Evaluation Of Ambient Air Pollution Impact On Carrot Plants At A Sub Urban Site Using Open Top Chambers

2006 ◽  
Vol 119 (1-3) ◽  
pp. 15-30 ◽  
Author(s):  
S. Tiwari ◽  
M. Agrawal ◽  
F. M. Marshall
2021 ◽  
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>


2006 ◽  
Vol 122 (4) ◽  
pp. 689-697 ◽  
Author(s):  
G. SCHENONE ◽  
G. BOTTESCHI ◽  
I. FUMAGALLI ◽  
F. MONTINARO

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.


Hypertension ◽  
2019 ◽  
Vol 74 (2) ◽  
pp. 384-390 ◽  
Author(s):  
Carrie J. Nobles ◽  
Andrew Williams ◽  
Marion Ouidir ◽  
Seth Sherman ◽  
Pauline Mendola

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