scholarly journals Mapping pediatric A&E respiratory presentations with air quality

2018 ◽  
Vol 3 (2) ◽  
Author(s):  
Dermot Glackin
Keyword(s):  
Public Health ◽  
Emergency Department ◽  
Air Quality ◽  
Air Pollutants ◽  
Causal Link ◽  
Quality Monitoring ◽  
Quality Data ◽  
Air Quality Monitoring ◽  
Respiratory Condition ◽  
Air Quality Data

IntroductionWest Belfast Partnership Board undertook a collaborative public health investigation to explore what if any correlation exists between air quality and children from the Falls Divis area presenting to RBHSC with a respiratory condition. BackgroundAn analysis of Emergency Department Attendances showed monthly trend in 2015/16 differed from previous years with a peak in November 2015 which was 27% higher than the number of attendances in November of 2014. The overall increase in 2015/16 across the 4 main paediatric categories was 10%. The increase for respiratory was 34% higher. West Belfast accounted for 32% (248n) of this spike. There exists a compelling case for linkage between air quality and a range of conditions which is socially patterned. Falls and Divis area appears in the top 3 areas of multiple deprivation. ApproachWe identified periods of elevated paediatric presentation at A&E with repository compliant and mapped over air quality monitoring data from the same period in the Falls Divis area; Factoring potential incubation time between exposure to potential harmful air pollutants. ConclusionBased upon a review of air quality data no causal link was established between air quality and periods of elevated presentation of children at A&E with respiratory evident.

Air Quality Data Management System Based on VB.NET

2014 ◽  
Vol 955-959 ◽  
pp. 1147-1150
Author(s):  
A Gu Da Mu Liu ◽  
Peng Yang ◽  
Wen Sheng Lv ◽  
Jie Liu
Keyword(s):  
Air Quality ◽  
Data Management ◽  
Management System ◽  
System Development ◽  
Quality Monitoring ◽  
Monitoring Data ◽  
Data Management System ◽  
Quality Data ◽  
Air Quality Monitoring ◽  
Air Quality Data

In order to achieve the automatic management of air quality monitoring data, the air quality data management system has been developed using VB.NET platform and Oracle as background database. It is also combined with the situation of the air quality in Beijing and based on the air quality monitoring data. The paper analyzes the system from 6 aspects, including technology selection, system architecture, system data flow diagram, system development environment, system functions and system features. Finally this paper explains the significance of the system development and application prospects.

scholarly journals VARMA-EGARCH Model for Air-Quality Analyses and Application in Southern Taiwan

Atmosphere ◽  
2020 ◽  
Vol 11 (10) ◽  
pp. 1096
Author(s):  
Edward Ming-Yang Wu ◽  
Shu-Lung Kuo
Keyword(s):  
Time Series ◽  
Air Quality ◽  
Air Pollutants ◽  
Quality Monitoring ◽  
Quality Data ◽  
Air Quality Monitoring ◽  
Egarch Model ◽  
Southern Taiwan ◽  
Air Quality Monitoring Stations ◽  
Monitoring Stations

This study adopted the Exponential Generalized Autoregressive Conditional Heteroscedasticity (EGARCH) model to analyze seven air pollutants (or the seven variables in this study) from ten air quality monitoring stations in the Kaohsiung–Pingtung Air Pollutant Control Area located in southern Taiwan. Before the verification analysis of the EGARCH model is conducted, the air quality data collected at the ten air quality monitoring stations in the Kaohsiung–Pingtung area are classified into three major factors using the factor analyses in multiple statistical analyses. The factors with the most significance are then selected as the targets for conducting investigations; they are termed “photochemical pollution factors”, or factors related to pollution caused by air pollutants, including particulate matter with particles below 10 microns (PM10), ozone (O3) and nitrogen dioxide (NO2). Then, we applied the Vector Autoregressive Moving Average-EGARCH (VARMA-EGARCH) model under the condition where the standardized residual existed in order to study the relationships among three air pollutants and how their concentration changed in the time series. By simulating the optimal model, namely VARMA (1,1)-EGARCH (1,1), we found that when O3 was the dependent variable, the concentration of O3 was not affected by the concentration of PM10 and NO2 in the same term. In terms of the impact response analysis on the predictive power of the three air pollutants in the time series, we found that the asymmetry effect of NO2 was the most significant, meaning that NO2 influenced the GARCH effect the least when the change of seasons caused the NO2 concentration to fluctuate; it also suggested that the concentration of NO2 produced in this area and the degree of change are lower than those of the other two air pollutants. This research is the first of its kind in the world to adopt a VARMA-EGARCH model to explore the interplay among various air pollutants and reactions triggered by it over time. The results of this study can be referenced by authorities for planning air quality total quantity control, applying and examining various air quality models, simulating the allowable increase in air quality limits, and evaluating the benefit of air quality improvement.

scholarly journals A WEB API AND WEB APPLICATION DEVELOPMENT FOR DISSEMINATION OF AIR QUALITY INFORMATION

2017 ◽  
Vol IV-4/W4 ◽  
pp. 373-378 ◽  
Author(s):  
K. Şahin ◽  
U. Işıkdağ
Keyword(s):  
Air Quality ◽  
Web Service ◽  
Monitoring Network ◽  
Data Access ◽  
Quality Monitoring ◽  
Quality Data ◽  
Series Data ◽  
Air Quality Monitoring ◽  
Air Quality Data

Various studies have been carried out since 2005 under the leadership of Ministry of Environment and Urbanism of Turkey, in order to observe the quality of air in Turkey, to develop new policies and to develop a sustainable air quality management strategy. For this reason, a national air quality monitoring network has been developed providing air quality indices. By this network, the quality of the air has been continuously monitored and an important information system has been constructed in order to take precautions for preventing a dangerous situation. The biggest handicap in the network is the data access problem for instant and time series data acquisition and processing because of its proprietary structure. Currently, there is no service offered by the current air quality monitoring system for exchanging information with third party applications. Within the context of this work, a web service has been developed to enable location based querying of the current/past air quality data in Turkey. This web service is equipped with up-todate and widely preferred technologies. In other words, an architecture is chosen in which applications can easily integrate. In the second phase of the study, a web-based application was developed to test the developed web service and this testing application can perform location based acquisition of air-quality data. This makes it possible to easily carry out operations such as screening and examination of the area in the given time-frame which cannot be done with the national monitoring network.

scholarly journals Short-term environmental impact of ambient air quality trends in during the COVID-19 pandemic in India

2021 ◽  
Vol 5 (1) ◽  
pp. 017-025
Author(s):  
Karuppasamy Manikanda Bharath ◽  
Natesan Usha ◽  
Periyasamy Balamadeswaran ◽  
S Srinivasalu
Keyword(s):  
Air Quality ◽  
Ambient Air ◽  
Air Pollutant ◽  
Quality Monitoring ◽  
Quality Data ◽  
Air Quality Monitoring ◽  
The North ◽  
Air Quality Monitoring Stations ◽  
Air Quality Data ◽  
Monitoring Stations

The lockdown, implemented in response to the COVID-19 epidemic, restricted the operation of various sectors in the country and its highlights a good environmental outcome. Thus, a comparison of air pollutants in India before and after the imposed lockdown indicated an overall improvement air quality across major Indian cities. This was established by utilizing the Central Pollution Control Board’s database of air quality monitoring station statistics, such as air quality patterns. During the COVID-19 epidemic, India’s pre-to-post nationwide lockdown was examined. The air quality data was collected from 30-12-2019 to 28-04-2020 and synthesized using 231 Automatic air quality monitoring stations in a major Indian metropolis. Specifically, air pollutant concentrations, temperature, and relative humidity variation during COVID-19 pandemic pre-to-post lockdown variation in India were monitored. As an outcome, several cities around the country have reported improved air quality. Generally, the air quality, on a categorical scale was found to be ‘Good’. However, a few cities from the North-eastern part of India were categorized as ‘Moderate/Satisfactory’. Overall, the particulate matters reduction was in around 60% and other gaseous pollutants was in 40% reduction was observed during the lockdown period. The results of this study include an analysis of air quality data derived from continuous air quality monitoring stations from the pre-lockdown to post-lockdown period. Air quality in India improved following the national lockdown, the interpretation of trends for PM 2.5, PM 10, SO2, NO2, and the Air Quality Index has been provided in studies for major cities across India, including Delhi, Gurugram, Noida, Mumbai, Kolkata, Bengaluru, Patna, and others.

scholarly journals Game-Like 3D Visualisation of Air Quality Data

2020 ◽  
Vol 4 (3) ◽  
pp. 54
Author(s):  
Bruno Teles ◽  
Pedro Mariano ◽  
Pedro Santana
Keyword(s):  
Air Quality ◽  
Visual Cues ◽  
Empirical Support ◽  
Quality Monitoring ◽  
Quality Data ◽  
Urban Air ◽  
Air Quality Monitoring ◽  
Usability Tests ◽  
3D Game ◽  
Air Quality Data

The data produced by sensor networks for urban air quality monitoring is becoming a valuable asset for informed health-aware human activity planning. However, in order to properly explore and exploit these data, citizens need intuitive and effective ways of interacting with it. This paper presents CityOnStats, a visualisation tool developed to provide users, mainly adults and young adults, with a game-like 3D environment populated with air quality sensing data, as an alternative to the traditionally passive visualisation techniques. CityOnStats provides several visual cues of pollution presence with the purpose of meeting each user’s preferences. Usability tests with a sample of 30 participants have shown the value of air quality 3D game-based visualisation and have provided empirical support for which visual cues are most adequate for the task at hand.

scholarly journals AirQMon: Indoor Air Quality Monitoring System Based on Microcontroller, Android and IoT

2020 ◽  
Vol 6 (2) ◽  
pp. 251
Author(s):  
Jacquline Waworundeng ◽  
Walfarid Hermawan Limbong
Keyword(s):  
Air Quality ◽  
Indoor Air Quality ◽  
Monitoring System ◽  
Indoor Air ◽  
Quality Monitoring ◽  
Quality Data ◽  
Air Quality Monitoring ◽  
Arduino Uno ◽  
Air Quality Data ◽  
Human Awareness

Humans were often unaware of the risk of contaminated indoor air quality. Based on this, the researcher designs an Indoor Air Quality Monitoring System based on Arduino which could help to raise the human awareness of air quality. This research is based on the Prototyping method. The system hardware built with Arduino Uno which connected to MQ135 sensor to monitor the air quality and Sound Buzzer to sound an alarm whenever the sensor sensed the air quality in a risky value. The Ethernet Shield is used to connect the Arduino Uno to the internet, which enables the process to upload the data which has been read by the sensor to an IoT platform called ThingSpeak. The air quality data which uploaded to ThingSpeak, then retrieved by AirQmon, a customized Android application developed by the researcher to monitor the air quality which is installed on the smartphone. The data is presented graphically to the user through AirQmon apps. This system results in a form of a device and application which could potentially be used as a monitoring system and raise human awareness of indoor air quality.

scholarly journals THE ANALYSE OF AIR ENVIRONMENT QUALITY MONITORING IMPROVEMENT POSSIBILITIES

2015 ◽  
Vol 1 ◽  
pp. 273
Author(s):  
Gotfrīds Noviks ◽  
Andris Skromulis
Keyword(s):  
Air Quality ◽  
Air Pollutants ◽  
Quality Evaluation ◽  
Quality Monitoring ◽  
Dust Particles ◽  
Action Program ◽  
Air Quality Monitoring ◽  
Environment Quality ◽  
Air Quality Measurements ◽  
Quality Measurements

Paper presents the results of air pollution analyses during last 8 years in Rezekne city. There is carried out a research of atmospheric dust particles, found correlations between concentrations of different air pollutants. Is given overview about air quality measurements in other countries, pointed out air ionization importance on air quality evaluation. The aim of the research – to ground the extension of air quality monitoring indicators including parameters of the air ionisation and to work out an action program to improve an air quality in working areas and recreating zones.

scholarly journals Healthier breath for all and everywhere – Urban air quality monitoring experience

2019 ◽  
Vol 29 (Supplement_4) ◽  
Author(s):  
J Gajic ◽  
D Dimovski ◽  
B Vukajlovic ◽  
M Jevtic
Keyword(s):  
Public Health ◽  
Air Pollution ◽  
Air Quality ◽  
Health Risk ◽  
Urban Health ◽  
Urban Areas ◽  
Danube River ◽  
Quality Monitoring ◽  
Air Quality Monitoring ◽  
Residential Areas

Abstract Issue/problem Increasing attention is being paid to air pollution as one of the greatest threats to public and urban health. The WHO’s Urban Health Initiative points out the importance of collecting data and mapping the present state of air quality in urban areas. For citizens, such engagement is enabled by the appearance of personal air quality measurement devices that use crowd-sourcing to make measurement results publicly accessible in real time. Description of the problem As a way of contributing to air pollution monitoring in their town, three PhD Public health students conducted over 40 measurements between the start of June and end of August 2018 on various locations in the city of Novi Sad, Serbia. Measurements were performed using AirBeam personal air quality monitoring devices and their results presented as μg/m3 of Particulate Matter 2.5 (PM2.5) and automatically uploaded to the internet using the Air-casting app. Results Measurements conducted in public transportation vehicles returned the rather high average value of 40 μg/m3, where coffee shops and restaurants scored an even higher value of 48,67 μg/m3. The lowest average air pollution levels were registered near the Danube river bank (5.67) and in the parks (6), while the sites near crossroads or in the street showed average air pollution of 8.33 μg/m3. Residential areas where smoking is present during the day reported 2.5 times higher PM2.5 values than those without smokers (33.8 and 12.78 μg/m3). Lessons Bearing in mind that the air quality is considered as a serious health risk in urban areas, results of this pilot investigation suggest potential health risk for citizens living in urban areas. The negative effects of combustion and smoking on air quality are strongly highlighted, as well as the positive impact of green areas and parks near residential areas. Key messages Air pollution exposure as a serious health risk in urban areas. Crowdsourcing as a way of air quality monitoring has great potential for contributing to public health.

scholarly journals Air Pollutants Prediction in Shenzhen Based on ARIMA and Prophet Method

2019 ◽  
Vol 136 ◽  
pp. 05001 ◽  
Author(s):  
Ziyuan Ye
Keyword(s):  
Air Quality ◽  
Hybrid Model ◽  
Air Pollutants ◽  
Moving Average ◽  
Mixing Time ◽  
Quality Monitoring ◽  
Air Quality Monitoring ◽  
Autoregressive Integrated Moving Average ◽  
Moving Average Model ◽  
Air Quality Monitoring Stations

In order to improve the accuracy of predicting the air pollutants in Shenzhen, a hybrid model based on ARIMA (Autoregressive Integrated Moving Average model) and prophet for mixing time and space relationships was proposed. First, ARIMA and Prophet method were applied to train the data from 11 air quality monitoring stations and gave them different weights. Then, finished the calculation about weight of impact in each air quality monitoring station to final results. Finally, built up the hybrid model and did the error evaluation. The result of the experiments illustrated that this hybrid method can improve the air pollutants prediction in Shenzhen.

scholarly journals Edge Computing Based IoT Architecture for Low Cost Air Pollution Monitoring Systems: A Comprehensive System Analysis, Design Considerations & Development

Sensors ◽  
2018 ◽  
Vol 18 (9) ◽  
pp. 3021 ◽  
Author(s):  
Zeba Idrees ◽  
Zhuo Zou ◽  
Lirong Zheng
Keyword(s):  
Air Quality ◽  
Power Consumption ◽  
Real Time ◽  
Low Cost ◽  
Edge Computing ◽  
Quality Monitoring ◽  
Quality Data ◽  
Monitoring Systems ◽  
Air Quality Monitoring ◽  
Computing Device

With the swift growth in commerce and transportation in the modern civilization, much attention has been paid to air quality monitoring, however existing monitoring systems are unable to provide sufficient spatial and temporal resolutions of the data with cost efficient and real time solutions. In this paper we have investigated the issues, infrastructure, computational complexity, and procedures of designing and implementing real-time air quality monitoring systems. To daze the defects of the existing monitoring systems and to decrease the overall cost, this paper devised a novel approach to implement the air quality monitoring system, employing the edge-computing based Internet-of-Things (IoT). In the proposed method, sensors gather the air quality data in real time and transmit it to the edge computing device that performs necessary processing and analysis. The complete infrastructure & prototype for evaluation is developed over the Arduino board and IBM Watson IoT platform. Our model is structured in such a way that it reduces the computational burden over sensing nodes (reduced to 70%) that is battery powered and balanced it with edge computing device that has its local data base and can be powered up directly as it is deployed indoor. Algorithms were employed to avoid temporary errors in low cost sensor, and to manage cross sensitivity problems. Automatic calibration is set up to ensure the accuracy of the sensors reporting, hence achieving data accuracy around 75–80% under different circumstances. In addition, a data transmission strategy is applied to minimize the redundant network traffic and power consumption. Our model acquires a power consumption reduction up to 23% with a significant low cost. Experimental evaluations were performed under different scenarios to validate the system’s effectiveness.

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