Source Apportionment of Air Pollution: A Case Study In Malaysia

2014 ◽  
Vol 72 (1) ◽  
Author(s):  
Azman Azid ◽  
Hafizan Juahir ◽  
Mohd Ekhwan Toriman ◽  
Azizah Endut ◽  
Mohd Khairul Amri Kamarudin ◽  
...  
Keyword(s):  
Air Pollution ◽  
Air Quality ◽  
Source Apportionment ◽  
Principal Component ◽  
Quality Parameters ◽  
Effective Management ◽  
Chemometric Technique ◽  
Pca Method ◽  
Point Pollution

Air pollution is becoming a major environmental issue in Malaysia. This study focused on the identification of potential sources of variations in air quality around the study area based on the data obtained from the Malaysian Department of Environment (DOE).  Eight air quality parameters in ten monitoring stations for seven years (2006 – 2012) were gathered.  The Principal Component Analysis (PCA) method from chemometric technique was applied to identify the source identification of pollution around the study area. The PCA method has identified methane (CH4), non-methane hydrocarbon (NmHC), total hydrocarbon (THC), ozone (O3) and particulate matter under 10 microns (PM10) are the most significant parameters around the study area.  From the study, it can be concluded that the application of the PCA method in chemometric techniques can be applied for the source apportionment purpose. Hence, this study indicated that for the future and effective management of the Malaysian air quality, an effort should be placed as a priority in controlling point and non-point pollution sources.

A Complex Analysis Employing ARIMA Model and Statistical Methods on Air Pollutants Recorded in Ploiesti, Romania

2017 ◽  
Vol 68 (4) ◽  
pp. 818-823 ◽  
Author(s):  
Alin Pohoata ◽  
Emil Lungu
Keyword(s):  
Air Pollution ◽  
Air Quality ◽  
Statistical Methods ◽  
Air Pollutants ◽  
Complex Analysis ◽  
Moving Average ◽  
Arima Model ◽  
Principal Component ◽  
Quality Parameters ◽  
Quality Data

Air pollution is an everyday issue, very relevant to public authorities, requiring control and monitoring to provide data for decision-making policies. The objective of this study was to evaluate the air quality in Ploiesti city, Romania and to observe the advantages and limitations of the some statistical methods used in forecasting air quality. Data for six air quality parameters collected at monitoring stations in Ploiesti during the 2013 year were statistically analyzed. Principal component analysis (PCA) was used to provide a relevant description in factors that can be explained in terms of different sources of air pollution. The measured pollutants data were statistically analyzed using the auto-regressive integrated moving average (ARIMA) method in order to assess the efficiency of using this method in forecasting the environmental air quality. The results revealed that ARIMA method has some limitations and do not produce satisfactory results for certain air pollutants such as PM10 and CO, even the forecasted period is short. By comparison, the ARIMA model obtained for NOx , NO2 , or O3 time series, provides good results, with relative errors around 5%.

scholarly journals Functional ANOVA approaches for detecting changes in air pollution during the COVID-19 pandemic

2021 ◽  
Author(s):  
Christian Acal ◽  
Ana M. Aguilera ◽  
Annalina Sarra ◽  
Adelia Evangelista ◽  
Tonio Di Battista ◽  
...  
Keyword(s):  
Air Pollution ◽  
Air Quality ◽  
Functional Data ◽  
Central Italy ◽  
Principal Component ◽  
Functional Principal Component Analysis ◽  
Area Of Interest ◽  
Pm 10 ◽  
The Impact ◽  
Monitoring Stations

AbstractFaced with novel coronavirus outbreak, the most hard-hit countries adopted a lockdown strategy to contrast the spread of virus. Many studies have already documented that the COVID-19 control actions have resulted in improved air quality locally and around the world. Following these lines of research, we focus on air quality changes in the urban territory of Chieti-Pescara (Central Italy), identified as an area of criticality in terms of air pollution. Concentrations of $$\hbox {NO}_{{2}}$$ NO 2 , $$\hbox {PM}_{{10}}$$ PM 10 , $$\hbox {PM}_{2.5}$$ PM 2.5 and benzene are used to evaluate air pollution changes in this Region. Data were measured by several monitoring stations over two specific periods: from 1st February to 10 th March 2020 (before lockdown period) and from 11st March 2020 to 18 th April 2020 (during lockdown period). The impact of lockdown on air quality is assessed through functional data analysis. Our work makes an important contribution to the analysis of variance for functional data (FANOVA). Specifically, a novel approach based on multivariate functional principal component analysis is introduced to tackle the multivariate FANOVA problem for independent measures, which is reduced to test multivariate homogeneity on the vectors of the most explicative principal components scores. Results of the present study suggest that the level of each pollutant changed during the confinement. Additionally, the differences in the mean functions of all pollutants according to the location and type of monitoring stations (background vs traffic), are ascribable to the $$\hbox {PM}_{{10}}$$ PM 10 and benzene concentrations for pre-lockdown and during-lockdown tenure, respectively. FANOVA has proven to be beneficial to monitoring the evolution of air quality in both periods of time. This can help environmental protection agencies in drawing a more holistic picture of air quality status in the area of interest.

scholarly journals From Black to Blue Skies: Civil Society Perceptions of Air Pollution in Shanghai

2021 ◽  
pp. 1-22
Author(s):  
Amanda K. Winter ◽  
Huong Le ◽  
Simon Roberts
Keyword(s):  
Air Pollution ◽  
Civil Society ◽  
Air Quality ◽  
Qualitative Case Study ◽  
Field Research ◽  
Ecological Civilization ◽  
Civil Society Participation ◽  
Quality Indexes

Abstract This paper explores the perception and politics of air pollution in Shanghai. We present a qualitative case study based on a literature review of relevant policies and research on civil society and air pollution, in dialogue with air quality indexes and field research data. We engage with the concept of China's authoritarian environmentalism and the political context of ecological civilization. We find that discussions about air pollution are often placed in a frame that is both locally temporal (environment) and internationally developmentalist (economy). We raise questions from an example of three applications with different presentations of air quality index measures for the same time and place. This example and frame highlight the central role and connection between technology, data and evidence, and pollution visibility in the case of the perception of air pollution. Our findings then point to two gaps in authoritarian environmentalism research, revealing a need to better understand (1) the role of technology within this governance context, and (2) the tensions created from this non-participatory approach with ecological civilization, which calls for civil society participation.

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 Case Study on Anthropogenic Air Pollution in Nagpur City

2021 ◽  
Vol 9 (VI) ◽  
pp. 2279-2282
Author(s):  
Mukul Dayaramani
Keyword(s):  
Air Pollution ◽  
Air Quality ◽  
Harmful Effect ◽  
Central India ◽  
Well Being ◽  
Good Health ◽  
Air Pollutant ◽  
Corporate Community ◽  
Health And Well Being

Air pollution is a very serious problem worldwide. Anthropogenic air pollution is mostly related to the combustion of various types of fuels. Air pollutant levels remain too high and air quality problems are still not solved. The presence of pollutants in the air has a harmful effect on the human health and the environment. Good air quality is a prerequisite for our good health and well-being. Nagpur city is located in Maharashtra state of central India. Business hub and increased industrialization in study area is affecting the environment adversely. n. Changing life style of corporate community and their effects on other population enhancing the contamination of environment

scholarly journals A Methodology for Evaluation and Distribution of Patent Applications to INPI-BR Patent Examiners: A Case Study in the Electricity Field

2021 ◽  
Author(s):  
Cesar Vianna Moreira Júnior ◽  
Daniel Marques Golodne ◽  
Ricardo Carvalho Rodrigues
Keyword(s):  
Principal Component ◽  
Patent Classification ◽  
Technological Field ◽  
International Patent ◽  
Relevant Variables ◽  
Pca Method ◽  
Patent Applications ◽  
Examination Process

This paper presents the development of a new methodology for evaluation and distribution of patent applications to the examiners at the Brazilian Patent Office considering a specific technological field, represented by classification of the application according to the International Patent Classification (IPC), and the variables corresponding to the volume of data of the application and its complexity for the examination process. After identifying the most relevant variables, such as the Specific Areas of Expertise (ZAE) of the examiners, a mathematical model was developed, including: (a) application of the principal component analysis (PCA) method; (b) calculation of a General Complexity Ratio (IGC); (c) classification into five classes (very light, light, moderate, heavy and very heavy) according to IGC average ranges and standard deviations; (d) implementation of a logic of distribution, compensating very heavy applications with very light ones, and light applications with heavy ones; and (e) calculation of a Distribution Balancing Ratio (IBD), considering the differences between the samples’ medians. The model was validated using a sample of patent applications including, in addition to the identified variables, the time for substantive examination by the examiner. Then, a correlation analysis of the variables with time and a comparison of the classifications according to the time and the IGC generated by the model were carried out. The results obtained showed a high correlation of the IGC with time, above 80%, as well as correct IGC classes in more than 80% of applications. The model proposed herein suggests that the three main relevant variables are: total number of pages, total number of claims, and total number of claim pages.

scholarly journals The Use of the Internet of Things for Estimating Personal Pollution Exposure

2019 ◽  
Vol 16 (17) ◽  
pp. 3130 ◽  
Author(s):  
Keith April G. Arano ◽  
Shengjing Sun ◽  
Joaquin Ordieres-Mere ◽  
and Bing Gong
Keyword(s):  
Air Pollution ◽  
Air Quality ◽  
Internet Of Things ◽  
Policy Development ◽  
Prediction Models ◽  
Low Cost ◽  
Activity Patterns ◽  
Dynamic Feedback ◽  
Pollution Exposure

This paper proposes a framework for an Air Quality Decision Support System (AQDSS), and as a proof of concept, develops an Internet of Things (IoT) application based on this framework. This application was assessed by means of a case study in the City of Madrid. We employed different sensors and combined outdoor and indoor data with spatiotemporal activity patterns to estimate the Personal Air Pollution Exposure (PAPE) of an individual. This pilot case study presents evidence that PAPE can be estimated by employing indoor air quality monitors and e-beacon technology that have not previously been used in similar studies and have the advantages of being low-cost and unobtrusive to the individual. In future work, our IoT application can be extended to include prediction models, enabling dynamic feedback about PAPE risks. Furthermore, PAPE data from this type of application could be useful for air quality policy development as well as in epidemiological studies that explore the effects of air pollution on certain diseases.

ASSESSMENT OF THE SPATIAL VARIATION AND SOURCE APPORTIONMENT OF AIR POLLUTION BASED ON CHEMOMETRIC TECHNIQUES: A CASE STUDY IN THE PENINSULAR MALAYSIA

2015 ◽  
Vol 77 (1) ◽  
Author(s):  
Hamza Ahmad Isiyaka ◽  
Hafizan Juahir ◽  
Mohd Ekhwan Toriman ◽  
Azman Azid ◽  
Barzani Mohd Gasim ◽  
...  
Keyword(s):  
Air Pollution ◽  
Spatial Variation ◽  
Source Apportionment ◽  
Anthropogenic Activities ◽  
Weather Condition ◽  
Principal Component ◽  
Peninsular Malaysia ◽  
Air Pollutant ◽  
Secondary Pollutants ◽  
Chemometric Techniques

This study aims to investigate the spatial variation in the source of air pollution, identify the percentage contribution of each pollutant and apportion the mass contribution of each source category using chemometric techniques. Hierarchical agglomerative cluster analysis (HACA) successfully grouped the five air monitoring sites into three groups (cluster 1, 2 and 3). Principal component analysis (PCA) was used to spot out the sources of air pollution which are attributed to anthropogenic activities. Multiple linear regression (MLR) was used to develop an equation model that explains the contribution of pollutants in each cluster. However, it was observed that particulate matter (PM10) and Ozone (O3) are the most significant pollutants influencing the value of air pollutant index (API). Meanwhile, the source apportionment indicates that cluster 1 is influenced by gas and non-gas pollutants to a degree of 84%, weather condition 15% and 1% by gas and secondary pollutants. Cluster 2 is affected by gas and secondary pollutants to a tune of 87% and 13% by weather condition while cluster 3 is apportioned with 98% secondary gas and non-gas pollutants and 2% weather condition. This study reveals the usefulness of chemometric technique in modeling and reducing the cost and time of monitoring redundant stations and parameters.

THE MOBILE ROBOT DEVELOPMENT FOR AIR POLLUTION TELE DATA CAPTURE

2016 ◽  
Vol 7 (2) ◽  
Author(s):  
Dirman Hanafi ◽  
Khairul Azlan A.Rahman
Keyword(s):  
Air Pollution ◽  
Air Quality ◽  
Mobile Robot ◽  
Environmental Issues ◽  
Quality Parameters ◽  
Outdoor Environment ◽  
Target Area ◽  
Central Control ◽  
Modern Era ◽  
Indoor And Outdoor

In the Modern era, the environmental issues have given significant impact to the human live. The air pollution indoor and outdoor environment sometimes dangerous to the human health and it needs to be justified. To fulfill this purpose, in this research tele-measurement process and technique based on the mobile robot with equipped by several air quality parameters sensors is developed. The robot is controlled using remote control and wireless communication system. The air quality in target area will be monitored by using sensors which will capture data and send it to the Central Control (laptop) for analyzing. And then to be able to monitor the certain area investigation, the mobile robot is guided by using wireless camera. From the experimental test, the robot able move to target area, capture the area condition and the air parameters monitor. Keywords: air pollution, tele-measured, mobile robot

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