Stations In City Research Articles

Pollution Characteristics and Transport contributions of Ambient Ozone and Volatile Organic Compounds in Southern Hebei Cities

The "14th Five-Year Plan" period is the key stage for southern Hebei cities (Shijiazhuang, Xingtai, and Handan) to be removed from the bottom ten of the Air Quality Composite Index. The hourly ozone (O3) data of 15 country-controlled monitoring stations in the southern cities of Hebei Province from April to October 2020, hourly data of three volatile organic compound (VOCs) supersites, and the meteorological data of the same period were used for analysis, combined with the spatiotemporal succession, O3 formation potential (OFP), backward trajectory modeling, and spatial statistical modeling. The results showed the following:firstly, the temporal variations in O3 in southern cities of Hebei Province from April to October presented an inverted "U" shape, and the spatial distribution was high in the south and low in the north. O3 pollution was the most serious in June, with Xingtai (233.8 μg·m-3)>Handan (225.2 μg·m-3)>Shijiazhuang (224.8 μg·m-3). O3 was positively correlated with temperature and wind speed and negatively correlated with humidity and VOCs; furthermore, the ρ(TVOC) from April to October followed the order of Xingtai (274 μg·m-3)>Shijiazhuang (266 μg·m-3)>Handan (218 μg·m-3). The total OFP of alkenes and aromatics accounted for more than half; moreover, the trajectory of O3 pollution in southern cities of Hebei Province showed spatial directionality and relevance. The highest mass concentration of O3 (198.92 μg·m-3) was in the trajectory from Shijiazhuang to Xingtai, and the highest frequency of O3 pollution was in the trajectory from Handan to Xingtai. Moreover, the transmission contributions of O3from Xingtai to Shijiazhuang agglomerations were high (27.39%), and Handan played a significant role in the transmission contribution of O3 to Xingtai (32.76%).

Forensic morphological and elemental analysis of gold jewellery: A case study

In a cheating case, report was launched in the police station of Raipur city of Chhattisgarh state. In this case, a person was cheated in buying gold beads worth nearly 16 lakhs. As in forensic physics branch analysis and comparison of physical properties is done, case was registered in state forensic Science Laboratory, Raipur. The aim of this paper is to understand and apply basic principles of physics to solve unsettled cases and create awareness, whenever we purchase precious ornaments. In this case, a garland consisting of large number of round golden beads was received for examination of gold content assuming it to be gold of lower purity. Scanning Electron Microscope (SEM) examination, Energy Dispersive X-ray analysis (EDAX) examination of these beads were done in the laboratory. The results were supervising that there was no Gold (Au) in all the golden beads of garland, it consisted of Copper (Cu) and Zinc (Zn) in the ratio of Cu: Zn::2:1.

Evaluation of Urban Rail Transit Station Effectiveness Based on TOD Principle -Taking Shanghai as an Example

The rapid development of China's cities has led to a variety of traffic problems. Building a public transportation-oriented urban space development model and playing the role of rail transit in urban development are important measures for the upgrading and construction of China's cities. In order to evaluate the development effect of TOD mode of existing rail transit stations, this paper combines the concept of TOD development and 5D principles to establish a set of urban rail transit station effectiveness evaluation index system, determines the four first-level indicators and 13 second-level indicators based on transportation, society, economy and environment, uses the analytic hierarchy method to determine the weights, and analyzes 30 stations of Shanghai Metro Line 2 as a case study.Based on the Arcgis spatial analysis technology, the data is organized and the indexes are calculated. The sites with the strongest TOD ability are Nanjing East Road and Jing'an Temple, the worst sites are Pudong International Airport and Haitian Third Road, their gap mainly lies in the level of economic development around the stations and the degree of crowd gathering,and finally the paper combined with the evaluation results to give development suggestions, this method can be used to study the level of development of rail transit stations in different cities and different regions. This method can be used to study the development level of rail transit stations in different cities and regions, and give suggestions for improving the TOD situation of stations.

Assessment of Physical activity Level and Sedentary Behaviour Among Pune City Police Personnel Using Global Physical Activity Questionnaire: A Survey

Background: Policemen being an integral part of the law implementation system have long working hours with huge workloads. They may not be able to save time for regular exercise or eat timely healthy meals which may put them at high risk of developing non-communicable diseases like cardiovascular diseases, diabetes, or lifestyle disorders such as obesity. The purpose of this study was to assess their existing physical activity level and sedentary behaviour using Global Physical Activity Questionnaire version 2.0. Objective: To assess the level of physical activity in police officers during work, travel and leisure-time and also determine the sedentary behaviour in them. Method: A cross-sectional study was conducted on 270 policemen, 168 males and 102 females, from 16 different police station of the Pune city using Global Physical Activity Questionnaire. Along with the analysis of demographic factors, data was analysed to evaluate if the study participants met the criteria for physical activity recommended by WHO. Participants were then divided into different categories depending on their energy expenditure i.e., MET-mins/week. Their sedentary behavior was calculated in terms of hours spent in sitting position. Result: Out of the total study participants, 50.4% were physically active and 49.6% were physically inactive.3.7% study participants were involved in the moderate-intensity physical activity at the workplace; 32.2% study participants were active in travel domain and 54.8%in leisure-time domain.12.2% of study participants were involved in vigorous-intensity physical activity in leisure-time domain only. 134 participants were inactive, 132 were low-active, 4 were moderately-active with not a single participant in highly-active category. The average amount of time spent sitting in the male participants was 6.11 + 3.03 hours whereas in female participants it was 7.50 + 2.62 hours. Conclusion: Even though 50.4% policemen were physically active, most of them were “low- active” and very few were “moderately-active” whereas not a single study participant was found to be “highly-active”. Sedentary behaviour in terms of average amount of time spent sitting was found to be more in female than male participants. Also,51.11% percentage of the study participants belonged to the overweight and obese category. Thus, there is huge scope for improving the physical activity level as well reducing the sedentary behavior in these professionals. KEY WORDS: GPAQ, physical activity, sedentary behavior, police personnel, Pune city.

Symbolic and Transformative: Alignments Toward Feminicídio Legal Reform inside the Brazilian Police

Abstract Feminism travels unevenly through state structures, and the state’s incorporation of feminist ideas remains controversial within feminist movements. This study uses the Brazilian Feminicídio Law, which increases punishment for gender-based homicides, as a case study to ask how law enforcement actors adopt a feminist legal reform. Data come from one year of in-depth fieldwork across police stations in a major Brazilian city and from newspaper articles. I show that state actors accept the feminist legal frame based on previous understandings of police practices. However, institutional divisions led them to develop different alignments toward the new legal reform. While police officers from the homicide division symbolically align toward feminicídio and do not aim to change police practices, officers from the women’s division perceive feminicídio as an opportunity to claim significant changes in police practices, revealing a transformative alignment. Struggles over legitimation and diverging professional beliefs and interests explain the two distinct responses.

Air pollution prediction system using XRSTH-LSTM algorithm.

Globally, there are significant worries about the rise in air pollution (AP) from substances that are harmful to human health, different living forms, and unfavorable environmental imbalances. To overcome the problem, AI-based prediction model is the need of the hour. Therefore, an attempt was made to develop a novel AP prediction system based on Xavier Reptile Switan-h-based Long-Short Term Memory (XRSTH-LSTM), which undergoes fine-tuning at various steps such as pre-processing, attribute extraction, and air-quality index prediction, in order to reduce computational cost and also to increase accuracy as well as precision. The dataset used to train the proposed methodology is Air Quality Data in India (2015-2020), taken from publically available sources Kaggle. The dataset includes information on the AQI and air quality at different stations in numerous Indian cities at hourly and daily intervals. The accuracy has been calculated using MSE, MAPE, RMSE, precision, recall, and F-measure. The robustness of the proposed model is tested using parameters such as negative predicted value and Mathew correlation coefficient. The proposed model is found to efficiently process air quality with an improved accuracy of 98.52% and precision of 99.79%, which is 0.74% higher than the existing state-of-the-art model. The testing findings showed that the proposed approach worked better than the current models and offered a higher rate of accuracy in predicting air pollution.

The Influence Of Product Quality, Service Quality, Price, And Place On Oil Fuel Purchase Decisions In Pertashop Lumajang District

Public Fuel Filling Stations (SPBU) in the collaboration system with Pertamina are very important. Of course, Pertamina must work well with gas stations, which are public places or infrastructure where the general public can meet their fuel needs. This form of cooperation doesn't end there, many small gas stations are standing in various cities to remote villages, starting from pertamini, pertashop, nitro and the like, by selling similar fuel oil to cover areas difficult to reach by large gas stations in cities. As was done by village-owned enterprises (Bumdes) in Bodang Village, Padang Lumajang District, they collaborated with establishing Pertashop type Pertamax ron 92. This study aims to analyze the effect of product quality, service quality, price and place on the decision to purchase fuel oil at Pertashop. Bodang Village, Padang Lumajang District. This study uses a quantitative method by looking for causal associative relationships . The data were obtained from a population of consumers purchasing personal fuel oil with a sample of 100 respondents. The data that has been collected is then analyzed using multiple linear regression analysis using the SPSS application. While the sampling technique uses non-probability sampling with accidental sampling . In conclusion, the results obtained are that product quality, service quality, price and location have a positive effect on the decision to purchase fuel oil at the Pertashop in Bodang Village.

TOD mode: study on land planning and land use optimization for urban rail transit station area

The rational planning of land around rail transit stations in cities can effectively improve the convenience of transportation and economic development of cities. This paper briefly introduced the transit-oriented development (TOD) mode of urban planning. We constructed a hierarchical structure for evaluating the quality of land plan-ning of urban rail transit stations through the analytic hierarchy process (AHP) method. The structure started from three large aspects, i.e., traffic volume, regional environmental quality, and regional economic efficiency, and every large aspect was divided into three small aspects. Then, an optimization model was established for land planning of rail transit stations. The land planning scheme was optimized by a genetic algorithm (GA). To enhance the optimization performance of the GA, it was improved by coevolution, i.e., plural populations iterated inde-pendently, and every population replaced the poor chromosomes in the other populations with its excellent chro-mosomes in the previous process. Finally, the Jinzhonghe street station in Hebei District, Tianjin city, was taken as a subject for analysis. The results suggested that the improved GA obtained a set of non-inferior Pareto solutions when solving a multi-objective optimization problem. The distribution of solutions in the set also indicated that any two objectives among traffic volume, environmental quality, and economic efficiency was improved at the cost of the remaining objectives. The land planning schemes optimized by the particle swarm optimization (PSO) algo-rithm, the traditional GA, and the improved GA, respectively, were superior than the initial scheme, and the opti-mized scheme of the improved GA was more in line with the characteristics of the TOD mode than the traditional one and the PSO algorithm, and the fitness value was also higher. In conclusion, the GA can be used to optimize the planning design of land in rail transit areas under the TOD mode, and the optimization performance of the GA can be improved by means of coevolution.

Assessment Of Air Pollution And Its Association With Population Health: Geo-Statistical Evidence From Pakistan

Human health is harmed by air pollution. The objective of this research was to show that air pollution in Pakistan is getting worse and is negatively impacting people’s health. IQ Air and the Institute for Health Metrics and Evaluation provided the data for this descriptive research. Monthly data of PM2.5 μg/m³ from ten different localities across Pakistan are used to show spatial distribution through the geospatial technique of interpolation. The findings show that two third of the country has high PM2.5 concentration, with Lahore as the most polluted city. In Pakistan, solid fuel use has decreased, leading to a decline in associated mortality and morbidity. However, there have been significant increases in PM2.5 and ozone levels, resulting in a rise in the country’s overall health burden caused by air pollution. Furthermore, the number of deaths attributed to air pollution has also increased since 1990. A total of 57% of chronic obstructive pulmonary disease, 40% of lower respiratory infections, 36% of ischemic stroke, 35% of ischemic heart diseases, 32% of lung cancer, 25% of diabetes, and 20% of neonatal outcomes are directly attributed to air pollution in Pakistan. The main contributors to air pollution are population growth, growing motorization, and unsustainable energy usage. The main challenges due to air pollution control and monitoring in Pakistan include a lack of awareness, poor policy creation and implementation, the use of improper fuel, rising energy demands, and an absence of pollution monitoring stations in most cities. Therefore, there is a need for a robust air pollution monitoring system, increased public awareness, and the implementation of clean and sustainable policies to regulate this environmental health issue.

Classification and determinants of high-speed rail stations using multi-source data: A case study in Jiangsu Province, China

High-speed rail (HSR) stations play a vital role in the HSR system. HSR stations not only facilitate the accessibility of interregional transportation but also stimulate population movements across various cities in China. HSR stations in different cities can vary greatly, and an efficient HSR system requires an in-depth understanding of the interrelations between the related influential factors and spatiotemporal passenger flow patterns of different HSR stations. This study adopts a new scheme for clustering HSR stations based on passengers' arrival and departure time series using mobile phone data in Jiangsu, China. To this end, 71 HSR stations are clustered into 3 classes and the spatiotemporal characteristics of passenger flow at different stations are compared. Finally, a geographically weighted multinomial logit model (GWMNL) is built to explore the influence of the built environment, socioeconomic indicators, and HSR station attributes on the classification results of HSR stations related to the time-varying characteristics of passenger flow. The model results show that the number of entertainment POIs, population, population density, area, GDP and building area are significantly associated with the classification results of HSR stations. Additionally, for HSR stations under the same classification result, these variables also have different effects on them in the geographical dimension. According to these findings, quantitative analysis of the linkages between the passenger flow patterns at different HSR stations and the impacting factors would offer implications for planners and policymakers in HSR station planning and associated urban development.

Hydrogen station allocation based on equilibrium traffic flow

The deployment of hydrogen refueling stations is vital to the development of fuel cell vehicles. Past studies on the hydrogen refueling stations didn't consider congestion on paths and assumed all flows are on the shortest paths of OD pairs, which is not consistent with travelers' route choice behavior. In this paper, we study flow refueling location allocation based on the user-equilibrium (UE) status, which is consistent with travelers' route choice behavior. We present a flow-capturing location allocation (FCLA) model on UE conditions. We also presented an equilibrium algorithm avoiding cannibalization to solve the model. Based on the transportation network of Anaheim city in California in the US, we compared the results of applying a non-equilibrium method to the FCLA model and applying the equilibrium method to the FCLA model on UE conditions. The results of the two algorithms and models are different. The equilibrium model and algorithm can capture more flow and has a higher flow-capturing ratio. What's more, the equilibrium model and algorithm can fully capture the expected flow in practice since the real transportation network is basically in UE status. The equilibrium model and algorithm presented in this paper is the first study of this kind to locate stations in cities and is useful in the deployment of hydrogen refueling stations.

Prediction of PM2.5 Concentration Based on CNN-BiGRU Model

The issue of air pollution has always been a concern. Bad smog weather not only brings inconvenience to people's travel, but also poses a threat to people's health. PM2.5 concentration is an important indicator of air conditions. Therefore, it is of long-term significance to analyze and predict the concentration of PM2.5. Aiming at the problem that a single machine learning model cannot consider the impact of multiple factors on PM2.5 concentration changes, and the data characteristics are complex, which cannot better capture all the characteristics of the data, and cannot highlight the regularity of PM2.5 changes over time, the construction of a combined model further improves the prediction accuracy. Firstly, based on the PM2.5 concentration values, air quality data, and meteorological data at various stations in New Taipei City, Taiwan Province, through analyzing the spatiotemporal distribution characteristics of the PM2.5 concentration at the target station, as well as the correlation with various pollutant factors and meteorological factors, Spearman correlation analysis is used for feature selection. The combined model CNN-BiGRU constructed in this paper utilizes its unique convolution operation to extract features from one-dimensional data, and combines the circular neural network BiGRU with bidirectional transmission function to model and predict PM2.5 concentration based on the functional advantages of both parties.

Prediction of PAHs Content in Soil Around Gas Stations in Beijing Based on BP Neural Network

With the rapid development of urbanization in China, the number of gas stations in cities is increasing. The composition of oil products in gas stations is complex and diverse, and a series of pollutants will be generated in the process of oil diffusion. Polycyclic aromatic hydrocarbons (PAHs) produced by gas stations can pollute the nearby soil and affect human health. In this study, soil samples (0-20 cm) near 117 gas stations in Beijing were collected, and the contents of seven PAHs were analyzed. Based on the BP neural network model, the contents of PAHs in soil of Beijing gas stations in 2025 and 2030 were predicted. The results showed that the total concentrations of the seven PAHs were 0.01-3.53 mg·kg-1. The concentrations of PAHs were lower than the soil environmental quality risk control standard for soil contamination of development land (Trial) GB 36600-2018. At the same time, the toxic equivalent concentrations (TEQ) of the above seven PAHs were lower than the standard value (1 mg·kg-1) of the World Health Organization (WHO), which they indicate a lower risk to human health. The prediction results showed that the rapid development of urbanization had a positive correlation with the increase in soil PAHs content. By 2030, the content of PAHs in Beijing gas station soil will continue to grow. The predicted concentrations of PAHs in the soil of Beijing gas stations in 2025 and 2030 were 0.085-4.077 mg·kg-1and 0.132-4.412 mg·kg-1, respectively. The contents of seven PAHs were lower than the soil pollution risk screening value of GB 36600-2018; however, the concentration of PAHs increased over time.The contents of PAHs in Chaoyang, Fengtai, and Haidian were relatively higher, which requires further attention.

Spatial analysis of particulate matter (PM10) using MODIS aerosol optical thickness observations and GIS over East Malaysia

Even though there are expert monitoring and assessment stations in large cities, air quality monitoring and measurement have a high cost and face significant issues. Data on air pollution can be acquired from remote sensing satellites for large areas and at a reasonable expense to compensate for monitoring stations on the ground. This research presented a method for retrieving PM10 from Moderate Resolution Imaging Spectroradiometer (MODIS) satellite Aerosol Optical Thickness (AOT) records. The study depends on a previously established equation to retrieve PM10 over Malaysia in September 2014. In Contrast Reduction Technique, we used Aerosol Robotic Network AERONET AOT to define the reference. The conversion factors, representing the relationship between AOT and PM10 satellite columns, were determined using a mathematical approach. The size and type of aerosol, relative humidity, and boundary layer height vary globally and seasonally, thus the AOT–PM10 relationship fluctuates spatially and temporally. The conversion factor was then applied to the MODIS image to predict the surface level of PM10 concentrations in micrograms via cubic meter (μg/m3). Moreover, the achieved correlation coefficient R2 of calculated PM10 based on ground truth data was equal to 0.92. Based on the results obtained from the thematic maps, PM10 levels are significantly higher in specific cities such as Kuala Lumpur and Johor. Where PM10 ranged from (26.5 to 72) µg/m3, while AOT values were between (0.12 and 0.83). It raises concerns about the environmental health threats and their relationship to air quality in these regions as a research topic.

Comparison of gasoline and hydrogen pathways in order to reduce the environmental hazards of a solar-hydrogen refueling station: Evaluation based on life cycle cost and Well-To-Wheel models

Today, due to increasing concerns about the use of fossil fuels, renewables have been introduced as a popular, efficient and green alternative. Since the transportation sector is one of the most important energy consumers, attention has been directed to the management of this energy consuming sector. It was proven that the development of electric-hydrogen vehicles can significantly reduce environmental concerns and dependence on fossil fuels in the transportation sector. However, improving the infrastructure of hydrogen refueling stations (HRSs) due to the high cost of hydrogen requires more and detailed works. In this article, the conceptual design and economic evaluation of an on-site HRS based on a photovoltaic (PV)-based solar unit coupled with the power grid has been developed and evaluated under various parameters and scenarios. The planned HRS is also comprised of a water electrolysis process (employing a polymer electrolyte membrane (PEM) electrolyzer unit), and hydrogen storage and dispenser. In the developed economic assessment, the levelized cost of hydrogen (LCOH) is calculated and discussed for different scenarios and plans based on the different size of the HRS and energy management approaches. The development of such refueling stations in cities can be an effective direction to achieve sustainable development. In addition, in order to increase believability, globalization and improve economic sustainability, an economic incentive approach based on Well-To-Wheel assessment (WTWA) and life cycle cost assessment (LCCA) was developed. The developed incentive strategy can lead to a decrease in the value of LCOH. A comprehensive comparison between hydrogen and gasoline refueling pathways is also provided. The outcomes indicated that, by applying the proposed economic incentives, the values of LCOH can be reduced by almost 15.5% and 2.98%, respectively, for discounted payback period s of 8 and 10 years. It was also found that, the WTWA index for the gasoline pathway is almost 33.8% higher compared to the hydrogen pathway. In addition, when the participation percentage of the PV-based solar unit is assumed to be 50% and 75%, the value of the WTWA index of the hydrogen pathway is reduced by approximately 25.3% and 62.8% compared to the gasoline pathway.

Estimating atmospheric radon deviation using statistical coefficients: Sulaymaniyah city, Iraq, as a case of study

ABSTRACT The authors studied the atmospheric radon concentration with associated meteorological parameters variation during the dust events from July to November 2017. We obtained the meteorological parameters data in weather station of Sulaymaniyah city, Iraq. In the environmental monitoring plan, the atmospheric radon fluctuated from 15 to 48 Bq m–3 around the mean value of 31.5 ± 7 Bq m–3 within the summer. In autumn, varied from 22 to 46 Bq m–3 with a mean value of 34 ± 12 Bq m–3. We employed this to determine the radon level anomalously. Using the modified statistical coefficients, such as the residual deviation (RD), residual fluctuation ratio (RFR), F-test, and p-value coefficients. Among the atmospheric radon fluctuation values, particularly one anomalous (42 Bq m–3) on 25 July was determined because the excessive value of the RD was 1.9 σ, and the RFR value was 66 %. Corresponding to our coefficients criteria, the minimum level of atmospheric radon (22 Bq m–3) does not consider anomalous because of increasing wind speed. Based on this, our method for determining the atmospheric radon anomalies that are influenced by the missed factors beyond the mentioned meteorological parameters is accurate.

SPAP: Simultaneous Demand Prediction and Planning for Electric Vehicle Chargers in a New City

For a new city that is committed to promoting Electric Vehicles (EVs), it is significant to plan the public charging infrastructure where charging demands are high. However, it is difficult to predict charging demands before the actual deployment of EV chargers for lack of operational data, resulting in a deadlock. A direct idea is to leverage the urban transfer learning paradigm to learn the knowledge from a source city, then exploit it to predict charging demands, and meanwhile determine locations and amounts of slow/fast chargers for charging stations in the target city. However, the demand prediction and charger planning depend on each other, and it is required to re-train the prediction model to eliminate the negative transfer between cities for each varied charger plan, leading to the unacceptable time complexity. To this end, we design an effective solution of S imultaneous Demand P rediction A nd P lanning ( SPAP ): discriminative features are extracted from multi-source data, and fed into an Attention-based Spatial-Temporal City Domain Adaptation Network ( AST-CDAN ) for cross-city demand prediction; a novel Transfer Iterative Optimization ( TIO ) algorithm is designed for charger planning by iteratively utilizing AST-CDAN and a charger plan fine-tuning algorithm. Extensive experiments on real-world datasets collected from three cities in China validate the effectiveness and efficiency of SPAP . Specially, SPAP improves at most 72.5% revenue compared with the real-world charger deployment.

Multiple Monitoring Stations in Big Cities: First Example of Three Spore Traps in Rome

(1) Background: Rome is a municipality with an area of 1287 km2 and presents floristic-vegetational complexity that is reflected in the composition of aerospora, which are responsible for pollinosis. The presence of airborne pollen can be detected by pollen monitoring. The large extent of the city’s territory makes it possible to verify possible changes in pollen composition in different sites of the city. With this in mind, a study was conducted to assess the differences in airborne pollen concentration, considering phenological and production indicators at three different sites in the city. (2) Methods: Pollen data of eight taxa were considered, Alnus spp., Castanea sativa Miller, Cupressaceae-Taxaceae, Olea europaea L., Platanaceae, Poaceae, Quercus spp., and Urticaceae, during 2020 and 2021, using three monitoring samplers. The airborne pollen concentration and the seasons of the three centers were calculated and compared with each other. (3) Results: The diversity between the three samplers shows a phenological succession in accordance with the microclimatic diversity present in the city. The heterogeneity of the airborne pollen concentration reflects the floristic-vegetational diversity, while qualitative and quantitative parameters indicate a homogeneous flowering trend reflecting the seasonality of the various species. (4) Conclusions: The present work and the Italian geographic context suggest the need for a greater number of sampling points to guarantee a true localization of the data. Having several sampling stations also contributes to the protection of health and green areas, which are difficult to manage, conserve, and maintain.

Prediction of effect of wind speed on air pollution level using machine learning technique

Abstract Air pollution is one of the most challenging issues poses serious threat to human health and environment. The increasing influx of population in metropolitan cities has further worsened the situation. Quantifying the air pollution experimentally is quite a challenging task as it depends on many parameters viz., wind speed, wind temperature, relative humidity, temperature etc. It requires the investment of huge money and manpower for controlling air pollution. Machine learning technique-based computer modelling reduces both of the parameters. In the present work, the dependence of air pollution level on wind speed and temperature has been taken up using machine learning in the form of ANN and LSTM model. The recorded data of air pollution level (PM2.5) is collected from a measurement station of Lucknow city situated at Central School, CPCB. The data is used in an Artificial Neural based network and in an LSTM model to predict suitably the level of air pollution for a known value of average wind speed and temperature without experimental measurements. LSTM model is found to predict the pollution level better than ANN for the developed ANN networks.

Kajian Manajemen Energi Listrik Pada Stasiun Pompa Air

One of the important components for a drinking water company is the operation of a pump station that functions to regulatethe water supply from existing water sources to customers. To operate the water pump, an electric motor is needed as the driving force. Inorder for the energy consumption needed to operate an electric motor to be regulated, it is necessary to manage electrical energy at thepump station. One example of a pump station is the local water company (PDAM) Unit Wendit Malang City. This unit consists of 3 pumpstations namely Wendit 1, Wendit 2 and Wendit 3. These three parts are supplied by 2 transformers with a capacity of 1110 kVA for Wendit2 and 1730 kVA for Wendit 1 and 3.From the results of power factor measurements in the three sections , it is known that the power factorvalue at the Wendit 3 pump station is 0.82. This value does not meet the PLN minimum standard, which is 0.85. If the power factor is lessthan 0.85 then the industry will incur the excess reactive power consumption (kVARh) charges. Therefore it is necessary to study energymanagement at the pump station of PDAM Unit Wendit Malang City. To improve the low power factor, two recommendations were given,namely the installation of VSD (Variable Speed Drive) at the PDAM Unit Wendit 1 and 3 pump stations and the installation of a CapasitorBank at the PDAM Unit Wendit 2 pump station.Based on the analysis, the power factor value PDAM Wendit 3, which was originally 0.82increased to 0.9. In addition, there are savings in electricity consumption per month of 10.48% at PDAM Unit Wendit 1 and 3 and 28.32%at PDAM Unit Wendit 2.