Combined Models for Forecasting the Air Pollution Level in Infocommunication Systems for the Environment State Monitoring

2018 ◽  
Author(s):  
Alexander Kuchansky ◽  
Andrii Biloshchytskyi ◽  
Yurii Andrashko ◽  
Vladimir Vatskel ◽  
Svitlana Biloshchytska ◽  
...  
Keyword(s):  
Air Pollution ◽  
Pollution Level ◽  
State Monitoring ◽  
Combined Models

An Urban Air Pollution Early Warning System Based on PM2.5 Prediction Applied in Ploiesti City

2017 ◽  
Vol 68 (4) ◽  
pp. 858-863
Author(s):  
Mihaela Oprea ◽  
Marius Olteanu ◽  
Radu Teodor Ianache
Keyword(s):  
Air Pollution ◽  
Early Warning ◽  
Urban Areas ◽  
Early Warning System ◽  
Urban Air Pollution ◽  
Warning System ◽  
Air Pollutant ◽  
Pollution Level ◽  
Urban Air ◽  
Prediction Approach

Fine particulate matter with a diameter less than 2.5 �m (i.e. PM2.5) is an air pollutant of special concern for urban areas due to its potential significant negative effects on human health, especially on children and elderly people. In order to reduce these effects, new tools based on PM2.5 monitoring infrastructures tailored to specific urban regions are needed by the local and regional environmental management systems for the provision of an expert support to decision makers in air quality planning for cities and also, to inform in real time the vulnerable population when PM2.5 related air pollution episodes occur. The paper focuses on urban air pollution early warning based on PM2.5 prediction. It describes the methodology used, the prediction approach, and the experimental system developed under the ROKIDAIR project for the analysis of PM2.5 air pollution level, health impact assessment and early warning of sensitive people in the Ploiesti city. The PM2.5 concentration evolution prediction is correlated with PM2.5 air pollution and health effects analysis, and the final result is processed by the ROKIDAIR Early Warning System (EWS) and sent as a message to the affected population via email or SMS. ROKIDAIR EWS is included in the ROKIDAIR decision support system.

scholarly journals A global association between Covid-19 cases and airborne particulate matter at regional level

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Angelo Solimini ◽  
F. Filipponi ◽  
D. Alunni Fegatelli ◽  
B. Caputo ◽  
C. M. De Marco ◽  
...  
Keyword(s):  
Air Pollution ◽  
Particulate Matter ◽  
Negative Binomial ◽  
Numerical Models ◽  
Regional Level ◽  
Pollution Level ◽  
Observation Data ◽  
Cumulative Number ◽  
Mixed Effect

AbstractEvidences of an association between air pollution and Covid-19 infections are mixed and inconclusive. We conducted an ecological analysis at regional scale of long-term exposure to air-borne particle matter and spread of Covid-19 cases during the first wave of epidemics. Global air pollution and climate data were calculated from satellite earth observation data assimilated into numerical models at 10 km resolution. Main outcome was defined as the cumulative number of cases of Covid-19 in the 14 days following the date when > 10 cumulative cases were reported. Negative binomial mixed effect models were applied to estimate the associations between the outcome and long-term exposure to air pollution at the regional level (PM10, PM2.5), after adjusting for relevant regional and country level covariates and spatial correlation. In total we collected 237,749 Covid-19 cases from 730 regions, 63 countries and 5 continents at May 30, 2020. A 10 μg/m3 increase of pollution level was associated with 8.1% (95% CI 5.4%, 10.5%) and 11.5% (95% CI 7.8%, 14.9%) increases in the number of cases in a 14 days window, for PM2.5 and PM10 respectively. We found an association between Covid-19 cases and air pollution suggestive of a possible causal link among particulate matter levels and incidence of COVID-19.

scholarly journals Scalable kernel-based SVM classification algorithm on imbalance air quality data for proficient healthcare

2021 ◽  
Author(s):  
Shwet Ketu ◽  
Pramod Kumar Mishra
Keyword(s):  
Air Pollution ◽  
Air Quality ◽  
Class Imbalance ◽  
Imbalanced Data ◽  
Classification Algorithm ◽  
Quality Data ◽  
Pollution Level ◽  
Classification Problems ◽  
Chi Square ◽  
The Impact

AbstractIn the last decade, we have seen drastic changes in the air pollution level, which has become a critical environmental issue. It should be handled carefully towards making the solutions for proficient healthcare. Reducing the impact of air pollution on human health is possible only if the data is correctly classified. In numerous classification problems, we are facing the class imbalance issue. Learning from imbalanced data is always a challenging task for researchers, and from time to time, possible solutions have been developed by researchers. In this paper, we are focused on dealing with the imbalanced class distribution in a way that the classification algorithm will not compromise its performance. The proposed algorithm is based on the concept of the adjusting kernel scaling (AKS) method to deal with the multi-class imbalanced dataset. The kernel function's selection has been evaluated with the help of weighting criteria and the chi-square test. All the experimental evaluation has been performed on sensor-based Indian Central Pollution Control Board (CPCB) dataset. The proposed algorithm with the highest accuracy of 99.66% wins the race among all the classification algorithms i.e. Adaboost (59.72%), Multi-Layer Perceptron (95.71%), GaussianNB (80.87%), and SVM (96.92). The results of the proposed algorithm are also better than the existing literature methods. It is also clear from these results that our proposed algorithm is efficient for dealing with class imbalance problems along with enhanced performance. Thus, accurate classification of air quality through our proposed algorithm will be useful for improving the existing preventive policies and will also help in enhancing the capabilities of effective emergency response in the worst pollution situation.

scholarly journals Pre-monsoon air quality over Lumbini, a world heritage site along the Himalayan foothills

2016 ◽  
Author(s):  
Dipesh Rupakheti ◽  
Bhupesh Adhikary ◽  
Puppala S. Praveen ◽  
Maheswar Rupakheti ◽  
Shichang Kang ◽  
...  
Keyword(s):  
Air Pollution ◽  
Air Quality ◽  
Forest Fires ◽  
Air Pollutants ◽  
Transport Model ◽  
World Heritage ◽  
World Heritage Site ◽  
Pollution Level ◽  
Pollution Transport ◽  
Heritage Site

Abstract. Lumbini, in southern Nepal, is a UNESCO world heritage site of universal value as the birthplace of Buddha. Poor air quality in Lumbini and surrounding regions is a great concern for public health as well as for preservation, protection and promotion of Buddhist heritage and culture. We present here results from measurements of ambient concentrations of key air pollutants (PM, BC, CO, O3) in Lumbini, first of its kind for Lumbini, conducted during an intensive measurement period of three months (April–June 2013) in the pre-monsoon season. The measurements were carried out as a part of the international air pollution measurement campaign; SusKat-ABC (Sustainable Atmosphere for the Kathmandu Valley – Atmospheric Brown Clouds). The ranges of hourly average concentrations were: PM10: 10.5–604.0 µg m−3, PM2.5: 6.1–272.2 µg m−3; BC: 0.3–30.0 µg m−3; CO: 125.0–1430.0 ppbv; and O3: 1.0–118.1 ppbv. These levels are comparable to other very heavily polluted sites throughout South Asia. The 24-h average PM2.5 and PM10 concentrations exceeded the WHO guideline very frequently (94 % and 85 % of the sampled period, respectively), which implies significant health risks for the residents and visitors in the region. These air pollutants exhibited clear diurnal cycles with high values in the morning and evening. During the study period, the worst air pollution episodes were mainly due to agro-residue burning and regional forest fires combined with meteorological conditions conducive of pollution transport to Lumbini. Fossil fuel combustion also contributed significantly, accounting for more than half of the ambient BC concentration according to aerosol spectral light absorption coefficients obtained in Lumbini. WRF-STEM, a regional chemical transport model, was used to simulate the meteorology and the concentrations of pollutants. The model was able to reproduce the variation in the pollutant concentrations well; however, estimated values were 1.5 to 5 times lower than the observed concentrations for CO and PM10 respectively. Regionally tagged CO tracers showed the majority of CO came from the upwind region of Ganges valley. The model was also used to examine the chemical composition of the aerosol mixture, indicating that organic carbon was the main constituent of fine mode PM2.5, followed by mineral dust. Given the high pollution level, there is a clear and urgent need for setting up a network of long-term air quality monitoring stations in the greater Lumbini region.

scholarly journals Implementation of dataflow programming based Fuzzy Logic algorithm for gas concentration index in around of Sidoarjo mudflow, Indonesia

2018 ◽  
Vol 154 ◽  
pp. 03012
Author(s):  
Edita Rosana Widasari ◽  
Barlian Henryranu Prasetio ◽  
Hurriyatul Fitriyah ◽  
Reza Hastuti
Keyword(s):  
Air Pollution ◽  
Fuzzy Logic ◽  
Air Quality ◽  
Quality Index ◽  
Methane Concentration ◽  
Air Quality Index ◽  
Pollution Level ◽  
Affected Area ◽  
Fuzzy Logic Algorithm ◽  
Dataflow Programming

Sidoarjo mudflow or known as Lapindo mudflow erupted since 2006. The Sidoarjo mudflow is located in Sidoarjo City, East Java, Indonesia. The mudflow-affected area has high air pollution level and high health risk. Therefore, in this paper was implemented a system that can categorize the level of air pollution into several categories. The air quality index can be categorized using fuzzy logic algorithm based on the concentration of air pollutant parameters in the mudflow-affected area. Furthermore, Dataflow programming is used to process the fuzzy logic algorithm. Based on the result, the measurement accuracy of the air quality index in the mudflow-affected area has an accuracy rate of 93.92% in Siring Barat, 93.34% in Mindi, and 95.96% in Jatirejo. The methane concentration is passes the standard quality even though the air quality index is safe. Hence, the area is indicated into Hazardous level. In addition, Mindi has highest and stable methane concentration. It means that Mindi has high-risk air pollution.

scholarly journals The Impact of COVID-19 on NO2 and PM2.5 Levels and Their Associations with Human Mobility Patterns in Singapore

2021 ◽  
Author(s):  
Yangyang Li ◽  
Yihan Zhu ◽  
Jia Yu Karen Tan ◽  
Hoong Chen Teo ◽  
Andrea Law ◽  
...  
Keyword(s):  
Air Pollution ◽  
East Coast ◽  
Human Mobility ◽  
Regional Scale ◽  
Air Pollutant ◽  
Pollution Level ◽  
The South ◽  
High Association ◽  
Pollutant Level ◽  
The Impact

AbstractThe decline in NO2 and PM2.5 pollutant levels were observed during COVID-19 around the world, especially during lockdowns. Previous studies explained such observed decline with the decrease in human mobility, whilst overlooking the meteorological changes (e.g., rainfall, wind speed) that could mediate air pollution level simultaneously. This pitfall could potentially lead to over-or under-estimation of the effect of COVID-19 on air pollution. Consequently, this study aims to re-evaluate the impact of COVID-19 on NO2 and PM2.5 pollutant level in Singapore, by incorporating the effect of meteorological parameters in predicting NO2 and PM2.5 baseline in 2020 using machine learning methods. The results found that NO2 and PM2.5 declined by a maximum of 38% and 36%, respectively, during lockdown period. As two proxies for change in human mobility, taxi availability and carpark availability were found to increase and decrease by a maximum of 12.6% and 9.8%, respectively, in 2020 from 2019 during lockdown. To investigate how human mobility influenced air pollutant level, two correlation analyses were conducted: one between PM2.5 and carpark availability changes at regional scale and the other between NO2 and taxi availability changes at a spatial resolution of 0.01°. The NO2 variation was found to be more associated with the change in human mobility, with the correlation coefficients vary spatially across Singapore. A cluster of stronger correlations were found in the South and East Coast of Singapore. Contrarily, PM2.5 and carpark availability had a weak correlation, which could be due to the limit of regional analyses. Drawing to the wider context, the high association between human mobility and NO2 in the South and East Coast area can provide insights into future NO2 reduction policy in Singapore.Graphical Abstract

scholarly journals ASSESSMENT OF AIR POLLUTION LEVEL OF NITROGEN DIOXIDE AND TRENDS OF IT CHANGES IN THE CITIES OF UKRAINE

2018 ◽  
pp. 87-95 ◽  
Author(s):  
Y. Yatsenko ◽  
O. Shevchenko ◽  
S. Snizhko
Keyword(s):  
Air Pollution ◽  
Nitrogen Dioxide ◽  
Pollution Level ◽  
Method Of Least Squares ◽  
Statistical Parameters ◽  
Group 3 ◽  
Environmental Measures ◽  
High Level

The purpose of the work is to study the current level and the main trends of atmospheric air pollution of the cities of Ukraine with nitrogen dioxide to identify the most polluted cities, their ranking to determine the list of cities for the priority implementation of environmental measures. For the purpose of the study, the information of the Central Geophysical Observatory on the average annual concentrations of nitrogen dioxide in the air of 51 cities of Ukraine for the period 1998-2015 was used. The study used the classical methods of applied mathematical statistics (estimation of statistical parameters of distribution of concentrations, construction of time trends on the method of least squares, graphical methods of visualization of levels of air pollution), which were implemented using the available programs "MS-Excell" and "Statistica-8.0". The classification of cities according to the level of MPC exceeds average annual concentrations of nitrogen dioxide. 3 groups of cities were allocated: 1 group (21 cities) permissible level of pollution (<1 MPC); 2 group (27 cities) – increased level of pollution (1-2 MPC); group 3 (3 cities) – high level of pollution (2-3 MPC). It has been established that in the air of 21 cities (41% of all cities where nitrogen dioxide is monitored in the atmosphere) of 51 cities, there is an acceptable level of air pollution. In the remaining cities (59%) – there is a stable excess of MPC. In 23 cities, even the minimum concentrations of NO2 exceed the permissible standards. The study of long-term dynamics of nitrogen dioxide in air has shown that the increase of concentrations of this pollutant for 1998-2015 is observed in 28 cities (55%) of 51. The most significant increase in concentrations in the air occurred in Kherson, Lutsk, Donetsk and Gorishni Plavni. In 13 cities reduction of concentrations was recorded, and in 10 cities the content of this pollutant in the air practically does not change.

scholarly journals Сarcinogenic substances in the atmospheric air of Dnipro city and risk to the population

2021 ◽  
Vol 26 (1) ◽  
pp. 226-231
Author(s):  
A.M. Serdiuk ◽  
I.O. Chernychenko ◽  
O.M. Lytvychenko ◽  
V.F. Babii ◽  
O.Ye. Kondratenko ◽  
...  
Keyword(s):  
Air Pollution ◽  
Physicochemical Analysis ◽  
Carcinogenic Risk ◽  
The State ◽  
State Monitoring ◽  
Dynamic Changes ◽  
Atmospheric Air ◽  
Emergency Situations ◽  
Chromium Vi ◽  
Industrial Center

The objective – to study the dynamic changes for the health risk of the population of the industrial center in accordance with the state of atmospheric air pollution with carcinogenic compounds. The assessment of the state of atmospheric air pollution was carried out by us based on the results of physicochemical analysis of samples taken in places attached to the locations of stationary posts of state monitoring. The concentration of identified substances was determined by conventional methods: spectral-luminescent and gas chromatographic. Heavy metal concentrations were determined using data from the Central Geophysical Observatory of the Ministry of Emergency Situations. The calculation of the inhalation load of chemical carcinogens and the risks associated with them (non-carcinogenic and carcinogenic) was carried out in accordance with domestic guidelines. The assessment of dynamic changes in the nature of atmospheric air pollution with a complex of carcinogenic substances was made 5 of them are constantly recorded at levels exceeding hygienic standards. When compared with the reference concentrations, all compounds are characterized by high coefficients, indicating the likelihood of their effect on the body's immune system, respiratory organs, malformations, etc. A high individual carcinogenic risk of the effect of chromium VI and nitrosamines was determined. A total carcinogenic risk is formed at levels of 2.5 – 3.9×10-3, which should be considered as high; this requires development and implementation of preventive measures. On the territory of the industrial center, a high level of air pollution with increased carcinogenic and non-carcinogenic risk is stably registered.

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