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  1. Land suitability analysis for turmeric crop for humid tropical Kerala, India, under current and future climate scenarios using advanced geospatial techniques
    Banu M, Krishnamurthy KS, Srinivasan V, Kandiannan K, Surendran U
    J Sci Food Agric, 2024 May;104(7):4176-4188.
    PMID: 38385763 DOI: 10.1002/jsfa.13299
    BACKGROUND: Turmeric cultivation primarily thrives in India, followed by Bangladesh, Cambodia, Thailand, China, Malaysia, Indonesia and the Philippines. India leads globally in both area and production of turmeric. Despite this, there is a recognized gap in research regarding the impact of climate change on site suitability of turmeric. The primary objective of the present study was to evaluate both the present and future suitability of turmeric cultivation within the humid tropical region of Kerala, India, by employing advanced geospatial techniques. The research utilized meteorological data from the Indian Meteorological Department for the period of 1986-2020 as historical data and projected future data from the Coupled Model Intercomparison Project Phase 6 (CMIP6). Four climatic scenarios of shared socioeconomic pathway (SSP) from the Intergovernmental Panel on Climate Change AR6 model of MIROC6 for the year 2050 (SSP 1-2.6, SSP 2-4.5, SSP 3-7.0 and SSP 5-8.5) were used.

    RESULTS: The results showed that suitable area for turmeric cultivation is declining in future scenario and this decline can be primarily attributed to fluctuations in temperature and an anticipated increase in rainfall in the year 2050. Notable changes in the spatial distribution of suitable areas over time were observed through the application of geographic information system (GIS) techniques. Importantly, as per the suitability criteria provided by ICAR-National Bureau of Soil Survey and Land Use Planning (ICAR-NBSS & LUP), all the districts in Kerala exhibited moderately suitable conditions for turmeric cultivation. With the GIS tools, the study identified highly suitable, moderately suitable, marginally suitable and not suitable areas of turmeric cultivation in Kerala. Presently 28% of area falls under highly suitable, 41% of area falls under moderately suitable and 11% falls under not suitable for turmeric cultivation. However, considering the projected scenarios for 2050 under the SSP framework, there will be a significant decrease in highly suitable area by 19% under SSP 5-8.5. This reduction in area will have an impact on the productivity of the crop as a result of changes in temperature and rainfall patterns.

    CONCLUSION: The outcome of the present research suggests that the state of Kerala needs to implement suitable climate change adaptation and management strategies for sustaining the turmeric cultivation. Additionally, the present study includes a discussion on potential management strategies to address the challenges posed by changing climatic conditions for optimizing turmeric production in the region. © 2024 Society of Chemical Industry.

    Matched MeSH terms: Climate Change
  2. Differential capacity of phragmites ecotypes in remediation of inorganic contaminants in coastal ecosystems: Implications for climate change
    Akhter N, Aqeel M, Shazia, Irshad MK, Shehnaz MM, Lee SS, et al.
    Environ Res, 2024 Apr 15;247:118127.
    PMID: 38220075 DOI: 10.1016/j.envres.2024.118127
    Remediating inorganic pollutants is an important part of protecting coastal ecosystems, which are especially at risk from the effects of climate change. Different Phragmites karka (Retz) Trin. ex Steud ecotypes were gathered from a variety of environments, and their abilities to remove inorganic contaminants from coastal wetlands were assessed. The goal is to learn how these ecotypes process innovation might help reduce the negative impacts of climate change on coastal environments. The Phragmites karka ecotype E1, found in a coastal environment in Ichkera that was impacted by residential wastewater, has higher biomass production and photosynthetic pigment content than the Phragmites karka ecotypes E2 (Kalsh) and E3 (Gatwala). Osmoprotectant accumulation was similar across ecotypes, suggesting that all were able to successfully adapt to polluted marine environments. The levels of both total soluble sugars and proteins were highest in E2. The amount of glycine betaine (GB) rose across the board, with the highest levels being found in the E3 ecotype. The study also demonstrated that differing coastal habitats significantly influenced the antioxidant activity of all ecotypes, with E1 displaying the lowest superoxide dismutase (SOD) activity, while E2 exhibited the lowest peroxidase (POD) and catalase (CAT) activities. Significant morphological changes were evident in E3, such as an expansion of the phloem, vascular bundle, and metaxylem cell areas. When compared to the E3 ecotype, the E1 and E2 ecotypes showed striking improvements across the board in leaf anatomy. Mechanistic links between architectural and physio-biochemical alterations are crucial to the ecological survival of different ecotypes of Phragmites karka in coastal environments affected by climate change. Their robustness and capacity to reduce pollution can help coastal ecosystems endure in the face of persistent climate change.
    Matched MeSH terms: Climate Change
  3. Fulltext Historical and projected response of Southeast Asian lakes surface water temperature to warming climate
    Virdis SGP, Kongwarakom S, Juneng L, Padedda BM, Shrestha S
    Environ Res, 2024 Apr 15;247:118412.
    PMID: 38316380 DOI: 10.1016/j.envres.2024.118412
    The temperature of surface and epilimnetic waters, closely related to regional air temperatures, responds quickly and directly to climatic changes. As a result, lake surface temperature (LSWT) can be considered an effective indicator of climate change. In this study, we reconstructed and investigated historical and future LSWT across different scenarios for over 80 major lakes in mainland Southeast Asia (SEA), an ecologically diverse region vulnerable to climate impacts. Five different predicting models, incorporating statistical, machine and deep learning approaches, were trained and validated using ERA5 and CHIRPS climatic feature datasets as predictors and 8-day MODIS-derived LSWT from 2000 to 2020 as reference dataset. Best performing model was then applied to predict both historical (1986-2020) and future (2020-2100) LSWT for SEA lakes, utilizing downscaled climatic CORDEX-SEA feature data and multiple Representative Concentration Pathway (RCP). The analysis uncovered historical and future thermal dynamics and long-term trends for both daytime and nighttime LSWT. Among 5 models, XGboost results the most performant (NSE 0.85, RMSE 1.14 °C, MAE 0.69 °C, MBE -0.08 °C) and it has been used for historical reconstruction and future LSWT prediction. The historical analysis revealed a warming trend in SEA lakes, with daytime LSWT increasing at a rate of +0.18 °C/decade and nighttime LSWT at +0.13 °C/decade over the past three decades. These trends appeared of smaller magnitude compared to global estimates of LSWT change rates and less pronounced than concurrent air temperature and LSWT increases in neighbouring regions. Projections under various RCP scenarios indicated continued LSWT warming. Daytime LSWT is projected to increase at varying rates per decade: +0.03 °C under RCP2.6, +0.14 °C under RCP4.5, and +0.29 °C under RCP8.5. Similarly, nighttime LSWT projections under these scenarios are: +0.03 °C, +0.10 °C, and +0.16 °C per decade, respectively. The most optimistic scenario predicted marginal increases of +0.38 °C on average, while the most pessimistic scenario indicated an average LSWT increase of +2.29 °C by end of the century. This study highlights the relevance of LSWT as a climate change indicator in major SEA's freshwater ecosystems. The integration of satellite-derived LSWT, historical and projected climate data into data-driven modelling has enabled new and a more nuanced understanding of LSWT dynamics in relation to climate throughout the entire SEA region.
    Matched MeSH terms: Climate Change
  4. Shaping a greener future: The role of geopolitical risk, renewable energy and financial development on environmental sustainability using the LCC hypothesis
    Wang W, Balsalobre-Lorente D, Anwar A, Adebayo TS, Cong PT, Quynh NN, et al.
    J Environ Manage, 2024 Apr;357:120708.
    PMID: 38552512 DOI: 10.1016/j.jenvman.2024.120708
    The recent progress report of Sustainable Development Goals (SDG) 2023 highlighted the extreme reactions of environmental degradation. This report also shows that the current efforts for achieving environmental sustainability (SDG 13) are inadequate and a comprehensive policy agenda is needed. However, the present literature has highlighted several determinants of environmental degradation but the influence of geopolitical risk on environmental quality (EQ) is relatively ignored. To fill this research gap and propose a inclusive policy structure for achieving the sustainable development goals. This study is the earliest attempt that delve into the effects o of geopolitical risk (GPR), financial development (FD), and renewable energy consumption (REC) on load capacity factor (LCF) under the framework of load capacity curve (LCC) hypothesis for selected Asian countries during 1990-2020. In this regard, we use several preliminary sensitivity tests to check the features and reliability of the dataset. Similarly, we use panel quantile regression for investigating long-run relationships. The factual results affirm the existence of the LCC hypothesis in selected Asian countries. Our findings also show that geopolitical risk reduces environmental quality whereas financial development and REC increase environmental quality. Drawing from the empirical findings, this study suggests a holistic policy approach for achieving the targets of SDG 13 (climate change).
    Matched MeSH terms: Climate Change*
  5. Unveiling the potential of membrane in climate change mitigation and environmental resilience in ecosystem
    Ahmad T, Kumar N, Kumar A, Mubashir M, Bokhari A, Paswan BK, et al.
    Environ Res, 2024 Mar 15;245:117960.
    PMID: 38135098 DOI: 10.1016/j.envres.2023.117960
    Carbon capture technologies are becoming increasingly crucial in addressing global climate change issues by lowering CO2 emissions from industrial and power generation activities. Post-combustion carbon capture, which uses membranes instead of adsorbents, has emerged as one of promising and environmentally friendly approaches among these technologies. The operation of membrane technology is based on the premise of selectively separating CO2 from flue gas emissions. This provides a number of different benefits, including improved energy efficiency and decreased costs of operation. Because of its adaptability to changing conditions and its low impact on the surrounding ecosystem, it is an appealing choice for a diverse array of uses. However, there are still issues to be resolved, such as those pertaining to establishing a high selectivity, membrane degradation, and the costs of the necessary materials. In this article, we evaluate and explore the prospective applications and roles of membrane technologies to control climate change by post-combustion carbon capturing. The primary proposition suggests that the utilization of membrane-based carbon capture has the potential to make a substantial impact in mitigating CO2 emissions originating from industrial and power production activities. This is due to its heightened ability to selectively absorb carbon, better efficiency in energy consumption, and its flexibility to various applications. The forthcoming challenges and potential associated with the application of membranes in post-carbon capture are also discussed.
    Matched MeSH terms: Climate Change*
  6. Geopolitical risk, financial development, and renewable energy consumption: empirical evidence from selected industrial economies
    Ben Abdallah A, Becha H, Sharif A, Bashir MF
    Environ Sci Pollut Res Int, 2024 Mar;31(14):21935-21946.
    PMID: 38400971 DOI: 10.1007/s11356-024-32565-x
    The rapid rise in climate and ecological challenges have allowed policymakers to introduce stringent environmental policies. In addition, financial limitations may pose challenges for countries looking to green energy investments as energy transition is associated with geopolitical risks that could create uncertainty and dissuade green energy investments. The current study uses PTR and PSTR as econometric strategy to investigate how geopolitical risks and financial development indicators influence energy transition in selected industrial economies. Our findings indicate a non-linear DCPB-RE relationship with a threshold equal to 39.361 in PTR model and 35.605 and 122.35 in PSTR model. Additionally, when the threshold was estimated above, financial development indicators and geopolitical risk positively impacts renewable energy. This confirms that these economies operate within a geopolitical context, with the objective of investing more in clean energy. We report novel policy suggestion to encourage policymakers promoting energy transition and advance the sustainable financing development and ecological sustainability.
    Matched MeSH terms: Climate*
  7. Fulltext Latitudinal patterns in stabilizing density dependence of forest communities
    Hülsmann L, Chisholm RA, Comita L, Visser MD, de Souza Leite M, Aguilar S, et al.
    Nature, 2024 Mar;627(8004):564-571.
    PMID: 38418889 DOI: 10.1038/s41586-024-07118-4
    Numerous studies have shown reduced performance in plants that are surrounded by neighbours of the same species1,2, a phenomenon known as conspecific negative density dependence (CNDD)3. A long-held ecological hypothesis posits that CNDD is more pronounced in tropical than in temperate forests4,5, which increases community stabilization, species coexistence and the diversity of local tree species6,7. Previous analyses supporting such a latitudinal gradient in CNDD8,9 have suffered from methodological limitations related to the use of static data10-12. Here we present a comprehensive assessment of latitudinal CNDD patterns using dynamic mortality data to estimate species-site-specific CNDD across 23 sites. Averaged across species, we found that stabilizing CNDD was present at all except one site, but that average stabilizing CNDD was not stronger toward the tropics. However, in tropical tree communities, rare and intermediate abundant species experienced stronger stabilizing CNDD than did common species. This pattern was absent in temperate forests, which suggests that CNDD influences species abundances more strongly in tropical forests than it does in temperate ones13. We also found that interspecific variation in CNDD, which might attenuate its stabilizing effect on species diversity14,15, was high but not significantly different across latitudes. Although the consequences of these patterns for latitudinal diversity gradients are difficult to evaluate, we speculate that a more effective regulation of population abundances could translate into greater stabilization of tropical tree communities and thus contribute to the high local diversity of tropical forests.
    Matched MeSH terms: Tropical Climate
  8. The Use of the Health Belief Model in the Context of Heatwaves Research: A Rapid Review
    Ullah F, Ragazzoni L, Hubloue I, Barone-Adesi F, Valente M
    Disaster Med Public Health Prep, 2024 Feb 22;18:e34.
    PMID: 38384190 DOI: 10.1017/dmp.2024.26
    As heatwaves increase and intensify worldwide, so has the research aimed at outlining strategies to protect individuals from their impact. Interventions that promote adaptive measures to heatwaves are encouraged, but evidence on how to develop such interventions is still scarce. Although the Health Belief Model is one of the leading frameworks guiding behavioral change interventions, the evidence of its use in heatwave research is limited. This rapid review aims to identify and describe the main themes and key findings in the literature regarding the use of the Health Belief Model in heatwaves research. It also highlights important research gaps and future research priorities. Following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines, 10 articles were included, with a geographic distribution as follows: United States (n = 1), Australia (n = 1), Pakistan (n = 1), and China (n = 1), as well as Malaysia (n = 2), Germany (n = 1), and Austria (n = 1). Results showed a lack of research using the Health Belief Model to study heatwaves induced by climate change. Half of the studies assessed heatwave risk perception, with the 2 most frequently used constructs being Perceived Susceptibility and Perceived Severity. The Self-efficacy construct was instead used less often. Most of the research was conducted in urban communities. This review underscores the need for further research using the Health Belief Model.
    Matched MeSH terms: Climate Change*
  9. Leveraging food waste for electricity: A low-carbon approach in energy sector for mitigating climate change and achieving net zero emission in Hong Kong (China)
    Kurniawan TA, Liang X, Goh HH, Dzarfan Othman MH, Anouzla A, Al-Hazmi HE, et al.
    J Environ Manage, 2024 Feb;351:119879.
    PMID: 38157574 DOI: 10.1016/j.jenvman.2023.119879
    In recent years, food waste has been a global concern that contributes to climate change. To deal with the rising impacts of climate change, in Hong Kong, food waste is converted into electricity in the framework of low-carbon approach. This work provides an overview of the conversion of food waste into electricity to achieve carbon neutrality. The production of methane and electricity from waste-to-energy (WTE) conversion are determined. Potential income from its sale and environmental benefits are also assessed quantitatively and qualitatively. It was found that the electricity generation from the food waste could reach 4.33 × 109 kWh annually, avoiding equivalent electricity charge worth USD 3.46 × 109 annually (based on US' 8/kWh). An equivalent CO2 mitigation of 9.9 × 108 kg annually was attained. The revenue from its electricity sale in market was USD 1.44×109 in the 1st year and USD 4.24 ×109 in the 15th year, respectively, according to the projected CH4 and electricity generation. The modelling study indicated that the electricity production is 0.8 kWh/kg of landfilled waste. The food waste could produce electricity as low as US' 8 per kW ∙ h. In spite of its promising results, there are techno-economic bottlenecks in commercial scale production and its application at comparable costs to conventional fossil fuels. Issues such as high GHG emissions and high production costs have been determined to be resolved later. Overall, this work not only leads to GHG avoidance, but also diversifies energy supply in providing power for homes in the future.
    Matched MeSH terms: Climate Change
  10. Benthic functionality under climate-induced environment changes offshore on the Antarctic Peninsula continental shelf
    Mohd Nasir N, Barnes DKA, Wan Hussin WMR
    Mar Environ Res, 2024 Feb;194:106341.
    PMID: 38183736 DOI: 10.1016/j.marenvres.2024.106341
    Marine ecosystems in Antarctica are thought to be highly vulnerable to aspects of dynamic global climate change, such as warming. In deep-water ecosystems, there has been little physico-chemical change in seawater there for millions of years. Thus, some benthic organisms are likely to include strong potential indicators of environmental changes and give early warnings of ecosystem vulnerability. In 2017 we sampled deep-water benthic assemblages across a continental shelf trough in outer Marguerite Bay, West Antarctic Peninsula (WAP). This region is one of the hotspots of climate-related physical change on Earth in terms of seasonal sea ice loss. Video and images of the seabed were captured at 5 stations, each with 20 replicates. From these, we identified substratum types and biota to functional groups to assess variability in benthic composition and diversity. We also collected coincident environmental information on depth, temperature, salinity, oxygen and chlorophyll-a (using a CTD). Climax sessile suspension feeders were the most spatially dominant group, comprising 539 individuals (39% of total abundance) that included Porifera, Brachiopoda and erect Bryozoa. ST5, the shallowest station was functionally contrasting with other stations. This functional difference was also influenced by hard substrata of ST5, which is typically preferred by climax sessile suspension feeders. Depth (or an associated driver) and hard substrates were the most apparent key factor which functionally characterised the communities, shown by the abundance of climax sessile suspension feeders. Our study showed that non-invasive, low taxonomic skill requirement, functional group approach is not only valuable in providing functional perspective on environment status, but such groupings also proved to be sensitive to environmental variability.
    Matched MeSH terms: Climate Change
  11. An evaluation framework for quantifying vegetation loss and recovery in response to meteorological drought based on SPEI and NDVI
    Wu C, Zhong L, Yeh PJ, Gong Z, Lv W, Chen B, et al.
    Sci Total Environ, 2024 Jan 01;906:167632.
    PMID: 37806579 DOI: 10.1016/j.scitotenv.2023.167632
    Drought affects vegetation growth to a large extent. Understanding the dynamic changes of vegetation during drought is of great significance for agricultural and ecological management and climate change adaptation. The relations between vegetation and drought have been widely investigated, but how vegetation loss and restoration in response to drought remains unclear. Using the standardized precipitation evapotranspiration index (SPEI) and the normalized difference vegetation index (NDVI) data, this study developed an evaluation framework for exploring the responses of vegetation loss and recovery to meteorological drought, and applied it to the humid subtropical Pearl River basin (PRB) in southern China for estimating the loss and recovery of three vegetation types (forest, grassland, cropland) during drought using the observed NDVI changes. Results indicate that vegetation is more sensitive to drought in high-elevation areas (lag time  8 months). Vegetation loss (especially in cropland) is found to be more sensitive to drought duration than drought severity and peak. No obvious linear relationship between drought intensity and the extent of vegetation loss is found. Regardless of the intensity, drought can cause the largest probability of mild loss of vegetation, followed by moderate loss, and the least probability of severe loss. Large spatial variability in the probability of vegetation loss and recovery time is found over the study domain, with a higher probability (up to 50 %) of drought-induced vegetation loss and a longer recovery time (>7 months) mostly in the high-elevation areas. Further analysis suggests that forest shows higher but cropland shows lower drought resistance than other vegetation types, and grassland requires a shorter recovery time (4.2-month) after loss than forest (5.1-month) and cropland (4.8-month).
    Matched MeSH terms: Climate Change
  12. Fulltext Consistent patterns of common species across tropical tree communities
    Cooper DLM, Lewis SL, Sullivan MJP, Prado PI, Ter Steege H, Barbier N, et al.
    Nature, 2024 Jan;625(7996):728-734.
    PMID: 38200314 DOI: 10.1038/s41586-023-06820-z
    Trees structure the Earth's most biodiverse ecosystem, tropical forests. The vast number of tree species presents a formidable challenge to understanding these forests, including their response to environmental change, as very little is known about most tropical tree species. A focus on the common species may circumvent this challenge. Here we investigate abundance patterns of common tree species using inventory data on 1,003,805 trees with trunk diameters of at least 10 cm across 1,568 locations1-6 in closed-canopy, structurally intact old-growth tropical forests in Africa, Amazonia and Southeast Asia. We estimate that 2.2%, 2.2% and 2.3% of species comprise 50% of the tropical trees in these regions, respectively. Extrapolating across all closed-canopy tropical forests, we estimate that just 1,053 species comprise half of Earth's 800 billion tropical trees with trunk diameters of at least 10 cm. Despite differing biogeographic, climatic and anthropogenic histories7, we find notably consistent patterns of common species and species abundance distributions across the continents. This suggests that fundamental mechanisms of tree community assembly may apply to all tropical forests. Resampling analyses show that the most common species are likely to belong to a manageable list of known species, enabling targeted efforts to understand their ecology. Although they do not detract from the importance of rare species, our results open new opportunities to understand the world's most diverse forests, including modelling their response to environmental change, by focusing on the common species that constitute the majority of their trees.
    Matched MeSH terms: Tropical Climate*
  13. Precision endoscopy in the era of climate change and sustainability
    Ueda T, Li JW, Ho SH, Singh R, Uedo N
    J Gastroenterol Hepatol, 2024 Jan;39(1):18-27.
    PMID: 37881033 DOI: 10.1111/jgh.16383
    Global warming caused by increased greenhouse gas (GHG) emissions has a direct impact on human health. Gastrointestinal (GI) endoscopy contributes significantly to GHG emissions due to energy consumption, reprocessing of endoscopes and accessories, production of equipment, safe disposal of biohazardous waste, and travel by patients. Moreover, GHGs are also generated in histopathology through tissue processing and the production of biopsy specimen bottles. The reduction in unnecessary surveillance endoscopies and biopsies is a practical approach to decrease GHG emissions without affecting disease outcomes. This narrative review explores the role of precision medicine in GI endoscopy, such as image-enhanced endoscopy and artificial intelligence, with a focus on decreasing unnecessary endoscopic procedures and biopsies in the surveillance and diagnosis of premalignant lesions in the esophagus, stomach, and colon. This review offers strategies to minimize unnecessary endoscopic procedures and biopsies, decrease GHG emissions, and maintain high-quality patient care, thereby contributing to sustainable healthcare practices.
    Matched MeSH terms: Climate Change*
  14. Heat and Wheat: Adaptation strategies with respect to heat shock proteins and antioxidant potential; an era of climate change
    Abasi F, Raja NI, Mashwani ZU, Ehsan M, Ali H, Shahbaz M
    Int J Biol Macromol, 2024 Jan;256(Pt 1):128379.
    PMID: 38000583 DOI: 10.1016/j.ijbiomac.2023.128379
    Extreme changes in weather including heat-wave and high-temperature fluctuations are predicted to increase in intensity and duration due to climate change. Wheat being a major staple crop is under severe threat of heat stress especially during the grain-filling stage. Widespread food insecurity underscores the critical need to comprehend crop responses to forthcoming climatic shifts, pivotal for devising adaptive strategies ensuring sustainable crop productivity. This review addresses insights concerning antioxidant, physiological, molecular impacts, tolerance mechanisms, and nanotechnology-based strategies and how wheat copes with heat stress at the reproductive stage. In this study stress resilience strategies were documented for sustainable grain production under heat stress at reproductive stage. Additionally, the mechanisms of heat resilience including gene expression, nanomaterials that trigger transcription factors, (HSPs) during stress, and physiological and antioxidant traits were explored. The most reliable method to improve plant resilience to heat stress must include nano-biotechnology-based strategies, such as the adoption of nano-fertilizers in climate-smart practices and the use of advanced molecular approaches. Notably, the novel resistance genes through advanced molecular approach and nanomaterials exhibit promise for incorporation into wheat cultivars, conferring resilience against imminent adverse environmental conditions. This review will help scientific communities in thermo-tolerance wheat cultivars and new emerging strategies to mitigate the deleterious impact of heat stress.
    Matched MeSH terms: Climate Change
  15. Fulltext Updates in Air Pollution: Current Research and Future Challenges
    Vilcins D, Christofferson RC, Yoon JH, Nazli SN, Sly PD, Cormier SA, et al.
    Ann Glob Health, 2024;90(1):9.
    PMID: 38312715 DOI: 10.5334/aogh.4363
    BACKGROUND: The United Nations has declared that humans have a right to clean air. Despite this, many deaths and disability-adjusted life years are attributed to air pollution exposure each year. We face both challenges to air quality and opportunities to improve, but several areas need to be addressed with urgency.

    OBJECTIVE: This paper summarises the recent research presented at the Pacific Basin Consortium for Environment and Health Symposium and focuses on three key areas of air pollution that are important to human health and require more research.

    FINDINGS AND CONCLUSION: Indoor spaces are commonly places of exposure to poor air quality and are difficult to monitor and regulate. Global climate change risks worsening air quality in a bi-directional fashion. The rising use of electric vehicles may offer opportunities to improve air quality, but it also presents new challenges. Government policies and initiatives could lead to improved air and environmental justice. Several populations, such as older people and children, face increased harm from air pollution and should become priority groups for action.

    Matched MeSH terms: Climate Change
  16. The 2023 report of the Lancet Countdown on health and climate change: the imperative for a health-centred response in a world facing irreversible harms
    Romanello M, Napoli CD, Green C, Kennard H, Lampard P, Scamman D, et al.
    Lancet, 2023 Dec 16;402(10419):2346-2394.
    PMID: 37977174 DOI: 10.1016/S0140-6736(23)01859-7
    Matched MeSH terms: Climate Change*
  17. Impact of air pollutants on climate change and prediction of air quality index using machine learning models
    Ravindiran G, Rajamanickam S, Kanagarathinam K, Hayder G, Janardhan G, Arunkumar P, et al.
    Environ Res, 2023 Dec 15;239(Pt 1):117354.
    PMID: 37821071 DOI: 10.1016/j.envres.2023.117354
    The impact of air pollution in Chennai metropolitan city, a southern Indian coastal city was examined to predict the Air Quality Index (AQI). Regular monitoring and prediction of the Air Quality Index (AQI) are critical for combating air pollution. The current study created machine learning models such as XGBoost, Random Forest, BaggingRegressor, and LGBMRegressor for the prediction of the AQI using the historical data available from 2017 to 2022. According to historical data, the AQI is highest in January, with a mean value of 104.6 g/gm, and the lowest in August, with a mean AQI value of 63.87 g/gm. Particulate matter, gaseous pollutants, and meteorological parameters were used to predict AQI, and the heat map generated showed that of all the parameters, PM2.5 has the greatest impact on AQI, with a value of 0.91. The log transformation method is used to normalize datasets and determine skewness and kurtosis. The XGBoost model demonstrated strong performance, achieving an R2 (correlation coefficient) of 0.9935, a mean absolute error (MAE) of 0.02, a mean square error (MSE) of 0.001, and a root mean square error (RMSE) of 0.04. In comparison, the LightGBM model's prediction was less effective, as it attained an R2 of 0.9748. According to the study, the AQI in Chennai has been increasing over the last two years, and if the same conditions persist, the city's air pollution will worsen in the future. Furthermore, accurate future air quality level predictions can be made using historical data and advanced machine learning algorithms.
    Matched MeSH terms: Climate Change
  18. Contributions of climate change and human activities to grassland degradation and improvement from 2001 to 2020 in Zhaosu County, China
    Zhang M, Zhang F, Guo L, Dong P, Cheng C, Kumar P, et al.
    J Environ Manage, 2023 Dec 15;348:119465.
    PMID: 37924697 DOI: 10.1016/j.jenvman.2023.119465
    Grassland degradation poses a serious threat to biodiversity, ecosystem services, and human well-being. In this study, we investigated grassland degradation in Zhaosu County, China, between 2001 and 2020, and analyzed the impacts of climate change and human activities using the Miami model. The actual net primary productivity (ANPP) obtained with CASA (Carnegie-Ames-Stanford Approach) modeling, showed a decreasing trend, reflecting the significant degradation that the grasslands in Zhaosu County have experienced in the past 20 years. Grassland degradation was found to be highest in 2018, while the degraded area continuously decreased in the last 3 years (2018-2020). Climatic factors for found to be the dominant factor affecting grassland degradation, particularly the decrease in precipitation. On the other hand, human activities were found to be the main factor affecting improvement of grasslands, especially in recent years. This finding profoundly elucidates the underlying causes of grassland degradation and improvement and helps implement ecological conservation and restoration measures. From a practical perspective, the research results provide an important reference for the formulation of policies and management strategies for sustainable land use.
    Matched MeSH terms: Climate Change
  19. Assessing coastal bathymetry and climate change impacts on coastal ecosystems using Landsat 8 and Sentinel-2 satellite imagery
    Mokhtar K, Chuah LF, Abdullah MA, Oloruntobi O, Ruslan SMM, Albasher G, et al.
    Environ Res, 2023 Dec 15;239(Pt 2):117314.
    PMID: 37805186 DOI: 10.1016/j.envres.2023.117314
    Coastal ecosystems are facing heightened risks due to human-induced climate change, including rising water levels and intensified storm events. Accurate bathymetry data is crucial for assessing the impacts of these threats. Traditional data collection methods can be cost-prohibitive. This study investigates the feasibility of using freely accessible Landsat and Sentinel satellite imagery to estimate bathymetry and its correlation with hydrographic chart soundings in Port Klang, Malaysia. Through analysis of the blue and green spectral bands from the Landsat 8 and Sentinel 2 datasets, a bathymetry map of Port Klang's seabed is generated. The precision of this derived bathymetry is evaluated using statistical metrics like Root Mean Square Error (RMSE) and the coefficient of determination. The results reveal a strong statistical connection (R2 = 0.9411) and correlation (R2 = 0.7958) between bathymetry data derived from hydrographic chart soundings and satellite imagery. This research not only advances our understanding of employing Landsat imagery for bathymetry assessment but also underscores the significance of such assessments in the context of climate change's impact on coastal ecosystems. The primary goal of this research is to contribute to the comprehension of Landsat imagery's utility in bathymetry evaluation, with the potential to enhance safety protocols in seaport terminals and provide valuable insights for decision-making concerning the management of coastal ecosystems amidst climate-related challenges. The findings of this research have practical implications for a wide range of stakeholders involved in coastal management, environmental protection, climate adaptation and disaster preparedness.
    Matched MeSH terms: Climate Change
  20. Enhancing coastal ecosystem resilience: Investigating the interplay between safety criteria and ferry employee's perceptions to address climate change impacts
    Azmi MA, Mokhtar K, Osnin NA, Razali Chan S, Albasher G, Ali A, et al.
    Environ Res, 2023 Dec 01;238(Pt 1):117074.
    PMID: 37678506 DOI: 10.1016/j.envres.2023.117074
    Coastal ecosystems play an important part in mitigating the effects of climate change. Coastal ecosystems are becoming more susceptible to climate change impacts due to human activities and maritime accidents. The global shipping industry, especially in Southeast Asia, has witnessed numerous accidents, particularly involving passenger ferries, resulting in injuries and fatalities in recent years. In order to mitigate the impact of climate change on coastal ecosystems, this study aimed to evaluate the relationship between employees' perceptions of safety criteria and their own safety behaviour on Langkawi Island, Malaysia. A straightforward random sampling technique was employed to collect data from 112 ferry employees aboard Malaysian-registered passenger boats by administering questionnaires. The findings shed light on the strong connection between providing safety instructions for passengers and safety behaviour among ferry workers. Safety instructions should contain climate-related information to successfully address the effects of climate change. The instructions might include guidance on responding to extreme weather events and understanding the potential consequences of sea-level rise on coastal communities. The ferry company staff should also expand their safe behaviour concept to include training and preparation for climate-related incidents. The need to recognise the interconnectedness between climate change, ferry safety and the protection of coastal ecosystems is emphasised in this study. The findings can be utilised by policymakers, regulatory agencies and ferry operators to design holistic policies that improve safety behaviour, minimise maritime mishaps and preserve the long-term sustainability of coastal ecosystems in the face of difficulties posed by climate change.
    Matched MeSH terms: Climate Change*
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