Environmental Emergency Response Research Articles

A new high-resolution Coastal Ice-Ocean Prediction System for the East Coast of Canada

The Coastal Ice Ocean Prediction System for the East Coast of Canada (CIOPS-E) was developed and implemented operationally at Environment and Climate Change Canada (ECCC) to support a variety of critical marine applications. These include support for ice services, search and rescue, environmental emergency response and maritime safety. CIOPS-E uses a 1/36° horizontal grid (~ 2 km) to simulate sea ice and ocean conditions over the northwest Atlantic Ocean and the Gulf of St. Lawrence (GSL). Forcing at lateral open boundaries is taken from ECCC’s data assimilative Regional Ice-Ocean Prediction System (RIOPS). A spectral nudging method is applied offshore to keep mesoscale features consistent with RIOPS. Over the continental shelf and GSL, the CIOPS-E solution is free to evolve according to the model dynamics. Overall, CIOPS-E significantly improves the representation of tidal and sub-tidal water levels compared to ECCC’s lower resolution systems: RIOPS (~ 6 km) and the Regional Marine Prediction System – GSL (RMPS-GSL, 5 km). Improvements in the GSL are due to the higher resolution and a better representation of bathymetry, boundary forcing and dynamics in the upper St. Lawrence Estuary. Sea surface temperatures show persistent summertime cold bias, larger in CIOPS-E than in RIOPS, as the latter is constrained by observations. The seasonal cycle of sea ice extent and volume, unconstrained in CIOPS-E, compares well with observational estimates, RIOPS and RMPS-GSL. A greater number of fine-scale features are found in CIOPS-E with narrow leads and more intense ice convergence zones, compared to both RIOPS and RMPS-GSL.

Super-resolution for Gas Distribution Mapping

Gas Distribution Mapping (GDM) is a valuable tool for monitoring the distribution of gases in a wide range of applications, including environmental monitoring, emergency response, and industrial safety. While GDM is actively researched in the scope of gas-sensitive mobile robots (Mobile Robot Olfaction), there is a potential for broader applications utilizing sensor networks. This study aims to address the lack of deep learning approaches in GDM and explore their potential for improved mapping of gas distributions. In this paper, we introduce Gas Distribution Decoder (GDD), a learning-based GDM method. GDD is a deep neural network for spatial interpolation between sparsely distributed sensor measurements that was trained on an extensive data set of realistic-shaped synthetic gas plumes based on actual airflow measurements. As access to ground truth representations of gas distributions remains a challenge in GDM research, we make our data sets, along with our models, publicly available. We test and compare GDD with state-of-the-art models on synthetic and real-world data. Our findings demonstrate that GDD significantly outperforms existing models, demonstrating a 35% improvement in accuracy on synthetic data when measured using the Root Mean Squared Error over the entire distribution map. Notably, GDD appears to have superior capabilities in reconstructing the edges and characteristic shapes of gas plumes compared to traditional models. These potentials offer new possibilities for more accurate and efficient environmental monitoring, and we hope to inspire other researchers to explore learning-based GDM.

Amine-functionalized activated carbon for 2-chloroethyl phenyl sulphide (2-CEPS) sensing using a portable electrochemical circuit

In this study, activated carbon (AC) is synthesized from waste thermocol sheets and functionalized it with amine groups to enhance the surface properties and selectivity. The synthesized material is further characterized using X-ray diffraction (XRD), Fourier Transform Infrared Spectroscopy (FTIR), Scanning Electron Microscopy (SEM), and X-ray Photoelectron Spectroscopy (XPS). SEM images revealed excellent porosity, XRD confirmed AC synthesis, and FTIR and XPS verified amine functionalization. The size of particles of the synthesized material is determined to be 38.4 nm using Dynamic Light Scattering (DLS). The modified carbon is used as a working electrode in an innovative portable electrochemical sensing prototype for detecting 2-chloroethyl Phenyl Sulphide (2-CEPS). Electrochemical characterizations, including cyclic voltammetry (CV) and differential pulse voltammetry (DPV), were conducted to evaluate the electrode's performance. Studies on analyte concentration effects, calibration plots, reproducibility, and stability were also performed. The prototype demonstrated a limit of detection (LOD) of 82.89 µM and a limit of quantification (LOQ) of 251.18 µM, with a linear range of 50-300 µM. Stability tests using 150 µM of 2-CEPS at pH 6 showed consistent peak current values, indicating the device's reliability. The prototype is cost-efficient, portable, and suitable for onsite detection of 2-CEPS, with potential applications in environmental monitoring, war zones, emergency response, border security, and industrial safety.

NIKKY THE HUMANOID ROBOT FOR HEALTHY AND SAFETY LIVING

As the global population ages, the demand for effective elderly care solutions has become increasingly urgent. With advancements in technology, there arises an opportunity to revolutionize the way we approach elderly care, moving beyond traditional models towards more innovative and integrated approaches. This project introduces an integrated smart home automation system designed to enhance the well-being and independence of seniors while providing invaluable support to caregivers. Leveraging cutting-edge technologies such as AI integration, IoT devices, and voice recognition, the system offers a seamless and intuitive user experience. Features include automated task management, real-time environmental monitoring, medication management, and emergency response capabilities. By streamlining daily routines, promoting social engagement, and ensuring safety, the system aims to improve the overall quality of life for seniors while alleviating stress and burden for caregivers. Additionally, this project explores the potential of humanoid robot technology, exemplified by robot Nikky, to further augment elderly care through human-like interactions and assistance. This integrated approach not only addresses physical needs but also focuses on cognitive stimulation and emotional well-being, fostering a sense of companionship and purpose for seniors. Through these efforts, this project seeks to address the evolving needs of aging populations and contribute to the advancement of technology-driven solutions in elderly care and support services. Key Words: Home automation, Robotics, Smart and healthy living, Humanoid Robot for personal interaction

A review of GIS applications in public health surveillance

This paper comprehensively reviews Geographic Information Systems (GIS) applications in public health surveillance. Tracing the historical evolution of GIS in public health, the literature review highlights key concepts, definitions, and frameworks. The role of GIS in disease surveillance is explored, encompassing tracking infectious diseases, monitoring environmental health, emergency response, and surveillance of non-communicable diseases. While GIS proves indispensable in providing a spatial lens for understanding health-related phenomena, challenges such as data quality, privacy concerns, and resource constraints must be addressed. Future directions and innovations, including integrating emerging technologies and improved spatial resolution, promise to propel GIS into a pivotal role in shaping the future of public health surveillance.

Activities efficiency assessment of the governing body’s task force under environmental emergency

Purpose. To work out the method for activities efficiency assessment of the governing body’s task force under environmental emergency. In order to achieve this goal, it is proposed to apply an integrated approach that allows increasing the effectiveness of its work. Methodology. The method for activities efficiency assessment of the governing body’s task force under environmental emergency was applied which allowed determining the degree of its capabilities realization. To study this process, a systematic approach was used, according to which the governing body is considered as a complex system that has a hierarchical structure and is a set of functionally interconnected structural units, united in their activities by the shared goal, concept and action plan. Findings. As the task force’s activity basis, a reasonable decision was determined of the governing body’s head, at the development and implementation of which the task force’s work is aimed. The task force’s efforts coordination is carried out in accordance with the tasks, directions, areas, time and methods of tasks performing that are assigned to the subdivisions of the governing body. As the main factor in activities efficiency assessment, the training level of the governing body’s task force was determined, that stipulates its professional and personal features. Originality. The proposed method for activities efficiency assessment of the governing body’s task force is estimated using an integral index – the degree of its capabilities realization to perform tasks. In the mentioned method, the criterion for activities efficiency of the governing body’s task force is determined as a condition under which the quotient from division of the total capabilities realized by the governing body’s task force indicator by the indicator of its total potential capabilities is in the range 0.8–1. A diagram of the method for assessing the task force’s activities efficiency was elaborated, containing interrelated blocks (activities), direct connections and feedback, which generally characterizes the sequence and actions content of the governing body’s head when implementing the mentioned method. Practical value. An example of estimating the activities efficiency of the governing body’s task force to achieve the goal in terms of an integral index – the degree of its capabilities realization to perform tasks, which is calculated using the proposed method, was considered. The initial data for calculation were the main tasks performed by the environmental emergency response headquarters’ task force, standard time indicators and prescribed time for tasks performance designated by the governing body’s head. On this basis, an analysis of the headquarters’ actions on eliminating the emergency consequences connected with the blowing up of the Kakhovska HPP was carried out, its main tasks and features of the decision-making process in uncertain conditions were established. The directions of increasing activities efficiency of the governing body’s task force were elaborated, in particular by increasing their professional competence, implementing innovative approaches to the transformation of governing styles, rational tasks distribution.

ENHANCING THE QUALITY OF CNN-BASED BURNED AREA DETECTION IN SATELLITE IMAGERY THROUGH DATA AUGMENTATION

Abstract. This study aims to enhance the quality of detecting burned areas in satellite imagery using deep learning by optimizing the training dataset volume through the application of various augmentation methods. The study analyzes the impact of image flipping, rotation, and noise addition on the overall accuracy for different classes of burned areas in a forest: fire, burned, smoke and background. Results demonstrate that while single augmentation techniques such as flipping and rotation alone did not result in significant improvements, a combined approach and the addition of noise resulted in an enhancement of the classification accuracy. Moreover, the study shows that augmenting the dataset through the use of multiple augmentation methods concurrently, resulting in a fivefold increase in input data, also enhanced the recognition accuracy. The study also highlights the need for further research in developing more efficient CNN models and in experimenting with additional augmentation methods to improve the accuracy of burned area detection, which would benefit environmental protection and emergency response services.

Drone-Based Environmental Emergency Response in the Brazilian Amazon

This paper introduces a location–allocation model to support environmental emergency response strategic planning using a drone-based network. Drones are used to verify potential emergencies, gathering additional information to support emergency response missions when time and resources are limited. The resulting discrete facility location–allocation model with mobile servers assumes a centralized network operated out of sight by first responders and government agents. The optimization problem seeks to find the minimal cost configuration that meets operational constraints and performance objectives. To test the practical applicability of the proposed model, a real-life case study was implemented for the municipality of Ji-Paraná, in the Brazilian Amazon, using demand data from a mobile whistle-blower application and from satellite imagery projects that monitor deforestation and fire incidents in the region. Experiments are performed to understand the model’s sensitivity to various demand scenarios and capacity restrictions.

A remotely controlled automated field measurement system for light extinction in coastal waters

The Secchi disk depth (SD) is an important parameter in aquatic ecosystem monitoring. As algal growth depends on solar irradiation, the SD - a measure of light extinction - gives an indirect indication of the chlorophyll concentration. However, most SD measurements are manually based and too sparse to resolve water quality variations during algal blooms.A remotely controlled automatic system for field measurement of light extinction has been developed and installed in three marine fish culture zones in Hong Kong. The visual images of the disk at different prescribed depths and the surrounding water are taken. Based on the contrast theory and image analysis, the recorded light intensity distributions can be analyzed to give the SD and the light extinction coefficient. The method has been extensively verified by field data over a wide range of water quality and hydro-meteorological conditions. The proposed system enables high frequency SD measurements on demand for environmental management and emergency response.

Energy harvesting space-air-sea integrated networks for MEC-enabled maritime Internet of Things

In recent years, various maritime applications such as unmanned surface vehicles, marine environment monitoring, target tracking, and emergency response have developed rapidly in maritime communication networks (MCNs), and these applications are often accompanied by complex computation tasks and low latency requirements. However, due to the limited resources of the vessels, it is critical to design an efficient mobile edge computing (MEC) enabled network for maritime computation. Inspired by this motivation, energy harvesting space-air-sea integrated networks (EH-SASINs) for maritime computation tasks offloading are proposed in this paper. We first make the optimal deployment of tethered aerostats (TAs) with the K-means method. In addition, we study the issue of computation task offloading for vessels, focusing on minimizing the process delay of computation task based on the proposed architecture. Finally, because of the NP-hard properties of the optimization problem, we solve it in two stages and propose an improved water-filling algorithm based on queuing theory. Simulation results show that the proposed EH-SASINs and algorithms outperform the existing scenarios and can reduce about 50% of the latency compared with local computation.

The Application of Environmental Monitoring in Ecological Environment Emergency Response

The Application of Environmental Monitoring in Ecological Environment Emergency Response

Contribution to Developing an Environmental Emergency Response for Industrial Sites

This study aims to guarantee that all anticipated emergencies are effectively planned, reviewed, and the necessary equipment and resources are made publicly available to prevent and reduce environmental damage in the event of emergencies for industrial sites. This research aims to ensure that all necessary steps are taken to protect the company's staff, contractors, the environment, neighbouring communities, and assets in the event of a catastrophic leak. It could also serve as a baseline for the industrial site and its subcontractors. Additional measures could be included to improve good practices; The Emergency Preparedness Strategy programs are broad action plans for dealing with situations that may arise at a facility or in the surrounding community. In the event of an emergency at an industrial site, this will allow lives to be saved and property damage to be minimized.

Meta-analysis of salt marsh vegetation impacts and recovery: a synthesis following the Deepwater Horizon oil spill.

Marine oil spills continue to be a global issue, heightened by spill events such as the 2010 Deepwater Horizon spill in the Gulf of Mexico, the largest marine oil spill in US waters and among the largest worldwide, affecting over 1,000 km of sensitive wetland shorelines, primarily salt marshes supporting numerous ecosystem functions. To synthesize the effects of the oil spill on foundational vegetation species in the salt marsh ecosystem, Spartina alterniflora and Juncus roemerianus, we performed a meta‐analysis using data from 10 studies and 255 sampling sites over seven years post‐spill. We examined the hypotheses that the oil spill reduced plant cover, stem density, vegetation height, aboveground biomass, and belowground biomass, and tracked the degree of effects temporally to estimate recovery time frames. All plant metrics indicated impacts from oiling, with 20–100% maximum reductions depending on oiling level and marsh zone. Peak reductions of ~70–90% in total plant cover, total aboveground biomass, and belowground biomass were observed for heavily oiled sites at the marsh edge. Both Spartina and Juncus were impacted, with Juncus affected to a greater degree. Most plant metrics had recovery time frames of three years or longer, including multiple metrics with incomplete recovery over the duration of our data, at least seven years post‐spill. Belowground biomass was particularly concerning, because it declined over time in contrast with recovery trends in most aboveground metrics, serving as a strong indicator of ongoing impact, limited recovery, and impaired resilience. We conclude that the Deepwater Horizon spill had multiyear impacts on salt marsh vegetation, with full recovery likely to exceed 10 years, particularly in heavily oiled marshes, where erosion may preclude full recovery. Vegetation impacts and delayed recovery is likely to have exerted substantial influences on ecosystem processes and associated species, especially along heavily oiled shorelines. Our synthesis affords a greater understanding of ecosystem impacts and recovery following the Deepwater Horizon oil spill, and informs environmental impact analysis, contingency planning, emergency response, damage assessment, and restoration efforts related to oil spills.

A Brain-Inspired Dynamic Environmental Emergency Response Framework for Sudden Water Pollution Accidents

Sudden water pollution accidents happen frequently in China, and the number of treated accidents is low, due to the slow response speed. In addition, there is a lack of decision support systems that can follow up the whole process instead of just giving a one-time method. This study constructs a framework suitable for China that has both the ability of quick responses and full-time dynamic decision support, such as an experienced expert, while not being affected by pressure, to be used an emergency response for sudden water pollution accidents. To allow new decisionmakers to integrate into this professional decision-making role more quickly, a brain-inspired system is realized through combining the machine learning algorithm KNN and the idea of iteration and dynamic programming. The feasibility of our framework is further tested through a major water pollution happened recently. The results show that this framework can be well connected with the emergency response technology system that has been completed before, while also supporting the rapid and robust decision making such as the decisionmaker’s second brain, reducing the demand for professional background and experience of emergency decisionmakers, thus effectively shorten the waiting period for response.

Improved multi‐criteria group decision‐making method considering hesitant fuzzy preference relations with self‐confidence behaviours for environmental pollution emergency response process evaluation

AbstractEnvironmental pollution is one of the major challenges in China, which seriously affects people's life, economy and society. This paper proposes a multi‐criteria group decision‐making method based on hesitant fuzzy preference relations with self‐confidence (HFPRs‐SC) behaviours and applies it to the evaluation of the environmental pollution emergency response process. Firstly, a comprehensive evaluation system is proposed that covers the environmental pollution emergency response process. Moreover, is utilized to obtain the normalized hesitant fuzzy preference relationship, and an algorithm that considers both the hesitant fuzzy preference value and the self‐confidence level is proposed to improve the consistency of HFPRs‐SC. In addition, combined with subjective and objective weights of experts, a weighted average operator based on the confidence level is applied to aggregate individual HFPR‐SC. Furthermore, the score function of HFPRs‐SC is designed to get the best ranking. Finally, a case study on an explosion accident in Fujian Province of China is conducted to verify the practicability and effectiveness of the proposed method with comparative analysis and sensitivity analysis. Based on the analysis, some suggestions are put forward for improving environmental pollution emergency response.

The Status of Oiled Wildlife Preparedness and Response in the NOWPAP Region

Abstract and introduction The Marine Environmental Emergency Preparedness and Response Regional Activity Centre (MERRAC) is one of four Regional Activity Centres of the Northwest Pacific Action Plan (NOWPAP). It was adopted in 1994 as a Regional Seas Programme of UNEP by the People's Republic of China, Japan, Republic of Korea and Russian Federation and is responsible for regional co-operation on marine pollution preparedness and response in the NOWPAP region. The shipping density has been growing greatly in the NOWPAP region due to the high level of industrial and economic development of the NOWPAP member states and consequently, the region has been severely exposed to oil spills. Oil spill incidents were identified as one of the threatening elements to the marine environment and coastal biota, especially, birds and marine mammals that live mostly near the coast. Objective: We collected existing data on oiled wildlife including relevant response techniques for rescuing, relevant national laws/policies and guidelines concerning response of the oiled wildlife from the NOWPAP Member States to mitigate the damage on the oiled wildlife. Based upon the reviews, we be identified weaknesses and challenges on oiled wildlife issues in the region, suggesting the possible future action plan to taken by NOWPAP members.

Evaluating the Influence of Resident Agencies’ Participation in Flood Management via Social Media, in Nigeria

Disaster management is conducted in multilevel and different stages. However, these different stages are tied together by the key infrastructural components of Information and Communication Technology (ICT) such as social media which is central to the effectual management of disaster through residents’ participation. Nevertheless, there has been limited access to information technologies that enhance quick recovery services, timely response, and effective dissemination of disaster-related information. Therefore, this study examined the influence of resident agencies’ participation in disaster management via the use of social media information planning and training possibilities (SMDPT) in Nigeria. The study used a survey questionnaire and stratified random sampling technique to collect 370 primary data from flood disaster management agencies in Ibadan, Nigeria. The collected data were analyzed using Partial Least Square - Structural Equation Modeling (PLS-SEM). The study found that social media information planning and training (SMDPT) had a positive influence on flood disaster preparedness (DPRE), disaster response (DRES), and disaster recovery (DREC). Therefore, the study concludes that social media has become an important tool for planning during an emergency situation. Hence, an important implication of this study to the environmental regulatory policymakers and emergency response agencies is to create more awareness on the usability and applicability of social media in providing credible information regarding disaster management.

A CLIMATE: A Tool for Assessment of Climate-Change–Related Health Consequences in the Emergency Department

Climate change is an urgent public health problem that has looming implications and associated deleterious health consequences. The intersection of climate change and health has broad implications for health professionals in a variety of settings but especially for ED settings. Climate change is already affecting human health and health systems—which includes impacts on ED care. Disaster response and emergency preparedness are critically important public health interventions in our climate-changing world, and the contributions of emergency nurses are essential. Disaster preparedness, environmental emergency response, and health emergency management are important elements of emergency nursing and are explicated in Sheehy’s Emergency Nursing Principles and Practices, 7th Edition. The purpose of this article is to present an overview of a clinical tool and mnemonic, A CLIMATE, developed by the authors with application to a case review. It is imperative that the nursing profession—particularly emergency clinicians—address the intersection of climate and health to engage in the assessment, intervention, management, evaluation, education, and referral of those who present to emergency departments with potential climate-related health impacts.

Transparency and stakeholder engagement in nuclear or radiological emergency management

Stakeholder involvement and transparency are strongly interrelated. Stakeholder involvement is key to strengthening transparency, while transparency is necessary for effective stakeholder involvement. International and European legal requirements in environmental decision-making, radiation protection, nuclear safety and emergency preparedness and response call for increasing levels of transparency and stakeholder engagement. However, recent nuclear or radiological events demonstrate that transparency and engagement in practice are perceived differently by authorities, media and the public. Research conducted in this study by means of a questionnaire sent to authorities responsible for nuclear/radiological emergency management shows a range of challenges related to transparency during a nuclear or radiological emergency, e.g. fear of panic or timely and proper information. Few countries use the full potential of tools and methods for stakeholder engagement in emergency preparedness, although these may also contribute to improved transparency. Despite lessons learned to enhance transparency and stakeholder engagement in nuclear or radiological emergency management, there is room for improvement at a practical level and for finding a common understanding among stakeholders.

The Landscape of Risk Communication Research: A Scientometric Analysis

Risk communication is a significant research domain with practical importance in supporting societal risk governance and informed private decision making. In this article, a high-level analysis of the risk communication research domain is performed using scientometrics methods and visualization tools. Output trends and geographical patterns are identified, and patterns in scientific categories determined. A journal distribution analysis provides insights into dominant journals and the domain’s intellectual base. Thematic clusters and temporal evolution of focus topics are obtained using a terms analysis, and a co-citation analysis provides insights into the evolution of research fronts and key documents. The results indicate that the research volume grows exponentially, with by far most contributions originating from Western countries. The domain is highly interdisciplinary, rooted in psychology and social sciences, and branching mainly into medicine and environmental sciences. Narrative themes focus on risk communication in medical and societal risk governance contexts. The domain originated from public health and environmental concerns, with subsequent research fronts addressing risk communication concepts and models. Applied research fronts are associated with environmental hazards, public health, medical risks, nuclear power, and emergency response to various natural hazards. Based on the results, various avenues for future research are described.