Effective Mitigation Measures Research Articles

Drought risk assessment on the eastern part of Indian peninsula-a study on Purulia district, West Bengal.

This study focuses on measuring the spatial nature of drought risk which is conceived as the product of drought severity, drought vulnerability, and drought exposure in the Purulia district, located in the eastern part of the Indian peninsula. Drought severity is measured using the Standard Precipitation Index and drought vulnerability is calculated as the average condition of meteorological, hydrological, agricultural, and socio-economic drought. The drought types and drought exposure conditions are the outcome of multi-criteria analysis where the Fuzzy Analytical Hierarchy Process is used for assigning weights to the respective parameters and the Analytical Hierarchy Process is used for determining the class ranks. 31.46% of the total district area has registered moderate to high and high vulnerability to drought situations, while 16.57% of the entire district area has been found moderate to high and highly exposed to drought situations. Similarly, 39.39% of the district's total area is under a significant drought risk. Blocks like Barabazar (75.49%), Jhalda-I (71.85%), and Purulia-II (52.66%) have the majority of their area under extreme drought risk conditions. The modeled outcome of drought vulnerability was found significant while being tested with phenomena highly correlated to drought events, land surface temperature, and aridity index. The computed spatial profile of the districts' drought risk condition is of substantial help for the policymakers in preparing effective drought mitigation measures to restrict drought impacts reasonably.

Unforeseen nitrate accumulation under nutrient mitigation measures in the east Pearl River Estuary: Phenomenon, drivers and implications

Study regionShenzhen Bay (SZB) in the east Pearl River Estuary, China Study focusEither NO3− or NH4+ is the dominant component of dissolved inorganic nitrogen (DIN) in most estuarine waters, but few studies focused on the mechanisms of ongoing DIN transformations under various hydrologic regimes. This analysis spans 31 years of DIN component changes and involves numerical simulations to identify the roles of various driving factors including runoff and biogeochemical actions. These new insights into DIN change mechanisms from the coupling biogeochemical and hydrodynamic processes would help to boost effective mitigation measures to deal with nitrate accumulation in estuarine waters, thereby supporting integrated land-ocean nutrient management. New hydrological insights for the regionThe dominant DIN component in the SZB was found to transition from NH4+ to NO3− between 1990 and 2020. Particularly in the -upper bay, there was an unexpected increase in the mean concentration fraction of NO3− in DIN, rising from 19.5% (1990‐2017) to 65.5% (2018‐2020). This change can be partially attributed to reduced runoff NH4+ inputs. Both runoff and tidal current can transport NH4+ and NO3−downstream, but the high background levels of NO3− in the lower bay contributed to sustaining NO3− in the upper bay through ebb and flow. Biogeochemical actions further strengthened the decline of NH4+ and the rise of NO3−. Even in scenarios without terrestrial source inputs, the simulated biogeochemical processes continued to help reduce NH4+ levels throughout the bay while increasing NO3− concentrations in the middle and lower bay.

The impact of landfill management approaches on methane emissions.

This article reports on how management approaches influence methane emissions from landfills. The project team created various landfill operational scenarios for different regions of the planet with respect to waste composition, organic waste reduction and landfill gas recovery timing. These scenarios were modelled by applying a basic gas generation model according to the United Nations Intergovernmental Panel on Climate Change (IPCC) recommendations. In general, the IPCC's recommended modelling parameters and default values were used. Based on the modelling undertaken, two options stand out as being the most effective methane mitigation measures in a wide range of conditions throughout the world: (a) early gas recovery and (b) reduction of the amount of biodegradable organic waste accepted in a landfill. It is noted that reduction of organic input to any given landfill can take many years to realize. Moreover, suitable alternative processing or disposal options for the organic waste can be unaffordable for a significant percentage of the planet's population. Although effective, organic waste reduction cannot therefore be the only landfill methane mitigation measure. Early landfill gas recovery can be very effective by applying basic technologies that can be deployed relatively quickly, and at modest cost. Policymakers and regulators from around the globe can significantly reduce adverse environmental impacts from landfill gas emissions by stimulating both the early capture and flaring and/or energy recovery of landfill gas and programmes to reduce the inflow of organic waste into landfills.

Assessing landscape ecological vulnerability to riverbank erosion in the Middle Brahmaputra floodplains of Assam, India using machine learning algorithms

Riverbank erosion is one of the most catastrophic hazards that renders floodplains vulnerable across the world vulnerable. It creates a significant negative impact on the environment and socio-economic life. This paper attempts to assess the landscape ecological vulnerability (LEV) to riverbank erosion in the Middle Brahmaputra floodplains of Assam, India by employing two machine learning models, namely artificial neural network-multilayer perceptron (ANN-MLP) and random forest (RF). Bagging ensembles were created for both ANN-MLP and RF (B-MLP and B-RF) to generate LEV zones. A total of eleven site-specific parameters were considered for the study. The receiver operating characteristic (ROC) based area under curve (AUC), accuracy, precision, recall and F1-score were used to validate the models and judge the models’ performance. A sensitivity analysis was performed to deduce the most influential LEV parameters. The results revealed that B-MLP was the better-performing model compared to B-RF based on all five validation metrics. The largest area was found under very high vulnerability zone followed by very low, low, high and moderate vulnerability zones, based on both ensemble models. The western part of the floodplains was found to be more vulnerable than the eastern part. Moreover, the southern bank faced more vulnerability in comparison to the northern bank. The factors namely rainfall, soil type, vegetation and land /use land cover (LULC) influenced bank erosion vulnerability. This research provides evidence that the study area is under severe threat to riverbank erosion and urgently requires the implementation of effective mitigation measures. The study might benefit policymakers and local stakeholders to protect the floodplains from bank erosion and reduce vulnerability.

Weathering the Storm: Planning and Building Smarter

The importance and challenge of utility distribution system strategy and planning cannot be overstated in light of climate change and the increasing frequency of extreme storms. Independent power producers, distributed energy resource (DER) providers, and retail energy providers similarly face the same challenges. The United States witnessed a record‐breaking hurricane season in 2020, resulting in staggering damages of approximately $95 billion. The most recent report from the Intergovernmental Panel on Climate Change (IPCC) highlights the urgency of reducing greenhouse gas (GHG) emissions to limit global warming to mitigate the disastrous and costly effects of climate change. The report indicated that these events are likely to become the norm and will worsen if mitigation and adaptation measures aren't established. These events are becoming more frequent and severe, making it imperative to establish effective mitigation and adaptation measures.

Understanding the impact of hydrodynamics on coastal erosion in Latin America: a systematic review

Coastal zones in Latin America support a significant regional population and are vital for providing essential ecosystem services that underpin crucial socio economic activities. However, these zones face pressing challenges, with coastal erosion being a prominent concern. Coastal erosion not only jeopardizes coastal stability but also leads to occasional loss of natural habitats. This is particularly worrisome for sandy beaches due to the consistent shoreline retreat in specific regions. Short term adverse effects of coastal erosion are often attributed to human activities. Nonetheless, the influence of hydrodynamic processes, intensified by extreme events, is gaining prominence. This is due to the combined impact of tides, waves, currents, and other factors, resulting in accelerated shoreline retreat and significant losses of infrastructure and beach areas across Latin America. This article conducts a comprehensive analysis of case studies in Latin America related to coastal erosion due to hydrodynamic processes. Employing a systematic review approach, data is extracted from Scopus and Web of Science databases. From an initial dataset of 701 records, 62 records meet strict eligibility criteria. Case studies present evidence of how hydrodynamic processes interact with various factors, encompassing oceanic climatic conditions, atmospheric climatic conditions, anthropogenic influences, geomorphological and bathymetric characteristics, geological and tectonic factors, and climate change related aspects. These interactions have an immediate and significant impact on sandy beaches, emphasizing the necessity of comprehensively addressing these linkages when analyzing shoreline changes. This approach aids in identifying key erosion mechanisms and developing effective mitigation measures. Furthermore, the article provides a concise overview of data sources, tools, and methodologies identified in the case studies, spanning from field investigations to the utilization of geographic information systems and numerical models. Underscores the crucial role of international academic collaboration in coastal erosion research, facilitating the adoption of innovative methodologies from other regions, potentially offering a more comprehensive perspective in the formulation of mitigation and adaptation strategies. Finally, potential areas for future research in Latin America are explored, including the assessment of extreme event variability and its impacts on local and regional hydrodynamic processes. This aspect holds critical importance in steering future research towards scenarios that encompass economic and social considerations.

Understanding the differences in the effect of urbanization on land surface temperature and air temperature in China: insights from heatwave and non-heatwave conditions

Accelerated urbanization and frequent heatwave events pose significant threats to human health. Analyses of the differences in air and land surface temperature (LST) under extreme climates can aid in understanding human-nature ecosystem coupling and the required adaptations to climate change. In this study, we quantified differences in urban and rural temperatures in China under heatwave (CHW) and non-heatwave periods (NHW) conditions and the influence of meteorological factors on these differences. Based on impervious surface data, 2421 urban and rural stations were dynamically classified from 2008 to 2017. Heatwaves were identified using relative thresholds, and differences were explored using meteorological data and MODIS LST data. For LST, urban–rural temperature difference (U-RTempdiff) was highest during the day, whereas air temperature peaks occurred at night, under both NHW and CHW conditions. During CHWs, the daytime U-RTempdiff was greater for LST than for air temperature, reaching 4.24 ± 3.38 °C. At night, U-RTempdiff was slightly lower (1.04 ± 1.41 °C). The proportion of air U-RTempdiff contributed by rural air temperature was significantly higher during CHW nights than during NHW nights, whereas the proportion of land surface and air U-RTempdiff remained relatively stable during daytime. Spatially, the daytime temperature difference in the north decreased with latitude, whereas the difference in the south was lower. Under CHWs, urbanization had a stronger effect on LST than on air temperature, with a slightly smaller difference (0.01 °C yr−1) during the day and a slightly larger difference (0.03 °C yr−1) at night. The contribution of urbanization to LST was higher than that to air temperature, particularly during the day (16.34%). The effects of wind speed and precipitation on the average air urban–rural temperature difference was greater than those of LST under CHW, accounting for 16.13%, with the effects of wind speed being more significant. These results show that a comprehensive perspective is needed to understand the risks associated with a temperature rise risk under extreme climate conditions and to formulate effective mitigation measures that will they improve human thermal comfort under climate change.

Inter-site variability in the Cape fur seal's behavioural response to boat noise exposure

The impact of man-made noise on wildlife is recognised as a major global concern affecting many taxa in both terrestrial and aquatic ecosystems, with the degree of impact varying among individuals or species. Understanding the factors inducing intra-species differences in response to noise is essential for the development of adapted and effective mitigation measures. This study compares the behavioural response of Cape fur seals to boat noise exposures at two study sites showing differences in their level of exposure to anthropogenic activities, and individual composition. Increased vigilance was found for Lambert's Bay seals exposed to high noise level (70–80 dB) compared to those tested at Cape Town harbour. Comparisons with a similar study performed in Namibia were made. Intrinsic factors such as individuals' age-class, sex or arousal state as well as extrinsic factors such as the ambient noise and the nature/extent of human-seal interactions were suggested to induce such variation.

Inclined rigid sliding walls to protect tunnels subjected to reverse faulting

Tunnels subjected to reverse faulting are dangerous, experiencing large inner forces and movements. However, there is a lack of effective mitigation measures to protect shield tunnels from reverse faulting. This study proposed a novel mitigation measure, inclined rigid sliding walls, for shallow buried shield tunnels subjected to reverse faulting. Validated numerical modeling is performed to explore the responses of the tunnel, the effects of the walls, and some influence factors. The results show that the walls are effective to protect the shield tunnel from revere faulting. The function of the walls is to release the fault deformation by sliding and develop a relatively stable condition between the walls with less shearing. The walls can decrease the soil pressures, inner forces, and movements of the tunnel. Three possible interaction mechanisms are summarized: hanging wall mechanism, shear mechanism, and footwall mechanism. The walls work best under the footwall mechanism. The detailed protection effects of IRSWs depend on the relative tunnel location, burial depth of the tunnel, the distance between the tunnel and walls, angle of walls, relative depth of walls, and fault dip angle.

Runoff mitigation on agricultural fields via micro-dams – Literature review and derivation of runoff curve number reductions

Water runoff and soil erosion by water from agricultural fields lead to a loss of water available for plant growth, loss of topsoil and transport of plant protection products (PPPs), hence constituting contaminant pathways to adjacent surface water. Several mitigation measures are used, including small earthen dams or depressions, referred to as micro-dams. This practice has been applied worldwide since the 1930s. In the regulatory exposure assessment for the registration of PPPs, runoff curve numbers (CNs) are used in the PRZM model to quantify runoff and the effect of mitigation measures. An overview of the pertinent literature is presented to enlarge the knowledge base to give robust recommendations for the inclusion of the practice in the regulatory exposure assessment of PPPs. Literature on micro-dams was collected here in a review of the reported results from field trials in terms of runoff, erosion, and PPP transport mitigation. Selected data were further evaluated to derive runoff CNs. From 21 studies with 252 individual setups and trials, we derived a geometric mean reduction of runoff of 62% (42%–90%); results for maize and potatoes only were 62% (53%–73%) and 81% (71%–93%), respectively. Erosion was reduced by 73% (60%–90%; maize: 75% [63%–88%]; potatoes 89% [83%–97%]). From 19 studies with 246 individual setups and trials, the geometric mean of the CN reduction is 11% (4%–25%; maize: 7% [3%–17%], potatoes: 14% [6%–36%]). For PPP transport (5 studies; 10 different PPP), a geometric mean reduction of 67% (48%–94%) was derived (maize: 56% [38%–81%; 3 studies; 10 PPP]; potatoes: 91% [1 study; 4 PPP]). The application of micro-dams provides considerable reductions and can therefore be factored into the environmental exposure assessment by using percent reductions of runoff, erosion, and PPP transport or lowering the runoff CN in numerical modelling.

Effect of the Slit on the Mechanical Tearing Behavior of High-Density Polyethylene and Polyester Geocell Strips

Geocells are widely applied in numerous infrastructure constructions, like heavy-haul railways and ports. The mechanical tearing behavior of a geocell strip is crucial to the stability of the geocell-reinforced soil structures. At present, extensive studies have been conducted on the tensile characteristics of geocell strips, while limited research has been performed to investigate the post-damage mechanical tearing behavior of geocell strips. Meanwhile, there is also a lack of research on the comparison of performance of strips before and after damage. In this paper, a series of trapezoidal tearing tests were performed on high-density polyethylene (HDPE) and polyester (PET) geocell strips. The tearing test results and failure mode of trapezoidal specimens with a slit were investigated, and the effect of the slit on the strength and deformation characteristics of the specimen were discussed by introducing the “damage ratio of tearing force (RTF)” and “damage ratio of tearing displacement (RTD)”. In addition, the mechanical tearing behavior of HDPE and PET trapezoidal specimens was also compared. The test results indicated that the failure mode of HDPE and PET specimens subjected to tearing force was ductile and brittle failure. The strength and deformation characteristics of post-damage HDPE and PET trapezoidal specimens decreased. The slit had a significant impact on the tearing displacement of HDPE and PET specimens, especially the post-peak tearing displacement. The post-peak tearing displacement of HDPE was 10.99 times that of PET. The peak tearing force of the HDPE specimen without the slit was about 1.61 times that of specimen with the slit. Before local tearing, the peak tearing force of the PET specimen without the slit was about 3.27 times that of the specimen with the slit. The strength damage to the HDPE and PET geocell strips caused by the slit was 38.0%, and 69.46%. The impact of the slit on the tearing force of the PET specimen was greater than that of the HDPE, and was 1.82 times for the HDPE. This study can enhance our understanding of the mechanical tearing behavior of the geocell strip after damage and develop effective mitigation measures.

Analysis of Vulnerability Assessment Technique Implementation on Network Using OpenVas

Vulnerability Assessment is an important method for identifying and analyzing security vulnerabilities within a network system. This research aims to identify security vulnerabilities within the PT. Dutakom Wibawa Putra network using OpenVAS as a research tool. In the vulnerability analysis phase, OpenVAS is utilized to scan the PT. Dutakom Wibawa Putra network and identify existing vulnerabilities. Subsequently, an evaluation is conducted on the identified vulnerabilities, including risk assessment and necessary mitigation recommendations. The outcomes of this study provide a clear overview of the security vulnerabilities present in the PT. Dutakom Wibawa Putra network. This research using method analysis of vulnerability assessment technique implementation on network using OpenVas, several significant vulnerabilities that could impact the security of the network and systems have been identified. The findings of this analysis report can serve as a foundation for developing improved security strategies and implementing effective mitigation measures. In conclusion, this study successfully applies Vulnerability Assessment techniques to the PT. Dutakom Wibawa Putra network using OpenVAS. The identified vulnerability analysis results offer valuable insights into security weaknesses that need to be addressed. It is hoped that this research can serve as a reference for PT. Dutakom Wibawa Putra and similar organizations in enhancing their network security through the implementation of effective Vulnerability Assessment techniques.

Prioritizing science efforts to inform decision making on public lands

Public land management agencies in the US are committed to using science‐informed decision making, but there has been little research on the types and topics of science that managers need most to inform their decisions. We used the National Environmental Policy Act to identify four types of science information needed for making decisions relevant to public lands: (1) data on resources of concern, (2) scientific studies relevant to potential effects of proposed actions, (3) methods for quantifying potential effects of proposed actions, and (4) effective mitigation measures. We then used this framework to analyze 70 Environmental Assessments completed by the Bureau of Land Management in Colorado. Commonly proposed actions were oil and gas development, livestock grazing, land transactions, and recreation. Commonly analyzed resources included terrestrial wildlife, protected birds, vegetation, and soils. Focusing research efforts on the intersection of these resources and actions, and on developing and evaluating the effectiveness of mitigation measures to protect these resources, could strengthen the science foundation for public lands decision making.

A Stochastic Model of an Early Warning System for Detecting Anomalous Incidence Values of COVID-19

AbstractThe ability to identify and predict outbreaks during epidemic and pandemic events is critical to the development and implementation of effective mitigation measures by the relevant health and political authorities. However, the spatiotemporal prediction of such diseases is not straightforward due to the highly non-linear behaviour of its evolution in both space and time. The methodology proposed herein is the basis of an early warning system to predict short-term anomalous values (i.e., high and low values) of the incidence of COVID-19 at the municipality level for mainland Portugal. The proposed modelling tool combines stochastic sequential simulation and machine learning, namely symbolic regression, to model the spatiotemporal evolution of the disease. The machine learning component is used to model the 14-day incidence rate curves of COVID-19, as provided by the Portuguese Directorate-General for Health, while the geostatistical simulation component models the spatial distribution of these predictions, for a simulation grid comprising the metropolitan area of Lisbon, following a pre-defined spatial continuity pattern. The method is illustrated for a period of 5 months during 2021, and considering the entire set of 19 municipalities belonging to the metropolitan area of Lisbon, Portugal. The results show the ability of the early warning system to predict and detect anomalous high and low incidence rate values for different periods of the pandemic event during this period.

Citizen and machine learning-aided high-resolution mapping of urban heat exposure and stress

Through conversion of land cover to more built-up, impervious surfaces, cities create hotter environments than their surroundings for urban residents, with large differences expected between different parts of the city. Existing measurements of ambient air temperature and heat stress, however, are often insufficient to capture the intra-urban variability in heat exposure. This study provides a replicable method for modeling air temperature, humidity, and moist heat stress over the urban area of Chapel Hill while engaging citizens to collect high-temporal and spatially-resolved air temperature and humidity measurements. We use low-cost, consumer-grade sensors combined with satellite remote sensing data and machine learning to map urban air temperature and relative humidity over various land-cover classes to understand intra-urban spatial variability of ambient heat exposure at a relatively high resolution (10 m). Our findings show that individuals may be exposed to higher levels of air temperature and moist heat stress than weather station data suggest, and that the ambient heat exposure varies according to land cover type, with tree-covered land the coolest and built-up areas the warmest, and time of day, with higher air temperatures observed during the early afternoon. Combining our resulting dataset with sociodemographic data, policymakers and urban planners in Chapel Hill can use data output from this method to identify areas exposed to high temperature and moist heat stress as a first step to design effective mitigation measures.

Green strategies for improving urban microclimate and air quality: A case study of an Italian industrial district and facility

Densely built areas are affected by higher air-pollutant concentrations, representing a significant risk to public health. At the same time, urban settlements have a remarkable environmental impact: cities are responsible for 70% of annual carbon emissions while buildings account for 37% of global energy and process emissions. Moreover, people living in urban areas are frequently exposed to extreme micro-climate conditions caused by the urban heat island effect, related to increased external air temperature and peculiarities of the built environment. Given this framework and considering the Sustainable Development Goals, it is necessary to point out some effective and strategical mitigation measures to ameliorate micro-climate conditions, reduce pollutants concentration and enhance building performance. This paper investigates the potential advantages of green roofs as retrofitting solutions and tree planting on several micro-climate parameters and particulate matter concentration, considering an industrial district located in Italy and using ENVI-met software. The influence of the extensive green roof on energy performance is further investigated at the building level recurring to Design Builder energy models. Results showed that an extensive green roof could reduce external air temperature by up to 1.5 °C, outer surface temperature by up to 15 °C and wind speed by 50% at roof level compared to current state conditions. The application of the green roof let also to achieve energy savings of 15% for both the summer and winter seasons. Focusing on the effect on particulate matter, intensive green roof solutions proved to be more efficient in capturing air pollutants.

Cost-benefit analysis for evacuation decision-support: challenges and possible solutions for applications in areas of distributed volcanism

During a volcanic crisis, evacuation is the most effective mitigation measure to preserve life. However, the decision to call an evacuation is typically complex and challenging, in part due to uncertainties related to the behaviour of the volcano. Cost-benefit analysis (CBA) can support decision-makers: this approach compares the cost of evacuating versus the expected loss from not evacuating, expressed as a ‘break-even’ probability of fatality. Here we combine CBA with a Bayesian Event Tree for Short-term Volcanic Hazard (BET_VHst) to create an evacuation decision-support tool to identify locations that are cost-beneficial to evacuate in the event of volcanic unrest within a distributed volcanic field. We test this approach with the monogenetic Auckland Volcanic Field (AVF), situated beneath the city of Auckland, New Zealand. We develop a BET_VHst for the AVF, extending a recently revised Bayesian Event Tree for Eruption Forecasting (BET_EF) to consider the eruptive style, phenomena produced, and the impact exceedance probability as a function of distance. The output of the BET_VHst is a probability of volcanic hazard impact at a given location. Furthermore, we propose amending the weight of the monitoring component within the BET_VHst framework to a transitional parameter, addressing limitations identified in a previous study. We examine how three possible transitional monitoring component weights affect the spatial vent likelihood and subsequent BET_VHst outputs, compared to the current default weight. For the CBA, we investigate four thresholds, based on two evacuation durations and two different estimates for the value of life that determine the cost of not evacuating. The combinations of CBA and BET_VHst are tested using a synthetic unrest dataset to define an evacuation area for each day. While suitable evacuation areas were identified, there are further considerations required before such an approach can be applied operationally to support crisis management.

Porpoises, by‐catch and the ‘pinger’ conundrum

Abstract The UK is committed to reducing or eliminating the by‐catch of protected species in fisheries. Of key concern is the by‐catch of harbour porpoise in static nets. Fishers do not want to catch harbour porpoise, and the only proven effective mitigation measure currently available is an acoustic device known as a ‘pinger’. Legislative requirements for the mandatory use of pingers on larger vessels (i.e. those greater than 12 m in length) has resulted in a by‐catch reduction of approximately 17% for the UK fleet annually. In most areas where the risk of by‐catch is high (i.e. the southern North Sea, English Channel, and Bristol Channel), smaller inshore vessels (i.e. less than 12 m in length) account for over 90% of the fishing effort (determined as days at sea). Small inshore vessels are not permitted to use pingers without a licence. The information required for a licence, however, makes it extremely difficult for fishers to obtain one. Without access to effective mitigation in most of the static net fleet, it seems unlikely that the UK will meet its ambition to minimize or eliminate harbour porpoise by‐catch. Finding workable and effective solutions for smaller vessels is essential. As harbour porpoise by‐catch is such a rare event, it is unlikely that the mandatory use of pingers on all static net vessels will be cost‐effective. Nor is such widespread deployment considered desirable because of the potential consequences on the conservation status of harbour porpoise. A potential solution within the current UK legislative framework is proposed that would facilitate the use of pingers in small‐scale localized fisheries with a high risk of by‐catch until a suitable mitigation alternative to pingers becomes available.

Developing a framework to achieve resilience in the oil and gas supply chain during logistics disruptions: an empirical study

PurposeOil and gas sector has more disruptions regarding its logistics management than any other industry. It is critical to understand which external security threats disrupt the oil and gas supply chain (OGSC). Recently, the time interval between these disruptions became frequent. the purpose of this paper is to identify key logistics elements that lead to such disruptions which would greatly benefit the oil and gas industry in developing more effective mitigation measures and resilient practices in the future.Design/methodology/approachThis research develops the theoretical framework through a critical review of all theories related to resilience, logistics disruptions and mitigation methods in the oil and gas industry. Afterward, semi-structured interviews were conducted with executives in the Egyptian oil and gas industry to develop a conceptual framework. Finally, an empirical study was conducted through questionnaires with managers in the Egyptian oil and gas sector to develop the applied framework.FindingsThis research revealed that achieving an elevated level of flexibility, redundancy, visibility and collaboration in the Egyptian OGSC will significantly increase the level of resilience in the sector and consequently help in mitigating probable logistics disruptions.Practical implicationsThis research contributes to academia by providing a conceptual framework for the most common logistics disruptions in the Egyptian OGSC and providing practitioners with the best resilience practices that are feasible and effective in mitigating logistics disruptions.Originality/valuePrevious research studied disruptions in OGSC from different perspectives: economic, social, political, technical, safety, legal and environmental perspectives, but no research highlighted the logistics perspective in the Egyptian context, to the best of the authors’ knowledge.

Deca-BDE emissions, validation, and environmental fate in China

Decabromodiphenyl ether (Deca-BDE) was officially listed in Annex A of the Stockholm Convention for persistent organic pollutants (POPs). It is necessary to establish its emission inventory to help reduce Deca-BDE contamination in the environment. We established a comprehensive Deca-BDE emission inventory in China. The results reveal that, from 2015 to 2017, the Deca-BDE emissions in its production source (source I) were less altered but increased annually in flame retarded plastics processing (source II), Deca-BDE-containing products usage (source III), and electronic waste (e-waste) treatment (source IV). We show that Deca-BDE emissions declined significantly in sources I and II but grew in source III and source IV from 2017 to 2018. We set up the provincial emission inventory to a gridded map on a spatial resolution of 0.25°× 0.25° latitude/longitude. The gridded inventory was incorporated into ChnMETOP model to simulate Deca-BDE concentrations in air and soil, and the modeled concentrations were compared to field-sampling data. The results show that the Deca-BDE emission inventory developed in this study agreed well with observed data, demonstrating that the Deca-BDE inventory in China developed in the present study is reliable. The inventory provides a support for quantifying human exposure risk to Deca-BDE and developing effective mitigation measures to mitigate Deca-BDE emissions.