Evening Peak Research Articles

Heterogeneous road traffic noise modeling at mid-block sections of mid-sized city in India.

This study attempted to develop a computer-based software for monitoring the traffic noise under heterogeneous traffic condition at the morning peak (MP), off peak (OP), and evening peak (EP) periods of mid-block sections of mid-sized city in India. Traffic noise dataset of 776 (LAeq, 1hr) were collected from 23 locations of Gorakhpur mid-sized city in the state of Uttar Pradesh in India. K-nearest neighbor (K-NN) algorithm was adopted for traffic noise prediction modeling. Moreover, principal component analysis (PCA) technique was used for the dimensionality reduction and to overcome the problem of multi-collinearity. The developed model exhibits R2 value of 0.81, 0.78, and 0.77 in the MP, OP, and EP, respectively, forLeq, and a value of 0.86, 0.80, and 0.84 for L10. The proposed model can predict more than 94% observations within an accuracy of ±3%. Ultimately, a user-friendly noise level calculator named "Traffic Noise Prediction Calculator for Heterogeneous Traffic (TNPC-H)" was developed for the benefit of field engineers and policy planners.

Research on Time-Based Fare Discount Strategy for Urban Rail Transit Peak Congestion

To alleviate peak-hour congestion in urban rail transit, this study proposes a new off-peak fare discount strategy to incentivize passengers to shift their departure time from peak to off-peak hours. Firstly, a questionnaire survey of Shanghai metro passengers is conducted to analyze their willingness to change departure time under different fare strategies. Secondly, based on the survey results, a time-differentiated fare discount model is constructed, considering both the company’s revenue and passengers’ travel benefits, and with the optimization objective of achieving balanced peak-hour and off-peak-hour train loads throughout the day. Subsequently, a genetic algorithm with nested fmincon functions is designed and combined with the actual data of Shanghai rail transit line 9 for arithmetic analysis. Finally, the effectiveness of the model is validated using the survey data. The research results show that the off-peak fare discount strategy can incentivize 6.88% of passengers traveling in the morning peak and 6.66% of passengers traveling in the evening peak to shift to off-peak travel. This research provides theoretical support and decision-making guidance for implementing time-differentiated pricing in urban rail transit systems.

Modeling Uncertain Travel Times in Distribution Logistics

Uncertainty quantification is a critical aspect of distribution logistics, particularly unpredictable travel times caused by traffic congestion and varying transportation conditions. This paper explores the modeling of uncertainty in dealing with travel times in the context of distribution logistics using the collocation method. First, we employ Monte Carlo simulations to assess the efficacy of the collocation method in modeling the variability and uncertainty associated with travel times. Second, we implement the collocation method in Casablanca, Morocco, a city renowned for its extensive distribution logistics operations and its dynamic traffic. Four distinct scenarios are considered: morning peak, inter-peak, evening peak, and off-peak periods. Our study explores two scenarios: one with recurrent congestion, representing typical daily conditions, and the other with unpredictable uncertainties in travel times, accounting for unexpected events that may occur during a distribution day. Our research findings enhance our understanding of the probabilistic nature of travel times in distribution logistics. This knowledge provides valuable insights applicable to both routine situations with recurrent congestion and non-recurrent congestion. The results’ findings contribute to a better understanding of the probabilistic nature of travel times in distribution logistics, offering valuable insights for optimizing route planning and scheduling.

Development and evaluation of processes affecting simulation of diel fine particulate matter variation in the GEOS-Chem model

Abstract. The capability of chemical transport models to represent fine particulate matter (PM2.5) over the course of a day is of vital importance for air quality simulation and assessment. In this work, we used the nested GEOS-Chem model at 0.25∘×0.3125∘ resolution to simulate the diel (24 h) variation in PM2.5 mass concentrations over the contiguous United States (US) in 2016. We evaluate the simulations with in situ measurements from a national monitoring network. Our base case simulation broadly reproduces the observed morning peak, afternoon dip, and evening peak of PM2.5, matching the timings of these features within 1–3 h. However, the simulated PM2.5 diel amplitude in our base case was 106 % biased high, relative to observations. We find that temporal resolution of emissions, subgrid vertical gradient between surface model-level center and observations, and biases in boundary layer mixing and aerosol nitrate are the major causes for this inconsistency. We applied an hourly anthropogenic emission inventory, converted the PM2.5 mass concentrations from the model-level center to the height of surface measurements by correcting for aerodynamic resistance, adjusted the boundary layer heights in the driving meteorological fields using aircraft observations, and constrained nitrate concentrations using in situ measurements. The bias in the PM2.5 diel amplitude was reduced to −12 % in the improved simulation. Gridded hourly emissions rather than diel scaling factors applied to monthly emissions reduced biases in simulated PM2.5 overnight. Resolving the subgrid vertical gradient in the surface model level aided the capturing of the timings of the PM2.5 morning peak and afternoon minimum. Based on the improved model, we find that the mean observed diel variation in PM2.5 for the contiguous US is driven by (1) building up of PM2.5 by 10 % in early morning (04:00–08:00 local time, LT), due to increasing anthropogenic emissions into a shallow mixed layer; (2) decreasing PM2.5 by 22 % from mid-morning (08:00 LT) through afternoon (15:00 LT), associated with mixed-layer growth; (3) increasing PM2.5 by 30 % from mid-afternoon (15:00 LT) though evening (22:00 LT) as emissions persist into a collapsing mixed layer; and (4) decreasing PM2.5 by 10 % overnight (22:00–04:00 LT) as emissions diminish.

Spatial and temporal variability of urban cyclists’ exposure to PM2.5 in Medellín, Colombia

Fine Particulate Matter (PM2.5) has become a major issue in cities around the world as it adversely affects human health and the environment. This study aims to develop a deeper understanding of the impact of bicycle lanes designs on cyclist exposure to air pollution in a developing-country city. PM2.5 concentrations were measured along a predefined route with different bicycle lane designs in the city of Medellín, Colombia. The measurement campaign was made between October and December 2020 during peak and off-peak hours on weekdays, where a total of 29 bicycle trips were carried out. To obtain accurate measurements, we used a laser-based particle monitoring system. The study's findings reveal that the bicycle route section without dedicated bicycle lanes had the highest PM2.5 exposure and inhaled dose per kilometer traveled. Furthermore, the mean PM2.5 exposure for cyclists during the morning peak hours was higher (33.8 μg/m3) compared to the evening peak (16.1 μg/m3) and off-peak hours (11.1 μg/m3). The inhaled PM2.5 dose was three times higher during morning peak hours than during off-peak hours and twice as high during evening peak hours. These results show that segregated cycling lanes on the sidewalk can considerably lower PM2.5 exposure and inhaled doses for cyclists when compared to other lane designs, highlighting the significance of infrastructure development in supporting sustainable transportation and public health.

Study on Community Detection Method for Morning and Evening Peak Shared Bicycle Trips in Urban Areas: A Case Study of Six Districts in Beijing

Examining the clustering characteristics and fluctuations within urban areas during peak hours through the lens of bike-sharing is of utmost importance in the optimization of bike-sharing systems and urban transportation planning. This investigation adopts the principles of urban spatial interaction network construction and employs streets as the fundamental units of analysis to model bike-sharing activities during morning and evening peak hours within Beijing’s six central districts. Subsequent to this, a comprehensive analysis of the network’s structural attributes was carried out. A Walktrap method, rooted in modularity analysis, was introduced to discern and scrutinize the clustering patterns and characteristics of communities within the network across different temporal intervals. Empirical findings reveal a predominant usage pattern of shared bicycles for short-distance travel during both morning and evening peak hours. Notably, distinctive community structures manifest during these periods, characterized by two large communities and multiple smaller ones during the morning peak, while the evening peak showcases a single large community alongside several medium-sized and smaller ones. Moreover, the extended interaction radius points to an expanded geographic range of interactions among streets. These findings bear significant implications for the management of urban transportation, bike-sharing enterprises, and urban residents, proffering valuable insights for the optimization of bike-sharing schemes and transportation strategies. These research findings not only contribute to enhancing urban transportation planning and bike-sharing systems but also provide robust guidance for advancing more efficient and sustainable urban transportation solutions, thereby fostering the sustainable development of cities.

Şarj Talebi ve Ekonomik Dinamikler Dikkate Alınarak Güneş Enerjisine Dayalı Elektrikli Araç Şarj İstasyonlarının Optimal Boyutlandırılması

Expanding and controlling charging infrastructure is critical as electric vehicle (EV) technologies develop and costs decline. The unplanned size of electric vehicle charging stations (EVCS) may negatively impact grid reliability, energy costs, and the environment. This study analyzes the integration potential of solar photovoltaic (PV) into EVCSs, considering the time variations in EV charging demand and economic parameters. Results show that optimal PV capacities can reduce the self-consumption rate (SCR) up to 55% during the daytime peak and at high economic rates. On the contrary, during the midday and evening peaks, SCR decreased less by up to 13%. The highest interest and inflation rates were found to affect the levelized cost of energy (COE) by up to 21.23% during the daytime and midday peaks, while the lowest interest and inflation rate affected COE by up to 32% during the evening peak. From the outcome of this paper’s investigation, it is possible to conclude that the optimal sizing of EVCSs should simultaneously consider economic parameters and EV charging demand variability.

Does docked bike-sharing usage complement or overlap public transport? the case of Brussels, Belgium

ABSTRACT This paper complements the existing literature on Bike Share Schemes (BSS) by investigating their use from a spatiotemporal perspective to assess their relationship with public transport (PT). We address these questions through the case of Brussels and its long-standing docked BSS ‘Villo!’. Our study analyses comprehensive (consecutive 12 months) and disaggregated (station level) data on rentals and returns and finds that Villo! is used mostly in dense (although not all) districts also well served by PT. However, temporal structures suggest Villo! overtakes PT at night in vibrant districts and possibly in selected districts with lower PT services over weekends. In addition, Villo! stations at key PT hubs usually do not show specific temporal patterns, which suggests intermodality may work at all times during PT operations. There could be an evening peak effect combined with the Brussels’ topography, but this needs to be confirmed by on-site surveys.

Impact of Roundabout Metering on the Operational Performance of Roundabout: A Case Study of Jawalakhel, Nepal

Roundabout is a type of intersection which improves efficiency and safety performance compared to other types of intersection. Jawalakhel roundabout serves to minimize the resulting conflict between the vehicles; however, due to increasing vehicular movements it is facing challenges like delay, poor level of service and traffic congestion. Classified traffic volume study through videographic survey is carried out and the volume is converted to passenger car unit at morning and evening peak period. SIDRA intersection V 8.0 was used for simulation and analysis of intersection’s performance. The performance is accessed in terms of delay, degree of saturation, level of service & 95% of queue vehicles were calculated for existing condition. As the operational performance was found unsatisfactory with level of service F; alternatives were considered. Among alternatives, roundabout metering on two approaches was adopted and their respective impact on the operational performance was analyzed. The overall roundabout improvement was not observed on two alternates of roundabout metering.

Power consumption regulation of enterprises for reducing of the energy system peak loads

Purpose. To propose measures for a partial solution to the problem of evening peak loads ensuring in the energy system of Ukraine by regulating the power consumption modes of industrial enterprises. This approach will reduce the level of such loads and align the power consumption profile. The methods. The methods of operations research and analysis of technological processes are used. The operation modes of the Ukrainian operating coal mines were studied and their electrical loading diagrams, which are formed by the appropriate technological processes, were analyzed. Findings. A comparative analysis of electrical loading diagrams of the power system and power consumption profiles of industrial facilities and the residential services was performed. The analysis showed the similarity of the electrical loading diagrams of coal mines, which is due to the typical mode of their operation, namely the presence of three work shifts (for coal mining) and one repair shift (for equipment maintenance). This creates prerequisites for the use of such enterprises as consumers-regulators of active power. As a result of which ways of "mitigation" of the problem of peak loads ensuring of the power system were proposed. Originality. The patterns of formation of the electric loading daily profiles for coal mines, determined by the operating mode of enterprises, were established.A new approach is proposed, which consists in changing the daily operation mode of coal mines, namely, moving the repair shift to a time that coincides with the period of evening peak loads in the Ukrainianpower system. Practical implementation. The practical value of this work lies in reducing the level of power consumption during peak loads in the power system,what is currently a very urgent problem for Ukrainian energy complex. The proposed approach allows to use the normal operation mode of a coal mine with the preservation of all necessary technological processes as an effective consumer-regulator of active load.

Dynamic quantification of on-road emissions in Hong Kong: Impact from traffic congestion and fleet composition variation

Policymakers need a good understanding of on-road air pollutant emission patterns to manage air quality effectively, but it can be challenging to dynamically capture emission patterns with high spatial and temporal resolutions in cities. In this study, we used traffic congestion index extracted from Google Map, traffic density model and local emission factors to develop a dynamic on-road emission inventory for Hong Kong. The pollutants include NOx, CO, NMVOC, CO2, PM2.5, PM10, and CH4. On weekdays, exhaust emissions increased by up to 50.0% compared with those on Sunday due to higher traffic congestion index. High emission rates were observed on highways during weekday evening peak hours and shifted to regional centers on Sunday evenings. Public light buses, goods vehicles, and taxis were the most significant contributors of NMVOC, NOx, and CO emissions, respectively. Control policy testing showed that replacing diesel-fueled buses with electric buses could significantly reduce NOx and PM exhaust emissions, whereas replacing liquefied petroleum gas fueled public light buses with electric buses could efficiently control NMVOC emissions. Eliminating private cars older than 15 years could effectively reduce CO emissions. This study provides a dynamic on-road emission inventory for Hong Kong with high temporal and spatial resolutions. The results can be extended to real-time air quality simulations and human exposure research in the future.

Efficacy, Safety, and Systemic Exposure of Once-Daily Indacaterol Acetate in Pediatric Asthma: A Randomized, Double-Blind, Controlled Dose-Finding Study.

Indacaterol acetate (IND), a long-acting β2-agonist in combination with mometasone furoate (MF), an inhaled corticosteroid (ICS), is being explored as a once-daily (od) treatment for asthma in children. This study examined the efficacy, safety, and systemic exposure of IND 75 µg and IND 150 µg in children with persistent asthma. In this Phase IIb, multicenter, randomized, double-blind, parallel-group study, pediatric patients (aged ≥6 to <12 years) with persistent asthma were randomized (1:1) to receive either IND 75 µg od or IND 150 µg od via Breezhaler® in combination with ICS background therapy. The primary endpoint was change from baseline in pre-dose trough forced expiratory volume in one second (FEV1) after two weeks of treatment. In total, 80 patients received IND 75 µg (n = 39) or IND 150 µg (n = 41). The study met its primary endpoint; both doses demonstrated improvements in pre-dose trough FEV1 from baseline to Day 14 (mean change [Δ]: 212 mL, IND 75 µg; 171 mL, IND 150 µg). The secondary spirometry parameters (post-dose FEV1 after 1-h, post-dose forced vital capacity; morning and evening peak expiratory flow) also improved. Overall, 36.1% in IND 75 μg group and 25% patients in IND 150 μg group achieved a decrease from baseline in Pediatric Interviewer-administered Asthma Control Questionnaire score of ≥0.5 units. A dose-dependent increase in plasma IND concentration was noted between the two groups. Both IND doses demonstrated an acceptable safety profile. Once-daily IND 75 μg and IND 150 μg via Breezhaler® in combination with background ICS therapy provided substantial bronchodilation in children with asthma and were well tolerated. Taken together, these clinical and systemic exposure findings support IND 75 μg as the most appropriate dose for evaluation in Phase III trials in combination with MF in pediatric asthma. ClinicalTrials.gov (NCT02892019; 08-Sep-2016).

A Study on Bicycle-Sharing Dispatching Station Site Selection and Planning Based on Multivariate Data

Bicycle-sharing is experiencing rapidly as a low-carbon transport mode of travel, with the advantages of low cost and sustainability. Bicycle-sharing operators use electronic fence parking points to manage bicycle-sharing, but it is too time-consuming and impractical to manage them individually. Therefore, it is necessary to cluster the electronic fence parking points and implement regionalized management. This study uses a Mean-shift clustering algorithm to cluster the electronic fence parking points on Xiamen Island, construct a bicycle-sharing dispatching station, and divide the management area. Singular value decomposition is employed to analyze the travel demand patterns of bicycle-sharing and travel characteristics. In addition, we constructed regression models to explore the relationship between the urban built environment and bicycle-sharing trips during the morning and evening peak hours. The study results show that: (1) The 73 dispatching stations constructed cover 86.72% of the bicycle-sharing data, with a good clustering effect. (2) The travel demand for bicycle-sharing shows multiple patterns and different characteristics in different spatial and temporal distributions, which are influenced by land use. (3) There are spatial and temporal differences in the impact of the urban built environment on bicycle-sharing trips, especially residential and enterprise poi densities have opposite effects on shared bicycle-sharing during morning and evening peak hours. The research results of this paper can serve in the planning of bicycle-sharing dispatch stations and the differentiated management and dispatch of bicycle-sharing, which can reduce operating costs and promote the development of sustainable urban transport.

Understanding the Spatiotemporal Impacts of the Built Environment on Different Types of Metro Ridership: A Case Study in Wuhan, China

As the backbone of passenger transportation in many large cities around the world, it is particularly important to explore the association between the built environment and metro ridership to promote the construction of smart cities. Although a large number of studies have explored the association between the built environment and metro ridership, they have rarely considered the spatial and temporal heterogeneity between metro ridership and the built environment. Based on metro smartcard data, this study used EM clustering to classify metro stations into five clusters based on the spatiotemporal travel characteristics of the ridership at metro stations. And the GBDT model in machine learning was used to explore the nonlinear association between the built environment and the ridership of different types of stations during four periods in a day (morning peak, noon, evening peak, and night). The results confirm the obvious spatial heterogeneity of the built environment’s impact on the ridership of different types of stations, as well as the obvious temporal heterogeneity of the impact on stations of the same type. In addition, almost all built environment factors have complex nonlinear effects on metro ridership and exhibit obvious threshold effects. It is worth noting that these findings will help the correct decisions be made in constructing land use measures that are compatible with metro functions in smart cities.

Dynamic risk assessment of urban flood disasters based on functional area division—A case study in Shenzhen, China

The assessment of urban flood risk plays a vital role in disaster prevention and mitigation. This work aims to assess the dynamic risk of urban flood triggered by population movements through dividing urban functional zoning from the perspective of collective cognition. Firstly, the urban functional areas are identified using Points of Interest data and then the population movements mobile is detected based on functional areas using mobile signaling big data. Then, one-dimensional and two-dimensional hydrodynamic models are employed to simulate the 50-year flood scenario in Futian District, Shenzhen. Finally, a spatio-temporal dynamic assessment model for urban flood risk is constructed based on the extent of inundation, water depth, population density, and the disaster-bearing capacity of functional areas. The research findings are as follows: (1) Futian District's urban planning showcases harmonious integration of single-function and mixed-function areas. Utilizing the 50% perception standard efficiently identifies distinct functional types across diverse urban zones. The results are highly consistent with the actual situation. (2) During morning peak hours, the population exhibits a nuanced pattern of dispersal, concentration, and transition. Lunchtime witnesses multiple central clusters forming and gradually dispersing, while the evening peak witnesses population regrouping, covering broader geographical extents. Dynamic utilization of functional areas and mobile phone signaling data outperforms static population metrics, offering deeper insights into the complexities of human activity. (3) Between 12:00 and 13:00, lunchtime movements lead to a surge of 6 high-risk zones in the central area and 5 in the Meiling area. The dynamic flood risk assessment model, based on functional area delineation, effectively identifies disparities and fluctuations in flood risk across diverse functional areas during rainfall scenarios, ensuring heightened precision and accuracy in risk assessment.

Risk Simulation of Urban Rainstorm Flood Disasters Considering Crowd Activities

Social activities have a significant impact on the rainstorm flood disaster risk. It is crucial to explore the dynamic changes of urban rainstorm flood disaster risk caused by crowd activities. In this study, a risk simulation method of urban rainstorm flood disasters is proposed, composed of an urban rainstorm flood model based on SWMM and LISFLOOD-FP and a crowd activities model based on ABM. Taking the Futian District of Shenzhen as an example, the temporal and spatial changes in rainstorm flood disaster risk for buildings and roads are analyzed under three scenarios: midnight, morning peak, and evening peak. The results show that: (1) Although the overall risk of urban rainstorm flood disasters increases as the inundation area expands, the average risks of roads and buildings increase rapidly and then stabilize during the morning peak due to commuting activities, while the average risk of roads remains high level during the evening peak due to commuting activities, while; (2) The risk of urban rainstorm flood varies significantly at different time periods. The average risk of buildings is the largest during the morning peak, about twice that during the evening peak. The number of high-risk roads during the evening peak is much higher than in the morning peak, and both buildings and roads have the least risk during midnight; (3) The spatial distribution of urban rainstorm flood disaster risk changes with the crowd activities, shifting from residential areas to industrial areas, schools, shopping malls, etc., during the morning peak, while the evening peak shows the reverse.

Abundant oxygenated volatile organic compounds and their contribution to photochemical pollution in subtropical Hong Kong

Volatile organic compounds (VOCs), which are ubiquitous pollutants in the urban and regional atmosphere, promote the formation of ozone (O3) and secondary organic aerosols, thereby significantly affecting the air quality and human health. The ambient VOCs at a coastal suburban site in Hong Kong were continuously measured using proton-transfer-reaction time-of-flight mass spectrometry (PTR-ToF-MS) from November 2020 to December 2020. 83 VOC species, including 23 CxHy, 53 CxHyO1-3, and 7 nitrogen-containing species, were measured during the campaign, with a mean concentration of 36.75 ppb. Oxygenated VOCs (OVOCs) accounted for most (77.4%) of the measured species, including CxHyO1 (50.7%) and CxHyO2 (25.1%). The measured VOC species exhibited distinct temporal and diurnal variations. High concentrations of isoprene and OVOCs were measured in autumn with more active photochemistry, whereas large evening peaks of aromatics from local and regional primary emissions were prominent in winter. The OH reactivity and O3 formation potential (OFP) of key precursors were quantified. OVOCs contributed about half of the total OH reactivity and OFP, followed by alkenes and aromatics, and the contribution of aromatics increased significantly in winter. The potential source contribution function was used to investigate the potential source regions associated with high VOC concentrations. Through positive matrix factorization analysis, six major sources were identified based on fingerprint molecules. The contributions of biogenic sources and secondary formation to the observed species were notable in late autumn, whereas vehicle emissions and solid fuel combustion had higher contributions in winter. The findings highlight the important role of OVOCs in photochemical pollution and provide valuable insights for the development of effective pollution control strategies.

The impact of traffic mobility measures on vehicle emissions for heterogeneous traffic in Lagos City

Emissions from vehicular traffic are one of the key drivers of urban environmental air pollution, degrading the ambient air quality in many African cities and across the globe. This study sought to assess the impact of traffic mobility measures on the emission levels of air pollutants from vehicle exhaust in Lagos, Nigeria. Traffic flow and vehicle mix were collected daily during morning, afternoon, and evening peak periods along selected arterial and two-lane collector roadways. Simultaneously, five (5) air pollutants from vehicular traffic emissions were observed at distinct monitoring stations along the roadways using portable gas detectors. The traffic flow and mobility measures were inputted into a multiple exponential model to estimate the concentration of each pollutant. The result of the vehicle fleet composition revealed 3.5%, 4.5%, 57%, 32%, 1.5%, and 2% for motorcycles, tricycles, personal cars, minibuses, large buses, and heavy goods vehicles, respectively, on the two-lane road and 10%, 35%, 27%, 10%, and 18% for motorcycles, personal cars, minibuses, large buses, and heavy goods vehicles, respectively, on the arterial. The results of a multiple exponential regression model (MER) showed significant contributions from traffic flow, speed, vehicle fleet proportion, and pollutant concentration (p <0.05). However, the impact on ambient air quality revealed severe pollution levels for CO and PM2.5, while SO2, NO2, and PM10 showed moderate, poor, and poor pollution levels. This study has provided evidence on how pollutant emissions increase rapidly during peak traffic conditions in heterogeneous traffic on different classes of roads and recommended policies for managing vehicle fleets and traffic congestion with the aim of reducing the impact on the ambient air quality and health of the public on heavily trafficked roadways in sub-Saharan African cities.

Online model-based predictive control with smart thermostats: application to an experimental house in Québec

This paper tests the impact of model resolution and structure on the performance of Model Predictive Control (MPC) implementation in an unoccupied research house in Québec equipped with smart thermostats. Two low-order models and a high-order multi-zone model were calibrated with measured data, with the structure of the multi-zone model being generated automatically during the calibration procedure. The three models were used to apply real-time MPC to an experimental house in Québec using the established dynamic tariffs for morning and evening peaks. MPC with any of the three models successfully preheated the house before the demand-response events, outperforming the reference reactive controller, reducing cost and thermal discomfort. The high-order multi-zone model performed the best, reducing average cost of electricity by 55% and high-price energy consumption by 71%, compared to the low-order models, which achieved cost reductions of 40% and 44% and energy consumption reductions of 48% and 54% respectively.

Evaluation of Traffic Noise Level in Residential Areas Along Jalan Kluang - Case Study in Sri Gading, Batu Pahat, Johor

Noise, recognized as an adverse factor affecting human health and overall well-being, poses a significant public health concern. This study focuses on evaluating the traffic noise levels in residential areas along Jalan Kluang. Measurements were conducted in four selected residential areas, namely Taman Sri Saga, Taman Cempaka Putih, Kampung Kluang, and Taman Bahagia Baru, during morning (7.30 am - 9.30 am) and evening (4.00 pm - 6.00 pm) peak hours on weekdays. The results indicated that certain locations exceeded the noise limit that set by the Department of Environment (DOE). Kampung Kluang exhibited LAeq values of 71.10 dBA and 71.48 dBA during the morning and evening peak hours, respectively, surpassing the DOE noise limit. Taman Cempaka Putih also recorded noise levels, with LAeq values of 69.40 dBA and 66.46 dBA during the morning and evening peak hours, respectively. In contrast, Taman Sri Saga and Taman Bahagia Baru demonstrated LAeq values still below the DOE limit during both peak hours. Taman Sri Saga recorded LAeq values of 55.63 dBA and 57.78 dBA, while Taman Bahagia Baru recorded LAeq values of 57.58 dBA and 59.65 dBA during the morning and evening peak hours, respectively. Therefore, it is crucial to address the excessive noise levels in the affected residential areas to mitigate the detrimental effects and ensure a healthier living environment for the affected residents in those areas.