Ghana's National Energy Transition Framework: Domestic aspirations and mistrust in international relations complicate ‘justice and equity’

Energy Research & Social Science, Journal Year: 2024, Volume and Issue: 110, P. 103465 - 103465

Published: Feb. 7, 2024

This paper draws on a new global framework for energy justice – fair distribution of decision making, representation, the costs, and benefits services across time space to interrogate Ghana's National Energy Transition (NET) framework. It examines government's justifications not prioritizing green moving slowly towards net zero emission target 2070. Whereas domestic considerations such as accessibility affordability drive framework, this finds maze other factors too. Using thematic analysis four main data sources (interviews, news items, Living Standards Surveys, policy documents), that quagmire economic considerations, politics, unresolved national historical grievances interfere with objectivity transition discourses, which also clouds obvious inconsistency between practice services. The business-as-usual posture cannot achieve NET targets, but attitudes can change if western countries major emitters demonstrate goodwill in terms around climate action transitions. scenario Ghana has some legitimacy from country's intellectual communities is microcosm wider tensions about equity north south. finalisation provides planning zero, although it's 2070 doesn't show urgency, it offers regulatory environment international development partners engage contribute meaningfully transition.

Language: Английский

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Future Amplification of Multivariate Risk of Compound Drought and Heatwave Events on South Asian Population

Earth s Future, Journal Year: 2023, Volume and Issue: 11(12)

Published: Dec. 1, 2023

Abstract Over the past few decades, South Asia (SA) has experienced an upsurge in frequency of severe monsoonal compound drought and heatwave (CDHW) occurrences. Climate models that identify land‐atmosphere coupling as a major contributing factor for this exacerbation anticipate increase intensity CDHW occurrences future also represent this. For first time, study investigated evolution events based on new generations CMIP6 population products by applying multivariate framework. Specifically, explored impacts natural climate variability event risks their bivariate return periods two time‐periods emission scenarios across SA its subregions. The odds were then examined using logistic regression model association with anthropogenic drivers was determined. results indicate CDHWs occurrence is anticipated to substantially during late twenty‐first century (2056–2090). 50‐year might two‐fold most mid‐21st under high scenario. We find co‐occurring dry warm conditions rapidly strengthens soil moisture temperature are further exacerbated land‐atmospheric feedback loops. Our findings show persistent spells contribute significantly events, emphasizing regional exposure changing climates.

Language: Английский

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Anthropogenic and atmospheric variability intensifies flash drought episodes in South Asia

Communications Earth & Environment, Journal Year: 2024, Volume and Issue: 5(1)

Published: May 20, 2024

Abstract Flash droughts are abrupt and rapid intensification of that affect agriculture, water, ecosystems commonplace in South Asia. Despite their potential impact, flash drought evolution characteristics underlying mechanisms Asia remain underexplored. We use a multivariate approach to analyze the onset speed, frequency, severity, duration, return period droughts, role atmospheric circulation human-induced climate change. find more common intense crop season, especially central India, western Pakistan, eastern Afghanistan. They caused by persistent patterns block moisture transport Additionally, anthropogenic change has intensified spring-summer with median fraction attributable risk 60%, 80%, 90% for Afghanistan, respectively. Our results suggest will expand worsen future, requiring adaptation measures energy sectors.

Language: Английский

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Utilizing machine learning and CMIP6 projections for short-term agricultural drought monitoring in central Europe (1900–2100)

Journal of Hydrology, Journal Year: 2024, Volume and Issue: 633, P. 130968 - 130968

Published: Feb. 28, 2024

Water availability for agricultural practices is dynamically influenced by climatic variables, particularly droughts. Consequently, the assessment of drought events directly related to strategic water management in sector. The application machine learning (ML) algorithms different scenarios variables a new approach that needs be evaluated. In this context, current research aims forecast short-term i.e., SPI-3 from predictors under historical (1901–2020) and future (2021–2100) employing (bagging (BG), random forest (RF), decision table (DT), M5P) Hungary, Central Europe. Three meteorological stations namely, Budapest (BD) (central Hungary), Szeged (SZ) (east south Szombathely (SzO) (west Hungary) were selected agriculture Standardized Precipitation Index (SPI-3) long run. For purpose, ensemble means three global circulation models GCMs CMIP6 are being used get projected time series indicators (i.e., rainfall R, mean temperature T, maximum Tmax, minimum Tmin two socioeconomic pathways (SSP2-4.5 SSP4-6.0). results study revealed more severe extreme past decades, which increase near (2021–2040). Man-Kendall test (Tau) along with Sen's slope (SS) also an increasing trend period Tau = −0.2, SS −0.05, −0.12, −0.09 SSP2-4.5 −0.1, −0.08 SSP4-6.0. Implementation ML scenarios: SC1 (R + T Tmax Tmin), SC2 (R), SC3 T)) at BD station RF-SC3 lowest RMSE RFSC3-TR 0.33, highest NSE 0.89 performed best forecasting on dataset. Hence, was implemented remaining (SZ SzO) 1901 2100 Interestingly, forecasted SSP2-4.5, 0.34 0.88 SZ 0.87 SzO SSP2-4.5. our findings recommend using provide accurate predictions R projections. This could foster gradual shift towards sustainability improve resources. However, concrete plans still needed mitigate negative impacts 2028, 2030, 2031, 2034. Finally, validation RF prediction large dataset makes it significant use other studies facilitates making disaster strategies.

Language: Английский

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Agricultural drought assessment in data-limited arid regions using opensource remotely sensed data: a case study from Jordan

Theoretical and Applied Climatology, Journal Year: 2025, Volume and Issue: 156(2)

Published: Jan. 10, 2025

Language: Английский

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Exploring rainfall-driven climate hazards using the climate hazard index and historical data from ERA5 (study case: Indonesia)

Theoretical and Applied Climatology, Journal Year: 2025, Volume and Issue: 156(3)

Published: Feb. 11, 2025

Language: Английский

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Application of RNN-LSTM in Predicting Drought Patterns in Pakistan: A Pathway to Sustainable Water Resource Management

Water, Journal Year: 2024, Volume and Issue: 16(11), P. 1492 - 1492

Published: May 23, 2024

Water is a fundamental and crucial natural resource for human survival. However, the global demand water increasing, leading to subsequent decrease in availability. This study addresses critical need improved forecasting models amidst scarcity concerns exacerbated by climate change. uses best weather model sustainable development. Employing Recurrent Neural Network–Long Short-Term Memory (RNN-LSTM) approach, research enhances drought prediction capabilities integrating secondary data of rainfall, temperature, ground surface supplies. The primary objective forecast resources under changing climatic conditions, facilitating development early warning systems vulnerable regions. results from LSTM show an increased trend temperature rainfall patterns. relatively unstable observed. statistical analysis result was observed with model; model’s accuracy 99%, showing that it quite good at presenting obtained precipitation, data. Meanwhile, value root mean squared error (RMSE) about 13, 15, 20, respectively. Therefore, study’s highlight most suitable among artificial neural networks weather, resources. will help forecasting, agriculture, meteorological departments be effective forecasting.

Language: Английский

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Recent and projected changes in water scarcity and unprecedented drought events over Southern Pakistan

Frontiers in Earth Science, Journal Year: 2023, Volume and Issue: 11

Published: May 11, 2023

In recent decades, water scarcity is a significant constraint for socioeconomic development and threatens livelihood in an agriculture-based developing country like Pakistan. The crisis the projected to exacerbate coming years, especially southern parts. This dire situation calls investigation of major droughts, associated scarcity, changes teleconnection patterns over Southern Moderate low Southeastern monsoon (SEM) precipitation triggered extreme drought episode (2017–2020) Pakistan intensified scarcity. study explored severity respective event, underlying mechanisms, To investigate future (1980–2050) coupling models (global hydrological (GHMs)-global climate (GCMs)) have been used achieve interannual performance availability total consumption. Besides, scenarios this are combinations SSPs RCPs, including middle-of-the-road (SSP1-RCP4.5) fossil-fueled (SSP2-RCP8.5). findings indicated deficit 45% during 4-year (2017–2020), depicting worst events past 50 years. South observed SEM droughts last as 2000–2005 was (precipitation 75%), followed by 2017–2020 with 49% deficit. Water exacerbated dry spells that developed most between 2017 2020 result moderate-to-exceptionally precipitation. Furthermore, accompanied cool phase Pacific equatorial Indian Oceans. regions present sharp increase under SSP2-RCP8.5 scenario anticipated be already stressed regions. research essential environmentalists, resources managers, provided crucial information identify hot spot areas target region so problems could reduced future.

Language: Английский

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Implications of climate change on surface temperature in North Indian states: evidence from CMIP6 model ensembles

Frontiers in Environmental Science, Journal Year: 2023, Volume and Issue: 11

Published: Sept. 20, 2023

Introduction: The significant impact of climate change on temperature is an important topic discussion as it rises globally. Hence, the present study designed to investigate profound influence by considering North Indian States. Methods: In this comprehensive case study, CMIP6 models are used behaviour in states India under 1.5°C and 2°C warming scenarios. Comparisons made between observed surface data from Climatic Research Unit (CRU) ensemble mean simulations CMIP6. Results Discussion: indicate that effectively depict climatological patterns with negligible discrepancies. Under both scenarios, extreme temperatures show increase compared preindustrial periods, suggesting elevated risk future severe heat events. Temperature changes relative period around 1.5°C, 3°C, 4.5°C for present, respectively. Return analysis shows a rise approximately 4.5° over return time 60 years. These findings highlight importance models, valuable studies, emphasize need accurately enhance model iterations’ precision simulating regional climates. Urgent mitigation strategies vital curb mitigate potential adverse impacts region. Conclusion: provides critical insights into India’s behavior, underscoring significance proactive measures address challenges within

Language: Английский

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Assessment of Variability in Hydrological Droughts Using the Improved Innovative Trend Analysis Method

Sustainability, Journal Year: 2023, Volume and Issue: 15(11), P. 9065 - 9065

Published: June 3, 2023

The use of hydro-climatological time series to identify patterns is essential for comprehending climate change and extreme events such as drought. Hence, in this study, hydrological drought variability based on the standard index (SDI) using DrinC was investigated at ten (10) stations Upper Indus River Basin (UIRB) Pakistan a monthly timescale period 1961–2018. Moreover, applicability improved innovative trend analysis by Sen Slope method (referred hereafter IITA) evaluated comparison with (ITA) Mann–Kendall (MK). findings demonstrated significant decreasing from October March; other hand, April through September, increasing observed. In addition that, consistency outcomes across three methods also observed most cases, some discrepancies direction, Kharmong station. Conclusively, results all showed that IITA reliable effective due its capability investigate trends low, median, high values hydrometeorological timeseries graphical representation. A degree-day or energy-based model can be used extend temporal range link effects droughts temperature, precipitation, snow cover sub-basin scale.

Language: Английский

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