Major Hazard Research Articles

Evaluation of the Domino Effect Caused by Pool Fires in a Tank Farm

Major hazard installations (MHIs), such as oil refineries, petrochemical plants, and terminals, use large-capacity storage tanks for storing crude oil and by-products. Pool fire is one of the most common types of storage tank fire incidents. This technical article aims to investigate the domino effect resulting from a pool fire in a tank farm consisting of eight large floating-roof storage tanks, with a focus on four specific tanks. A crude oil storage tank was selected as the primary tank (source tank). Point source and plume solid models were used to estimate the thermal radiation. It has been noted that the thermal radiation from the source tank to the adjacent tank in the same dike exceeds the threshold heat radiation level and might result in a domino effect; however, the thermal radiation from the source tank alone does not reach the threshold level for the tanks in the other dike. Additionally, it was found that the thermal radiation from both the primary and secondary tanks just reaches the threshold level for the farther-away tank in the other dike. The domino effect occurs provided that the firefighting system is not activated and the emergency response team does not intervene within ten minutes.

Ground Deformation and Damage Assessment using SAR Observations: A Case Study of Hinatuan, Philippines in the 2023 Surigao Del Sur Earthquake

Abstract. Earthquakes are among the major hazards that lead to economic loss every year. Rapid damage assessment is essential for a more efficient disaster response. The 2023 Surigao del Sur earthquake in the Philippines with moment magnitude (Mw) 7.4 occurred on December 2, 2023, with Hinatuan as the nearest municipality located 12 km south of the epicenter. Thus, this study examined the co-seismic impacts in Hinatuan using Synthetic Aperture Radar (SAR) observations. Using phase interferometry and displacement maps to estimate the ground surface deformation, results show that the phase interferograms, Line-of-sight (LOS) displacements, and vertical displacements were consistent, with most of Hinatuan experiencing an uplift of up to 7.2 cm. In contrast, subsidence as low as –9.0 cm was observed in some isolated areas. The damage assessment conducted through change detection analysis revealed 6.15 ha (6.4%) of built area out of the total 84 ha was significantly damaged. The damage mainly occurred in the uplifted regions between 0 to 5 cm. Building codes, land-use planning, and risk management and assessment can be improved and strengthened with these findings for a more earthquake-resilient community. The findings will be a basis for disaster risk reduction and management actions. These may, furthermore, serve as a reference for the development planning of local government units, especially for urban and built-up areas. These can also be used in developing Information, Education, and Communication (IEC) materials and advisory for residents in Hinatuan and the vulnerable adjacent regions.

Pressurised flow in cracks in embankment dam cores

A major hazard to embankment dams is internal erosion and piping arising from concentrated leaks through cracks in the core due to differential settlement. Previous work (Peirson et al., 2023) quantified the hydraulics of flow through near-surface transverse cracks subject to near-horizontal pressure gradients. This present short note extends the previous work to address pressurised flow through cracks that might occur deeper within the core. Water speeds, hydraulic shear stresses, flows are computed as a function of the applied hydraulic gradient. These results extend previous work addressing the hydraulics of very narrow cracks.

Association between long-term PM2.5 exposure and mortality on Sumatra Island: Indonesian Family Life Survey (IFLS) 2000-2014.

The concentration of PM2.5 (particulate matter with a diameter < 2.5µm) on Sumatra Island has increased, mainly because of forest and peatland fires, transportation, and industry. Biomass burning releases partially burned carbon into the atmosphere, resulting in a smoky haze containing PM2.5. Air quality has deteriorated quickly, and PM2.5 has become a major health hazard in Indonesia. Studies on long-term exposure to PM2.5 have indicated its associations with both morbidity and mortality. Here, we measured long-term (2000-2014) exposure to PM2.5 on the basis of satellite-derived aerosol optical depth measurements (1 × 1 km2) used to predict ground-level PM2.5 concentrations. Additionally, population data on Sumatra Island residents from the fourth wave of the Indonesian Family Life Survey (IFLS) were obtained. We investigated the association between long-term PM2.5 exposure and mortality with a retrospective cohort study design. A total of 2409 subjects aged ≥ 40years participated in the IFLS-3 beginning in November 2000, and we examined mortality outcomes until the IFLS-5 in September 2014. We used Cox regression models to calculate hazard ratios (HRs) of mortality associated with PM2.5 exposure. According to the adjusted model, the mortality HRs per 10µg/m3 increase in PM2.5 concentration were 1.10 (95% CI 1.03, 1.17) for all natural causes, 1.17 (95% CI 1.05, 1.25) for cardiovascular causes, and 1.19 (95% CI 1.04, 1.36) for respiratory causes. Long-term exposure to PM2.5 was associated with all-natural, cardiovascular, and respiratory mortality on Sumatra Island, where PM2.5 levels exceed the WHO and US-EPA air quality standards.

Comparing theeffect of applying different types of amendments on carbon emissions and kinetics of degrading total petroleum hydrocarbons in artificial petroleum-contaminated soil.

Contamination byspent engine oil represents a significant global environmental challenge as it poses a major hazard to human health, animals, plants, microorganisms, the soil ecosystem, and aquatic ecosystems. This study assumes that some amendments differ significantly in their ability to degrade petroleum hydrocarbons. Therefore, this incubation study was conductedto investigate the effect of different types of inorganic and organic amendments (zeolite, bone char, banana leaves biochar, and wood chips biochar) on carbon emissions (CO2-C) and the kinetics of total petroleum hydrocarbons (TPHC) degradation in artificial petroleum-contaminated soil. These amendments wereadded to the soil under study at adose of 3% (w/w). At the end of the incubation period, applying zeolite, bone char, banana leaves biochar, and wood chips biochar to artificial petroleum-contaminated soil significantly reduced cumulative CO2-C emissions compared to the control. The banana leaves biochar significantly decreased TPHC concentrations in artificial petroleum-contaminated soil compared to the control treatment. At the end of the incubation period, adding banana leaves biochar to the soil showed high degradation efficiencies of TPHC which was36% higher than soil before incubation. The effectiveness of applying amendments used in this experiment on the degradation of TPHC increase was in the order of banana leaves biochar > bone char > wood chips biochar > control > zeolite. The second-order model described the kinetics of total petroleum hydrocarbons better than thefirst-order model. Banana leaves biochar added to the soil resulted in a significant increase in the degradation rate constant of total petroleum hydrocarbons (k2) compared with the control. A higher k2 value indicates that TPHC degrades more rapidly. The half-life of TPHC degradation in the soil was decreased significantly by adding banana leaves biochar. According to the second-order equation, the half-lives of control, zeolite, bone char, banana leaves biochar, and wood chips biochar were 4.0, 5.3, 2.7, 1.0, and 3.6 years, respectively. The banana leaves biochar amendment might be cheaper and more environmentally friendly than other organic amendments because it has the high potential for carbon sequestration and remediate petroleum-contaminated soil, which would increase the sustainable use of petroleum-contaminated soil leading to preserving the environment.

Synthesis of Dispersed Magnetic Fe3O4 Nanohydrogel Based on Gelatine by Gamma Irradiation for Toxic Heavy Metals Removal

AbstractHeavy metals are among the problematic groups of contaminants. They are discharged from various industries. The wastewater disposed by heavy metals is causing major hazards to the environment. Different hydrogels based on Gelatin (gelt/AAm/EDTA) and nano- (Fe3O4/gelt/AAm/EDTA) were prepared by gamma radiation at 60 KGy and employed for heavy metals elimination. The structure and surface morphology of the manufactured hydrogels were confirmed with FTIR, X-ray, surface area, and SEM. The prepared hydrogels were characterized in terms of their gel content. The swelling properties were studied as a function of time. This research aims to investigate the adsorption properties of diverse hydrogels concerning heavy metal ions, specifically copper, cobalt, and nickel. The impact of key experimental factors, including initial metal concentration, temperature, time, and pH, was inspected via batch adsorption experiments utilizing atomic absorption spectroscopy. It was found that the adsorption of Cu+2‏, Co+2‏ and Ni+2‏ ions is pH-dependent, and the optimal pH for adsorption of Cu+2 is pH 4‏, Co+2 ‏is 5, and Ni+2‏ is 4. The highest metals removal was copper, nickel, and cobalt ions by nano (Fe3O4/gelt/AAm/EDTA) hydrogel with removal percent 98.5% for Cu+2, 96.8%for Ni+2, and 93.9%for Co+2. Graphical Abstract

Compound spatial extremes of heatwaves and downstream air pollution events in East Asia

In light of increasing climate hazards globally that pose risk to public health, the compounded effects of two major hazards, heatwaves and air pollution, have become a focal point for environmental and health research. This study explores the intricate relationship between extreme temperature events in North China (NC) and South China (SC) – two prominent areas of aerosol exposure in East Asia – and the associated changes in aerosol optical depth (AOD) across the region. The heatwave events and regional AOD distribution revealed distinct patterns in their respective regions from June to September. Both NC and SC showed reduced AOD during heatwave events, while downstream regions experienced increased AOD levels. From the perspective of heatwaves in NC and SC, we present a more holistic picture of how large-scale modulators contribute to inducing air pollution hazards across East Asia. The analysis revealed a link between blocking high-pressure system and heatwave occurrences in NC, while a dominant Rossby wave train, influenced by the South China Sea, was identified as a major modulator in SC. Additionally, other large-scale circulatory systems, such as the Western Pacific Subtropical High, the East Asian jet stream, and the South Asian High, also play crucial roles in shaping these events. This suggests the potential for predicting downstream AOD events. The study underscores the importance of understanding the interconnectedness of meteorological and air quality phenomena to mitigate the adverse environmental impacts in East Asia.

Blue space resilient urban planning to enhance severely distressed thermal environment

Water resilience is a vital aspect of current smart city planning. Maintaining the quality and volume of urban blue spaces can benefit local ecology, environment, and social well-being. The application of geospatial techniques provides an opportunity to achieve such goals in a spatially and temporally effective manner. While researchers often highlight city-level environmental problems, location-based solutions are insufficient, particularly for the rapidly sprawling Asian cities—the current work aimed to examine the water-resilient urban planning scopes for an Indian tropical megacity. The work assessed a major environmental hazard, i.e., urban heat island, which appeared to cover 9.6 % to 17.4 % of the area of the city region during the summer months. The importance of blue spaces in mitigating heat islands was quantified using data from nearly 150 waterbodies, including a river, a vast wetland, and multiple lakes and urban tanks. Linear and logarithmic models established how the cooling effect increases with larger water bodies. Blue space ranging between 1.8 km2 and 2.3 km2 was recommended as the smallest yet effective size for future recreational zones. Incorporating ambient wind patterns further aided in deciding the locations of blue wedges that can be key for heat island mitigation. Moreover, to substantially amplify the blue resource recharge rate in a cost-effective manner, a multi-parameter decision analysis was carried out. Overlay of five surface characteristics contributed to planning sites for surface infiltration systems. The entire framework of the work was built to achieve sustainable development goals.

A Neural-Metaheuristic Kalman Filter for Moving Microburst Wind Shear Identification

Microburst wind shears (MB) are powerful localized three dimensional (3D) columns of wind that occur when cooled air drops from the base of thunderstorms at high speeds. They eventually hit the ground and spread out in all directions. As such MBs are considered a major atmospheric hazard for aircrafts (ACs), especially in terminal flight phases. Though pilots train regularly to survive it, yet the most recommended practice within the aviation community is to avoid its encounter upon detection. Some modern aircrafts have predictive wind shear warning systems, but they have limited short range capability and do not provide quantitative data for engineering application. In this sense, accurate onboard detection and identification of MBs and its characteristics is of importance for flight safety, whose success can lead to design of automatic flight control systems (FCSs) that reduce the risk of aircraft crash landings and accidents. Even though there are some studies on FCS designs for MB encounter, research on MB identification is rare but ongoing. To this aim, the present study is among the firsts that focuses on online identification of multiple and moving MB parameters using onboard aircraft air data and inertial sensors. The identification task is initially performed using the aircraft six degrees of freedom (6DoF) equations of motion (EOM) integrated with a 3D MB model via the utility of nonlinear Kalman filtering (KF) algorithms. Subsequently, an enhanced neural metaheuristic Kalman filter (NMKF) is proposed that improves the estimation accuracy of the MB model parameters. The results demonstrate the efficacy of the proposed NMKF in comparison with previous studies.

A-posteriori analysis of the performance of a rockfall susceptibility map

BackgroundRockfalls pose a serious threat along the main road network, representing a major hazard in mountainous territory and causing damage and victims. Currently, susceptibility mapping represents a starting point to identify areas more susceptible to rockfall occurrence, a key approach in land use planning and risk management. Despite the extensive use of these maps by decision makers and administrators, the usability of such maps over time and their reliability represent a poorly discussed and examined feature.MethodsHere, we proposed a-posteriori analysis of a three-year-old rockfall susceptibility map, generated along the main road network of the Aosta Valley, an alpine region of north-western Italy. To verify map consistency over time, we implemented a dual-analysis in GIS-environment and by text mining, to respectively analyse the geocoded data and textual information derivable from the regional landslide inventory. The first one allowed us to extract rockfall events occurred after the susceptibility map generation. By this way, we operated to spatially and temporally verify the map consistency. Jointly, the textual information reported in the Event Description Form, linked to each geocoded event, are being exploited. This allowed us to derive relevant information about occurred damage and their degree, presence of protective measures or secondary roads, i.e. involvement of, farm or forestry, road.ResultsThe implemented approach allowed us to prove the quality of the previous map in terms of reliability, robustness and degree of fitting respect to the succession of rockfall occurrence over time. After only three years as many as 198 rockfall events have been occurred and collected since the map was generated. Particularly, 80% of rockfall fit with “high” and “very high” susceptibility classes, and pointed out large involvement of main roads in rockfall occurrence, representing the most affected target with damage to road pavement and vehicles, as well as a relevant involvement of existing rockfall barriers and of the dense network of forestry roads and footpaths that characterize this alpine region.ResultsThe proposed approach representing a starting point in landslide susceptibility map verification and usability as valid instrument for a reliable land planning.

Study on gas explosion propagation law in excavation roadway with TBM

Gas explosion is one of the five major hazards in mines, with about 36% of such incidents occurring in the excavation working face. Therefore, to investigate the impact of gas explosion propagation laws within excavation roadways, we conducted a simulation analysis of parameters such as peak of explosion overpressure, peak rate of pressure rise, and flame propagation speed in the presence of a Tunnel Boring Machine (TBM). In the presence of the TBM, the explosion overpressure approximately doubles, and the flame propagation speed also greatly increases, exacerbating the explosion hazard. Thus, when investigating gas explosion laws within excavation roadways, the presence of a TBM emerges as a significant factor that cannot be overlooked. Furthermore, an analysis of the effects of methane concentration and gas accumulation length on explosion parameters was conducted. The results indicate that when the flame passes through the TBM baffle, the average flame propagation speed increases the most when the methane concentration is 9.5%, increasing by about 6 times. In addition, as the gas accumulation length increases, both explosion overpressure and flame propagation speed gradually increase. Additionally, TBM has a certain impact on flame propagation and methane dissipation.

Glacial lake outburst flood risk assessment of a rapidly expanding glacial lake in the Ladakh region of Western Himalaya, using hydrodynamic modeling

The ongoing trend of warming climate has made Glacial Lake Outburst Floods (GLOFs) a major cryospheric hazard worldwide, especially in the Himalayas. GLOFs in the Himalayan region are mostly caused by moraine-dammed proglacial lakes and ice-dammed lakes. These sporadic disasters have resulted in significant loss of life and property. This study offers a comprehensive analysis of the GLOF hazard potential of a potentially dangerous proglacial lake (PDGL) in the Ladakh region. This research explores the GLOF threat from the lake using multi-criteria analysis and advanced 2D hydrodynamic modeling approaches. The mass balance response of the mother glacier, its flow dynamics, and glacier-lake interactions were examined for the past 22 years. The findings show that over this period, the PDGL has had a notable expansion of 78.7%, accompanied by a significant recession of 13.2% in its feeding glacier. The glacier has witnessed an average thickness loss of ⁓7 m at the rate of 0.32 m a−1 during this period. The average, lowest, and maximum depth of the glacier were found to be 30.95, 14.30, and 50.57 m, respectively and the average velocity of the glacier was estimated as 3.38 m a−1. Because of the lake’s rapid expansion and steep surrounding slopes, it was classified as a high-hazard lake. The risk to the downstream community was assessed through 2D hydrodynamic modeling using the HEC-RAS tool. The maximum discharge under the worst-case scenario for the piping and overtopping failures was estimated as 3890.99 m3s−1 and 5111.39 m3s−1, respectively. The area potentially under the threat of inundation was calculated to be 4.74 and 5.38 km2 for the moderate and worst-case scenarios respectively. The expected maximum flood velocities range from 18.26 to 23.78 meters, respectively for the moderate and worst-case scenarios. At several locations in the downstream area, routed hydrographs representing the GLOF propagation were generated. The findings show that the flood wave in the worst-case scenario would arrive at the first settlement in 50 min, with a peak velocity of 12.36 m s−1. The potentially inundated area includes critical infrastructure such as bridges, residential houses, and roads. To mitigate the potential risk associated with this lake, a more detailed and on-site study is highly recommended.

Centering and uplifting youth voice in planning for a more resilient climate future in rural Colorado: a case study of a student resilience team asking for change

Rural communities are increasingly facing challenges from climate-related natural hazards such as drought, wildfire, and flood. These cascading hazards threaten social, emotional, physical, and economic well-being, and pose unique challenges to rural areas which may already struggle to find enough resources. Yet, rural areas are rich in social capital, creativity, and resilience, and future leaders are learning how to build agency and increase their community’s resilience in school settings. Students in Estes Park, Colorado, have experienced major climate-fueled hazards in their lifetimes, surviving the floods in 2013 and the East Troublesome and Cameron Peak wildfires in 2020. At Estes Park Middle School, the Environmental Resilience Team (ERT) is an afterschool group of students who are actively participating in promoting public awareness, mitigation, and policy-making to increase resilience to natural hazards. Supported by the Hazard, Education, Awareness, and Resilience Task Force (HEART Force) Program, a comprehensive curriculum that immerses students in the study of their community’s resilience to floods and fires, in conjunction with the Earth Force Environmental Civic Action resources, students and educators gained the tools needed to spearhead community discussions on resilience, all while striving to mitigate and minimize future risks. In this paper, we tell the story of the Environmental Resilience Team’s campaign to pass statewide legislation to implement Wildland Urban Interface (WUI) Building Codes in high-risk areas. Students visited the Colorado State Capitol, met with their State Senator and Governor to lobby for the passage of the bill. This initiative builds upon years of action projects, including service projects to mitigate fire risk in vulnerable populations within the mountain town of Estes Park and build community education and awareness through the distribution of “go-bags” to community members. By including youth voice in public decision-making and planning for climate resilience, community leaders and policymakers can develop more holistic plans that include multigenerational input. This research is part of a broader study across implementations of HEART Force in several classrooms that showed that the HEART Force program helped students develop a sense of agency and grow in their understanding of community resilience.

Evening humid-heat maxima near the southern Persian/Arabian Gulf

Extreme humid heat is a major climate hazard for the coastal Arabian Peninsula. However, many of its characteristics, including diurnal and spatial variations, remain incompletely explored. Here we present evidence from multiple reanalysis and in situ datasets that evening or nighttime daily maxima in extreme wet-bulb temperature and heat index are widespread along the southern Persian/Arabian Gulf coastline and adjacent inland desert, driven principally by sea-breeze-related movements of moist maritime air. This timing runs counter to the general expectation of more intense heat and greater heat-stress risk during daytime hours. While wet-bulb temperature is one of many metrics relevant for understanding heat hazards, it has featured prominently in recent literature and its values are closer to uncompensable-heat limits in coastal Arabia than anywhere else. Deviations from an afternoon-peak assumption about heat risks are thus of critical importance and heighten the value of improved understanding of extreme-humid-heat meteorology, in this region and in others subject to similar physical processes.

A perspective view of salt crystallization from solution in porous media: morphology, mechanism, and salt efflorescence.

Salt efflorescence is one of the major hazards to cultural heritages, masonries, and highways etc. It is now generally accepted that damages caused by salt efflorescence are mainly due to continuous cycles of salt crystallization/dissolution or hydration/dehydration in confined spaces. The position where salt efflorescence occurs and its type are closely related to the degree of damages caused by salt efflorescence. It is known that water is the key environmental factor determining the salt crystallization position. But influence of the correlation between water supply and evaporation on the position of salt crystallization is still not clearly understood. In this work, a set of experiments are designed to investigate salt efflorescence in porous matrix. It is found that the types and positions of salt efflorescence have little to do with nucleation, but are mainly governed by crystal growth, which is controlled by the rates of water evaporation, water and salt supply, capillary forces and surface properties of the porous matrices.

Consequences of acute and long-term excessive iodine intake: A literature review focusing on seaweed as a potential dietary iodine source.

Macroalgae, also called seaweed, are becoming more widespread as food in Western diets. Seaweed can accumulate iodine, an essential nutrient for humans. However, some species of seaweed may contain very high amounts of iodine, and therefore, iodine has been identified as one of the major hazards in the seaweed food chain. Macroalgae may be consumed regularly, though many consumers report eating macroalgae only occasionally. The aim of this paper is to explore possible health consequences of excessive iodine intake according to long-term (chronic) or occasional (acute) excessive exposure to iodine, relating to a regular (chronic) or occasional (acute) seaweed intake, respectively. Furthermore, through a modeling exercise, we add different amounts of seaweed to the diet in a population group to explore the possible safe amounts that can be added without exceeding excessive iodine intakes and risking detrimental health effects. Chronic excessive iodine intakes were associated with several negative health outcomes at variable doses in various studies. For acute excessive iodine exposure, negative health effects seemed to be associated with higher iodine exposures. However, the research on this topic was limited. The chronic and acute iodine exposures needed to result in negative health outcomes may easily be ingested by macroalgae consumption. Adding seaweed to the diet must be done thoughtfully to avoid the risk of exceeding thresholds for excessive iodine intake.

Older Adult Fall Risk Prediction with Deep Learning and Timed Up and Go (TUG) Test Data.

Falls are a major health hazard for older adults; therefore, in the context of an aging population, predicting the risk of a patient suffering falls in the near future is of great impact for health care systems. Currently, the standard prospective fall risk assessment instrument relies on a set of clinical and functional mobility assessment tools, one of them being the Timed Up and Go (TUG) test. Recently, wearable inertial measurement units (IMUs) have been proposed to capture motion data that would allow for the building of estimates of fall risk. The hypothesis of this study is that the data gathered from IMU readings while the patient is performing the TUG test can be used to build a predictive model that would provide an estimate of the probability of suffering a fall in the near future, i.e., assessing prospective fall risk. This study applies deep learning convolutional neural networks (CNN) and recurrent neural networks (RNN) to build such predictive models based on features extracted from IMU data acquired during TUG test realizations. Data were obtained from a cohort of 106 older adults wearing wireless IMU sensors with sampling frequencies of 100 Hz while performing the TUG test. The dependent variable is a binary variable that is true if the patient suffered a fall in the six-month follow-up period. This variable was used as the output variable for the supervised training and validations of the deep learning architectures and competing machine learning approaches. A hold-out validation process using 75 subjects for training and 31 subjects for testing was repeated one hundred times to obtain robust estimations of model performances At each repetition, 5-fold cross-validation was carried out to select the best model over the training subset. Best results were achieved by a bidirectional long short-term memory (BLSTM), obtaining an accuracy of 0.83 and AUC of 0.73 with good sensitivity and specificity values.

Time-evolving traffic resilience performance forecasting during hazardous weather toward proactive intervention

Transportation systems experience significant disruptions and loss during hazardous weather events, exhibiting great needs of timely intervention to effectively improve the resilience of the affected traffic systems. An informed and science-based proactive intervention strategy depends on accurate forecasting of the resilience performance of traffic systems with essential lead time during hazards. A new resilience performance forecasting methodology at both global and local scales is proposed for traffic networks under natural hazards by addressing unique challenges such as scarcity and time-evolving nature of hazard-specific data. The proposed methodology consists of two modules: the local traffic resilience performance short-term forecasting module based on the modified diffusion convolutional recurrent neural network (DCRNN) and transfer learning techniques, and the global traffic resilience performance forecasting module integrating percolation-based robustness assessment and SIR-based congestion propagation modeling. A case study of an urban traffic network during a major snowstorm hazard is conducted as a demonstration, followed by the feasibility investigation to guide proactive intervention during hazards. It is found the proposed methodology can forecast the time-evolving traffic resilience performance with good accuracy at both global and local scales. With sufficient lead time for the forecast, it bears promising potential to assist the stakeholders to make informed and timely decision about possible proactive intervention by providing key information to help identify the optimal moments and individual strategic links for possible intervention.

Novel methods for the control of blast noise from explosive depth hardening

DNV Spadeadam undertakes crucial major hazards testing to improve safety across a wide range of industries, including energy and infrastructure. One common form of testing is Explosive Depth Hardening (EDH) in which plastic explosives up to 10 kg TNT are used to harden pre-cast railway crossings in order to support national transport infrastructure. The operations produce extremely high intensity noise and are carried out up to 10 times per day. The source characteristics of the explosion are not well understood and vary significantly with operational demands. This has implications on occupational and environmental blast noise impacts. Quantification of the source characteristics are important for the exposures of site personnel with regards to providing adequate hearing protection. Moreover, for the purpose of managing environmental noise impacts on local communities, the uncertainties around source directivity and strength make long-range blast noise prediction difficult. This paper presents the current research on novel blast noise mitigation undertaken in the laboratory, such as experimental water curtains, water sprays, and metamaterial designs. It is proposed to implement novel methods developed in the laboratory for use during EDH shots at full-scale, and the potential improvements to occupational and environmental noise impacts will be discussed.

Groundwater geochemistry using modified integrated water quality index (IWQI) and health indices with special emphasis on nitrates and heavy metals in southern parts of Tirupati, South India.

Groundwater is particularly vulnerable to pollution in places with a high population density and extensive human usage of the land, especially in southern parts of Tirupati, India. To assess this, 60 bore-well samples were obtained and assessed for physical specifications, ion chemistry, and heavy metals during the pre- and post-monsoon seasons 2022. The current investigation employed a modified integrated water quality index (IWQI), conventional graphical and human health risk assessment (HHRA) of nitrates and heavy metals to know the groundwater chemistry and its detrimental health effects on humans. The major ions were analyzed using American public health association (APHA)standards, whereas heavy metals were analyzed using inductively coupled plasma optical emission spectrometry(ICP-OES). Additionally, pH Redox Equilibrium and C (PHREEQC),a geochemical model written in C programming language was employed to determine the saturation indices of mineral facies and ArcGIS 10.3.1 was used for spatial distribution patterns of IWQI. Then, the HHRA of nitrates and heavy metals was performed using United States environmental protection agency (USEPA)guidelines. The noteworthy outcomes include elevated levels of Ca2+, Mg2+, Cl-, NO3-, Cu,Fe, Mn, and Pb, demonstrating rock-water interaction, silicate weathering, Ca-Mg-HCO3 followed by mixed water facies, dissolution/precipitation, reverse exchange, and anthropogenic contamination are the major controlling processes in groundwater of southern Tirupati, India. The modified IWQI reveals that most groundwater samples (38%) fall under the bad quality class, with (47%) in the poor quality class and only (15%) classified as medium qualityclass in pre- and post-monsoon seasons. Elevated IWQI were observed in all directions except in the east, which is suitable for drinking. Moreover, the major hazard quotient (HQ) and hazard index (HI)for nitrates (NO3-) and heavy metals like copper(Cu), iron (Fe), manganese (Mn), lead (Pb) and zinc (Zn) are above the critical value of 1, revealing potential risk to humans, especially infants, followed by children and adults, entailing the instantaneous implementation of proper remedial measures and stringent policies to reduce the risk associated with groundwater pollution in the southern parts of Tirupati.