scholarly journals Estimation of vehicular emissions and PM2.5 – A case study in Madurai city

2021 ◽  
Vol 23 (11) ◽  
pp. 475-483
Author(s):  
D Nancy Deborah ◽  
◽  
R Velkennedy ◽  

Air quality monitoring, as important as it is, is impeded by a shortage of monitoring stations in nations like India. This research takes a different approach of monitoring and estimating automobile emissions. This is a case study that is only have been used in Madurai at this juncture. The use of a portable electro-chemical sensor at pre-determined stationary and mobile points and routes has been employed. Then after, the measurements were compared to the estimated emission values. The observations and experimental studies demonstrated that highspeed vehicle movement reduces particulate matter concentrations, and that reducing congestion could be one way to address the rising emissions crisis. One reason for the preference for airconditioned cars and fast-moving vehicles, even if it is a two-wheeler, is the average temperature. Ironically, this has resulted in an increase in vehicle emissions. Vehicle emissions were estimated, and 2.5-micron particulate matter was observed and discussed. The recommended strategy was discovered to be in agreement with the computed estimates. The proposed methodology for developing a database with minimal personnel and instrumental setup can reliably compensate the lack of data availability given the lack of monitoring stations.

2018 ◽  
Vol 24 (3) ◽  
pp. 341-358 ◽  
Author(s):  
Xiaotong Ji ◽  
Yingying Zhang ◽  
Guangke Li ◽  
Nan Sang

Recently, numerous studies have found that particulate matter (PM) exposure is correlated with increased hospitalization and mortality from heart failure (HF). In addition to problems with circulation, HF patients often display high expression of cytokines in the failing heart. Thus, as a recurring heart problem, HF is thought to be a disorder characterized in part by the inflammatory response. In this review, we intend to discuss the relationship between PM exposure and HF that is based on inflammatory mechanism and to provide a comprehensive, updated evaluation of the related studies. Epidemiological studies on PM-induced heart diseases are focused on high concentrations of PM, high pollutant load exposure in winter, or susceptible groups with heart diseases, etc. Furthermore, it appears that the relationship between fine or ultrafine PM and HF is stronger than that between HF and coarse PM. However, fewer studies paid attention to PM components. As for experimental studies, it is worth noting that coarse PM may indirectly promote the inflammatory response in the heart through systematic circulation of cytokines produced primarily in the lungs, while ultrafine PM and its components can enter circulation and further induce inflammation directly in the heart. In terms of PM exposure and enhanced inflammation during the pathogenesis of HF, this article reviews the following mechanisms: hemodynamics, oxidative stress, Toll-like receptors (TLRs) and epigenetic regulation. However, many problems are still unsolved, and future work will be needed to clarify the complex biologic mechanisms and to identify the specific components of PM responsible for adverse effects on heart health.


Foods ◽  
2020 ◽  
Vol 10 (1) ◽  
pp. 37 ◽  
Author(s):  
José S. Câmara ◽  
Bianca R. Albuquerque ◽  
Joselin Aguiar ◽  
Rúbia C. G. Corrêa ◽  
João L. Gonçalves ◽  
...  

Experimental studies have provided convincing evidence that food bioactive compounds (FBCs) have a positive biological impact on human health, exerting protective effects against non-communicable diseases (NCD) including cancer and cardiovascular (CVDs), metabolic, and neurodegenerative disorders (NDDs). These benefits have been associated with the presence of secondary metabolites, namely polyphenols, glucosinolates, carotenoids, terpenoids, alkaloids, saponins, vitamins, and fibres, among others, derived from their antioxidant, antiatherogenic, anti-inflammatory, antimicrobial, antithrombotic, cardioprotective, and vasodilator properties. Polyphenols as one of the most abundant classes of bioactive compounds present in plant-based foods emerge as a promising approach for the development of efficacious preventive agents against NCDs with reduced side effects. The aim of this review is to present comprehensive and deep insights into the potential of polyphenols, from their chemical structure classification and biosynthesis to preventive effects on NCDs, namely cancer, CVDs, and NDDS. The challenge of polyphenols bioavailability and bioaccessibility will be explored in addition to useful industrial and environmental applications. Advanced and emerging extraction techniques will be highlighted and the high-resolution analytical techniques used for FBCs characterization, identification, and quantification will be considered.


2021 ◽  
Vol 13 (15) ◽  
pp. 8263
Author(s):  
Marius Bodor

An important aspect of air pollution analysis consists of the varied presence of particulate matter in analyzed air samples. In this respect, the present work aims to present a case study regarding the evolution in time of quantified particulate matter of different sizes. This study is based on data acquisitioned in an indoor location, already used in a former particulate matter-related article; thus, it can be considered as a continuation of that study, with the general aim to demonstrate the necessity to expand the existing network for pollution monitoring. Besides particle matter quantification, a correlation of the obtained results is also presented against meteorological data acquisitioned by the National Air Quality Monitoring Network. The transformation of quantified PM data in mass per volume and a comparison with other results are also addressed.


Sensors ◽  
2021 ◽  
Vol 21 (4) ◽  
pp. 1044
Author(s):  
Yassine Bouabdallaoui ◽  
Zoubeir Lafhaj ◽  
Pascal Yim ◽  
Laure Ducoulombier ◽  
Belkacem Bennadji

The operation and maintenance of buildings has seen several advances in recent years. Multiple information and communication technology (ICT) solutions have been introduced to better manage building maintenance. However, maintenance practices in buildings remain less efficient and lead to significant energy waste. In this paper, a predictive maintenance framework based on machine learning techniques is proposed. This framework aims to provide guidelines to implement predictive maintenance for building installations. The framework is organised into five steps: data collection, data processing, model development, fault notification and model improvement. A sport facility was selected as a case study in this work to demonstrate the framework. Data were collected from different heating ventilation and air conditioning (HVAC) installations using Internet of Things (IoT) devices and a building automation system (BAS). Then, a deep learning model was used to predict failures. The case study showed the potential of this framework to predict failures. However, multiple obstacles and barriers were observed related to data availability and feedback collection. The overall results of this paper can help to provide guidelines for scientists and practitioners to implement predictive maintenance approaches in buildings.


Author(s):  
Sajan Thomas ◽  
Joselin Herbert ◽  
Jacob Thottathil Varghese ◽  
C.R.K Sathish ◽  
Abdul Quadir ◽  
...  

2020 ◽  
Vol 11 (6) ◽  
pp. 24-31 ◽  
Author(s):  
Luciana Ferreira Leite Leirião ◽  
Daniela Debone ◽  
Theotonio Pauliquevis ◽  
Nilton Manuel Évora do Rosário ◽  
Simone Georges El Khouri Miraglia

Measurement ◽  
2021 ◽  
Vol 185 ◽  
pp. 110061
Author(s):  
Sneha Gautam ◽  
Cyril Sammuel ◽  
Aniket Bhardwaj ◽  
Zahra Shams Esfandabadi ◽  
M. Santosh ◽  
...  

2013 ◽  
Vol 864-867 ◽  
pp. 1586-1591
Author(s):  
Hong Liang Zhang

In this study, an interval-parameter programming method has been used for urban vehicle emissions management under uncertainty. The model improves upon the existing optimization methods with advantages in uncertainty reflection, system costs and limitation of emission. Moreover, the model is applied to a case study of urban vehicle emissions management in a virtual city. The results indicate that the interval linear traffic planning model can effectively reduce the vehicles emission and provide strategies for authorities to deal with problems of transportation system.


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