scholarly journals PM2.5 dispersion modelling from La Ronde fireworks events in Montreal using AERMOD and ArcMap

2021 ◽  
Author(s):  
Deon Bridge

Particulate matter from fireworks events are poorly understood sources of PM2.5 despite their potential to add significant quantities of PM2.5 to the atmosphere. PM2.5 has been found to aggravate various cardiovascular and respiratory illnesses and has been linked to premature death. Each year La Ronde amusement park on Sainte-Helene Island exhibits numerous firework events in what is considered one of the world's premiere pyrotechnic competitions. These individual events are the centre of study for this project. Each event was modelled using Lakes Environmental's version of AERMOD, which estimated PM2.5 concentration plumes which then underwent geospatial analysis using ArcMap. This project details the PM2.5 plume dynamics from La Ronde fireworks events from 1990-2004, and how these events impact a ten kilometer radius around the island of Sainte-Helene in Montreal, Canada.

2021 ◽  
Author(s):  
Deon Bridge

Particulate matter from fireworks events are poorly understood sources of PM2.5 despite their potential to add significant quantities of PM2.5 to the atmosphere. PM2.5 has been found to aggravate various cardiovascular and respiratory illnesses and has been linked to premature death. Each year La Ronde amusement park on Sainte-Helene Island exhibits numerous firework events in what is considered one of the world's premiere pyrotechnic competitions. These individual events are the centre of study for this project. Each event was modelled using Lakes Environmental's version of AERMOD, which estimated PM2.5 concentration plumes which then underwent geospatial analysis using ArcMap. This project details the PM2.5 plume dynamics from La Ronde fireworks events from 1990-2004, and how these events impact a ten kilometer radius around the island of Sainte-Helene in Montreal, Canada.


Author(s):  
Youngrin Kwag ◽  
Min-ho Kim ◽  
Shinhee Ye ◽  
Jongmin Oh ◽  
Gyeyoon Yim ◽  
...  

Background: Preterm birth contributes to the morbidity and mortality of newborns and infants. Recent studies have shown that maternal exposure to particulate matter and extreme temperatures results in immune dysfunction, which can induce preterm birth. This study aimed to evaluate the association between fine particulate matter (PM2.5) exposure, temperature, and preterm birth in Seoul, Republic of Korea. Methods: We used 2010–2016 birth data from Seoul, obtained from the Korea National Statistical Office Microdata. PM2.5 concentration data from Seoul were generated through the Community Multiscale Air Quality (CMAQ) model. Seoul temperature data were collected from the Korea Meteorological Administration (KMA). The exposure period of PM2.5 and temperature were divided into the first (TR1), second (TR2), and third (TR3) trimesters of pregnancy. The mean PM2.5 concentration was used in units of ×10 µg/m3 and the mean temperature was divided into four categories based on quartiles. Logistic regression analyses were performed to evaluate the association between PM2.5 exposure and preterm birth, as well as the combined effects of PM2.5 exposure and temperature on preterm birth. Result: In a model that includes three trimesters of PM2.5 and temperature data as exposures, which assumes an interaction between PM2.5 and temperature in each trimester, the risk of preterm birth was positively associated with TR1 PM2.5 exposure among pregnant women exposed to relatively low mean temperatures (<3.4 °C) during TR1 (OR 1.134, 95% CI 1.061–1.213, p < 0.001). Conclusions: When we assumed the interaction between PM2.5 exposure and temperature exposure, PM2.5 exposure during TR1 increased the risk of preterm birth among pregnant women exposed to low temperatures during TR1. Pregnant women should be aware of the risk associated with combined exposure to particulate matter and low temperatures during TR1 to prevent preterm birth.


Atmosphere ◽  
2021 ◽  
Vol 12 (4) ◽  
pp. 460
Author(s):  
Jiun-Horng Tsai ◽  
Ming-Ye Lee ◽  
Hung-Lung Chiang

The Community Multiscale Air Quality (CMAQ) measurement was employed for evaluating the effectiveness of fine particulate matter control strategies in Taiwan. There are three scenarios as follows: (I) the 2014 baseline year emission, (II) 2020 emissions reduced via the Clean Air Act (CAA), and (III) other emissions reduced stringently via the Clean Air Act. Based on the Taiwan Emission Data System (TEDs) 8.1, established in 2014, the emission of particulate matter 2.5 (PM2.5) was 73.5 thousand tons y−1, that of SOx was 121.3 thousand tons y−1, and that of NOx was 404.4 thousand tons y−1 in Taiwan. The CMAQ model simulation indicated that the PM2.5 concentration was 21.9 μg m−3. This could be underestimated by 24% in comparison with data from the ambient air quality monitoring stations of the Taiwan Environmental Protection Administration (TEPA). The results of the simulation of the PM2.5 concentration showed high PM2.5 concentrations in central and southwestern Taiwan, especially in Taichung and Kaohsiung. Compared to scenario I, the average annual concentrations of PM2.5 for scenario II and scenario III showed reductions of 20.1% and 28.8%, respectively. From the results derived from the simulation, it can be seen that control of NOx emissions may improve daily airborne PM2.5 concentrations in Taiwan significantly and control of directly emitted PM2.5 emissions may improve airborne PM2.5 concentrations each month. Nevertheless, the results reveal that the preliminary control plan could not achievethe air quality standard. Therefore, the efficacy and effectiveness of the control measures must be considered to better reduce emissions in the future.


Gefahrstoffe ◽  
2019 ◽  
Vol 79 (11-12) ◽  
pp. 443-450
Author(s):  
P. Bächler ◽  
J. Meyer ◽  
A. Dittler

The reduction of fine dust emissions with pulse-jet cleaned filters plays an important role in industrial gas cleaning to meet emission standards and protect the environment. The dust emission of technical facilities is typically measured “end of pipe”, so that no information about the local emission contribution of individual filter elements exists. Cheap and compact low-cost sensors for the detection of particulate matter (PM) concentrations, which have been prominently applied for immission monitoring in recent years have the potential for emission measurement of filters to improve process monitoring. This publication discusses the suitability of a low-cost PM-sensor, the model SPS30 from the manufacturer Sensirion, in terms of the potential for particle emission measurement of surface filters in a filter test rig based on DIN ISO 11057. A Promo® 2000 in combination with a Welas® 2100 sensor serves as the optical reference device for the evaluation of the detected PM2.5 concentration and particle size distribution of the emission measured by the low-cost sensor. The Sensirion sensor shows qualitatively similar results of the detected PM2.5 emission as the low-cost sensor SDS011 from the manufacturer Nova Fitness, which was investigated by Schwarz et al. in a former study. The typical emission peak after jet-pulse cleaning of the filter, due to the penetration of particles through the filter medium, is detected during Δp-controlled operation. The particle size distribution calculated from the size resolved number concentrations of the low-cost sensor yields a distinct distribution for three different employed filter media and qualitatively fits the size distribution detected by the Palas® reference. The emission of these three different types of filter media can be distinguished clearly by the measured PM2.5 concentration and the emitted mass per cycle and filter area, demonstrating the potential for PM emission monitoring by the low-cost PM-sensor. During the period of Δt-controlled filter aging, a decreasing emission, caused by an increasing amount of stored particles in the filter medium, is detected. Due to the reduced particle emission after filter aging, the specified maximum concentration of the low-cost sensor is not exceeded so that coincidence is unlikely to affect the measurement results of the sensor for all but the very first stage of filter life.


2019 ◽  
Vol 25 (6) ◽  
pp. 898-907 ◽  
Author(s):  
M. Gokul Raj ◽  
S. Karthikeyan

Daily commuting increases level of contaminants inhaled by urban community and it is influenced by mode and time of commuting. In this study, the commuters’ exposure to ambient particulate matter (PM2.5) and nitrogen dioxide (NO2) was assessed during three modes of travel in six different road stretches of Chennai. The mean distance of road stretches was 25 km and the exposure to pollutants was assessed during peak hours and off-peak hours. The average travel duration was in the range of 39 to 91 min in motorbike, 83 to 140 min in car and 110 to 161 min in bus. Though there was variation on exposure to concentration in modes of transportation, the maximum exposure concentration of PM2.5 was observed as 709 μg/m<sup>3</sup> in bus and the minimum exposure concentration was 29 μg/m<sup>3</sup> in closed car. Similarly, the maximum exposure concentration of NO2 was observed to be 312 μg/m<sup>3</sup> in bus and the minimum exposure concentration was 21 μg/m<sup>3</sup> in car. The concentration of elements in PM2.5 was in the order of Si > Na > Ca > Al ≥ K > S ≥ Cd, with Si and Cd concentration as 60% and < 1% of the PM2.5 concentration.


2022 ◽  
Vol 71 (2) ◽  
pp. 3051-3068
Author(s):  
Muhammad Zulqarnain ◽  
Rozaida Ghazali ◽  
Habib Shah ◽  
Lokman Hakim Ismail ◽  
Abdullah Alsheddy ◽  
...  

2019 ◽  
Vol 8 (3) ◽  
pp. 7922-7927

In Taiwan country Annan, Chiayi, Giran, and Puzi cities are facing a serious fine particulate matter (PM2.5) issue. To date the impressive advance has been made toward understanding the PM2.5 issue, counting special temporal characterization, driving variables and well-being impacted. However, notable research as has been done on the interaction of the content between the selected cities of Taiwan country for particulate matter (PM2.5) concentration. In this paper, we purposed a visualization technique based on this principle of the visualization, cross-correlation method and also the time-series concentration with particulate matter (PM2.5) for different cities in Taiwan. The visualization also shows that the correlation between the different meteorological factors as well as the different air pollution pollutants for particular cities in Taiwan. This visualization approach helps to determine the concentration of the air pollution levels in different cities and also determine the Pearson correlation, r values of selected cities are Annan, Puzi, Giran, and Wugu.


Author(s):  
Qing Tian ◽  
Mei Li ◽  
Scott Montgomery ◽  
Bo Fang ◽  
Chunfang Wang ◽  
...  

Background: Exposures to both ambient fine particulate matter (PM2.5) and extreme weather conditions have been associated with cardiovascular disease (CVD) deaths in numerous epidemiologic studies. However, evidence on the associations with CVD deaths for interaction effects between PM2.5 and weather conditions is still limited. This study aimed to investigate associations of exposures to PM2.5 and weather conditions with cardiovascular mortality, and further to investigate the synergistic or antagonistic effects of ambient air pollutants and synoptic weather types (SWTs). Methods: Information on daily CVD deaths, air pollution, and meteorological conditions between 1 January 2012 and 31 December 2014 was obtained in Shanghai, China. Generalized additive models were used to assess the associations of daily PM2.5 concentrations and meteorological factors with CVD deaths. A 15-day lag analysis was conducted using a polynomial distributed lag model to access the lag patterns for associations with PM2.5. Results: During the study period, the total number of CVD deaths in Shanghai was 59,486, with a daily mean of 54.3 deaths. The average daily PM2.5 concentration was 55.0 µg/m3. Each 10 µg/m3 increase in PM2.5 concentration was associated with a 1.26% (95% confidence interval (CI): 0.40%, 2.12%) increase in CVD mortality. No SWT was statistically significantly associated with CVD deaths. For the interaction between PM2.5 and SWT, statistically significant interactions were found between PM2.5 and cold weather, with risk for PM2.5 in cold dry SWT decreasing by 1.47% (95% CI: 0.54%, 2.39%), and in cold humid SWT the risk decreased by 1.45% (95% CI: 0.52%, 2.36%). In the lag effect analysis, statistically significant positive associations were found for PM2.5 in the 1–3 lag days, while no statistically significant effects were found for other lag day periods. Conclusions: Exposure to PM2.5 was associated with short-term increased risk of cardiovascular deaths with some lag effects, while the cold weather may have an antagonistic effect with PM2.5. However, the ecological study design limited the possibility to identify a causal relationship, so prospective studies with individual level data are warranted.


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