20253 research outputs found
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From discourses to systems—policymaking for adaptive management in the Brahmaputra River basin
Get PDFFlood and riverbank erosion management in the Brahmaputra River basin (BRB) has traditionally relied on structural engineering interventions. However, there is growing evidence of their ineffectiveness and the social-ecological concerns they raise, including emergent systemic risks. This paper presents a social-ecological systems approach, offering a model that acts as a boundary object to integrate knowledge, foster stakeholder collaboration to tackle community vulnerability, and facilitate policy experimentation—key elements for advancing adaptive management. Employing systems thinking and system dynamics-based modelling can bridge the divide between science and policy, especially in areas characterized by data limitations and uncertainties like the BRB. This study adopts a nested approach encompassing three scales: macro (basin-level hydro-geomorphology), meso (flood control policies and infrastructure at administrative levels), and micro (village-level socio-economic conditions). The constructed boundary object promotes cross-scale learning and policy experimentation. Model scenarios of policy alternatives demonstrate that an integrated strategy—leveraging land covered with coarse sediment, innovating land use, and redesigning floodplains—significantly enhances effective land use and minimizes embankment failures. The findings emphasize the reinforcing dynamics between embankment degradation and community protests, highlight the limitations of compensation mechanisms, and reveal the erosion of adaptive capacity under the current control-based policy regime. A crucial insight from this study is that flood management strategies must evolve continually, reflecting scientific advancements, assessing policy impacts, and addressing local adaptation needs. Furthermore, a greater focus on riparian land use within development strategies is essential. The model scenarios advocate transitioning from traditional flood control to a landscape design harmonizing cropping practices and floodplain development with river morphology dynamics. While rooted in the Indian BRB context, the modelling framework provides a basis for adaptive water governance in other sediment-rich, politically sensitive, and hydrologically dynamic transboundary basins
A multi-level integration framework for sustainable nitrogen management in tropical agriculture
No full textNitrogen (N) loss and inefficiency threaten both food security and environmental sustainability in tropical agriculture. Despite growing N inputs, many tropical systems suffer from low N use efficiency (NUE) and high pollution due to poor management. Aligning agricultural productivity with environmental safety remains a major challenge, given the lack of integrated, context-specific decision-support approaches. Here, we present a systematic multi-level integration framework to assess the N carrying capacity required to meet crop productivity while staying within safe N surplus limits, enabling a hierarchy of strategic interventions—including N fertilizer quotas, 4R-plus stewardship, and integrated crop-livestock systems. Using Hainan Island, China, as a representative case, we demonstrate that achieving N carrying capacity, target NUE levels, and halving N losses requires combining optimized cropland management with enhanced internal nutrient recycling. Scenario analysis shows that integrated strategies can increase NUE by up to 26 percentage points (from 23% to 49%) and reduce synthetic N input by nearly 50%. This work offers a scalable pathway to support evidence-based technological and policy solutions for sustainable N management in tropical agriculture
Exploring the use of satellite imagery and computer vision‐based machine learning method to improve the spatial granularity of poverty statistics
No full textSpatially granular poverty statistics can enhance the efficiency of targeting resources to improve the living conditions of the poor. Previous studies suggest that the use of high‐resolution satellite imagery may be an alternative approach in generating granular poverty maps. This study outlines the methods in improving the spatial granularity of government‐published poverty estimates using convolutional neural networks and ridge regression applied on publicly available satellite imagery, household surveys, and census data from the Philippines and Thailand. A convolutional neural network (CNN) was used to extract features of satellite images that are correlated with the intensity of nightlights. These features were then aggregated at the same level for which government‐published estimates were available to estimate a prediction model for poverty rates. Results suggest that the adopted methodology performed satisfactorily in predicting lower levels of nightlight intensity for the specific years considered in this study. Additional preliminary numerical assessment also reveals that prediction accuracy may be enhanced by using random forest as an alternative to ridge regression. The use of proprietary satellite images with higher resolution may also improve prediction accuracy
Capacity building needed to reap the benefits of access to biodiversity collections
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Global conservation efforts increasingly depend on digitised natural history collections, yet the benefits of this digital data are not equally shared. We analysed biodiversity specimens and citation data from Montserrat and the Cayman Islands to assess who collected these specimens, how they are used, and by whom. We found that despite increased accessibility, research using these data is still dominated by institutions in the Global North, with limited involvement or benefit for local communities. Our findings underscore the urgent need for investment in training, infrastructure, and equitable partnerships to ensure long‐term conservation capacity in biodiverse but under‐resourced regions.
Summary
This research examines biodiversity specimens from two areas of the Caribbean to understand patterns of collection and the roles of the people involved. Using open data from the Global Biodiversity Information Facility (GBIF) and Wikidata, we aimed to uncover geographic and historical trends in specimen use. This study aims to provide concrete evidence to guide collaboration between collection‐holding institutions and the communities that need their resources most.
We analysed biodiversity specimens from Montserrat and the Cayman Islands in three steps. First, we extracted specimen data from GBIF, disambiguated collector names, and linked them to unique biographical entries. Next, we connected collectors to their publications and specimens. Finally, we analysed the modern use of these specimens through citation data, mapping author affiliations and research themes.
Specimens are predominantly housed in the Global North and were initially used by their collectors, whose focus was largely on taxonomy and biogeography. With digitisation, use of these collections remains concentrated in the Global North and covers a broader range of subjects, although Brazil and China stand out as significant users of digital collection data compared to other similar countries.
The availability of open digital data from collections in the Global North has led to a substantial increase in the reuse of these data across biodiversity science. Nonetheless, most research using these data is still conducted in the Global North. For the non‐monetary benefits of digitisation to extend to the countries of origin, capacity building in the Global South is crucial, and Open Data alone are insufficient
The Demographic Race between India and China
Get PDFAs India surpasses China as the world’s most populous country, questions arise as to whether this demographic shift will lead India to overtake China economically. This paper examines this demographic race beyond population size. Using multi-dimensional demographic projections by age, sex, education, and labor force participation, we show that China’s current apparent demographic travails will not necessarily threaten its leading status relative to India for most of the next half century given India’s disadvantage in educational attainment and very low female labor force participation. India’s young population could provide a demographic dividend later this century, but only if it makes substantial investments in education and increasing women’s labor force participation rates. The demographic race between giants will be determined more by human capital development than simply by total population size
Drivers of environmental externality reduction in China's electric power industry: A spatial-temporal analysis
No full textChina's electric power industry has made significant efforts to reduce environmental externality in the past two decades. However, the extent of the reduction, the driving factors behind it, and the regional performance are not well clarified. This study constructs a comprehensive framework that integrates the impact pathway approach with index decomposition analysis to explore the driving factors behind the reduction of environmental externality from a spatial-temporal perspective. First, the Greenhouse Gas-Air Pollution Interactions and Synergies (GAINS) model is adopted in the impact pathway approach to assess the environmental losses in China's electric power industry. Second, the temporal index decomposition analysis is used to explore the driving factors behind the reduction in environmental losses during 2005-2020. Third, the spatial index decomposition analysis is employed to investigate the differences in environmental performance across regions and the driving forces behind these differences. The results show that the environmental losses caused by China's electric power industry have been significantly reduced from 3082.1 thousand years of life lost (YLL) in 2005 to 892.3 thousand YLL in 2020, mainly due to the reduction in air pollutant emissions, followed by the cleaner power structure and the adjustment of the spatial layout of electricity. While, increases in power generation scale, population size, and aging have played a negative role in reducing environmental losses. The gaps in environmental losses per unit of electricity between different provinces can be tens or even hundreds of times. The primary drivers of these gaps, apart from the power structure, are atmospheric dispersion conditions and population density. While, the differences in emission intensity effects among provinces are relatively small. Thus, the orientation of policy design needs to shift from setting stricter emission concentration limits to adjusting energy structure and enhancing the construction of electricity transfer channels. Government departments should consider the implicit environmental externality from a more macro perspective when conducting power planning and management
Place attachment, activation of personal norms, and the role of emotions to save water in scarcity
Get PDFWater bodies across (semi)arid regions are being pressured by climate change and agriculture. Aptly, in Iran, Urmia Lake's fate is in contestation of these two stressors. Whereas climate change mitigation mandates a huge far-lasting global endeavor, some regional adaptations may support the lake to survive ecologically. This needs accountable actions by both institutions and individuals, contributing to the agricultural dynamism. To ensure the effectiveness of institutional lake restoration plans, the consent, cooperation, and active participation of farmers are essential. The critical issue is to know how to persuade farmers and foster prudent water consumption as the prime strategy. This requires understanding farmers intention and behavior in relation to water conservation. To explore this in the region, a specific sociopsychological model was developed. Utilizing the Norm Activation Model enriched by the constructs of Place Attachment and Expression of Emotion, farmers' moral water conservation behavior in the Urmia Lake Basin was investigated. The results of structural equation modeling revealed that all factors of the model influence the water conservation intention and behavior. While awareness of consequences strongly affects personal norms and appraisal of responsibility, place attachment and appraisal of responsibility positively impact emotions and correspondingly emotions and place attachment affect intention significantly. Whereas personal norms were influenced by awareness of consequences and appraisal of responsibility, they impact behavior and intention significantly and eventually intention makes the strongest relationship with behavior. Uncovering this, the study aims to expose further pragmatic insights for credible and sustainable environmental management policies
Delayed Monetary Policy Effects in a Multi-Regime Cointegrated VAR(MRCIVAR)
No full textThe effectiveness of monetary policies under delayed policy impacts are explored. Initially, in the context of a differential delay system, the macro-finance link is investigated. The nonlinear macro system with delays gives rise to a time-delayed optimal control problem. The optimality conditions are then analyzed, and the control problem is numerically solved by discretization and optimization methods. These solutions suggest that with too much delay, destabilizing financial conditions may emerge, rendering the policy ineffective. Then the possibility of asymmetric adjustments to a long-run steady-state, in a non-stationary environment is explored using a multi-regime cointegrated VAR (MRCIVAR) model for both an interest rate cut, and a non-interest rate cut regime. Though the rate cuts may not perform well with too long of a delay, given diverse shocks, monetary policy still performs better in a rate cut regime. Given the perils of deteriorating financial conditions, the better stabilization properties in a rate cut regime are empirically validated through data for European countries and the US
Multidimensional sustainability implications of alternative iron and steel industry decarbonization strategies in China
No full textThe urgency of a rapid and deep decarbonization of the iron and steel (IS) industry cannot be overstated in pursuing China's carbon neutrality target. Beyond CO2 emissions, the IS industry is also responsible for numerous non-climate impacts. We explored the impacts of alternative decarbonization options of the IS industry on economic cost, water, energy, CO2, and air pollutant emissions from a systematic perspective. While all decarbonization pathways yield co-benefits on air pollutants emissions for the IS industry, the profiles of carbon leakage and spillover effect depend strongly on technology choice. Mitigation scenarios focusing on hydrogen-based direct reduction result in increases of CO2, SO2, and NOx emissions from upstream energy supply. In CCS-led scenarios, fuel substitution could result in an expansion of charcoal-making and corresponding emissions of particulate matter. Thus, policymakers must consider the proper combination of upstream energy supply chain and decarbonization options for IS to avoid undesirable outcomes
System impacts of wind energy developments: Key research challenges and opportunities
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Wind energy is currently one of the cheapest renewable energy technologies and plays a central role in many countries’ climate and energy strategies. However, like any electricity-generation technology, wind energy affects and interacts with the broader environmental, social, economic, technical, and legal systems it integrates with. These impacts can potentially slow its deployment, delaying progress on essential decarbonization and energy security objectives. Solutions often exist, but challenges remain due to fundamental research gaps and limited understanding of the true scale of impacts. This article identifies four broad impact categories and fourteen individual impacts, which we systematically analyze through a review of over 400 scientific articles. We qualitatively assess these impacts in terms of importance and spatial diversity, proposing concrete solutions where possible, and suggesting directions for future research. We also demonstrate that some recurring issues are actually not substantial, such as bird and bat collisions, noise and health impacts, local weather changes, and market price impacts at low penetration levels. However, we identify several genuine issues that are currently hard to solve, such as lengthy planning and permitting processes, rare earth material dependency, the recycling of blades, visual impacts on landscapes, and integration into power systems at high penetration levels.
Summary
Wind power accounted for 8% of global electricity generation in 2023 and is one of the cheapest forms of low-carbon electricity. Although fully commercial, many challenges remain in achieving the required scale-up, relating to integrating wind farms into wider technical, economic, social, and natural systems. We review the main challenges, outline existing solutions, and propose future research needed to overcome existing problems. Although the techno-economic challenges of grid and market integration are seen as significant obstacles to scaling up wind power, the field is replete with solutions. In many countries, planning and permitting are immediate barriers to wind-power deployment; although solutions are emerging in the EU and several countries, the effectiveness and long-term acceptance of fast-track permissions and go-to areas remains to be seen. Environmental impacts on wildlife and recycling challenges are rising issues for which tested and scalable solutions are often still lacking, pointing to large remaining research requirements