Estimation of atmospheric trace metal emissions in Vilnius City, Lithuania, using vertical concentration gradient and road tunnel measurement data

Valiulis, D.; Čeburnis, Darius; Šakalys, J.; Kviȩtkus, K.

doi:10.1016/s1352-2310(02)00764-1

Cited by 38 publications

(19 citation statements)

References 13 publications

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“…During the past decade, a number of studies on atmospheric deposition trends of heavy metals in different areas were published [16][17][18][19][20][21]. Pb levels were reduced by about 25% during the period 1982-1995, and a slight decreasing trend was found for Co and Hg during the same period.…”

Section: Introductionmentioning

confidence: 99%

Trends of atmospheric heavy metal deposition in Lithuania

Kviȩtkus¹,

Šakalys²,

Valiulis³

2011

Lith. J. Phys.

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The results of long-term measurements of heavy metal (Pb, Zn, Cr, Ni, Cu, Mn, Cd, Fe, As, Hg) Different deposited amounts of heavy metals are related to higher concentration of heavy metals in the air and higher amounts of precipitation in the western part of lithuania. A decreasing trend of Pb concentration in precipitation and an increasing trend for Cr, Ni and Cu in precipitation and deposited amounts were observed at both stations. Common correlating groups of element concentrations for both stations were established: As-Cd, Ni-Cr-Cu, and Mn-Cu. These groups are probably typical of the entire territory of lithuania and are caused by long-range transfer of air masses.

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Section: Introductionmentioning

confidence: 99%

Trends of atmospheric heavy metal deposition in Lithuania

Kviȩtkus¹,

Šakalys²,

Valiulis³

2011

Lith. J. Phys.

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“…In Table 6, the estimated EFs (g/km-veh) for CO and TNMCH based on the LLT data tend to be higher in comparison 82 5928 88-96 0.00% 144AE22 2217 The Fort McHenry Tunnel 90 26665 60-85 3.30% 230AE20 2199 À1.80% 147AE6 2211 The Gelizinis Vilkas Tunnel (Valiulis et al, 2002) 90 1800 3.04AE0.30 0.24AE0.16 0.18AE0.04 Fort McHenry Tunnel 3.95AE0.34 0.50AE0.06 0.39AE0.06 Taipei Tunnel (Hwa et al, 2002) 3.64AE0.26 0.9AE0.18 0.44AE0.06 Chung-Cheng Tunnel (Hsu et al, 2001) 6.25 1.02 1.51 Gubrist Tunnel (John et al, 1999) 4.18AE0.38 1.05AE0.09 0.46AE0.04 48 3.9 2.9 Fort McHenry Tunnel 56 4.9 7.8 Callahan Tunnel 45 9.2 4.5 Deck Park Tunnel (Gertler et al, 1997;Sagebiel et al, 1996) 45 8.4 6.1 Sepulveda Tunnel (Gertler et al, 1997;Sagebiel et al, 1996) 56 7.3 5.3 Lincoln Tunnel (Gertler et al, 1997) 39 10 5.2 Caldecott Tunnel (Ban-Weiss et al, 2008) 18 0.027 with other studies (except for the Chung-Cheng tunnel located in Taiwan), while NOx is between two and ten times lower. In the same way, Table 7 indicates that the LLT EFs (g/L) for CO and TNMHC are between two and four times higher, while the LLT NOx EF is comparable or up to half the value of other tunnel studies.…”

Section: Ef Comparisonmentioning

confidence: 98%

“…These two points, named "inlet" and "outlet," served as the limits of the control volume over which the mass balances were performed to estimate the corresponding mobile emissions. The distance between sampling points and between the "inlet" sampling point and the actual entrance to the tunnel ( Figure 2) were determined based on similar tunnel studies performed elsewhere (Valiulis et al, 2002;Cheng et al, 2010). Each sampling location was equipped with a Testo 435 device, which registered 1-min averages of CO 2 levels, temperature, relative humidity, and absolute pressure.…”

Section: Experimental Sitementioning

confidence: 99%

A tunnel study to estimate emission factors from mobile sources in Monterrey, Mexico

Mancilla

Araizaga

Mendoza

2012

Journal of the Air & Waste Management Association

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A six-day tunnel field study was conducted in the city of Monterrey, Mexico, during June 2009 to derive on-road emission factors (EFs) for trace gases and fine particulate matter from the local vehicle fleet. The Loma Larga Tunnel (LLT) is a 532-m-long structure that is mainly used by light-duty gasoline-powered vehicles. It is composed of two independent bores that have a semicircular cross section, 17 m in diameter with a 3.5% slope. During the study, a fleet of 108,569 vehicles with average speeds that ranged from 43 to 76 km/hr was sampled. Ambient air samples were taken inside each bore using 6-L SUMMA-polished canisters and low-volume samplers for the quantification of total nonmethane hydrocarbons (TNMHC) and PM 2.5 , respectively. The effect of road dust resuspension was considered in the computation of PM 2.5 EFs. Additional equipment was used to measure real-time levels of CO 2 and NOx; CO EFs were estimated using NOx as a surrogate. TNMHC samples and NOx levels were obtained for 2-hr time periods, while PM 2.5 samples and CO 2 levels were obtained using 2.5-hr time periods, which included the time periods of the TNMHC and NOx measurements. Estimated EFs for TNMHC, CO, NOx, and PM 2.5 were 1.16 AE 0.05, 4.83 AE 2.9, and 0.11 AE 0.07 g/km-veh (2-hr average) and 17.5 AE 5.7 mg/veh-km (2.5-hr average), respectively, while CO 2 EFs were 182.7 AE 44 g/km-veh for the 2-hr time periods and 170 AE 22 g/veh-km for the 2.5-hr time periods. The average fuel economy estimated from the field data was 12.3 AE 2.3 km/L. The CO 2 and TNMHC EFs (on a mass per distance basis) tended to be higher for traffic moving upslope, while the inverse occurred for the PM 2.5 EFs. In comparison to other tunnel studies, the CO 2 EFs obtained were similar, the NOx and PM 2.5 EFs were lower, and the CO and TNMHC EFs were higher.Implications: Mobile source emission factors (EFs) for Mexican cities other than Mexico City are scarce. In Monterrey, Mexico, one of the three major cities in the country, emissions inventories are constructed based on EFs from other locations. However, it is quite relevant to obtain local information to construct reliable inventories. We present what is, to our knowledge, the first tunnel study conducted in a Mexican city other than Mexico City to estimate fleet-average mobile source EFs. This is also the first study that reports PM 2.5 EFs derived from a tunnel study in the country.

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“…The sampling site representing Vilnius city was chosen in our previous investigations [10]. Daytime samples were collected between 8:00 a.m. and 9:00 p.m. and night-time samples between 10:00 p.m. and 7:00 a.m. One hour after the sampling period was set for the sample change.…”

Section: Samplingmentioning

confidence: 99%

Heavy metal penetration into the human respiratory tract in Vilnius

Valiulis¹

2008

Lithuanian J. Phys.

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The peculiarities of the aerosol particle deposition in the human respiratory tract depending on the particle size and the breathing rate have been analysed. The highest deposition efficiency (0.85) was determined for the largest particles (10-20 µm) and the lowest efficiency (0.28) for the finer particles (0.3 µm). The heavy metal amount penetrating into the human respiratory tract at a different breathing rate in Vilnius has been evaluated. It has been determined that the deposition efficiency of heavy metals in the human respiratory tract changes insignificantly with the increase in the breathing rate, and when the breathing rate increases threefold (from 10 to 30 L min −1 ) the efficiency decreases only by about 10%. On the average, about 60% of heavy metals in the inhaled air penetrate into the respiratory tract. The comparison of Pb, V, and Zn concentrations in Vilnius city with those at the Preila background station has shown that they differ up to two times. It means that the contribution to the pollution with these metals in Vilnius city is insubstantial, and there is no considerable threat to human health.

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Estimation of atmospheric trace metal emissions in Vilnius City, Lithuania, using vertical concentration gradient and road tunnel measurement data

Cited by 38 publications

References 13 publications

Trends of atmospheric heavy metal deposition in Lithuania

Trends of atmospheric heavy metal deposition in Lithuania

A tunnel study to estimate emission factors from mobile sources in Monterrey, Mexico

Heavy metal penetration into the human respiratory tract in Vilnius

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