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  1. Contribution of tree community structure to forest productivity across a thermal gradient in eastern Asia
    Kohyama TI, Sheil D, Sun IF, Niiyama K, Suzuki E, Hiura T, et al.
    Nat Commun, 2023 Mar 13;14(1):1113.
    PMID: 36914632 DOI: 10.1038/s41467-023-36671-1
    Despite their fundamental importance the links between forest productivity, diversity and climate remain contentious. We consider whether variation in productivity across climates reflects adjustment among tree species and individuals, or changes in tree community structure. We analysed data from 60 plots of humid old-growth forests spanning mean annual temperatures (MAT) from 2.0 to 26.6 °C. Comparing forests at equivalent aboveground biomass (160 Mg C ha-1), tropical forests ≥24 °C MAT averaged more than double the aboveground woody productivity of forests <12 °C (3.7 ± 0.3 versus 1.6 ± 0.1 Mg C ha-1 yr-1). Nonetheless, species with similar standing biomass and maximum stature had similar productivity across plots regardless of temperature. We find that differences in the relative contribution of smaller- and larger-biomass species explained 86% of the observed productivity differences. Species-rich tropical forests are more productive than other forests due to the high relative productivity of many short-stature, small-biomass species.
    Matched MeSH terms: Tropical Climate
  2. Revisiting the social cost of carbon after INDC implementation in Malaysia: 2050
    Sarkar MSK, Al-Amin AQ, Filho WL
    Environ Sci Pollut Res Int, 2019 Feb;26(6):6000-6013.
    PMID: 30612378 DOI: 10.1007/s11356-018-3947-1
    This article projects the social cost of carbon (SCC) and other related consequences of climate change by using Malaysia's intended nationally determined contribution (INDC) and climate vision 2040 (CV2040) by 2050. It compares the projections derived from the Dynamic Integrated Model of the Climate and Economy (DICME) based on the respective INDC and CV2040 scenario. The results reveal that industrial emissions would incur a substantial increase every 5 years under the scenario CV2040, while Malaysia would experience lower industrial emissions in the coming years under the scenario INDC. Emission intensity in Malaysia will be 0.61 and 0.59 tons/capita in 2030 for scenario CV2040 and scenario INDC respectively. Malaysia would face climate damage of MYR456 billion and MYR 49 billion by 2050 under CV2040 and INDC scenario respectively. However, climate damage could be much lower if the INDC regime were adopted, as this scenario would decrease climatic impacts over time. The estimated SSC per ton of CO2 varies between MYR74 and MYR97 for scenario CV2040 and MYR44 and MYR62 for scenario INDC in 2030 and 2050 respectively. Considering different aspects, including industrial emissions, damage cost, and social cost of carbon, INDC is the best policy compared to CV2040. Thus, Malaysia could achieve its emissions reduction target by implementing INDC by 2050.
    Matched MeSH terms: Climate Change
  3. The impact of climate variables on marine fish production: an empirical evidence from Bangladesh based on autoregressive distributed lag (ARDL) approach
    Begum M, Masud MM, Alam L, Mokhtar MB, Amir AA
    Environ Sci Pollut Res Int, 2022 Dec;29(58):87923-87937.
    PMID: 35819668 DOI: 10.1007/s11356-022-21845-z
    Several studies have highlighted the significant impact of climate change on agriculture. However, there have been little empirical enquiries into the impact of climate change on marine fish production, particularly in Bangladesh. Hence, this study aims to investigate the impact of climate change on marine fish production in Bangladesh using data from 1961 to 2019. Data were obtained from the Food and Agriculture Organization, Bangladesh Meteorological Department, the World Development Indicators, and the National Oceanic and Atmospheric Administration. The autoregressive distributed lag (ARDL) model was used to describe the dynamic link between CO2 emissions, average temperature, Sea Surface Temperature (SST), rainfall, sunshine, wind and marine fish production. The ARDL approach to cointegration revealed that SST (β = 0.258), rainfall (β =0.297), and sunshine (β =0.663) significantly influence marine fish production at 1% and 10% levels in the short run and at 1% level in the long run. The results also found that average temperature has a significant negative impact on fish production in both short and long runs. On the other hand, CO2 emissions have a negative impact on marine fish production in the short run. Specifically, for every 1% rise in CO2 emissions, marine fish production will decline by 0.11%. The findings of this study suggest that policymakers formulate better policy frameworks for climate change adaptation and sustainable management of marine fisheries at the national level. Research and development in Bangladesh's fisheries sector should also focus on marine fish species that can resist high sea surface temperatures, CO2 emissions, and average temperatures.
    Matched MeSH terms: Climate Change
  4. 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
  5. The nexus between government spending, economic growth, and tourism under climate change: testing the CEM model for the USA
    Bulut U, Ongan S, Dogru T, Işık C, Ahmad M, Alvarado R, et al.
    Environ Sci Pollut Res Int, 2023 Aug;30(36):86138-86154.
    PMID: 37400702 DOI: 10.1007/s11356-023-28319-w
    This study examines the impact of government spending, income, and tourism consumption on CO2 emissions in the 50 US states through a novel theoretical model derived from the Armey Curve model and the Environmental Kuznets Curve hypothesis. The findings of this research are essential for policymakers to develop effective strategies for mitigating environmental pollution. Utilizing panel cointegration analysis, the study provides valuable insights into whether continued increases in government spending contribute to higher pollution levels. By identifying the threshold point of spending as a percentage of GDP, policymakers can make informed decisions to avoid the trade-off between increased spending and environmental degradation. For instance, the analysis reveals that Hawaii's tipping point is 16.40%. The empirical results underscore the importance of adopting sustainable policies that foster economic growth while minimizing environmental harm. These findings will aid policymakers in formulating targeted and efficient approaches to tackle climate change and promote long-term environmental sustainability in the United States. Moreover, the impact of tourism development on CO2 emissions varies across states, with some US states experiencing a decrease while others see an increase.
    Matched MeSH terms: Climate Change
  6. Ecotourism and mangrove conservation in Southeast Asia: Current trends and perspectives
    Blanton A, Ewane EB, McTavish F, Watt MS, Rogers K, Daneil R, et al.
    J Environ Manage, 2024 Aug;365:121529.
    PMID: 38963961 DOI: 10.1016/j.jenvman.2024.121529
    Mangroves in Southeast Asia provide numerous supporting, provisioning, regulating, and cultural services that are crucial to the environment and local livelihoods since they support biodiversity conservation and climate change resilience. However, Southeast Asia mangroves face deforestation threats from the expansion of commercial aquaculture, agriculture, and urban development, along with climate change-related natural processes. Ecotourism has gained prominence as a financial incentive tool to support mangrove conservation and restoration. Through a systematic literature review approach, we examined the relationships between ecotourism and mangrove conservation in Southeast Asia based on scientific papers published from 2010 to 2022. Most of the studies were reported in Indonesia, Malaysia, Philippines, Thailand, and Vietnam, respectively, which were associated with the highest number of vibrant mangrove ecotourism sites and largest mangrove areas compared to the other countries of Southeast Asia. Mangrove-related ecotourism activities in the above countries mainly include boat tours, bird and wildlife watching, mangrove planting, kayaking, eating seafood, and snorkeling. The economic benefits, such as an increase in income associated with mangrove ecotourism, have stimulated infrastructural development in ecotourism destinations. Local communities benefited from increased access to social amenities such as clean water, electricity, transportation networks, schools, and health services that are intended to make destinations more attractive to tourists. Economic benefits from mangrove ecotourism motivated the implementation of several community-based mangrove conservation and restoration initiatives, which attracted international financial incentives and public-private partnerships. Since mangroves are mostly located on the land occupied by indigenous people and local communities, ensuring respect for their land rights and equity in economic benefit sharing may increase their intrinsic motivation and participation in mangrove restoration and conservation initiatives. Remote sensing tools for mangrove monitoring, evaluation, and reporting, and integrated education and awareness campaigns can ensure the long-term conservation of mangroves while sustaining ecotourism's economic infrastructure and social amenities benefits.
    Matched MeSH terms: Climate Change
  7. 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
  8. Potential role of seaweeds in climate change mitigation
    Ross FWR, Boyd PW, Filbee-Dexter K, Watanabe K, Ortega A, Krause-Jensen D, et al.
    Sci Total Environ, 2023 Aug 10;885:163699.
    PMID: 37149169 DOI: 10.1016/j.scitotenv.2023.163699
    Seaweed (macroalgae) has attracted attention globally given its potential for climate change mitigation. A topical and contentious question is: Can seaweeds' contribution to climate change mitigation be enhanced at globally meaningful scales? Here, we provide an overview of the pressing research needs surrounding the potential role of seaweed in climate change mitigation and current scientific consensus via eight key research challenges. There are four categories where seaweed has been suggested to be used for climate change mitigation: 1) protecting and restoring wild seaweed forests with potential climate change mitigation co-benefits; 2) expanding sustainable nearshore seaweed aquaculture with potential climate change mitigation co-benefits; 3) offsetting industrial CO2 emissions using seaweed products for emission abatement; and 4) sinking seaweed into the deep sea to sequester CO2. Uncertainties remain about quantification of the net impact of carbon export from seaweed restoration and seaweed farming sites on atmospheric CO2. Evidence suggests that nearshore seaweed farming contributes to carbon storage in sediments below farm sites, but how scalable is this process? Products from seaweed aquaculture, such as the livestock methane-reducing seaweed Asparagopsis or low carbon food resources show promise for climate change mitigation, yet the carbon footprint and emission abatement potential remains unquantified for most seaweed products. Similarly, purposely cultivating then sinking seaweed biomass in the open ocean raises ecological concerns and the climate change mitigation potential of this concept is poorly constrained. Improving the tracing of seaweed carbon export to ocean sinks is a critical step in seaweed carbon accounting. Despite carbon accounting uncertainties, seaweed provides many other ecosystem services that justify conservation and restoration and the uptake of seaweed aquaculture will contribute to the United Nations Sustainable Development Goals. However, we caution that verified seaweed carbon accounting and associated sustainability thresholds are needed before large-scale investment into climate change mitigation from seaweed projects.
    Matched MeSH terms: Climate Change
  9. Fulltext Agro-climatic sensitivity analysis for sustainable crop diversification; the case of Proso millet (Panicum miliaceum L.)
    Wimalasiri EM, Ashfold MJ, Jahanshiri E, Walker S, Azam-Ali SN, Karunaratne AS
    PLoS One, 2023;18(3):e0283298.
    PMID: 36952502 DOI: 10.1371/journal.pone.0283298
    Current agricultural production depends on very limited species grown as monocultures that are highly vulnerable to climate change, presenting a threat to the sustainability of agri-food systems. However, many hundreds of neglected crop species have the potential to cater to the challenges of climate change by means of resilience to adverse climate conditions. Proso millet (Panicum miliaceum L.), one of the underutilised minor millets grown as a rainfed subsistence crop, was selected in this study as an exemplary climate-resilient crop. Using a previously calibrated version of the Agricultural Production Systems Simulator (APSIM), the sensitivity of the crop to changes in temperature and precipitation was studied using the protocol of the Coordinated Climate Crop Modelling Project (C3MP). The future (2040-2069) production was simulated using bias-corrected climate data from 20 general circulation models of the Coupled Model Intercomparison Project (CMIP5) under RCP4.5 and 8.5 scenarios. According to the C3MP analysis, we found a 1°C increment of temperature decreased the yield by 5-10% at zero rainfall change. However, Proso millet yields increased by 5% within a restricted climate change space of up to 2°C of warming with increased rainfall. Simulated future climate yields were lower than the simulated yields under the baseline climate of the 1980-2009 period (mean 1707 kg ha-1) under both RCP4.5 (-7.3%) and RCP8.5 (-16.6%) though these changes were not significantly (p > 0.05) different from the baseline yields. Proso millet is currently cultivated in limited areas of Sri Lanka, but our yield mapping shows the potential for expansion of the crop to new areas under both current and future climates. The results of the study, indicating minor impacts from projected climate change, reveal that Proso millet is an excellent candidate for low-input farming systems under changing climate. More generally, through this study, a framework that can be used to assess the climate sensitivity of underutilized crops was also developed.
    Matched MeSH terms: Climate Change
  10. 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
  11. 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
  12. Thermal design and zeotropic working fluids mixture selection optimization for a solar waste heat driven combined cooling and power system
    Kheimi M, K Salamah S, A Maddah H, Mustafa Al Bakri Abdullah M
    Chemosphere, 2023 Sep;335:139036.
    PMID: 37245592 DOI: 10.1016/j.chemosphere.2023.139036
    Considering the limitation of fossil fuel resources and their environmental effects, the use of renewable energies is increasing. In the current research, a combined cooling and power production (CCPP) system is investigated, the energy source of which is solar energy. Solar energy absorbs by solar flat plate collectors (SFPC). The system produces power with the help of an organic Rankine cycle (ORC). An ejector refrigeration cycle (ERC) system is considered to provide cooling capacity. The motive flow is supplied from the expander extraction in the ERC system. Various working fluids have been applied so far for the ORC-ERC cogeneration system. This research investigates the effect of using two working fluids R-11 and R-2545fa, and the zeotropic mixtures obtained by mixing these two fluids. A multiobjective optimization process is considered to select the appropriate working fluid. In the optimization design process, the goal is to minimize the total cost rate (TCR) and maximize the exergy efficiency of the system. The design variables are the quantity of SFPC, heat recovery vapor generator (HRVG) pressure, ejector motive flow pressure, evaporator pressure, condenser pressure, and entertainment ratio. Finally, it is observed that using zeotropic mixtures obtained from these two refrigerants has a better result than using pure refrigerants. Finally, it is observed that the best performance is achieved when R-11 and R245fa are mixed with a ratio of 80 to 20%, respectively and led to 8.5% improvement in exergy efficiency, while the increase in TCR is only 1.5%.
    Matched MeSH terms: Climate
  13. The impact of environmental knowledge and green supply chain practices in improving sustainable energy production: the moderating role of green behavior and green leadership
    Chen SL, Su YS, Diep GL, Sivanandan P, Sadiq M, Phan TTH
    Environ Sci Pollut Res Int, 2023 Apr;30(19):57017-57031.
    PMID: 36930320 DOI: 10.1007/s11356-023-26340-7
    Global warming and the dreadful climate condition in China demands the sustainable energy transition and production that must be far away from coal-based energy production. The present article, thereby, intends to assess the effectiveness of environmental knowledge and green supply chain practices on sustainable energy production. The study also introduces green behavior and green leadership as a moderator to evaluate the proposed relationship. Primary data has been collected and assessed by PLS-SEM. The findings reveal that environmental knowledge, green purchases, and internal environmental management (IEM) have a positive association with sustainable energy production (SEP) in China. The outcomes also indicate that green behavior significantly moderates among environmental knowledge, green purchases, and SEP, and green leadership significantly moderates among IEM and SEP in China. The research guides the policymakers in establishing policies related to SEP using green behavior, GSC practices, and environmental knowledge.
    Matched MeSH terms: Climate
  14. Fulltext Stem girth changes in response to soil water potential in lowland dipterocarp forest in Borneo: An individualistic time-series analysis
    Newbery DM, Lingenfelder M
    PLoS One, 2022;17(6):e0270140.
    PMID: 35771743 DOI: 10.1371/journal.pone.0270140
    Time-series data offer a way of investigating the causes driving ecological processes as phenomena. To test for possible differences in water relations between species of different forest structural guilds at Danum (Sabah, NE Borneo), daily stem girth increments (gthi), of 18 trees across six species were regressed individually on soil moisture potential (SMP) and temperature (TEMP), accounting for temporal autocorrelation (in GLS-arima models), and compared between a wet and a dry period. The best-fitting significant variables were SMP the day before and TEMP the same day. The first resulted in a mix of positive and negative coefficients, the second largely positive ones. An adjustment for dry-period showers was applied. Interactions were stronger in dry than wet period. Negative relationships for overstorey trees can be interpreted in a reversed causal sense: fast transporting stems depleted soil water and lowered SMP. Positive relationships for understorey trees meant they took up most water at high SMP. The unexpected negative relationships for these small trees may have been due to their roots accessing deeper water supplies (if SMP was inversely related to that of the surface layer), and this was influenced by competition with larger neighbour trees. A tree-soil flux dynamics manifold may have been operating. Patterns of mean diurnal girth variation were more consistent among species, and time-series coefficients were negatively related to their maxima. Expected differences in response to SMP in the wet and dry periods did not clearly support a previous hypothesis differentiating drought and non-drought tolerant understorey guilds. Trees within species showed highly individual responses when tree size was standardized. Data on individual root systems and SMP at several depths are needed to get closer to the mechanisms that underlie the tree-soil water phenomena in these tropical forests. Neighborhood stochasticity importantly creates varying local environments experienced by individual trees.
    Matched MeSH terms: Tropical Climate
  15. Fulltext Bulk Processing of Multi-Temporal Modis Data, Statistical Analyses and Machine Learning Algorithms to Understand Climate Variables in the Indian Himalayan Region
    Haq MA, Baral P, Yaragal S, Pradhan B
    Sensors (Basel), 2021 Nov 08;21(21).
    PMID: 34770722 DOI: 10.3390/s21217416
    Studies relating to trends of vegetation, snowfall and temperature in the north-western Himalayan region of India are generally focused on specific areas. Therefore, a proper understanding of regional changes in climate parameters over large time periods is generally absent, which increases the complexity of making appropriate conclusions related to climate change-induced effects in the Himalayan region. This study provides a broad overview of changes in patterns of vegetation, snow covers and temperature in Uttarakhand state of India through bulk processing of remotely sensed Moderate Resolution Imaging Spectroradiometer (MODIS) data, meteorological records and simulated global climate data. Additionally, regression using machine learning algorithms such as Support Vectors and Long Short-term Memory (LSTM) network is carried out to check the possibility of predicting these environmental variables. Results from 17 years of data show an increasing trend of snow-covered areas during pre-monsoon and decreasing vegetation covers during monsoon since 2001. Solar radiation and cloud cover largely control the lapse rate variations. Mean MODIS-derived land surface temperature (LST) observations are in close agreement with global climate data. Future studies focused on climate trends and environmental parameters in Uttarakhand could fairly rely upon the remotely sensed measurements and simulated climate data for the region.
    Matched MeSH terms: Climate Change
  16. 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
  17. 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
  18. 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
  19. Fulltext What is next in African neuroscience?
    Donald KA, Maina M, Patel N, Nguemeni C, Mohammed W, Abubakar A, et al.
    Elife, 2022 Jun 22;11.
    PMID: 35731202 DOI: 10.7554/eLife.80488
    Working in Africa provides neuroscientists with opportunities that are not available in other continents. Populations in this region exhibit the greatest genetic diversity; they live in ecosystems with diverse flora and fauna; and they face unique stresses to brain health, including child brain health and development, due to high levels of traumatic brain injury and diseases endemic to the region. However, the neuroscience community in Africa has yet to reach its full potential. In this article we report the outcomes from a series of meetings at which the African neuroscience community came together to identify barriers and opportunities, and to discuss ways forward. This exercise resulted in the identification of six domains of distinction in African neuroscience: the diverse DNA of African populations; diverse flora, fauna and ecosystems for comparative research; child brain health and development; the impact of climate change on mental and neurological health; access to clinical populations with important conditions less prevalent in the global North; and resourcefulness in the reuse and adaption of existing technologies and resources to answer new questions. The article also outlines plans to advance the field of neuroscience in Africa in order to unlock the potential of African neuroscientists to address regional and global mental health and neurological problems.
    Matched MeSH terms: Climate Change
  20. The impact of increasing ambient temperature on allergic rhinitis: A systematic review and meta-analysis of observational studies
    Wei Rong CW, Salleh H, Nishio H, Lee M
    Sci Total Environ, 2024 Oct 15;947:174348.
    PMID: 38960184 DOI: 10.1016/j.scitotenv.2024.174348
    INTRODUCTION: Global warming appears to initiate and aggravate allergic respiratory conditions via interaction with numerous environmental factors. Temperature, commonly identified as a factor in climate change, is important in this process. Allergic rhinitis, a common respiratory allergy, is on the rise and affects approximately 500 million individuals worldwide. The increasing ambient temperature requires evaluation regarding its influence on allergic rhinitis, taking into account regional climate zones.

    METHODS: A detailed search of PubMed, EMBASE, Scopus, Web of Science, MEDLINE, and CINAHL Plus databases, was conducted, encompassing observational studies published from 1991 to 2023. Original studies examining the relationship between increasing temperature and allergic rhinitis were assessed for eligibility followed by a risk of bias assessment. Random effects meta-analysis was utilized to measure the association between a 1 °C increase in temperature and allergic rhinitis-related outcomes.

    RESULTS: 20 studies were included in the qualitative synthesis, with nine of them subsequently selected for the quantitative synthesis. 20 included studies were rated as Level 4 evidence according to the Oxford Centre for Evidence-Based Medicine, and the majority of these reported good-quality evidence based on the Newcastle-Ottawa Quality Rating Scale. Using the Risk of Bias In Non-Randomized Studies of Exposure tool, the majority of studies exhibit a high risk of bias. Every 1 °C increase in temperature significantly raised the risk of allergic rhinitis-related outcomes by 29 % (RR = 1.26, 95 % CI: 1.11 to 1.50). Conversely, every 1 °C rise in temperature showed no significant increase in the odds of allergic rhinitis-related outcomes by 7 % (OR = 1.07, 95 % CI: 0.95 to 1.21). Subsequent subgroup analysis identified climate zone as an influential factor influencing this association.

    CONCLUSION: It is inconclusive to definitively suggest a harmful effect of increasing temperature exposure on allergic rhinitis, due overall very low certainty of evidence. Further original research with better methodological quality is required.

    Matched MeSH terms: Climate Change
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