High Traffic Regions Research Articles

Analysis of air pollution from three main transportation vehicles: a case study

ABSTRACT The environmental effects of transportation vehicles have been steadily increasing for decades. In high traffic regions, the gases released into the atmosphere have become a big threat for all living creatures. In this study, emissions from aircrafts, cars and ships on Tuzla region which include Istanbul Sabiha Gökçen Airport were calculated and the emission estimation for the next 50 years (between 2022 and 2072 years) was made considering the current situation with linear regression method. In the study, considering environmental concerns, changes in these emissions with alternative fuel use were also evaluated. In addition, the emission changes of an aircraft during the flight were calculated. The emission amounts of aircraft, ships and cars in Tuzla region per hour were 389.8 µg/m3 CO2, 0.454 µg/m3 CO, 0.68297 µg/m3 NOx, 0.00374 µg/m3 SOx., 0. 687 µg/m3 SOx+NOx, 169 µg/m3 H20. It was found that in Istanbul, 13.589 ktons/year of CO2 and 121.526 tons/year of NOx, SOx emissions arise. SOx + NOx emission from vehicles at Sabiha Gökçen Airport was calculated as 24.2 kg/h and CO2 emission was calculated as 455.27 kg/h. It was found that the biggest source of CO was related with LPG vehicles. When the calculated values were compared with the current emissions, it was seen that these emission values were significantly reduced by using alternative fuels. In conclusion, if gasoline is used; CO emissions can be reduced by 6.5%, NO and NO2 emissions by 27.488%, SOx+ NOx emissions by 50.7%. If biodiesel is used, CO2 emissions can be reduced by 65%. Emissions will increase by 143.7% after 50 years.

Using date palm (Phoenix dactylifera L.) as bio-monitors of environmental quality for exposure assessment and pollution source tracking

The entry of potentially toxic elements (PTEs) into the environment has been raised as a problem for various countries. So, this study aimed to investigate the PTEs concentration in the environment. In this cross-sectional study, Ahvaz city, the capital city of Khuzestan province, was divided into 5 areas. At each site, three-date palms were selected. Leaves and mesh fibers samples were collected from the young palm (3 years) with a maximum trunk height of 3–4 m. Plant leaves samples were separated from the middle section of the main leaves area of the plant and mesh fibers were selected from the different parts of the palm data trunk (top, middle, and bottom of the palm data trunk on all four sides of the palm). Then, data palm samples were divided into two groups of washed/unwashed. Soil samples were collected from the closest point to the palms date at a depth of 0–50 cm including at two depths (0–20 cm and 20–40 cm), and then combined to make a composite soil sample. After the preparation of samples, PTEs were measured by ICP-OES. The highest PTEs concentrations were found in industrial and high-traffic sites and the lowest was obtained at the control site. The largest bioconcentration factor (BCF) was related to copper (2.34–7.49) in mesh fibers samples and in the leaves (1.65) in the control area. Principal component analysis (PCA) results showed metal(loid)s (copper, nickel, zinc, lead, iron, arsenic, and cobalt) are mostly related to brake wear and tire of vehicles and asphalt and road dust, while the metals (Manganese, chromium, and cadmium) mostly originate from industrial sources. Palm leaves, mesh fibers, and soil can be used as a cheap biomonitoring factor for PTEs analysis, especially in industrial and high-traffic regions.

Sex-specific association of exposure to air pollutants and Nrf2 gene expression and inflammatory biomarkers in exhaled breath of healthy adolescents

Studies investigating the nuclear factor erythroid 2-related factor 2 (Nrf2) expression levels in the respiratory system of healthy subjects are scarce. Moreover, separate studies on the health-related outcomes of air pollution for each sex are limited. The current panel study investigated sex-specific Nrf2 expression levels and related oxidative stress and inflammatory responses among healthy adolescents exposed to PM2.5, PM10, O3, and PM2.5-bounded metals in a high traffic region. Forty-nine healthy nonsmoking subjects participated in the study for five consecutive months (Nov. 2019 to Feb. 2020). Each subject was asked to provide 1 mL of exhaled breath condensate (EBC). Data were analyzed using linear mixed-effects models. The results showed that PM10, PM2.5, O3, and PM2.5-bounded metals were negatively linked to Nrf2 expression level in EBC of females with −58.3% (95% CI: 79.5, −15.4), −32.1% (95% CI: −50.3, −7.1), −76.2% (95% CI: −92.6, −23.9), and −1.9 (95% CI: −3.4, −0.4), respectively. While our results presented no significant association between the studied pollutants and Nrf2 gene expression in males, significant associations were observed between the pollutants and total nitric oxide (NOx), interleukins 6 (IL-6), and tumor necrosis factor-alpha (TNF-α) in the EBC of females. In the case of males, only EBC cytokines showed a significant association with air pollutants. Overall, this study suggests that exposure to ambient air pollutants may affect the respiratory system with biologically different mechanisms in males and females. PM2.5 concentration had a positive correlation with exhaled TNF-α and IL6 values in females while positive correlation with TNF-α and negative correlation with IL6 values in males. O3 had a negative correlation with TNF-α in males.

Edge Oriented Urban Hotspot Prediction for Human-Centric Internet of Things

Mobile edge computing works well with the rapid growth of human-centric IoT applications by providing timely and in-situ data caching and processing. Edge oriented urban hotspot prediction is to predict the high traffic regions in case to provide basis for further deployment and replenishment of edge servers. Most of the existing hotspot analysis work is not well suited for human-centric IoT application scenarios especially for large-scale urban city areas. Instead, in this paper we propose edge-oriented hotspot prediction scheme based on information Interactive Graph Attention Networks (I-GAN) for urban city within the human-centric IoT and MEC application scenarios. I-GAN makes reasoning on the user service needs by learning the interactive relations of multifaceted human-centric factors: including online human behavior and offline crowd flow through graph attention networks. On the other hand, I-GAN makes representation of urban-scale edge service capability by graph embeddings through inductive learning with distributed multi-layer graph convolutions. Based on it, I-GAN makes matching between them and then predicts the edge-oriented hotspots with time variance. The performance evaluations are based on realistic dataset of a southern city of China provided by China Unicom. I-GAN is compared with the other related hotspot analysis schemes. The results show that I-GAN is with much better prediction accuracy with multiple time dimensions.

Radiology Department Preparedness in the Coronavirus Disease 2019 (COVID-19) Postshutdown Environment.

Radiology Department Preparedness in the Coronavirus Disease 2019 (COVID-19) Postshutdown Environment.

Satellite Telemetry Reveals Spatial Overlap Between Vessel High-Traffic Areas and Humpback Whales (Megaptera novaeangliae) Near the Mouth of the Chesapeake Bay

During winter months, humpback whales (Megaptera novaeangliae) frequent the coastal waters of Virginia near the mouth of the Chesapeake Bay. Located within the Bay is Naval Station Norfolk, the world’s largest naval military installation, and the Port of Virginia, the sixth busiest container port in the United States. These large seaports, combined with the presence of recreational boaters, commercial fishing vessels, and sport-fishing boats, result in a constant heavy flow of vessel traffic through the mouth of the Chesapeake Bay and adjacent areas. From December 2015 to February 2017, 35 satellite tags were deployed on humpback whales to gain a better understanding on the occurrence, movements, site-fidelity, and overall behavior of this species within this high-traffic region. The tags transmitted data for an average of 13.7 days (range 2.7–43.8 days). Location data showed that at some point during tag deployment, nearly all whales occurred within, or in close proximity to, the shipping channels located in the study area. Approximately one quarter of all filtered and modeled locations occurred within the shipping channels. Hierarchical state-space modeling results suggest that humpback whales spend considerable time (82.0%) engaged in foraging behavior at or near the mouth of the Chesapeake Bay. Of the 106 humpback whales photo-identified during this research, nine individuals (8.5%) had evidence of propeller strikes. One whale that had previously been tagged and tracked within shipping channels, was found dead on a local beach; a fatality resulting from a vessel strike. The findings from this study demonstrate that a substantial number of humpback whales frequent high-traffic areas near the mouth of the Chesapeake Bay, increasing the likelihood of injurious vessel interactions that can result in mortalities.

Heavy metal concentrations in the outdoor and indoor air of high-traffic areas in Tehran, Iran

Tehran is a polluted metropolitan and the capital of Iran, where heavy traffic and excessive energy consumption (especially gasoline) are the major sources of heavy metal emissions. This study aimed to investigate the variations in heavy metal concentrations on the aerosols of the outdoor and indoor environments in the high-traffic regions of Tehran. This was a descriptive, applied research in terms of methodology. Six internal-external stations were specified in three high-traffic regions. Sampling was performed in six replications for each station during fall 2018(n=36). After the extraction of the heavy metals from the fiberglass filters using acidic digestion based on the ASTM method, their concentrations were measured via ICP-OES. Data analysis was performed in SPSS using MANOVA. According to the results, regions 2, 3, and 15 had the highest traffic in Tehran during the study, with the traffic rate estimated at 25-27% hours per day on average. A significant difference was observed between the outdoor and indoor regions in terms of heavy metal concentrations (P Fe>Pb>Mn>Cu>Zn>Cr>As>Ni>Cd. Aluminum and cadmium had the highest and lowest concentrations, respectively. In addition, the high concentration of lead and heavy traffic was alarming in Afsariyeh Street (region 15). Considering the adverse effects of pollution on the health of citizens, serious measures should be taken to control traffic in Tehran. Keywords: Heavy metals, Traffic volume, Tehran metropolitan, Indoor and outdoor environment

Indoor and outdoor airborne bacterial air quality in day-care centers (DCCs) in greater Ahvaz, Iran

Air pollution is considered as one of the major causes of environmental health problems. Young children and infants are more susceptible than adults due to age and higher sensitivity to environmental hazards. The aim of the present study was to an investigation of indoor/outdoor, regional and seasonal variations of airborne bacteria and PM concentrations of six randomly selected child day-care centers (DCCs) in greater Ahvaz. bio-aerosol sampling, PM measurement, and meteorological parameters data capture were performed monthly in DCCs of industrial, high traffic and residential regions during autumn, winter, and spring. The results revealed that the highest and the lowest of indoor and outdoor of mean concentrations of airborne bacteria were observed in the DCCs in the high traffic regions and residential area, respectively. The monthly highest and the lowest mean of culturable bacteria was determined in February (812 CFU/m3) and November (188 CFU/m3), respectively. There is a positive correlation between concentrations of PM and airborne bacteria in the DCCs during the study. The highest mean concentrations of airborne bacteria in indoor air samples were measured in winter season in high traffic and residential regions with 789 CFU/m3 and 646 CFU/m3, respectively, this value for outdoor samples was determined in spring and winter seasons at industrial and residential regions with 335.41 CFU/m3 and 306.34 CFU/m3, respectively. The highest and the lowest indoor/outdoor (I/O) ratio of mean concentrations of bacteria were determined in the autumn and spring at the industrial region with I/O ratio of 23.17 and 1.37, respectively. In the indoor and outdoor conditions of all DCCs, the Gram-positive bacteria were the dominant species which shows higher concentration than Gram-negative bacteria. The dominant bacterial genera were Bacillus spp. and Staphylococcus spp. in air samples. The results of the present study suggest strongly that instead of natural ventilation using windows, use of artificial ventilation and air conditioning systems could improve indoor air quality (IAQ) in the DCCs. Facial air filters and air treatment devices are recommended particularly at the time of dust event days in cities like Ahvaz.

A Novel Approach for Boosting Base Station Anonymity in a WSN

Nodes in a wireless sensor network scrutinize the nearby region and transmit their findings to the base station (BS) using multi-hop transmission. As the BS plays an important role in a wireless sensor network, therefore an adversary who wants to interrupt the operation of the network would avidly look for the BS location and imposes maximum damage by destroying the BS physically. The multi-hop data transmission towards BS makes a prominent pattern of the traffic (huge traffic near the BS region) that indicates the presence of BS in the nearby region and thus the location of the BS may expose to the adversaries. This work aims to provide a novel approach which will increase the BS anonymity. For this purpose, a randomly roamed BS and the special nodes are proposed to achieve the above mentioned objective. The special nodes produce a large number of high traffic regions, which are similar to the BS region. Now, there are many regions which look like BS region and hence the probability to get the BS region using traffic analysis is very low. Therefore, this approach increases the effort of adversaries in order to find the exact BS position. We have used a standard entropy model to measure the anonymity of the base station and the GSAT test is used to calculate the number of steps required to find the base station. The results show that the proposed technique provides better results in terms of anonymity compared to the existing techniques.

Passive photo-catalytic destruction of air-borne VOCs in high traffic areas using TiO2-coated flexible PVC sheet

Photo-catalytic oxidation (PCO) of VOCs in high traffic regions can be achieved by providing optimum catalyst coating on large surface areas of advertising boards. Nine different sol–gel preparation techniques were attempted for coating TiO2 on flexible PVC sheet used for advertising boards. These coatings were characterized for structural continuity, surface roughness, surface impurities, strong surface attachment and particle size using AFM, XRD, FESEM, and EDX analyzers and optimum sol preparation technique for coating was adopted. Several sets of experiments were conducted for oxidation of benzene and toluene in a batch reactor (having optimum coating on PVC sheet) and parameters like reaction rate constant, order of reaction and removal efficiency etc. were evaluated. The reactions followed 1st order reaction rate model with rate constants for benzene 1.65×10−5min−1cm−2 and toluene 1.07×10−4min−1cm−2. The oxidation rate achieved on PVC sheet using natural sunlight for benzene and toluene was around 50% and 68% of that achieved for artificially controlled UV light. This study proposes a novel method of ambient air VOC destruction using PCO technique under natural sunlight in high traffic areas having large advertisement boards that can provide surface for catalytic coating.

Energy-Efficient Hybrid One- and Two-Way Relay Transmission

Two-way relaying is more spectral efficient than one-way relaying and is expected to consume less transmit power than one-way relaying to achieve the same data rate. However, when circuit power consumption is also taken into account, two-way relaying may not be more energy efficient, particularly when the bits to be transmitted from two source nodes have different numbers. To always offer high energy efficiency (EE), we propose a hybrid relay strategy, which conveys bidirectional messages with both one-way and two-way relaying. To maximize its EE, we jointly optimize the number of bits and transmission time allocated to the one- and two-way relaying stages to minimize the overall energy consumption, including the transmit power and circuit power. To reveal the behavior of the optimized hybrid relay strategy, we analyze the optimal bit allocation for the hybrid relaying under different circuit power consumption and bidirectional data amounts. Analytical and simulation results show that, in a high-traffic region where the transmit power dominates the energy consumption, the hybrid relaying degenerates into two-way relaying. By contrast, in a low-traffic region where the circuit power consumption is dominant, the proposed hybrid relaying offers significant performance gain in the sense of EE over the pure one- and two-way relaying.

Climate Impact of Biofuels in Shipping: Global Model Studies of the Aerosol Indirect Effect

Aerosol emissions from international shipping are recognized to have a large impact on the Earth's radiation budget, directly by scattering and absorbing solar radiation and indirectly by altering cloud properties. New regulations have recently been approved by the International Maritime Organization (IMO) aiming at progressive reductions of the maximum sulfur content allowed in marine fuels from current 4.5% by mass down to 0.5% in 2020, with more restrictive limits already applied in some coastal regions. In this context, we use a global bottom-up algorithm to calculate geographically resolved emission inventories of gaseous (NO(x), CO, SO(2)) and aerosol (black carbon, organic matter, sulfate) species for different kinds of low-sulfur fuels in shipping. We apply these inventories to study the resulting changes in radiative forcing, attributed to particles from shipping, with the global aerosol-climate model EMAC-MADE. The emission factors for the different fuels are based on measurements at a test bed of a large diesel engine. We consider both fossil fuel (marine gas oil) and biofuels (palm and soy bean oil) as a substitute for heavy fuel oil in the current (2006) fleet and compare their climate impact to that resulting from heavy fuel oil use. Our simulations suggest that ship-induced surface level concentrations of sulfate aerosol are strongly reduced, up to about 40-60% in the high-traffic regions. This clearly has positive consequences for pollution reduction in the vicinity of major harbors. Additionally, such reductions in the aerosol loading lead to a decrease of a factor of 3-4 in the indirect global aerosol effect induced by emissions from international shipping.

An optimized energy saving mechanism in IEEE 802.16e Mobile WiMAX systems

The IEEE 802.16e standard defines a sleep mode operation for conserving power to support the battery life of mobile broadband wireless access (BWA) devices. The system saves energy when it goes through a sleep period with some delay in packet arrival response time. The relationship between energy consumption and the delay is studied to ensure best performance for mobile devices. This relationship has been analyzed by using a mathematical model. A new scheduling method is proposed to adjust the sleep cycle periods by adding a small increase to the next sleep cycle compared with the previous cycle instead of just simply doubling the previous cycle. The simulated results were obtained after adjusting the length of the first sleep cycle period (T min ). Adjusting T min provides a result of 54% reduction in the time needed for every frame to get a response especially in a lower traffic region. In a high traffic region, a reduction of 21.5% has been obtained in energy consumption for each sleep mode operation. Therefore, the proposed idea confirms a faster frame response time at lower energy consumption.

혼잡한 환경에서 적응적 가우시안 혼합 모델을 이용한 계층적 객체 검출

For the detection of moving objects, background subtraction methods are widely used. In case the background has variation, we need to update the background in real-time for the reliable detection of foreground objects. Gaussian mixture model (GMM) combined with probabilistic learning is one of the most popular methods for the real-time update of the background. However, it does not work well in the complex and dynamic backgrounds with high traffic regions. In this paper, we propose a new method for modelling and updating more reliably the complex and dynamic backgrounds based on the probabilistic learning and the layered processing.

Mining spatio-temporal patterns in object mobility databases

With the increasing use of wireless communication devices and the ability to track people and objects cheaply and easily, the amount of spatio-temporal data is growing substantially. Many of these applications cannot easily locate the exact position of objects, but they can determine the region in which each object is contained. Furthermore, the regions are fixed and may vary greatly in size. Examples include mobile/cell phone networks, RFID tag readers and satellite tracking. This demands techniques to mine such data. These techniques must also correct for the bias produced by different sized regions. We provide a comprehensive definition of Spatio-Temporal Association Rules (STARs) that describe how objects move between regions over time. We also present other patterns that are useful for mobility data; stationary regions and high traffic regions. The latter consists of sources, sinks and thoroughfares. These patterns describe important temporal characteristics of regions and we show that they can be considered as special STARs. We define spatial support to effectively deal with the problem of different sized regions. We provide an efficient algorithm--STAR-Miner--to find these patterns by exploiting several pruning properties.

Packet Combining With Adaptive Retransmission Control in DS-CDMA Random Access Networks

Packet combining with adaptive retransmission control (ARC) in DS-CDMA random access networks has been investigated. The proposed system uses diversity packet combining while adaptively adjusting the retransmission probability of backlog users to optimize packet retransmissions. A soft decision DS-CDMA analysis is used to derive the optimum channel input for ARC. Simulation results show that packet combining with ARC can significantly increase the throughput and maintain the performance very close to its optimum in the high traffic region.