Management Scenarios Research Articles

Bridge Information Modeling (BrIM) aplicado na operação e manutenção de Obras de Arte Especiais (OAEs)

Abstract Studies have shown a worrisome condition as to the conservation of Civil Engineering Structures (CESs) in Brazilian highways. This situation mainly results from the lack of an efficient system for managing such structures, specifically during their operational stage, when periodic maintenance is required. As a solution, the Bridge Information Modeling (BrIM) has proven to be an efficient system for managing CESs, integrating different technologies into this process. The purpose of this paper is to assess how BrIM can contribute to improve the management procedures of these structures. The research methodology has been divided into two stages. The first one is the literature review detailing the management scenario of CESs in the country, as well as the analysis of the BrIM used as a tool to manage such structures in a general context. The second stage is a case study addressing the operational and maintenance process of CESs used by a highway concessionaire in an important Brazilian state. The analysis concluded that, although recent, the adoption of BrIM has been growing in several countries, and it can substantially contribute to improving the operational and maintenance stages of CESs.

Meta-learning Based Domain Generalization Framework for Fault Diagnosis With Gradient Aligning and Semantic Matching

Intelligent fault diagnosis models have demonstrated a superior performance in industrial prognostics health management scenarios. However, these models may struggle to generalize in complicated industrial environments, when encountering new working conditions and handling low-resource and heterogeneous data. To cope with the aforementioned issues, we focus on constructing a universal training framework with domain generalization technique that will encourage fault diagnosis model to generalize well in unseen working conditions. Firstly, a model-agnostic meta-learning based training framework called Meta-GENE is proposed for homogeneous and heterogeneous domain generalization. Secondly, a gradient aligning algorithm is introduced in meta-learning framework to learn domain-invariant strategy for robust prediction in unseen working conditions. Thirdly, a semantic matching technique is proposed for utilizing heterogeneous data to alleviate low-resource problem. Our method has yielded excellent performance on the PHM09 fault diagnosis dataset and achieved superior results on a set of generalization tasks across various working conditions.

Modelling plastic fluxes with INCA-macroplastics in the Imus catchment: impacts of long-term accumulation and extreme events

Plastic environmental pollution is threatening water resources, aquatic ecosystems, and human wellbeing but is still highly uncertain with global fluxes to sea of 0.4–13 Mt\\yr, and up to 517 Mt of mismanaged plastics on land. Catchment modelling tools are required to challenge current knowledge, simulate impacts of management initiatives, and complement global and observation-based studies. Here we present the first spatiotemporally explicit model for mismanaged plastic mobilization and transport from land to sea from the INtegrated CAtchment (INCA) family. INCA-Macroplastics encompasses all components of the catchment, is driven by available data (weather, population, solid waste) and enables calibration and validation against diverse observations (river monitoring, household surveys). INCA-Macroplastics was applied to the Imus River, Philippines, one of World’s most polluted rivers. Given large uncertainties on catchment plastic retention, two calibrations and two emission scenarios were developed to describe catchment plastic fluxes, residence time and stocks over 1990–2020. Plastic fluxes to the sea are highly variable over years and seasons (55–75% exported during the wet season) and have increased exponentially over 1990–2020 from 5–100 to 2000–15000 tons\\yr. INCA-Macroplastics is the first model handling plastic accumulation on land and highlights the importance of extreme flooding events in mobilizing and transporting legacy plastics. Model outputs explicitly show that current land plastic pollution can impact fluxes to the ocean for up to 30 years into the future. INCA-Macroplastics is useful to provide tailored recommendations for local monitoring, testing waste management scenarios and pointing towards future research avenues.

Assessment of the Potential Impacts of Climate Change on the Hydrology and Canola Yield Using the DRAINMOD Model

HighlightsTotal precipitation and average temperature are projected to increase in the Interlake region of Manitoba.DRAINMOD model results suggest that controlled drainage (CD) would significantly decrease subsurface drainage.Due to dry stress, canola yield is projected to decrease under free drainage (FD) and controlled drainage (CD).Simulation results suggest that capturing, storing, and reusing drainage water could be an adaptive and mitigative strategy for climate change impacts.Abstract.Climate change is a major concern for agricultural production regions like the Canadian Prairies. Therefore, understanding the hydrologic and crop yield response to climate change is important to developing adaptative and mitigative strategies. Downscaled climate model projections from two GCMs for historical (1981-2010), midcentury (2041-2070), and late-century (2071–2100) periods under three representative concentration pathways (RCP2.6, RCP4.5, and RCP 8.5) were used as climate inputs to drive a calibrated and validated DRAINMOD model under two water management scenarios: free drainage (FD) and controlled drainage (CD). Field data, including water table depth, was collected for two canola growing seasons at the PESAI (Prairies East Sustainable Agriculture Initiative) research site in Arborg, Manitoba, Canada. The model was calibrated and validated using the 2019 and 2020 water table depth. The projected changes in the climatic variables showed a slight increase in the mean annual precipitation and the mean temperature across the seasons. DRAINMOD simulation results suggest that CD would significantly decrease subsurface drainage, while water loss through evapotranspiration (ET) and surface runoff are projected to increase considerably under CD and FD. Furthermore, results showed that the relative canola yield would decrease under FD and CD. Stressor analysis showed that canola yield reduction was driven by dry stress due to the projected temperature rise, which outweighs the slight increase in precipitation. Simulation results suggest that the capture, storage, and reuse of drainage water could be an adaptive and mitigative strategy to address the predicted impacts. Keywords: Canola yield, Climate change, DRAINMOD model, Subsurface drainage.

Simulation modeling of forest plantation condition

The article substantiates the necessity of creating a simulation model of changes in the states of forest plantations. Such a model makes it possible to repeatedly conduct experiments on the object of study on changes in different parameters in order to predict the consequences and develop operational management scenarios to reduce the negative impact on its processes and objects. The use of structural analysis, synthesis and classification methods allowed us to identify the key objects of such an ecosystem and the processes that influence their germination, growth and death. The results obtained became the basis for the creation of a system dynamics model reflecting the nature of the behavior of the objects and processes under study. With the help of simulation modeling methods, a system of differential equations was created, which takes into account the quantitative instances of objects and the rate of their changes depending on external parameters. Based on this, a graphical model reflecting all aspects of the realization of such processes has been created.

Cadmium and lead flow analysis as a decisions support data for waste management

Striving for EU membership, the Republic of Serbia must adjust its waste management practices to comply with EU directives, including targets to reduce biodegradable waste disposal in landfills, as outlined in its Waste Management Program 2022?2031. Cadmium and lead, two highly toxic heavy metals, that are present in municipal solid waste, can pose high environmental and human health threats if not properly managed. The research evaluates how different technologies for biodegradable waste treatment influence the transformation of cadmium and lead flows through waste management systems. Hence, two waste management scenarios were modelled and developed for the Republic of Serbia, where the flows of cadmium and lead are monitored. The results indicate the differences between quantities and concentrations of cadmium and lead emitted in environmental media, thus confirming the various impacts of different waste technologies on achieving the vital goal of waste management ? protection of the human health and the environment. The research concludes the crucial role of the versatile approach, where the quality of waste management outputs is highlighted.

Construction and Application of Safety Management Scenarios at Construction Sites

With the rapid development of the construction industry, there have been an uncountable number of damages caused by safety accidents at construction sites. Traditional safety management methods are no longer able to meet the needs of production. This paper presents the concept of constructing safety management scenarios for construction engineering sites. Using a production base project as a research case, it analyzes the natural and human factors involved in constructing spatial–temporal scenarios at construction sites. By employing a spatial–temporal overlay method to analyze multiple safety assessment indicators, a spatial–temporal safety management scenario for the production base project is established. Subsequently, BIM and GIS technologies are applied to perform a spatial–temporal simulation of the construction site safety management scenario. This process delineates safety and hazard areas across different construction phases based on time and spatial dimensions, enabling a comprehensive safety assessment of the construction site of the production base project. The study offers a reference and guidance for improving the level of safety management at construction project sites.

Experience in calibrating the VISSIM microscopic simulation model for an unsignalized intersection in Pekanbaru, Indonesia

Traffic activity is unique and occurs throughout the region. All moving traffic movements cause a build up of vehicles when there are conflicts between vehicles and result in congestion, one of which is in the intersection area located on Jalan SM Amin, Pekanbaru. Traffic modelling can assist traffic management through accurate simulation results with field conditions based on driving behavior value VISSIM is a simulation tool used to simulate dynamic traffic flow conditions. The research has aim to modelling and calibrating driver behavior value based on traffic flow conditions at unsignalised intersections in Pekanbaru. This research uses simulation modelling with VISSIM as the modeler and GEH and MAPE as validation tools to choose which right model. Simulation process will used calibration process based on driving behavior value for the right model by trial and error method.. The result showed that simulation model based on default parameter of driving Behavior cannot represent for real traffic. Then changes in the combination of Driving Behaviour values affect the accuracy of model conditions with field conditions. The accuracy is measured using the reference volume of vehicles exiting the unsignalled intersection. Therefore, this research could be can assist in smoothing traffic flow model in Pekanbaru which more easily by using live traffic flow simulation that can be utilized for traffic intersection management scenarios.

Estimated impacts of forest restoration scenarios on smoke exposures among outdoor agricultural workers in California

As wildfires continue to worsen across western United States, forest managers are increasingly employing prescribed burns as a way to reduce excess fuels and future wildfire risk. While the ecological benefits of these fuel treatments are clear, little is known about the smoke exposure tradeoffs of using prescribed burns to mitigate wildfires, particularly among at-risk populations. Outdoor agricultural workers are a population at increased risk of smoke exposure because of their time spent outside and the physical demands of their work. Here, we assess the smoke exposure impacts among outdoor agricultural workers resulting from the implementation of six forest management scenarios proposed for a landscape in the Central Sierra, California. We leverage emissions estimates from LANDIS-II to model daily PM2.5 concentrations with the Hybrid Single Particle Lagrangian Integrated Trajectory Model (HYSPLIT) and link those to agricultural employment data from the Bureau of Labor Statistics. We find a u-shaped result, in that moderate amounts of prescribed burning result in the greatest reduction in total smoke exposure among outdoor agricultural workers, particularly during months of peak agricultural activity due to wildfire-specific smoke reductions. The reduction in total smoke exposure, relative to scenarios with the least amount of management, decreases as more prescribed burning is applied to the landscape due to the contributions of the fuel treatments themselves to overall smoke burden. The results of this analysis may contribute to preparedness efforts aimed at reducing smoke exposures among outdoor agricultural workers, while also informing forest management planning for this specific landscape.

XR4DRAMA a knowledge-based system for disaster management and media planning

Abstract In the previous two decades, Knowledge Graphs (KGs) have evolved, inspiring developers to build ever-more context-related KGs. Because of this development, Artificial Intelligence (AI) applications can now access open domain-specific information in a format that is both semantically rich and machine comprehensible. In this article, we introduce the XR4DRAMA framework. The KG of the XR4DRAMA framework can represent data for media preparation and disaster management. More specifically, the KG of the XR4DRAMA framework can represent information about: (a) Observations and Events (e.g., data collection of biometric sensors, information in photos and text messages), (b) Spatio-temporal (e.g., highlighted locations and timestamps), (c) Mitigation and response plans in crisis (e.g., first responder teams). In addition, we provide a mechanism that allows Points of Interest (POI) to be created or updated based on videos, photos, and text messages sent by users. For improved disaster management and media coverage of a location, POI serve as markers to journalists and first responders. A task creation mechanism is also provided for the disaster management scenario with the XR4DRAMA framework, which indicates to first responders and citizens what tasks need to be performed in case of an emergency. Finally, the XR4DRAMA framework has a danger zone creation mechanism. Danger zones are regions in a map that are considered as dangerous for citizens and first responders during a disaster management scenario and are annotated by a severity score. The last two mechanisms are based on a Decision Support System (DSS).

An individual-based model to predict the spatial distribution of northern pike, European perch and pikeperch from habitat use in a reservoir subject to water level fluctuations

Reservoirs are subject to artificial water level fluctuations leading to a degradation of the littoral habitats. This often results in reduced productivity and biological diversity, particularly for fish. The development of predictive tools of fish population dynamics linked to habitat characteristics can help to optimize management actions such as habitat restoration. We developed a spatially explicit individual-based model, the 3Plake model, which predicts the spatial distribution of three fish species, northern pike, European perch and pikeperch, over seasons and diel cycles according to their habitat use. The model was calibrated with an accurate description of habitat and high spatial and temporal resolution data of fish movements in a French reservoir. The model calibration is only based on a species-specific coefficient of habitat selectivity. It was chosen to (i) match the observed and simulated traveled hourly and daily distances and (ii) minimize a metric quantifying the distance between observed and simulated density maps. The 3Plake model correctly simulated the means of traveled distances and the species distributions along the year on the study reservoir. The minimal input required (HSI maps and maximum distance range) allows its easy implementation on other reservoirs and fish species. It could be used to assess the impact of habitat restoration or water level management scenarios on fish distribution.

Multi-Station Hydrological Modelling to Assess Groundwater Recharge of a Vast Semi-Arid Basin Considering the Problem of Lack of Data: A Case Study in Seybouse Basin, Algeria

Water resource management scenarios have become more crucial for arid to semi-arid regions. Their application prerequisites rigorous hydrological modelling approaches since data are usually exposed to uncertainties and inaccuracies. In this work, Soil Water Assessment Tool (SWAT), an open source semi-distributed, continuous-time, process-based physical hydrological model is used to model hydrological processes and eventually calculate groundwater recharge estimations in Seybouse basin, Northeast Algeria. The model uses estimated rainfall to calibrate the model with observed discharge from hydrometric stations. Model calibration and validation are performed over four hydrometric stations located in the basin. Uncertainty analysis and sensitivity analysis supported the calibration period. SUFI-2 algorithm is used for uncertainty estimations along with a global sensitivity analysis prior to calibration simulations. Simulated flood hydrographs showed generally good accuracy with few misfits on the peaks. The model obtained satisfactory and consistent calibration and validation results for which the Nash score varied from 0.5 to 0.7 for calibration and from −0.1 to 0.6 for validation and R2 from 0.6 to 0.7 for calibration and 0.03 to 0.8 for validation. Moreover, estimated water budget values show strong similarities with the observed values found in the literature. The present work shows that the rigorously calibrated and validated SWAT model can simulate hydrological processes as well as major high and low flows using estimated rainfall data.

Current Scenario of Solid Waste Management in Raju Colony, Balanagar

Municipal solid waste management is one of the major environmental concerns globally. Improper management of Municipal solid waste poses a severe threat to all living beings and also to the surrounding environment. Various studies reveal that about 90% of Municipal Solid Waste is due to improper management of open dumping sites and landfills, creating severe problems to public health and the environment. Rapid population growth, Urbanization, industrialization and lack of awareness among people are the major drawbacks for enormous quantities of solid waste generation. An attempt has been made to comprehensively review waste characteristics, generation, collection, transportation, treatment & safe disposal methods of MSW practiced in Hyderabad City. Daywise activities pertaining to MSW have been carried out in order to evaluate the present existing status & to identify the major problems pertaining to it. Hence various methods used for MSW treatment are critically reviewed along with their merits & limitations.

Управление устойчивостью аграрного землепользования на локальном уровне с использованием ГИС-технологий и специального картографического материала

The purpose of the study: analysis of geoecological factors and conditions affecting the sustainability of agricultural land use in the forest-steppe zone of the Altai Krai and its assessment. Research methods: The main scientific method of this study was system analysis, which was used to study the agricultural landscape management system. Methods of analysis and synthesis were used to identify structural units of land management, structuring the land information system (LIS) and special cartographic material, as well as studying the structure of agricultural landscapes. We also used the cartographic method in the design of unique map diagrams and information analysis in modeling agricultural land use. Research results. Based on the results of a long-term assessment of the sustainability of three agricultural land uses located in different natural and climatic zones, the conditions and factors that form the basis of the agricultural land use management system using GIS technologies were established. We found out that in order to manage the sustainability of agricultural landscapes, the mandatory information layers included in the data bank of a geographic information system (land information system) must include the following special cartographic materials: maps (scale 1:10000 or 1:25000) – landscape, soil, slope steepness, erosion, types of areas, tracts, lands, as well as the geomorphological profile of the surface. By processing materials with an information system, it is possible to implement at least 10 models for managing the sustainability of agricultural land use, which involve varying the structure of lands, lands, crop rotations, a set of crops, farming systems, a list of agro-, phyto-, reclamation techniques and measures aimed at achieving ecological and economic balance and, as a consequence, the efficiency of use of land resources. Conclusions. 1. Based on long-term spatio-temporal studies of agricultural landscapes of agricultural enterprises, a mandatory set of special cartographic materials of the geographic information system data bank has been determined, aimed at managing the sustainability of agricultural land use. 2. Using unique cartographic materials as an example, the possibility of modeling management scenarios in different natural conditions, characterized by different stability and efficiency, is shown. Modeling of agricultural land use makes it possible to determine capital investments and economic costs (economic and agronomic sustainability) when implementing the selected model, created on the basis of an analysis of the limiting factors of the territory. 3. The results of scientific research can be used in managing the sustainability of agricultural land use at the level of a municipal district and agricultural organization.

Urban flood hazard assessment in Awka metropolis using multi-criteria decision process

Urban flooding is an escalating global threat, and Awka Metropolis in Anambra state Nigeria is no exception. The city's rapid urbanization and inadequate infrastructure have left it increasingly vulnerable to flooding, exacerbated by the impacts of climate change. Anticipated flood effects include disruption of daily life, infrastructure damage, and threats to public safety, necessitating urgent attention. This study presents a comprehensive assessment of urban flood hazards in Awka Metropolis, utilizing an integrated approach combining the Analytical Hierarchy Process (AHP) and Flood Hazard Index (FHI) to gauge the city's flood vulnerability. The primary objectives were to identify key geophysical factors contributing to flooding, categorize these factors by their vulnerability, determine their reliability indices, delineate flood-prone zones, and generate a spatial flood extent map. The methodology encompassed data acquisition, pre-processing, Flood Modeling (evaluating slope, Elevation, Drainage Network, and flow accumulation), the application of Analytical Hierarchy Process, and the utilization of the Flood Hazard Index. The results classified Awka Metropolis into three flood risk zones: high (837.84 hectares, 14.70%), moderate (2182.65 hectares, 38.30%), and low (2678.45 hectares, 46.99%). These findings provide indispensable insights into the distribution of flood hazards across the city, enabling urban planners and authorities to strategically allocate resources, prioritize mitigation initiatives, and formulate targeted flood risk reduction strategies. Importantly, the incorporation of stakeholder input enhances the study's practical relevance and applicability in real-world urban planning and disaster management scenarios. In conclusion, this research offers a robust and multidimensional framework for assessing urban flood hazards in Awka Metropolis. The synergy of the Analytical Hierarchy Process and Flood Hazard Index equips urban planners, policymakers, and disaster management agencies to proactively tackle the mounting urban flooding challenges. The study's outcomes contribute to the development of sustainable flood risk reduction measures, ultimately enhancing the resilience of Awka Metropolis to future flood events.

Potensi Reduksi Sampah Domestik PT. X Surabaya Berdasarkan Komposisi Sampah

Waste reduction efforts need to be made to reduce the burden of landfill in processing waste. The absence of a study on the potential for reducing domestic waste at PT X is an obstacle for the company to determine the right waste management scenario. PT X's waste management still adheres to the collection, transportation, and disposal system. The test of this study is to analyze the potential waste reduction that can be done by PT X. This study was carried out by collecting waste transportation data and waste composition data obtained through the SNI 19-3964-1995 method. Waste transportation data will be reduced by waste composition data that has the potential to be used for kembai. The average waste transported to landfill is 6480 kg / month with the composition of waste dominated by 26.09% of food waste and plastic waste. Total waste that can be reduced by 52.07% by managing organic waste into compost and collecting and selling waste that still has a selling value. By carrying out this management, the average waste disposal of PT X can be reduced to 3374 kg / month.

Balancing Forest Regulations and Stakeholder Needs in Latvia: Modeling the Long-Term Impacts of Forest Management Strategies on Standing Volume and Carbon Storage

Forest ecosystems are significant carbon pools on a global scale, and also a source of renewable raw materials. Moreover, the European Union (EU) aims to tackle climate change and reach climate neutrality; therefore, forest regulations are designed to promote sustainable forest management practices and ensure the long-term health and productivity of forests. It is important to balance regulatory requirements with the economic, social, and environmental needs of forest stakeholders. This study analyses four theoretical scenarios (business as usual, green deal, intensive forestry, and intensive forestry with afforestation) and prognoses the management impact on standing volume and carbon stock in living trees and harvested wood products (HWPs). Thus, the aim of this study is to evaluate different theoretical forest management scenarios to predict changes in standing volume and carbon stock in living tree biomass and HWPs for the 100 next years. The results suggest that intensive targeted forestry practices may enhance carbon sequestration and were found to be the most suitable strategy for Latvia’s hemiboreal zone, as they balance economic benefits with carbon sequestration and ecosystem services. The obtained results can be valuable for policymakers and forest managers to promote sustainability and balance the diverse needs of society and forest stakeholders.

Addition of biochar decreased soil respiration in a permanent no-till cover crop system for organic soybean production

The increase in soil carbon sequestration under long-term no-till (NT) and cover crop management has been shown to form part of a sustainable agricultural management practice system. Along with the increase in soil organic carbon (SOC), soil respiration in this system was also enhanced by the increased soil temperature through the decomposition that causes carbon loss from the soil. To overcome this issue, biochar can be applied. However, the addition of biochar into this system is not well studied. Therefore, the aim of this study was to investigate the effect of this system on soil respiration. The experiment was conducted at the Center for International Field Agriculture Research & Education, Ibaraki University. Long-term tillage practices, such as NT and moldboard plowing (MP), cover crops such as rye (RY) and fallow (FA), and biochar application such as with biochar (WB) and no biochar (NB) were applied to a split–split plot in a randomized complete block design with four replications. The daily CO2 flux was measured every week at 9:00–11:00 a.m. The daily soil respiration was affected by tillage and cover crop with NT practice had significantly higher daily CO2 flux than that of MP (23.8%–107.4% and 38.0%–107.8%), while RY had higher flux than that of FA (11.9%–81.2% and 34.9%–65.4%) in 2020 and 2021 soybean growing season, respectively. Additionally, in the 2020 cover crop growing season RY also increased daily CO2 flux approximately 41.8%–88.2% compared to FA. Biochar addition significantly reduced soil respiration in soybean and cover crop seasons compared to NB by 24.0%–50.7% and by 25.9%–48.3%, respectively. This reduction in soil respiration by the biochar decreased annual CO2 emissions by 17.6% and 13.0% in 2020 and 2021. The values of these emissions ranged from 9.6 Mg ha−1 for MP FA WB to 18.9 Mg ha−1 for MP RY NB in 2020 and from 7.5 Mg ha−1 for MP FA WB to 13.7 Mg ha−1 for NT FA NB in 2021. This study highlights the crucial role of biochar in reducing soil respiration and enhancing SOC sequestration. The addition of biochar into this system was able to reduce soil respiration by regulating the soil temperature, soil moisture, and protect the SOC from decomposition. Biochar addition also increased the SOC and decreased the soil bulk density, which improves soil porosity. Therefore, these findings would be very useful to be included within the global scenario of soil organic matter management.

Cost-Effectiveness of Performing Reference Ultrasonography in Patients with Deep Vein Thrombosis.

The diagnosis of recurrent ipsilateral deep vein thrombosis (DVT) with compression ultrasonography (CUS) may be hindered by residual intravascular obstruction after previous DVT. A reference CUS, an additional ultrasound performed at anticoagulant discontinuation, may improve the diagnostic work-up of suspected recurrent ipsilateral DVT by providing baseline images for future comparison. To evaluate the cost-effectiveness of routinely performing reference CUS in DVT patients. Patient-level data (n = 96) from a prospective management study (Theia study; NCT02262052) and claims data were used in a decision analytic model to compare 12 scenarios for diagnostic management of suspected recurrent ipsilateral DVT. Estimated health care costs and mortality due to misdiagnosis, recurrent venous thromboembolism, and bleeding during the first year of follow-up after presentation with suspected recurrence were compared. All six scenarios including reference CUS had higher estimated 1-year costs (€1,763-€1,913) than the six without reference CUS (€1,192-€1,474). Costs were higher because reference CUS results often remained unused, as 20% of patients (according to claims data) would return with suspected recurrent DVT. Estimated mortality was comparable in scenarios with (14.8-17.9 per 10,000 patients) and without reference CUS (14.0-18.5 per 10,000). None of the four potentially most desirable scenarios included reference CUS. One-year health care costs of diagnostic strategies for suspected recurrent ipsilateral DVT including reference CUS are higher compared to strategies without reference CUS, without mortality benefit. These results can inform policy-makers regarding use of health care resources during follow-up after DVT. From a cost-effectiveness perspective, the findings do not support the routine application of reference CUS.

Quantifying the smoke-related public health trade-offs of forest management

AbstractPrescribed burning can mitigate extreme wildfire risk and reduce total smoke emissions. Yet prescribed burns’ emissions may also contribute to smoke exposures in nearby communities. Incorporating public health considerations into forest management planning efforts may help reduce prescribed burn-related exposure impacts. We present a methodological framework linking landscape ecology, air-quality modelling and health impact assessment to quantify the air-quality and health impacts of specific management strategies. We apply this framework to six forest management scenarios proposed for a landscape in the Central Sierra, California. We find that moderate amounts of prescribed burning can decrease wildfire-specific PM2.5 exposures and reduce asthma-related health impacts in the surrounding region; however, the magnitude of that benefit levels off under scenarios with additional prescribed burning because of the added treatment-related smoke burdens. This framework can be applied to other fire-prone landscapes to incorporate public health considerations into forest management planning.