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Summary: We propose the construction of conditional growth densities under stressed factor scenarios to assess the level of exposure of an economy to small probability but potentially catastrophic economic and/or financial scenarios, which can be either domestic or international. The choice of severe yet plausible stress scenarios is based on the joint probability distribution of the underlying factors driving growth, which are extracted with a multilevel dynamic factor model (DFM) from a wide set of domestic/worldwide and/or macroeconomic/financial variables. All together, we provide a risk management tool that allows for a complete visualization of the dynamics of the growth densities under average scenarios and extreme scenarios. We calculate growth‐in‐stress (GiS) measures, defined as the 5% quantile of the stressed growth densities, and show that GiS is a useful and complementary tool to growth‐at‐risk (GaR) when policymakers wish to carry out a multidimensional scenario analysis. The unprecedented economic shock brought by the COVID‐19 pandemic provides a natural environment to assess the vulnerability of US growth with the proposed methodology.

Recycling schemes for long‐lived products are challenged by the presence of “legacy substances,” which have been used in production in the past, but are nowadays classified as substances of concern. This study quantitatively evaluates the trade‐offs between phasing out legacy substances, increasing circularity levels, and reducing life cycle impacts of polyvinylchloride (PVC) window profiles recycling in Germany based on a comprehensive dynamic material and substance flow analysis coupled with a prospective life cycle assessment. Scenario results indicate that although lead had been phased out in virgin PVC by 2015, lead concentrations in end‐of‐life PVC window profiles will remain above 0.3% until the end of the century without a restriction of lead in recycled PVC and will be by factor 3–5 higher compared to a restriction as stipulated by EU 2023/923. However, the latter is associated with lower recycling rates and higher life cycle environmental impacts of PVC window frame waste management, which cannot be fully compensated by the introduction of new waste treatment pathways using currently available technologies. The study serves to introduce a new comprehensive modeling framework, which allows for the consideration of trade‐offs between substance, material, and environmental impact dimensions as a basis for discussing and developing sustainable waste management strategies. [ABSTRACT FROM AUTHOR]

As the largest producer and consumer of copper, China is facing enormous challenges from carbon peaking and neutrality. This article adopts “bottom‐up” and “top‐down” methods to construct a more accurate model, to predict the CO2 emissions of China's copper smelting industry, and explores its potential for carbon reduction in the future from three scenarios as the baseline scenario (BAU), the general low‐carbon (NLC), and the enhanced low‐carbon (ELC). The results show that the CO2 emissions can achieve a peak in 2028 either in NLC or ELC scenarios, with a peak range of 14.9–16.88 million tonnes. Prior to reaching the peak, the contributions of energy adjustment, material substitution, and process selection to carbon reduction have significantly improved, and the contribution rates increased from 30.91%, 4.11%, and 1.46% to 42.7%, 32.07%, and 15.63% in ELC scenario. After the peak, the contribution of energy adjustment gradually slows down, while the material substitution continues to increase, and the contribution rates increased from 21.25% and 32.07% to 29.38% and 40.01% in NLC and ELC scenarios. In the future, concentrate oxygen‐enriched bottom‐blowing smelting and direct refining from waste copper anode furnaces show ideal potential for carbon reduction before 2025, increasing the proportion of recycled copper production, and adjusting energy structure will be more effective from 2025 to 2035. The conclusions of this study can provide a scientific basis for formulating policy recommendations for green and low‐carbon development of the copper industry in China and all over the world in the future. [ABSTRACT FROM AUTHOR]

Background: An increasing number of orphan medicinal products (OMPs) are being included in social health insurance schemes, significantly improving access to medicines for patients with rare diseases. However, high-priced OMPs are still not covered, primarily due to health equity controversies and inadequate data systems required for economic evaluation. The aim of this study was to estimate the burden of drug expenditures and the size of the reimbursement budget required for high-priced OMPs from the perspectives of society and healthcare payers. Methods: The study performed a budget impact analysis using data from multiple sources to estimate the reimbursement budget for high-priced OMPs in Chengdu, a densely populated metropolis in China. The budget analysis consisted of three main elements: the number of patients, the price of drugs, and the simulated policy scenario. By adjusting the combinations of these elements, the budget fluctuations for payers were estimated. Furthermore, the study predicted the budget trend for the next three years to validate its sustainability. Results: The analysis indicated that 98 rare disease patients in Chengdu required high-priced OMPs in 2019. This suggested a projected budget of CNY 179 million for these patients without reimbursement policies, from a societal perspective. Under six assumed policy scenarios, this budget ranged from CNY 32 million to CNY 156 million. Over the next three years, the annual budget was estimated to range from CNY 200 million to CNY 1.303 billion. Conclusion: Integration of multi-source data helps to obtain more scientifically reliable results on budget impacts. The study found that the budgetary impacts of high-priced OMPs on society and payers are relatively limited. Health policymakers can choose appropriate reimbursement strategies based on financial affordability among a diverse mix of elements. The results of related studies provided insights for optimizing the allocation of health resources and improving patient access to medications. [ABSTRACT FROM AUTHOR]

The democratization of artificial intelligence (AI) involves extending access to AI technologies beyond specialized technical experts to a broader spectrum of users and organizations. This paper provides an overview of AI's historical context and evolution, emphasizing the concept of AI democratization. Current trends shaping AI democratization are analyzed, highlighting key challenges and opportunities. The roles of pivotal stakeholders, including technology firms, educational entities, and governmental bodies, are examined in facilitating widespread AI adoption. A comprehensive framework elucidates the components, drivers, challenges, and strategies crucial to AI democratization. This framework is subsequently applied in the context of scenario analyses, offering insights into potential outcomes and implications. The paper concludes with recommendations for future research directions and strategic actions to foster responsible and inclusive AI development globally. [ABSTRACT FROM AUTHOR]

Aluminum metal is used in a wide range of applications such as construction, transportation, power, and aerospace. Previous studies have mainly used a top-down approach to explore future aluminum stocks and flows in China. In this study, we developed a dynamic material flow analysis model using a bottom-up approach to simulate aluminum flows and stocks in China until 2050, based on current government and sector policies. The results show that China's aluminum stocks will be nearly saturated by 2050, with a total and per capita of 591 million tons (Mt) and 449 kg/per, respectively. The domestic demand for aluminum will grow until 2030 and will remain relatively stable thereafter at around 28–30 Mt. Construction and transport are the two sectors with the highest demand for aluminum, accounting for over 60% of the total aluminum demand. The domestic aluminum scrap will increase almost sevenfold, from 2.7 Mt to 20.0 Mt between 2020 and 2050. However, even assuming a 90% recycling rate, secondary aluminum will at best meet around 70% of demand by 2050. To realize sustainable development in China's aluminum industry, extending the life of aluminum products and increasing aluminum scrap recycling are sensible measures. [ABSTRACT FROM AUTHOR]

This paper aimed to address the challenges of climate change and water scarcity in the sustainable development of agriculture in the Yellow River Basin by promoting the cultivation of drought-tolerant crops, thereby alleviating regional agricultural water pressure and analyzing their water-saving and carbon-reducing synergistic effects. The study has designed different development scenarios including trend as usual, slow growth, technology-driven and policy-supported scenarios, formulating the analysis schemes for the water-saving and carbon-reducing synergistic effects of expanding the cultivation of four drought-tolerant crops of wheat, maize, sorghum and potato. The agricultural water-saving potential correction model and the agricultural carbon reduction potential model were utilized to quantitatively evaluate the water- saving effects and carbon-reduction potential of expanding drought-resistant crops under different scenarios. The results show that wheat and maize have the largest planting areas, while sorghum and potato have relatively smaller areas. Under the policy-supported scenario, the expansion scale of these crops will reach to 231.2 thousand hectares (wheat), 173.4 thousand hectares (maize), 346.8 thousand hectares (sorghum) and 404.5 thousand hectares (potato) by 2060. In the technology-driven and policy-supported scenarios, the water-saving and carbon reduction effects of crops in the middle and lower reaches of the Yellow River will be significantly increased, the total water saving in the study area will reach to 15.35 billion cubic meters, and the average carbon reduction potential will reach to 65.93 t/km² by 2060. There- fore, promoting drought-tolerant crops in the middle and lower reaches of the Yellow River can help alleviate water scarcity, ensure regional food security, and achieve multiple goals of water-saving, carbon-reduction and income-increasing. [ABSTRACT FROM AUTHOR]

Mitigating agricultural carbon emissions is pivotal for attaining the objectives of carbon peak and carbon neutrality. Utilizing a time-varying parametric Cobb-Douglas (C-D) production function, this study employs an enhanced Logarithmic Mean Divisia Index (LMDI) decomposition approach, the Tapio decoupling model, and Monte Carlo simulations to investigate the determinants and decoupling dynamics of agricultural carbon emissions within Sichuan Province from 2010 to 2020. The findings reveal that: (1) Factors such as carbon emission intensity, agricultural structure, labor inputs, and capital stock played a significant role in suppressing agricultural carbon emissions, collectively contributing to a reduction of 484.12 million tonnes. (2) The unstable decoupling of agricultural carbon emissions from economic development in Sichuan Province. Capital stock, alongside carbon emission intensity and agricultural structure, significantly contributed to this decoupling. To harmonize agricultural economic growth with carbon emission reduction, emphasis should be placed on manure management and resource utilization in livestock and poultry farming. Furthermore, leveraging technological advancements to enhance resource efficiency is crucial for reducing carbon emissions. Simultaneously, strategic management of fixed asset growth, focused on energy conservation, can catalyze the synergistic effects of economic development and technological spillovers. [ABSTRACT FROM AUTHOR]

Characterizing and quantifying livestock carbon emissions helps mitigate temperature rise and potential climate risks. Here, the spatial and temporal characteristics of China's carbon emissions of meat, egg, and milk are analyzed from the perspective of production and consumption. A driving factor decomposition model of carbon emissions of meat, egg, and milk production and consumption is established using the logarithmic mean Divisia index (LMDI). Using a static scenario analysis and dynamic Monte Carlo simulations (MCS), the evolution trajectory of carbon peak in meat, egg, and milk production and consumption in China during 2021–2030 is analyzed. China's carbon emissions from meat, egg, and milk production and consumption have risen in 2020, reaching 794.1 and 465.88 Mt, respectively. Moreover, western China has the highest carbon emissions in production (33.84%), which are concentrated in Sichuan, Inner Mongolia, and Xinjiang. For consumption, the carbon emissions are mainly concentrated in the eastern region (42.96%), and Guangdong is the primary source of carbon emissions in eastern China. The key drivers of carbon emissions for this production and consumption are the farmland output value and residential income effects, respectively. Conversely, reverse urbanization, agricultural industry structure, and food money purchasing power effects play significant suppressive roles. Under the business-as-usual scenario (BAU), China's carbon emissions from meat, egg, and milk production and consumption in 2030 will increase by 40.1% and 4.86% from 2020, respectively. The middle low-carbon scenario (Mid-LC) mitigates carbon emission growth by 24.51% and − 5.7%, respectively, for the production and consumption of meat, egg, and milk in 2030 compared to 2020. In the highly low-carbon scenario (Hig-LC), production and consumption will achieve a carbon peak by 2030. Ultimately, this study highlights the importance of reducing carbon emissions from livestock on production and consumption, and provides help for China's agricultural green development from the geospatial characteristics, drivers, and future trends of carbon emissions at both the production and consumption sides. [ABSTRACT FROM AUTHOR]

The water–energy–food (WEF) nexus constitutes a pivotal aspect of regional ecological protection and high-quality development. The exertion of multiple WEF-related policies would engender both synergies and trade-offs within the WEF nexus. However, a quantified framework that integrates the impact of multiple WEF-related policies with conventional WEF nexus assessments and simulations is currently lacking. This study quantified the WEF nexus in the Yellow River basin (YRB) of China under the influence of multiple policies, calculated the current and future WEF scores under different policy combination scenarios using the improved entropy weight method, the auto-regressive integrated moving average (ARIMA) model, and the linear optimization method. The results revealed the following: (1) From 2000 to 2020, WEF overall scores and subsystem scores were substantially increased with spatial heterogeneity. (2) Scenario analysis indicated that policy implementation would generally accelerate WEF score improvements in each city, yet embracing all policies simultaneously was not optimal for each city. (3) The spatial heterogeneity in policy impacts was also found in the YRB, with higher trade-offs in the upper reaches of cities, and higher synergies in the middle and lower reaches of cities. To attain high-quality development within the YRB, the related policies' implementation should consider the regional disparities and enhance the optimization of resource allocation across the regions. [ABSTRACT FROM AUTHOR]

In 2022, a severe outbreak of disease caused by clade 2.3.4.4b Highly Pathogenic Avian Influenza (HPAI) H5N1 virus resulted in unprecedented mortality among wild birds in eastern Canada. Tens of thousands of birds were reported sick or dead, prompting a comprehensive assessment of mortality spanning the breeding season between April 1 and September 30, 2022. Mortality reports were collated from federal, Indigenous, provincial, and municipal agencies, the Canadian Wildlife Health Cooperative, and other nongovernmental organizations, universities, and citizen science platforms. A scenario analysis was conducted to refine mortality estimates, accounting for potential double counts from multiple sources under a range of spatial and temporal overlaps. Correcting for double counting, HPAI is estimated to have caused 40,391 wild bird mortalities in eastern Canada during the spring and summer of 2022; however, this figure underestimates total mortality as it excludes unreported deaths on land and at sea. Seabirds and sea ducks, long‐lived species that are slow to recover from perturbations, accounted for 98.7% of estimated mortalities. Our study provides estimates of bird mortality, with Northern Gannets (Morus bassanus; 25,669), Common Murres (Uria aalge; 8133), and American Common Eiders (Somateria mollissima dresseri; 1894) exhibiting the highest mortality figures. We then compare these mortality estimates with recent population estimates and trends and make an initial assessment of whether biologically meaningful population‐level impacts are possible. Specifically, we focus on the Northern Gannet, a species that has suffered significant global mortality, and two harvested species, Common Murre and American Common Eider, to inform management decisions. Our analysis suggests population‐level impacts in eastern Canada are possible for Northern Gannets and American Common Eiders, but are unlikely for Common Murres. This study demonstrates a comprehensive approach to assessing mortality and underscores the urgent need for further research to understand the broader ecological ramifications of the HPAI outbreak on wild bird populations. [ABSTRACT FROM AUTHOR]

Municipal solid waste management has a potential to increase circularity by reduction of virgin material extraction and use of secondary materials. A scenario analysis tool was developed to assess whether circular economy goals are attainable with the existing infrastructure and technologies by calculating sorting and recycling rates using waste amount and composition estimations. Three scenarios, Current Road (business as usual), Circular Road (improved sorting) and Frugal Road (waste reduction), were developed and implemented. Sorting rates targets for food waste are achieved in all scenarios. For plastic, sorting rate targets are achieved only for Circular and Frugal, while European Union recycling targets are not reached in any, showing the important role of recycling efficiency. Policy makers can use the scenario development approach of this study to evaluate if circular economy goals are attainable with the current system and assess the impact of key factors such as waste generation and sorting behavior. The scenario analysis tool can be utilized to simulate the effects of different measures in the waste amounts and composition, which is crucial for the planning of the future management system. Further, sorting and recycling rates provide quantitative information about the circularity gap and qualitative information on bottlenecks and opportunities. [ABSTRACT FROM AUTHOR]

This paper incorporates mortality shocks in the scenarios for future mortality rates produced by a stochastic multi‐population mortality model. Hereto, the proposed model combines a decreasing stochastic mortality trend with a mechanism that switches between regimes of low and high volatility. During the high volatility regimes, mortality shocks occur that last from one to several years and temporarily impact the mortality rates before returning to the overall mortality trend. Furthermore, we account for the age‐specific impact of these mortality shocks on mortality rates. Actuaries and risk managers can tailor this scenario generator to their specific needs, risk management objectives, or supervisory requirements. The generated scenarios allow (re)insurers, policymakers, or actuaries to evaluate the effects of different catastrophe risk scenarios on, for example, the calculation of solvency capital requirements. [ABSTRACT FROM AUTHOR]

Forest management allows the sustained removal of significant amounts of carbon from the atmosphere. Within different activities in the forest, wood utilisation has the most significant man-made environmental impact which affects the carbon balance, which is important to know, to be able to accurately identify its role in climate change. This study aims to determine the carbon footprint of logging during utilisation based on scenario analysis in national default and theoretical assortment structures (11 additional scenarios for each forest stand) within the entire life cycle of raw wood products. Based on a common functional unit (100 m3 of cut wood), a comparative environmental life cycle analysis (LCA) for intermediate and final cutting was performed in shortwood forestry work systems in beech (Fagus spp.), oak (Quercus spp.), spruce (Picea spp.), black locust (Robinia pseudoacacia), and hybrid poplar (Populus x euramericana) stands in Hungary. After obtaining the results, the present study calculated the carbon footprint order for the utilisation life cycle phases and the entire tree utilisation life cycle. The distribution of absolute carbon footprint (ACF: considered emitted CO2 from fossil and biotic origins together) by final cutting exhibited the following order: hybrid poplar (6%)—spruce (8%)—beech (26%)—oak (27%)—black locust (33%). The ACF ranking for the whole technological life cycle (intermediate and final cutting, 400 m3 of cut wood) was hybrid poplar– spruce—oak—beech–black locust. The carbon footprint rankings of the studied stands were expanded to the national level. [ABSTRACT FROM AUTHOR]

Urban greening is a major goal in policies for sustainable cities, and spatial planners are nowadays strongly interested in the benefits of greenspace for the well-being of urban residents. We present a novel, model-based approach to support the development of effective greening strategies. The approach is quantitative and spatially explicit and accounts for multiple health benefits as well as burdens. In our study, we applied this generic approach to the city of Maastricht (The Netherlands) and conducted an integrated, city-scale assessment of the health benefits and burdens of four urban greenspace designs. These included: 'No greenspace', 'Current greenspace', 'Green parking lots and squares', and 'Optimized greenspace locations'. For each greenspace design, indicator values were calculated for five determinants of health and well-being: heat stress, air pollution, perceived unsafety, unattractive views, and tick-bite risk. To assess the health contribution of urban greenspace in a given design, these indicator values were compared with the values in the 'No greenspace' design. The study produced clear, quantitative conclusions about the health benefits and burdens of the urban greenspace designs for the case of Maastricht but also generated novel, more general insights relevant to the planning of urban greenspace for health and well-being. These insights concern the importance of translating health policy objectives into specific target values or thresholds and the importance of 'smart' choices in greenspace type and location that can effectively reduce trade-offs between health benefits and burdens, as well as the insights that adding more greenery not always improves urban health and that urban greenspace alone cannot solve major air pollution problems. The priorities for future research, which will address the limitations of the presented approach, concern a further expansion of the range of health benefits and burdens covered by the model and the development of a common metric for the entire range of health benefits and burdens to optimize greenspace design and maximize its overall net health benefit. [ABSTRACT FROM AUTHOR]

Combined PM2.5 and O3 pollution in China has caused negative health impacts on residents and reduced crop yields. The quantitative assessment and prediction of these impacts could provide a scientific basis for policy development. This study assessed the nationwide premature mortality, health effects, and crop damage attributable to PM2.5 and O3 pollution in 2019, and projected the associated health and agricultural losses under a business-as-usual (BAU) scenario for 2025. The economic benefits of improving air quality under different policy scenarios, including the 14th Five-Year Plan (FFP), Secondary Standard Limit (SSL), and Primary Standard Limit (PSL), were also explored. The results showed PM2.5 pollution in 2019 resulted in 246,000 all-cause premature deaths and the economic health loss was RMB 196.509 billion. Similarly, O3 pollution caused 186,300 premature deaths and the economic health loss was RMB 155.807 billion. O3 pollution has led to a loss of 28.5241 million tonnes of crop production and an economic loss of RMB 62.268 billion. Compared with 2019, the avoidable premature deaths from PM2.5 under different scenarios in 2025 were 50,600, 43,000, and 200,300 cases, respectively, exceeding the number of avoided premature deaths from O3 pollution. Compared with the BAU, reducing PM2.5 under different scenarios could generate economic benefits of RMB 70.178 billion, RMB 60.916 billion, and RMB 229.268 billion. Furthermore, the FFP scenario outperformed the SSL in mitigating winter wheat production losses caused by O3 pollution. These results provide important scientific support for the development and evaluation of future comprehensive pollution control measures for PM2.5 and O3. [ABSTRACT FROM AUTHOR]

The walkability is closely related to the lifestyle and health of local residents. Unreasonable community design may result in spatially segregated spaces, creating walking barriers for residents and reducing walking accessibility. If a community's physical layout can be optimized through better walking-related planning at the community level, people would be more convenient to reach more facilities with a better walking accessibility. A microscale measurement method for walkability at the community level is necessary to assist in community planning. This study developed a new measurement of walkability using a hexagon-based adaptive crystal growth algorithm and verified its effectiveness by examining the impact of gated communities on walkability. Taking three communities in Beijing as cases, this study created two kinds of accessibility planes (with-wall and no-wall) to compare changes in walkability between gated and open communities. The findings show that gate and wall removal can partially improve community walkability and that the algorithm can accurately measure community walkability in different scenarios. The proposed algorithm provides a new perspective for walkability measurements and offers a scientific tool for people-oriented community planning. [ABSTRACT FROM AUTHOR]

The power to gas (P2G) equipment serves as a critical linkage in integrated energy systems that foster bidirectional energy flow to enhance the share of renewable energy and curb uncertainty. By bringing together P2G hydrogen production and hydrogen injection into gas grid technology, the energy conversion loss associated with P2G applications can be significantly reduced. Nonetheless, the strict criteria concerning hydrogen blending ratios pose limitations on the integration of renewable energy. This paper proposes a comprehensive energy system model that couples gas grid hydrogen injection with a hybrid P2G process, aiming to reduce energy conversion losses and overcome the constraints posed by hydrogen blending ratios. This approach promotes the efficient utilization of renewable energy in integrated energy systems (IES). For wind power uncertainty, a scenario analysis method combining Latin hypercube sampling and scenario curtailment 0–1 algorithm is employed. The model's nonlinear constraints are linearized through piecewise linearization, transforming the problem into a mixed-integer programming one for solution simulation results demonstrate that the application of the hybrid P2G process in IES systems with hydrogen injection into gas grid technology reduces certain energy conversion stages and cost inputs compared to using only power to hydrogen conversion. This approach shows significant improvements in economic and environmental performance. The hybrid P2G scheme reduces the hydrogen blending ratio of the system to the minimum operating cost from 12 % to 6 %. At the same time, its minimum value is 20.1 thousand USD lower than that of the scheme using only power to hydrogen conversion, which is about 4.7 % of the total cost. [Display omitted] • An IES based on hybrid P2G and hydrogen injection into gas grid is proposed. • The conversion rate is used to analyze the effect of renewable energy consumption. • The 0–1 algorithm is used to curtailment scenarios to capture the uncertainties. • A multi-scenario model is constructed to optimize capacities and operation. • The optimal economic performance is achieved at the hydrogen blending ratio of 6 %. [ABSTRACT FROM AUTHOR]

The emerging field of prospective life cycle assessment (pLCA) offers opportunities for evaluating the environmental impacts of possible future consumption shifts. One such shift involves a transition from meat‐based to plant‐forward diets, acknowledged to mitigate environmental impacts of the food system under present day conditions. Current diets are often meat intensive (“meat‐based”), whilst “plant‐forward” diets include mainly plant‐based foods, encompassing flexitarian, vegetarian, and vegan diets. Here we illustrate the application of pLCA in a case study of meal options, implementing shared socio‐economic pathway scenarios in the LCA background system to represent future production conditions. We assess the climate footprints and land‐based biodiversity footprints of a typical meat‐based meal in Germany and Indonesia compared to a plant‐forward meal in both countries (i.e., four meals), now and in 2050. Our findings show that the plant‐forward alternative maintains a lower impact per serving in all future scenarios. At the same time, the reduction in impact for the meat‐based meals is more pronounced in future scenarios due to shifts in the agricultural system. Our findings highlight the importance of supply‐side measures to produce lower‐impact ingredients, complementing demand‐side interventions to reshape food consumption. Results are further evaluated in cultural and nutritional contexts, highlighting the practical decision‐making constraints faced by consumers. We find potential “leakage” effects in calories and nutrition when choosing a lower‐impact, plant‐forward meal. These leakage effects should be considered in future studies seeking to evaluate the environmental implications of meal substitutions in the context of broader dietary requirements. [ABSTRACT FROM AUTHOR]

Jiangsu Province is a region with a high concentration of economy and population in China, as well as a spatial unit with relatively concentrated carbon emissions. It is also the pioneer in achieving carbon peak. Analyzing the factors influencing carbon emissions and predicting the peak year of carbon emissions will help Jiangsu Province clarify the direction of carbon reduction and take the lead in achieving carbon peak. This article selects relevant data from Jiangsu Province from 2005 to 2020, uses the STIRPAT model to analyze the influencing factors of carbon emissions in Jiangsu Province, predicts the carbon emissions and peak times of 13 prefecture-level cities in four different scenarios, and constructs a carbon peak prediction model to calculate the carbon peak pressure, carbon emission reduction potential, and carbon peak driving force of each prefecture-level city. Research has found that the population size, wealth level, technological level, urbanization level, and industrial structure have significant impacts on carbon emissions in Jiangsu Province. The prediction results for carbon peak in 13 prefecture-level cities indicate that Nantong, Huai'an, Yancheng, Suzhou, Nanjing, and Wuxi can achieve carbon peak before 2030 in all four scenarios. Changzhou, Xuzhou, Yangzhou, Taizhou, Suqian, Lianyungang, and Zhenjiang are all able to achieve carbon peak between 2025 and 2029 under the low-growth, slow-consumption scenario (P2G2E1) and low-growth, fast-consumption scenario (P2G2E2), but they cannot achieve carbon peak before 2030 under the high-growth, slow-consumption scenario (P1G1E1) and high-growth, fast-consumption scenario (P1G1E2). Finally, based on the carbon peak prediction model, the prefecture-level cities are classified, and differentiated carbon peak implementation paths for different types of prefecture-level cities are proposed. [ABSTRACT FROM AUTHOR]

How to decouple economic growth from carbon dioxide emissions and achieve low-carbon transformation of the Chinese economy has become an urgent problem that needs to be solved. Firstly, the Tapio index is used to identify China's carbon peak status, and then the Technology Choice Index (TCI) and economic complexity are introduced into the comprehensive factor analysis framework for carbon dioxide emissions. Key influencing factors are identified using random forest and ridge regression. On this basis, a novel sparrow search algorithm–long short-term memory (SSA-LSTM) model which has more prediction accuracy compared with past studies is constructed to predict the dynamic evolution trend of carbon dioxide emissions, and in combination with scenario analysis, the path towards the carbon peak is simulated. The following conclusions are obtained: The benchmark scenario peaks in 2031, with a peak of 12.346 billion tons, and the low-carbon scenario peaks in 2030, with a peak of 11.962 billion tons. The extensive scenario peaks in 2037, with a peak of 13.291 billion tons. Under six scenarios, it can be concluded that energy intensity is the key factor in reducing the peak. These research results provide theoretical support for decision-makers to formulate emission reduction policies and adjust the carbon peak path. [ABSTRACT FROM AUTHOR]

Chlorine-based disinfectants (CBDs) have been widely used to prevent and control the spread of the COVID-19, which may lead to the formation of carcinogenic hazards. In China, strict disinfection strategies by local governments/communities or volunteering by residents have been implemented to meet the Dynamic COVID Zero (DCZ) Strategy. However, the amount of CBDs used has not been estimated. The author proposed an urban-scale disinfectant consumption estimation (ALICE) model to quantify weekly CBD consumption. The results show that the CBD consumption for the urban region of Beijing during the DCZ strategy was 3704.0 t (0.43 kg/(cap·yr)), equivalent to a monthly increase of 15 g/cap (70.5%) in CBD consumption compared with that in pre-pandemic. According to the scenario analysis, a stricter strategy with a shorter response time toward new cases will decrease the total CBD consumption by 1.2% compared with the baseline estimation. A more precise prevention strategy with a smaller delineation of risk area and a less stringent strategy with a longer response time will lower the total CBD consumption by 0.42% and 0.35%, respectively. Specifically, the more precise prevention strategy will reduce CBD consumption of close off and lockdown area (COLD area) by 16.9%, and the stricter strategy will reduce this consumption by 37.7%. This study highlights the impact of pandemic prevention and control strategies on chlorine-based disinfectant consumption and some implications for future environmental pollution and risk assessments. [ABSTRACT FROM AUTHOR]

Water hyacinth (WH) is an aquatic weed with an experimentally proven potential as a feedstock for bioethanol production. Unlike other bioethanol feedstocks, water hyacinth has no requirement for land use and resource consumption for cultivation. This study evaluates scaled-up bioethanol production process routes, modelled using the Aspen Plus process simulator to analyse the process performance of water hyacinth as a bioethanol feedstock. Four process scenarios are developed by combining two different feedstock pretreatment methods (i.e., alkali pretreatment and diluted acid pretreatment) and bioethanol dehydration techniques (i.e., azeotropic distillation and extractive distillation). Mass and energy flows of the four scenarios are comparatively analysed. Results show that the alkali pretreatment method provides a higher bioethanol yield (i.e., 254 L/tonne-WH) compared with the dilute acid pretreatment method (i.e., 210 L/tonne-WH). In addition, the process route combining alkali pretreatment and extractive dehydration techniques indicates the least process energy consumption of 45,310 MJ/m3 of bioethanol. The process energy flow analysis evaluates two energy sustainability indicators, i.e., net energy gain and renewability factor, with further interpretation of variation effects of the key process parameters through a sensitivity analysis. The feasible ways of utilising water hyacinth as a fuel-grade bioethanol feedstock for industrial-scale production are discussed. [ABSTRACT FROM AUTHOR]

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A variety of energy-efficient and energy-generating products, such as photovoltaics (PV) and electric vehicles, have diffused into the market to reduce greenhouse gas emissions in the residential sector. Understanding future changes in electricity demand and supply is complicated by uncertainties such as lifestyle shifts and national energy policies, and how such changes interact with the diffusion of products. To address this issue, this study adopts a scenario approach to analyze the impact of product diffusion on residential electricity demand under different social circumstances. Two simulation models are employed for the analysis: (i) a model for estimating the diffusion of products based on consumer preferences and (ii) a model to estimate electricity demand in residential sectors considering product diffusion. To demonstrate the proposed method, a scenario analysis case study was conducted, estimating the electricity demand in the residential sector of Toyonaka City, Osaka, Japan, for 2030. The results show that compared to 2012, the net electricity demand in the city in 2030 is projected to decrease by 20–39% depending on the scenarios considered, with changes in demographics and PV diffusion identified as among the most critical factors. [ABSTRACT FROM AUTHOR]

The farming mode of yellowtail kingfish (Seriola aureovittata) in China tends to be mature. However, there are some problems with environmental impact and economic benefits that cannot be ignored in the sustainable farming process. This study focused on a yellowtail kingfish aquaculture company in Dalian, China, and carried out a life cycle environmental and cost assessment (LCA and LCC) study to evaluate the environmental impact and economic benefits of the yellowtail kingfish farming process. According to the LCA and LCC results, the environmental impact is significantly influenced by fossil energy consumption and feed production. Moreover, five improvement scenarios were proposed and discussed, and the results show that replacing coal and thermal power generation with wind power generation will comprehensively (scenario 5) reduce environmental impact by 82.14% and decrease costs by 24.25%. The results of this study can provide effective improvement scenarios for yellowtail kingfish aquaculture enterprises and enrich the international aquaculture LCA basic database with data support. [ABSTRACT FROM AUTHOR]

Many resource‐oriented regions on plateaus (RORP) are facing the double threat of ecological destruction and resource exploitation. The traditional development mode will destroy fragile ecosystems in RORP, resulting in substantial environmental governance costs and environmental restoration difficulties. Therefore, realizing the sustainable development of these regions has become a major topic of interest. In this study, we designed a sustainable development mode, that is, "conservation mining‐ecological restoration‐substitute industries‐energy saving and emission reduction" (CESE), for RORP. The integration of the Integrated Valuation of Ecosystem Service and Tradeoffs (InVEST) model and the system dynamics (SD) model were used to evaluate and simulate the comprehensive effect and future trends of the sustainable development mode in the RORP. The evaluation and simulation results clearly show that through long‐term stable operation, this sustainable development mode can alleviate the double threat of the "unbridled development‐fragile ecosystem"(UDFE) and achieve synchronous growth of ecological, economic, and social benefits. Additionally, this study further proposes the potential risks of this mode and directions for iterative improvements, serving as goals of regional optimization and improvement in the future. The sustainable development mode of RORP proposed in this study has important theoretical significance and practical value for mitigating the double threat associated with the development of RORP. [ABSTRACT FROM AUTHOR]

Abstract Background An increasing number of orphan medicinal products (OMPs) are being included in social health insurance schemes, significantly improving access to medicines for patients with rare diseases. However, high-priced OMPs are still not covered, primarily due to health equity controversies and inadequate data systems required for economic evaluation. The aim of this study was to estimate the burden of drug expenditures and the size of the reimbursement budget required for high-priced OMPs from the perspectives of society and healthcare payers. Methods The study performed a budget impact analysis using data from multiple sources to estimate the reimbursement budget for high-priced OMPs in Chengdu, a densely populated metropolis in China. The budget analysis consisted of three main elements: the number of patients, the price of drugs, and the simulated policy scenario. By adjusting the combinations of these elements, the budget fluctuations for payers were estimated. Furthermore, the study predicted the budget trend for the next three years to validate its sustainability. Results The analysis indicated that 98 rare disease patients in Chengdu required high-priced OMPs in 2019. This suggested a projected budget of CNY 179 million for these patients without reimbursement policies, from a societal perspective. Under six assumed policy scenarios, this budget ranged from CNY 32 million to CNY 156 million. Over the next three years, the annual budget was estimated to range from CNY 200 million to CNY 1.303 billion. Conclusion Integration of multi-source data helps to obtain more scientifically reliable results on budget impacts. The study found that the budgetary impacts of high-priced OMPs on society and payers are relatively limited. Health policymakers can choose appropriate reimbursement strategies based on financial affordability among a diverse mix of elements. The results of related studies provided insights for optimizing the allocation of health resources and improving patient access to medications.

Screenplay writing is the most important element that forms the basis of a film / series project. For this reason, how to write a script and how to analyse a written script gain special importance. This study seeks to answer the question of how to analyse a written script. While investigating the answer to this question, an in-depth examination was conducted using a qualitative research design and a literature review. As a result, a comprehensive new method for script evaluation and analysis is proposed. Suggested form can be used by producers, screenwriters and dramaturgs to evaluate the success of a film / series script project. According to the results of the study and the form, the decisive criteria of a successful script are a clear genre and tone, a compelling message, an intriguing premise, a well-constructed story line, engaging conflict, effective use of time, the presence of emotional intensity, effective characters and dialogue, marketability, and conformity to appropriate format features. The proposed scenario analysis form is a comprehensive tool that can be used to assess these criteria. It is thought that this analysis form can be useful for all stakeholders in the sector. [ABSTRACT FROM AUTHOR]

Indonesia is located in one of the most seismically active regions in the world and often experiences damaging earthquakes. In the past the housing sector has sustained higher earthquake related damage and losses than other sectors. This is often attributed to the fact that the most common houses in Indonesia are non-engineered, built with poor quality workmanship, poor quality materials and without resilient seismic design features. However little effort has been made to quantify how fragile Indonesian houses are, or how their fragility may vary according to the population density or relative wealth of a region. It is not possible to derive empirical fragility functions for Indonesia due to insufficient damage data. The aim of this study is to determine whether existing earthquake fragility functions can be applied to common house types in Indonesia. Scenario damage analyses simulating the 2006 Yogyakarta and 2009 Padang events were undertaken several times testing different fragility functions. The simulated damage results were then compared to the damage observed post event to determine whether an accurate damage prediction could be achieved. It was found that the common house types in Yogyakarta and Central Java vary according to age of construction, location and relative wealth of a region and can be reasonably well represented by existing fragility functions. However, the houses in Padang and surrounding West Sumatra did not vary in a predictable manner and are more fragile than anticipated. Therefore, the fragility of the most common house types in Indonesia differs between Central Java and West Sumatra. This has important implications for seismic damage and risk assessment undertaken in Indonesia. [ABSTRACT FROM AUTHOR]

Ecological restoration programs (ERPs) can lead to dramatic land use change, thereby affecting ecosystem services and their interaction. Determining the optimal ERPs is a crucial issue for ecological restoration in ecologically fragile regions. This study analyzed the impacts of land use change on four water-related ecosystem services (WESs), namely water yield, soil retention, water purification, and food production in the Ganjiang River basin, China during the past two decades. Then, trade-off and synergy between WESs were detected based on correlation analysis. Finally, to quantify the effect of ERPs on WESs, we comprehensively considered the types and intensity of ERPs and designed four categories of scenarios: returning farmland to forest (RFF) scenarios; planting forest (PF) scenarios; riparian forestland buffer (RFB) scenarios; and riparian grassland buffer (RGB) scenarios. Each category contains five scenarios of different intensities. The results showed that water yield, soil retention, and food production increased while water purification decreased from 2000 to 2020. The deterioration of water quality was mainly due to transitions from forestland to farmland and built-up land. Trade-offs only occurred between regulating services and provisioning services. Among all ecological restoration scenarios, only the RFF scenarios can significantly improve soil retention and water purification at the same time, although food production will decrease. Considering food security, returning farmland with a slope greater than 10 degrees to forestland was the optimal scenario in the study area. This study highlighted that both the type and intensity of ERPs should be considered in ecological restoration. This study can contribute to ecological restoration in the Ganjiang River basin and other subtropical mountainous regions. [ABSTRACT FROM AUTHOR]

The impact of flooding on cities is becoming increasingly significant in the context of climate change and rapid urbanization. Based on the analysis of the land use changes and rainstorm waterlogging inundation scenarios of Jiangqiao Town from 1980 to 2020, a scenario analysis was conducted to simulate and assess the rainstorm waterlogging disaster risk in 2040 under three land use scenarios (a natural development scenario, Scenario ND; an economic growth scenario, Scenario EG; and an ecological development priority scenario, Scenario EP) and three rainstorm scenarios with return periods of 10, 50, and 100 years. The following results were found: (1) Land use change is a significant factor in the risk of urban rainstorm waterlogging disaster caused by surface runoff and inundation depth change. In particular, the resultant increase in impermeable surfaces such as residential land and industrial land and the decrease in farmland during urbanization would lead to an increase in urban rainstorm waterlogging disaster risk. (2) Under three rainstorm scenarios, the future land use exposure elements and losses are consistent in terms of spatial distribution; from 10-year to 100-year return periods, they manifest as an expansion from the south to the surroundings, especially to the central region of the study area. The locations at risk are mainly distributed in the central and southern regions of Jiangqiao Town. (3) The economic losses are different in different land use scenarios and rainstorm scenarios. In the context of rainstorm scenarios with return periods of 10, 50, and 100 years, the total losses in land use scenario ND are CNY 560 million, CNY 890 million, and CNY 1.07 billion; those in land use scenario EG are CNY 630 million, CNY 980 million, and CNY 1.19 billion; and those in land use scenario EP are CNY 480 million, CNY 750 million, and CNY 910 million. The total losses of land use EP are the lowest by comparison. So, the influence of land use change on the rainstorm waterlogging disaster risk shows obvious differences among different rainstorm scenarios. This study has important reference value for decision making on land use management and flood disaster risk management in rapidly urbanizing areas. [ABSTRACT FROM AUTHOR]

Land use change has a significant impact on the sustainability of ecosystems, and ecological security patterns (ESPs) can improve environmental quality through spatial planning. This study explored a multi-scenario ESP framework by integrating future land use simulation (FLUS) and minimum cumulative resistance (MCR) for urban agglomeration along the Yellow River Basin (YRB) in Ningxia. The research involved simulating land use change in 2035 under four development scenarios, identifying ecological security networks, and evaluating network stability for each scenario. The study revealed that the ecological sources under different development scenarios, including a natural development scenario (NDS), an economic development scenario (EDS), a food security scenario (FSS), and an ecological protection scenario (EPS), were 834.82 km2, 715.46 km2, 785.56 km2, and 1091.43 km2, respectively. The overall connectivity values (OG) for these scenarios were 0.351, 0.466, 0.334, and 0.520, respectively. It was found that under an EPS, the ESPs had the largest area of ecological sources and the most stable ecological network structure, which can effectively protect natural habitats. This study provides a valuable method for identifying ESPs that can respond to diversity and the uncertainty of future development. It can assist decision-makers in enhancing the ecological quality of the study area while considering various development scenarios. [ABSTRACT FROM AUTHOR]

This paper generalizes the concept of capacity from the portfolio level to the investment process for systematic equity strategies. Capacity is often understood as the maximum asset under management, above which additional inflows would have too great a negative impact on performance. The concept of capacity is often limited to the study of a given portfolio. However, setting up a capacity management framework must consider what the portfolio might look like in the future. This is obviously complicated for discretionary portfolios but theoretically conceivable for portfolios implementing systematic strategies, if we can simulate all possible scenarios. In our framework, we extend the traditional definition of capacity from a number to a random variable, allowing portfolio managers to integrate it into their risk considerations. We provide examples of how portfolio managers can approach this problem, with full-search or modelling methods. Our framework includes several capacity metrics that can be used jointly or selected to align better with the features of each strategy. [ABSTRACT FROM AUTHOR]

This study presents a novel comparative analysis on global energy scenarios in terms of main characteristics, scenario building frameworks and time frames. The study analyzes each energy scenario's outputs and outlooks by 2040 such as gross domestic product growth, technology developments, primary energy demand by sector, energy supply by fuel, energy intensity and carbon emissions. Based on the foresight semiquantitative method, global energy driving forces which play significant roles in reshaping the world energy future by 2040 have been identified. The study applies mathematical principles to quantify the rational judgments of an expert panel in social, technological, economic, environmental and political framework through cross-impact analysis. Among the 10 global energy driving forces by 2040, population growth rate and climate change are identified as social and environmental driving forces, respectively. Investment in infrastructures, financial shocks, consumer behavior and energy efficiency are marked as economic driving forces, while global governance and geopolitical relationships are identified as the global energy market's political driving force. And finally, technological development in renewable energies as well as in oil and gas upstream sector is recognized as a technological driving force. [ABSTRACT FROM AUTHOR]

Over the past decades, the significant high environmental impacts of meat consumption have drawn increasing attention around the globe. This study took 2018 meat consumption levels as baselines. It explored the emission implications of the more sustainable counterfactual healthy red meat diet (HRMD), healthy poultry meat diet (HPMD), and world balanced meat diet (WBMD). Meat commodity supply for human consumption data was extracted from the FAOSTAT database. The data were then adjusted for cooking and edible meat yields to obtain the cooked-and-edible meat. Emission factors obtained from published meta-analyses were used to estimate the emission implications of cooked-and-edible meat consumption. Counterfactual HRMD showed that adjusting 18 regions' (10% of the world population) red meat consumption to a serving per day and poultry meat consumption to three servings per week equivalent could reduce the meat-related emission by 4%. The HPMD showed that further reducing red meat consumption in the HRMD to the world average in 21 regions (13% of the world population) and substituting the reductions with poultry meat could reduce the meat-related emission by 12%. WBMD showed aligning all regions' meat consumption to a serving of each bovine, pig, and poultry meat per week, and the ovine meat consumption to the world average could reduce the meat-related emission by 21%. HRMD and HPMD could be the step-by-step transition strategies towards a WBMD to reduce greenhouse gas emissions and simultaneously address malnourishment issues. [ABSTRACT FROM AUTHOR]

Scenario analysis is a comprehensive approach to assess the impact of climate-related transition risk on businesses. Environmental, social, and governance (ESG) scores are popular tools with financial institutions (FI's) for green-scoring practices and since they characterise a company's performance from an ESG perspective, they have been criticised for enabling "greenwashing" when used within the context of climate risk. Commercially available ESG scores are also available for listed entities, while FI counterparties are often unlisted. This study develops a methodology for creating in-house environmental scores (E-scores), which are then used to effectively choose appropriate transition pathways to be used in company-specific forward-looking scenario analysis. Such scenario analysis can be used to forecast the company's financial position, including the cost of its greenhouse gas (GHG) emissions, and quantify the impact of transition climate risk on specified metrics. The choice of metrics depends on what the results of the analysis are used for. Two metrics are identified for being useful for risk management and credit decisions: future profitability and weighted average carbon intensity. Finally, the study demonstrates how this process can be implemented with a practical worked example, using only publicly available data. [ABSTRACT FROM AUTHOR]

Plateau pikas, small mammals native to the Qinghai‐Tibet Plateau (QTP), create bare patches through burrowing. No previous assessment exists on their impact on permafrost. This study fills this gap by simulating hypothetical scenarios in the Three Rivers Headwaters Region of the QTP using the Noah‐MP model for the plant growing seasons during 2015–2018. Our findings reveal a significant increase in soil temperature in the active layer due to pika‐induced bare patches, particularly during July–August. The average temperature rise at 2.5 cm depth was 0.36°C in permafrost regions and 0.29°C in seasonally frozen ground regions during August. Minimal impact on unfrozen water content was observed, with a slight increase in deep soil layers in permafrost regions, and negligible in seasonally frozen areas. These findings underscore the previously unexplored influence of pika burrowing on permafrost temperature, suggesting a potential risk of accelerating permafrost degradation, especially in permafrost‐dominated regions. Plain Language Summary: On the vast Qinghai‐Tibet Plateau (QTP), plateau pikas are actively excavating burrows, creating bare patches of exposed earth within the typical grassland landscape. These seemingly minor disturbances can have significant consequences, as they alter heat and water conditions within the underlying permafrost. However, a comprehensive understanding of how these pika‐made patches impact the permafrost remains elusive. To address this gap, our study employed a computer model and simulating scenarios with and without pika patches in the ecologically fragile Three Rivers Headwaters Region (TRHR) of the QTP. We found that the pika‐induced bare patches significantly raised permafrost temperatures, especially in the shallow soil layers. During August, the peak pika activity month, the average soil temperature at a depth of 2.5 cm increased by 0.36°C in permafrost zones and 0.29°C in seasonally frozen ground zones. While the patches had minimal impact on unfrozen water content in the active layer, the temperature rise in permafrost warrants future concern. Key Points: Bare patches due to plateau pika burrowing warmed permafrost, particularly during peak activity months and in shallow soil layersPika bare patches warmed permafrost and seasonally frozen ground by about 0.36°C–0.29°C, respectively, at a 2.5 cm depth in AugustPika‐induced bare patches had negligible impact on the unfrozen water content in the active layer of permafrost [ABSTRACT FROM AUTHOR]

As increasing disbursements (such as costs and fees) and risk (such as portfolio risk and leverage risk) may affect managed fund performance, analysts go beyond risk-adjusted return measures for performance appraisal. A methodology that assesses performance in a multidimensional framework is data envelopment analysis (DEA). A variant of DEA is inverse DEA. In this paper, inverse DEA is applied to determine output (investment income and benefit payments) targets for a given fund to perform at a desired efficiency level when increase in disbursements and risk at known levels is envisaged. An output-oriented inverse DEA model assuming variable returns to scale is formulated with theoretical underpinning. The proposed modelling framework ensures that, when an input augmented fund with estimated output targets is included in the observed fund set, the frontier of best performance established with the observed fund set does not change. The inverse DEA model is applied to a sample of Australian superannuation funds to demonstrate how a given fund may obtain pathways to improve its performance under different input-augmentation scenarios. As different pathways suggest feasible output targets, fund managers may find them valuable in forward planning. [ABSTRACT FROM AUTHOR]

[Objective] The aims of this study are to quantitatively analyze the response of runoff and sediment yields to land use change in Fu River Watershed, and to provide scientific evidences for the planning and management of water and soil resources and ecological construction in the river basins. [Methods] The SWAT distributed hydrological model was applied. Three natural scenarios and three extreme scenarios were set up to qualify the variation of land use change during 1990 and 2010 and corresponding contribution rates to watershed runoff and sediment discharge. [Results] (1) From 1999 to 2010, the upper reaches of the watershed was dominated by woodland and grassland, comprising approximately 46% of the total watershed area. The middle and lower reaches of the watershed were primarily composed of agricultural and urban areas, with cultivated land accounting for approximately 51% of the total area. As a result of rapid urbanization, urban land and bare land expanded significantly at rates of 95.86% and 434.43%, respectively. Under the natural scenarios, the change rate of water yield was less than 5%, and the change rate of sediment yield is less than 15%. (2) SWAT model had strong applicability in Fu River Watershed, the R² and NSE values for runoff at calibration and verification periods were 0.86, 0.85 and 0.80, 0.78, respectively, and for sediment discharge were 0.68, 0.67 and 0.68, 0.43, respectively. Scenario simulation analyses illustrated the effects of specific land use types on runoff decreased in the order: woodland＞grassland＞bare land. Compared with the base period, the woodland cover scenario reduced runoff by 35.66%. Impact of different land use types on sediment yields decreased in the order: bare land＞woodland＞grassland. Compared with the base period, the bare land scenario increased the sediment yield by 56.74%, and the woodland and grassland decreased sediment yield by 43.57% and 30.04%, respectively. (3) The importance ranking results of independent variables based on random forest algorithm showed that the first three land use types affecting runoff were farmland, woodland and grassland, and the random forest weights were 2.057, 2.030 and 1.148, respectively, while grassland, farmland and woodland affected sediment yield most significantly and the random forest weights were 1.753, 1.208 and 1.003, respectively. [Conclusion] In addition to farmland, the response of runoff to forestland change is the most significant, and the response of erosion and sediment yield to grassland change is the most significant. The conversion of land use type to grassland and woodland significantly reduces water and sediment yields in the basin, while the bare land has a significant impact on sediment yield in the watershed. This research can provide scientific basis for future land use structure optimization and rational planning of water and soil resources in the Fu River Watershed. [ABSTRACT FROM AUTHOR]

In recent years, carbon emission reduction in the shipping sector has increasingly garnered scholarly attention. This study delves into the pathways for carbon emission reduction in shipping across the Yangtze River, emphasizing fuel alternatives. It initiates by introducing a novel ship carbon emission calculation methodology predicated on voyage data, followed by the development of a predictive model for ship carbon emissions tailored to specific voyages. Then, emission reduction scenarios for various voyage categories are designed and exemplary alternative fuels selected to assess their potential for emission mitigation. Subsequently, scenario analysis is employed to scrutinize the CO2 emission trajectories under diverse conditions, pinpointing the most efficacious route for carbon emission abatement for inland vessels. Finally, the proposed method is applied to the middle and lower reaches of the Yangtze River. The results indicate that accelerating the adoption of alternative fuels for long-distance cargo ships would greatly accelerate the development of environmentally friendly shipping. Under a scenario prioritizing zero-carbon growth, emissions from inland vessels are anticipated to reach their zenith by 2040. These findings can provide theoretical guidance for emission reductions in inland shipping and effectively promote the green and sustainable development of the shipping sector. [ABSTRACT FROM AUTHOR]

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Transportation significantly influences greenhouse gas emissions—particularly carbon dioxide (CO2)—thereby affecting climate, health, and various socioeconomic aspects. Therefore, in developing and implementing targeted and effective policies to mitigate the environmental impacts of transportation-related carbon dioxide emissions, governments and decision-makers have focused on identifying methods for the accurate and reliable forecasting of carbon emissions in the transportation sector. This study evaluates these policies' impacts on CO2 emissions using three forecasting models: ANN, SVR, and ARIMAX. Data spanning the years 1993–2022, including those on population, GDP, and vehicle kilometers, were analyzed. The results indicate the superior performance of the ANN model, which yielded the lowest mean absolute percentage error (MAPE = 6.395). Moreover, the results highlight the limitations of the ARIMAX model; particularly its susceptibility to disruptions, such as the COVID-19 pandemic, due to its reliance on historical data. Leveraging the ANN model, a scenario analysis of trends under the "30@30" policy revealed a reduction in CO2 emissions from fuel combustion in the transportation sector to 14,996.888 kTons in 2030. These findings provide valuable insights for policymakers in the fields of strategic planning and sustainable transportation development. [ABSTRACT FROM AUTHOR]

This paper presents an in-depth analysis of decarbonizing the electricity sector in the Dominican Republic, pivotal for addressing climate change and fostering economic growth. Employing the robust-decision making methodology, we studied multiple scenarios via computational models, capturing inputs from stakeholders and evaluating each scenario across 1,000 futures to capture deep uncertainty. Four scenarios were examined: baseline, reference, natural gas, and renewable. The renewable scenario emerged as the most advantageous, proposing the replacement of coal-fired power generation with renewable sources, primarily solar and wind, coupled with batteries. A significant investment, averaging US$3.3 billion, is necessary for this shift toward renewable energy; however, these investments are overcompensated by savings in operational costs. Crucially, this transition promises substantial benefits by 2050: an estimated cumulative average net economic gain of US$2.7 billion, an 8% reduction in average generation costs in 2050, the creation of 160,000 direct jobs, and the avoidance of circa 140 million tons of C02. The findings underscore the feasibility and economic viability of transitioning to a 55% renewable energy generation by 2050. The study offers a critical roadmap for policymakers, highlighting renewable energy expansion, transmission grid strengthening, and strategic coal generation replacement, thus offering a comprehensive blueprint for the nation's energy transition. [ABSTRACT FROM AUTHOR]

Investigating the spatial network structure of urban agglomerations based on traffic accessibility has an important practical significance in accelerating the process of regional integration. Taking urban agglomeration in the middle reaches of the Yangtze River (UAMRYR) as the case study, this study aims to examine the characteristics associated with the spatial network structure based on traffic accessibility and its changes under scenarios of different traffic accessibilities by adopting real-time traffic data, modified gravity model, and social network analysis (SNA). The main conclusions are as follows. Wuhan, Changsha, and Nanchang are the central cities in the spatial network; the spatial network structure of UAMRYR is imbalanced and in the agglomeration stage of regional economic development. With the development of traffic accessibility, resources first gather in the individual center cities and then spread to other cities, and the network tends toward equilibrium. [ABSTRACT FROM AUTHOR]

As a major emitter of CO2, China needs to take responsibility for slowing down global warming. In this paper, the potential carbon emission intensity of provinces is firstly calculated using the non-radial directional distance function under the group- and meta-frontier techniques, and then six scenarios based on two factors (economic development and carbon intensity) are set up to estimate the emission reduction potential of China and each province. Considering the goal of carbon neutrality, the calculation of CO2 emission reduction potential quantifies the amount of emissions that can be reduced and the amount of emissions that should be balanced. Additionally, the degree of difficulty in achieving abatement potential is also calculated. The findings are as follows: First, assuming that the economic growth rate is reduced to 4.4% (achieving the second "100-year goal") and each province adopts the most advanced low-carbon technologies, China could reduce carbon emissions by 5970.56 Mt compared to 2019 levels. To achieve net-zero emissions, the remaining 3824.2 Mt of carbon emissions should be removed by carbon reduction technologies. Second, the effect of slowing down economic growth and decreasing carbon intensity varies greatly among provinces. Hebei and Shandong should be prioritized as they have the greatest potential for emission reductions under both scenarios. Third, it is more difficult for Beijing, Shanghai, Hubei, Hunan, Inner Mongolia Autonomous Region, Chongqing, and Sichuan to achieve the abatement potential and they require more effort to reduce the same amount of carbon emissions compared to other provinces. The study provides a reference for achieving carbon neutrality and helps provinces to develop differentiated emission reduction strategies. [ABSTRACT FROM AUTHOR]

In order to explore the low-carbon development direction of the transportation sector, based on the LEAP model, a transportation energy and environment model for the road traffic sector in Xi 'an was established to simulate the energy demand, CO2 and pollutant emission trends and emission reduction potential of the transportation sector under different scenarios in 2021—2050. The results show that the energy consumption and CO2 emissions under the low-carbon scenario(LC)peak around 2031, and the reduction rates in 2050 relative to the baseline scenario(BAU)are 32. 62% and 30. 21%, respectively. CO, NOx and PM10 all show good emission reduction effects, and the reduction rates relative to BAU are 33. 88%, 36. 27% and 40. 33%, respectively. Among the sub-scenarios, the transportation structure adjustment scenario(TSA)contributes the most to energy conservation and emission reduction, followed by the green car scenario(GC)and the technical energy-saving scenarios (TES). In order to achieve carbon emission reduction and pollutant emission control in the transportation sector, it is necessary to adjust the traffic structure, eliminate old models and vigorously develop public transportation, and constantly improve the corresponding infrastructure to increase the market share of new energy vehicles. [ABSTRACT FROM AUTHOR]

The studies of heavy metal input and output fluxes from farmland soils will contribute to sustainable agricultural practices. However, debate on the primary pollution to crops has not resulted in the emergence of practical remediation strategies. Hence, the flux should be identified with precision for targeted pollution control. In this study, a catchment downstream of a metal mining area was selected for investigation of Cadmium pollution in the topsoil of farmlands, including the input and output fluxes in different environmental media. The results showed that irrigation was the main input source of Cd to soil, accounting for more than 75%, in which the contribution of dissolved Cd in water was 1–2 orders of magnitude higher than that of Cd adsorbed on suspended particles. Crop harvesting, surface runoff, and leaching were the main Cd output pathways from this area. The dynamic prediction results under different scenarios showed that Cd in farmland soil would be in a cumulative state in the following years by 2050. Straw removing could significantly reduce Cd accumulation in farmland soil. In addition, the substantial increase of crop yield in the future would increase the Cd output flux. This work revealed the accumulation pattern of Cd in farmland soils, and will aid in the development of remediation strategies for cadmium contamination of agricultural soils. [ABSTRACT FROM AUTHOR]

China has been the world's largest carbon emitter since 2003, especially in 2018, China's carbon dioxide emissions have exceeded 10 billion tons, accounting for more than a quarter of the world's total carbon dioxide emissions. Therefore, China's government had set the target to achieve the 'carbon peak' in year of 2030. In this study, we firstly analyzed the historical development trend, regional economy, population, urbanization and carbon emissions of the four major regions, including the East, the Middle, the North-east and the West China, respectively. Then, we used the IPAT model to design 48 peak CO2 emission scenarios, and used the centralized DEA to evaluate the allocative efficiency of scenario-based CO2 emission paths. Consequently, we found that maintaining relatively high GDP growth (around 6%), reducing energy intensity by about 75% of average annual decline rate (around 4%) and increasing non-fossil energy to 21% to meet the requirements of the Innovation plan of energy technology revolution 2016-2030 is the most efficient low-carbon behaviors towards 2030 peak CO2 emissions of 10.57Gt. The results obviously indicate the A1B2C2 scenario has the highest potential emission efficiency in scenarios where carbon emissions peak by 2030. In the peak scenario in 2025, A1B2C1 has more stringent requirements for optimizing the energy structure than A1B2C2, and the potential output efficiency of CO2 emissions is slightly lower than other scenarios. It is also found that in the future path of the predicted optimal scenario, only economic scale and low carbon per unit output value make a great contribution to the changes in carbon dioxide emissions. [ABSTRACT FROM AUTHOR]

Reducing greenhouse gas emissions is a crucial challenge in urban areas characterized by high energy consumption and reduced exposure to nature. In this context, the urban green system could play a pivotal role. In the literature, scholars have analyzed both the ability of species-specific and layout-specific green infrastructure to increase carbon sequestration and the best location sites for new green infrastructure to increase the provision of overall ecosystem services. There is a lack of studies helping green urban planners and designers choose where and which green infrastructure to implement based on vegetation species-specific performance and the local carbon emissions of city components. This paper uses tree inventory data from a medium-sized city in central Italy (Perugia) to develop a spatial analysis of urban park performance in carbon sequestration. Then, the method evaluates the carbon emission of a public city building to generate a spatialized balance between building demand and tree supply to support local decisions about the best locations for new green infrastructure and the choice between species. The paper contributes to GIS-based tools that vary the recommended location sites and species for new green infrastructure based on the demanded ecosystem service. [ABSTRACT FROM AUTHOR]