Baseline Scenario Research Articles

Optimizing vehicle Front-End structure for e-bike rider Safety: An advanced Multi-Objective approach using injury prediction models

A multi-objective optimization method based on an injury prediction model is proposed to address the increasingly prominent safety issues for e-bike riders in Chinese road traffic. This method aims to enhance the protective effect of vehicle front-end for e-bike riders by encompassing a broader range of test scenarios. Initially, large-scale rider injury response data were collected using automated Madymo simulations. A machine learning model was then trained to accurately predict the risk of rider injury under varied crash conditions. Subsequently, this model was integrated into a multi-objective optimization framework, combined with multi-criteria decision analysis, to effectively evaluate and rank various design alternatives on the Pareto frontier. This process entailed a comparative analysis of the design in a baseline scenario before and after optimization, focusing on both kinematic and injury responses of riders. Through detailed injury mechanism analysis, key design variables such as the height of the hood front and the width of the bumper were identified. This led to the proposal of specific optimization strategies for these structural parameters. The results from this study demonstrate that the proposed optimization method not only guides the design process accurately and efficiently but also balances the injury risks across different body parts. This approach significantly reduces the injury risk for riders in car-to-e-bike collisions and provides actionable insights for vehicle design enhancements.

Spatio-temporal distribution and peak prediction of energy consumption and carbon emissions of residential buildings in China

With the acceleration of urbanization and the improvement of people's living standards, the carbon emissions of residential buildings (BCE) in China have been increasing, hindering the achievement of carbon peaking and carbon neutrality goals. It has become increasingly urgent and important to analyze and grasp the dynamic trends of BCE. Given the notable regional variations in carbon emissions, it is necessary to delve into the distribution characteristics of BCE and the underlying factors influencing them. First, based on the emission factor method, the energy consumption and carbon emissions calculation models are established. Next, the main influencing factors are obtained by improving Kaya's constant equation. Meanwhile, the GA-PPC-Kmeans model is established to divide BCE into different regions. Then, the STIRPAT-Ridge model is built to predict the peak carbon emissions. Finally, a combination of static and dynamic methods is used to forecast peaks under three scenarios, which are low-carbon (LC) scenario, baseline (BA) scenario, and high-carbon (HC) scenario. The results show that five pivotal factors significantly impact BCE in China, which are energy carbon emission intensity (ECEI), energy intensity (EI), economic density (ED), residential housing level (RHL) and population size(P). Furthermore, BCE is categorized into five distinct regions: low-carbon demonstration area, energy efficiency improvement area, carbon concentration and innovation area, high-carbon optimization area, and carbon poverty development area. Under BA scenario, the peaks for BCE in these regions converge primarily around 2040 and 2045. This study provides a regional research perspective for China's residential buildings to reach the peak of carbon emissions, and serves as a reference for formulating carbon emission reduction plans in different regions.

Multi-Scenario Ecological Network Conservation Planning Based on Climate and Land Changes: A Multi-Species Study in the Southeast Qinghai–Tibet Plateau

The Qinghai–Tibet Plateau ecosystem is fragile, experiencing rapid changes in land cover driven by both climate change and human activities, leading to habitat fragmentation and loss and resulting in biodiversity decline. Habitat ecological networks (HA-ENs) are considered effective solutions for habitat connectivity and biodiversity conservation in response to these dual drivers. However, HA-EN studies typically rely on current or historical landscape data, which hinders the formulation of future conservation strategies. This study proposes three future scenarios—improvement, deterioration, and baseline scenarios—focused on the southeastern Qinghai–Tibet Plateau (SE-QPT). The habitats of 10 species across three classes are extracted, integrating land use and climate change data into habitat ecological network modeling to assess the long-term dynamics of HA-ENs in the SE-QPT. Finally, conservation management strategies are proposed based on regional heterogeneity. The results show the following: Climate change and human activities are expected to reduce the suitable habitat area for species, intensifying resource competition among multiple species. By 2030, under all scenarios, the forest structure will become more fragmented, and grassland degradation will be primarily concentrated in the southeastern and western parts of the study area. Compared to 1985 (71,891.3 km2), the habitat area by 2030 is projected to decrease by 12.9% (62,629.3 km2). The overlap rate of species habitats increases from 25.4% in 1985 to 30.9% by 2030. Compared to the HA-EN control in 1985, all scenarios show a decrease in connectivity and complexity, with only the improvement scenario showing some signs of recovery towards the control network, albeit limited. Finally, based on regional heterogeneity, a conservation management strategy of “two points, two cores, two corridors, and two regions” is proposed. This strategy aims to provide a framework for future conservation efforts in response to climate change and human activities.

Insights into different marine aquaculture infrastructures from a life cycle perspective

Aquaculture facilities represent an often-neglected process in environmental impact studies. This study focus on the environmental impact assessment of alternative net materials in Mediterranean marine aquaculture. A Life Cycle Assessment was conducted using primary and secondary data from specific databases and literature. Three baseline scenarios were compared: copper alloy net cages with 100 % of recycled material (CAN100), 75 % of recycled material (CAN75), and polyethylene net (PEN) System boundaries include manufacturing and disposal of cages, nets, and mooring system. The use and emissions of antifouling paints and CAN were considered. Sensitivity analysis of the most impacting sub-processes and Uncertainty analysis were also conducted. The use of CAN is advantageous in terms of environmental impact, but only considering a complete recyclability of the net at the end of its service life. Moreover, when considering a reduced service life of the PEN due to the detrimental effect of biofouling, the advantage of the CAN is even more evident. To counteract the negative effect of biofouling, copper-based antifouling paints are generally used in marine aquaculture. These products are a main environmental hotspot in PEN systems. Therefore, a higher consumption of such products could determine an environmental burden shifting from CAN to PEN ones. So far, CAN are not widespread in the aquaculture industry, mainly due to the high cost of initial investment compared to traditional PEN. Considering operational and environmental advantages, CAN cages could represent an affordable and resilient solution for aquaculture enhancing environmental, economic, and social performances of this industry.

Multi-Objective optimal scheduling of energy Hubs, integrating different solar generation technologies considering uncertainty

For a few decades, operators of energy systems have sought to achieve appropriate frameworks due to energy crises and rapid growth in energy requirements. In this regard, this study presents a multi-objective optimization model for an energy hub (EH) designed to manage a diverse energy portfolio. The EH receives electricity, natural gas, hydrogen, seawater, and solar energy as inputs, aiming to satisfy electricity, heating, and freshwater demands at the output port while considering a limited available area. The model incorporates the selection of the optimal solar energy technology (photovoltaics, parabolic dish, or parabolic trough collector) through a comprehensive evaluation encompassing technical, economic, and environmental aspects. To achieve optimal scheduling of the EH’s production units, the model factors in forecasts of solar energy availability alongside electrical, heat, and water load demands. The evaluation of the EH’s performance is conducted through a multi-objective framework considering social welfare, CO2 emissions, voltage stability margin (VSM), a newly proposed simplified fast temperature stability index (SFTSI), and a similarly novel simplified fast pressure stability index (SFPSI). The optimization problem is formulated within a MATLAB environment and solved using a multi-objective Archimedes optimization algorithm across five distinct case studies, each characterized by a varying designated area for solar energy generation. The effectiveness of the proposed model and optimization technique is validated through test systems, with the obtained results demonstrating significant improvements compared to a baseline scenario. These improvements include a 36.18% reduction in CO2 emissions, a 14.22% increase in total social welfare, and reductions in the average values of VSM, SFTSI, and SFPSI when incorporating all solar energy technologies.

Effect of nirsevimab on hospitalisations for respiratory syncytial virus bronchiolitis in France, 2023–24: a modelling study

Respiratory syncytial virus (RSV) is a major cause of hospitalisations and deaths among infants worldwide. France was one of the first countries to implement a national programme (beginning on Sept 15, 2023) for administration of nirsevimab, a single-dose long-acting monoclonal antibody treatment, to infants born on or after Feb 6, 2023, to prevent lower respiratory tract infection caused by RSV. We aimed to estimate the effectiveness of nirsevimab and the number of hospitalisations averted in children younger than 24 months in real-world settings. In this modelling study, we developed an age-structured deterministic model characterising RSV transmission as well as plausible scenarios for the administration of nirsevimab doses based on maternity ward and community pharmacy supply data. We retrospectively estimated nirsevimab effectiveness in infants younger than 24 months during the 2023-24 RSV season in France (excluding overseas territories) and the number of averted hospitalisations for RSV bronchiolitis occurring after emergency department visits, by calibrating the model to hospital and virological surveillance data from Aug 21, 2017, to Feb 4, 2024, alongside serological data from a previous cross-sectional study. To assess the robustness of our estimates, we conducted sensitivity analyses in which we modified our assumptions about the number of doses administered, the reconstruction of the number of RSV-associated hospitalisations for bronchiolitis, the duration of maternal and post-infection immunity to RSV, and the number of contacts in children aged 0-2 months. We estimated that nirsevimab administration prevented 5800 (95% credible interval 3700-7800) RSV-associated hospitalisations for bronchiolitis after emergency department visits among children younger than 24 months, including 4200 (2900-5600) hospitalisations among those aged 0-2 months, between Sept 15, 2023 (the date nirsevimab was introduced), and Feb 4, 2024-a 23% (16-30) reduction in the total number of hospitalisations and a 35% (25-44) reduction in the 0-2 months age group, compared with the scenario without administration. In our baseline scenario, in which we estimated that 215 000 doses of nirsevimab were administered by Jan 31, 2024, the estimated effectiveness against RSV-associated hospitalisations for bronchiolitis was 73% (61-84), corresponding to one hospitalisation averted for every 39 (26-54) doses administered. In sensitivity analyses, nirsevimab remained effective against RSV-associated hospitalisations for bronchiolitis after emergency department attendance. Our findings show that nirsevimab administration campaigns could effectively reduce the RSV-related hospital burden of bronchiolitis in children younger than 24 months. European Commission, Laboratoire d'Excellence Integrative Biology of Emerging Infectious Diseases programme, and INCEPTION project.

Enhancing natural carbon sinks: Simulation of land use change under different carbon market scenarios by developing an ANN-ABM model

The carbon market mechanism presents an innovative approach to achieving carbon neutrality, however, its impact on regional carbon sink enhancement remains uncertain. This paper proposes an analysis framework based on an Artificial Neural Network-Agent-Based Model (ANN-ABM) to simulate the potential contribution of carbon market mechanism in enhancing carbon sinks. Taking the case of Chongming, China, the results demonstrate significant economic potential with forest land expansion from 2010 to 2020, equivalent to 30.69 % of eco-compensation. Under scenarios introducing a carbon market, there is an increased probability of converting land to high carbon sink types. Compared to the baseline scenario, carbon prices at 1.34 US$/t and 6.27 US$/t result in additional funds of 8.94 % and 41.46 %, respectively, and increase the carbon sink by 12.52 % and 30.28 %. The findings contribute to an understanding of how the value of carbon sinks can be realized through market mechanism and offer guidance for innovative eco-compensation approaches.

Overview of recent experimental results on the EAST Tokamak

Since the last IAEA-FEC in 2021, significant progress on the development of long pulse steady state scenario and its related key physics and technologies have been achieved, including the reproducible 403 s long-pulse steady-state H-mode plasma with pure radio frequency (RF) power heating. A thousand-second time scale (∼1056 s) fully non-inductive plasma with high injected energy up to 1.73 GJ has also been achieved. The EAST operational regime of high β P has been significantly extended (H 98y2 > 1.3, β P ∼ 4.0, β N ∼ 2.4 and n e/n GW ∼ 1.0) using RF and neutral beam injection (NBI). The full edge localized mode suppression using the n = 4 resonant magnetic perturbations has been achieved in ITER-like standard type-I ELMy H-mode plasmas with q 95 ≈ 3.1 on EAST, extrapolating favorably to the ITER baseline scenario. The sustained large ELM control and stable partial detachment have been achieved with Ne seeding. The underlying physics of plasma-beta effect for error field penetration, where toroidal effect dominates, is disclosed by comparing the results in cylindrical theory and MARS-Q simulation in EAST. Breakdown and plasma initiation at low toroidal electric fields (<0.3 V m−1) with EC pre-ionization is developed. A beneficial role on the lower hybrid wave injection to control the tungsten concentration in the NBI discharge is observed for the first time in EAST suggesting a potential way toward steady-state H-mode NBI operation.

Impacts of Climate Change on Streamflow on Dawa Sub-watershed, Genale-Dawa River Basin, Southern Ethiopia

&amp;lt;i&amp;gt;Climate change is statistical variations over an extended period in the features of the climate system, such as variations in global temperatures and precipitation, caused by human and natural sources.&amp;lt;/i&amp;gt; In this study aimed to measure and examine how streamflow in the Dawa sub-basin, Genale Dawa River basin was affected by climate change. It used the average of five regional climate models from the Coordinated Regional Climate Downscaling Experiment (CORDEX) Africa, under two different scenarios of Representative Concentration Pathways: RCP4.5 and RCP8.5. The baseline scenario was based on the data from 1975 to 2005, while the future scenarios were based on the data from 2020s (2025–2054) and 2050s (2055–2084). The HBV hydrological model used to assess the impact on streamflow. The HBV model showed good statistical performance in simulating the impact of climate change on streamflow, with a coefficient of determination (R&amp;lt;sup&amp;gt;2&amp;lt;/sup&amp;gt;) of 0.88 and Nash-Sutcliffe Efficiency (NSE) of 0.77 for monthly calibration, and R&amp;lt;sup&amp;gt;2&amp;lt;/sup&amp;gt; of 0.86 and NSE of 0.83 for monthly validation. The impacts quantified using the mean monthly changes in precipitation, maximum and minimum temperatures. The bias-corrected precipitation and temperature showed a reasonable increase in both future periods for both RCP 4.5 and RCP 8.5 scenarios. These changes in climate variables resulted in a decrease in mean annual streamflow by 1.6 and 3.5% for RCP 4.5 and by 4.6 and 4.9% for RCP 8.5 scenarios of the 2020s and 2050s, respectively. Based on the analysis that predicted a drop in precipitation during the months, and seasons and an increase in precipitation during the &amp;lt;i&amp;gt;Belg&amp;lt;/i&amp;gt; season, with a corresponding decrease and rise in stream flow throughout the watershed. So to offset the variation in the watershed, community should adopt various; Soil and water conservation technologies, Using drought tolerant crops, Implementing various trees and appropriate design and applying a water harvesting structure like in-situ, internal or micro catchment, external or macro catchment water harvesting and Surface runoff harvesting. This result offers useful information for current and future water resource management in the basin and similar other watershed in the country.

Improving the Decision-Making for Sustainable Demolition Waste Management by Combining a Building Information Modelling-Based Life Cycle Sustainability Assessment Framework and Hybrid Multi-Criteria Decision-Aiding Approach

Increasing efforts have been devoted to promoting sustainable demolition waste management (DWM) from a life cycle thinking perspective. To this end, facilitating sustainability-oriented decision-making for DWM planning requires a sustainability assessment framework for assessing the trade-offs among multifaceted criteria. This study develops a BIM-based DWM sustainability assessment approach to facilitate the life cycle sustainability assessment (LCSA) and decision-making by integrating LCSA-related properties and hybrid Multi-Criteria Decision-Aiding (MCDA) methods into a BIM environment using Dynamo visual scripting. A dynamic linkage is developed in the streamlined BIM-based LCSA process, where the enriched Industry Foundation Class (IFC) models are coupled with custom LCSA data templates to achieve seamless data exchange between the BIM platform and external LCA tools. Subsequently, hybrid MCDA methods convert the assessment results into DWM scenario ranking. A pilot study verifies the applicability of the BIM-based framework. The results unveil that the sustainability score ascended with the recycling rate. The optimal DWM alternative with the highest recycling rate yields the highest sustainability score at 91.63. Conversely, a DWM alternative reflecting the ‘status quo’ in China’s recycling industry has the lowest score at 8.37, significantly lower than the baseline scenario with a 50% recycling rate. It is worth noting that the ‘growth curve’ of the sustainability score continuously flattens as the target recycling rate escalates. The increment in recycling rate from the “Australian standard” scenario to the optimal scenario is 18.4%, whereas the sustainability score merely increases by 2.3%, implying that the former scenario arrived at an optimum point for maximising the cost-efficiency of DWM under the predefined settings.

Optimizing water-energy-food nexus index, CO2 emissions, and chemical pollutants under irrigation water salinity scenarios

The escalation of crises related to water quantity of quality, energy, food, and the environment has posed numerous challenges to sustainable development in the agricultural sector. This study seeks to establish an optimal and sustainable framework within the agricultural sector by meeting the objectives of the WEF (Water-Energy-Food) nexus index and environmental. For this, we individually optimized the objectives: maximizing the WEFN index (O1), minimizing CO2 emissions (O2), reducing chemical fertilizer consumption (O3), minimizing chemical pesticide usage (O4), and maximizing gross margin (O5) under various electrical conductivity (EC) scenarios (optimistic, moderate, and pessimistic) within the irrigation network of the Jiroft plain in Iran. In the second stage, we employed a Multi-Objective Programming (MOP) Model to attain these objectives using a weighted sum approach simultaneously. The results of the first stage revealed that under moderate and pessimistic EC irrigation water scenarios, significant alterations in the crop selection within the optimized models for O1 and O5 objectives occurred compared to the baseline scenario, which did not consider EC irrigation water. Specifically, in the pessimistic scenario with an EC irrigation water level of 2.25 ds/m, crops such as onions, tomatoes, and potatoes were replaced within the optimal cropping pattern by wheat, barley, and green-maize, leading to a notable decline in program efficiency. The results from the MOP optimization model indicated that in the pessimistic EC irrigation water scenario, the WEFN index, CO2 emissions, fertilizer consumption, pesticide consumption, and gross margin would change by approximately +12%, −48%, −28%, −8%, and −74%, respectively, compared to the baseline scenario. Consequently, an increase in EC irrigation water, despite improving environmental conditions, would substantially diminish economic profit. Thus, overlooking the impact of EC irrigation water in the WEF nexus analysis could result in misleading conclusions.

Epidemiological impact of Neisseria gonorrhoeae and Chlamydia trachomatis screening in men having sex with men: a modelling study

ObjectivesThe impact of the systematic screening of Neisseria gonorrhoeae (NG) and Chlamydia trachomatis (CT) in men having sex with men (MSM) on these pathogens’ epidemiology remains unclear. We conducted a...

Overview of ASDEX upgrade results in view of ITER and DEMO

Experiments on ASDEX Upgrade (AUG) in 2021 and 2022 have addressed a number of critical issues for ITER and EU DEMO. A major objective of the AUG programme is to shed light on the underlying physics of confinement, stability, and plasma exhaust in order to allow reliable extrapolation of results obtained on present day machines to these reactor-grade devices. Concerning pedestal physics, the mitigation of edge localised modes (ELMs) using resonant magnetic perturbations (RMPs) was found to be consistent with a reduction of the linear peeling-ballooning stability threshold due to the helical deformation of the plasma. Conversely, ELM suppression by RMPs is ascribed to an increased pedestal transport that keeps the plasma away from this boundary. Candidates for this increased transport are locally enhanced turbulence and a locked magnetic island in the pedestal. The enhanced D-alpha (EDA) and quasi-continuous exhaust (QCE) regimes have been established as promising ELM-free scenarios. Here, the pressure gradient at the foot of the H-mode pedestal is reduced by a quasi-coherent mode, consistent with violation of the high-n ballooning mode stability limit there. This is suggestive that the EDA and QCE regimes have a common underlying physics origin. In the area of transport physics, full radius models for both L- and H-modes have been developed. These models predict energy confinement in AUG better than the commonly used global scaling laws, representing a large step towards the goal of predictive capability. A new momentum transport analysis framework has been developed that provides access to the intrinsic torque in the plasma core. In the field of exhaust, the X-Point Radiator (XPR), a cold and dense plasma region on closed flux surfaces close to the X-point, was described by an analytical model that provides an understanding of its formation as well as its stability, i.e., the conditions under which it transitions into a deleterious MARFE with the potential to result in a disruptive termination. With the XPR close to the divertor target, a new detached divertor concept, the compact radiative divertor, was developed. Here, the exhaust power is radiated before reaching the target, allowing close proximity of the X-point to the target. No limitations by the shallow field line angle due to the large flux expansion were observed, and sufficient compression of neutral density was demonstrated. With respect to the pumping of non-recycling impurities, the divertor enrichment was found to mainly depend on the ionisation energy of the impurity under consideration. In the area of MHD physics, analysis of the hot plasma core motion in sawtooth crashes showed good agreement with nonlinear 2-fluid simulations. This indicates that the fast reconnection observed in these events is adequately described including the pressure gradient and the electron inertia in the parallel Ohm’s law. Concerning disruption physics, a shattered pellet injection system was installed in collaboration with the ITER International Organisation. Thanks to the ability to vary the shard size distribution independently of the injection velocity, as well as its impurity admixture, it was possible to tailor the current quench rate, which is an important requirement for future large devices such as ITER. Progress was also made modelling the force reduction of VDEs induced by massive gas injection on AUG. The H-mode density limit was characterised in terms of safe operational space with a newly developed active feedback control method that allowed the stability boundary to be probed several times within a single discharge without inducing a disruptive termination. Regarding integrated operation scenarios, the role of density peaking in the confinement of the ITER baseline scenario (high plasma current) was clarified. The usual energy confinement scaling ITER98(p,y) does not capture this effect, but the more recent H20 scaling does, highlighting again the importance of developing adequate physics based models. Advanced tokamak scenarios, aiming at large non-inductive current fraction due to non-standard profiles of the safety factor in combination with high normalised plasma pressure were studied with a focus on their access conditions. A method to guide the approach of the targeted safety factor profiles was developed, and the conditions for achieving good confinement were clarified. Based on this, two types of advanced scenarios (‘hybrid’ and ‘elevated’ q-profile) were established on AUG and characterised concerning their plasma performance.

Green energy and rooftop innovation: Unlocking the carbon reduction potential of photovoltaic-green roofs

As urbanization progresses rapidly, cities encounter significant environmental and energy challenges. Photovoltaic-Green Roof (PV-GR) technology offers an innovative strategy with the potential to alleviate urban carbon emissions and resource scarcity issues. However, the carbon reduction potential of PV-GR technology remains unclear. Hence, this study aims to comprehensively assess the carbon reduction potential of PV-GR. This is achieved by integrating Geographic Information Systems (GIS), lifecycle assessment, the Denitrification-Decomposition Model (DNDC), and solar simulation. Using Fuzhou City as a case study, the research indicates: (1) Fuzhou has approximately 72.9 km2 of rooftops suitable for PV-GR development, with an annual biomass production from herbaceous plants estimated at around 2.958 × 107 kg. The annual electricity production under the baseline scenario reaches 9,678 GWh, satisfying about 17 % of Fuzhou’s annual electricity demand. Moreover, in an optimistic scenario, electricity generation rises to 10,176 GWh, and even in a pessimistic scenario, it could achieve 9,471 GWh. (2) In the baseline scenario, Fuzhou’s PV-GR annual carbon reduction is estimated at 6.678 × 106 t CO2, potentially offsetting about 11.14 % of the city’s annual carbon emissions. In an optimistic scenario, this reduction increases to 7.022 × 106 t CO2, and even in a pessimistic scenario, the reduction remains significant at 6.535 × 106 t CO2. (3) Over a 30-year lifecycle, the carbon emissions from PV-GR are projected to total 3.092 × 107 t CO2, accounting for 51.34 % of Fuzhou’s annual emissions. In an ideal baseline scenario, the net carbon reduction over the lifecycle of PV-GR could total 1.703×108 t CO2, effectively offsetting 282.76 % of Fuzhou’s annual carbon emissions. Additionally, scenario simulations suggest that by 2030, potential electricity generation from PV-GR could increase to between 10,463 GWh and 10,901 GWh, due to changes in power structure and urban expansion. Overall, this study demonstrates that PV-GR holds considerable potential for carbon reduction.

Simulation of hydrodynamic changes and salinity intrusion in the lower Vietnamese Mekong Delta under climate change-induced sea level rise and upstream river discharge

Saltwater intrusion results from a complex interaction of many factors, such as global climate change, extreme climate patterns and overuse of natural resources. Currently, the Vietnamese Mekong Delta (VMD) faces great challenges from saltwater intrusion. This situation is very serious, tends to increase in scope and scale, directly threatens life and property, and negatively impacts the sustainable economic development of this area. The objective of this study is to evaluate and predict changes in the hydrodynamic regime and salinity intrusion in the Lower VMD (from Can Tho and My Thuan to estuaries and coastal regions) caused by anticipated increases in sea level and the decrease in river discharge from upstream, using a two-dimensional numerical model. The research includes many scenarios, such as a baseline scenario in February 2020 and eight sea level rise (SLR) scenarios ranging from 14 cm to 58 cm in 2050 and 2100. The simulation findings indicate that when the sea level rises, there is a significant increase in salinity and saltwater intrusion length, resulting in increased wave height, decreased current speed, and a decline in upstream discharge of the rivers. The work has enhanced our comprehension of the impact of these hydrodynamic alterations on saltwater incursion and riverbank erosion.

Simulation of smallholder farmers’ adaptation to irrigation-induced landslides: An ABM application in human-land-policy interaction

Understanding the dynamic interaction between smallholder farmers' adaptation decision-making behavior and the policy environment in the context of human-induced disasters is vital for developing effective policies to enhance farmers' participation in disaster risk reduction (DRR). From the perspective of bounded rationality theory, this study constructs the farmer-land-policy interaction (FLPI) model, taking Heifangtai in Loess Plateau, China, as a case study. Based on first-hand micro data, this study combines static econometric model analysis with dynamic simulation techniques, achieving a combination of micro decision-making and macro policies to understand the interaction between farmers and the policy environment. The FLPI model simulates farmers' future adaptations under multiple policy scenarios (baseline, mandatory policy, and subsidy policy scenario with a combination of different policy tools) from 2021 to 2030. Compared with the simulation results of the baseline scenario, the results indicate that mandatory and subsidy policies are effective interventions incentivizing farmers’ adaptation behavior for effective DRR. Mandatory policies rely on policy intervention to ensure that farmers adopt drip irrigation and to promote the generation of long-term behavior of farmers. And the results also propose a suitable subsidy range of 700–900 yuan and with a period of more than 2 years for subsidy policy. This study enriches the research on the interaction simulation between farmer behavior and policy environment under the background of human-induced disasters. And the FLPI model uses survey data as input, which could provide behavior rules closer to real situations than that of simplifying assumptions. The research indicates that the “bottom-up” approach of the FLPI model proven more appropriate to presenting micro-level adaptation and dynamic changes than traditional statistical models.And the agent-based model is very suitable for simulating the behavioral decision-making changes of farmers in policy environments.

How increased heifer growth rate and reduced dairy cow replacement rate can improve farm economy and reduce greenhouse gas emissions - a win to win situation?

Rearing of replacement heifers makes up a significant part of the total costs in dairy farming. Nevertheless, the average age at first calving for dairy heifers still stays well above 2 years in many countries. This study examined the economic and environmental impacts of increased heifer growth rates and reduced replacement rates on Norwegian dairy farms. The current average growth rate in Norway (baseline scenario) was compared to an accelerated growth rate scenario. Within each of the two growth rate scenarios, we compared three different cow replacement rates. A farm account survey dataset containing physical and economic data on 311 Norwegian farms was clustered into three farm groups: small, medium, and large. To model economic consequences, we used the whole-farm linear programming model ScotFarm. A life cycle analysis model was used to model the environmental impacts of the baseline scenario and an accelerated growth rate scenario on the three farm groups. Accelerated heifer growth rate had a positive effect (14–28%) on farm annual gross margin depending on farm size. While accelerated growth rate resulted in only minor reductions in total emissions at farm level compared to the baseline scenario, reduced replacement rate lowered total farm level emissions by up to 8%, and emissions per unit of output by up to 6%. We conclude that an accelerated heifer growth rate scenario could potentially increase farm gross margin by some 14–28% compared with a baseline growth rate scenario. Reducing the replacement rate would be more efficient to reduce farm−level greenhouse gas emissions.

Intensified effect of nitrogen forms on dominant phytoplankton species succession by climate change

Nutrient proportion, light intensity, and temperature affect the succession of dominant phytoplankton species. Despite these insights, this transformation mechanism in highly turbid lakes remains a research gap, especially in response to climate change. To fill this gap, we investigated the mechanism by which multi-environmental factors influence the succession of dominant phytoplankton species in Lake Chagan. This investigation deployed the structural equation model (SEM) and the hydrodynamic-water quality-water ecology mechanism model. Results demonstrated that the dominant phytoplankton species in Lake Chagan transformed from diatom to cyanobacteria during 2012 and 2022. Notably, Microcystis was detected in 2022. SEM revealed the primary environment variables for this succession, including water temperature (Tw), nutrients (total nitrogen (TN), total phosphorus (TP), and ammonia nitrogen (NH4N)), and total suspended solids (TSS). Moreover, this event was not the consequence of zooplankton grazing. An integrated hydrodynamic-water quality-bloom mechanism model was built to explore the mechanism driving phytoplankton succession and its response to climate change. Nutrients determined the phytoplankton biomass and dominant species succession based on various proportions. High NH4N:NO3N ratios favored cyanobacteria and inhibited diatom under high TSS. Additionally, the biomass proportions of diatom (30.77 % vs. 22.28 %) and green (30.56 % vs. 23.30 %) decreased dramatically. In contrast, cyanobacteria abundance remarkably increased (35.78 % to 51.71 %) with the increasing NH4-N:NO3-N ratios. In addition, the proportion of non-nitrogen-fixing cyanobacteria was higher than that of the nitrogen-fixing cyanobacteria counterparts when TN:TP≥20 and NH4N:NO3N ≥ 10. Light-limitation phenotypes also experienced an increase with the rising NH4N:NO3N ratios. Notably, the cyanobacterial biomass reached 3–6 times that in the baseline scenario when the air temperature escalated by 3.0 °C until 2061 under the SSP585 scenario. We highlighted the effect of nitrogen forms on the succession of dominant phytoplankton species. Climate warming will increase nitrogen proportion, providing an insightful reference for controlling cyanobacterial blooms.

Impact of mitigating obesity, smoking, and physical inactivity on type 2 diabetes mellitus burden in Oman: insights from mathematical modeling

IntroductionTo estimate the impact of reducing obesity, smoking, and physical inactivity (PIA) prevalence, and of introducing physical activity (PA) as an explicit intervention, on the prevalence, incidence, and mortality of...

Enriching IAM scenarios for effective pLCA integration: A clinker case study

Integrated assessment models are increasingly used to build prospective life cycle databases. While these models provide projections on an economy-wide scale, they can lack detail, with some industries aggregated at sector level and a technological resolution that tends to be too low for the demands of an LCA. This limitation hinders the accurate modelling of several industries in a prospective LCA. This paper aims to bridge the gap in detail between LCA and Integrated assessment models by means of an econometric model, using the cement industry as a case study. While this model sits outside of the integrated assessment model, it ensures consistency with the integrated assessment model's scenario by using data from the integrated assessment model to build its projections. The case study estimates the capital stock required, the fuel mix in the kiln, the most cost-effective kiln type and finally the capital stock composition. This was done for a baseline, moderate and climate stringent scenario, for the EU, USA and Canada. The projections of the model were integrated into a prospective life cycle assessment to determine the global warming potential of clinker production in the future. Results show an increase in alternative fuel use, especially for the EU. The use of natural gas increases for the USA and Canada but remains negligent for the EU. Kilns with carbon capture are adopted, if the carbon tax is high enough and the alternative fuel share is not too high.