Dynamic Assessment Model Research Articles

Wheels of Change: The Environmental Paradox of Accelerating Vehicle Retirement Program.

Accelerated vehicle retirement is recognized as crucial for managing fleet emissions effectively. However, the emergence of new energy vehicles introduces complexities in assessing their environmental impacts. This study developed a dynamic fleet-based life cycle assessment model to analyze the effects of four distinct scrappage strategies in China from 2021 to 2060. The results underscore the importance of a meticulously chosen retirement strategy that harmonizes fleet characteristics with advancements in vehicle technology to promote sustainable mobility. Accelerated retirement strategies are demonstrated to enhance vehicle sales and expedite the incorporation of new energy vehicles into the fleet. Although these policies reduce greenhouse gas and carbon monoxide emissions, they may exacerbate other air pollutants, necessitating vigilant management. Additionally, the temporal distribution of environmental impacts reveals the critical need for long-term assessments. By evaluating six negative externalities of emissions, the research indicates that targeted scrappage policies, which advocate for the retirement of older vehicles, could potentially generate economic benefits of 6.81 to 7.29 billion dollars in reduced losses. However, an overly aggressive scrappage policy could increase negative externalities, leading to additional costs ranging from 0.84 to 3.31 billion dollars. This study reveals the intricate long-term environmental consequences of scrappage strategies accompanying the rise of new energy vehicles and lays a methodological groundwork for ongoing research into the most effective retirement scheme.

A dynamic system reliability analysis model on safety instrumented systems

This paper introduces a novel hybrid dynamic model for complex systems reliability assessment. The model synergizes expert knowledge elicitation and an enhanced Dempster-Shafer Theory (DST) with Dynamic Bayesian Networks (DBNs) modeling, aiming to surmount the limitations such as uncertainty and static modeling inherent in traditional methods. The proposed model is deployed on a Safety Instrumented System (SIS) designed to prevent runaway reactions within a Continuously Stirred Tank Reactor (CSTR), considering factors such as system degradation, human interventions, and proof testing on system reliability. The analysis pinpointed the logic solver subsystem as the principal vulnerability within the assessed SIS, leading to targeted recommendations to bolster system reliability. The outcomes offer insights for a wide range of safety-critical systems aiming to augment the safety and efficacy of SISs, thereby advancing safety and resilience management across various complex engineering systems, particularly in contexts where field data is scant.

Estimating construction and demolition waste in the building sector in China: Towards the end of the century

Amid China’s rapid urbanization and economic growth, increasing construction and demolition waste (CDW) has become a critical environmental and management challenge. In the present study, we introduce a dynamic recursive-based CDW assessment model designed to systematically track and analyze the origins, distribution, and composition of CDW across China. Our results show that China is projected to generate 224.08 billion tonnes (Bt) of CDW from 2000 to 2100, mostly gravel (34.15%), sand (30.08%), and brick/tile (14.37%). Additionally, the primary source of CDW generation will shift from rural to urban public and commercial (P&C) buildings. The proportion of metals such as steel in CDW is rapidly increasing, rising from 2.11% in 2000 to 17.66% in 2100. From 2020 to 2100, reducing material waste during the construction phase can decrease the amount of CDW by 6.88 Bt. Extending the building lifespan during the operation phase can further reduce the amount of CDW by 50.25 Bt. In comparison, implementing recycling strategies during the demolition phase can achieve the most significant reduction in the amount of CDW, with an estimated cumulative decrease of 151.25 Bt. The amounts of gravel, sand, and steel are anticipated to contribute the most to this reduction, accounting for 44.93%, 37.66%, and 8.8% of the total reduction in the amount of CDW, respectively.

Well-planned greenery improves air urban quality - Modelling the effect of altered airflow and pollutant deposition

Urban air quality is influenced by vegetation through alterations in airflow and pollutant deposition processes. We investigated these interactions by integrating the Vegetation Impact Dynamic Assessment model (VIDA) with the Large-Eddy Simulation model PALM. Our analysis focus on nitrogen dioxide (NO₂) and particulate matter (PM) concentrations at the local scale, considering three tree genera. Our findings reveal the necessity of accounting for both gaseous pollutants and particles separately due to their differing mechanisms of deposition onto leaves. The coupled PALM-VIDA model demonstrates a significant reduction in PM levels across the modelling domain and within street canyons when deposition to vegetation is incorporated. Reduction in NO₂ through deposition to vegetation is lower but human NO2 exposure can still be decreased if tree species selection and placement leads to desirable effects on air flow. Sparse tree arrangements or species with sparse crowns facilitate ventilation and are often better at reducing NO₂ concentrations in street canyons compared to denser vegetation with higher deposition but negative effects on ventilation. Our study informs urban planning and green infrastructure design, underscoring the multifaceted role of urban greenery in air pollution mitigation strategies. Its main conclusion is that both deposition processes and the influence of air mixing and ventilation need to be considered to accurately assess the effects of urban trees on local air quality. Ill-considered placement and species selection may cause a net increase in pollutants underneath the trees. However, careful planning can address this risk and instead improve overall air quality.

Optimal design of building envelope towards life cycle performance: Impact of considering dynamic grid emission factors

Building-related carbon emissions in the construction and operation stages account for more than one-third of global energy-related emissions. Optimizing during the early design stage is an effective way to reduce building carbon emissions. However, current studies adopt a constant grid emission factor (GEF) to assess the environmental impacts of buildings while ignoring the dynamic changes of the future electricity mix. This will overestimate the operational carbon emissions of the building in the context of the increasing share of renewable energy in power generation. In this study, a dynamic life cycle assessment model based on dynamic GEF is constructed to evaluate the life cycle environmental impacts of buildings. On this basis, a building optimization design framework considering dynamic GEF is proposed, and the impact of considering future variations of GEF on the optimal design of the building envelope is explored. The study is conducted in three steps. First, dynamically changing GEFs are predicted under the future electricity mix based on scenario analysis. Second, a multi-objective optimization framework is established to minimize the life cycle carbon emissions (LCCE) of the building while optimizing its life cycle costs (LCC) and indoor discomfort hours (IDH). Finally, the proposed optimization framework is applied to a prototype office building in Shanghai, and a comparative analysis is conducted for the optimal schemes between a static and two dynamic scenarios. The result reveals that ignoring future variations will lead to overestimating the operational carbon emissions by 49.0%-64.8%, which in turn will result in an over-insulated design of the envelope (i.e., additional material consumption). In addition, compared to the static scenario, consideration of dynamic GEF results in a 38.7%-51.6% reduction in LCCE, a 5.2%-6.1% reduction in LCC, and a 5.3%-9.5% increase in IDH for the optimal solutions. This research illustrates the importance of considering dynamic GEF in identifying the optimal design parameters and can help decision-makers reasonably choose the optimal schemes during early-stage design.

CCUS source-sink matching model based on sink well placement optimization

Realizing the dual-carbon target is a major strategic plan made by the Party Central Committee and a solemn commitment to address climate change of global significance. Source-sink matching technology in carbon capture, utilization, and storage (CCUS) technology is crucial to achieving the dual-carbon target. However, most previous studies constructed source-sink matching models based on sink-fixed sequestration potential, making it difficult to accurately assess the potential of sequestration sites and thus affect the source-sink matching scheme. Therefore, a dynamic storage potential assessment model has been established which can quickly assess the injection capacity of sinks under different well deployment schemes and then a source-sink matching model based on the overall optimization of sink deployment schemes has been constructed by combining the dynamic storage potential assessment model. The model considers the source matching problem as a mixed-integer linear programming (MILP) problem and obtains the computational results of the dynamic storage potential assessment model to realize the correct matching and simultaneous optimization of the source-sink pipeline network layout and the sink-well deployment scheme. With the proposed model, source-sink matching cases for national-level and project-level have been analyzed. It has been shown that the dynamic storage potential assessment model and the combined method improve the accuracy of the source-sink matching model in the form of MILP while minimizing the total cost and additional computations.

Possibility and pathways of China's nonferrous metals industry to achieve its carbon peak target before 2030: A new integrated dynamic forecasting model

The Chinese government has mandated that the nonferrous metals industry (NMI) achieve carbon peaking before 2030. Consequently, nonscientific mitigation measures, such as indiscriminate closure of production lines, have been implemented. An appropriate carbon peak pathway must be developed NMI. This study designs three carbon peaking pathways for two subsectors within the industrial chain of the NMI according to the latest industry policies and industry characteristics. Subsequently, a novel integrated dynamic assessment model is constructed in this study to evaluate the probability of carbon peaking under various pathways and choose an appropriate one. Results indicate that: (1) Under the baseline development pathway, the likelihood of meeting the target as anticipated is 61.6 % for the nonferrous metal mining and processing industry (MS) and 9.9 % for the nonferrous metal smelting and refining industry (SS). (2) The low-carbon scenario is the most suitable development path for both subsectors. Under this pathway, the likelihood of MS and SS reaching their targets on time increases to 100 % and 87.4 %, respectively. MS likely peaked in 2013, with a peak at 28 Mt. SS is projected to peak in carbon emissions by 2025, with the highest probability of peaking between 417.6 Mt and 424.5 Mt. If no fluctuations will takes place during the implementation of low-carbon policies, then the peak would occur at 423.9 Mt (3) In this pathway, the industrial value added and energy intensity have the greatest influence on the probability of missing the deadline. This study enriches prediction methods for CO2 emissions and offers guidance to the Chinese nonferrous metal industry for effectively achieving the peak carbon target.

Dynamic evolution characteristics and hazard assessment of compound drought/waterlogging and low temperature events for maize

Hazard assessment is fundamental in the field of disaster risk management. With the increase in global warming, compound water and temperature events have become more frequent. Current research lacks risk assessments of low temperatures and their compound events, necessitating relevant hazard assessment work to improve the accuracy and diversity of maize disaster prevention and mitigation strategies. This study comparatively analyzed the dynamic evolution characteristics and hazards of compound drought/waterlogging and low temperature events (CDLEs and CWLEs) for maize in the Songliao Plain during different growth periods from 1981 to 2020. First, composite drought/waterlogging and low temperature magnitude indices (CDLMI and CWLMI) were constructed to quantify the intensity of CDLEs and CWLEs by fitting non-exceedance probabilities. Next, static and dynamic hazard assessment models were developed by fitting probability density and cumulative probability density curves to CDLMI and CWLMI. The results showed that the correlations between SPRI and LTI across different decades were mainly negative during the three growth periods. The hazard ratings for both CDLEs and CWLEs were relatively high in the northern part of the study area, consistent with the higher occurrence, duration, and severity of both CDLEs and CWLEs at higher latitudes. Relative to 2001–2010, the center of gravity of hazard shifted southward for CDLEs and northward for CWLEs in 2011–2020. The mean duration, frequency, and hazard were generally higher for CWLEs, but CDLEs were associated with more severe maize yield reductions. This study provides new insights into compound disaster risk assessment, and the research methodology can be generalized to other agricultural growing areas to promote sustainable development of agricultural systems and food security.

Ecological carrying capacity assessment incorporating ecosystem service flows

Ecological carrying capacity focuses on the limits of human development, serving as a policy instrument for guiding regional sustainable development. Regional space exhibits openness and dynamics. Nonetheless, ecological carrying capacity assessments seldom account for the potential influence of dynamic elements. The endeavor to integrate ecosystem service flows into ecological carrying capacity assessment represents an innovative approach to address this issue. This paper reviews multiple methods of assessing ecological carrying capacity and highlights the deficiencies in representing dynamic elements. Subsequently, the research progress in ecosystem service flows is examined, encompassing connotations, features, and models. Based on common theories, intermediary linkages, and the impact of incorporating spatiotemporal dynamics, the relationship between them is analyzed. The advantages of ecosystem service flows are also elucidated, which provide explicit spatial information and integrate biophysical processes when representing dynamic elements. The framework for ecological carrying capacity assessment incorporating ecosystem service flows comprises five steps: key theory selection, objectives and scope establishment, identification of supply and demand matching and assessment of flow utility, ecosystem service flow analysis, and ecological carrying capacity assessment. In the future, the research will focus on conducting quantitative pilot projects in typical regions, removing barriers to ecosystem service flows, and developing a dynamic ecological carrying capacity assessment model that considers multiple factors.

The effects of interactionist versus interventionist dynamic assessment models on Iranian EFL learners’ speaking sub-skills: a mixed-method study

Dynamic assessment has been proven to effectively promote EFL learners' speaking proficiency, but its implementation in teaching speaking skills has been limited. One of the main reasons is that, thus far, very few studies have scrutinized the impacts of its two main models, interactionist and interventionist, on the speaking sub-skills of EFL learners. Instead of examining speaking as a general skill, this research focused on four speaking sub-skills, including grammatical range and accuracy, vocabulary, fluency, and pronunciation, with a concurrent experimental mixed-method design. To this aim, 30 undergraduate students from the Islamic Azad University, North Tehran Branch, were recruited through convenience sampling and participated in both phases. The quantitative data were collected from participants' pre-and post-test scores in the IELTS speaking module, and qualitative data consisted of the transcribed recordings of the intervention sessions. The integration of the quantitative and qualitative results revealed that while both models positively affected EFL learners' speaking proficiency, they differed in the extent and mechanisms of their impacts. The interactionist DA effectively improved grammatical range and accuracy, pronunciation, and vocabulary depth, and the interventionist DA enhanced fluency and vocabulary breadth more efficiently. The findings dissect the differential effects of DA models in one-to-one speaking lessons, offering practical insights for ELT practitioners and stakeholders.

Integrated SEAWAT model and GALDIT method for dynamic vulnerability assessment of coastal aquifer to seawater intrusion

Seawater intrusion (SI) has become a global issue exacerbated by intense anthropogenic activities and climate change. It is imperative to seek a synergistic strategy to reconcile environmental and economic benefits in the coastal regions. However, the intricate SI process and data scarcity present formidable challenges in dynamically assessing the coastal groundwater vulnerability. To address the challenge, this study proposed a novel framework that integrates the existing vulnerability assessment method (GALDIT) and variable-density groundwater model (SEAWAT). The future scenarios from 2019 to 2050 were investigated monthly under climate change (SSP1–2.6, SSP2–4.5, SSP3–7.0 and SSP5–8.5) and human activities (80 % and 50 % of current groundwater abstraction) in Longkou city, China, a typical coastal region subject to extensive SI, compared with the status quo in 2018. Results indicated that by 2050, the high vulnerability area, is in a narrow buffer within 1.2 km from the shoreline and exhibits minor changes while the salt concentration here increased by about 2700 mg/L compared with the current situation. The moderate vulnerability zone expands by about 30 km2, and the low vulnerable area decreases proportionally. The groundwater over-abstraction is identified as a more critical factor compared to the regional precipitation under climate change. When groundwater abstraction is reduced to 80 % of the current scale, the expansion rate of the moderate-vulnerable area slows down significantly, with an expansion area of only 18 km2 by 2050. Further reducing groundwater abstraction to 50 % of the current scale shifts the evolution trend of the medium-vulnerable area from expansion to contraction, with the area shrinking by about 11 km2 by 2050. The integrated vulnerability assessment framework can be applied not only in the similar coastal regions but also provides insights into other natural hazards.

Greenhouse gas emissions benefits of the lightweight vehicle fleet in China: A dynamic fleet perspective

Lightweighting is believed to be a silver bullet to reduce greenhouse gas (GHG) emissions related to the road transportation. However, the fleet-scale and long-term GHG emissions estimation on the light-duty passenger vehicle (LDPV) fleet in China is still underexplored. A dynamic fleet-based life cycle assessment (LCA) model is developed to predict the annual GHG emissions attributable to the lightweight LDPV fleet in China at provincial level. With the most aggressive implementation of lightweighting, the cumulative mitigation potential of lightweight LDPV fleet from 2021 to 2050 is 0.72 Gt CO2 eq and 0.55 Gt CO2 eq using high-strength steel (AHSS) and aluminium (Al), respectively. Sooner implementation brings a higher cumulative reduction in GHG emissions. Delaying the implementation by five years would sacrifice 0.16 Gt CO2 eq ∼0.2 Gt CO2 eq cumulative reduction, and the loss would increase to 0.31 Gt CO2 eq ∼0.41 Gt CO2 eq when postpone the lightweighting by ten years.

Estimation of the Ecosystem Service Value of the Yellow River Delta-Laizhou Bay Coastal Zone Considering Regional Differences and Social Development.

With economic and societal development, the ecological environment of the Yellow River Delta-Laizhou Bay coastal zone has been seriously damaged. Exploring the changes in land use and ecosystem service value (ESV) is essential to ecological construction of the region. The random forest classification method was used for land cover interpretation of the four periods of remote sensing images in the study area from 1990 to 2020. Newly calculated regional difference coefficients and social development coefficients were used to construct a dynamic ESV assessment model and to study its changes from overall and sea‒land gradient perspectives. The results showed that construction land, salt pans, aquaculture ponds, and inland water masses expanded rapidly, while cropland, tidal flats, and shallow waters shrank sharply over the past 30 years. The ESV in the study area has continued to decrease from 34.47 billion yuan in 1990 to 25.23 billion yuan in 2020, a total decrease of 9.23 billion yuan. This is mostly due to the encroachment of construction land, salt pans, and aquaculture ponds, and the flow of ecosystem services from high-value land cover types (tidal flats, herbaceous wetlands, and cropland) to medium- and low-value land cover types. Moreover, the land cover transfer and ESVs exhibited a decreasing trend from sea to land, with significant sea-land gradient differences. Land conversion is most common in the 0-15 km coastal zone, mainly from natural wetlands to artificial wetlands, where the ESV also decreases rapidly. Considering the regional differences and social development in this paper, the ESV of small-scale areas can be reasonably evaluated to explore the characteristics and causes of changes in land use and ESVs, which can provide an important reference for ecological protection and land use management in the region.

Air pollution removal with urban greenery – Introducing the Vegetation Impact Dynamic Assessment model (VIDA)

Urban greenery is identified as a potential tool in air pollution mitigation. However, the impact is still debated. This paper introduces the innovative VIDA (Vegetation Impact Dynamic Assessment) model, specifically designed to quantify air pollution removal through deposition on vegetation. The VIDA model offers an advanced representation of vegetation that could be integrated into urban air quality dispersion models in the future. Furthermore, the model serves as a valuable tool for exploring the intricate interactions among deposition, resuspension, and wash-off processes, as well as understanding how meteorological conditions and various leaf traits influence these processes.The current version of the model focuses on particulate matter (PM) and encompasses a range of processes, including deposition on vegetation surfaces, encapsulation within the waxy cuticle, wind-driven resuspension, and wash-off. Additionally, the model takes into consideration dynamic changes in PM concentrations on the leaf surface over time, incorporating factors such as PM size fractions, meteorological conditions, and leaf characteristics. This comprehensive approach allows for the evaluation of various species or species groups based on their distinct traits. The VIDA model effectively reproduces measured data, yet continued evaluation remains crucial as new data emerges. Notably, challenges were encountered due to data scarcity and the absence of standardized methods for characterizing vegetation traits. Addressing these challenges and refining the representation of wash-off process will enhance the VIDA model's utility in predicting the dynamic relationship between vegetation and air quality.The introduction of VIDA provides a significant advancement in modelling air pollution removal by deposition to vegetation at a relevant local scale and enables inclusion of urban greenery as tool in urban planning for air pollution mitigation.

Review of Integrated Library Planning: A New Model for Strategic and Dynamic Planning, Management, and Assessment

This is a review of Integrated Library Planning: A New Model for Strategic and Dynamic Planning, Management, and Assessment by Myka Kennedy Stephens. Chicago: Association of College and Research Libraries. 160 pp. ISBN 978-0-8389-3937-6 $62

The construction of a dynamic assessment model of reading ability in secondary school students' English classroom

Secondary school students' reading ability in English classroom is an important ability for secondary school students' English learning, and it is also highly valued by teachers, parents as well as students. Regarding the English proficiency test, the assessment of students' English reading ability is necessary. Based on this, this paper constructs a dynamic assessment model of secondary school students' reading ability in the English classroom, and through the evaluation results of the implementation of this model in secondary school students' English reading teaching, it can be seen that the dynamic assessment model can help students to master reading strategies, significantly improve their reading performance, and have a good effect of intermediary intervention.

Integrated Library Planning: A New Model for Strategic and Dynamic Planning, Management and Assessment, Myka Kennedy Stephens, Association of College and Research Libraries Publications, 2023, Softcover, 160 pages, $62.00.

Integrated Library Planning: A New Model for Strategic and Dynamic Planning, Management and Assessment, Myka Kennedy Stephens, Association of College and Research Libraries Publications, 2023, Softcover, 160 pages, $62.00.

Dynamic Reliability Assessment Model for IoT-Enabled Smart Offshore Wind Farm

Dynamic Reliability Assessment Model for IoT-Enabled Smart Offshore Wind Farm

Virtualized Protection, Automation, and Control in Electrical Substations: An Open-Source Dynamic Cost-Benefit Assessment Model

Virtualized Protection, Automation, and Control in Electrical Substations: An Open-Source Dynamic Cost-Benefit Assessment Model

Optimization study of a dynamic assessment model of physical fitness for youth basketball training

Abstract Physical fitness assessment is of great significance for the design and adjustment of youth basketball training, and talent selection and evaluation of training teams. In this paper, a dynamic assessment model of physical fitness and health is designed, and a convolutional neural network and autoencoder are used to achieve feature learning of raw body side data. According to the learning results, the Gaussian mixture model is selected for physical fitness assessment, and the quantitative evaluation method of physical fitness is established based on the parameter-solving results of the EM algorithm. The ablation experiment demonstrates that the model in this paper has a low feature loss and excellent convergence, and the mAP value is 89.12%, which is the most accurate performance. The comprehensive accuracy of the assessment reaches 97.5%, indicating that the assessment performance of the dynamic assessment model of physical fitness and health proposed in this paper is better and can provide help for youth basketball training.