Air pollution in an urban street canyon: Novel insights from highly resolved traffic information and meteorology

Author(s):  
Laura Ehrnsperger ◽  
Otto Klemm

<p>Ambient air pollution caused by fine particulate matter (PM) and trace gases is a pressing topic as it affects the vast majority of the world's population, especially in densely populated urban environments. The main sources of ambient air pollution in cities are road traffic, industries and domestic heating. Alongside nitrogen oxides (NO<sub>x</sub>) and PM, ammonia (NH<sub>3</sub>) is also a relevant air pollutant due to its role as a precursor of particulate ammonium (NH<sub>4</sub><sup>+</sup>). To examine the temporal patterns and sources of air pollutants, this study used fast-response air quality measurements in combination with highly resolved traffic information in Münster, NW Germany. The temporal dynamics of NO<sub>x</sub> and the particle number concentration (PN<sub>10</sub>) were similar to the diurnal and weekly courses of the traffic density. On very short timescales, the real-world peak ratios of NO<sub>x</sub> and PM ≤ 10 µm diameter (PM<sub>10</sub>) exceeded the predicted pollutant emission ratios of the Handbook for Emission Factors for Road Transport (HBEFA) by a factor of 6.4 and 2.0, respectively. A relative importance model revealed that light-duty vehicles (LDVs) are the major relative contributor to PN<sub>10</sub> (38 %) despite their low abundance (4 %) in the local vehicle fleet.  Diesel and gasoline vehicles contributed similarly to the concentrations of PM<sub>10</sub> and PN<sub>10</sub>, while the impact of gasoline vehicles on the PM<sub>1</sub> concentration was greater than that of diesel vehicles by a factor of 4.4. The most recent emission class Euro 6 had the highest influence on PM<sub>10</sub>. Meteorological parameters explained a large portion of the variations in PM<sub>10</sub> and PM<sub>1</sub>, while meteorology had only a minor influence on PN<sub>10</sub>. We also studied the short-term temporal dynamics of urban NH<sub>3 </sub>concentrations, the role of road traffic and agriculture as NH<sub>3</sub> sources and the importance of ammonia for secondary particle formation (SPF). The NH<sub>3</sub> mixing ratio was rather high (mean: 17 ppb) compared to other urban areas and showed distinct diurnal maxima around 10 a.m. and 9 p.m. The main source for ammonia in Münster was agriculture, but road traffic also contributed through local emissions from vehicle catalysts. NH<sub>3</sub> from surrounding agricultural areas accumulated in the nocturnal boundary layer and contributed to SPF in the city center. The size-resolved chemical composition of inorganic ions in PM<sub>10</sub> was dominated by NH<sub>4</sub><sup>+</sup> (8.7 µg m<sup>-3</sup>), followed by NO<sub>3</sub><sup>-</sup> (3.9 µg m<sup>-3</sup>), SO<sub>4</sub><sup>2-</sup> (1.6 µg m<sup>-3</sup>) and Cl<sup>-</sup> (1.3 µg m<sup>-3</sup>). Particles in the accumulation range (diameter: 0.1 – 1 µm) showed the highest inorganic ion concentrations. The ammonium neutralization index J (111 %) indicated an excess of NH<sub>4</sub><sup>+</sup> leading to mostly alkaline PM. High ammonia emissions from surrounding agricultural areas combined with large amounts of NO<sub>x</sub> from road traffic play a crucial role for SPF in Münster. Our results further indicate that replacing fossil-fuelled LDVs with electrical vehicles would greatly reduce the PN<sub>10</sub> concentrations at this urban site.</p>

2021 ◽  
Vol 152 ◽  
pp. 106464 ◽  
Author(s):  
Shuo Liu ◽  
Youn-Hee Lim ◽  
Marie Pedersen ◽  
Jeanette T. Jørgensen ◽  
Heresh Amini ◽  
...  

2017 ◽  
Vol 108 ◽  
pp. 253-260 ◽  
Author(s):  
Marie Pedersen ◽  
Sjurdur F. Olsen ◽  
Thorhallur I. Halldorsson ◽  
Cuilin Zhang ◽  
Dorrit Hjortebjerg ◽  
...  

2019 ◽  
Vol 3 (5) ◽  
pp. e069
Author(s):  
Marie Pedersen ◽  
Thorhallur I. Halldorsson ◽  
Matthias Ketzel ◽  
Charlotta Grandström ◽  
Ole Raaschou-Nielsen ◽  
...  

2021 ◽  
Author(s):  
J. Toutouh ◽  
S. Nesmachnow ◽  
D.G. Rossit

Urbanization trends worldwide show a clear preference for motorized road mobility, which has led to a degradation of air quality in recent years. Modelling and forecasting ambient air pollution is a relevant problem because it helps decision-makers and urban city planners understand this phenomenon, which is a significant threat to citizens’ health. Generally, datadriven models suffer from a lack of data. This article addresses the issue of having limited access to road traffic density and pollution concentration data by applying deep generative models, specifically, Conditional Generative Adversarial Networks (CGAN). The main idea is to train CGANs to generate synthetic nitrogen dioxide concentration values given the road traffic density. The experimental data analysis from Montevideo (Uruguay) shows that the proposed method generates realistic (accurate and diverse) pollution data while using reduced computational resources.


2014 ◽  
Vol 133 ◽  
pp. 49-55 ◽  
Author(s):  
Mette Sørensen ◽  
Pernille Lühdorf ◽  
Matthias Ketzel ◽  
Zorana J. Andersen ◽  
Anne Tjønneland ◽  
...  

Author(s):  
Soheil Sohrabi ◽  
Joe Zietsman ◽  
Haneen Khreis

With recent rapid urbanization, sustainable development is required to prevent health risks associated with adverse environmental exposures from the unsustainable development of cities. Ambient air pollution is the greatest environmental risk factor for human health and is responsible for considerable levels of mortality worldwide. Burden of disease assessment (BoD) of air pollution in and across cities, and how these estimates vary according to socioeconomic status and exposure to road traffic, can help city planners and health practitioners to mitigate adverse exposures and promote public health. In this study, we quantified the health impacts of air pollution exposure (PM2.5 and NO2) at the census tract level in Houston, Texas, employing a standard BoD assessment framework to estimate the premature deaths (adults 30 to 78 years old) attributable to PM2.5 and NO2. We found that 631 (95% CI: 366–809) premature deaths were attributable to PM2.5 in Houston, and 159 (95% CI: 0-609) were attributable to NO2, in 2010. Complying with the World Health Organization air quality guidelines (annual mean: 10 μg/m3 for PM2.5) and the US National Ambient Air Quality standard (annual mean: 12 μg/m3 for PM2.5) could save 82 (95% CI: 42–95) and 8 (95% CI: 6–10) lives in Houston, respectively. PM2.5 was responsible for 7.3% of all-cause premature deaths in Houston, in 2010, which is higher than the death rate associated with diabetes mellites, Alzheimer’s disease, or motor vehicle crashes in the US. Households with lower income had a higher risk of adverse exposure and attributable premature deaths. We also showed a positive relationship between health impacts attributable to air pollution and road traffic passing through census tracts, which was more prominent for NO2.


2017 ◽  
Vol 38 (29) ◽  
pp. 2290-2296 ◽  
Author(s):  
Yutong Cai ◽  
Anna L. Hansell ◽  
Marta Blangiardo ◽  
Paul R. Burton ◽  
Kees de Hoogh ◽  
...  

2018 ◽  
Vol 24 (1) ◽  
Author(s):  
V. S. CHAUHAN ◽  
BHANUMATI SINGH ◽  
SHREE GANESH ◽  
JAMSHED ZAIDI

Studies on air pollution in large cities of India showed that ambient air pollution concentrations are at such levels where serious health effects are possible. This paper presents overview on the status of air quality index (AQI) of Jhansi city by using multivariate statistical techniques. This base line data can help governmental and non-governmental organizations for the management of air pollution.


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