Damage Costs Research Articles

Incorporating seismic risk assessment into the determination of the optimal route for gas pipelines

ABSTRACT Earthquake-induced damage to gas pipelines can have severe economic, social, and environmental consequences. To mitigate these risks, one effective way is to carefully design the route of gas pipelines, considering the seismic hazard of the region. This paper proposes a methodology that incorporates seismic risk assessment into the process of designing gas pipeline routes. Conventional gas pipeline design methods consider only minimum distances from faults and fail to account for seismic potential. The methodology is applied to three gas pipeline routing problems in the high seismic region of southern Iran. Seismic risk is evaluated using the HAZUS method, and routing is performed through a GIS-based approach. Results are compared with conventional approaches in terms of length, seismic risks, and damage costs, showing the proposed method’s effectiveness in reducing immediate consequences like leaks and breaks in gas transportation. The proposed method reduces seismic damage by 3 to 68% for routing problems.

Uncertainty over uncertainty in environmental policy adoption: Bayesian learning of unpredictable socioeconomic costs

The socioeconomic impact of pollution naturally comes with uncertainty due to, e.g., current new technological developments in emissions' abatement or demographic changes. On top of that, the trend of the future costs of the environmental damage is unknown: Will global warming dominate or technological advancements prevail? The truth is that we do not know which scenario will be realised and the scientific debate is still open. This paper captures those two layers of uncertainty by developing a real-options-like model in which a decision maker aims at adopting a once-and-for-all costly reduction in the current emissions rate, when the stochastic dynamics of the socioeconomic costs of pollution are subject to Brownian shocks and the drift is an unobservable random variable. By keeping track of the actual evolution of the costs, the decision maker is able to learn the unknown drift and to form a posterior dynamic belief of its true value. The resulting decision maker's timing problem boils down to a truly two-dimensional optimal stopping problem which we address via probabilistic free-boundary methods and a state-space transformation. We completely characterise the solution by showing that the optimal timing for implementing the emissions reduction policy is the first time that the learning process has become “decisive” enough; that is, when it exceeds a time-dependent percentage. This is given in terms of an endogenously determined threshold function, which solves uniquely a nonlinear integral equation. We numerically illustrate our results, discuss the implications of the optimal policy and also perform comparative statics to understand the role of the relevant model's parameters in the optimal policy.

What is known, unknown, and needed to be known about damage caused by wild pigs

AbstractDamage assessments provide evidence for initiating and evaluating management programs that protect natural resources and human livelihoods against invasive species. Wild pigs (Sus scrofa) cause extensive damage in their native and non-native ranges, but the extent of current damage and efficacy of management of the damage (i.e., population control of wild pigs, exclusion fencing, etc.) remains poorly described. We conducted a systematic review of physical damage caused by wild pigs to summarize what is known and identify knowledge gaps for damage assessment. Wild pig damage assessments have been overwhelmingly qualitative (84% of studies) and measured differently across studies, which prevents the determination of typical damage amounts to a particular resource and comparison across studies. Key priorities going forward are to standardize damage assessments quantitatively and measure population density (or index of such) of wild pigs concurrently with damage assessments to determine the relationship between damage and population levels. We provide a framework for inferring damage in new areas and assessing the benefits of management—to evaluate and optimize landscape-scale management programs. Overall, we recommend future studies strive for: (1) report the amount of damages in a standardized fashion (e.g., area damaged/area surveyed), (2) evaluate and report the amount of damage relative to the density of wild pigs, and (3) when reporting economic costs of damages incurred and management actions, describe the economic valuation method used along with the year of reference for the valuation. Capturing these elements are necessary steps to predict the benefits of management for an area with particular profile of resources and wild pig density, even in areas where damage assessments are not available. Meeting these criteria with allow for more generalizable results that can inform managers across the nearly global distribution of wild pigs.

Climate Change-Related Disaster Risk Mitigation through Innovative Insurance Mechanism: A System Dynamics Model Application for a Case Study in Latvia

This study explores how the System Dynamics modeling approach can help deal with the problem of conventional insurance mechanisms by studying the feedback loops governing complex systems connected to the disaster insurance mechanism. Instead of addressing the disaster’s underlying risk, the traditional disaster insurance strategy largely focuses on providing financial security for asset recovery after a disaster. This constraint becomes especially concerning as the threat of climate-related disasters grows since it may result in rising long-term damage expenditures. A new insurance mechanism is suggested as a solution to this problem to lower damage costs while safeguarding insured assets and luring new assets to be protected. A local case study utilizing a System Dynamics stock and flow model is created and validated by examining the model’s structure, sensitivity analysis, and extreme value test. The results of the case study performed on a city in Latvia highlight the significance of effective disaster risk reduction strategies applied within the innovative insurance mechanism in lowering overall disaster costs. The logical coherence seen throughout the analysis of simulated scenario results strengthens the established model’s plausibility. The case study’s findings support the innovative insurance mechanism’s dynamic hypothesis and show the main influencing factors on the dynamics within the proposed innovative insurance mechanism. The information this study can help insurance firms, policy planners, and disaster risk managers make decisions that will benefit local communities and other stakeholders regarding climate-related disaster risk mitigation.

Agricultural damage following the recent expansion of wild boar (Sus scrofa)—farmer perceptions and preconditions

The wild boar (Sus scrofa) population has recently increased in Fennoscandia, leading to increasing interactions with humans, e.g. in the form of hunting opportunities or property damages. These experiences may shape the attitudes towards wild boars and affect their population management. We studied attitudes among 165 farmers towards wild boar by means of survey data. We also made preliminary estimates of wild boar damage costs in Finland. Our analysis revealed three attitude groups among farmers, emphasizing various perspectives: “hunting resource”, “pest-of-concern”, and “ambivalent”. The benefits, costs, feelings, and perceived wild boar population development partly explained the division. The direct annual damage costs in southeast Finland were broadly estimated to be circa 990,000€ and mitigation costs circa 350,000€. Reconciling differing opinions and goals into a widely accepted management strategy is a key precondition for sustainable coexistence. While the level of economic loss is so far not substantial, monitoring of crop damages is vital. Our results provide a valuable baseline for future evaluations, as the wild boar population is expected to grow.

Health risk management: The ASL BT experience

ASL BT, born from the merger of three company branches, now eighteen years old, has a transversal departmental organization. In the Staff Department, there is the Clinical Risk Management Unit, which carries out prospective planning activities in the medium/long term. The systematic monitoring of all incident reporting systems, as well as requests for compensation and the economic aspects relating to direct costs (for damages related to adverse events) and indirect costs (for disputes), allow the UO to plan the prevention activities. This prevents the health risk and the recurrence of events, which in various ways have generated "losses" for the patient, the Company and the professionals. The establishment of a clinical risk network made up of representatives and facilitators, the sharing of all the proposed procedures and protocols and above all, the training aimed at increasing the culture of safety and awareness among all employees Healthcare, have a crucial role.

Inventory Model for Deteriorating Pharmaceutical Items with Linear Demand Rate

Good management of goods is needed so that the inventory activities of a business can run smoothly as the part of supply chain management which aims to monitor the flow of stock of goods from the purchasing process, and storage to the point of sale. In terms of inventory or supplies of pharmaceutical goods, conditions such as shortages or stockouts must also be considered which are a matter of control, management, and security. In this study, an inventory model is formulated with deterioration or damage to pharmaceutical goods that occurs due to the length of time when the goods are stored with a linear demand level. In the optimal solution, the inventory time occurs when it reaches the zero point (t1) of 0.34 and the cycle length (T1) of 0.83 with an average minimum total cost (TC) of $445.25 per cycle which is completed by WolframAlpha software. Sensitivity analysis changes the value results in the value of (TC) which that increases for all parameters. In increasing the linear function variables (a and b), it produces t1 and T1 stable values. An increase in the cost of each item damage (DC) and constant damage rate (theta) produces a t1 stable value, but the value of T1 increases. The increase in storage costs (h) results in a decrease in the value of t1 and T1. An increase in the cost of shortages (s) results in an increase in the value of t1 and a decrease in the value of T1.

Exploring the influence of density-dependence and weather on the spatial and temporal variation in common vole (Microtus arvalis) abundance in Castilla y León, NW Spain.

The common vole has invaded the agroecosystems of northwestern Spain, where outbreaks cause important crop damage and management costs. Little is yet known about the factors causing or modulating vole fluctuations. Here, we used 11 years of vole abundance monitoring data in 40 sites to study density-dependence and weather influence on vole dynamics. Our objective was to identify the population dynamics structure and determine whether there is direct or delayed density-dependence. An evaluation of climatic variables followed, to determine whether they influenced vole population peaks. First- and second-order outbreak dynamics were detected at 7 and 33 study sites, respectively, together with second-order variability in periodicity (2-3 to 4-5-year cycles). Vole population growth was explained by previous year abundance (mainly numbers in summer and spring) at 21 of the sites (52.5%), by weather variables at 11 sites (27.5%; precipitation or temperature in six and five sites, respectively), and by a combination of previous abundance and weather variables in eight sites (20%). We detected variability in vole spatiotemporal abundance dynamics, which differs in cyclicity and period. We also found regional variation in the relative importance of previous abundances and weather as factors modulating vole fluctuations. Most vole populations were cyclical, with variable periodicity across the region. Our study is a first step towards the development of predictive modeling, by disclosing relevant factors that might trigger vole outbreaks. It improves decision-making processes within integrated management dealing with mitigation of the agricultural impacts caused by voles. © 2023 Society of Chemical Industry.

Estimating intraevent and interevent variability and spatial correlation of tropical cyclone wind fields and their use for the risk assessment of a portfolio of structures

Often the tropical cyclone (TC) wind hazard assessment requires the use of the TC wind field model. While theoretical models typically predict the observed wind field well, there can be a spatially varying residual correlation that impacts the damage assessment of communities or groups of structures. In this study, we focus on developing spatial correlation models and assessing the intraevent and interevent variability of the TC wind field using the H*Wind dataset and two widely used wind field models - the vertically averaged boundary layer slab model and the gradient wind field-based model. Our models and the statistics of the interevent and intraevent variability are integrated into a framework for evaluating the wind-induced damage of a portfolio of structures. The framework includes simulating TC tracks and wind fields, considering interevent and intraevent variabilities, and assessing peak linear elastic and nonlinear responses. Numerical examples illustrating the use of this framework are provided, indicating that realistic spatial correlation of the TC wind field needs to be considered to assess the correlation coefficient of the damage factor of a pair of spatially distributed structures and the probability distribution of the damage cost of a portfolio of structures.

A diet-related health prompt with the Swiss Food Pyramid as a nudge to reduce meat consumption

High meat consumption in Western societies is a major contributor to climate change, environmental damage, and health costs. One way to reduce meat consumption is through nudges in staff restaurants. Though previous studies have shown that nudges can influence consumer choices, there is a lack of comparative studies of the different types of nudges in the context of staff restaurants. The present study thus aimed to compare, individually and in combination, the effectiveness of a written prompt, a visual prompt (the Swiss Food Pyramid), and a dynamic social norm in encouraging consumers to more frequently choose meatless menu options. A 1 × 8 between-subjects design was applied, and an online choice experiment (n = 2198) was conducted, where the participants chose 15 times between a meat menu, a vegetarian menu, and a salad buffet. The participants who encountered the written prompt combined with the visual prompt chose the meatless option more often than those in the control condition. The written prompt contributed most to the intervention’s effectiveness. Although the effect size was small, this intervention combination is worth testing in the field, as it proved effective for all participants regardless of their psychological characteristics.

Cover crop impacts on nitrogen losses and environmental damage cost

There is a need to explore management practices that reduce nitrate (NO3-) leaching and aid in meeting current greenhouse gas reduction goals. Tile drainage involves using perforated pipes to remove excess subsurface water from agricultural fields, also removing nutrients. The inclusion of cover crops in tile-drained systems in the Midwest has been shown to reduce NO3- losses and is potentially a strategy to mitigate soil nitrous oxide (N2O) emissions. The objectives of this research were to 1) evaluate cumulative soil NO3- and soil N2O losses with and without the inclusion of cover crops in a corn-soybean rotation on a tile-drained landscape and; 2) assess the environmental damage cost (EDC) of N losses with and without the inclusion of cover crops in a corn-soybean rotation on a tile-drained landscape. Corn (Zea mays L.) was grown in 2017, and soybean (Glycine max L.) in 2018. The cover crop used in this experiment was a 92% cereal rye (Secale cereal L.) and 8% daikon radish (Raphanus sativus L.) blend. Treatments included cover crop inclusion, no cover crop inclusion, and a zero control, which did not include cover crops or receive N fertilization. Each treatment was replicated three times in individually tile-drained plots established in Lexington, IL during the 2017 and 2018 growing seasons. In 2017, cover crop inclusion led to a reduction in NO3– losses of over 50% when compared to the no cover and zero control. In 2018, total N losses were identical; however, there was an increase in soil N2O emissions across all treatments compared to 2017. Despite the apparent tradeoff between N loss pathways in 2018, the overall EDC was reduced primarily because of the reduction in NO3- loss in the presence of cover crops. The results of this study indicated that the inclusion of a cover crop resulted in a sizeable reduction in N loss during the corn year that equated to a 64% reduction in EDC across a two-year crop rotation.

Некоторые особенности решения имущественных и наследственных споров в горских словесных судах Кубанской и Терской областей в 1871–1918 гг.

The article studies some features of solving property and inheritance disputes in the mountain word courts of the Kuban and Terek regions in 1871–1918. The specifics of their activities are studied on the records and statistical materials of the Yekaterinodar, Maikop and Balalpashinsky mountain word courts (MWC) in the Kuban region and Khasav-Yurtovsky, Groznensky, Vedensky, Shatoevsky, Nalchik, Nazranovsky and in the Terek region. The models of decision-making on typologically similar disputes and conflicts and their forms of documenting them were characterized common for all MWC; the specifics of their traditional institutions of socio-normative culture and local peculiarities of dispute and conflict resolution were revealed. On the basis of the analysis of law enforcement practice of the mountain verbal courts, the list of types of civil disputes that they deal with is proposed. Interim measures applied by the verbal courts to enforce court decisions (arrest of the defendant’s property, sale of the debtor’s property from public tenders and auctions, etc.) are described. The grounds for termination of proceedings in civil cases have been identified. It was determined that pre-trial reconciliation of conflicting parties in civil and inheritance disputes was documented in the form of “amicable deals “amicable tales “amicable tales”. It was found that the final amount of material compensation (the main form of liability in the resolution of this category of disputes by the MWC) almost always consisted of two components: the cost of damage and the costs associated with the resolution of the dispute (the sum of all losses incurred by the injured party). The conclusion is made that among the positive effects of such activity was the consideration of regional and ethnic traditions in resolving disputes and conflicts, while the negative ones were the slowness of the MWC in making decisions, accumulation of unresolved cases, etc.

Responsabilidade por produtos defeituosos na era da IA — Proposta de uma solução de “duas vias”

In 1985 the Council of the European Communities adopted the Directive 85/374/EEC to harmonise product liability within Europe. In 2024, this directive will most likely be replaced by a new Product Liability Directive designed to reflect the technical developments of the last 40 years. The new Directive contains some significant changes. However, regarding the overarching concept of product liability, it remains faithful to the old Directive: Manufacturers are still not liable for all damage caused by their products, but only for damage caused by a “defect” in a product. This defect-based approach is problematic. When it comes to new digital technologies, especially Artificial Intelligence, it is difficult for courts to assess a product’s defectiveness. Moreover, in many cases, the defect-based approach is insufficient to provide liability solutions that are both efficient and fair. This paper seeks to lay the foundations for a more comprehensive reform: The current product liability for defective products should be complemented by a second “track” of product liability. In the case of particularly dangerous products, such as autonomous cars and medical devices, manufacturers should compensate victims regardless of whether their products are defective or not. Such “truly” strict liability could partially relieve courts of the burden of assessing a product’s defectiveness and would lead to fair and efficient prevention and distribution of damages. Damage costs would be allocated to manufacturers as the cheapest cost avoiders. In addition, the advantages and disadvantages of dangerous products would be more evenly distributed among manufacturers, users, consumers and “innocent bystanders”. However, to avoid over-deterrence and stifling of innovations strict liability should be limited to particularly dangerous products. Legislators should introduce a general clause of truly strict liability, which would allow courts to assess whether a product is particularly dangerous or not. A general clause is preferable to a list of particularly dangerous products because it would provide for the flexibility needed to deal with rapidly developing technologies.

Optimization of hydrological calculations of surface and drainage water runoff treatment systems

Objective: to develop a method for determining the optimal hydrological characteristics of treatment systems for polluted surface and drainage water. Methods: Pollutant balance equation is applied. For comparison, the technique of the Vodgeo Research Institute was used. The costs of cleaning and environmental damage from pollution of watercourses under various options of water content of the year and parameters of treatment facilities were investigated. The types of pollutants (suspended materials and petroleum products) and the effluent separation factor in the separation chambers were selected as the main parameters. Results: the method of optimization calculations of hydrological characteristics of surface and drainage water treatment systems has been developed, considering the probability of runoff in high waters and floodwaters, costs of construction and operation of treatment facilities and damage from watercourse pollution. Optimization calculations of several options for treatment of melt, rain and drainage runoff are performed as an example. Practical significance: the method of optimization calculations of wastewater will allow more substantiated and more accurate determination of the required degree of wastewater treatment, productivity and parameters of treatment facilities, and in some cases to reduce the degree of pollution of watercourses.

Flood Risk Management in the Upper Caroni River Basin

Flooding is more common than earthquakes and hurricanes, leaving casualties, infrastructure damage, and economic losses in its wake. The October 2018 floods in Trinidad heightened public concern about the ability of public authorities to manage floods. This study investigates the impact of five combinations of detention basins and embankments on the cost of physical damage to residential buildings in the Caroni River Basin. Further comparison of the maximum flood depth before and after the implementation of structural mitigation combinations was conducted for typical design return periods of 5, 25, 50, and 100 years. The results showed that strategically introducing detention ponds along the Aripo and Guanapo Rivers caused the greatest reduction in flood damage cost (12.86%). Evidence also suggests that attenuation of flood waters by detention ponds is a better alternative to flood protection by embankment-only options

A Novel Predictive Analysis and Classification of Land Subsidence Vulnerability Mapping based on GIS using Hybrid Optimized Machine Learning Techniques and Computer Vision

Land subsidence is a natural disaster caused by the extraction of the earth's material strength on the surface that causes the earth's surface to settle and sink. Land subsidence can also result in significant financial losses since it causes structural damage and expensive maintenance costs for roads, trains, barriers, pipelines, ground water, oil, natural gas, mines, and buildings. The Geographic Information System (GIS) and Google Earth Platform (GEP) can be used to map this land subsidence. This provides a comprehensive view of land pattern subsidence and its interactions with other geographical elements. It applies to both progressive subsidence caused by fluid extraction (groundwater, oil, or natural gas) and rapid surface subsidence caused by the collapse of an underground mine. Risk mitigation is the most effective way to deal with the experimental model. This research study focuses on the use of Predictive Data Analysis (PDA), a powerful environment in data analytics that provides a set of tools that make it easier to evaluate optimal models. The proposed model makes use of a dataset that includes specific land subsidence circumstances as input. The prediction result is achieved using a hybrid machine learning technique that combines Stochastic Gradient Descent (SGD) with Long Short-Term Memory (LSTM) and is compared to K-Nearest Neighbor (KNN), Generative Adversarial Network (GAN), and Artificial Neural Network (ANN). The proposed system employs LSTM and SGD as optimizers, resulting in a hybrid model that improves accuracy. Among the four algorithms investigated the LSTM-SGD network has the highest accuracy (97%), followed by KNN (96%), GAN (90%), and ANN (89%). Due to their ability to capture complicated nonlinear correlations in data and manage temporal dependencies, optimized hybrid ML models LSTM-SGD and KNN models appear to be particularly well-suited for land subsidence prediction.

ОЦІНКА ЕКОЛОГІЧНИХ ЗБИТКІВ ВІД ВИКИДІВ ТРАНСПОРТНО-ЛОГІСТИЧНИХ ЗАСОБІВ В КОНТЕКСТІ СТАЛОГО РОЗВИТКУ

This article thoroughly examines the environmental damage caused by emis-sions from transportation and logistics vehicles in Odesa, within the framework of sustai-nable development objectives. It presents a detailed analysis of the main pollutants emitted by vehicles using gasoline, diesel, and liquefied petroleum gas, underscoring the significant contribution these emissions make to both local and global environmental issues. The study highlights the substantial volumes of greenhouse gases produced and the current lack of economic regulatory mechanisms to manage them effectively. Comparative analysis of global environmental tax rates on CO2 demonstrates Ukraine's position as having the lowest rate, suggesting inadequate regulatory measures. Through methodical calculations, it was deter-mined that Odesa's total CO2 emissions for the year 2022 amounted to 1,089,421.9 tons. This resulted in an estimated environmental damage cost of $893,326 USD, which remains uncompensated due to regulatory shortcomings.The findings emphasize the necessity of integrating such emission data into environ-mental damage assessments and implementing robust economic instruments to regulate emissions. Additionally, the paper explores strategic approaches to enhance emission regu-lations, including the potential introduction of more stringent environmental taxes or cap-and-trade systems, and suggests ways to align these with international environmental stan-dards. The broader implications of such regulatory adjustments are discussed, particularly their role in facilitating sustainable urban development. This comprehensive analysis aims to provide policymakers and urban planners with an understanding of the environmental stakes involved and practical steps towards achieving sustainability in urban transportation systems. By comparing Ukraine’s policies to international standards, the research offers valuable insights into potential reforms that can drive the sustainable future for Ukraine. Keywords: transportation and logistics vehicles, environmental damage, sustainable development, greenhouse gases, emission regulation, environmental tax.

Performance of graphene oxide as a water-repellent coating nanomaterial to extend the service life of concrete structures

Surface treatments help to protect the built heritage against damage (environmental, accidental, etc.), reducing repair and restitution costs and increasing the useful life of building materials. The use of nanomaterials is currently the most important field of research in surface treatment technology for the preservation of building materials and, more specifically, to improve their durability and prevent their deterioration, extending their useful life. This paper studies the influence of a graphene oxide (GO) suspension as a surface treatment on the properties of concrete. The results indicate that, at best, surface treatment with GO can decrease both the water absorption and capillary absorption of concrete by about 15 %. The increase in the amount of GO deposited as a surface treatment leads to a further reduction in concrete water absorption. It is shown that, at best, GO coating also reduces water penetration at low and high pressures by approximately 20 % and 60 %, respectively. In addition, scanning electron microscopy analysis shows that GO surface treatment facilitates the hydration process and densifies the concrete microstructure. A simple aqueous suspension of GO is revealed as a tool with a high potential to protect concrete surfaces in a fast and cost-effective way, thanks to the easy application by spraying and the small amount of material needed to obtain great results.

Machine Learning Models to Identify Anomalies in the Production of Flat Glass

This work presents an innovative proposal for the prediction of defects in industrial glass refining processes. Although it is a complex process with several points that can cause defects, the current approach of specialists is only reactive, that is, they can only act after the damage has been caused. This study proposes the use of data collected from the industrial processes of a real company as a case study to create prediction models, in order to identify a possible failure before it occurs. The objective is to use multiple linear regression as a model and allow specialists to take preventive corrective measures, avoiding damage and reducing production costs.

Experimental Studies of a Universal Mathematical Model of Leakage Currents and Ground Currents Distribution on the Elements of HVPTL

In Kazakhstan, the main power transmission line with a line voltage of 500 kV, geographically runs through the whole of Republic from north to south. The high-voltage power line is of strategic importance. The failure of one support leads to a halt in the technological process of transporting electricity to entire regions of the country. In order to increase reliability and reduce operating costs, various modifications of diagnostics and monitoring systems for overhead power lines are being widely introduced in the CIS countries. Currently, the introduction of a complex of diagnostics of structural elements of the 500 kV HVPL has become particularly relevant, firstly, the cost of damage in accidents has increased significantly, and secondly, due to the long service life, the reliability of the power system has decreased. For the successful implementation of the diagnostic complex, an accurate representation of the processes occurring during the operation of the supports is necessary. For this purpose, a universal model of leakage currents and spreading currents along the elements of the overhead line supports was developed.