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Atmosphere
Special Issues
Extreme Weather, Air Pollution, and Human Health
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Extreme Weather, Air Pollution, and Human Health

A special issue of Atmosphere (ISSN 2073-4433). This special issue belongs to the section "Air Quality and Health".

Deadline for manuscript submissions: closed (30 November 2021) | Viewed by 20430

Special Issue Editors

Dr. Jun Yang

E-Mail Website
Guest Editor
Institute for Environmental and Climate Research, Jinan University, Guangzhou 510632, China
Interests: environmental epidemiology and biostatistics; climate change; extreme weather; air pollution; public health
Dr. Wenjun Ma

E-Mail Website1 Website2
Guest Editor
Public Health and Preventive Medicine, School of Medicine, Jinan University, Guangzhou, China
Interests: climate change; air pollution; health risk assessment
Special Issues, Collections and Topics in MDPI journals
Dr. Wei Ma

E-Mail Website
Guest Editor
1. Department of Epidemiology, School of Public Health, Shandong University, Jinan 250012, China
2. Shandong University Climate Change and Health Center, Jinan 250012, China
Interests: epidemiology; climate change; extreme weather; infectious diseases
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Extreme weather and air pollution are two leading environmental health stressors, which annually cause millions of premature deaths worldwide, according to recent reports on the global burden of disease and climate risk index. Under climate change, the frequency and severity of extreme weather events are projected to be significantly enhanced in future, and air quality worsens. Previous studies have mainly linked extreme weather and air pollution to excess mortality and morbidity of non-external cause. However, evidence is still scarce on other susceptible health outcomes, such as injury, mental health, and infectious diseases. The synergistic health effects among these environmental stressors are also unclear.

This Special Issue aims to present new articles or reviews on the health risks of both extreme weather and air pollution. Topics to be covered include but are not limited to the following:

(1) Health risk assessment of air pollution, particularly indoor air pollution;

(2) Health risk assessment of extreme weather, particularly compound extremes;

(3) Projection of health risks of extreme weather and air pollution under climate change scenarios;

(4) Synergistic health effects of air pollution with extreme weather conditions (such as extreme temperature and humidity);

(5) Health benefits of mitigation and adaptation to air pollution and extreme weather;

(6) New methods for air pollution exposure assessment;

(7) Health warning of air pollution and extreme weather events.

Dr. Jun Yang
Prof. Dr. Wenjun Ma
Dr. Wei Ma
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Atmosphere is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2400 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • Extreme weather
  • Air pollution
  • Climate change
  • Human health
  • Synergistic effects
  • Environmental exposure

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Published Papers (6 papers)

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Research

21 pages, 8747 KiB  
Article
Assessment of Climate-Driven Variations in Malaria Transmission in Senegal Using the VECTRI Model
by Papa Fall, Ibrahima Diouf, Abdoulaye Deme and Doudou Sene
Atmosphere 2022, 13(3), 418; https://doi.org/10.3390/atmos13030418 - 3 Mar 2022
Cited by 11 | Viewed by 4363
Abstract
Several vector-borne diseases, such as malaria, are sensitive to climate and weather conditions. When unusual conditions prevail, for example, during periods of heavy rainfall, mosquito populations can multiply and trigger epidemics. This study, which consists of better understanding the link between malaria transmission [...] Read more.
Several vector-borne diseases, such as malaria, are sensitive to climate and weather conditions. When unusual conditions prevail, for example, during periods of heavy rainfall, mosquito populations can multiply and trigger epidemics. This study, which consists of better understanding the link between malaria transmission and climate factors at a national level, aims to validate the VECTRI model (VECtor borne disease community model of ICTP, TRIeste) in Senegal. The VECTRI model is a grid-distributed dynamical model that couples a biological model for the vector and parasite life cycles to a simple compartmental Susceptible-Exposed-Infectious-Recovered (SEIR) representation of the disease progression in the human host. In this study, a VECTRI model driven by reanalysis data (ERA-5) was used to simulate malaria parameters, such as the entomological inoculation rate (EIR) in Senegal. In addition to the ERA5-Land daily reanalysis rainfall, other daily rainfall data come from different meteorological products, including the CPC Global Unified Gauge-Based Analysis of Daily Precipitation (CPC for Climate Prediction Center), satellite data from the African Rainfall Climatology 2.0 (ARC2), and the Climate Hazards InfraRed Precipitation with Station data (CHIRPS). Observed malaria data from the National Malaria Control Program in Senegal (PNLP/Programme National de Lutte contre le Paludisme au Senegal) and outputs from the climate data used in this study were compared. The findings highlight the unimodal shape of temporal malaria occurrence, and the seasonal malaria transmission contrast is closely linked to the latitudinal variation of the rainfall, showing a south–north gradient over Senegal. This study showed that the peak of malaria takes place from September to October, with a lag of about one month from the peak of rainfall in Senegal. There is an agreement between observations and simulations about decreasing malaria cases on time. These results indicate that the southern area of Senegal is at the highest risk of malaria spread outbreaks. The findings in the paper are expected to guide community-based early-warning systems and adaptation strategies in Senegal, which will feed into the national malaria prevention, response, and care strategies adapted to the needs of local communities. Full article
(This article belongs to the Special Issue Extreme Weather, Air Pollution, and Human Health)
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21 pages, 4196 KiB  
Article
Effect of the Near-Future Climate Change under RCP8.5 on the Heat Stress and Associated Work Performance in Thailand
by Teerachai Amnuaylojaroen, Atsamon Limsakul, Sukrit Kirtsaeng, Nichapa Parasin and Vanisa Surapipith
Atmosphere 2022, 13(2), 325; https://doi.org/10.3390/atmos13020325 - 15 Feb 2022
Cited by 19 | Viewed by 4365
Abstract
Increased heat stress affects well-being, comfort, and economic activities across the world. It also causes a significant decrease in work performance, as well as heat-related mortality. This study aims to investigate the impacts of the projected climate change scenario under RCP8.5 on heat [...] Read more.
Increased heat stress affects well-being, comfort, and economic activities across the world. It also causes a significant decrease in work performance, as well as heat-related mortality. This study aims to investigate the impacts of the projected climate change scenario under RCP8.5 on heat stress and associated work performance in Thailand during the years 2020–2029. The model evaluation shows exceptional performance in the present-day simulation (1990–1999) of temperature and relative humidity, with R2 values ranging from 0.79 to 0.87; however, the modeled temperature and relative humidity are all underestimated when compared to observation data by −0.9 °C and −27%, respectively. The model results show that the temperature change will tend to increase by 0.62 °C per decade in the future. This could lead to an increase in the heat index by 2.57 °C if the temperature increases by up to 1.5 °C in Thailand. The effect of climate change is predicted to increase heat stress by 0.1 °C to 4 °C and to reduce work performance in the range of 4% to >10% across Thailand during the years 2020 and 2029. Full article
(This article belongs to the Special Issue Extreme Weather, Air Pollution, and Human Health)
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14 pages, 2087 KiB  
Article
Trend Analysis and Spatial Distribution of Meteorological Disaster Losses in China, 2004–2015
by Qian Qi, Baofa Jiang, Wei Ma and Gifty Marley
Atmosphere 2022, 13(2), 208; https://doi.org/10.3390/atmos13020208 - 27 Jan 2022
Cited by 6 | Viewed by 2654
Abstract
Meteorological disasters caused a lot of losses. We involved six categories (all disasters, floods, hail, typhoon, snow and heatwave) to observe their death and economic losses’ spatial-time distribution. The time trend of mortality was analyzed using a chi-square test for linear trends. Economic [...] Read more.
Meteorological disasters caused a lot of losses. We involved six categories (all disasters, floods, hail, typhoon, snow and heatwave) to observe their death and economic losses’ spatial-time distribution. The time trend of mortality was analyzed using a chi-square test for linear trends. Economic loss was described by direct economic loss and loss rate of GDP, whose trends were described by a trend line. Using annual percent change (APC) estimated by fitting weighted linear regression model, the change degree of mortality was assessed. On a national level, there was a statistically significant decreasing trend in mortality of all disasters (Z = −39.82, p < 0.05), floods (Z = −18.79, p < 0.05), hail (Z = −20.43, p < 0.05), typhoon (Z = −37.47, p < 0.05), snow (Z = −9.02, p < 0.05) and heatwave (Z = −8.76, p < 0.05) from 2004 to 2015 in China. The time trend of the loss rate of GDP was decreasing while the trend of direct economic losses was increasing. Western China was the most seriously hit area. APCs remained in downward trends (APCs < 0) in most of the provinces, while central provinces were with upward trends (APCs > 0). Areas with increasing mortality (APCs > 0) for different disasters included the southwest areas and Zhejiang (for floods), the northwest and south areas (for hail), Sichuan, Guangxi and Hainan (for typhoon), the west and northeast areas (for snow) and Hebei, Henan and Shanghai (for heatwave). As for economic losses, eastern areas were hit with a high amount of economic losses, but central areas were hit with a high GDP loss rate. Generally, nationwide death and economic losses caused by meteorological disasters have decreased. However, there were some relatively serious effects in the central and western areas for which urgent attention from policymakers is required. Full article
(This article belongs to the Special Issue Extreme Weather, Air Pollution, and Human Health)
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18 pages, 39661 KiB  
Article
Potential Contribution of Climate Conditions on COVID-19 Pandemic Transmission over West and North African Countries
by Ibrahima Diouf, Souleymane Sy, Habib Senghor, Papa Fall, Diarra Diouf, Moussa Diakhaté, Wassila M. Thiaw and Amadou T. Gaye
Atmosphere 2022, 13(1), 34; https://doi.org/10.3390/atmos13010034 - 27 Dec 2021
Cited by 6 | Viewed by 3957
Abstract
COVID-19, caused by the Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2), is a very contagious disease that has killed many people worldwide. According to data from the World Health Organization (WHO), the spread of the disease appears to be slower in Africa. Although [...] Read more.
COVID-19, caused by the Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2), is a very contagious disease that has killed many people worldwide. According to data from the World Health Organization (WHO), the spread of the disease appears to be slower in Africa. Although several studies have been published on the relationship between meteorological parameters and COVID-19 transmission, the effects of climate conditions on COVID-19 remain largely unexplored and without consensus. However, the transmission of COVID-19 and sensitivity to climate conditions are also not fully understood in Africa. Here, using available epidemiological data over 275 days (i.e., from 1 March to 30 November 2020) taken from the European Center for Disease Prevention and Control of the European Union database and daily data of surface air temperature specific humidity and water vapor from the National Center for Environmental Prediction (NCEP), this paper investigates the potential contribution of climate conditions on COVID-19 transmission over 16 selected countries throughout three climatic regions of Africa (i.e., Sahel, Maghreb, and Gulf of Guinea). The results highlight statistically significant inverse correlations between COVID-19 cases and temperature over the Maghreb and the Gulf of Guinea regions. In contrast, positive correlations are found over the Sahel area, especially in the central part, including Niger and Mali. Correlations with specific humidity and water vapor parameters display significant and positive values over the Sahelian and the Gulf of Guinea countries and negative values over the Maghreb countries. Then, the COVID-19 pandemic transmission is influenced differently across the three climatic regions: (i) cold and dry environmental conditions over the Maghreb; (ii) warm and humid conditions over the Sahel; and (iii) cold and humid conditions over the Gulf of Guinea. In addition, for all three climatic regions, even though the climate impact has been found to be significant, its effect appears to display a secondary role based on the explanatory power variance compared to non-climatic factors assumed to be dominated by socio-economic factors and early strong public health measures. Full article
(This article belongs to the Special Issue Extreme Weather, Air Pollution, and Human Health)
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11 pages, 1735 KiB  
Article
A New Method to Estimate Heat Exposure Days and Its Impacts in China
by Guizhen Guo, Dandan Wang, Zhoupeng Ren, Qian Yin and Yunbing Gao
Atmosphere 2021, 12(10), 1294; https://doi.org/10.3390/atmos12101294 - 5 Oct 2021
Cited by 1 | Viewed by 1856
Abstract
Understanding the spatiotemporal trends of temperature in the context of global warming is significant for public health. Although many studies have examined changes in temperature and the impacts on human health over the past few decades in many regions, they have often been [...] Read more.
Understanding the spatiotemporal trends of temperature in the context of global warming is significant for public health. Although many studies have examined changes in temperature and the impacts on human health over the past few decades in many regions, they have often been carried out in data-rich regions and have rarely considered acclimatization explicitly. The most frequent temperature (MFT) indicator provides us with the ability to solve this problem. MFT is defined as the longest period of temperature throughout the year to which a human is exposed and therefore acclimates. In this study, we propose a new method to estimate the number of heat exposure days from the perspective of temperature distribution and MFT, based on the daily mean temperature readings of 2142 weather stations in eight major climate zones in China over the past 20 years. This method can be used to calculate the number of heat exposure days in terms of heat-related mortality risk without the need for mortality data. We estimated the distribution and changes of annual mean temperature (AMT), minimum mortality temperature (MMT), and the number of heat exposure days in different climate zones in China. The AMT, MMT, and number of heat exposure days vary considerably across China. They all tend to decrease gradually from low to high latitudes. Heat exposure days are closely related to the risk of heat-related mortality. In addition, we utilized multiple linear regression (MLR) to analyze the association between the risk of heat-related mortality and the city and its climatic characteristics. Results showed that the number of heat exposure days, GDP per capita, urban population ratio, proportion of elderly population, and climate zone were found to modify the estimate on heat effect, with an R2 of 0.71. These findings will be helpful for the creation of public policies protecting against high-temperature-induced mortalities. Full article
(This article belongs to the Special Issue Extreme Weather, Air Pollution, and Human Health)
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20 pages, 1095 KiB  
Article
A Novel Framework for Forecasting, Evaluation and Early-Warning for the Influence of PM10 on Public Health
by Wendong Yang, Guolin Tang, Yan Hao and Jianzhou Wang
Atmosphere 2021, 12(8), 1020; https://doi.org/10.3390/atmos12081020 - 9 Aug 2021
Cited by 6 | Viewed by 2060
Abstract
PM2.5 has attracted widespread attention since the public has become aware of it, while attention to PM10 has started to wane. Considering the significance of PM10, this study takes PM10 as the research object and raises a significant [...] Read more.
PM2.5 has attracted widespread attention since the public has become aware of it, while attention to PM10 has started to wane. Considering the significance of PM10, this study takes PM10 as the research object and raises a significant question: when will the influence of PM10 on public health end? To answer the abovementioned question, two promising research areas, i.e., air pollution forecasting and health effects analysis, are employed, and a novel hybrid framework is developed in this study, which consists of one effective model and one evaluation model. More specifically, this study first introduces one advanced optimization algorithm and cycle prediction theory into the grey forecasting model to develop an effective model for multistep forecasting of PM10, which can achieve reasonable forecasting of PM10. Then, an evaluation model is designed to evaluate the health effects and economic losses caused by PM10. Considering the significance of providing the future impact of PM10 on public health, we extend our forecasting results to evaluate future changes in health effects and economic losses based on our proposed health economic losses evaluation model. Accordingly, policymakers can adjust current air pollution prevention plans and formulate new plans according to the results of forecasting, evaluation and early-warning. Empirical research shows that the developed framework is applicable in China and may become a promising technique to enrich the current research and meet the requirements of air quality management and haze governance. Full article
(This article belongs to the Special Issue Extreme Weather, Air Pollution, and Human Health)
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