Sequential Scenario Research Articles

Rapid, Accurate and Reproducible Prediction of the Glass Transition Temperature Using Ensemble-Based Molecular Dynamics Simulation.

For the computational design of new polymeric materials, accurate methods for determining the glass transition temperature (Tg) are required. We apply an ensemble approach in molecular dynamics (MD) and examine its predictions of Tg and their associated uncertainty. We separate the uncertainty into the aleatoric contributions arising from dynamical chaos and that due to the computational scenarios chosen to compute Tg. We propose a new scenario for computing Tg, where the density-temperature behavior is computed by running all temperatures concurrently, rather than invoking a sequential approach, thereby significantly reducing wall-clock time from days to several hours without increasing the aleatoric uncertainty. On comparing concurrent and sequential scenarios on six highly cross-linked epoxy resins cured with aromatic amines, we find excellent agreement with our experimentally determined Tg using dynamical mechanical analysis for both scenarios. The confidence intervals are found to scale as N-0.5, where N is the number of members in the ensemble, implying that ensembles comprised of at least ten replicas are required to predict Tg using MD with 95% confidence intervals of less than 20 K. The optimal MD simulation protocol is 4 ns of burn-in time followed by 2 ns of production run time.

Assessing the Deterrent Effects of Ignition Interlock Devices

IntroductionIgnition interlock devices installed after conviction for driving under the influence of alcohol (DUI) have been shown to reduce subsequent DUI arrests (specific deterrence). However, there is little evidence on how interlock-device penalties might affect general deterrence, that is, deterring people from driving after consuming alcohol prior to a DUI conviction. MethodsA discrete choice experiment was conducted and data were analyzed in 2023 with 583 U.S.-based adults who consume alcohol at least once in the past week to assess the deterrent effects of five different penalties (fine, jail time, interlock device, license suspension, alcohol treatment) for alcohol-impaired driving under randomized sequential scenarios of high (20% chance of being caught) and low (1%) police enforcement. Participants resided in 46 states. ResultsDeterrent effects of an interlock penalty, operationalized as having to install an interlock device for one year, are large and on par with a twentyfold increase in police enforcement activity (from 1% chance of being caught to 20%), or a $2,000 increase in the DUI fine under the status quo enforcement regime. On average, a 1-year interlock penalty had the same deterrent effect as a 10-day increase in jail time. ConclusionsWider use of interlock devices as a DUI penalty could have large deterrent effects, independent of their ability to physically prevent the motor vehicle of an intoxicated driver from starting. The deterrent effect documented here adds to evidence on interlock devices’ overall effectiveness as well as their potential to shift DUI penalties away from criminalization (jail time) and towards immobilization and rehabilitation.

Producing Green or Brown? A Game of Green Innovation in an Asymmetric Oligopoly

As consensus grows for low-carbon development, innovation becomes vital for green growth, given the substantial technology adoption needed for long-term environmental targets. This paper explores market-driven incentives for green product innovation in an asymmetric duopoly using a game theory approach without relying on direct government intervention. The roles that market dynamics and rivalry have on the supply of green or brown products are explored in simultaneous and sequential scenarios, considering technology costs, demand-creating effects, rivalry gains, and information availability. Results reveal that a fully green market is contingent on low innovation costs, depending especially on the magnitude of demand creation effects. Notably, product differentiation occurs only under extreme cost asymmetry. Recommendations underscore the importance of incentivising low-cost innovations, assessing the impact of product differentiation and diversity, especially concerning lower-income consumers, and proposing measures to improve the transparency of firms’ strategic choices.

Contextuality as a Precondition for Quantum Entanglement.

Quantum theory features several phenomena which can be considered as resources for information processing tasks. Some of these effects, such as entanglement, arise in a nonlocal scenario, where a quantum state is distributed between different parties. Other phenomena, such as contextuality, can be observed if quantum states are prepared and then subjected to sequences of measurements. We use robust remote state preparation to connect the nonlocal and sequential scenarios and provide an intimate connection between different resources: We prove that entanglement in a nonlocal scenario can arise only if there is preparation and measurement contextuality in the corresponding sequential scenario and that the absence of entanglement implies the absence of contextuality. As a direct consequence, our result allows us to translate any inequality for testing preparation and measurement contextuality into an entanglement test; in addition, entanglement witnesses can be used to design novel contextuality inequalities.

Quantifying the intrinsic randomness in sequential measurements

In the standard Bell scenario, when making a local projective measurement on each system component, the amount of randomness generated is restricted. However, this limitation can be surpassed through the implementation of sequential measurements. Nonetheless, a rigorous definition of random numbers in the context of sequential measurements is yet to be established, except for the lower quantification in device-independent scenarios. In this paper, we define quantum intrinsic randomness in sequential measurements and quantify the randomness in the Collins–Gisin–Linden–Massar–Popescu inequality sequential scenario. Initially, we investigate the quantum intrinsic randomness of the mixed states under sequential projective measurements and the intrinsic randomness of the sequential positive-operator-valued measure (POVM) under pure states. Naturally, we rigorously define quantum intrinsic randomness under sequential POVM for arbitrary quantum states. Furthermore, we apply our method to one-Alice and two-Bobs sequential measurement scenarios, and quantify the quantum intrinsic randomness of the maximally entangled state and maximally violated state by giving an extremal decomposition. Finally, using the sequential Navascues–Pironio–Acin hierarchy in the device-independent scenario, we derive lower bounds on the quantum intrinsic randomness of the maximally entangled state and maximally violated state.

What is simulation-based medical education (SBME) debriefing in prehospital medicine? A qualitative, ethnographic study exploring SBME debriefing in prehospital medical education

IntroductionSimulation-based medical education (SBME) debriefing – a construct distinct from clinical debriefing – is used following simulated scenarios and is central to learning and development in fields ranging from aviation to emergency medicine. However, little research into SBME debriefing in prehospital medicine exists. This qualitative study explored the facilitation and effects of prehospital SBME debriefing, and identified obstacles to debriefing, using the London’s Air Ambulance Pre-Hospital Care Course (PHCC) as a model.MethodEthnographic observations of moulages and debriefs were conducted over two consecutive days of the PHCC in October 2019. Detailed contemporaneous field notes were made and analysed thematically. Subsequently, seven one-to-one, semi-structured interviews were conducted with four PHCC debrief facilitators and three course participants to explore their experiences of prehospital SBME debriefing. Interview data were transcribed and analysed thematically.ResultsFour overarching themes were identified: approach to facilitation of debriefs, effects of debriefing, facilitator development, and obstacles to debriefing.The unpredictable debriefing environment was seen as both hindering and, paradoxically, benefitting SBME debriefing. Despite using varied debriefing structures, facilitators emphasised similar key debriefing components including exploring participants’ reasoning and sharing experiences to improve learning and prevent future errors.Debriefing was associated with three effects: releasing emotion; learning and improving, particularly compound learning as participants progressed through sequential scenarios; and the application of learning to clinical practice. Facilitator training and feedback were central to facilitator learning and development.Several obstacles to debriefing were identified, including mismatch of participant and facilitator agendas, pressure and time.ConclusionsSBME debriefing in prehospital medicine is complex, requiring an understanding of participant agendas and facilitator experience to maximise participant learning. Aspects unique to prehospital SBME debriefing were identified, notably, the unpredictable debriefing environment, and the paradoxical benefit of educational obstacles for learning. Aspects of SBME debriefing not extensively detailed in the literature were also highlighted, such as compound participant learning, facilitator candour, and facilitator learning, which require further exploration.

Sequential diversification with Miocene extinction and Pliocene speciation linked to mountain uplift explains the diversity of the African rain forest clade Monodoreae (Annonaceae).

Throughout the Cenozoic, Africa underwent several climatic and geological changes impacting the evolution of tropical rain forests (TRFs). African TRFs are thought to have extended from east to west in a 'pan-African' TRF, followed by several events of fragmentation during drier climate periods. During the Miocene, climate cooling and mountain uplift led to the aridification of tropical Africa and open habitats expanded at the expense of TRFs, which probably experienced local extinctions. However, in plants, these drivers were previously inferred using limited taxonomic and molecular data. Here, we tested the impact of climate and geological changes on diversification within the diverse clade Monodoreae (Annonaceae) composed of 90 tree species restricted to African TRFs. We reconstructed a near-complete phylogenetic tree, based on 32 nuclear genes, and dated using relaxed clocks and fossil calibrations in a Bayesian framework. We inferred the biogeographical history and the diversification dynamics of the clade using multiple birth-death models. Monodoreae originated in East African TRFs ~25 million years ago (Ma) and expanded toward Central Africa during the Miocene. We inferred range contractions during the middle Miocene and document important connections between East and West African TRFs after 15-13 Ma. Our results indicated a sudden extinction event during the late Miocene, followed by an increase in speciation rates. Birth-death models suggested that African elevation change (orogeny) is positively linked to speciation in this clade. East Africa is inferred as an important source of Monodoreae species, and possibly for African plant diversity in general. Our results support a 'sequential scenario of diversification' in which increased aridification triggered extinction of TRF species in Monodoreae. This was quickly followed by fragmentation of rain forests, subsequently enhancing lagged speciation resulting from vicariance and improved climate conditions. In contrast to previous ideas, the uplift of East Africa is shown to have played a positive role in Monodoreae diversification.

Event-related potentials in response to early terminated and completed sequential decision-making

The process of outcome evaluation effectively navigates subsequent choices in humans. However, it is largely unclear how people evaluate decision outcomes in a sequential scenario, as well as the neural mechanisms underlying this process. To address this research gap, the study employed a sequential decision task in which participants were required to make a series of choices in each trial, with the option to terminate their choices. Based on participants' decisions, two outcome patterns were classified: the “reached” condition and the “unreached” condition, and the event-related potentials (ERPs) were recorded. Further, in the unreached condition, we investigated how the distance (i.e., the position interval between the actual outcome and potential outcome) modulated outcome evaluation. Behavioral data showed a higher emotion rating when people got a reward rather than a loss (i.e., the reached condition), while the opposite was true in the unreached condition. ERP results showed a larger feedback-related negativity (FRN), a smaller P3, and a larger late positive potential (LPP) when people got a loss compared to a reward. Importantly, a hierarchical processing pattern was found in the unreached condition: people processed separately the potential outcome and the distance at the early stage, manifested in the FRN amplitude; subsequently, the brain focused on the distance—a lower distance elicited an enhanced P3 amplitude. Finally, the potential outcome and distance were processed interactively in the LPP amplitude. Overall, these findings shed light on the neural underpinnings of outcome evaluation in sequential decision-making.

Dual Strategy of Reconfiguration with Capacitor Placement for Improvement Reliability and Power Quality in Distribution System

The demand for electrical power has been increasing rapidly due to higher industrial output and deregulation. The concerns have been raised about the ability of distribution networks to provide adequate power for the customers with an appropriate level of quality and reliability. To ameliorate the performance of the radial distribution system (RDS), the optimal capacitor placement (OCP), and the distribution system reconfiguration (DSR) strategies have been implemented in the current work to achieve the highest power quality and system reliability in a balanced manner at the same time. Three different scenarios were implemented, the first scenario of dual sequential (OCP after DSR), the second scenario of dual sequential (DSR after OCP), and the third scenario of dual simultaneous (DSR with OCP). These scenarios were tested on typical 33 and 69 bus IEEE RDS using the binary salp swarm algorithm (BSSA) based on the multiobjective functions (MOFs), in order to identify the most effective scenario performance that achieved the highest power quality and system reliability. The MOF was formulated to improve the power quality by increasing the voltage buses and reducing the power losses. While the constraints include limits of system reliability indices to provide optimal constraints on negative interactions of power quality. The simulation results demonstrate that the second scenario of dual sequential (DSR after OCP) provide superior in comparison with the first scenario of dual sequential (OCP after DSR) for enhancing the RDS reliability indices, voltage buses, and reducing power losses. Finally, the best result can be realized with dual simultaneous (DSR and OCP) in the third scenario compared to the dual sequential scenarios.

Introduction of the carbon tax in Italy: Is there room for a quadruple-dividend effect?

This study seeks to examine the environmental and societal impacts of a carbon tax in Italy, where the policy has yet to be implemented but has been the subject of much debate. We use numerical simulations based on the EUROGREEN macro-system dynamic model (D’Alessandro et al., 2020) to evaluate the potential benefits and drawbacks of this policy from 2010 to 2050.We employ a sequential scenario approach, starting with a baseline that incorporates Italy’s Integrated National Energy and Climate Plan (PNIEC), followed by the introduction of a gradually increasing carbon tax. Additionally, we test two hypotheses regarding the possible adaptive behaviors of consumers and producers in response to the policy. Our analysis evaluates the long-term impacts of the carbon tax on GDP, unemployment, public debt, carbon emissions, and income inequality, in pursuit of a ”quadruple-dividend” effect.Our findings suggest that the carbon tax: (i) has a limited impact on reducing carbon emissions, with a difference of only 2% compared to the PNIEC by 2050, (ii) has the potential to mitigate regressive effects through the redistribution of its revenue to low-income households, resulting in an improvement of approximately 2 Gini-points compared to the PNIEC, and (iii) can achieve a quadruple-dividend effect only if consumers and industries adapt their behavior to the policy.Our research argues that Italy could reap the benefits of a carbon tax, with the revenue being redistributed to low-income households, leading to a more equitable and sustainable energy transition. This can only be achieved by combining top-down policies with bottom-up initiatives and public interventions, making environmental taxation more acceptable to the general public.

Sharing entanglement of the Werner state by arbitrarily many independent observers

The problem of sharing quantum correlations is an interesting problem in the study of quantum information theory. Silva et al. proposed the study of sharing quantum nonlocality at first. They studied the fundamental limits on nonlocality, asking whether a single pair of entangled qubits could generate a long sequence of nonlocal correlations. At the same time, the sequential scenario was also introduced first, in which Alice and Bob each have half of a pair of entangled qubit states. The first Bob measures his half and then passes his part to a second Bob who measures again and so on. Obviously, even partial preservation of entanglement in a shared state in spite of a few sequences of local operations performed by the sharing parties can be important for information processing schemes in which entanglement is utilized as a resource. Thus, the problem of sharing quantum entanglement has also been extensively investigated. Recently, Srivastava et al. proved that there exist a class of T-states whose entanglement can be shared by arbitrarily many independent observers in [<ext-link ext-link-type="uri" xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="http://doi.org/10.1103/PhysRevA.105.062413"><i>Phys. Rev. A</i> 2022 <b>105</b> 062413</ext-link>]. Here, we want to find whether there are other entangled states that can be shared entanglement arbitrarily many times. In this paper, we consider the problem of sharing quantum entanglement when the initial shared state is a two-qubit entangled Werner state. The goal is to maximize the number of Bobs that can share entanglement with a single Alice. By suitably choosing the entanglement witness operator and the unsharp measurement settings by the Bobs, we prove that there exist two-qubit entangled initial shared Werner states whose entanglement can be detected by arbitrarily many sequential observers Bobs with a single Alice. Then, we also consider the special case of the Werner state, that is, the maximally entangled state as the initial shared state. In this case, its entanglement can also be witnessed arbitrarily many times, and the number of Bobs increases with the decrease of parameter.

Interactive effects of increased salinity and heatwaves on freshwater zooplankton communities in simultaneous and sequential treatments

Abstract Elevated lake chloride concentration has been observed in many regions, due to human activities such as mining, agriculture, and urbanisation. Meanwhile, lakes are also experiencing increasing frequency and intensity of heatwaves. The combination of elevated salinity and heatwaves has not been thoroughly studied in freshwater communities, limiting our ability to predict outcomes of future disturbances. We conducted a mesocosm experiment to investigate the individual and interactive effects of increased salinity and heatwaves on a freshwater zooplankton community. The combined effects of the two stressors were examined in two scenarios: when they occurred simultaneously and when a heatwave was preceded by an 8‐week increase in salinity. We expected to see a synergistic effect when the two stressors were applied simultaneously, as organisms might experience energy deficiency due to physiological changes caused by salinity stress and be overwhelmed by the heat treatment. When the two stressors were applied sequentially, we expected them to act independently as the two stressors trigger different physiological responses and physiological homeostasis may have already recovered from previous salt exposure and not influence an organism's response to a subsequent stressor. Individually, increased salinity and heatwave conditions both impaired zooplankton communities with largest effects on copepod nauplii and cladocerans. Together, these stressors caused antagonistic effects on total zooplankton abundance and biomass in both the simultaneous and sequential scenarios, with the combined effects being similar to the salt‐only effects. Our experiment illustrates the potential for heatwaves to have hidden effects when they occur in lakes experiencing salinisation. The findings suggested that the two stressors negatively impacted some zooplankton taxonomic groups, and at the community level, they acted antagonistically such that the occurrence of a 3‐day heatwave did not cause any additional loss of abundance or biomass regardless of whether the community was exposed to the sequential or simultaneous scenario. Our findings also illustrated that even when the two stressors were decoupled in time, the community could still be influenced by a previous stressor.

Finite element modeling of reinforced concrete short columns subjected to shear in two perpendicular directions

PurposeShort columns can cause serious damage when subjected to an earthquake due to their high stiffness with low ductility. These columns can be exposed to multidirectional shear forces, which encouraged this study to investigate the behavior of structural short columns under bi-directional shear.Design/methodology/approachFinite element analysis (FEA) using ABAQUS is conducted and calibrated based on experimental data tested by previous researchers who studied the uni-directional behavior of short columns subjected to cyclic shear displacements. Then, the calibrated column models are further investigated to study the influence of bidirectional cyclic shear. Two scenarios are investigated, namely “simultaneous” and “sequential,” to compare the performance in terms of shear strength reduction.FindingsThe results show that the shear strength reduction significantly appears when 1:1 simultaneous bi-directional cyclic shear is applied. However, the shear reduction is more significant when the sequential scenario is applied. The seismic forces or deformations applied in orthogonal directions should be combined to achieve the maximum seismic response of structures as specified in Federal Emergency Management Agency (FEMA) 356 Standard. Finally, the combinations presented in literature to consider bi-directional shear are investigated. Based on FE results, the effect of applied 1:0.30 bi-directional cyclic shear simultaneously does not result in significant effect on the considered columns properly design for seismic forces.Originality/valueTo investigate the effect of multidirectional shear forces on the shear strength capacity of short columns, the presented effect of multidirectional shear forces in literature to consider bi-directional shear are investigated.

Signaling between time steps does not allow for nonlocality beyond hidden nonlocality

Hidden nonlocality is the phenomenon that entangled states can be local in the standard Bell scenario but display nonlocality after local filtering. However, there exist entangled states for which all measurement statistics can be described via a local hidden variable model even after local filtering. In this work we consider the scenario that measurement outcomes and settings of Alice can influence measurements of Bob in subsequent time steps (and vice versa), however, there is no signaling among them for measurements at the same time step. We show that in this scenario states that only display local statistics after local filtering remain local even when considering the complete statistics of arbitrary sequences and therefore no advantage can be gained by performing longer sequences in this scenario. We first determine the extreme points of the polytope defined by the no-signaling conditions within the same time step and the arrow-of-time constraints. Based on these results we introduce a notion of locality and provide a complete representation of the corresponding local polytope in terms of inequalities in the simplest scenario. These results imply that in the scenario considered here there is no nonlocality beyond hidden nonlocality. We further propose a device-dependent Schmidt number witness and we compare our finding to known local models in the sequential scenario.

Computing Quantal Stackelberg Equilibrium in Extensive-Form Games

Deployments of game-theoretic solution concepts in the real world have highlighted the necessity to consider human opponents' boundedly rational behavior. If subrationality is not addressed, the system can face significant losses in terms of expected utility. While there exist algorithms for computing optimal strategies to commit to when facing subrational decision-makers in one-shot interactions, these algorithms cannot be generalized for solving sequential scenarios because of the inherent curse of strategy-space dimensionality in sequential games and because humans act subrationally in each decision point separately. We study optimal strategies to commit to against subrational opponents in sequential games for the first time and make the following key contributions: (1) we prove the problem is NP-hard in general; (2) to enable further analysis, we introduce a non-fractional reformulation of the direct non-concave representation of the equilibrium; (3) we identify conditions under which the problem can be approximated in polynomial time in the size of the representation; (4) we show how an MILP can approximate the reformulation with a guaranteed bounded error, and (5) we experimentally demonstrate that our algorithm provides higher quality results several orders of magnitude faster than a baseline method for general non-linear optimization.

VINTERGATAN III: how to reset the metallicity of the Milky Way

ABSTRACT Using the cosmological zoom simulation VINTERGATAN, we present a new scenario for the onset of star formation at the metal-poor end of the low-[α/Fe] sequence in a Milky Way-like galaxy. In this scenario, the galaxy is fuelled by two distinct gas flows. One is enriched by outflows from massive galaxies, but not the other. While the former feeds the inner galactic region, the latter fuels an outer gas disc, inclined with respect to the main galactic plane, and with a significantly poorer chemical content. The first passage of the last major merger galaxy triggers tidal compression in the outer disc, which increases the gas density and eventually leads to star formation, at a metallicity 0.75 dex lower than the inner galaxy. This forms the first stars of the low-[α/Fe] sequence. These in situ stars have halo-like kinematics, similar to what is observed in the Milky Way, due to the inclination of the outer disc that eventually aligns with the inner one via gravitational torques. We show that this tilting disc scenario is likely to be common in Milky Way-like galaxies. This process implies that the low-[α/Fe] sequence is populated in situ, simultaneously from two formation channels, in the inner and the outer galaxy, with distinct metallicities. This contrasts with purely sequential scenarios for the assembly of the Milky Way disc and could be tested observationally.

Designing blood supply policy using simulation approach

Blood transfusion is one of the critical requirements of many medical treatments. To ensure timely blood availability, the Indonesian Red Cross (Palang Merah Indonesia/PMI) has to tackle the blood supply challenges of stockouts and overdates. This research aims to develop a simulation model to determine the blood supply policy to reduce stockouts and overdates. The simulation model was developed according to the existing system at UDD PMI Padang. Simulation experiments were then attempted with some sequential scenarios and carried out on variables that affect the blood supply. The simulation result recommends the blood supply policy to reduce blood stockout and overdate at a higher service level, at conditions of the blood demand is assumed to be constant or increased.

Sequential Bifurcation Trees to Chaos in Nonlinear Time-Delay Systems

Abstract In this book, the global sequential scenario of bifurcation trees of periodic motions to chaos in nonlinear dynamical systems is presented for a better understanding of global behaviors an...

Supply commitment contract in capacity allocation games

This paper considers a supply chain with one supplier and two retailers. The supplier has limited normal capacity. When the orders of two retailers exceed the capacity, the supplier can satisfy the retailers with the limited normal capacity, or he can start an emergent production to increase his capacity in a short time with a high unit production cost. When the cost of quickly expanding capacity is lower than the market price, it is profitable for the whole system to start the emergent production. But the supplier has no incentives to do additional production if his cost is higher than the wholesale price. To resolve this issue, we propose a supply commitment contract that the supplier will fully fill a retailer’s order if the retailer pays a premium to the supplier. We consider a practical setting that each retailer has private information on her average demand. Two contracting scenarios of the supplier are compared: contracting with the two retailers simultaneously (the simultaneous scenario) and sequentially (the sequential scenario). It is shown that the retailers will adopt the threshold strategy based on their private demand information to pay the premium. By numerically studies, we further illustrate the supplier’s optimal contract choices and the consequent system performance. First, the suppliers always prefer the retailers to move simultaneous although the supplier’s profit is only slightly higher than that of the sequential scenario; second, the supplier sets a lower wholesale price and a higher commitment fee in the sequential scenario than those of simultaneous scenario; finally, the sequential scenario is a better choice from the perspectives of both the whole supply chain system and the retailers. Our research recommends the sequential moving in the supply commitment contract that it benefits the whole supply chain system with only slightly less efficient for the supplier.

Enhancement of Naphthalene Degradation by a Sequential Sulfate Injection Scenario in a (Semi)-Arid Coastal Soil: a Flow-Through Reactor Experiment

Engineered sulfate injection has been introduced as an effective technology to enhance the remediation of soil and groundwater contaminated by petroleum hydrocarbons. While some studies indicate that sulfate injection is a promising method for the treatment of hydrocarbon-contaminated subsurface systems, its application in the brackish soil environments is unknown. In this study, we explored related geochemical indicators along with soil adsorption and dissolved phase concentrations to provide an improved understanding of the hydrocarbon-contaminated subsurface responses to the sulfate injection in brackish environments. A series of flow-through experiments representing in situ groundwater anaerobic bioremediation were conducted and two sulfate injection episodes were applied to examine the degradation of dissolved naphthalene under low salinity and brackish conditions. As opposed to the substantial body of previous studies that salinity restricts biodegradation, the results from this study showed that naphthalene anaerobic degradation was more stable once the salinity was as high as that at the sampling location in the coastal brackish environment. While increasing naphthalene concentration from 4 to 12 mg L−1 did not limit biodegradation efficiency under brackish condition similar to the sampling location, it adversely restricted the developed reducing conditions and biodegradation process under low salinity conditions. This highlights the adaption of the microbial communities within the soil to the brackish environment at the sampling location suggesting that changing the salinity during engineered sulfate application can make the remediation process more susceptible against the environmental stresses and substrate toxicity. The results of this study provide insight into the engineered sulfate application as a remediation strategy for potential removal of dissolved naphthalene from the contaminated brackish groundwater.