Development of roadway link screening model for regional-level near-road air quality analysis: A case study for particulate matter

2020 ◽  
Vol 237 ◽  
pp. 117677
Author(s):  
Daejin Kim ◽  
Haobing Liu ◽  
Michael O. Rodgers ◽  
Randall Guensler
Keyword(s):  
Particulate Matter ◽  
Air Quality ◽  
Regional Level ◽  
Quality Analysis ◽  
Screening Model

scholarly journals Residents’ Perceptions of and Response Behaviors to Particulate Matter—A Case Study in Seoul, Korea

2019 ◽  
Vol 9 (18) ◽  
pp. 3660 ◽  
Author(s):  
Myung Eun Cho ◽  
Mi Jeong Kim
Keyword(s):  
Particulate Matter ◽  
Air Quality ◽  
Indoor Air Quality ◽  
Indoor Air ◽  
Physical Symptoms ◽  
Influential Factor ◽  
Psychological Attributes ◽  
Mitigation Action ◽  
Response Behaviors

This study is interested in understanding the particulate matter perceptions and response behaviors of residents. The purpose of this study was to identify indoor air quality along with the response behaviors of residents in Seoul, to ascertain whether there is a difference in behaviors when particulate matter is present, according to the characteristics of residents and to grasp the nature of this difference. A questionnaire survey of 171 respondents was conducted. The questionnaire measured the indoor air quality perceived by residents, the health symptoms caused by particulate matter, residents’ response behaviors to particulate matter and the psychological attributes affecting those response behaviors. Residents of Seoul were divided into college students in their twenties, male workers in their thirties and forties and female housewives in their thirties and forties. The data were calibrated by SPSS 23 using a one-way analysis of variance (ANOVA) and multiple regression analyses. The results show that most people found particulate matter to be an important problem but were unable to do sufficient mitigation action to prevent its presence. Residents showed greater psychological stress resulting in difficulty going out than physical symptoms. The most influential factor on response behaviors was psychological attributes. Participants were aware of the risks of particulate matter but believed it to be generated by external factors; thus, they felt powerless to do anything about it, which proved to be an obstacle to response behaviors.

scholarly journals A Time-Based Assessment of Particulate Matter (PM2.5) Levels at a Highly Trafficked Intersection: Case Study of Sango-Ota, Nigeria

Atmosphere ◽  
2021 ◽  
Vol 12 (5) ◽  
pp. 532
Author(s):  
David Olukanni ◽  
David Enetomhe ◽  
Gideon Bamigboye ◽  
Daniel Bassey
Keyword(s):  
Particulate Matter ◽  
Air Quality ◽  
Health Risks ◽  
Air Pollutants ◽  
Air Contamination ◽  
Ogun State ◽  
Sight Distance ◽  
Volatile Organic ◽  
Road Corridors

Vehicle emissions have become one of the most prevailing air contamination sources, including nitrogen oxides, volatile organic compounds, carbon monoxide and particulate matter (PM). Among other air pollutants, PM limits visible sight distance and poses health risks upon inhalation into the human body. This study focused on assessing PM2.5 concentrations in air at different periods of the day at the highly trafficked grade-separated intersection of Sango-Ota, Ogun State, Nigeria. PM2.5 readings were taken at three at-grade points around the intersection’s roundabout between 10:00 a.m. and 5:00 p.m. for four (4) days using the BR-SMART-126 Portable 4-in-1 air quality monitor. The highest level of PM2.5 obtained on Day 1 (Monday) and Day 4 (Thursday) was about 45.1% and 38.6%, respectively, lower than that of Day 3 (Wednesday). The highest concentrations of PM2.5 were recorded between 11:00 and 13:00 and between 16:00 and 18:00 (up to 217 µg/m3) whereas the lowest levels were recorded between 14:00 and 15:00 (as low as 86 µg/m3). The concentration of PM2.5 at the Sango-Ota intersection is adjudged “very poor” with average hourly concentrations between 97 and 370 µg/m3. Outcomes obtained indicate the need for improved measures to control air quality along major road corridors and at intersections in Ogun State and Nigeria at large.

scholarly journals Behavior of the Average Concentrations As Well As Their PM10 and PM2.5 Variability in the Metropolitan Area of Lima, Peru: Case Study February and July 2016

2021 ◽  
Vol 12 (7) ◽  
pp. 204-213
Author(s):  
Reátegui-Romero Warren ◽  
F. Zaldivar-Alvarez Walter ◽  
Pacsi–Valdivia Sergio ◽  
R. Sánchez-Ccoyllo Odón ◽  
E. García-Rivero Alberto ◽  
...  
Keyword(s):  
Particulate Matter ◽  
Air Quality ◽  
Relative Humidity ◽  
Metropolitan Area ◽  
Vehicular Traffic ◽  
Northern Area ◽  
The North ◽  
Pm10 And Pm2.5 ◽  
Traffic Behavior

This research focused on analyzing the behavior of the hourly average concentrations of PM10 and PM2.5 in relation to vehicular traffic, as well as the effect of relative humidity on these concentrations. Measurements of hourly particulate matter concentrations were recorded by the National Meteorology and Hydrology Service of Peru (SENAMHI) at five surface air quality stations. The profiles of PM10 concentrations are related to traffic behavior, showing high levels of concentrations at peak hours, while the PM2.5 profiles are flatter and better related to traffic in February (summer). The decrease in relative humidity between 80 to 65% in the mornings has a greater effect on the increase in PM10 and PM2.5 concentrations in February than in July (winter), and the increase in relative humidity between 65 to 80 % in the afternoon, it has a greater effect on the decrease in the concentration of PM2.5 in February than in July. The air quality in the north (PPD and CRB stations) and east (SJL station) of the Metropolitan Area of Lima (MAL) are the most polluted. The factors that relate PM10 concentrations with the Peruvian standard in February at these stations were 2.79, 1.78 and 1.26, and in July 2.74, 1.28 and 1.36 respectively. The highest and lowest variability of PM10 and PM2.5 in February and July occurred in the northern area (PPD and SMP stations).

scholarly journals Air quality analysis for a metropolitan area in Romania during the first half of 2021

2022 ◽  
Vol 354 ◽  
pp. 00066
Author(s):  
Clementina Sabina Moldovan ◽  
Liana-Simona Sbîrnă ◽  
Sebastian Sbîrnă
Keyword(s):  
European Union ◽  
Particulate Matter ◽  
Air Quality ◽  
Metropolitan Area ◽  
Quality Analysis ◽  
The European Union ◽  
Suspended Particulate ◽  
Air Quality Monitoring Stations ◽  
Matter Concentration

This paper aims to interpret and to use within a statistical analysis the concentration profiles of the main air pollutants – i.e., nitrogen oxides (NOx), sulfur dioxide (SO2), carbon monoxide (CO) and suspended particulate matter (PM10) – results recorded during the first half of 2021 by two air quality monitoring stations in Craiova, which is an important metropolitan area in Southern Romania. Another goal of the paper is finding the best numerical diffusion model to fit the recorded values for PM10, as this pollutant seems to be the major problem, because its daily average is often higher than the European Union threshold, meaning that imperative measures have to be taken for reducing particulate matter concentration in Craiova (like in other major Romanian metropolitan areas), in order for Romania to get the exoneration regarding air pollution from the European Union and, of course, for its citizens to improve the quality of their lives.

scholarly journals Climate impact on airborne particulate matter concentrations in California using seven year analysis periods

2010 ◽  
Vol 10 (2) ◽  
pp. 2985-3020 ◽  
Author(s):  
A. Mahmud ◽  
M. Hixson ◽  
J. Hu ◽  
Z. Zhao ◽  
S. Chen ◽  
...  
Keyword(s):  
Climate Change ◽  
Particulate Matter ◽  
Air Quality ◽  
Los Angeles ◽  
Spatial Resolution ◽  
Quality Analysis ◽  
Present Climate ◽  
Annual Average ◽  
Starting Point ◽  
Quality Modeling

Abstract. The effect of global climate change on the annual average concentration of fine particulate matter (PM2.5) in California was studied using a climate – air quality modeling system composed of global through regional models. Output from the NCAR/DOE Parallel Climate Model (PCM) generated under the "business as usual" global emissions scenario was downscaled using the Weather Research and Forecasting (WRF) model followed by air quality simulations using the UCD/CIT airshed model. The air quality simulations were carried out for the entire state of California with a resolution of 8-km for the years 2000–2006 (present climate) and 2047–2053 (future climate). The 7-year windows were chosen to properly account for annual variability with the added benefit that the air quality predictions under the present climate could be compared to actual measurements. The climate – air quality modeling system successfully predicted the spatial pattern of present climate PM2.5 concentrations in California but the absolute magnitude of the annual average PM2.5 concentrations were under-predicted by ~35–40% in the major air basins. The majority of this under-prediction was caused by excess ventilation predicted by PCM-WRF that should be present to the same degree in the current and future time periods so that the net bias introduced into the comparison is minimized. Surface temperature, relative humidity (RH), rain rate, and wind speed were predicted to increase in the future climate while the ultra violet (UV) radiation was predicted to decrease in major urban areas in the San Joaquin Valley (SJV) and South Coast Air Basin (SoCAB). These changes resulted in a ~0.6–1.9 μg m−3 decrease in predicted PM2.5 concentrations in coastal and central Los Angeles. Annual average PM2.5 concentrations were predicted to increase at certain locations within the SJV and the Sacramento Valley due to the effects of climate change, but a corresponding analysis of the annual variability showed that these predictions are not statistically significant (i.e. the choice of a different 7-year period could produce a different outcome for these regions). Overall, virtually no region in California outside of coastal and central Los Angeles experienced a statistically significant change in annual average PM2.5 concentrations due to the effects of climate change in the present study. The present study employs the highest spatial resolution (8 km) and the longest analysis windows (7 years) of any climate-air quality analysis conducted for California to date, but the results still have some degree of uncertainty. Most significantly, GCM calculations have inherent uncertainty that is not fully represented in the current study since a single GCM was used as the starting point for all calculations. Ensembles of GCM results are usually employed to build confidence in climate calculations. The current results provide a first data-point for the climate-air quality analysis that simultaneously employ the fine spatial resolution and long time scales needed to capture the behavior of climate-PM2.5 interactions in California. Future downscaling studies should follow up with a full ensemble of GCMs as their starting point.

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