scholarly journals Twelve-Year Analysis of NO2 Concentration Measurements at Belisario Station (Quito, Ecuador) Using Statistical Inference Techniques

Sensors ◽  
2020 ◽  
Vol 20 (20) ◽  
pp. 5831 ◽  
Author(s):  
Wilmar Hernandez ◽  
Alfredo Mendez
Keyword(s):  
Air Pollution ◽  
Air Quality ◽  
Quality Index ◽  
Bootstrap Method ◽  
Central Tendency ◽  
Concentration Measurements ◽  
Inference Techniques ◽  
The Right ◽  
The City ◽  
Robust Statistical Methods

In this paper, a robust analysis of nitrogen dioxide (NO2) concentration measurements taken at Belisario station (Quito, Ecuador) was performed. The data used for the analysis constitute a set of measurements taken from 1 January 2008 to 31 December 2019. Furthermore, the analysis was carried out in a robust way, defining variables that represent years, months, days and hours, and classifying these variables based on estimates of the central tendency and dispersion of the data. The estimators used here were classic, nonparametric, based on a bootstrap method, and robust. Additionally, confidence intervals based on these estimators were built, and these intervals were used to categorize the variables under study. The results of this research showed that the NO2 concentration at Belisario station is not harmful to humans. Moreover, it was shown that this concentration tends to be stable across the years, changes slightly during the days of the week, and varies greatly when analyzed by months and hours of the day. Here, the precision provided by both nonparametric and robust statistical methods served to comprehensively proof the aforementioned. Finally, it can be concluded that the city of Quito is progressing on the right path in terms of improving air quality, because it has been shown that there is a decreasing tendency in the NO2 concentration across the years. In addition, according to the Quito Air Quality Index, most of the observations are in either the desirable level or acceptable level of air pollution, and the number of observations that are in the desirable level of air pollution increases across the years.

scholarly journals Pre and Post Covid-19 Lockdown: How the AQI of Three Major Cities of Pakistan will Change?

2020 ◽  
Vol 6 (4) ◽  
pp. 1377-1387
Author(s):  
Ume Laila ◽  
Najma Sadiq ◽  
Tahir Mehmood ◽  
Tooba Rehan Haqqi
Keyword(s):  
Air Pollution ◽  
Air Quality ◽  
Quality Index ◽  
Analytical Approach ◽  
Atmospheric Condition ◽  
Situational Analysis ◽  
Policy Recommendations ◽  
Before And After ◽  
The City ◽  
Quality Indexes

Pakistan being in the list of developing countries has shown tremendous response towards the control of pandemic COVID-19. This paper evaluates the pre and post COVID 19 lockdown situation of air quality and provides an evidence of the air quality amid the lockdown and how it started to improve. The air quality indexes of three major cities of Pakistan i.e. Karachi, Islamabad and Lahore are compared, taking into account the indexes before and after the imposition of lockdown.  The city wide presence of major pollutants like Sulphur Dioxide and Nitrogen Dioxide also reduced. The results show how taking serious measures can help in reducing the air pollution and help the environment to restore.  Following analytical approach and situational analysis certain inferences have been drawn that the air quality index has worsen, and the atmospheric condition have turn out to be shoddier than the pre-pandemic situation. In the last section certain policy recommendations have been provided in order to maintain a healthy air quality.

scholarly journals Contribution of Local and Transboundary Air Pollution to the Urban Air Quality of Fukuoka, Japan

Atmosphere ◽  
2021 ◽  
Vol 12 (4) ◽  
pp. 431
Author(s):  
Ayako Yoshino ◽  
Akinori Takami ◽  
Keiichiro Hara ◽  
Chiharu Nishita-Hara ◽  
Masahiko Hayashi ◽  
...  
Keyword(s):  
Air Pollution ◽  
Air Quality ◽  
Urban Areas ◽  
Air Pollutants ◽  
Regional Scale ◽  
Gaseous Species ◽  
Transboundary Air Pollution ◽  
Local Air Pollution ◽  
The City

Transboundary air pollution (TAP) and local air pollution (LAP) influence the air quality of urban areas. Fukuoka, located on the west side of Japan and affected by TAP from the Asian continent, is a unique example for understanding the contribution of LAP and TAP. Gaseous species and particulate matter (PM) were measured for approximately three weeks in Fukuoka in the winter of 2018. We classified two distinctive periods, LAP and TAP, based on wind speed. The classification was supported by variations in the concentration of gaseous species and by backward trajectories. Most air pollutants, including NOx and PM, were high in the LAP period and low in the TAP period. However, ozone was the exception. Therefore, our findings suggest that reducing local emissions is necessary. Ozone was higher in the TAP period, and the variation in ozone concentration was relatively small, indicating that ozone was produced outside of the city and transported to Fukuoka. Thus, air pollutants must also be reduced at a regional scale, including in China.

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 IMPROVING THE QUALITY OF INFORMATION SUPPORT FOR MONITORING AIR POLLUTION FROM VEHICLES (CASE STUDY OF ST. PETERSBURG)

2021 ◽  
Vol 26 (2) ◽  
pp. 65-74
Author(s):  
V. N. Lozhkin ◽  
◽  
O. V. Lozhkina ◽  
Keyword(s):  
Air Pollution ◽  
Air Quality ◽  
Information Support ◽  
Information Process ◽  
Limit Values ◽  
Standard Limit ◽  
The City ◽  
Original Information

Introduction. St. Petersburg is the cultural and sea capital of Russia. The city is characterized by environmental problems typical for the largest cities in the world. It has a technical system for instrumental online monitoring and computational forecasting of air quality. Methods. The system maintains the information process by means of computational monitoring of its current and future state. Results. The paper describes methodological approaches to the generation of instrumental information about the structure and intensity of traffic flows in the urban road network and its digital transformation into GIS maps of air pollution in terms of pollutants standard limit values excess. Conclusion. The original information technology for air quality control was introduced at the regional level in the form of an official methodology and is used in environmental management activities.

scholarly journals The impact of air quality on its Baidu index: grey model analysis

2021 ◽  
Author(s):  
Leping Tu ◽  
Yan Chen
Keyword(s):  
Air Pollution ◽  
Air Quality ◽  
Quality Index ◽  
Air Quality Index ◽  
Grey Correlation ◽  
Convolution Model ◽  
Grey Correlation Analysis ◽  
And Control ◽  
The Impact ◽  
The Relationship

Abstract To investigate the relationship between air quality and its Baidu index, we collect the annual Baidu index of air pollution hazards, causes and responses. Grey correlation analysis, particle swarm optimization and grey multivariate convolution model are used to simulate and forecast the comprehensive air quality index. The result shows that the excessive growth of the comprehensive air quality index will lead to an increase in the corresponding Baidu index. The number of search for the causes of air quality has the closest link with the comprehensive air quality index. Strengthening the awareness of public about air pollution is conducive to the improvement of air quality. The result provides a reference for relevant departments to prevent and control air pollution.

scholarly journals Real Time Air Quality Index from Various Locations

2020 ◽  
Vol 9 (2) ◽  
pp. 368-372
Keyword(s):  
Air Pollution ◽  
Air Quality ◽  
Real Time ◽  
Environmental Protection Agency ◽  
Quality Index ◽  
Ground Level ◽  
Air Quality Index ◽  
Time Data ◽  
Open Government Data ◽  
Government Data

The surveys regarding air pollution shows that there has been a hasty growth due to the emission of fuels and exhaust gases from factories. The Air Quality Index (AQI) has been launched to note the contemporary status of the air quality. The intent of AQI is to aid every individual know how the regional air quality will make an impact on them. The Environmental Protection Agency assess the AQI for five major air pollutants namely Nitrogen dioxide (NO2), ground-level ozone (O3), particle pollution (PM10, PM2.5), carbon monoxide (CO), and sulphur dioxide (SO2). The intent of the project is to congregate real-time Air Quality Index from distinct monitoring stations across India, analysing the data and reporting on it. Collect the real-time data using the API key provided by Open Government Data (OGD) platform India. This is done by making use of Microsoft Business Intelligence (MSBI) and Power BI Tools to transform, analyse and visualize the data. This project can be utilized to develop various programs like Ozone today in Europe and in mobile applications which acts as an alert system that can protect people from air pollution.

scholarly journals Air Pollution and Nasal Mucociliary Clearance Time among Urban and Rural Residents in Two Philippine Communities

2020 ◽  
Vol 35 (1) ◽  
pp. 33-35
Author(s):  
Soraya Joson ◽  
Joman Laxamana
Keyword(s):  
Air Pollution ◽  
Methylene Blue ◽  
Air Quality ◽  
Quality Index ◽  
Mucociliary Clearance ◽  
Air Quality Index ◽  
Clearance Time ◽  
Rural Residents ◽  
Air Index ◽  
Nasal Mucociliary Clearance

ABSTRACT Objective: To measure the nasal mucociliary clearance (NMC) time among adults residing in two Philippine communities with different air quality indices using the saccharin and methylene blue test. Methods: Design: Cross-Sectional Study Setting: Diliman, Quezon City and Puerto Princesa, Palawan Participantss: Fifty (50) participants, 25 residing in an urban city with fair air quality index and 25 residing in a rural province with good air quality index. Results: The mean NMC time of the urban group was 22.15±12.68 mins and was significantly longer than the NMC time of the rural group which was 5.29±2.87mins; t(48) = 6.643, p<0.0001). Conclusion: Increased air pollution may be associated with significant prolongation of nasal mucociliary clearance time among urban residents with fair quality air index compared to rural residents with good quality air index. Keywords: nasal mucociliary clearance, naso mucociliary clearance time, air pollution, air quality index, saccharin test, methylene blue

NESTED HIGH-RESOLUTION NOx AND PM SIMULATIONS OVER ZÜRICH

2021 ◽  
Author(s):  
Ivo Suter ◽  
Lukas Emmenegger ◽  
Dominik Brunner
Keyword(s):  
Air Pollution ◽  
Air Quality ◽  
Boundary Conditions ◽  
Meteorological Conditions ◽  
Model Systems ◽  
Multi Scale ◽  
Wide Range ◽  
The Impact ◽  
The City ◽  
Concentration Levels

&lt;p&gt;Reducing air pollution, which is the world's largest single environmental health risk, demands better-informed air quality policies. Consequently, multi-scale air quality models are being developed with the goal to resolve cities. One of the major challenges in such model systems is to accurately represent all large- and regional-scale processes that may critically determine the background concentration levels over a given city. This is particularly true for longer-lived species such as aerosols, for which background levels often dominate the concentration levels, even within the city. Furthermore, the heterogeneous local emissions, and complex dispersion in the city have to be considered carefully.&lt;/p&gt;&lt;p&gt;In this study, the impact of processes across a wide range of scales on background concentrations over Switzerland and the city of Zurich was modelled by performing one year of nested European and Swiss national COSMO-ART simulations to obtain adequate boundary conditions for gas-phase chemical, aerosol and meteorological conditions for city-resolving simulations. The regional climate chemistry model COSMO-ART (Vogel et al. 2009) was used in a 1-way coupled mode. The outer, European, domain, which was driven by chemical boundary conditions from the global MOZART model, had a 6.6 km horizontal resolution and the inner, Swiss, domain one of 2.2 km. For the city scale, a catalogue of more than 1000 mesoscale flow patterns with 100 m resolution was created with the model GRAMM, based on a discrete set of atmospheric stabilities, wind speeds and directions, accounting for the influence of land-use and topography. Finally, the flow around buildings was solved with the CFD model GRAL forced at the boundaries by GRAMM. Subsequently, Lagrangian dispersion simulations for a set of air pollutants and emission sectors (traffic, industry, ...) based on extremely detailed building and emission data was performed in GRAL. The result of this nested procedure is a library of 3-dimensional air pollution maps representative of hourly situations in Zurich (Berchet et al. 2017). From these pre-computed situations, time-series and concentration maps can be obtained by selecting situations according to observed or modelled meteorological conditions.&lt;/p&gt;&lt;p&gt;The results were compared to measurements from air quality monitoring network stations. Modelled concentrations of NO&lt;sub&gt;x&lt;/sub&gt; and PM compared well to measurements across multiple locations, provided background conditions were considered carefully. The nested multi-scale modelling system COSMO-ART/GRAMM/GRAL can adequately reproduce local air quality and help understanding the relative contributions of local versus distant emissions, as well as fill the space between precise point measurements from monitoring sites. This information is useful for research, policy-making, and epidemiological studies particularly under the assumption that exceedingly high concentrations become more and more localised phenomenon in the future.&lt;/p&gt;

scholarly journals A Facility Location Model for Air Pollution Detection

2018 ◽  
Vol 2018 ◽  
pp. 1-8 ◽  
Author(s):  
G. Lancia ◽  
F. Rinaldi ◽  
P. Serafini
Keyword(s):  
Genetic Algorithm ◽  
Air Pollution ◽  
Air Quality ◽  
Mathematical Models ◽  
Facility Location ◽  
Large City ◽  
Location Model ◽  
Practical Algorithms ◽  
Pollution Detection ◽  
The City

We describe mathematical models and practical algorithms for a problem concerned with monitoring the air pollution in a large city. We have worked on this problem within a project for assessing the air quality in the city of Rome by placing a certain number of sensors on some of the city buses. We cast the problem as a facility location model. By reducing the large number of data variables and constraints, we were able to solve to optimality the resulting MILP model within minutes. Furthermore, we designed a genetic algorithm whose solutions were on average very close to the optimal ones. In our computational experiments we studied the placement of sensors on 187 candidate bus routes. We considered the coverage provided by 10 up to 60 sensors.

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