Pollution, Property Value, and Air Quality Control Strategies

1977 ◽  
Vol 9 (11) ◽  
pp. 1307-1314 ◽  
Author(s):  
R Bednarz
Keyword(s):  
Air Pollution ◽  
Quality Control ◽  
Air Quality ◽  
Housing Stock ◽  
Control Strategies ◽  
Property Values ◽  
Property Value ◽  
Pollution Intensity ◽  
Air Quality Control ◽  
The Relationship

The housing stock of Chicago is divided into several groups based on the race and income of the residents in the housing. It is shown that the relationship between air pollution intensity and property values varies greatly from group to group. The ramifications of these findings for the interpretation of similar studies by other researchers are discussed in light of this conclusion.

scholarly journals Risk and Impact Control of PM2.5 and SO2 Exposure of Power Plant to Communities (A Case Study in the Steam Power Plant Babelan Bekasi)

2021 ◽  
Vol 13 (2) ◽  
pp. 121
Author(s):  
Belathea Chastine Hutauruk ◽  
Dwi Nowo Martono ◽  
Ahyahudin Sodri
Keyword(s):  
Air Pollution ◽  
Air Quality ◽  
Power Plant ◽  
Pollution Control ◽  
Control Strategies ◽  
Electrical Energy ◽  
Air Pollution Control ◽  
Steam Power ◽  
Steam Power Plant ◽  
Air Quality Control

Introduction: Coal consumption for electrical energy at Steam Power Plant increase often with economic and population growth. Burning coal produces harmful pollutants such as PM2.5 and SO2 affecting public health problems and decline in social and economic conditions. Therefore, implement the strategies are needed to reduce risks and long-term impacts on the environment. The research aimed to analyze the risk and impact of air pollutants exposure and develop control strategies. Methods: This study used the methods of environmental health risk analysis, analysis of the level of understanding and perception, cost of illness analysis, and Strength, Weakness, Opportunities, and Threats analysis, Data obtained by survey, interviews using questionnaire instrument to 293 respondents, five experts to determine risk control strategies and the secondary data from Environmental Agency of Bekasi Regency. Results and Discussion: The result showed that most risk is 13-55 years old, and people who live less than two square kilometres from the power plant. The level of public understanding and perception resulted in moderate criteria. The average cost of illness is 14.51% of the average monthly income of each person. The recommendation strategies are implemented regulations of power plant location, providing guidelines for environmental controlling, air quality control regularly, tightening air quality standards, prioritizing air pollution control budgets, providing green space, implementing clean energy and renewable energy, and building capacity air quality control. Conclusion: The production of electrical energy on Steam Power Plant had an air pollution impact such as health problems, decreased income, and social disruption. Air pollution control includes structural and nonstructural strategies from internal and external Steam Power Plant to provide environmentally friendly energy production for the communities.

scholarly journals Applying EPA’s instruction to calculate air quality index (AQI) in Tehran

2019 ◽  
Author(s):  
Somayeh Yousefi ◽  
Abbas Shahsavani ◽  
Mostafa Hadei
Keyword(s):  
Air Pollution ◽  
Quality Control ◽  
Air Quality ◽  
Quality Index ◽  
Good Condition ◽  
Air Quality Index ◽  
Sudden Increase ◽  
Governmental Organizations ◽  
Abnormal Distribution ◽  
Air Quality Control

Introduction: This study aimed to calculate and evaluate air quality index (AQI) in Tehran according to the EPA’s instruction, and evaluate the obtained values. Materials and methods: The study period included three years of 2013, 2015, and 2017 within the six-year period of 2013-2017. The concentrations of six studied pollutants were acquired from Department of Environment (DE) and Air Quality Control Company of Tehran (AQCC). EPA’s method was applied to calculate AQI values during the study period, selecting the highest AQI value among all of the pollutants and monitors. Results: The three-year average of AQI was about 147. During all the three years, the air quality had never been in a “good” condition (AQI<50). About 92%, 91%, 87% of AQIs indicated the conditions unhealthy for sensitive groups (100<AQI<150) or unhealthy for all groups (150<AQI<200). PM2.5 accounted for most of the AQI values in Tehran, followed by NO2 and O3. Evaluating the histogram of AQI values indicated a strange form of distribu- tion, showing a decline in the 100-150 range and a sudden increase just after AQIs higher than 150. Conclusion: This study indicated that governmental organizations should follow EPA’s instruction for AQI calculations to avoid underestimation of air pollution, and broadcast accurate and reliable AQIs to public. To determine the reason for the abnormal distribution of AQI, further studies with longer study periods are required.

scholarly journals Development of an Automatic Low-Cost Air Quality Control System: A Radon Application

2021 ◽  
Vol 11 (5) ◽  
pp. 2169
Author(s):  
Alberto Alvarellos ◽  
Andrea Lopez Chao ◽  
Juan Ramón Rabuñal ◽  
María D. García-Vidaurrázaga ◽  
Alejandro Pazos
Keyword(s):  
Lung Cancer ◽  
Air Pollution ◽  
Quality Control ◽  
Control System ◽  
Air Quality ◽  
Radon Concentration ◽  
Low Cost ◽  
Ventilation System ◽  
Quality Control System ◽  
Air Quality Control

Air pollution is the fourth-largest overall risk factor for human health worldwide. Ambient air pollution (outdoors) and household air pollution (indoors) cause about 6.5 million premature deaths. The World Health Organization has established that between 3% and 14% of lung cancer cases are due to radon gas, making it the most important cause of lung cancer after smoking. This work presents a fully automated, low-cost indoor air quality control system that can monitor temperature, pressure, humidity, total volatile organic compounds (TOVC), and radon concentration. Using the radon concentration as an air quality measure, we created a prediction algorithm. The system uses those predictions to control a ventilation system automatically. We tested the algorithm for different prediction windows and compared the results with those without the ventilation system in a radon research room. In this room, the radon concentration is high 100% of the time, reaching a level eleven times higher than the recommended limit. The results show that the system can achieve an 86% reduction of the radon concentration, maintaining it low 90% of the time while having the ventilation system on during only 34% of the time. This work demonstrates that we can control air quality using low-cost resources, keeping a household or workplace safe but comfortable.

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