Economic Scenarios Research Articles

Life Cycle Assessment of Biochar from Residual Lignocellulosic Biomass Using Kon-Tiki Kilns: Applications in Soil Amendment and Wastewater Filtration

Producing biochar from residual biomass is an opportunity for health, environmental, and economic benefits to farmers in small traditional parcels, which are widespread in Latin America. This study presents a life cycle assessment of biochar in two circular economy scenarios: soil amendment and wastewater filtration. Seven mid-point environmental impact categories were assessed using the CML-IA method: acidification (AP), abiotic depletion (ADP), fossil fuels depletion (ADP-FF), eutrophication (EP), global warming (GWP), human toxicity (HTP), and smog formation (POCP). The soil amendment scenario showed lower impacts per tonne of biochar in all categories, especially for GWP (−801.3 kg CO2eq) and ADP-FF (−374.3 MJ), compared to the filtration scenario (−123.54 kg CO2eq and 827.85 MJ). Negative GWP values reflect reduced emissions from avoided fertilizers and carbon sequestration. However, POCP and HTP increased due to air emissions (CH4, NOx, NMVOC, and PM10) from the kiln. In both scenarios, biochar production contributed to 40–90% of the total impacts. Indirect emissions from electricity used for water pumping were identified as a hotspot in the filtration scenario.

Preference reversal in intertemporal decision making.

This study examines asymmetric preference reversals in intertemporal decision-making by comparing gain and loss contexts across choice and bidding tasks. In the gain context, participants preferred smaller, sooner (SS) rewards in choice tasks but assigned higher valuations to larger, later (LL) rewards in bidding tasks. Conversely, in the loss context, they showed a preference for LL options in choice tasks but provided lower bids for SS options. Bidding tasks consistently required longer decision times than choice tasks, indicating greater cognitive demands during valuation processes. A real-world questionnaire involving 370 participants validated these findings across economic and health-related scenarios. These results underscore the role of task formats in shaping preferences, offering practical insights for refining strategies in behavioral decision-making and applied contexts.

Unveiling the nexus of scientific plans and real-world outcomes: A comparative analysis of land use optimization and agent-based simulation results in a natural landscape

Sustainable land management requires balancing the socio-economic needs of local communities with land conservation. Effective land management programs hinge on how well plans align with the demands and actions of land users in natural landscapes. This study aimed to create optimized land use plans for a Jahan-Nama protected area in Iran as the initial step, followed by simulating stakeholder plans and conducting a comparative analysis. A combination of compromise programming and a simulated annealing algorithm, alongside an agent-based model (ABM) to simulate stakeholder preferences, was employed for land use optimization. The study compared the outcomes of eight optimized scenarios that considered both socio-economic needs (social, economic) and environmental sustainability (environmental), along with stakeholder preferences reflected in multi-objective scenarios with varying priorities and a single-use livestock grazing scenario. Findings revealed that the grazing scenario (single-use) offered the highest employment rate (201 individuals) within the study area, but had the lowest economic efficiency (profitability ratio: 13.38). Additionally, the grazing scenario exhibited the highest water consumption (42,200 L/day) and the highest erosion rate compared to the other scenarios. Conversely, the beekeeping and ecotourism scenario emerged as the most economically efficient (profitability ratio: 46.31) with the lowest water consumption (23,000 L/day). Among the scenarios examined, the highest level of agreement was observed for the simulated sites chosen by beekeepers and the beekeeping and ecotourism (BTP) scenario (Kappa = 0.176). Conversely, the economic scenario (EC) had the lowest agreement with the beekeepers' selected sites (Kappa = 0.135). In terms of ecotourism, the results indicated the highest agreement between the tourists' sites and the ecotourism and recreational scenario (Kappa = 0.332 in single-agent mode and 0.405 in multi-agent mode). On the other hand, the livestock grazing scenario had the lowest level of agreement with the tourists' selected sites (Kappa = 0.282 in single-agent mode and 0.362 in multi-agent mode).

Study on Territorial Spatial Equilibrium Based on Ecosystem Service Value: A Case Study of the Southwest Guangxi Karst‐Beibu Gulf, China

ABSTRACTExploring the regional territorial spatial equilibrium state (TSES) has emerged as a key goal of “Two Mountains” planning and decision‐making, as well as territorial spatial governance. However, there is still a shortage of perspectives that consider the ecosystem service value (ESV) to reveal and predict TSES. To this end, this study develops a framework for analyzing the interaction between ESV and socio‐economic value (SEV), investigates the pattern, process, and mechanism of their interaction employing spatial equilibrium model, and couples the MOP‐PLUS model to predict the interaction between the two under different scenarios, in order to fill in the gaps of the current research. The results show that: (1) From 1980 to 2020, the ESV (decreasing trend) and SEV (increasing trend) in the Southwest Guangxi Karst‐Beibu Gulf (SGK‐BG) show opposite trends and distribution patterns. Under all three simulated projection scenarios, the projected ESV of SGK‐BG in 2030 shows different degrees of decreases, with economic development leading to the greatest fluctuations in the rate of decrease; the implementation of an ecological protection strategy leads to a small decrease in the SEV, and vice versa. (2) The TSE for coordinated equilibrium state (CES) districts and counties are mainly clustered in the GSK region, with the number in 2020 increasing by 30% compared to 1980; the ecological imbalance state (EIS) areas are mainly located in the central part of the study area and some districts along the coast of the Beibu Gulf, and the developmental imbalance state (DIS) areas are located in the northwestern part of the study area. The above three TSES have the highest number of distributions in the business as usual scenario (BAUS), the economic development first scenario (EDFS), and the ecological conservation first scenario (ECFS), respectively. The above differences in different spatial equilibriums reveal a serious developmental imbalance between economic development and ecological conservation. This study emphasizes the pathways evolution of different equilibrium subregions under the realization of ESV, and the evaluation results are not only a useful supplement to the research on the “Two Mountains” theory, but also can help policymakers to provide scientific decisions in promoting the synergistic, equilibrium and orderly development of the region.

Analysis of the Adoption of Corporate Social Responsibility Strategies in Partnership with the Association Comitê Ponto Chic, in Nova Iguaçu, Baixada Fluminense, Brazil

Objective: The objective of this paper is to investigate whether the adoption of Corporate Social Responsibility (CSR) strategies can positively impact the contribution to territorial development and social inclusion of the local community through sustainable practices, highlighting the importance of incorporating CSR as a strategy administrative and its role in the current socio-environmental and economic scenario. Theoretical Framework: The theoretical framework of the paper is addressed the importance and evolution of Corporate Social Responsibility (CSR), from its origins to the current practices adopted by organizations. The literature review explored the growing need for companies to incorporate social, environmental and ethical dimensions into their strategies, highlighting the role of corporate social responsibility and highlighting how companies can act more responsibly and socially towards society and the environment. Method: The methodology adopted for this research involves the use of qualitative and quantitative methods. Documentary research, interviews and field research were carried out with interviews at the headquarters of the Ponto Chic Nova Iguaçu Committee Association, Rio de Janeiro. Results and Discussion: The results obtained revealed that organizations that work with CSR contribute to collective, social and environmental development in the territories where they operate. It was observed that the adoption of CSR practices has positive impacts on promoting territorial development and social inclusion. Research Implications: The results of this study influence the field of administrative social sciences, since the understanding of CSR in Brazil is growing, and implies that Baixada Fluminense is a socially vulnerable region witch new articles of this theme. Originality/Value: This study contributes to the literature in the field of administrative social sciences, and the originality of this article lies in its analysis of the implementation of CSR strategies in the Association object of this article, the Ponto Chic Committee, highlighting the role of CSR as a fundamental tool for organizations face socio-environmental challenges.

Changing characteristics, driving factors and future predictions of land use in the Weigan-Kuqa River Delta Oasis, China

The oasis serves as the central component of the arid ecosystem and plays a crucial role in supporting human activities. However, the ecological environment in the oasis region is fragile, and even a minor alteration in land use (LU) can significantly impact the stability of the ecosystem. Therefore, it is imperative to undertake comprehensive research on the spatio–temporal patterns of LU change in the oasis, reveal its driving factors, and predict future development. This is crucial for devising scientifically and logically sound land management strategies, upholding the equilibrium between humans and land in arid areas, and attaining sustainable development of the regional ecology and economy. This study focuses on the Weigan–Kuqa River Delta Oasis in China as the research area, analyzes the changes in LU in the oasis from 2010 to 2022 using various methods such as transition matrix, dynamic degree, intensity analysis, and center of gravity shift. The study also investigates the factors influencing these changes using the optimal parameters–based geographical detector (OPGD). Additionally, it predicts the future trends in LU development under four different scenarios using the mixed–cell cellular automata (MCCA), and illustrates distribution characteristics by combining Moran’s I index and hotspot analysis. The results suggest that: (1) Between 2010 and 2022, the LU in the oasis changed rapidly, with consistent increase in the amount of construction land, arable land, and garden land, while the amount of forest-grassland and unused land decreased overall. (2) Population density played a leading role in the changes, but soil type also had a significant impact. Over the course of time, the influence of roads and transportation has progressively increased. (3) Compared with 2022, the acreage of arable land, garden land, and construction land increases under the four future scenarios: natural development scenario (NDS), economic development scenario (EDS), cropland development scenario (CDS), and ecological protection scenario (EPS). However, the acreage of forest–grassland and unused land decrease. From a spatial perspective, large towns, the downstream of alluvial fans, and the central oasis are key areas where the distribution of hot spots and sub–hot spots of each LU type varies significantly among the four scenarios. The EPS provides a certain level of protection for forest-grassland areas and water bodies, making it the most appropriate development model for oases. These findings have the potential to offer valuable academic guidance for oasis land resource management and are crucial for achieving coordinated development at regional level.

INTELIGÊNCIA COMPETITIVA E INTERNACIONALIZAÇÃO: ESTRATÉGIAS PARA EMPRESAS EM EXPANSÃO

Internationalization, defined by the expansion of companies beyond national borders through products, services or investments, emerges as an essential element for corporations in response to a unified and highly competitive global market environment. This study aims to explore the dynamics of business internationalization, highlighting the main driving forces, obstacles and tactics linked to this phenomenon. Adopting a qualitative and descriptive approach, the research is based on a comprehensive literature review. The study reveals several perspectives — economic, behavioral and cultural — that shape the motives and methods adopted by companies in their international expansion journey, in addition to examining various internationalization strategies, including exporting, licensing and the creation of subsidiaries abroad. Generally, companies seek internationalization to capitalize on their competitive advantages, increase revenues or reduce expenses. However, insufficient knowledge about international markets and the challenges inherent in the internationalization process can represent significant barriers to global expansion. The conclusion highlights that, faced with the challenges and opportunities of global trade, internationalization emerges as a vital strategy for companies to seek greater competitiveness in the contemporary global economic scenario.

Economic Justice in the Design of a Sugarcane-Derived Biofuel Supply Chain: A Fair Profit Distribution Approach

Background: In agricultural supply chains, unequal bargaining power often leads to economic inequality, particularly for farmers. The fair profit distribution (FPD) approach offers a solution by optimizing supply chain flows (materials, information, and money) to promote economic equity among members. However, our literature review highlights a gap in applying the FPD approach to the facility location-allocation problem in supply chain network design (SCND), particularly in sugarcane-derived biofuel supply chains. Methods: Consequently, we propose a multi-period optimization model based on FPD to design a sugarcane biofuel supply chain. The methodology involves four steps: constructing a conceptual model, developing a mathematical model, designing a solution strategy, and generating insights. This model considers both investment (crop development, biorefinery construction) and operational phases over a long-term planning horizon, focusing on farm location and crop allocation. Results: By comparing the FPD model to a traditional centralized planning supply chain (CSC) approach, we examine the impact of the planning horizon, number of farms, and sugarcane prices paid by biorefineries on financial performance. While the FPD model results in lower overall system profits, it fosters a fairer economic scenario for farmers. Conclusions: This study contributes to economic justice in supply chains and offers insights to promote fair trade among stakeholders.

Assessing the Interaction Impacts of Multi-Scenario Land Use and Landscape Pattern on Water Ecosystem Services in the Greater Bay Area by Multi-Model Coupling

Water ecosystem services (WESs) are intrinsically associated with the livelihood of urban residents and are frequently disrupted by human activities. Land use and landscape patterns are key driving factors of alterations in WESs. However, existing research primarily quantifies single-factor influences and often overlooks the interactions between these factors. This study addresses this gap by employing a multi-model coupling approach, integrating the Patch-generating Land Use Simulation (PLUS), Integrated Valuation of Ecosystem Services and Trade-offs (InVEST) model, and Geographical Detector (GD) models alongside various indicators to analyse the evolution of land use, landscape patterns and WESs in the Greater Bay Area from 2000 to 2020, and to simulate spatio-temporal change patterns in different scenarios from 2030 to 2050. Additionally, this study examines the multi-factorial interactions between land use, landscape patterns, and WESs. The results indicate that (1) urbanisation steadily increased, leading to intensified landscape fragmentation, and water yield (WY) and total phosphorus (TP) consistently increased, while total nitrogen (TN) in water gradually decreased; (2) urban areas exerted the most significant impact on WY in the Greater Bay Area while Patch density (PD) had a stronger influence on WY, and Shannon’s diversity index (SHDI) had the most pronounced effect on TN and TP; (3) the interaction between any two land-use types or landscape indices exerted a greater impact on WESs compared with the impact of individual factors alone. The interaction between urban areas and cropland substantially influenced WY (q¯ = 0.634) and most strongly affected TN and TP in water (q¯ = 0.74 and 0.73, respectively). SHDI and PD had the most significant impact on WY in the economic development scenario (q¯ = 0.19) and exhibited the greatest influence on the TN and TP levels in the ecological priority scenario (q¯ = 0.12 and 0.15, respectively). Our findings can provide theoretical and technical support for the integrated scientific planning of regional water ecosystems and the development of comprehensive land use policies in the future.

Growth Simulation of Agriculturally Dominant Cities by Incorporating Multiple Drivers into a CA-based patch-generating Land Use Simulation Model: A Case Study in Siracusa, Italy

Abstract. Understanding the historical trajectory of land use and land cover (LULC) and predicting future alterations is essential to advancing the SDGs. Current researches on LULC in agriculture-dominated cities primarily focuses on the spatiotemporal pattern analysis of carbon storage changes, with relatively little attention given to LULC simulation studies. Moreover, most studies employing cellular automata (CA) models concentrate on urban centers, overlooking the specific sustainable development of agricultural cities. This paper selects Siracusa, Italy, as a case study, incorporating multiple drivers and constructing four development scenarios. The patch-generating land use simulation (PLUS) model is employed to predict the LULC for Siracusa by 2030 and to examine potential transformations under each scenario. Our findings show that 60% of the land in Siracusa is designated as cropland, predominantly situated in flat regions. Our simulation results reveal that urbanization and demographic growth are the main factors driving cropland conversion to urban areas. Different development scenarios exhibit significant variations in future land use structures; the cropland protection scenario emphasizes the stability and sustainability of agricultural development, whereas the economic development scenario highlights the substantial impact of urban and industrial expansion on agricultural land. These insights are instrumental for land use planning and policy-making in Siracusa and other agriculture-centric cities, providing a framework to guide urbanization while promoting agricultural sustainability.

ASSESSING THE DEVELOPMENT OF THE BRAZILIAN ELECTRIC VEHICLES MARKET: A STUDY INTEGRATING A STRUCTURE-CONDUCT-PERFORMANCE (SCP) MODEL AND A PESTEL ANALYSIS

Climate change is one of the biggest political and economic challenges faced by global economy. To slow down climate change, mitigation actions and greenhouse gas (GHG) emission targets have been adopted, promoting electric vehicles (EVs) globally. In Brazil, however, emission reduction strategies for the transport sector are based on the broad use of biofuels. This paper studies the Brazilian light-duty vehicle EVs market investigating the reasons behind its current state. A Structure-Conduct-Performance Model with a PESTEL Analysis and the Herfindahl–Hirschman Index integrated to the structure analysis was used. The Brazilian EV market has grown in the period from 2019 to 2023, albeit timidly and restricted to a luxury market. The lack of actions promoting electric mobility, a less than promising economic scenario, the challenges in implementing a charging infrastructure and the conduct of the incumbent firm in the market – investing in high priced hybrid models – contribute to low penetration of EVs in the market and the dominance of hybrids amongst them. In the light of these findings, this study highlights that the Brazilian EVs market would benefit from public policies developed to promote electric mobility, and investment of private companies to develop EV models with more competitive prices.

Enabling crowdfunding platforms in Qatar: a regulatory framework for growth and sustainable innovation based on network analysis and Monte Carlo simulation

Purpose This study aims to explore the structure and dynamics of Qatar’s crowdfunding ecosystem to support economic diversification and enhance entrepreneurial activities. This research focuses on analyzing the development of the industry, its regulatory environment and the collaborative dynamics among stakeholders. Design/methodology/approach This study used network analysis and Monte Carlo simulations to examine the interplay between various stakeholders, including entrepreneurs, to understand their roles and interconnections. This study also simulated different economic scenarios to evaluate the potential impact of crowdfunding under various market conditions and regulatory frameworks. Findings The analysis reveals a moderate level of crowdfunding activity characterized by conservative fundraising outcomes. The key factors identified include the pivotal role of a supportive regulatory framework and the necessity of robust stakeholder collaboration and infrastructure to ensure the industry’s resilience and growth. Research limitations/implications The findings are constrained by the simulated scenarios and the current state of the crowdfunding market in Qatar, suggesting that further research could explore emerging trends as the market evolves. Practical implications This study provides actionable recommendations for policymakers and regulatory authorities to boost a conducive environment for crowdfunding platforms. This includes enhancing connectivity among stakeholders and building robust infrastructure to support industry growth. Social implications This study underlines the significant social benefits of crowdfunding, including promoting innovation, supporting economic growth and facilitating entrepreneurship. These elements are vital to Qatar’s broader economic diversification strategy. Originality/value This study provides original insights into the crowdfunding landscape in Qatar, particularly in terms of strategic planning and risk management, using advanced simulation techniques to predict the outcomes of different regulatory and economic scenarios.

Spatiotemporal Dynamics and Prediction of Habitat Quality Based on Land Use and Cover Change in Jiangsu, China

Analyzing the spatiotemporal evolution characteristics of urban land use and habitat quality is crucial for the sustainable development of urban ecological environments. This study utilizes the land use data of Jiangsu Province for the years 2000, 2010, and 2020, applying the FLUS model to investigate the driving force behind land expansion and to simulate a prediction for the land use of 2030. By integrating the InVEST model and landscape pattern indices, this study analyzes the spatiotemporal evolution characteristics of habitat quality in Jiangsu Province and uses geographical detector analysis to examine the synergistic effects of influencing factors. The results indicate that, from 2000 to 2020, habitat degradation in Jiangsu Province progressively increased, with the spatial distribution of degradation levels showing a gradual change. Under the ecological protection scenario in 2030, habitat fragmentation was alleviated. Conversely, under the economic development scenario, habitat quality further deteriorated, resulting in the largest area of low-quality regions. Minimal changes occurred under the natural development scenario. (2) The landscape indices in Jiangsu Province experienced significant changes from 2000 to 2020. The continuous expansion of urban land into other land use types led to a trend of fragmentation, with a clear increasing trend in dispersion, sprawl, and Shannon’s diversity index, accompanied by a decrease in cohesion. (3) The dominant interacting factors affecting habitat quality were combinations of socioeconomic factors with other factors, indicating that the economy largely determines the spatial distribution pattern of habitat quality. The findings of this study provide optimization strategies for future spatial planning of land use types in Jiangsu Province and offer references for habitat quality restoration efforts in the region.

Building performance optimization through sensitivity Analysis, and economic insights using AI

Optimizing building designs for energy efficiency and occupant comfort presents significant challenges due to the complex and often conflicting requirements of various stakeholders. Consequently, this study conducts a multifaceted sensitivity and economic impact analysis that aims to improve building performance in terms of energy efficiency and occupant comfort by implementing machine learning techniques. Using a broad dataset comprising of 12,000 energy simulation runs for Tvedestrand Upper Secondary School in Norway, several machine learning models were employed with Multi-Layer Perceptron outperforming the others. In addition, several sensitivity analysis methods were used to explore the influence of individual parameters on building performance. The analysis reveals that ventilation rate, room depth, U-value of the facade, and heat gains significantly affect energy consumption. Economic impact analysis was also carried out to compare the cost-effectiveness of traditional HVAC systems with Building Management System (BMS) HVAC solutions. The BMS HVAC system shows significantly lower operational costs over time, with investment costs averaging around 1200 Norwegian kroner (NOK)/m2 and operational costs of approximately 150 NOK/m2 per year. Sensitivity analysis under different economic scenarios highlights the economic viability of the BMS HVAC system. This study identifies optimal building parameters that balance energy efficiency and thermal comfort, achieving total energy consumption between 11.05 and 22.51 kWh/m2 and zero discomfort hours (h > 26 °C). In sum, the findings offer valuable insights for stakeholders, enabling informed decisions about sustainable building design and energy efficiency improvements, ensuring both technical soundness and financial viability under a wide range of conditions, while using the tested tools.

Mathematical modeling of Ethiopia's energy demand by sectors and energy types, with forecasts for the next 30 years

Due to the scarcity of economic resources, it is vital to optimize everything so that the supply and demand lines intersect in an optimized quantity, with no shortage or surplus of a provided item or service. Energy supply contains both surplus and shortage, thus estimating the amount of projected energy demand is a key work that must be completed. The objective of this paper is generating a mathematical model based on the actual data for thirty years forecasting. To create a mathematical model using actual data from the last fifteen years, a model that can represent the past trend and be used for future forecasting. This study provides a general overview of Ethiopia's current energy requirement with different energy type as well as sector-specific energy demand and estimates for different economic growth scenarios up to 2052. This model was created using a linear regression polynomial fit through Origin graphic and analysis software, and an econometric model was also applied. GDP was utilized as an independent variable in the economic model to determine the trend of energy consumption. Another input-output model is also used for multilinear regression to evaluate the change of four variables, GDP, population growth, urbanization growth rate, and general inflation rate, which was quantitatively linked with total energy requirement using Weka software. The mathematical model developed through linear and multilinear regression has been validated by using a different assumption on GDP growth based on past growth rate as low, medium and high growth rate and using the mathematical formula to generate an energy demand trend that can be compared with the actual trend; as a result, all the mathematical model that are generated has been found to be valid for the purpose of the intended work. Based on the generated mathematical model and different GDP growth rate scenario as low, medium, business as usual (BAU) and high a future energy demand was forecasted up to 2052 for thirty years. The model's results can help energy planners ensure that the country's supply capacity keeps up with predicted energy demand growth.

Multi-Scenario land cover changes and carbon emissions prediction for peak carbon emissions in the Yellow River Basin, China

Research on future land cover changes and carbon emissions is essential for effective land resource management and developing feasible carbon mitigation strategies. This study focused on the Yellow River Basin and employed the Future Land Use Simulation (FLUS) and Autoregressive Integrated Moving Average (ARIMA) models to project future land cover and carbon emissions. Additionally, bivariate spatial autocorrelation was utilized to analyze the relationship between them. Key findings are as follows: 1) Historically, the Yellow River Basin has experienced an expansion in construction land, forests, grasslands, and water, while cropland and unused land have diminished. Notably, construction land displayed the most significant changes, whereas grasslands showed minimal modification. Looking ahead, both the ecological protection and inertial development scenarios exhibit consistent trends with historical patterns across the land type categories. In contrast, the economic priority development scenario forecasts an increase in construction land, cropland, and grasslands, indicating a distinct shift compared to the other scenarios. However, the ecological protection scenario proves to be more sustainable. 2) In the absence of intervention, the simulated carbon emissions from construction land throughout the basin display a linear increase across various scenarios, with provincial-level variations showing an increase from southwest to northeast. However, Henan and Sichuan are expected to experience slower reductions in carbon emissions, compared to other projections. There is a notable positive correlation between carbon emissions and the comprehensive index, indicating that regions with high emissions typically experience substantial land and economic development. 3) Energy consumption projections for 2030 and 2060 indicate that to align with China’s carbon goals, it is essential to reduce energy consumption and adjust the fossil to non-fossil fuel ratio to reduce carbon emissions. Substituting coal with clean energy and enhancing energy efficiency will be more effective for achieving low-carbon emission targets. In summary, this study provides significant guidance for China’s ecological conservation, low-carbon emission strategies, and global carbon emission control efforts.

Lignocellulosic pruning waste adsorbents to remove emerging contaminants from tyre wear and pharmaceuticals present in wastewater in circular economy scenario

The following work explores a sustainable approach to repurpose organic waste from poplar pruning into lignocellulosic waste-based activated carbons (LPWACs) through environmentally friendly thermochemical processes and in line with circular economy principles. The developed LPWACs, activated by potassium hydroxide (KOH) at two different temperatures and weight ratios, exhibited promising textural properties with BET surface area (SBET) and total pore volume (VTOT) reaching up to 1336 m2·g−1 and 0.588 cm3·g−1, respectively. In addition, they displayed a developed microporous structure with a significant oxygen content (up to 11 %). These activated carbons were used to remove five emerging organic pollutants from the leaching of tyre wear particles (TWPs) and pharmaceuticals present in water. The increase in oxygen groups had a negative effect on the adsorption capacity of 1H-benzotriazole (BZTL), while electrostatic influences hindered diatrizoic acid (DZT) adsorption. LPWACs effectively remove pharmaceutical and tyre contaminants, supporting the circular economy in water treatment.

Quantitative Analysis of Human Activities and Climatic Change in Grassland Ecosystems in the Qinghai–Tibet Plateau

Net primary production (NPP) serves as a critical proxy for monitoring changes in the global capacity for vegetation carbon sequestration. The assessment of the factors (i.e., human activities and climate changes) influencing NPP is of great value for the study of terrestrial systems. To investigate the influence of factors on grassland NPP, the ecologically vulnerable Qinghai–Tibet Plateau region was considered an appropriate study area for the period from 2000 to 2020. We innovated the use of the RICI index to quantitatively represent human activities and analyzed the effects of RICI and climatic factors on grassland NPP using the geographical detector. In addition, the future NPP was predicted through the integration of two modeling approaches: The Patch-Generating Land Use Simulation (PLUS) model and the Carnegie–Ames–Stanford Approach (CASA) model. The assessment revealed that the expanded grassland contributed 7.55 × 104 Gg C (Gg = 109 g) to the total NPP, whereas the deterioration of grassland resulted in a decline of 1.06 × 105 Gg C. The climatic factor was identified as the dominant factor in grassland restoration, representing 70.85% of the total NPP, as well as the dominant factor in grassland degradation, representing 92.54% of the total NPP. By subdividing the climate change and human activity factors into sub-factors and detecting them with a geographical detector, the results show that climate change and anthropogenic factors have significant ability to explain geographic variation in NPP to a considerable extent, and the effect on NPP is greater when the factors interact. The q-values of the Relative Impact Contribution Index (RICI) and the RICI of the land use change NPP are consistently greater than 0.6, with the RICI of the human management practices NPP and the evapotranspiration remaining at approximately 0.5. The analysis of the interaction between climate and human activity factors reveals an average impact of greater than 0.8. By 2030, the NPP of the natural development scenario, economic development scenario (ED), and ecological protection scenario (EP) show a decreasing trend due to climate change, the dominant factor, causing them to decrease. Human activities play a role in the improvement. The EP indicates a positive expansion in the growth rate of forests, water, and wetlands, while the ED reveals rapid urbanization. It is notable that this is accompanied by a temporary suspension of urban greening.

A CDSS based Integrated Pathway for Influenza Vaccination Across Primary and Secondary Care

Abstract Background In Italy, influenza vaccination coverage in people ≥ 65 years is unsatisfactory (56.7%), underlining the need to improve current vaccination strategies. The objectives of this study have been: to define a novel pathway to increase influenza vaccination adherence among ≥ 65 years population in the Lazio region; to provide a predictive estimate of the epidemiological and economic pathway’s potential impact. Methods A multidisciplinary working group (WG) featuring cross-sectoral expertise was created and WG periodic meetings were held to define the patient journey and its flow-chart representation. The pathway’s potential impact was assessed through epidemiological and economic indicators and scenario analyses. Results An integrated pathway across primary and secondary care was defined, based on the active patient in-Hospital recruitment and vaccination and enhanced by a Clinical Decision Support System relying on a digital algorithm to identify eligible patients. Assuming an increase of influenza vaccination coverage from the current rate of 60% (scenario 1) to 65% (scenario 2) in ≥ 65 years population in the Lazio region thanks to the pathway implementation, an increase of 8% in avoided influenza cases, influenza- or pneumonia-related hospitalizations and influenza-related outpatient visits was estimated with a relative increase in savings for hospitalizations and outpatients visits of up 2,367,310 euros. Setting the vaccination coverage at 70% (scenario 3), an increase of 16% in avoided influenza cases, hospitalizations and outpatient visits was estimated with a relative increase in savings for hospitalizations and outpatients’ visits of up to 4,833,259 euros. Conclusions Alongside offering a predictive estimate of the relevant pathway’s potential impact, both epidemiological and economic, this project, with its robust methodology, may serve as a scalable and transferable model for enhancing vaccination coverage at national and international level. Key messages • The proposed pathway, offering the option of receiving flu vaccination within the Hospital, supports the paradigm shift towards primary prevention pathways in secondary care settings. • Another relevant aspect of the integrated pathway is the adoption of an Artificial Intelligence tool to identify suitable patients and improve their recruitment and adherence to vaccination.

Future Scenarios of Forest Carbon Sink in a Typical Subtropical County

In the context of achieving global carbon neutrality, forests play a pivotal role in sequestering atmospheric CO2, particularly in China, where forest management is central to national climate strategies. This study evaluates the forest carbon sink capacity in Zixi County, a subtropical region, under varying climate scenarios (SSP2-4.5 and SSP5-8.5). Using the Forest-DNDC (Denitrification–Decomposition) model, combined with high-precision climate data and a random forest model, we simulate forest carbon density and forest carbon sink under different management strategies. The results indicate that under the baseline scenario, forest carbon density in Zixi County increases by 31% over 42 years under the SSP2-4.5 climate scenario and by 28.6% under SSP5-8.5. In the enhancing economic scenario, carbon density increases by 8.5% under SSP2-4.5 and by 7.2% under SSP5-8.5. For the natural development scenario, a significant increase of 130% is observed under SSP2-4.5, while SSP5-8.5 shows an increase of 120%. Spatially, forest carbon sinks in Zixi County total 843,152 T C in 2020, 542,852 T C in 2030, and 877,802 T C in 2060 under the baseline SSP2-4.5 scenario; under SSP5-8.5, these values are 841,321 T C in 2020, 531,301 T C in 2030, and 1,016,402 T C in 2060. In the enhancing economic scenario, the total carbon sink is 34,650 T C in both 2020 and 2030, increasing to 427,351 T C in 2060 under SSP2-4.5, while under SSP5-8.5, it is 46,200 T C in 2020, 34,650 T C in 2030, and 415,801 T C in 2060. The natural development scenario shows the total carbon sink under SSP2-4.5 as 11,157,332 T C in 2020, 3,441,910 T C in 2030, and 1,409,104 T C in 2060, and under SSP5-8.5, it is 10,903,231 T C in 2020, 3,337,960 T C in 2030, and 1,131,903 T C in 2060. Spatial analysis reveals that elevation and forest type significantly affect carbon density, with high-altitude areas and forests dominated by Chinese fir and broadleaf species showing higher carbon accumulation. The findings highlight the importance of targeted forest management, prioritizing species with higher carbon sequestration potential and considering spatial heterogeneity. These strategies, applied locally, can contribute to broader national and global carbon neutrality efforts.