Atmosphere

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21 pages, 3729 KiB

Open AccessArticle

Differential Impacts on Human Physiological Responses on Heatwave and Non-Heatwave Days: A Comparative Study Using Wearable Devices in Beijing

by Tong Sheng, Qi Liu, Yumeng Kou, Guole Shang and Miaomiao Xie

Atmosphere 2025, 16(4), 413; https://doi.org/10.3390/atmos16040413 - 1 Apr 2025

Viewed by 290

Abstract

As global warming intensifies heatwave events, their impact on human health is becoming increasingly significant. To further understand the dynamic response of humans to heatwaves, this study selected samples from different age groups under various thermal conditions in Beijing, China. Physiological parameters, including [...] Read more.

As global warming intensifies heatwave events, their impact on human health is becoming increasingly significant. To further understand the dynamic response of humans to heatwaves, this study selected samples from different age groups under various thermal conditions in Beijing, China. Physiological parameters, including blood pressure, blood glucose, heart rate, blood oxygen, and body temperature, were monitored during both heatwave and non-heatwave periods using wearable devices. The results show that during heatwaves, the average blood pressure increased by about 10%, blood glucose levels rose by about 4%, heart rates increased by about 12%, and blood oxygen levels decreased by an average of about 7%. These effects were particularly pronounced in people aged 50 and above, with heart rate and blood oxygen saturation showing significant age-related differences. The study indicates that heat waves have a more substantial impact on the elderly population, with age being a key factor in determining physiological responses to extreme heat. Therefore, it is necessary to develop age-specific health management strategies to address vulnerability under high-temperature conditions. Full article

(This article belongs to the Special Issue Climate Change and Extreme Weather Disaster Risks)

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16 pages, 5643 KiB

Open AccessArticle

Changes in the Distribution of Precipitation with the Potential to Cause Extreme Events in the State of Rio de Janeiro for a Future Climate Change Scenario

by Wanderley Philippe Cardoso Ferreira, Henderson Silva Wanderley and Rafael Coll Delgado

Atmosphere 2025, 16(4), 358; https://doi.org/10.3390/atmos16040358 - 21 Mar 2025

Viewed by 268

Abstract

Climate change can alter the frequency and magnitude of extreme precipitation events (EPEs), both in terms of scarcity and excess, impacting society as a whole. The aim of this study was, therefore, to identify changes in the distribution of precipitation with the potential [...] Read more.

Climate change can alter the frequency and magnitude of extreme precipitation events (EPEs), both in terms of scarcity and excess, impacting society as a whole. The aim of this study was, therefore, to identify changes in the distribution of precipitation with the potential to cause extreme events in the state of Rio de Janeiro (SRJ) for current and future climate change scenarios. Climate change indices were selected that refer to changes in the distribution and magnitude of rainfall events for the state of Rio de Janeiro. The analysis was carried out for the historical period between 2000 and 2020 and for future climate change scenarios between the years 2021 and 2100. The analysis for future climate change scenarios was carried out using data from climate models of the general circulation of the atmosphere (CMIP-6) for future climate change scenarios SSP 4.5 and SSP 8.5. Total annual precipitation in the SRJ by the end of the 21st century will be reduced by between 24% and 47% for the intermediate and pessimistic scenarios, respectively. The projections also indicate an increase in the number of consecutive dry days, which could be greater than 130% in the pessimistic scenario, and a reduction in consecutive wet days. An increase in the number of humid and extremely humid days is also projected for the SRJ, which could increase the EPEs. Full article

(This article belongs to the Special Issue Climate Change and Extreme Weather Disaster Risks)

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14 pages, 5435 KiB

Open AccessArticle

Fault Risk Assessment of Transmission Lines Under Extreme Weather Conditions Based on Genetic Algorithm Back-Propagation Neural Network

by Jialu Li, Ruilin Lei, Yongqiang Gao, Aoyu Lei, Junqiu Fan, Yong Mei, Wenwei Tao, Haohuai Wang, Linzi Wang, Taiji Li and Qiansheng Zhao

Atmosphere 2025, 16(3), 282; https://doi.org/10.3390/atmos16030282 - 27 Feb 2025

Viewed by 547

Abstract

In the context of global climate change environment, China’s power grid is faced with many extreme weather challenges, especially the southern China power grid region, which faces typhoons, torrential rain, high temperature, drought, frost and other disasters that greatly affect the safe and [...] Read more.

In the context of global climate change environment, China’s power grid is faced with many extreme weather challenges, especially the southern China power grid region, which faces typhoons, torrential rain, high temperature, drought, frost and other disasters that greatly affect the safe and stable operation of the power system and the normal social order in this region. This study proposes a risk assessment model combining a genetic algorithm-optimized neural network (GA-BP) with GIS spatial analysis to evaluate transmission line faults under extreme weather in southern China. Experimental results demonstrate the model’s effectiveness in identifying high-risk regions, with significant correlations between extreme precipitation, prolonged drought, and circuit failures. Full article

(This article belongs to the Special Issue Climate Change and Extreme Weather Disaster Risks)

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21 pages, 4993 KiB

Open AccessArticle

The Spatiotemporal Evolution of Geo-Disaster Resilience in China and the Impact Mechanism of Environmental Governance

by Hao Zhu, Xing Zhu, Yong Li, Yibin Ao, Xugong Jia, Panyu Peng, Mingyang Li and Jiayue Li

Atmosphere 2025, 16(3), 247; https://doi.org/10.3390/atmos16030247 - 21 Feb 2025

Viewed by 427

Abstract

The increasing frequency of extreme climate events has posed severe challenges to China’s socio-economic development and ecological environment due to geological disasters. Therefore, there is an urgent need for effective adaptive strategies to enhance geo-disaster resilience. Environmental governance, as an effective measure to [...] Read more.

The increasing frequency of extreme climate events has posed severe challenges to China’s socio-economic development and ecological environment due to geological disasters. Therefore, there is an urgent need for effective adaptive strategies to enhance geo-disaster resilience. Environmental governance, as an effective measure to reduce risks from extreme climates and disasters while promoting high-quality social development, remains underexplored in terms of its impact on geo-disaster resilience. This study innovatively constructs a resilience assessment framework that considers extreme climate and geo-disaster intensity, integrating various statistical methods, including the Super-Efficiency Slacks-Based Measure Data Envelopment Analysis (SBM-DEA) model, spatial Markov chains, and methods such as Geodetector and the Geographically and Temporally Weighted Regression (GTWR), to reveal the spatiotemporal evolution of geo-disaster resilience in China from 2007 to 2022, while also analyzing the mechanisms through which environmental governance influences resilience and its spatiotemporal variations. The findings indicate that China’s geo-disaster resilience exhibits unstable growth with significant regional disparities. Spatially, resilience shows notable spillover effects and a tendency toward convergence within similar regions. Environmental governance unevenly enhances resilience over time and space: soil and water conservation and afforestation are generally effective measures, while the contributions of ecological water replenishment, environmental facility management personnel, fiscal expenditure, and nature reserve protection vary by region. This research offers key insights into improving geo-disaster resilience and optimizing environmental governance strategies to enhance China’s disaster response capacity and regional sustainable development. Full article

(This article belongs to the Special Issue Climate Change and Extreme Weather Disaster Risks)

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14 pages, 3566 KiB

Open AccessArticle

Asymmetrical Time-Lagged Response of Vegetation to Drought and Extreme Precipitation Across China

by Wenli Lai, Yongxiang Chen, Jie Zhang and Huai Yang

Atmosphere 2025, 16(3), 240; https://doi.org/10.3390/atmos16030240 - 20 Feb 2025

Viewed by 420

Abstract

In this study, a study area was chosen in China to analyze the lagged response relationship between normalized difference vegetation index (NDVI) and extreme precipitation/drought from 1982 to 2015. A logistical function was applied to explain the increase in NDVI with mean annual [...] Read more.

In this study, a study area was chosen in China to analyze the lagged response relationship between normalized difference vegetation index (NDVI) and extreme precipitation/drought from 1982 to 2015. A logistical function was applied to explain the increase in NDVI with mean annual precipitation in nine sub-regions, and the inflection point of precipitation was found to be very close to the threshold value for separating arid or humid regions. NDVI had a strong positive correlation with drought and extreme precipitation in the arid regions, while in humid regions, it presented a strong correlation with drought during 2000–2015; however, a weak correlation with drought was found before the 21st century. In this study, we quantified the time-lagged response of vegetation to drought (LTRD) and extreme precipitation (LTREP). Then, we defined four gradients (

\frac{\partial L T R D}{\partial P}

,

\frac{\partial L T R D}{\partial T}

,

\frac{\partial L T R E P}{\partial P}

, and

\frac{\partial L T R E P}{\partial T}

) to quantify the precipitation and temperature gradients with the lag-time response to drought or extreme precipitation, respectively. Decreasing gradients were observed for humid regions with

\frac{\partial L T R D}{\partial P}

= −0.19 month·100 mm⁻¹ for “wetting” and

\frac{\partial L T R D}{\partial T}

= −0.13 month·K⁻¹ for “warming”, while increasing gradients were found in the same regions with

\frac{\partial L T R E P}{\partial P}

= +0.18 month·100 mm⁻¹ for “wetting” and

\frac{\partial L T R E P}{\partial T}

= +0.14 month·K⁻¹ for “warming”. These results suggest that the lagging responses of vegetation to extreme precipitation and droughts exhibit opposing regional patterns across China. Full article

(This article belongs to the Special Issue Climate Change and Extreme Weather Disaster Risks)

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24 pages, 6645 KiB

Open AccessArticle

Assessing the Impacts of Transition and Physical Climate Risks on Industrial Metal Markets: Evidence from the Novel Multivariate Quantile-on-Quantile Regression

by Ousama Ben-Salha, Mourad Zmami, Sami Sobhi Waked, Bechir Raggad, Faouzi Najjar and Yazeed Mohammad Alenazi

Atmosphere 2025, 16(2), 233; https://doi.org/10.3390/atmos16020233 - 18 Feb 2025

Cited by 1 | Viewed by 563

Abstract

Climate change and global warming have been shown to increase the frequency and intensity of extreme weather events. Concurrently, substantial efforts are being directed toward fostering the transition to a low-carbon economy. These concurrent trends result in the emergence of both physical and [...] Read more.

Climate change and global warming have been shown to increase the frequency and intensity of extreme weather events. Concurrently, substantial efforts are being directed toward fostering the transition to a low-carbon economy. These concurrent trends result in the emergence of both physical and transition climate risks. This study investigates the impacts of climate risks, both physical and transition, on the return of major industrial metals (aluminum, copper, iron, lead, tin, nickel, and zinc) between January 2005 and December 2023. Employing the novel multivariate quantile-on-quantile regression (m-QQR) approach, this study examines how climate risks affect metal markets under different market conditions and risk levels. The results reveal that transition risks exert a more significant adverse impact on metal returns during bearish markets conditions, particularly for metals linked to high-emission industries, while physical risks affect metal returns across a wider range of quantiles, often increasing volatility during extreme market conditions. Furthermore, copper and nickel, both of which are crucial for renewable energy development, demonstrate resilience at higher quantiles, highlighting their role in the transition to a low-carbon economy. Finally, these two metals may serve as effective hedges against losses in other metals that are more vulnerable to transition risks, like aluminum and lead. Full article

(This article belongs to the Special Issue Climate Change and Extreme Weather Disaster Risks)

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17 pages, 8843 KiB

Open AccessArticle

Temporal and Spatial Pattern of Pulmonary Tuberculosis in Gansu Province and Its Environmental Factors Detection and Analysis

by Haili Zhao, Jun Wang and Minghui Wu

Atmosphere 2025, 16(1), 55; https://doi.org/10.3390/atmos16010055 - 8 Jan 2025

Viewed by 670

Abstract

As one of the major public health security issues, pulmonary tuberculosis had a global death rate of 1.6 million in 2021 alone, ranking 13th in the world, posing a great threat to society and families. Analyzing the temporal and spatial distribution and evolution [...] Read more.

As one of the major public health security issues, pulmonary tuberculosis had a global death rate of 1.6 million in 2021 alone, ranking 13th in the world, posing a great threat to society and families. Analyzing the temporal and spatial distribution and evolution trend of tuberculosis, discussing the exposure factors and studying the environmental background that affects the incidence can provide the basis for accurate prevention and control and promote the healthy and stable development of society. Based on the county scale, this study determined the high-incidence areas through hot spot analysis and selected nine districts and counties covering meteorological stations and air monitoring stations. The explanatory power of each factor to the incidence of pulmonary tuberculosis was analyzed by geographical detector, and the main influencing factors were explored. The results show that the following: (1) The number and incidence of pulmonary tuberculosis in Gansu Province declined from 2020 to 2022. (2) The influence of meteorological conditions such as temperature, precipitation and air pressure on pulmonary tuberculosis in different regions shows significant regional differences. Although the meteorological influence in adjacent regions shows certain convergence, the change in wind speed has no significant influence on the risk of pulmonary tuberculosis. (3) PM₁₀, altitude, temperature, population density and GDP per capita have strong explanatory power to the incidence of tuberculosis, and the interaction between any two factors exceeds the effect of a single factor in explanatory power, showing the characteristics of two-factor enhancement and nonlinear enhancement. Full article

(This article belongs to the Special Issue Climate Change and Extreme Weather Disaster Risks)

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21 pages, 11587 KiB

Open AccessArticle

Intensification of Natural Disasters in the State of Pará and the Triggering Mechanisms Across the Eastern Amazon

by Everaldo B. de Souza, Douglas B. S. Ferreira, Luciano J. S. Anjos, Alan C. Cunha, João Athaydes Silva, Jr., Eliane C. Coutinho, Adriano M. L. Sousa, Paulo J. O. P. Souza, Waleria P. Monteiro Correa, Thaiane S. Silva Dias, Alexandre M. C. do Carmo, Carlos B. B. Gutierrez, Giordani R. C. Sodré, Aline M. M. Lima, Edson J. P. Rocha, Bergson C. Moraes, Luciano P. Pezzi and Tercio Ambrizzi

Atmosphere 2025, 16(1), 7; https://doi.org/10.3390/atmos16010007 - 25 Dec 2024

Cited by 1 | Viewed by 974

Abstract

Based on statistical analyses applied to official data from the Digital Atlas of Disasters in Brazil over the last 25 years, we evidenced a consistent intensification in the annual occurrence of natural disasters in the state of Pará, located in the eastern Brazilian [...] Read more.

Based on statistical analyses applied to official data from the Digital Atlas of Disasters in Brazil over the last 25 years, we evidenced a consistent intensification in the annual occurrence of natural disasters in the state of Pará, located in the eastern Brazilian Amazon. The quantitative comparison between the averages of the most intense period of disasters (2017 to 2023) and the earlier years (1999 to 2016) revealed a remarkable percentage increase of 473%. Approximately 81% of the state’s municipalities were affected, as indicated by disaster mapping. A clear seasonal pattern was observed, with Hydrological disasters (Inundations, Flash floods, and Heavy rainfall) peaking between February and May, while Climatological disasters (Droughts and Forest fires) were most frequent from August to October. The catastrophic impacts on people and the economy were documented, showing a significant rise in the number of homeless individuals and those directly affected, alongside considerable material damage and economic losses for both the public and private sectors. Furthermore, we conducted a comprehensive composite analysis on the tropical ocean–atmosphere dynamic structure that elucidated the various triggering mechanisms of disasters arising from Inundations, Droughts, and Forest fires (on seasonal scale), and Flash floods and Heavy rainfall (on sub-monthly scale) in Pará. The detailed characterization of disasters on a municipal scale is relevant in terms of the scientific contribution applied to the strategic decision-making, planning, and implementation of public policies aimed at early risk management (rather than post-disaster response), which is critical for safeguarding human well-being and strengthening the resilience of Amazonian communities vulnerable to climate change. Full article

(This article belongs to the Special Issue Climate Change and Extreme Weather Disaster Risks)

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14 pages, 2866 KiB

Open AccessArticle

Greenland Wind-Wave Bivariate Dynamics by Gaidai Natural Hazard Spatiotemporal Evaluation Approach

by Oleg Gaidai, Shicheng He, Alia Ashraf, Jinlu Sheng and Yan Zhu

Atmosphere 2024, 15(11), 1357; https://doi.org/10.3390/atmos15111357 - 12 Nov 2024

Cited by 7 | Viewed by 716

Abstract

The current work presents a case study for the state-of-the-art multimodal risk assessment approach, which is especially appropriate for environmental wind-wave dynamic systems that are either directly physically observed or numerically modeled. High dimensionality of the wind-wave environmental system and cross-correlations between its [...] Read more.

The current work presents a case study for the state-of-the-art multimodal risk assessment approach, which is especially appropriate for environmental wind-wave dynamic systems that are either directly physically observed or numerically modeled. High dimensionality of the wind-wave environmental system and cross-correlations between its primary dimensions or components make it quite challenging for existing reliability methods. The primary goal of this investigation has been the application of a novel multivariate hazard assessment methodology to a combined windspeed and correlated wave-height unfiltered/raw dataset, which was recorded in 2024 by in situ NOAA buoy located southeast offshore of Greenland. Existing hazard/risk assessment methods are mostly limited to univariate or at most bivariate dynamic systems. It is well known that the interaction of windspeeds and corresponding wave heights results in a multimodal, nonstationary, and nonlinear dynamic environmental system with cross-correlated components. Alleged global warming may represent additional factor/covariate, affecting ocean windspeeds and related wave heights dynamics. Accurate hazard/risk assessment of in situ environmental systems is necessary for naval, marine, and offshore structures that operate within particular offshore/ocean zones of interest, susceptible to nonstationary ocean weather conditions. Benchmarking of the novel spatiotemporal multivariate reliability approach, which may efficiently extract relevant information from the underlying in situ field dataset, has been the primary objective of the current work. The proposed multimodal hazard/risk evaluation methodology presented in this study may assist designers and engineers to effectively assess in situ environmental and structural risks for multimodal, nonstationary, nonlinear ocean-driven wind-wave-related environmental/structural systems. The key result of the presented case study lies within the demonstration of the methodological superiority, compared to a popular bivariate copula reliability approach. Full article

(This article belongs to the Special Issue Climate Change and Extreme Weather Disaster Risks)

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24 pages, 4142 KiB

Open AccessArticle

The Impact of Climate Variability on the Livelihoods of Smallholder Farmers in an Agricultural Village in the Wider Belfast Area, Mpumalanga Province, South Africa

by Mashford Zenda, Michael Rudolph and Charis Harley

Atmosphere 2024, 15(11), 1353; https://doi.org/10.3390/atmos15111353 - 11 Nov 2024

Cited by 2 | Viewed by 2551

Abstract

The purpose of this study was to investigate the impact of climate change on smallholder farmers in South Africa, particularly focusing on the relationship between agriculture and weather patterns. Understanding this connection is crucial for helping farmers adapt to changing climate conditions and [...] Read more.

The purpose of this study was to investigate the impact of climate change on smallholder farmers in South Africa, particularly focusing on the relationship between agriculture and weather patterns. Understanding this connection is crucial for helping farmers adapt to changing climate conditions and improve their resilience and sustainability. This research analyses 33 years of climate data (1990–2023) from the Belfast weather station to identify long-term climate trends, seasonal shifts, and the frequency of extreme weather events. Statistical analysis, including the Mann–Kendall test, revealed significant changes in temperature, rainfall, and the intensity of extreme weather events, indicating that climate change is already affecting the region. Specifically, the research highlighted significant damage to agricultural infrastructure, such as greenhouses, due to climate-related wind events. This study emphasises the importance of using digital technologies to monitor weather patterns in real-time, aiding in decision-making, and enhancing agricultural efficiency. Additionally, it calls for further research into the social impacts of climate variability, including its effects on community cohesion, migration, and access to social services among smallholder farmers. These findings provide a foundation for developing effective interventions to support the resilience of smallholder farming communities in the face of climate change. Future studies need to consider how climate variability affects farmers’ abilities to access markets, both in terms of transport and product quality. Full article

(This article belongs to the Special Issue Climate Change and Extreme Weather Disaster Risks)

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21 pages, 1517 KiB

Open AccessEditor’s ChoiceArticle

Global Health Emergencies of Extreme Drought Events: Historical Impacts and Future Preparedness

by Zakaria A. Mani, Amir Khorram-Manesh and Krzysztof Goniewicz

Atmosphere 2024, 15(9), 1137; https://doi.org/10.3390/atmos15091137 - 20 Sep 2024

Cited by 6 | Viewed by 2889

Abstract

This study examines the global health implications of extreme drought events from 2000 to 2023. Utilizing data from the International Disaster Database (EM-DAT), we analyzed the number of people affected and the total deaths attributed to drought. Our findings reveal that over 1.6 [...] Read more.

This study examines the global health implications of extreme drought events from 2000 to 2023. Utilizing data from the International Disaster Database (EM-DAT), we analyzed the number of people affected and the total deaths attributed to drought. Our findings reveal that over 1.6 billion people have been impacted by drought globally, with Southern Asia and Sub-Saharan Africa being the most severely affected regions. India and China account for a significant portion of the affected population, with 688.2 million and 327.35 million impacted people, respectively. Drought-related mortality has also been substantial, with over 24,000 deaths recorded globally, including more than 20,000 in Somalia alone. The study highlights the uneven distribution of drought impacts, underscoring the need for targeted interventions and comprehensive drought preparedness strategies. Our analysis also reveals the critical role of socio-economic factors in exacerbating the health impacts of drought, particularly in regions with inadequate healthcare infrastructure and limited access to resources. This study provides novel insights into the specific health impacts of drought, including the correlation between drought frequency and mortality rates, and offers actionable recommendations for improving future emergency responses and health system preparedness. These recommendations are tailored to address the unique challenges faced by the most vulnerable regions, emphasizing the importance of context-specific strategies to enhance resilience against the growing threat of climate-induced droughts. Full article

(This article belongs to the Special Issue Climate Change and Extreme Weather Disaster Risks)

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18 pages, 15073 KiB

Open AccessArticle

Risk Assessment of Community-Scale High-Temperature and Rainstorm Waterlogging Disasters: A Case Study of the Dongsi Community in Beijing

by Pei Xing, Ruozi Yang, Wupeng Du, Ya Gao, Chunyi Xuan, Jiayi Zhang, Jun Wang, Mengxin Bai, Bing Dang and Feilin Xiong

Atmosphere 2024, 15(9), 1132; https://doi.org/10.3390/atmos15091132 - 18 Sep 2024

Viewed by 898

Abstract

With the advancement of urbanization and acceleration of global warming, extreme weather and climate events are becoming increasingly frequent and severe, and climate risk continues to rise. Each community is irreplaceable and important in coping with extreme climate risk and improving urban resilience. [...] Read more.

With the advancement of urbanization and acceleration of global warming, extreme weather and climate events are becoming increasingly frequent and severe, and climate risk continues to rise. Each community is irreplaceable and important in coping with extreme climate risk and improving urban resilience. In this study, the Dongsi Community in the functional core area of Beijing was explored, and the risk assessment of high temperatures and rainstorm waterlogging was implemented at the community scale. Local navigation observations were integrated into a theoretical framework for traditional disaster risk assessment. The risk assessment indicator system for community-scale high-temperature and rainstorm waterlogging disasters was established and improved from a microscopic perspective (a total of 22 indicators were selected from the three dimensions of hazard, exposure, and vulnerability). Geographic Information Systems (GIS) technology was used to integrate geographic information, meteorological, planning, municipal, socioeconomic and other multisource information layers, thus enabling more detailed spatial distribution characteristics of the hazard, exposure, vulnerability, and risk levels of community-scale high temperatures and rainstorm waterlogging to be obtained. The results revealed that the high-risk area and slightly high-risk area of high-temperature disasters accounted for 13.5% and 15.1%, respectively. The high-risk area and slightly high-risk area of rainstorm waterlogging disasters accounted for 9.8% and 31.6%, respectively. The high-risk areas common to high temperatures and waterlogging accounted for 3.9%. In general, the risk of high-temperature and rainstorm waterlogging disasters at the community scale showed obvious spatial imbalances; that is, the risk in the area around the middle section of Dongsi Santiao was the lowest, while a degree of high temperatures or rainstorm waterlogging was found in other areas. In particular, the risk of high-temperature and rainstorm waterlogging disasters along Dongsi North Street, the surrounding areas of Dongsi Liutiao, and some areas along the Dongsi Jiutiao route was relatively high. These spatial differences were affected to a greater extent by land cover (buildings, vegetation, etc.) and population density within the community. This study is a useful exploration of climate risk research for resilient community construction, and provides scientific support for the planning of climate-adaptive communities, as well as the proposal of overall adaptation goals, action frameworks, and specific planning strategies at the community level. Full article

(This article belongs to the Special Issue Climate Change and Extreme Weather Disaster Risks)

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Review

Jump to: Research

8 pages, 195 KiB

Open AccessReview

Examining the Impact of Climate Change Risks on Pregnancy through a Climate Justice Lens: A Review

by Olivia J. Keenan, Stefania Papatheodorou and Arnab K. Ghosh

Atmosphere 2024, 15(8), 975; https://doi.org/10.3390/atmos15080975 - 14 Aug 2024

Viewed by 1492

Abstract

Climate change impacts such as climate-amplified weather events are increasing in intensity, frequency, and severity. Despite climate change affecting areas all around the world, the adverse impacts of climate change are unequally distributed, causing specific populations to be more susceptible to the impacts [...] Read more.

Climate change impacts such as climate-amplified weather events are increasing in intensity, frequency, and severity. Despite climate change affecting areas all around the world, the adverse impacts of climate change are unequally distributed, causing specific populations to be more susceptible to the impacts of climate change. Addressing climate inequalities in health research requires a climate justice approach, which prioritizes recognitional, distributional, and procedural justice in research and intervention design. Pregnant individuals are particularly vulnerable to climate change impacts since pregnancy represents a time of both psychological and physiological change that can be extremely sensitive to the environment. Nevertheless, there are few studies examining the association between pregnancy health and climate justice. This review evaluates the status of climate change impacts and pregnancy health outcomes through recognitional, distributive, and procedural justice definitions. We identify four themes already present in the literature: 1. Vulnerable Populations Within an Already Vulnerable Population, 2. Need for More Ecological-level Studies, 3. Addressing the Structural Factors that Drive Climate Injustice, and 4. Community-Centered Solutions Moving Forward. Our findings emphasize the importance of transdisciplinary, participatory, and multisectoral collaboration to improve climate-related pregnancy health interventions. Full article

(This article belongs to the Special Issue Climate Change and Extreme Weather Disaster Risks)

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