Influence of Temperature, Relative Humidity and Seasonal Variability on Ambient Air Quality in a Coastal Urban Area

Jayamurugan, Ramasamy; Kumaravel, B.; Palanivelraja, S.; Chockalingam, Muthukumar

doi:10.1155/2013/264046

Cited by 133 publications

(94 citation statements)

References 8 publications

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“…In their paper titled "Influence of Temperature, Relative Humidity and Seasonal Variability on Ambient Air Quality in a Coastal Urban Area", Jayamurugan, R., Kumaravel, B., Palanivelraja, S., & Chockalingam, M. P. establish a correlation between ambient atmospheric temperature and concentrations of greenhouse gases [7]. The conclusion reached in their paper agrees with the results derived here through analysis of lidar data, such as NRB and NRB error.…”

Section: Resultssupporting

confidence: 77%

Tracking Air Pollution in the City of Baltimore, Maryland Utilizing Light Detection and Ranging (LIDAR)

McCullum¹

2017

IJESD

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expansive bodies of water in the United States, extending from the southernmost tip of Virginia gradually reducing its reach into upstate New York. The airshed of the Chesapeake Bay, however, is influenced by nearly the entire Eastern and Midwestern United States, consequently necessitating recurrent monitoring of air contamination levels. Currently, there are limited practical methods available to keep a record of the true levels of pollution in the atmosphere. A simple approach to alleviate this limitation is the use of light detection and ranging, or lidar, by means of stationary emplacements located near major toxic hotspot zones. The efficacy of this system can be attributed to the particulates in the atmosphere that can be detected as a result of pollution deriving from different sources. Furthermore, the level of air pollution has been shown to be directly correlated to the atmospheric temperature, subsequently allowing relationships to be established between the atmospheric temperature and various forms of lidar data. Implications of a significant correlation being discovered between atmospheric temperature and any form of lidar data collected would provide insight on the effectiveness of lidar towards detecting and monitoring air pollution. In a broader sense, results from this investigation may be utilized to improve the atmospheric health and quality around the Chesapeake Bay and subsequently, the world.

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Section: Resultssupporting

confidence: 77%

Tracking Air Pollution in the City of Baltimore, Maryland Utilizing Light Detection and Ranging (LIDAR)

McCullum¹

2017

IJESD

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“…We first estimated models with only the regional dependent variable, and then in subsequent models added weather variables as covariates. Weather variables were considered because of the possible effects of these variables on pollutant levels . We conducted a sensitivity analysis that excluded days with humidity >95%.…”

Section: Methodsmentioning

confidence: 99%

Air Quality in Association With Rural Coal Mining and Combustion in New South Wales Australia

Hendryx

Higginbotham

Ewald

et al. 2019

The Journal of Rural Health

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Purpose Rural areas may face under‐recognized threats to air quality. We tested 2 hypotheses that 1) rural areas in New South Wales, Australia, would have better air quality than metropolitan Sydney, and that 2) the rural Upper Hunter region characterized by coal mining and coal combustion would have worse air quality than other rural areas of the state. Methods We analyzed 2017 daily mean values for New South Wales, Australia, for particulate matter (PM2.5 and PM10), sulfur dioxide (SO2), nitric oxide (NO), nitrogen dioxide (NO2), and NOx (sum of NO and NO2). Forty‐six air monitoring stations were grouped into 6 rural and urban regional areas. Linear regression models examined pollution levels in association with rural and urban regions and meteorological covariates. Results Findings show that daily mean pollutant levels in the rural Upper Hunter were the highest of all regions, and were significantly higher than metropolitan Sydney, with and without control for weather conditions, for every pollutant. For example, daily mean PM2.5 was 8.64 µg/m3 in the rural Upper Hunter, compared to 7.23 µg/m3 in metropolitan Sydney. Conclusions Results highlight the need to consider both urban and rural sources of pollution in air quality studies, and appropriate policy steps to address likely rural air pollution from coal mining.

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“…Thus, temperature can affect NO 2 negatively in two ways: firstly through direct effect by enhancing the photo-dissociation; and secondly through affecting other meteorological parameters, such as wind speed and atmospheric stability to enhance the dispersion process. Jayamurugan et al (2013) have also reported negative association between temperature and NO 2 , stating that heating of earth by the sun induces thermal turbulence during summer and increases the mixing height and therefore help increase the dispersion process of NO 2 . Therefore, it seems likely that reduction in the levels of NO 2 and THCs at extremely high temperature are causing ozone level to decrease and is the likely reason of the negative ozone-temperature slopes at extremely high temperature.…”

Section: Resultsmentioning

confidence: 99%

Modelling Ozone-Temperature Slope under Atypically High Temperature in Arid Climatic Conditions of Makkah, Saudi Arabia

Munir

Habeebullah

Ropkins

et al. 2015

Aerosol Air Qual. Res.

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Ground level ozone concentration is dependent on its precursors, such as Nitrogen Oxides (NO x ) and hydrocarbons (HCs) and meteorological parameters, most importantly air temperature. Positive ozone-temperature slope at average temperature is well-documented. However, how this relationship breaks at extremely high temperature in hotter climates is still debatable. As this could have implications for long term global modelling predictions, this paper explores evidence for a negative ozone-temperature slope during atypically high temperature events in Makkah, Saudi Arabia, where temperature levels as high as 50°C are recorded. At temperature levels (15-42°C) statistical analysis showed positive ozone-temperature slopes, however the slopes became negative at atypically high temperature levels (> 42°C). Using data when hourly mean temperature was greater than 42°C, Quantile Regression Model (QRM) showed negative ozone-temperature slopes. The negative slopes at quantile 0.2, 0.3, 0.4, 0.5, 0.6, 0.7, 0.8 and 0.9 were -1.88, -5.83, -7.89, -7.08, -11.11, -15.00, -18.28, and -28.57 µg/m 3 /°C, respectively. Mean slope determined by linear regression was -11.51 µg/m 3 /°C. Furthermore, the negative slopes were stronger at higher quantiles of ozone distribution, indicating non-linearities in the association of ozone and temperature. Reduction in the levels of ozone precursors, such as total hydrocarbons (THCs) and nitrogen dioxide (NO 2 ) is probably the most likely reason for the negative ozone-temperature slope at extremely high temperature. Previously concerns have been expressed that under the warming climate scenario increasing temperature may further increase ozone levels, particularly in urban areas during pollution episodes, however this study suggests the opposite at extremely high temperature in hot arid climatic conditions.

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Influence of Temperature, Relative Humidity and Seasonal Variability on Ambient Air Quality in a Coastal Urban Area

Cited by 133 publications

References 8 publications

Tracking Air Pollution in the City of Baltimore, Maryland Utilizing Light Detection and Ranging (LIDAR)

Tracking Air Pollution in the City of Baltimore, Maryland Utilizing Light Detection and Ranging (LIDAR)

Air Quality in Association With Rural Coal Mining and Combustion in New South Wales Australia

Modelling Ozone-Temperature Slope under Atypically High Temperature in Arid Climatic Conditions of Makkah, Saudi Arabia

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