Particulate matter intake fractions for vehicular emissions at elementary schools in Hamilton, Canada: an assessment of outdoor and indoor exposure

2017 ◽  
Vol 10 (10) ◽  
pp. 1259-1267
Author(s):  
Weeberb J. Requia ◽  
Matthew D. Adams ◽  
Altaf Arain ◽  
Mark Ferguson
2021 ◽  
Author(s):  
Yovitza Romero ◽  
Priyanka deSouza ◽  
Fabio Duarte ◽  
Patrick Kinney ◽  
Carlo Ratti ◽  
...  

Abstract Lima has been ranked among the top most polluted cities in the Americas. Vehicular emissions are the dominant source of pollution in the city. In order to reduce congestion and pollution levels during the XVIII Pan- and Parapan-American Games, Lima government officials enacted the pico y placa policy to restrict the number of vehicles on certain heavily trafficked roads in the city at rush hours between Monday to Thursday based on the last digit of their license plates. This policy was retained after the Games. In this paper we evaluate the impact of this policy on fine particulate matter concentration levels (PM2.5) at a background site in the city using a difference-in-difference approach. We find that the policy resulted in increases on PM2.5 levels on Monday-Thursday compared to Friday-Sunday levels after the policy was enacted, compared to previous years. However, such an increase was not significant. These results suggest the need for additional policies to reduce pollution due to traffic in Lima. It also suggests the need to track the response to this policy over time to evaluate its efficacy.


2007 ◽  
Vol 57 (4) ◽  
pp. 394-406 ◽  
Author(s):  
Kuruvilla John ◽  
Saritha Karnae ◽  
Kevin Crist ◽  
Myoungwoo Kim ◽  
Amol Kulkarni

2014 ◽  
Vol 14 (22) ◽  
pp. 12085-12097 ◽  
Author(s):  
S. Hasheminassab ◽  
N. Daher ◽  
A. Saffari ◽  
D. Wang ◽  
B. D. Ostro ◽  
...  

Abstract. To identify major sources of ambient fine particulate matter (PM2.5, dp < 2.5 μm) and quantify their contributions in the state of California, a positive matrix factorization (PMF) receptor model was applied on Speciation Trends Network (STN) data, collected between 2002 and 2007 at eight distinct sampling locations, including El Cajon, Rubidoux, Los Angeles, Simi Valley, Bakersfield, Fresno, San Jose, and Sacramento. Between five to nine sources of fine PM were identified at each sampling site, several of which were common among multiple locations. Secondary aerosols, including secondary ammonium nitrate and ammonium sulfate, were the most abundant contributor to ambient PM2.5 mass at all sampling sites, except for San Jose, with an annual average cumulative contribution of 26 to 63%, across the state. On an annual average basis, vehicular emissions (including both diesel and gasoline vehicles) were the largest primary source of fine PM at all sampling sites in southern California (17–18% of total mass), whereas in Fresno and San Jose, biomass burning was the most dominant primary contributor to ambient PM2.5 (27 and 35% of total mass, respectively), in general agreement with the results of previous source apportionment studies in California. In Bakersfield and Sacramento, vehicular emissions and biomass burning displayed relatively equal annual contributions to ambient PM2.5 mass (12 and 25%, respectively). Other commonly identified sources at all sites included aged and fresh sea salt and soil, which contributed to 0.5–13%, 2–27%, and 1–19% of the total mass, respectively, across all sites and seasons. In addition, a few minor sources were identified exclusively at some of the sites (e.g., chlorine sources, sulfate-bearing road dust, and different types of industrial emissions). These sources overall accounted for a small fraction of the total PM mass across the sampling locations (1 to 15%, on an annual average basis).


2020 ◽  
Vol 2 (4) ◽  
pp. 136-140
Author(s):  
Clara Rodrigues Pereira ◽  
Lílian Lefol Nani Guarieiro

Studies show that exposure to particulate matter (PM) from vehicular combustion processes can pose severe risks to human health since the impact degree of PM on the respiratory system will depend on its size and composition. Thus, the objective of this study was to perform a systematic review on this topic, searching information that can highlight causes and solutions that may allow a greater understanding of this problem. We concluded that China is a country that stands out in the number of deaths caused by the emission of PM, given a highly polluted urban scenario. Besides, fine particles (PM2.5) are the most recurrent incidence of respiratory disease, as they are emitted mainly by industrial activities and vehicular emissions.


2017 ◽  
Vol 6 (2) ◽  
Author(s):  
Batoul Chami ◽  
Elizabeth Johnson ◽  
J. Mike Courage ◽  
Serge Danielson-Francois

The exposure of particulate matter on children, ages 1-18, is considered in this paper using a quantitative research approach. Utilizing foundational and seminal sources, this is a review of asthma and its triggers, and particulate matter, specifically ultrafine particles with a dimension of less than or equal to 100 nanometers (nm). An interest sparked with the effect of these ultrafine particles and their possible ignition of asthma. A troubling area was a lack of information on what may cause a greater link when exposed to these ultrafine particles: an ambient/indoor environment or an outdoor/non-ambient environment. This posed a significant concern because even though both environments may lead to asthma, the lack of information was not evident and not uninformed. To conduct this study, a systematic review occurred using a statistical program. Data was accumulated from multiple sources that tested for either an association of pediatric asthma and particulate matter with an outdoor exposure or an indoor exposure. Analyses were ran and statistical evidence resulted in a greater association in an indoor environment. The variables accounted for were odds ratio, confidence intervals and their limits, the setting of the tests run within the research and the exposure of the particulate matter.


2015 ◽  
Vol 207 ◽  
pp. 161-167 ◽  
Author(s):  
Jia Xu ◽  
Taosheng Jin ◽  
Yaning Miao ◽  
Bin Han ◽  
Jiajia Gao ◽  
...  

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