A Relational Database Structure for Linking Air Pollution Levels with Children’s Respiratory Illnesses

Pohoata

2016

IJERPH

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The overall objective of this research was to study children’s respiratory illness levels in Targoviste (Romania) in relationship to the outdoor concentrations of airborne particulate matter with an aerodynamic diameter below 2.5 µm (PM2.5). We monitored and analysed the PM2.5 concentrations according to a complex experimental protocol. The health trial was conducted over three months (October–December 2015) and required the active cooperation of the children’s parents to monitor carefully the respiratory symptoms of the child, i.e., coughing, rhinorrhoea, wheezing, and fever, as well as their outdoor program. We selected the most sensitive children (n = 25; age: 2–10 years) with perturbed respiratory health, i.e., wheezing, asthma, and associated symptoms. The estimated average PM2.5 doses were 0.8–14.5 µg·day−1 for weekdays, and 0.4–6.6 µg·day−1 for the weekend. The frequency and duration of the symptoms decreased with increasing age. The 4- to 5-year old children recorded the longest duration of symptoms, except for rhinorrhoea, which suggested that this age interval is the most vulnerable to exogenous trigger agents (p < 0.01) compared to the other age groups. PM2.5 air pollution was found to have a direct positive correlation with the number of wheezing episodes (r = 0.87; p < 0.01) in November 2015. Monitoring of wheezing occurrences in the absence of fever can provide a reliable assessment of the air pollution effect on the exacerbation of asthma and respiratory disorders in sensitive children.

Section: Methodsmentioning

confidence: 99%

“…The multi-criteria approach was developed for use with a database consisting of cases of children having respiratory issues, PM 2.5 records, dispersion modelling results, and meteorological data. This facilitated the production of thematic maps with specific attributes [46]. …”

Section: Methodsmentioning

confidence: 99%

Fine Particulate Matter in Urban Environments: A Trigger of Respiratory Symptoms in Sensitive Children

Pohoata

2016

IJERPH

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“…A software application was developed to collect on-line data from the official Romanian air quality website (Dunea et al 2014). Furthermore, dailyaveraged time series of 24-h recorded concentrations were extracted from the EIONET Airbase starting from the date when each automated station begun to fully operate (2009-2012 interval).…”

Section: Methodsmentioning

confidence: 99%

Using wavelet–feedforward neural networks to improve air pollution forecasting in urban environments

Pohoata

2015

Environ Monit Assess

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The paper presents the screening of various feedforward neural networks (FANN) and wavelet-feedforward neural networks (WFANN) applied to time series of ground-level ozone (O3), nitrogen dioxide (NO2), and particulate matter (PM10 and PM2.5 fractions) recorded at four monitoring stations located in various urban areas of Romania, to identify common configurations with optimal generalization performance. Two distinct model runs were performed as follows: data processing using hourly-recorded time series of airborne pollutants during cold months (O3, NO2, and PM10), when residential heating increases the local emissions, and data processing using 24-h daily averaged concentrations (PM2.5) recorded between 2009 and 2012. Dataset variability was assessed using statistical analysis. Time series were passed through various FANNs. Each time series was decomposed in four time-scale components using three-level wavelets, which have been passed also through FANN, and recomposed into a single time series. The agreement between observed and modelled output was evaluated based on the statistical significance (r coefficient and correlation between errors and data). Daubechies db3 wavelet-Rprop FANN (6-4-1) utilization gave positive results for O3 time series optimizing the exclusive use of the FANN for hourly-recorded time series. NO2 was difficult to model due to time series specificity, but wavelet integration improved FANN performances. Daubechies db3 wavelet did not improve the FANN outputs for PM10 time series. Both models (FANN/WFANN) overestimated PM2.5 forecasted values in the last quarter of time series. A potential improvement of the forecasted values could be the integration of a smoothing algorithm to adjust the PM2.5 model outputs.

“…The data used in the ROKIDAIR research project to synthesize the key information on the impact of PM 2.5 pollution on children's health in urban areas, were integrated into a database management system that was divided into several sub-database, as follows [13]: AIRBASE EIONET pollutant database recorded by national monitoring stations located in the envisaged areas (Targoviste and Ploiesti cities); Current levels of air pollution database (an application that extracts specific information from other e-platforms e.g., www.calitateaer.ro); Meteorological parameters database recorded at world meteorological stations (WMO) from Targoviste (WMO_id 153750) and Ploiesti (WMO_id 153770); Medical database; Receptor database (children residential address, kindergartens, schools, playgrounds, and pediatric hospitals). Fig.…”

Section: A the Data Layermentioning

confidence: 99%

A Cyberinfrastructure for Air Quality Monitoring and Early Warnings to Protect Children with Respiratory Disorders

2015 20th International Conference on Control Systems and Computer Science

Lungu

et al. 2015

Self Cite

Air pollution and health are closely connected. An efficient management of air quality involves the collecting and analysis of a wide variety of data types that make cyberinfrastructures especially important for this scientific field. In the new information-driven world, a cyberinfrastructure allows to bring people together, high performance computational platforms, data integration techniques, visualization, and analysis tools, with the aim to make the research more effective and efficient. Currently, there is an important requirement for the development of information networks that are specific to air quality management, promoting the exchange and integration of data and applications. The paper presents the developing of a cyberinfrastructure for air quality management to protect children's health in Romania developed by ROKIDAIR research project. This infrastructure combines already existing air quality monitoring systems with new modes of data processing and displaying to be accessed by the concerned parents of children.