Analysis of Ambient Air Quality Status and Trends from 2010 to 2012 in Chengkou County of Chongqing City in China

2013 ◽  
Vol 726-731 ◽  
pp. 1427-1430
Author(s):  
Wen Hua Jiang ◽  
Dao Jin Chen ◽  
Xian Qiong Long
Keyword(s):  
Air Quality ◽  
Southwest China ◽  
Ambient Air ◽  
Quality Monitoring ◽  
Air Quality Monitoring ◽  
Ambient Air Quality ◽  
Monthly Average ◽  
Chongqing City ◽  
Quality Status

The air quality monitoring data from 2010 to 2012 in Chengkou County of Chongqing City in Southwest China was analyzed.The results show that in recent years the air pollutans affecting the air quality in Chengkou County mainly is PM10 and secondly is SO2. The monthly average concentrations of PM10 and SO2 show a U-shape trend with the highest values in January.The average concentrations of PM10 and SO2 are highest in winter and lowest in summer with obvious seasonal changes.The air quality of Chengkou in 2011 and 2011 has been somewhat improved compared with that in 2010.

An assessment of ambient air quality using AQI and exceedance factor for Udaipur City, Rajasthan (India)

2021 ◽  
pp. 94-106
Author(s):  
Porush Kumar ◽  
Kuldeep ◽  
Nilima Gautam
Keyword(s):  
Air Pollution ◽  
Air Quality ◽  
Pollution Control ◽  
Urban Air Pollution ◽  
Ambient Air ◽  
Quality Monitoring ◽  
Urban Air ◽  
Air Quality Monitoring ◽  
Ambient Air Quality ◽  
Control Board

Air pollution is a severe issue of concern worldwide due to its most significant environmental risk to human health today. All substances that appear in excessive amounts in the environment, such as PM10, NO2, or SO2, may be associated with severe health problems. Anthropogenic sources of these pollutants are mainly responsible for the deterioration of urban air quality. These sources include stationary point sources, mobile sources, waste disposal landfills, open burning, and similar others. Due to these pollutants, people are at increased risk of various serious diseases like breathing problems and heart disease, and the death rate due to these diseases can also increase. Hence, air quality monitoring is essential in urban areas to control and regulate the emission of these pollutants to reduce the health impacts on human beings. Udaipur has been selected for the assessment of air quality with monitored air quality data. Air quality monitoring stations in Udaipur city are operated by the CPCB (Central Pollution Control Board) and RSPCB (Rajasthan State Pollution Control Board). The purpose of this study is to characterize the level of urban air pollution through the measurement of PM10, NO2, or SO2 in Udaipur city, Rajasthan (India). Four sampling locations were selected for Udaipur city to assess the effect of urban air pollution and ambient air quality, and it was monitored for a year from 1st January 2019 to 31st December 2019. The air quality index has been calculated with measured values of PM10, NO2, and SO2. The concentration of PM10 is at a critical level of pollution and primarily responsible for bad air quality and high air quality Index in Udaipur city.

Ambient Air Quality Monitoring and Audit over Athi River Township, Kenya

2015 ◽  
Vol 3 (8) ◽  
pp. 291-301
Author(s):  
Zablon W. Shilenje ◽  
Kennedy Thiong’o ◽  
Kennedy I. Ondimu ◽  
Paul M. Nguru ◽  
John Kaniaru Nguyo ◽  
...  
Keyword(s):  
Air Quality ◽  
Ambient Air ◽  
Quality Monitoring ◽  
Air Quality Monitoring ◽  
Ambient Air Quality

A Vague Sets Based Approach of Multi-Sensor Information Fusion for Urban Ambient Air Quality Monitoring

2013 ◽  
Vol 380-384 ◽  
pp. 1077-1080
Author(s):  
Jin Gang Li ◽  
Xiao Hong Su ◽  
Hong Wei Xuan ◽  
Shi Lei Zhao
Keyword(s):  
Air Quality ◽  
Information Fusion ◽  
Ambient Air ◽  
Quality Monitoring ◽  
Air Quality Monitoring ◽  
Ambient Air Quality ◽  
Monitoring Method ◽  
Vague Sets ◽  
Level Information ◽  
Sensor Information

In order to enhance the organization and management efficiency of multi-source heterogeneous data in the collection process for urban ambient air quality monitoring, according to the analysis of the limitations, the existing methods and the features of data collected, a new kind of multi-sensor and multi-level information fusion approach based on vague sets is proposed. The approach takes full advantage of the redundancy and complementarities from inter-level information to achieve the purpose of information integration. The mathematical description of vague sets based on the multi-sensor information fusion is defined and the corresponding model is developed in which the data organization and the monitoring method and the implementation of the hierarchical algorithm are discussed. Finally, the proposed approach is applied to a computing system of the ambient air quality monitoring. The study of this approach can supply scientific accordance for comprehensive monitoring of urban ambient air quality.

scholarly journals Air quality at bus stop microenvironments in a Metro Vancouver urban and suburban area

2014 ◽  
Author(s):  
Erin Nielsen ◽  
BCIT School of Health Sciences, Environmental Health ◽  
Bobby Sidhu
Keyword(s):  
Air Quality ◽  
Monitoring Network ◽  
Ambient Air ◽  
The Other ◽  
Quality Monitoring ◽  
Small Scale ◽  
Air Quality Monitoring ◽  
Ambient Air Quality ◽  
Bus Stop ◽  
Metro Vancouver

  BACKGROUND Those commuters waiting in small-scale transportation microenvironments, such as bus stops, can be exposed to levels of pollution higher than what is registered by ambient air quality monitoring stations. In addition, historically, those commuting in urban areas experience greater exposure to air pollutants than those commuting in suburban or rural areas, due to the nature of the environment. Little quantitative research has been conducted in the Metro Vancouver area regarding air quality in small scale transportation microenvironments. OBJECTIVES The aim of this study was to assess the differences in commuter exposure during AM Peak and PM Peak periods between an urban (Vancouver) and suburban (Ladner) bus stop. Furthermore, results were to be compared to the Metro Vancouver 24 hour rolling average objective as well as nearby Lower Fraser Valley (LFV) Ambient Air Quality Monitoring Network stations. METHODS The author measured particulate matter (PM) 2.5 (particulate matter ≤ 2.5 μm in aerodynamic diameter), using the DustTrakTM Aerosol Monitor 8520 between January 6, 2014 and January 21, 2014 on 12 weekdays, from 6:30am to 7:00am and 5:00pm to 5:30pm, at Stop #55165 Northbound Harvest Dr at Ladner Trunk Rd in Ladner, BC and from Stop #50043 Burrard Stn Bay1 in Vancouver, BC. In addition, meteorological conditions, traffic density, bus volume, and other observations were taken during sampling periods. RESULTS The author found that average PM2.5 exposures were highest during the morning in Ladner (μ=34.38667μg/m3) and lowest during the morning in Vancouver (μ=13.44 μg/m3). In addition, there was a statistically significant difference (p<0.05) between Vancouver AM and the other groups (Ladner AM, Ladner PM [μ=28.07778 μg/m3], and Vancouver PM [μ=30.16667 μg/m3]), but the other groups were not significantly different from each other. Furthermore, the author found that the Vancouver AM average (μ=13.44 μg/m3) was below the Metro Vancouver 24 hour rolling average (25μg/m3) while all other groups (Ladner AM, Ladner PM, and Vancouver PM) exceeded this average. Lastly, when comparing all groups to the AM and PM hourly averages of their respective LFV Air Quality Monitoring Network stations (Ladner AM and PM vs. Tsawwassen AM and PM and Vancouver AM and PM vs. Kitsalano AM and PM), the author found that all groups averages exceeded the hourly averages of their respective stations. CONCLUSION Commuters’ peak hour exposures were significantly influenced by different microenvironments and were found to be higher than the ambient PM2.5 levels registered by the respective LFV Air Quality Monitoring Network stations. In order to address this, Metro Vancouver should implement personal exposure assessments, especially near roadways, to obtain actual levels of exposure to pollutants, such as PM2.5, by their residents. In this way, acute and chronic health outcome risks to air pollution can be better understood.  

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