Estimating ground level PM2.5 concentrations and associated health risk in India using satellite based AOD and WRF predicted meteorological parameters

Meteorological parameters and traffic flows have a direct impact on air quality in large urban areas, and hence on the quality of life in them. A large number of done surveys confirmed the great dependence of the concentration of ground-level ozone (O3) upon meteorological parameters and the size, structure and imbalances of traffic flows. As part of the research conducted in the period from November 5th to December 8th 2014 in Brcko in Muderis Ibrahimbegic St concentrations of ground-level ozone (O3) were measured, meteorological parameters (temperature, humidity, wind speed and intensity of solar radiation) and characteristics of traffic flow of road motor vehicles. The maximum concentrations of ground-level ozone (O3) in the measurement period was 106.54μg/m³, while the minimum concentration was 4.794μg/m³. By analyzing the results of measurements the high coefficient of correlation between wind speed, air temperature and humidity was established. The correlation coefficient between the traffic flows on the one hand and the concentration of ground-level ozone (O3), on the other hand is very low and does not exceed the value of 0.301. A negative correlation coefficient between traffic flows and concentrations of ground-level ozone (O3) is also observed in the certain time of the day.

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Study of ground-level ozone and its health risk assessment in residents in Ahvaz City, Iran during 2013

Toxin Reviews ◽

10.1080/15569543.2016.1225769 ◽

2016 ◽

Vol 35 (3-4) ◽

pp. 201-206 ◽

Cited By ~ 32

Author(s):

Ahmad Reza Yari ◽

Gholamreza Goudarzi ◽

Sahar Geravandi ◽

Sina Dobaradaran ◽

Farid Yousefi ◽

...

Keyword(s):

Risk Assessment ◽

Health Risk ◽

Health Risk Assessment ◽

Ground Level ◽

Ground Level Ozone

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Dew on reindeer lichen

Canadian Journal of Forest Research ◽

10.1139/x91-198 ◽

1991 ◽

Vol 21 (9) ◽

pp. 1415-1418 ◽

Cited By ~ 3

Author(s):

Gyula Péch

Keyword(s):

Moisture Content ◽

Meteorological Parameters ◽

Ground Level ◽

Meteorological Station ◽

Mass Measurements ◽

Moisture Contents ◽

Hourly Rate ◽

Simple Linear Relationship ◽

Maximum Moisture Content ◽

Reindeer Lichen

Four reindeer lichen (Cladinarangiferina (L.) Nyl) samples were placed near ground level in the open at a meteorological station where dew and other meteorological parameters were measured. One sample was covered occasionally from sunset to sunrise to prevent dew and to evaluate moisture gain due to wetting by atmospheric vapour alone. Mass measurements were done day and night following a set schedule. At the conclusion of the field program the samples were oven-dried and all weight measurements were converted to moisture contents. The results showed that a simple linear relationship adequately describes the overnight rise of lichen moisture caused by dew, and that atmospheric vapour alone, on nights without rain or condensation, can raise lichen moisture by 15%. Further, the results confirmed that nocturnal moisture gains by either dew or atmospheric vapour dissipate on subsequent clear mornings by noon. These findings suggest that at locations where humidity is measured at night and dew may be assessed visually in the morning, one can estimate both the 06:00 maximum moisture content of the lichen and, on subsequent clear mornings, the hourly rate of its drying.

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Daily Concentrations of PM2.5 in the Valencian Community Using Random Forest for the Period 2008–2018

Proceedings ◽

10.3390/proceedings2019019013 ◽

2019 ◽

Vol 19 (1) ◽

pp. 13

Author(s):

Represa ◽

Palomar-Vázquez ◽

Porta ◽

Fernández-Sarría

Keyword(s):

Climate Change ◽

Random Forest ◽

Cross Validation ◽

Meteorological Parameters ◽

Fine Particulate Matter ◽

Ground Level ◽

Test Set ◽

Quality Models ◽

Final Model ◽

Fine Particulate

Fine particulate matter (PM2.5) is a global problem that affects the population health and contributes to climate change. Remote sensing provides useful information for the development of air quality models. This work aims to obtain a daily model of PM2.5 levels in the Valencian Community with a resolution of 1 km for the period 2008–2018. MODIS-MAIAC images, meteorological parameters of the MERRA-2 project, land cover information and ground level measurements of PM2.5 levels were analysed with Random Forest. The verification of the model was carried out using cross-validation repeated ten times, and an evaluation of a test set with 20% of the collected information. The final model was used to generate maps of the daily concentrations of PM2.5 for the area of the Valencian Community throughout the study period.

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Assessment of the impact of traffic volume on NO2 levels in Munich during the lock-down periods

10.5194/dach2022-161 ◽

2021 ◽

Author(s):

Sheng Ye ◽

Ka Lok Chan ◽

Tamara Brunner ◽

Hanlin Zhang ◽

Alexander Geiß ◽

...

Keyword(s):

Meteorological Parameters ◽

Early Stage ◽

Measurement Techniques ◽

Absolute Humidity ◽

Ground Level ◽

Traffic Volume ◽

Impact Factors ◽

Long Term Study ◽

The Impact

The global pandemic has many negative economic, social and health impacts, but the lock-downs also led to a reduction of traffic volume which resulted in lower NO2 levels in some areas. Our study made use of different air quality measurement techniques (in-situ, on-road, satellite remote sensing) to monitor long-term NO2 levels in Munich. While comparing NO2 levels associate with traffic volume before and after a lock-down, other influences based on meteorological parameters should be considered as well. In addition to traffic data we used records of wind, mixing layer height, temperature, humidity and other meteorological parameters to analyze the impact on measured pollution levels using a Generalized Additive Model (GAM) regression. Our long-term study using data between 2018 and 2021 shows that the dominating factor is wind speed, followed by traffic volume as the main factors for impacting NO2 levels, while absolute humidity and wind direction show less effects. We utilized those findings to find best suited time periods comparable to the lockdown time in terms of meteorological conditions. In order to focus on the traffic volume factor, we applied these findings to minimize other impact factors to evaluate the NO2 variability of different years comparing to the data from the lockdown periods. A significant reduction of the ground level NO2 concentrations in Munich during the early stage of the lockdown period in March 2020 could clearly be associated with a significant reduction of traffic volume.

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Risk Assessment for People Exposed to PM2.5 and Constituents at Different Vertical Heights in an Urban Area of Taiwan

Atmosphere ◽

10.3390/atmos11111145 ◽

2020 ◽

Vol 11 (11) ◽

pp. 1145

Author(s):

Hsiu-Ling Chen ◽

Chi-Pei Li ◽

Chin-Sheng Tang ◽

Shih-Chun Candice Lung ◽

Hsiao-Chi Chuang ◽

...

Keyword(s):

Risk Assessment ◽

Health Risk ◽

Urban Area ◽

Urban Areas ◽

Lung Cancer Mortality ◽

Ground Level ◽

Epidemiological Studies ◽

Pollutant Concentrations ◽

Vertical Distributions ◽

Pm2.5 And Pm10

Environmental epidemiological studies have consistently reported associations between ambient particulate matter (PM) concentrations and everyday mortality/morbidity. Many urban dwellers in Asia live in high-rise apartment buildings; thus, the pollutant concentrations of their immediate outdoor environments are affected by the vertical distribution of pollutants in the atmosphere. The vertical distributions of pollutants provide unique information about their sources and dynamic transport in urban areas, as well as their relationship to people’s exposure at ground level, while the vertical distributions of pollutants have rarely been considered in exposure assessment. In the current study, PM concentrations (with aerodynamic diameters less than 1.0 μm (PM1), 2.5 μm (PM2.5), and 10 μm (PM10)), nanoparticles, black carbon (BC), and particle-bound polycyclic aromatic hydrocarbons (p-PAHs) were measured at different residential heights—6 m, 16 m, and 27 m—at Feng Chia University near a popular night market in Western Taiwan. PM2.5 data were further adopted for health risk estimations. In winter, the magnitude of PM1, PM2.5, and PM10 concentrations were 16 m > 6 m > 27 m; nanoparticle concentrations were 6 m > 27 m > 16 m; and BC and p-PAHs concentrations were 27 m > 16 m > 6 m. In summer, PM1, PM2.5, and PM10 concentrations ranged from 6 m > 16 m > 27 m; nanoparticle concentrations were 6 m > 16 m; and BC and p-PAHs concentrations were from 27 m > 16 m. PM and constituents concentrations during winter were significantly higher in the nighttime than those in daytime, and levels of PM1, PM2.5, and PM10 increased rapidly on 6 m and 16 m heights (but did not increase at 27 m) after 5 pm, whereas these trends became less significant in summer. Health risk analysis for PM2.5 concentrations showed a decrease in lung cancer mortality rate and an extended lifespan for residents living at 27 m. Overall, the current study investigated the vertical profile of particulate matters and analyzed health impacts of PM2.5 at different residential heights in urban area of Taiwan. As the distributions of PM and the constituents varied at different residential heights, exposure and risk assessment of particle concentrations with multiple sizes and various components at broader vertical heights should be further investigated.

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