Search Results (59)

The increasing risk of air pollution in closed areas like passenger vehicles requires smart and real-time air quality reading solutions. Gases such as carbon monoxide (CO)—which is colorless and odorless and is produced by exhaust systems—air conditioners, and combustion sources are very dangerous to health because they can cause respiratory distress and poisoning at high levels. Traditional in-vehicle CO monitoring systems use a single-point sensor and a fixed threshold, which are insufficient in a dynamic cabin environment subject to factors such as vehicle size, ventilation rate, number of occupants, and incoming traffic. To address these drawbacks, this paper proposes a new E-Nose system with Virtual Sensor-Augmented Embedded Intelligence to estimate the CO concentration in vehicle cabins in real time. The system combines data from cheap gas sensors and improves it using virtual sensor machine learning models trained to predict or enhance sensor responses in real time. Embedded intelligence, deployed locally on edge hardware, supports low-latency processing, dynamic calibration, and noise filtering to respond to fluctuating environmental conditions adaptively. This architecture enables more accurate, robust, and context-aware estimation of CO levels compared to traditional threshold-based methods. Experimental validation across varied vehicular scenarios demonstrates superior precision and responsiveness, providing timely warnings even under complex dispersion patterns. Classifier Gradient Boosting, which builds an ensemble of weak learners sequentially, matched the Random Forest with 99.94% training and 98.59% model accuracy, confirming its strong predictive capability. The system is designed to be cost-effective, scalable, and easily integrable into modern automotive platforms. This study also contributes to the field of smart ecological recording and demonstrates the effectiveness of the virtual sensor-enhanced embedded system as an effective way to improve passenger safety by providing pre-emptive on-board air quality monitoring. Full article

Driven by rapid global urbanization and expanding urban footprints, air pollution, particularly from industrial emissions and vehicular exhaust, has intensified, with rising concentrations of inhalable particulate matter (PM) posing direct threats to public health. To address this challenge, we conducted field measurements of ambient PM concentrations across diverse urban plant communities and quantitatively compared their capacity to mitigate four key size-fractionated pollutants: total suspended particles (TSPs), PM₁₀, PM_2.5, and PM₁. Our objective was to identify the most effective plant community type for PM abatement in urban settings. Results demonstrate that: (1) evergreen broad-leaved forests exhibit the highest overall PM removal efficiency among all studied communities; (2) removal efficacy declines markedly with decreasing particle size, indicating limited capacity to capture ultrafine particles (e.g., PM₁); and (3) seasonal performance peaks in summer, especially for deciduous broad-leaved forests attributable to maximal leaf area index, enhanced stomatal activity, and favorable meteorological conditions. By rigorously evaluating species composition, canopy structure, and seasonal dynamics, this study provides empirically grounded guidance for evidence-based urban greening strategies aimed at optimizing airborne particulate mitigation worldwide. Full article

Hourly concentrations of PM_2.5-bound elements were continuously monitored in Windsor, Canada, from April 2021 to April 2023. Health risk assessment methods of the USEPA were utilized to quantify lifetime cumulative cancer risks (CRs) using six PM_2.5-bound elements, and chronic non-cancer hazard quotients (HQs) using 11 elements, for each season, each source factor, and each hour of day. The two-year average PM_2.5 mass concentration was 9.2 μg/m³, slightly exceeding Ontario’s Ambient Air Quality Criteria of 8.8 μg/m³. A discernible diurnal concentration pattern was noted for most elements, peaking during morning rush hours and tapering during the daytime, largely attributed to local human activities and changes in atmospheric mixing heights. Despite this, both the total lifetime cumulative CR (4.1 × 10⁻⁵) and non-cancer total HQ (0.82) from exposure to ambient elements remained below the corresponding USEPA-acceptable levels. The seasonal variation in CRs and HQs was minimal. However, the diurnal variation was strong, with higher risks during morning rush hours (6:00–8:00) when traffic volume peaks, and lower risks during the daytime (12:00–20:00) when atmospheric mixing height is enhanced. Metal processing emerged as the most significant contributor to the total CR (52%) and HQ (60%), followed by coal/heavy oil burning (19% and 16%, respectively), and vehicular exhaust (19% and 12%, respectively). The remaining two source factors accounted for 10% of CR and 12% of HQ. Cd (62%) was the largest contributor to CRs, followed by Cr(VI) (25%), Co (6%), As (5%), Ni (2%), and Pb (<0.1%). Similarly, Cd dominated HQs (73%), followed by Mn (11%), Ni (6.3%), with the remaining eight elements collectively contributing 9.7%. Although levels of CRs and HQs are low, efforts to mitigate ambient Cd emissions from metal processing sources will help reduce exposure and protect the environment and human health, given Cd is the primary contributor to the total CR and HQ during the study period. Full article

The evaporation of gasoline serves as an important contributor to volatile organic compounds (VOCs) within urban regions. However, most previous studies have focused on summertime gasoline evaporation, with relatively limited attention to wintertime emissions. Within the present research, online VOC monitoring was carried out at three urban locations across Beijing over the winter seasons of 2014–2015 and 2021–2022. A wintertime gasoline evaporation VOC source profile was established using enhancement ratio analysis and positive matrix factorization, based on observations at a site near a gasoline station. The results show that n-butane dominated wintertime gasoline evaporation VOCs (35%), exceeding i-pentane (20%), in contrast to the i-pentane dominance reported in previous studies. The chemical mass balance (CMB) model was then applied to apportion VOC sources and assess the sensitivity to different gasoline evaporation source profiles. Gasoline evaporation was found to contribute 12–17% of wintertime VOCs, 2.3–3 times higher than estimates based on the literature profiles. Comparisons between the winters of 2014–2015 and 2021–2022 reveal a 63% decrease in VOC concentrations, with the coal combustion contribution dropping by 85% and vehicular exhaust and gasoline evaporation by 51–60%. These findings demonstrate that gasoline evaporation remains a non-negligible VOC source in winter and highlight that season- and observation-based source profiles are essential for reliable VOC source apportionment and effective air quality management. Full article

Traffic congestion not only severely impacts residents’ daily travel quality and increases travel costs, but also triggers traffic accidents, causes environmental pollution, and leads to resource waste. There is a practical need to implement engineering measures simultaneously across multiple intersections to mitigate urban road traffic congestion, which necessitates in-depth research into selecting critical intersection clusters. Based on existing research, the relationship between vehicle emissions and the degree of saturation was derived. The network efficiency evaluation metric was refined using the degree of saturation, and a model linking vehicle emissions to network efficiency was established. A validation experiment was designed using the core road network of Xining City, Qinghai Province, as an example. The results indicate that vehicular exhaust emissions per kilometer are proportional to the saturation degree metric value. The network efficiency metric is inversely proportional to the network’s overall (or average) saturation degree. Vehicular exhaust emissions exhibit an inverse relationship with network efficiency. As the road traffic operational state shifts from congestion to free-flow conditions, for every 1-unit increase in network efficiency value, the average exhaust emissions per vehicle per kilometer decrease by 3.976 kg. Different congestion mitigation node selection schemes correspond to varying total emission reductions during the morning peak. When ranked by the magnitude of increase in network efficiency (from the largest increase to the smallest), the corresponding total morning peak emission reductions gradually decrease in a stepwise manner. According to the $C_{60}^2$ and $C_{60}^3$ experimental results, compared to the worst node cluster selection scheme, the optimal node cluster selection scheme can reduce vehicular exhaust emissions by 4441 kg and 6616 kg, respectively. These findings provide valuable theoretical and practical insights for implementing energy-saving and emission reduction strategies in urban traffic management. Full article

Accurate analysis of trace elements in particulate matter (PM) emitted by brake systems critically depends on the filter selection and handling processes, which can significantly impact analytical results due to contamination and elemental interference from filter elemental composition. This study systematically evaluated two widely used filter types, EMFAB (borosilicate glass microfiber reinforced with PTFE) and Teflon (PTFE), for their suitability in the trace element determination of brake-wear PM₁₀ collected using a tribometer set-up. A total of twenty-three PM₁₀ samples were analyzed, encompassing two different friction materials, to thoroughly assess the performance and analytical implications of each filter type. Filters were tested for their chemical background, handling practicality and potential contamination risk through extensive elemental analysis by inductively coupled plasma–optical emission spectrometry (ICP-OES) and inductively coupled plasma-mass spectrometry (ICP-MS). Additionally, morphological characterization of both filter types was conducted via scanning electron microscopy (SEM) coupled with energy-dispersive X-ray spectroscopy (EDS) to elucidate structural features affecting particle capture and subsequent analytical performance. Significant differences emerged between the two filters regarding elemental interferences: EMFAB filters exhibited substantial background contribution, particularly for alkali and alkaline earth metals (Ca, Na, Mg and K), complicating accurate quantification at trace levels. Conversely, Teflon filters demonstrated considerably lower background but required careful manipulation due to their structural fragility and the necessity to remove supporting rings, potentially introducing analytical variability. Statistical analysis confirmed that the filter material significantly affects elemental quantification, particularly when the collected PM₁₀ mass is limited, highlighting the importance of careful filter selection and handling procedures. Recommendations for optimal analytical practices are provided to minimize contamination risks and enhance reliability in trace element analysis of PM₁₀ emissions. These findings contribute to refining analytical methodologies essential for accurate environmental monitoring and regulatory assessments of vehicular non-exhaust emissions. Full article

Accurate assessment of vehicular air pollution in arid urban environments remains a challenge because standard emission models often overlook localized influences such as climate-driven dust resuspension and urban canyon effects. This study develops an enhanced modeling framework that integrates critical regional parameters into established algorithms to improve estimates of traffic-related emissions, including PM₁₀, PM₂.₅, CO, and NO₂. The US EPA’s AP-42 algorithm was modified to incorporate a novel highway width-to-building height ratio (I/H) and a climate-driven dynamic silt loading model derived from satellite data, while the European EEA algorithm was refined by introducing an explicit fuel density correction (ρ). The framework was applied and validated on two representative highways in Jordan—an industrial corridor and an urban-commercial artery—using continuous sensor-based measurements. Results indicate substantial improvement in predictive performance, with reductions of 60–77% in normalized difference for particulate matter and 72% for CO. The model successfully distinguished between emission regimes, capturing a seasonal silt-loading peak of approximately 17.5 g/m² during autumn at the industrial site, compared to more stable, traffic-dominated emissions along the urban corridor. Although NO₂ performance showed modest gains (4–40%) due to complex photochemical processes, the overall framework proved to be a robust and reliable tool for air quality assessment in arid cities. This adaptable approach provides a foundation for targeted air pollution management, and future work will integrate real-time dispersion dynamics and photochemical modules to better capture secondary pollutant formation. Full article

An optical camera-based integrated sensing and communication (OC-ISAC) system model is proposed to address the intrinsic requirements of vehicular-to-everything (V2X) applications in complex outdoor environments. The model enables the coexistence and potential mutual enhancement of environmental sensing and data transmission within the visible light spectrum. It characterizes the OC-ISAC channel by modeling how light, either actively emitted for communication or passively reflected from the environment, originating from any voxel in three-dimensional space, propagates to the image sensor and contributes to the observed pixel values. This framework is leveraged to systematically analyze the impact of camera imaging parameters, particularly exposure time, on the joint performance of sensing and communication. To address the resulting trade-off, we develop an analytically tractable suboptimal algorithm that determines a near-optimal exposure time in closed form. Compared with the exhaustive numerical search for the global optimum, the suboptimal algorithm reduces computational complexity from $O\left(N\right)$ to $O\left(1\right)$, while introducing only a modest average normalized deviation of 5.71%. Both theoretical analysis and experimental results confirm that, in high-speed communication or mobile sensing scenarios, careful selection of exposure time and explicit compensation for the camera’s low-pass filtering effect in receiver design are essential to achieving optimal dual-functional performance. Full article

In the realm of sustainable public transportation, the integration of intelligent electric bus propulsion systems represents a novel and promising approach to reducing environmental impact—particularly through the mitigation of NOx emissions and overall exhaust pollutants. This emerging technology underscores the growing need for advanced drive control architectures that ensure not only operational safety and reliability but also compliance with increasingly stringent emissions standards. The present article introduces an innovative analysis of energy-optimized dual-drive electric propulsion systems, with a specific focus on their potential for real-world application in emission-conscious urban mobility. A detailed dynamic model of a dual-drive electric bus was developed in MATLAB Simulink, incorporating a Fuzzy Logic-based decision-making algorithm embedded within the Transmission Control Unit (TCU). The proposed control architecture includes a torque-limiting safety strategy designed to prevent motor overspeed conditions, thereby enhancing both efficiency and mechanical integrity. Furthermore, the system architecture enables supervisory override of the Fuzzy Inference System (FIS) during critical scenarios, such as gear-shifting transitions, allowing adaptive control refinement. The study addresses the unique control and coordination challenges inherent in dual-drive systems, particularly in relation to optimizing gear selection for reduced energy consumption and emissions. Key areas of investigation include maximizing efficiency along the motor torque–speed characteristic, maintaining vehicular dynamic stability, and minimizing thermally induced performance degradation. The thermal modeling approach is grounded in integral formulations capturing major loss contributors including copper, iron, and mechanical losses while also evaluating convective heat transfer mechanisms to improve cooling effectiveness. These insights confirm that advanced thermal management is not only vital for performance optimization but also plays a central role in supporting long-term strategies for emission reduction and clean, efficient public transportation. Full article

Named Data Networking (NDN) represents a promising Information-Centric Networking architecture that addresses limitations of traditional host-centric Internet protocols by emphasizing content names rather than host addresses for communication. While NDN offers advantages in content distribution, mobility support, and built-in security features, its stateful forwarding plane introduces significant vulnerabilities, particularly Interest Flooding Attacks (IFAs). These IFA attacks exploit the Pending Interest Table (PIT) by injecting malicious interest packets for non-existent or unsatisfiable content, leading to resource exhaustion and denial-of-service attacks against legitimate users. This survey examines research advances in IFA detection and mitigation from 2013 to 2024, analyzing seven relevant published detection and mitigation strategies to provide current insights into this evolving security challenge. We establish a taxonomy of attack variants, including Fake Interest, Unsatisfiable Interest, Interest Loop, and Collusive models, while examining their operational characteristics and network performance impacts. Our analysis categorizes defense mechanisms into five primary approaches: rate-limiting strategies, PIT management techniques, machine learning and artificial intelligence methods, reputation-based systems, and blockchain-enabled solutions. These approaches are evaluated for their effectiveness, computational requirements, and deployment feasibility. The survey extends to domain-specific implementations in resource-constrained environments, examining adaptations for Internet of Things deployments, wireless sensor networks, and high-mobility vehicular scenarios. Five critical research directions are proposed: adaptive defense mechanisms against sophisticated attackers, privacy-preserving detection techniques, real-time optimization for edge computing environments, standardized evaluation frameworks, and hybrid approaches combining multiple mitigation strategies. Full article

The dynamic characteristics of super-large-diameter twin tunnels under train vibration loads have become a critical issue affecting not only the engineering safety of their own tunnels but also adjacent tunnels. A numerical model of super-large-diameter (D = 15.2 m) twin tunnels was established by the discrete element method (DEM) to analyze the static and dynamic responses of adjacent tunnel structures and surroundings under train-induced vibrations. Three parameters were considered: internal walls, absolute and relative spacing, and water pressure. The results indicate that internal walls in super-large twin tunnels can significantly reduce the static and dynamic responses in both the structures and surroundings of the adjacent tunnel. The vehicular lane board (wall2) plays a determinative role, followed by the smoke exhaust board (wall1), while the left and right partition walls (wall3 and wall4) exhibit the least effectiveness. The static–dynamic responses of the liners and surroundings of adjacent tunnels in super-large twin tunnels are significantly greater than those in smaller twin tunnels when the absolute spacing is identical. Moreover, the significant differences in displacement and velocity between the liners and surroundings can lead to cracks, leakage, or even instability. Appropriate water pressure (149 kPa) can effectively mitigate dynamic responses in adjacent tunnel structures and surroundings. The dynamic characteristics of super-large-diameter twin tunnels differ markedly from those of small-diameter twin tunnels, with internal walls, twin tunnel spacing, and water pressure all influencing their static and dynamic behaviors. This study provides theoretical guidance for the design and operation of super-large-diameter twin tunnels. Full article

Evaluating the impact on roadside environments of NH₃ from vehicle emissions is important for protecting the ecosystem from air pollution by fine particulate matter and nitrogen deposition. This study used passive samplers to measure NH₃ and NO_X at multiple points near a major road to observe the distribution of these gases in the area. The impact of NH₃ emitted from vehicles on a major road on the environmental concentration of NH₃ at different distances from the roadside was found to be similar to that of NO_X and NO₂. The concentration of NH₃ rapidly decreased due to dilution and diffusion within approximately 50 m of the road, and after 100 m the concentration remained almost the same or decreased slowly. Furthermore, CO₂ observations taken in the same period along the roadside and in the background yielded a vehicular emission factor of 4–50 mg/km for NH₃, which is comparable with previous research. This emission factor level contributes 4–11 ppb to the NH₃ concentrations in roadside air through the dilution and diffusion process. A correlation was found between the emission factors of NH₃ and NO_X that was different from the trade-off relationship seen when single-vehicle exhaust is measured. Full article

Air pollution, particularly from vehicular emissions, has emerged as a critical environmental health concern, contributing to a global estimated 7 million premature deaths annually. Diesel exhaust, a major component of urban air pollution, contains fine particulate matter and gases that evade respiratory filtration, penetrating deep into the lungs and triggering oxidative stress, inflammation, and immune dysregulation. Epidemiological and in vitro studies have linked diesel exhaust exposure to respiratory diseases such as asthma, chronic obstructive pulmonary disease, pulmonary fibrosis, and lung cancer, with immunological mechanisms playing a central role. Diesel exhaust particles induce oxidative stress, impair macrophage phagocytosis, and skew T-cell polarization toward pro-inflammatory Th2 and Th17 responses, exacerbating chronic inflammation and tissue damage. Despite these insights, significant gaps remain in understanding the precise immunomodulatory pathways and long-term systemic effects of diesel exhaust exposure. While animal models and in vitro studies provide valuable data, they often fail to capture the complexity of human exposure and immune responses. Further research is needed to elucidate the mechanisms underlying diesel exhaust-induced immune dysregulation, particularly in vulnerable populations with pre-existing respiratory conditions. This review focuses on summarizing the current knowledge and identifying gaps that are essential for developing targeted interventions and policies to mitigate the adverse health impacts of diesel exhaust and improve respiratory health outcomes globally. Full article

Urban stormwater may contain pollutants from different traffic vehicular sources including brake and tire wear, exhaust emissions, and atmospheric deposition. In this research, we took advantage of COVID-19 restrictions to evaluate the effects of historically low vehicular circulation on stormwater quality (metal concentrations and mass loads) generated from an urban watershed in Denver (Colorado). The analysis was performed at different hydrograph stages, i.e., first flush, peak flow, and recession stages during and after the imposition of the COVID-19 restrictions. Metal concentrations were compared with the maximum contaminant levels (MCLs) defined by the US Environmental Protection Agency (EPA) for drinking water as an indicator of water quality degradation. The results indicate that the Fe and Mn levels were constantly above the MCLs in stormwater, while then level of Pb occasionally surpassed the limits. Additionally, the highest pollutant mass loads generally occurred during peak flow conditions. Importantly, there was a clear effect of COVID-19 restrictions, suggesting that more stormwater pollution occurred after the restrictions were lifted, as a result of more vehicles circulating. Considering local climate, the mass loads of Fe, Mn, and Pb (the pollutants of concern) were estimated to be 0.4489, 0.0772, and 0.00032 MT/year, respectively, which are similar to loads reported in the literature for cities with similar climates and development levels. Full article

Particulate matter (PM) is a major component of ambient air pollution. PM exposure is linked to numerous adverse health effects, including chronic lung diseases. Air quality guidelines designed to regulate levels of ambient PM are currently based on the mass concentration of different particle sizes, independent of their origin and chemical composition. The objective of this study was to assess the relative hazardous effects of carbonaceous particles (soot), ammonium nitrate, ammonium sulfate, and copper oxide (CuO), which are standard components of ambient air, reflecting contributions from primary combustion, secondary inorganic constituents, and non-exhaust emissions (NEE) from vehicular traffic. Human epithelial cells representing bronchial (BEAS-2B) and alveolar locations (H441 and A549) in the airways, human lung fibroblasts (HFL-1), and rat precision-cut lung slices (PCLS) were exposed in submerged cultures to different concentrations of particles for 5–72 h. Following exposure, cell viability, metabolic activity, reactive oxygen species (ROS) formation, and inflammatory responses were analyzed. CuO and, to a lesser extent, soot reduced cell viability in a dose-dependent manner, increased ROS formation, and induced inflammatory responses. Ammonium nitrate and ammonium sulfate did not elicit any significant cytotoxic responses but induced immunomodulatory alterations at very high concentrations. Our findings demonstrate that secondary inorganic components of PM have a lower hazard cytotoxicity compared with combustion-derived and indicative NEE components, and alveolar epithelial cells are more sensitive to PM exposure. This information should help to inform which sources of PM to target and feed into improved, targeted air quality guidelines. Full article