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Estimation of Primary NO2/NOx Emission Ratio from Road Vehicles Using Ambient Monitoring Data Yasuyuki Itano*1, Makiko Yamagami2, Toshimasa Ohara3 Osaka City Institute of Public Health and Environmental Sciences 8-34 Tojo-cho, Tennoji-ku, Osaka 543-0026, Japan 2Nagoya City Institute for Environmental Sciences, 5-16-8 Toyoda, Minami-ku, Nagoya, Aichi 457-0841, Japan 3National Institute for Environmental Studies, 16-1 Onogawa, Tsukuba, Ibaraki 305-8506, Japan 1
*1
y-itano@city.osaka.lg.jp
Abstract We developed a new method to estimate the primary emission ratio of nitrogen dioxide (NO2) to total oxides of nitrogen (NOx: NO + NO2) from road vehicles. A pair of simultaneous monitoring data for NO2, NOx, and O3 concentrations at two neighboring roadside sites was used for estimation. The primary NO2/NOx emission ratio was estimated by adjusting the α value so that Ox′ ([Ox′] = [O3] + [NO2] – α × [NOx]) concentrations at the two sites would show the best consistency. The present method does not need to select a suitable background site, as is necessary in some previous methods. Furthermore, the present method seemed to estimate the ratio with a smaller error range than preceding works. The monthly estimated primary NO2/NOx emission ratio for Osaka City, Japan from May 2006–April 2007 ranged 0.10–0.15. These values showed good agreement with those estimated from different datasets from another pairs of monitoring sites in Osaka City. An increasing trend of the ratio was observed in Osaka City for 2003–2010. Keywords Automobile Exhaust; Oxidant; Ptential Ozone; Urban Air Pollution; Vehicular Emissions
Introduction It is well recognized that atmospheric nitrogen dioxide (NO2) adversely affects human health. Furthermore, it plays a key role in photochemical air pollution, especially as the direct precursor of tropospheric ozone (O3). The World Health Organization (2006) has set a guideline value for atmospheric NO2 (40 μg/m3 for annual mean, 200 μg/m3 for 1-hour mean) for worldwide use. However, NO2 concentrations remain at high levels in large cities of the world (Baldasano et al., 2003). In Japan, air pollution from NO2 is a crucial concern,
especially at sites that are strongly affected by vehicular exhaust. In 1992, the Law Concerning Special Measure for Total Emission Reduction of Nitrogen Oxides from Automobiles in Specific Areas was issued, under which the use of some older vehicles in specific areas has been prohibited, and introduction of low-emission vehicles has been promoted. Consequently, average NO2 concentrations have recently shown a decreasing trend. However, the rate of the reduction is slower than that observed in total oxides of nitrogen (NOx: NO + NO2) concentration (Itano et al., 2007). Carslaw and Beevers (2005) showed similar trend in London, UK, where NO2 concentrations showed no clear trend during 1997–2003 though NOx was reduced significantly, and pointed out the increase in the primary NO2/NOx emission ratio from vehicles as the possible factor. To settle NO2 pollution problems in urban roadside environments, the primary NO2/NOx emission from vehicles is an important issue (Carslaw and Beevers, 2004a). Preceding works demonstrated that the primary NO2/NOx emission ratio varies among different engine types, exhaust treatment systems, cruising speeds, and accelerations (Lennerm et al., 1983; Soltic and Weilenmann, 2003; Alvarez et al., 2008; Kobayashi et al., 2008). The primary NO2/NOx emission ratios from the vehicular fleet under actual driving conditions were estimated from the proportion of increment in oxidant (Ox, [Ox] = [O3] + [NO2]) concentrations versus to that in NOx concentrations at a roadside site (Kimura and Shiihashi, 1988; Clapp and Jenkin, 2001; Minoura and Ito, 2010). Itano et al. (2007) roughly estimated the ratio by plotting hourly NO2/NOx ratios versus NOx concentrations at a roadside, which converged at
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about 0.1 at the higher NOx. These methods have the advantage of being able to estimate the ratio from monitoring data at a single site of consideration. Nevertheless, their estimates might be affected by variations in the background air quality (Carslaw and Beevers, 2004b). Kimura (1978), Kimura and Aikawa (1991), and Carslaw and Beevers (2004b) attempted to eliminate effects of the variation in background air quality using monitoring data at a roadside and a neighboring background site. They estimated the primary NO2/NOx emission ratio from the slope of the increment of Ox versus that of NOx at the roadside site above their background levels. Carslaw and Beevers (2005) proposed a method to estimate the ratio from the combination of roadside monitoring data, the background, and a simple chemical reaction model. This method is applicable for a site where O3 data is not available: they sought a pair of the ratio and the NO-O3 reaction time that yields the best agreement of the monitored and model-derived NO2 concentrations for the roadside site. These methods will be free from variation in background air quality if the background site is selected appropriately. However, it is sometimes difficult to find an appropriate background site for a roadside site within a permissible distance. Recent advances in vehicular exhaust treatment can alter the primary NO2/NOx emission ratios. For example, ratios from diesel-powered vehicles equipped with diesel particle filters (DPF) are significantly higher than those from older vehicles without DPF (Kobayashi et al., 2008). Therefore, estimating the primary NO2/NOx emission ratios from real-world vehicles and investigating long-term changes of the ratio are important issues to improve urban NO2 air quality. As described herein, a new method was proposed to estimate the primary NO2/NOx emission ratios more accurately and simply. A case study was presented to show the practical procedure for the estimation. Method Theory In a roadside atmosphere, NO emitted from road vehicles is subjected to reactions with background O3 and with peroxy radicals (ROO) to form NO2. In addition to the NO–O3 and NO–ROO reactions, directly emitted NO2 and background NO2 contribute to NO2 concentrations in the roadside air. Involving a
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series of complicated reactions with a wide variety of hydrocarbon species, contributions from the NO–ROO reactions are generally smaller than those from the NO–O3 reactions with respect to NO2 production. Therefore, if two neighboring monitoring sites in a roadside are considered, then the contribution of NO– ROO reaction to the NO2 concentration differs little between the two sites. Furthermore, because the background air quality for the neighboring two sites can be equal, the difference in the direct NO2 between the two sites is the sole factor determining the difference in Ox concentrations. Defining Ox′ as [Ox′] ≡ [Ox] – [NO2]d , = [O3] + [NO2] – α × [NOx], (1) where [NO2]d denotes the fraction of NO2 concentration from the direct NO2, and α as the variable representing the primary NO2/NOx emission ratio, then Ox′ concentrations at the two sites can be expected to be mutually consistent. Note that Ox′ is the background Ox concentration to which direct NO2 is to be added at each site. Consequently, one can estimate the most probable primary NO2/NOx emission ratio by adjusting the α value so that the Ox′ concentrations between two neighboring sites show the best consistency. Practical Estimation of Primary NO2/NOx Emission Ratio For practical estimation of the primary NO2/NOx emission ratio, scatter plots of hourly Ox′ concentrations between two selected sites for certain time periods were made while varying the α value in equation 1. The coefficient of determination (R2 value) for least-squares fitting forced through the origin was calculated for each α. The most probable primary NO2/NOx emission ratio was determined from the thus obtained α–R2 relation so that the α value would yield the highest R2. The method was tested with the routine monitoring data from May 1, 2006 – April 30, 2007 in Osaka City, the largest city in western Japan. Three monitoring sites (Site A, B, and C) were considered for the evaluation. As shown in Fig. 1, Site A, Site B, and Site C were located in the area covered by dense roadway network between Tamatsukuri Ave. and Imazato Ave. Site A was near a junction of five streets with heavy traffic. The average concentration of NOx at Site A was 85 parts per billion by volume (ppbv). Site B was on the rooftop of a five-storey building standing about 1.5 km north of Site A. Site C was on the rooftop of a three-storey junior high school building at about 1.8
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E
D B
A
C
FIG. 1 ROAD NETWORK IN OSAKA CITY AND SITE LOCATION
km southwest of Site A. The hourly concentrations of NOx and O3 were monitored by commercially available automated monitor (the chemiluminescensedetection with cataritic converter for NOx, and the UV absorption for O3). We also tried to assess the long-term trend of the primary NO2/NOx emission ratio. For this purpose, a pair of monitoring sites that located within an acceptable distanse, and long-term data for NOx and O3 are available. Sites D and Site E in Fig. 1 were separated by about 2.8 km. The both sites were near a national road R43, a trunk road connecting Osaka and Kobe. Although both NOx and O3 have been monitored since the 1960s at these sites, early monitoring had been based on wet methods involving the Saltzman method and the neutral KI method for NOx and O3, respectively. We excluded such data for their lower accuracy, and we focused on the data for fiscal 2003–2010, when NOx and O3 were monitored using chemiluminescence-based and the UV absorption-based instruments at both sites. The monitoring data for O3 in May and July in 2004 was lacking at Site D because of an instrumental problem; they were excluded from this study.
spatiotemporal resolution of this test run, we regarded this result as the averaged value over the time, space, vehicular types, and the driving conditions. Figure 3 shows scatter plots of Ox′ between Site A and Site B in January for the cases of α = 0.00, 0.12, and 0.25. With α = 0.00 the distribution of Ox′ tended to incline toward Site A. In contrast, Ox′ tended to incline toward Site B with α = 0.25; some data showed negative values as depicted in Fig. 3. Such a tendency was improved and the dispersion was minimized with α = 0.12, the best estimate for the primary NO2/NOx ratio. These results suggest that Ox′ showed good consistency between the two sites over widely varying Ox′ concentrations, irrespective of their NOx concentrations, when the most probable primary NO2/NOx emission ratio was applied for the α value in equation 1. Table 1 lists the monthly estimated primary NO2/NOx emission ratios and related statistic data from Site A and Site B, and Site A and Site C for comparison. The results consisted within ±0.01 for the most cases with high R2 value (> 0.99). The accuracy of the estimation seems dependent on the curvature of the α–R2 plots. In Fig. 2 the large curvatures appeared on July, November, December, January, and Feburary. Contrasting with Table 1, such months with large curverture can be characterized by high NOx concentrations. This result was related to the fact that the variation of Ox′ concentration per unit α is larger under higher NOx conditions according to eq. 1. For this reason, the current method seemed favorable to use under high NOx conditions. Figure 4 presents a comparison of the α–R2 relation in high NOx season (November–January) obtained from Site A and Site B with that from Site A and Site C. Both cases resembled each other in the α–R2 variation, and the primary NO2/NOx emission ratios were successfully estimated as 0.12 for the both cases. 1.00 May Jun 0.99 Jul
Results and Discussion 2
Sep
R
Estimation of Primary NO2/NOx Emission Ratio in Osaka City
Aug 0.98
Oct 0.97 Nov Dec
The variations of R2 values along with the α values obtained from Site A and Site B on monthly bases are presented in Fig. 2. The variation of R2 showed a single maximum in all months. For example, the R2 value showed its maximum (0.997) at α = 0.12 in January. Thereby, the most probable primary NO2/NOx ratio was estimated as 0.12 for the month. Becouse of the
0.96 Jan Feb 0.95 Mar Apr 0.94 0.00
0.10
α
0.20
FIG. 2 VARIATION OF R2 VALUE ALONG WITH α OBTAINED FROM SITE A AND SITE B
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1.00
100
α =0.00, R 2=0.989 α =0.12, R 2=0.997 α =0.25, R 2=0.957
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Ox' at site B (ppbv)
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60
R
2
0.98 40
0.97 20
0.96 0
Site_A vs. Site_B Site_A vs Site_C
0.95 0.00
-20 -20
0
20
40
60
80
100
0.10
0.20
0.30
α
Ox' at site A (ppbv) α–R2
FIG. 4 COMPARISON OF PLOTS IN HIGH NOx SEASON BETWEEN TWO DIFFERENT PAIRS OF SITES
FIG. 3 INTER-SITE CORRELATION OF OX′ AT SITE A AND SITE B IN JANUARY CALCULATED WITH DIFFERENT α VALUE
TABLE 1 ESTIMATED PRIMARY NO2/NOX EMISSION RATIO AND STATISTICAL DATA
Month
06_May Jun Jul Aug Sep Oct Nov Dec 07_Jan Feb Mar Apr a b
Site A vs B
Site A vs C
Concentrations at Site Aa
Concentrations at Site Ba
Concentrations at Site Ca
α
R2
α
R2
NOx
NO2
O3
Ox′b
NOx
NO2
O3
Ox′b
NOx
NO2
O3
Ox′b
0.14 0.12 0.14 0.11 0.13 0.13 0.12 0.12 0.12 0.11 0.11 0.13
0.996 0.994 0.993 0.990 0.996 0.997 0.997 0.997 0.997 0.997 0.995 0.997
0.15 0.11 0.13 0.12 0.13 0.12 0.13 0.12 0.12 0.11 0.10 0.11
0.995 0.995 0.993 0.991 0.995 0.997 0.995 0.995 0.994 0.997 0.995 0.998
69.5 87.1 95.8 69.7 57.2 69.5 95.1 105.8 99.5 85.2 88.1 76.2
38.9 46.9 38.5 36.0 30.5 36.7 40.2 38.8 39.5 41.6 42.6 42.6
22.8 18.3 6.5 14.1 15.7 13.1 7.3 5.5 8.1 11.7 14.1 21.0
52.3 54.1 32.7 41.0 38.6 40.5 35.1 30.6 34.7 41.6 45.3 53.9
30.2 34.0 34.3 25.1 25.2 33.9 47.8 59.8 51.2 48.9 45.0 32.0
26.0 29.7 25.1 21.5 21.7 28.4 32.4 33.0 31.5 32.8 32.0 27.1
34.1 37.0 16.7 31.8 28.2 24.4 15.3 11.1 15.0 20.2 25.1 36.2
56.2 61.7 37.9 50.0 46.6 48.0 41.4 36.3 39.8 46.8 50.9 59.1
28.5 34.4 33.7 24.1 21.2 28.0 43.2 56.8 49.4 46.2 43.1 30.8
23.9 29.0 24.4 19.9 17.4 22.8 28.2 30.5 29.7 30.6 30.0 25.7
36.8 39.0 18.4 33.1 33.5 29.7 19.0 13.8 17.6 21.1 29.9 40.6
51.3 63.8 38.9 50.0 47.5 49.4 41.5 37.4 41.3 46.8 55.2 63.0
Average pollutant concentrations with unit in ppbv. Ox' ([Ox'] = [O3] + [NO2] - α × [NOx]) calculated with α being the estimated primary NO2/NOx emission ratio.
Comparison with Previously Reported Methods Kimura (1978) presented a method to estimate the primary NO2/NOx emission ratio using the monitoring data of NO2, NOx, and O3 at a roadside and a background site, from the slope of the scatter plot of the increment in Ox concentration at the roadside site above the background site (ΔOx) versus that in NOx (ΔNOx). This method is based on the assumption that the NOx and Ox concentrations at the roadside site were always higher than or equal to those at the background site. Furthermore, the appropriate selection of the background site sometimes seems difficult; the background air quality for an urban site changes depending on the wind direction. Under the current method, based on direct comparison of Ox′ concentrations between two
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neighboring sites, is free from such a precondition. Furthermore, the current method has an advantage related to error propagation: the maximum errors in ΔOx and ΔNOx can be expressed as δ[ΔOx] = δ[O3]R + δ[NO2]R + δ[O3]B + δ[NO2]B, (2) δ[ΔNOx] = δ[NOx]R + δ[NOx]B,
(3)
where δ[M] represents the errors for the estimation of component M, with subscripts R and B denoting roadside and background sites. The range of error accompanied by a data point of the ΔOx–ΔNOx scatter plot differs between x- and y-axes. In contrast, the current method is based on the scatter plot of a single component (Ox′) between the two sites, for which the error is expressed as δ[Ox′] = δ[O3] + δ[NO2] + α × δ[NOx].
(4)
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Carslaw and Beevers (2005) proposed another method to estimate the primary NO2/NOx emission ratio using simultaneous monitoring data from a roadside and from the background sites. They predicted the NO2 concentrations at the roadside site from concentrations of O3 and NO2 at the background site and NOx at the roadside site using a simple chemical reaction model, with the primary NO2/NOx emission ratio and NO–O3 reaction time (τ) as parameters. They optimized the combination of the ratio and τ that yields the best agreement of the measured and model-derived NO2 concentrations. The current method requires no model simulation nor does it consider the NO–O3 reaction time because it is based simply on a direct comparison of Ox′ concentrations between two sites. Besides, number of parameters was minimized in the current method. Consequently, the current method provides a more precise estimation of the primary NO2/NOx emission ratio through a simpler manner than the preceding works. Potential Factors Affecting the Accuracy of the Estimation As discussed in the previous section, the current method is applicable for two neighboring sites with high NOx levels. The required NOx levels might vary depending on the level and variation of the background O3. However, even though the levels of NOx were sufficiently high, the α–R2 relation would not show a maximum if both the levels and variations of NOx at the two sites were similar. Actually, we could not determine the primary NO2/NOx emission ratio from Site B and Site C because their levels and variations of NOx were very similar. Therefore, it is necessary to select the two sites so that the levels and/or variations of NOx mutually differ from application of this method. Because the monitoring data of NO2, NOx, and O3 at two certain neighboring sites are the only input, their accuracy and precision directly affect the accuracy of the estimation. For example, the interferences of nitrogen-containing compounds other than NO2 on
commercial NOx instruments (Arthur et al., 1974) can cause the overestimation of the ratio. Using data of ideal accuracy and precision, the average concentrations of Ox′ for a certain period would be consistent between the two sites. However, the correlation of Ox′, with α being the best estimate, between Site A and Site C differed slightly from the one-to-one relation depicted in Fig. 3. In detail, the Ox′ concentrations were consistently higher at Site B, where O3 concentrations were higher, in all months in Table 1. We suspected the poor comparability among NO2, NOx, and O3 measurements to be one of the major factors explaining the inconsistency in Ox′: all NO2, NOx, and O3 should have been calibrated using the same scale for more accurate estimation because they behave as a single pollutant (Ox′) in the current method. The gas-phase titration technique (Rehme, 1976) is expected to provide the better calibration for this purpose. Recent Trend of Primary NO2/NOx Emission Ratio The current method was applied for the dataset from Site D and Site E to assess the recent trends of primary NO2/NOx emission ratio in Osaka during 2003–2010. The year-by-year change of the ratio estimated from their data in high NOx season (November–January) was presented in Fig. 5. The error bars represent the highest and the lowest value of the monthly estimation. Although the result was a preliminary one, an increasing trend after 2006 was observed in Fig. 5. Carslaw (2005) found an increasing trend in the ratio in London, and pointed out the diffusion of desel particulate filter (DPF) as a possible factor. Grice (2009) also estimated the increasing trend of the primary NO2/NOx emission ratio in Europe, possibly 0.20
Estimated NO 2/NOx emission ratio
Considering that generally reported primary NO2/NOx emission ratios are around 0.1 (e.g., Soltic and Weilenmann, 2003), then δ[Ox′] would be about one-half the value of δ[ΔOx] derived using eq. 2. Consequently, based on data plots with smaller error ranges, the current method potentially estimates the ratio more precisely than Kimura (1978).
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0.15
0.10
0.05
0.00 2003
2004
2005
2006
2007
2008
2009
2010
Fiscal year
FIG. 5 ESTIMATED YEAR-BY-YEAR VARIATION OF PRIMARY NO2/NOx EMISSION RATIO IN OSAKA CITY
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because of the treatment of desel exhaust gas. As presented in Chapter 1, the Law Concerning Special Measure for Total Emission Reduction of Nitrogen Oxides from Automobiles in Specific Areas was issued in 1992 in Japan. The law was amended to include regulation of particulate matter emissions in 2003. Consequently, installation of DPF, which can increase the primary NO2/NOx emission ratios (Kobayashi et al., 2008), into diesel-powered vehicles has been promoted in areas surrounding Osaka. These background conditions might raise the ratio in Osaka. Summary and Conclusions A new method to estimate the primary NO2/NOx emission ratio from ambient monitoring data of NO2, NOx, and O3 was proposed. This method is based on a search for the α value that yields the best consistency of Ox′ ([Ox′] = [O3] + [NO2] – α × [NOx]) between two neighboring sites. The present method does not require a suitable background site as is needed in some preceding works. The proposed method also estimates the primary NO2/NOx emission ratio with smaller error ranges than the preceding works. The monthly estimated primary NO2/NOx emission ratio for Osaka City from May 2006–April 2007 was 0.10–0.15, and the ratio showed an increasing trend for the period 2003–2010. The present method is based on the following assumptions. 1. The two sites have the same background air quality, 2. The two sites are affected by emission from similar masses of vehicles with a certain primary NO2/NOx emission ratio, and effects from other sources than the vehicular emission are small, 3. The difference in ROO-NO reaction between the two sites is negligible. Although the effect of the third item is uncertain, one can minimize the effect by selecting data in photochemically inactive conditions (i.e. winter or nighttime). In applying the method, one should consider the following to select the monitoring sites. 4. The NOx concentrations of at least one of the two sites should be sufficiently high, 5. The level and/or variation in NOx should differ between the two sites.
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One can select the two sites, for example of an ideal case to meet the above conditions, at the both sides of a trunk road facing each other. Finally, for more accurate estimation of the ratio, the following is important. 6. The accuracy and precision directly affect the accuracy of the estimation. The interference of nitrogen-containing compounds on commercially available NOx instrument is one of the major concerns. 7. Both NOx and O3 monitors should be well calibrated with the same scale. The present method seems to be able to estimate the primary NO2/NOx emission ratio with higher temporal and spatial resolution, if well-controlled monitoring that meets the above points is conducted. ACKNOWLEDGMENT
This study was conducted under the joint research project between National Institute for Environmental Studies (NIES) and environmental research in stitutions in local governments, “Study on characteristics of photochemical oxidants and particulate matter”. This work was also supported by JSPS KAKENHI Grant Number 23241008. We thank Ms. Naoko Take at Asian Center for Air Pollution Research for her useful discussions and comments. REFERENCES
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Yasuyuki Itano was born in Okayama City in Japan in 1973. He graduated from Graduate School of Engineering, Osaka Prefecture University and received his Doctor of Engineering there in 2005. He is working for Osaka City Institute of Public Health and Environmental Sciences, Osaka, Japan since 1998, is now a Senior Researcher. Dr. Itano received Paper Awards from Japan Society of Atmospheric Environment for his research on PM2.5 and photochemical air pollution. Makiko Yamagami graduated from Graduate School of Pharmaceutical Sciences, Nagoya City University, Japan in 1992. She is working for Nagoya City Institute for Environmental Sciences as a Senior Researcher. Her current work is on urban air pollution, especially particulate matter. She recieved Paper Awards and the Best Poster Award from Japan Society of Atmospheric Environment. Toshimasa Ohara graduated from Graduate School of Engineering, Hokkaido University, Japan in 1982, and received his Doctor of Engineering. His research area is multi-scale air pollution simulation, emission inventories, and their application. Dr. Ohara is the Director of Center for Regional Environment Research, Natinal Institute for Environmental Studies, Japan. He also posted at Professor in Tsukuba University, Japan.
Lennerm, M., Lindqvist, O., Rosén, Å., 1983. The NO2/NOx
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