep 2021

Cited by 3 | Viewed by 2074

Abstract

The China–US trade conflict will inevitably have a negative impact on China’s trade imports and exports, industrial development, and economic growth, and will affect the achievement of climate change goals. In the short term, the impact of the trade conflict on China’s import [...] Read more.

The China–US trade conflict will inevitably have a negative impact on China’s trade imports and exports, industrial development, and economic growth, and will affect the achievement of climate change goals. In the short term, the impact of the trade conflict on China’s import and export trade will cause the carbon emissions contained in traded commodities to change accordingly. To assess the impact of the trade conflict on China’s climate policy, this paper combines a model from the Global Trade Analysis Project (GTAP) and the input–output analysis method and calculates the carbon emissions in international trade before and after the conflict. The conclusions are as follows: (1) The trade war has led to a sharp decline in China–US trade, but for China as a whole, imports and exports have not changed much; (2) China’s export emissions have changed little, its import emissions have dropped slightly, and its net emissions have increased; and (3) China’s exports are still concentrated in energy-intensive industries. Changes in trade will bring challenges to China’s balancing of climate and trade exigencies. China–US cooperation based on energy and technology will help China cope with climate change after the trade conflict. Full article

(This article belongs to the Special Issue Sustainability with Changing Climate and Extremes)

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