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Seasonal variations in the NO2 artifact from chemiluminescence measurements with a molybdenum converter at a suburban site in Korea (downwind of the Asian continental outflow) during 2015–2016
Atmospheric Environment 165 (2017) 290e300
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Atmospheric Environment journal homepage: www.elsevier.com/locate/atmosenv
Seasonal variations in the NO2 artifact from chemiluminescence measurements with a molybdenum converter at a suburban site in Korea (downwind of the Asian continental outflow) during 2015e2016 Jinsang Jung*, JaeYong Lee, ByungMoon Kim, SangHyub Oh Center for Gas Analysis, Korea Research Institute of Standards and Science, Daejeon 305-340, Republic of Korea
h i g h l i g h t s The conversion efficiency of the BLC2 photolytic converter reached ~95% at ambient NO2 levels (<100 ppbv). Molybdenum converter overestimated NO2 levels by 20.4 ± 14.7% compared to the actual NO2 level. NO2 artifact correlated well with the PM2.5 mass concentration during the fall and winter seasons.
a r t i c l e i n f o
a b s t r a c t
Article history: Received 15 February 2017 Received in revised form 28 June 2017 Accepted 4 July 2017 Available online 5 July 2017
This paper investigates the NO2 artifact associated with the chemiluminescence measurement technique that uses a molybdenum converter by applying the same technique but with a photolytic converter at a site downwind of the Asian continental outflow (Daejeon, Korea). The NO2 to NO conversion efficiencies of the molybdenum and photolytic converters were found to be 100% and 95%, respectively, at an ambient level of NO2 (<100 ppbv). Two NO2 monitors equipped with molybdenum and photolytic converters were deployed for ambient NO2 measurements in Daejeon, Korea between the fall of 2015 and the summer of 2016. It was found that the monitor equipped with the molybdenum converter overestimated NO2 levels by 20.4 ± 14.7% when compared with the actual NO2 level in the Daejeon atmosphere over the entire measurement period. This NO2 artifact (DNO2), defined as the difference between molybdenum NO2 and photolytic NO2 values, correlated well with the PM2.5 mass concentration during the fall and winter seasons. Based on these findings, this study develops a simple correction model for DNO2 using the PM2.5 mass concentration during the fall and winter seasons. The model-corrected NO2 concentration correlated well with the actual NO2 values with a slope of approximately 1.0 and R2 value of 0.98 during the fall and winter seasons. © 2017 Elsevier Ltd. All rights reserved.
Keywords: Chemiluminescence NO2 artifact Molybdenum converter Photolytic converter
1. Introduction Nitric oxide (NO) is an important trace gas in the troposphere and is emitted primarily from high-temperature combustion sources such as vehicles and power plants (Seinfeld and Pandis, 1998). Nitrogen dioxide (NO2) forms mainly via oxidative reaction in the atmosphere. NO2 plays an important role in atmospheric chemical processes by participating in O3 and secondary aerosol
* Corresponding author. E-mail address: [email protected] (J. Jung). http://dx.doi.org/10.1016/j.atmosenv.2017.07.010 1352-2310/© 2017 Elsevier Ltd. All rights reserved.
formation (Seinfeld and Pandis, 1998). In addition, NO2 can absorb incoming solar radiation and thus reduce visibility (IMPROVE, 2006), and also affects human health by damaging the respiratory system (Pandey et al., 2005; Katsoulis et al., 2014). Due to the importance of NO2 to human health and the atmosphere, NO2 was designated as one of the Korean Environmental Agency's “criteria pollutants”. The Korean Environmental Agency regulates NO2 levels based on hourly averaged maxima of 100 ppbv, daily averaged maxima of 60 ppbv, and yearly averaged maxima of 30 ppbv. A gradual increase in the annual mean NO2 concentration was observed in Seoul, Korea from 1989 to 1999, but this was converted to a slight decreasing trend from 2000 to 2010 following the
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successful implementation of a scheme that replaced diesel buses with natural gas vehicles (Nguyen et al., 2015). However, the annual mean NO2 values in Seoul over the last decade still exceeded the Korean government's regulatory threshold (Nguyen et al., 2015). Long-term satellite observations of the spatial distribution of NO2 over China have revealed that there was a continuous rise in NO2 levels between 2005 and 2011. This was caused mainly by the increasing numbers of vehicles (there was a 155% increase between 2006 and 2012). However, this trend was reversed, and NO2 levels began to fall again between 2011 and 2014, possibly because of the implementation of effective central governmental policies aimed at reducing NO2 emissions (Zhang et al., 2017). Chemiluminescence equipment fitted with a molybdenum converter is the most widely used method for measuring surface NO2 concentration. In Korea, more than 300 national monitoring sites use this technique for continuous monitoring of NO2. The advantages of the chemiluminescence technique are that it is simple to operate, has good sensitivity, and is easy to calibrate. As only NO is quantified based on the chemiluminescent reaction of NO with O3, an NO2 to NO converter is required to obtain the NO2 levels. Thus, when using the chemiluminescence technique, NO2 levels are measured indirectly using the difference between the total NO value measured after passing through an NO2 to NO converter and the initial NO value measured directly (i.e., before passing through the converter). Typically, a molybdenum converter heated to 300e350 C is used for the conversion of NO2 to NO. Although molybdenum converters show good conversion efficiencies, the conversion is not specific to NO2. Besides NO2, it can also convert other oxidized nitrogen compounds such as nitric acid (HNO3), peroxyacetyl nitrate (PAN) like species (peroxyacylnitrates), and organic nitrates to NO (Winer et al., 1974; Grosjean and Harrison, 1985; Gehrig and Baumann, 1993). These results indicate that the last several decades of NO2 measurements made in Korea were overestimated when compared with the actual NO2 level in the atmosphere, and this error was caused mainly by the NO2 measurement artifact. Thus, the uncertainty associated with molybdenum NO2
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measurements needs to be quantified at the seasonal scale. Although the NO2 measurement artifact caused by molybdenum converters has been previously investigated in mainland China (e.g., Xu et al., 2013), there have been no studies of the NO2 measurement artifact downwind of the Asian continental outflow. There are many alternative NO2 monitoring techniques that are free from NO2 measurement artifacts. For example, the laser induced fluorescence (LIF), differential optical absorption spectroscopy (DOAS), cavity attenuation phase shift (CAPS), and tunable infrared laser differential absorption spectroscopy (TILDAS) techniques can measure NO2 directly in air. There have been several intercomparison studies between these optical techniques and the chemiluminescence NO2 measurement technique (Thornton et al., 2003; Nakamura et al., 2003; Osthoff et al., 2006; Dunlea et al., 2007; Villena et al., 2012). Even though these optical techniques are free from NO2 measurement artifacts when compared with the chemiluminescence technique, they are not suitable for long-term continuous monitoring of NO2 in the atmosphere. A photolytic NO2 to NO converter that can be applied to the chemiluminescence technique has been developed that selectively reduces NO2 to NO using ultra violet (UV) light and, thus, is almost free from interference (Parrish et al., 1990; Sadanaga et al., 2010). This chemiluminescence apparatus equipped with a photolytic converter is the suitable method for the online monitoring of NO2 at medium pollution level. The NO2 to NO conversion efficiency of the earlier versions of the photolytic converters that used metal halides and xenon arc lamps only reached 70% and they were not stable (Parrish et al., 1990; Ryerson et al., 2000; Steinbacher et al., 2007). Recently, UV light-emitting diodes (LED) have been used as a light source for the photolytic converter (Sadanaga et al., 2010). This UV LED technique increased the conversion efficiency of the photolytic converter up to 90% and also showed good stability for long-term use (Sadanaga et al., 2010). If we intend to replace the molybdenum converter with a photolytic converter across the Korean national monitoring network, it will be necessary to carry out a long-term intercomparison of the NO2 levels obtained from the two converters.
Fig. 1. Map showing the sampling site (Google Map and Google Earth imagery (© Google Inc.)). The sampling site is located at the Korea Research Institute of Standards and Science (36 230 1900 N, 127 220 2100 E) in Daejeon, Korea.
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The term NOz is defined as the difference between total reactive nitrogen (NOy) including NOx (sum of NO and NO2), HNO2, HNO3, PANs, etc and NOx. Suzuki et al. (2011) measured NO2 concentrations using the chemiluminescence apparatus equipped with a molybdenum converter and the LIF technique. They observed high NO2 artifacts in the molybdenum NO2 measurements when O3 concentrations were over 50 ppbv at an urban site in Tokyo, Japan. They also found that peroxy nitrate species made a significant contribution to the NO2 measurement artifacts generated by the molybdenum converter under high O3 conditions. Dunlea et al. (2007) found that HNO3 and alkyl and multifunctional alkyl nitrates mainly contributed to the NO2 measurement artifacts recorded in Mexico City. If we are to be able to compensate for the NO2 measurement artifacts caused by the molybdenum converter, it will be necessary to characterize the temporal and diurnal variations in the NO2 measurement artifacts. In addition, a simple correction model will be needed to correct NO2 values measured by molybdenum converters. In this study, we made continuous NO2 measurements using the chemiluminescence technique at a suburban site in Daejeon, Korea (downwind of the Asian continental outflow) between fall 2015
and summer 2016. The seasonal and diurnal variations of the NO2 measurement artifact associated with the molybdenum converter were evaluated against the NO2 data obtained using a photolytic converter. In addition, we evaluated the dependence of the NO2 measurement artifact on the levels of gaseous and particulate pollutants. Finally, we developed a simple correction model to compensate for the NO2 artifacts. 2. Experimental methods 2.1. Measurement site Ambient NO2 was measured at a suburban site (36 2301900 N, 127 220 2100 E) in Daejeon, Korea, during four seasons in 2015e2016: fall (25 September30 November 2015), winter (1 December 2015e31 January 2016), spring (24 March15 April 2016), and summer (23 June8 August 2016). Two NO2 monitors were installed inside a temperature-controlled container (25 ± 3 C) located at the Korea Research Institute of Standards and Science (KRISS) (Fig. 1). Ambient air was drawn from the rooftop of the container through a glass tube and supplied to the instruments via
Table 1 Measurement parameters and techniques used in this study. Parameter
Measurement method
Instrument
NO2 to NO converter
Converter temperature
Detection limit
NO, NO*2, NO*x NO, NO2, NOx
Chemiluminescence Chemiluminescence
Kentek, Mezus 210 Kentek, Mezus 210P
Molybdenum Photolytic
325 C e
0.4 ppbv 0.4 ppbv
Fig. 2. Scatter plots of the NO concentrations measured using NOx analyzer equipped with a photolytic converter versus that by a molybdenum converter during (a) fall, (b) winter, (c) spring, and (d) summer.
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a manifold. The NO2 concentration was measured at intervals of 1 min and we used the hourly average values in this study. Hourly O3 and PM2.5 mass concentrations were also obtained from the Korean National Observatory, which is approximately 1.8 km south of the measurement site (http://www.airkorea.or.kr/airkorea/eng/ index.jsp). Because the NO2 measurement site and the Korean National Observatory are located at suburban areas in Daejeon and there are no particular sources between the two sites, we assumed that differences of O3 and PM2.5 levels between the two sites are negligible. Unless stated otherwise, the times shown in this study are Korean local time (LT ¼ GMTþ9). 2.2. NO2 measurement NO, NO2, and NOx were measured using a chemiluminescence monitor equipped with NO2 to NO converters as shown in Table 1. Two NOx monitors, one equipped with a molybdenum converter (Kentek, model Mezus 210) and the other with a photolytic converter (Kentek, model Mezus 210P), were used to measure the ambient NO2 levels. In the molybdenum converter, NO2 is converted to NO on the heated (320 C) molybdenum surface. In the photolytic converter, NO2 is converted to NO using UV light centered at 395 nm. For this study, we used a commercial photolytic converter (AQD, model BLC2). The surface temperature of the photolytic converter was maintained as 45e50 C using Peltier cooling modules. Zero and span drifts were determined from the differences seen in the zero air and 400 ppbv NO standard gas measurements, respectively, over a period of 24 h. The zero and span drifts were less than 0.1 and 1.1 ppbv, respectively. Good
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linearity was obtained in the range of 0e400 ppbv with a slope of 1 and R2 value of 1.0. The detection limit of the NOx monitors, defined as 3 the standard deviation of the zero air measurement, was 0.4 ppbv with an uncertainty of 2%. As NO2 measured by the molybdenum converter was influenced by the NOz artifact, NO2 levels obtained using the molybdenum converter are denoted by NO*2 in this study, whereas those measured using the photolytic converter are denoted by NO2. 2.3. Quality assurance of the NOx monitors To calibrate the NOx monitors, a 100 ppm of NO in nitrogen standard gas mixture was prepared by KRISS. Zero air was generated using a zero air generator (API, model 701). This 100 ppm of NO standard gas mixture was then diluted to 400 ppbv using a gas calibrator (API, model 700E) and introduced to the NOx monitor. The flowrates of the gas calibrator was calibrated using a volumetric flow calibrator (MesaLabs, Definer 220). Zero air and span calibrations were performed every week. The NO2 to NO conversion efficiencies of the molybdenum and photolytic converters were evaluated using the NO2 standard gas prepared by KRISS. Because KRISS is the metrology institute in Korea, KRISS has international traceability on NO2 gas mixture with an uncertainty of less than 3% through an inter-comparison between international metrology institutes (Flores et al., 2012). First, 50 ppmv of the NO2 in nitrogen gas mixture was diluted to give levels between 50 and 400 ppbv using the gas calibrator. The conversion efficiencies of the converters were then determined from the ratio of the measured NO2 to the standard NO2 gas level.
Fig. 3. Scatter plots of the NO2 concentrations measured using the photolytic converter versus that using the molybdenum converter (NO*2) during (a) fall, (b) winter, (c) spring, and (d) summer.
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The conversion efficiency of the molybdenum converter was approximately 100% across the 50e400 ppbv NO2 range. However, the conversion efficiency of the photolytic converter varied with the NO2 concentration. In general, the conversion efficiency increased as the NO2 concentration decreased. The conversion efficiency of the photolytic converter reached approximately 95% when the NO2 concentration was lower than 100 ppbv. As the ambient NO2 level in an urban environment in Korea is generally lower than 100 ppbv, we used a constant conversion efficiency of 95% for the photolytic converter. The conversion efficiencies of the molybdenum and photolytic converters were confirmed using a gas-phase titration method (here NO standard gas mixture was used). The NO2 levels measured with the photolytic converter were corrected using the NO2 to NO conversion efficiency for use in this
study. 2.4. Interferences of the photolytic converter As already reported by Reed et al. (2016) and Villena et al. (2012), a photolytic converter is affected by negative or positive interferences. The negative interference can be caused by the formation of HO2/RO2 radicals inside the photolytic converter or by the back titration of NO with ambient O3 inside the photolytic converter. Villena et al. (2012) performed a smog chamber study to investigate the negative interference induced by the formation of HO2/RO2 radicals inside the photolytic converter. The negative interference of the photolytic converter was obtained as ~10% in a typical urban situation (Villena et al., 2012). Thus, the negative
Table 2 Summary of seasonal variations in NO2 measurements. Parameter
Unit
1 Year
Falla
Winterb
Springc
Summerd
NO*2
ppbv
NO2 DNO2e DNO2 fraction
%
14.6 ± 11.3 17.6 ± 12.5 2.9 ± 2.2 20.4 ± 14.7
15.8 ± 11.3 18.7 ± 12.7 2.9 ± 2.5 17.7 ± 13.2
19.9 ± 11.8 23.3 ± 13.1 3.4 ± 2.3 16.6 ± 10.4
12.6 ± 10.6 16.3 ± 10.8 3.7 ± 2.0 28.9 ± 18.8
7.3 ± 5.2 9.1 ± 5.3 1.9 ± 1.1 25.0 ± 16.1
a b c d e
Fall: 25 September30 November 2015. Winter: 1 December 2015e31 January 2016. Spring: 24 March15 April 2016. Summer: 23 June8 August 2016. DNO2: NO2*-NO2.
Fig. 4. The DNO2/NO*2 ratios as a function of NO*2 concentrations during (a) fall, (b) winter, (c) spring, and (d) summer. DNO2 is the difference between the NO*2 and NO2 concentrations.
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interference of the photolytic converter was assumed to be ~10% according to the field study by Villena et al. (2012). The manufacturer of AQD BLC2 photolytic converter provided the change in conversion efficiency of NO2 due to the back titration of NO with ambient O3 (AQD, 2015). The percent change of conversion efficiency of the photolytic converter is less than 1% when O3 concentration is lower than 100 ppbv with a 1 s residence time. Because the flowrate of the photolytic converter was maintained as ~0.7 L min1, residence time was calculated as ~1.5 s. Thus, decrease in conversion efficiency of the photolytic converter for 1.5 s residence time was determined to be less than 1.8% when O3 concentration is less than 100 ppbv. Thermal decomposition of PAN type species inside the photolytic converter can overestimate NO2 concentration (Reed et al., 2016). This effect is significant in pristine environments and at high elevation where NOx concentration is low (less than 1 ppbv). Because the measurement site in this study was located in a suburban area, it was expected that thermal decomposition of PAN type species inside the photolytic converter might be less significant for the NO2 measurement compared to pristine environment. The model simulation showed that the monthly maximum positive interference of NO2 by the photolytic converter estimated to be 1e5% over the Korean Peninsula (Reed et al., 2016). From the negative and positive interferences discussed above, the measurement uncertainty of NO2 by the photolytic converter was determined to be less than 11.5%.
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3. Results and discussion 3.1. Intercomparison of two NOx analyzers (molybdenum vs. photolytic converters) The NO concentrations measured using the two NOx analyzers were compared to check for consistency between the two methods. Fig. 2 shows scatter plots of the NO concentrations measured using the NOx analyzer equipped with the photolytic converter versus that equipped with the molybdenum converter during fall, winter, spring, and summer of 2015e2016. The highest NO concentrations were observed during winter, followed by fall, spring, and summer (Fig. 2). Excellent correlations of NO concentrations were observed between the two NOx analyzers with slopes of 0.99e1.01 and R2 values of 0.99e1.0. These results indicate that the sensitivity of the NOx analyzers will not influence the evaluation of the NO2 measurement artifacts associated with the molybdenum converter. Because no converters were applied in both NOx analyzers for the NO measurement, NO comparison results can represent the combined precision errors of the two NOx analyzers. The combined precision errors of the two NOx analyzers for the NO measurement was determined to ±1% from regression slopes in Fig. 2. Fig. 3 shows scatter plots of the NO2 concentrations measured by the two NOx analyzers. The NO*2 concentrations were higher than those obtained from the photolytic converter (NO2) during the entire measurement period. Good correlations were observed between NO*2 and NO2 (R2 ¼ 0.96e0.98; Fig. 3). Regression slopes of
Fig. 5. Diurnal variations in the NO*2and NO2 concentrations during (a) fall, (b) winter, (c) spring, and (d) summer.
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NO2 versus NO*2 ranged from 1.0 to 1.11 with intercepts at 1.2e3.7 ppbv. The average NO2 levels were 15.8 ± 11.3, 19.9 ± 11.8, 12.6 ± 10.6, and 7.3 ± 5.2 ppbv during fall, winter, spring, and summer, respectively, whereas the average NO*2 values were 18.7 ± 12.7, 23.3 ± 13.1, 16.3 ± 10.8, and 9.1 ± 5.3 ppbv, respectively (Table 2). The annual average NO2 concentration was 14.6 ± 11.3 ppbv, which was 20.4 ± 14.7% lower than the annual average NO*2 concentration (17.6 ± 12.5 ppbv). 3.2. Seasonal and diurnal variations in the NO2 artifact (DNO2) The NO2 measurement artifact (DNO2) was determined from the difference between the NO*2 and NO2 concentrations. Most NOz can be quantified using chemiluminescence apparatus equipped with a molybdenum converter but some NOz species such as HNO3 can be sticking on the surface of the inlet. Thus, even though most DNO2 is caused by NOz, it doesn't represent total NOz. The annual average DNO2 was 2.9 ± 2.2 ppbv, which equates to 20.4 ± 14.7% of NO*2. DNO2 showed a clear seasonal pattern (Table 2), with higher values during winter (3.4 ± 2.3 ppbv) and spring (3.7 ± 2.0 ppbv), followed by fall (2.9 ± 2.5 ppbv) and summer (1.9 ± 1.1). However, the contribution of DNO2 to NO*2 showed a different seasonal pattern, with higher values during spring (28.9 ± 18.8%) and summer (25.0 ± 16.1%), followed by fall (17.7 ± 13.2%) and winter (16.6 ± 10.4%). The higher interferences during spring and summer were attributed to the higher photochemistry of the atmosphere leading to higher NOz formation. Fig. 4 shows the DNO2/NO*2 ratios as a function of NO*2 concentration. Ratios are expressed as percentages throughout. Generally, decreasing DNO2/NO*2 ratios were observed as NO*2 concentration increased, especially during spring and summer. The average DNO2/ NO*2 ratio during spring increased to 38.9 ± 21.5% when NO*2 was less than 10 ppbv but then decreased to 6.7 ± 2.4% when NO*2 was greater than 50 ppbv. Fig. 4d shows that a similar pattern also developed during the summer. However, the DNO2/NO*2 ratios were relatively insensitive to the changing NO*2 concentration during fall and winter (Fig. 4a and b). The average DNO2/NO*2 ratios during fall and winter varied between 10% and 20%. Fig. 5 shows the diurnal variations in the NO2 and NO*2 concentrations during the four seasons. The NO2 and NO*2 concentrations show similar diurnal patterns, with peak values during morning and nighttime that can be related mainly to rush hour traffic and the low boundary layer height, respectively. The mean values during the morning rush hour NO2 peak were similar to those of the nighttime peaks during fall, winter, and summer. However, the morning rush hour NO2 peak was dominant during spring (Fig. 5c). The mean NO2 values during the morning rush hour reached 19.4, 23.3, 23.5, and 10.0 ppbv during fall, winter, spring and summer, respectively. The diurnal minimum NO2 values in the afternoon fell to 8.5, 13.8, 4.7, and 3.8 ppbv during fall, winter, spring and summer, respectively, which are almost 2 lower than the morning rush hour peaks. Diurnal variations of NO*2 were slightly higher than those of NO2 during the four seasons. Fig. 6 shows the DNO2 concentration, DNO2/NO*2 ratio, and O3 levels. Typically, a sharp increase in DNO2 concentrations occurred between 0 600 and 0 900 LT and reached peak values around 0 900 to 1 000 LT After the peak, there was a gradual decrease in DNO2 (Fig. 6a). Interestingly, in addition to the morning DNO2 peaks, an additional afternoon DNO2 peak was observed during spring. The DNO2/NO*2 ratio shows a clear diurnal pattern, with peak values around 1 400e1 600 LT that correspond to the diurnal O3 peak in the afternoon. The relatively high DNO2/NO*2 ratio in the afternoon can be partially explained by lower NO2 concentration in the afternoon caused by the stronger vertical mixing. Relatively high diurnal maxima of DNO2/NO*2 ratios were observed during spring
Fig. 6. Diurnal variations in (a) the DNO2, (b) DNO2/NO*2 ratio, and (c) O3 levels during the four seasons.
and summer, with mean values of 48.1% and 41.6%, respectively, whereas relatively low values were observed during fall (29.8%) and winter (20.4%). These seasonal variations in the diurnal maximum DNO2/NO*2 ratio were consistent with those of O3, with the highest O3 values being recorded during spring (63.7 ppbv) and summer (47.4 ppbv), followed by fall (35.2 ppbv) and winter (22.9 ppbv). These results imply that DNO2 formation in the afternoon is closely related to O3 formation. 3.3. Relationship between the NO2 artifact and PM2.5 mass and O3 levels Fig. 7 shows the temporal variations in the PM2.5 mass concentration and the DNO2 concentration. Interestingly, Fig. 7a and b shows similar temporal variations for PM2.5 mass and DNO2 during
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Fig. 7. Temporal variations in the PM2.5 mass concentration and DNO2 during (a) fall, (b) winter, (c) spring, and (d) summer.
Fig. 8. Scatter plots of the PM2.5 mass concentration versus DNO2 during (a) fall, (b) winter, (c) spring, and (d) summer.
fall and winter. However, different temporal patterns were observed during the latter half of spring and the first half of summer (Fig. 7c and d). Fig. 8 shows scatter plots of DNO2 versus PM2.5 mass concentrations. As already indicated in Fig. 7a and b, there is a good correlation between DNO2 and PM2.5 mass concentration
during fall and winter, with R2 values of 0.59 and 0.54, respectively (Fig. 8a and b). The regression slopes between DNO2 and PM2.5 mass concentration were 0.095 and 0.105 ppbv/(mg/m3), during fall and winter, respectively. Even though the R2 values between DNO2 and the PM2.5 mass concentration were low during spring and
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summer (Fig. 8c and d), the associated regression slopes were similar to those during fall and winter. It is well known that most NOz species are secondarily formed via photochemical reaction in atmosphere. Similarly, more than half of PM2.5 mass at a suburban site in Korea was also secondarily formed via photochemical reaction in atmosphere (Jung et al., 2016). Consequently, good correlation between NOz and PM2.5 mass can be expected. This result can explain the similarity of the temporal variations in DNO2 and PM2.5 mass during fall and winter. Similar diurnal patterns have been observed linking DNO2 and O3 at urban sites in China (Xu et al., 2013) and Japan (Suzuki et al., 2011). A positive correlation was observed between DNO2 and O3 at urban sites in Chile (Villena et al., 2012) and China (Sun et al., 2011). In contrast to these previous studies, even though similar diurnal variations are apparent for the DNO2/NO*2 ratio and O3 concentration in Fig. 6, there is a poor correlation between DNO2 and O3 concentrations during all seasons (Fig. 9).
NO2 at two rural sites in Switzerland.
DNO2 NO*2 NO2 ¼ a,NO*2 þ b,O3 þ c,factorðmonthÞ
þ d,factor
day night
þe
Xu et al. (2013) applied a similar correction model at four urban sites in China by adding the term NO/NO*x to reflect the age of air.
NO þd NO*x
DNO2 NO*2 NO2 ¼ a,NO*2 þ b,O3 þ c,
As shown in Figs. 8 and 9, there is a relatively good correlation between DNO2 and PM2.5, but a poor correlation between DNO2 and O3. Therefore, we propose a simple correction model based on the PM2.5 mass concentration as follows.
DNO2 NO*2 NO2 ¼ a,PM2:5 3.4. Correction of the NO2 artifact As most national monitoring sites in Korea use a chemiluminescence detector equipped with a molybdenum converter to measure NO2, we have developed a correction model to retrieve the true NO2 levels from the molybdenum NO*2 measurements. Similar correction models were suggested by Steinbacher et al. (2007) and Xu et al. (2013). They used the O3 concentration as the main parameter in their correction models. For example, Steinbacher et al. (2007) applied the following correction model to retrieve
Here, a represents the regression slope between the DNO2 and the PM2.5 mass concentrations (Fig. 8) of 0.095 and 0.105 ppbv/(mg/m3) for fall and winter, respectively. Fig. 10 compares the measured and modeled DNO2 values for fall and winter. The modeled DNO2 describes well the temporal variations in the measured DNO2. We found that the modeled DNO2 can explain approximately 88% of the measured DNO2 during fall and winter. The NO2 levels measured using a molybdenum converter were corrected using the calculated DNO2 and then compared with the NO2 levels obtained from the
Fig. 9. Scatter plots of the O3 mass concentration versus DNO2 during (a) fall, (b) winter, (c) spring, and (d) summer.
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photolytic converter (Fig. 11). The regression slopes and intercepts during fall and winter were close to 1 and 0, respectively (Fig. 11), indicating that our correction model can be used to retrieve the true NO2 levels from previously measured NO*2. The simple correction model suggested in this study is site-specific. Thus, the simple correction model can only be applied for the present field site. 4. Summary and conclusions NO2 measurements made using chemiluminescence detectors equipped with two different converters at a suburban site in Korea showed that the molybdenum converter significantly overestimates the actual NO2 concentration, with an annual average overestimate of 20.4%. There were well-defined seasonal variations, with the highest NO2 artifacts occurring during spring (28.9%) and summer (25.0%), followed by fall (17.7%) and winter (16.6%). These results indicate that only 71%e83% of NO2 measurements made by the molybdenum converter could be attributed to real NO2 at our suburban study site in Korea. Because most NOz and a large fraction
299
of PM2.5 mass are secondarily formed via photochemical reaction in atmosphere and NO2 artifacts are caused mostly by NOz, good correlations between NO2 artifacts and PM2.5 mass during fall and winter imply that the NO2 measurement artifact can be corrected using PM2.5 mass. Thus, we suggest a simple correction model for the present field site using the PM2.5 mass concentration. The fraction of NO2 artifact in NO2 measured by the molybdenum converter showed a peak value in the afternoon that corresponds to the diurnal O3 peak. These results imply that DNO2 formation in the afternoon is closely related to O3 formation. The chemiluminescence technique is currently the most widely used method of online continuous monitoring of NO2 because of its stability. Molybdenum converters are commonly used with the chemiluminescence technique due to their stability and good NO2 to NO conversion efficiency. In Korea, over 300 national monitoring sites use chemiluminescence monitors equipped with molybdenum converters for NO2 measurement. This study found that only between 71% (spring) and 83% (winter) of the NO2 levels obtained using the molybdenum converter could be attributed to the actual NO2 concentration in the air samples. In other words, the NO2
Fig. 10. Temporal variations in the measured and modeled DNO2 during (a) fall and (b) winter.
Fig. 11. Scatter plots of the measured and modeled DNO2 during (a) fall and (b) winter.
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values reported from the national monitoring sites in Korea have been overestimated over the last few decades. The NO2 to NO conversion efficiency of photolytic converters has been improved considerably. For example, in this study, the NO2 to NO conversion efficiency of the BLC2 photolytic converter reached approximately 95% at ambient NO2 levels (<100 ppbv). Therefore, we suggest that the use of artifact-free NO2 monitors for long-term online monitoring and climate research should be considered. Acknowledgements This work was supported by a grant (2016001870001) from the Ministry of Environment (Korea) under the Green Patrol ProjectDevelopment of automated instruments for measuring hazardous chemicals (CO, SO2, NOx, O3) in ambient and workplace and also by a grant (17011010) from the Korea Research Institute of Standards and Science (KRISS) under the Basic R&D Project of Establishment of National Gas Analysis Measurement Standards and Improvements of Calibration and Measurement Capabilities. References AQD, 2015. 42i BLC upgrade: manual. Air Quality Design, Inc.. Golden, CO. www. airqualitydesign.com. Dunlea, E.J., et al., 2007. Evaluation of nitrogen dioxide chemiluminescence monitors in a polluted urban environment. Atmos. Chem. Phys. 7, 2691e2704. Flores, E., et al., 2012. Final report on international comparison CCQM-K74: nitrogen dioxide, 10 mmol/mol. Metrologia 49 (1A), 08005. http://dx.doi.org/10.1088/ 0026-1394/49/1A/08005. Gehrig, R., Baumann, R., 1993. Comparison of 4 Different Types of Commercially Available Monitors for Nitrogen Oxides with Test Gas Mixtures of NH3, HNO3, PAN and VOC and in Ambient Air. Paper Presented at EMEP Workshop on Measurements of Nitrogen-Containing Compounds. EMEP/CCC Report 1/93. Les Diablerets, Switzerland. Grosjean, D., Harrison, J., 1985. Response of chemiluminescence NOx analyzers and ultraviolet ozone analyzers to organic air pollutants. Environ. Sci. Technol. 19, 862e865. IMPROVE, 2006. Spatial and Seasonal Patterns and Temporal Variability of Haze and its Constituents in the United States. Report IV. Available from: http://vista.cira. colostate.edu/improve/Publications/Reports/2006/2006.htm. Jung, J., Yu, J., Lyu, Y., Lee, M., Hwang, T., Lee, S., 2016. Ground based characterization of spectral optical properties of haze and Asian dust episodes under Asian continental outflow during winter 2014. Atmos. Chem. Phys. Discuss. http:// dx.doi.org/10.5194/acp-2016-961. Katsoulis, M., Dimakopoulou, K., Pedeli, X., Trichopoulos, D., Gryparis, A., Trichopoulou, A., Katsouyanni, K., 2014. Long-term exposure to traffic-related air pollution and cardiovascular health in a Greek cohort study. Sci. Total Environ. 490, 934e940.
Nakamura, K., et al., 2003. Measurement of NO2 by the photolysis conversion technique during the transport and chemical evolution over the Pacific (TRACEP) campaign. J. Geophys. Res. Atmos. 108 (D24), 4752. http://dx.doi.org/10.1029/ 2003JD003712. Nguyen, H.T., Kim, K.-H., Park, C., 2015. Long-term trend of NO2 in major urban areas of Korea and possible consequences for health. Atmos. Environ. 106, 347e357. Osthoff, H.D., et al., 2006. Measurement of atmospheric NO2 by pulsed cavity ringdown spectroscopy. J. Geophys. Res. Atmos. 111, D12305. http://dx.doi.org/ 10.1029/2005JD006942. Pandey, J.S., Kumar, R., Devotta, S., 2005. Health risks of NO2, SPM and SO2 in Delhi (India). Atmos. Environ. 39, 6868e6874. Parrish, D.D., Hahn, C.H., Fahey, D.W., Williams, E.J., Bollinger, M.J., Hübler, G., Buhr, M.P., Murphy, P.C., Trainer, M., Hsie, E.Y., Liu, S.C., Fehsenfeld, F.C., 1990. Systematic variations in the concentration of NOx (NO plus NO2) at niwot ridge, Colorado. J. Geophys. Res. Atmos. 95, 1817e1836. Reed, C., Evans, M.J., Carlo, P.D., Lee, J.D., Carpenter, L.J., 2016. Interferences in photolytic NO2 measurements: explanation for an apparent missing oxidant? Atmos. Chem. Phys. 16, 4707e4724. Ryerson, T.B., Williams, E.J., Fehsenfeld, F.C., 2000. An efficient photolysis system for fast-response NO2 measurements. J. Geophys. Res. Atmos. 105, 26447e26461. Sadanaga, Y., Fukumori, Y., Kobashi, T., Nagata, M., Takenaka, N., Bandow, H., 2010. Development of a selective light-emitting diode photolytic NO2 converter for continuously measuring NO2 in the atmosphere. Anal. Chem. 82, 9234e9239. Seinfeld, J.H., Pandis, S.N., 1998. Atmospheric Chemistry and Physics: from Air Pollution to Climate Change. John Wiley, Hoboken, N. J. Steinbacher, M., Zellweger, C., Schwarzenbach, B., Bugmann, S., Buchmann, B., n ez, C., Prevot, A.S.H., Hueglin, C., 2007. Nitrogen oxide measurements at Ordo rural sites in Switzerland: bias of conventional measurement techniques. J. Geophys. Res. Atmos. 112, D11307. http://dx.doi.org/10.1029/2006JD007971. Sun, Y., Wang, L., Wang, Y., Quan, L., Zirui, L., 2011. In situ measurements of SO2, NOx, NOy, and O3 in Beijing, China during August 2008. Sci. Tot. Environ. 409, 933e940. Suzuki, H., Miyao, Y., Nakayama, T., Pearce, J.K., Matsumi, Y., Takahashi, K., Kita, K., Tonokura, K., 2011. Comparison of laser-induced fluorescence and chemiluminescence measurements of NO2 at an urban site. Atmos. Environ. 45, 6233e6240. Thornton, J.A., Wooldridge, P.J., Cohen, R.C., Williams, E.J., Hereid, D., Fehsenfeld, F.C., Stutz, J., Alicke, B., 2003. Comparisons of in situ and long path measurements of NO2 in urban plumes. J. Geophys. Res. Atmos. 108 (D16), 4496. http://dx.doi.org/10.1029/2003JD003559. Villena, G., Bejan, I., Kurtenbach, R., Wiesen, P., Kleffmann, J., 2012. Interferences of commercial NO2 instruments in the urban atmosphere and in a smog chamber. Atmos. Meas. Tech. 5, 149e159. Winer, A.M., Peters, J.W., Smith, J.P., Pitts Jr., J.N., 1974. Response of commercial chemiluminescence NOeNO2 analyzers to other nitrogen containing compounds. Environ. Sci. Technol. 8, 1118e1121. Xu, Z., Wang, T., Xue, L.K., Louie, P.K.K., Luk, C.W.Y., Gao, J., Wang, S.L., Chai, F.H., Wang, W.X., 2013. Evaluating the uncertainties of thermal catalytic conversion in measuring atmospheric nitrogen dioxide at four differently polluted sites in China. Atmos. Environ. 76, 221e226. Zhang, L., Lee, C.S., Zhang, R., Chen, L., 2017. Spatial and temporal evaluation of long term trend (2005-2014) of OMI retrieved NO2 and SO2 concentrations in Henan Province, China. Atmos. Environ. 154, 151e166.
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Seasonal variations in the NO2 artifact from chemiluminescence measurements with a molybdenum converter at a suburban site in Korea (downwind of the Asian continental outflow) during 2015e2016 Jinsang Jung*, JaeYong Lee, ByungMoon Kim, SangHyub Oh Center for Gas Analysis, Korea Research Institute of Standards and Science, Daejeon 305-340, Republic of Korea
h i g h l i g h t s The conversion efficiency of the BLC2 photolytic converter reached ~95% at ambient NO2 levels (<100 ppbv). Molybdenum converter overestimated NO2 levels by 20.4 ± 14.7% compared to the actual NO2 level. NO2 artifact correlated well with the PM2.5 mass concentration during the fall and winter seasons.
a r t i c l e i n f o
a b s t r a c t
Article history: Received 15 February 2017 Received in revised form 28 June 2017 Accepted 4 July 2017 Available online 5 July 2017
This paper investigates the NO2 artifact associated with the chemiluminescence measurement technique that uses a molybdenum converter by applying the same technique but with a photolytic converter at a site downwind of the Asian continental outflow (Daejeon, Korea). The NO2 to NO conversion efficiencies of the molybdenum and photolytic converters were found to be 100% and 95%, respectively, at an ambient level of NO2 (<100 ppbv). Two NO2 monitors equipped with molybdenum and photolytic converters were deployed for ambient NO2 measurements in Daejeon, Korea between the fall of 2015 and the summer of 2016. It was found that the monitor equipped with the molybdenum converter overestimated NO2 levels by 20.4 ± 14.7% when compared with the actual NO2 level in the Daejeon atmosphere over the entire measurement period. This NO2 artifact (DNO2), defined as the difference between molybdenum NO2 and photolytic NO2 values, correlated well with the PM2.5 mass concentration during the fall and winter seasons. Based on these findings, this study develops a simple correction model for DNO2 using the PM2.5 mass concentration during the fall and winter seasons. The model-corrected NO2 concentration correlated well with the actual NO2 values with a slope of approximately 1.0 and R2 value of 0.98 during the fall and winter seasons. © 2017 Elsevier Ltd. All rights reserved.
Keywords: Chemiluminescence NO2 artifact Molybdenum converter Photolytic converter
1. Introduction Nitric oxide (NO) is an important trace gas in the troposphere and is emitted primarily from high-temperature combustion sources such as vehicles and power plants (Seinfeld and Pandis, 1998). Nitrogen dioxide (NO2) forms mainly via oxidative reaction in the atmosphere. NO2 plays an important role in atmospheric chemical processes by participating in O3 and secondary aerosol
* Corresponding author. E-mail address: [email protected] (J. Jung). http://dx.doi.org/10.1016/j.atmosenv.2017.07.010 1352-2310/© 2017 Elsevier Ltd. All rights reserved.
formation (Seinfeld and Pandis, 1998). In addition, NO2 can absorb incoming solar radiation and thus reduce visibility (IMPROVE, 2006), and also affects human health by damaging the respiratory system (Pandey et al., 2005; Katsoulis et al., 2014). Due to the importance of NO2 to human health and the atmosphere, NO2 was designated as one of the Korean Environmental Agency's “criteria pollutants”. The Korean Environmental Agency regulates NO2 levels based on hourly averaged maxima of 100 ppbv, daily averaged maxima of 60 ppbv, and yearly averaged maxima of 30 ppbv. A gradual increase in the annual mean NO2 concentration was observed in Seoul, Korea from 1989 to 1999, but this was converted to a slight decreasing trend from 2000 to 2010 following the
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successful implementation of a scheme that replaced diesel buses with natural gas vehicles (Nguyen et al., 2015). However, the annual mean NO2 values in Seoul over the last decade still exceeded the Korean government's regulatory threshold (Nguyen et al., 2015). Long-term satellite observations of the spatial distribution of NO2 over China have revealed that there was a continuous rise in NO2 levels between 2005 and 2011. This was caused mainly by the increasing numbers of vehicles (there was a 155% increase between 2006 and 2012). However, this trend was reversed, and NO2 levels began to fall again between 2011 and 2014, possibly because of the implementation of effective central governmental policies aimed at reducing NO2 emissions (Zhang et al., 2017). Chemiluminescence equipment fitted with a molybdenum converter is the most widely used method for measuring surface NO2 concentration. In Korea, more than 300 national monitoring sites use this technique for continuous monitoring of NO2. The advantages of the chemiluminescence technique are that it is simple to operate, has good sensitivity, and is easy to calibrate. As only NO is quantified based on the chemiluminescent reaction of NO with O3, an NO2 to NO converter is required to obtain the NO2 levels. Thus, when using the chemiluminescence technique, NO2 levels are measured indirectly using the difference between the total NO value measured after passing through an NO2 to NO converter and the initial NO value measured directly (i.e., before passing through the converter). Typically, a molybdenum converter heated to 300e350 C is used for the conversion of NO2 to NO. Although molybdenum converters show good conversion efficiencies, the conversion is not specific to NO2. Besides NO2, it can also convert other oxidized nitrogen compounds such as nitric acid (HNO3), peroxyacetyl nitrate (PAN) like species (peroxyacylnitrates), and organic nitrates to NO (Winer et al., 1974; Grosjean and Harrison, 1985; Gehrig and Baumann, 1993). These results indicate that the last several decades of NO2 measurements made in Korea were overestimated when compared with the actual NO2 level in the atmosphere, and this error was caused mainly by the NO2 measurement artifact. Thus, the uncertainty associated with molybdenum NO2
291
measurements needs to be quantified at the seasonal scale. Although the NO2 measurement artifact caused by molybdenum converters has been previously investigated in mainland China (e.g., Xu et al., 2013), there have been no studies of the NO2 measurement artifact downwind of the Asian continental outflow. There are many alternative NO2 monitoring techniques that are free from NO2 measurement artifacts. For example, the laser induced fluorescence (LIF), differential optical absorption spectroscopy (DOAS), cavity attenuation phase shift (CAPS), and tunable infrared laser differential absorption spectroscopy (TILDAS) techniques can measure NO2 directly in air. There have been several intercomparison studies between these optical techniques and the chemiluminescence NO2 measurement technique (Thornton et al., 2003; Nakamura et al., 2003; Osthoff et al., 2006; Dunlea et al., 2007; Villena et al., 2012). Even though these optical techniques are free from NO2 measurement artifacts when compared with the chemiluminescence technique, they are not suitable for long-term continuous monitoring of NO2 in the atmosphere. A photolytic NO2 to NO converter that can be applied to the chemiluminescence technique has been developed that selectively reduces NO2 to NO using ultra violet (UV) light and, thus, is almost free from interference (Parrish et al., 1990; Sadanaga et al., 2010). This chemiluminescence apparatus equipped with a photolytic converter is the suitable method for the online monitoring of NO2 at medium pollution level. The NO2 to NO conversion efficiency of the earlier versions of the photolytic converters that used metal halides and xenon arc lamps only reached 70% and they were not stable (Parrish et al., 1990; Ryerson et al., 2000; Steinbacher et al., 2007). Recently, UV light-emitting diodes (LED) have been used as a light source for the photolytic converter (Sadanaga et al., 2010). This UV LED technique increased the conversion efficiency of the photolytic converter up to 90% and also showed good stability for long-term use (Sadanaga et al., 2010). If we intend to replace the molybdenum converter with a photolytic converter across the Korean national monitoring network, it will be necessary to carry out a long-term intercomparison of the NO2 levels obtained from the two converters.
Fig. 1. Map showing the sampling site (Google Map and Google Earth imagery (© Google Inc.)). The sampling site is located at the Korea Research Institute of Standards and Science (36 230 1900 N, 127 220 2100 E) in Daejeon, Korea.
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The term NOz is defined as the difference between total reactive nitrogen (NOy) including NOx (sum of NO and NO2), HNO2, HNO3, PANs, etc and NOx. Suzuki et al. (2011) measured NO2 concentrations using the chemiluminescence apparatus equipped with a molybdenum converter and the LIF technique. They observed high NO2 artifacts in the molybdenum NO2 measurements when O3 concentrations were over 50 ppbv at an urban site in Tokyo, Japan. They also found that peroxy nitrate species made a significant contribution to the NO2 measurement artifacts generated by the molybdenum converter under high O3 conditions. Dunlea et al. (2007) found that HNO3 and alkyl and multifunctional alkyl nitrates mainly contributed to the NO2 measurement artifacts recorded in Mexico City. If we are to be able to compensate for the NO2 measurement artifacts caused by the molybdenum converter, it will be necessary to characterize the temporal and diurnal variations in the NO2 measurement artifacts. In addition, a simple correction model will be needed to correct NO2 values measured by molybdenum converters. In this study, we made continuous NO2 measurements using the chemiluminescence technique at a suburban site in Daejeon, Korea (downwind of the Asian continental outflow) between fall 2015
and summer 2016. The seasonal and diurnal variations of the NO2 measurement artifact associated with the molybdenum converter were evaluated against the NO2 data obtained using a photolytic converter. In addition, we evaluated the dependence of the NO2 measurement artifact on the levels of gaseous and particulate pollutants. Finally, we developed a simple correction model to compensate for the NO2 artifacts. 2. Experimental methods 2.1. Measurement site Ambient NO2 was measured at a suburban site (36 2301900 N, 127 220 2100 E) in Daejeon, Korea, during four seasons in 2015e2016: fall (25 September30 November 2015), winter (1 December 2015e31 January 2016), spring (24 March15 April 2016), and summer (23 June8 August 2016). Two NO2 monitors were installed inside a temperature-controlled container (25 ± 3 C) located at the Korea Research Institute of Standards and Science (KRISS) (Fig. 1). Ambient air was drawn from the rooftop of the container through a glass tube and supplied to the instruments via
Table 1 Measurement parameters and techniques used in this study. Parameter
Measurement method
Instrument
NO2 to NO converter
Converter temperature
Detection limit
NO, NO*2, NO*x NO, NO2, NOx
Chemiluminescence Chemiluminescence
Kentek, Mezus 210 Kentek, Mezus 210P
Molybdenum Photolytic
325 C e
0.4 ppbv 0.4 ppbv
Fig. 2. Scatter plots of the NO concentrations measured using NOx analyzer equipped with a photolytic converter versus that by a molybdenum converter during (a) fall, (b) winter, (c) spring, and (d) summer.
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a manifold. The NO2 concentration was measured at intervals of 1 min and we used the hourly average values in this study. Hourly O3 and PM2.5 mass concentrations were also obtained from the Korean National Observatory, which is approximately 1.8 km south of the measurement site (http://www.airkorea.or.kr/airkorea/eng/ index.jsp). Because the NO2 measurement site and the Korean National Observatory are located at suburban areas in Daejeon and there are no particular sources between the two sites, we assumed that differences of O3 and PM2.5 levels between the two sites are negligible. Unless stated otherwise, the times shown in this study are Korean local time (LT ¼ GMTþ9). 2.2. NO2 measurement NO, NO2, and NOx were measured using a chemiluminescence monitor equipped with NO2 to NO converters as shown in Table 1. Two NOx monitors, one equipped with a molybdenum converter (Kentek, model Mezus 210) and the other with a photolytic converter (Kentek, model Mezus 210P), were used to measure the ambient NO2 levels. In the molybdenum converter, NO2 is converted to NO on the heated (320 C) molybdenum surface. In the photolytic converter, NO2 is converted to NO using UV light centered at 395 nm. For this study, we used a commercial photolytic converter (AQD, model BLC2). The surface temperature of the photolytic converter was maintained as 45e50 C using Peltier cooling modules. Zero and span drifts were determined from the differences seen in the zero air and 400 ppbv NO standard gas measurements, respectively, over a period of 24 h. The zero and span drifts were less than 0.1 and 1.1 ppbv, respectively. Good
293
linearity was obtained in the range of 0e400 ppbv with a slope of 1 and R2 value of 1.0. The detection limit of the NOx monitors, defined as 3 the standard deviation of the zero air measurement, was 0.4 ppbv with an uncertainty of 2%. As NO2 measured by the molybdenum converter was influenced by the NOz artifact, NO2 levels obtained using the molybdenum converter are denoted by NO*2 in this study, whereas those measured using the photolytic converter are denoted by NO2. 2.3. Quality assurance of the NOx monitors To calibrate the NOx monitors, a 100 ppm of NO in nitrogen standard gas mixture was prepared by KRISS. Zero air was generated using a zero air generator (API, model 701). This 100 ppm of NO standard gas mixture was then diluted to 400 ppbv using a gas calibrator (API, model 700E) and introduced to the NOx monitor. The flowrates of the gas calibrator was calibrated using a volumetric flow calibrator (MesaLabs, Definer 220). Zero air and span calibrations were performed every week. The NO2 to NO conversion efficiencies of the molybdenum and photolytic converters were evaluated using the NO2 standard gas prepared by KRISS. Because KRISS is the metrology institute in Korea, KRISS has international traceability on NO2 gas mixture with an uncertainty of less than 3% through an inter-comparison between international metrology institutes (Flores et al., 2012). First, 50 ppmv of the NO2 in nitrogen gas mixture was diluted to give levels between 50 and 400 ppbv using the gas calibrator. The conversion efficiencies of the converters were then determined from the ratio of the measured NO2 to the standard NO2 gas level.
Fig. 3. Scatter plots of the NO2 concentrations measured using the photolytic converter versus that using the molybdenum converter (NO*2) during (a) fall, (b) winter, (c) spring, and (d) summer.
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The conversion efficiency of the molybdenum converter was approximately 100% across the 50e400 ppbv NO2 range. However, the conversion efficiency of the photolytic converter varied with the NO2 concentration. In general, the conversion efficiency increased as the NO2 concentration decreased. The conversion efficiency of the photolytic converter reached approximately 95% when the NO2 concentration was lower than 100 ppbv. As the ambient NO2 level in an urban environment in Korea is generally lower than 100 ppbv, we used a constant conversion efficiency of 95% for the photolytic converter. The conversion efficiencies of the molybdenum and photolytic converters were confirmed using a gas-phase titration method (here NO standard gas mixture was used). The NO2 levels measured with the photolytic converter were corrected using the NO2 to NO conversion efficiency for use in this
study. 2.4. Interferences of the photolytic converter As already reported by Reed et al. (2016) and Villena et al. (2012), a photolytic converter is affected by negative or positive interferences. The negative interference can be caused by the formation of HO2/RO2 radicals inside the photolytic converter or by the back titration of NO with ambient O3 inside the photolytic converter. Villena et al. (2012) performed a smog chamber study to investigate the negative interference induced by the formation of HO2/RO2 radicals inside the photolytic converter. The negative interference of the photolytic converter was obtained as ~10% in a typical urban situation (Villena et al., 2012). Thus, the negative
Table 2 Summary of seasonal variations in NO2 measurements. Parameter
Unit
1 Year
Falla
Winterb
Springc
Summerd
NO*2
ppbv
NO2 DNO2e DNO2 fraction
%
14.6 ± 11.3 17.6 ± 12.5 2.9 ± 2.2 20.4 ± 14.7
15.8 ± 11.3 18.7 ± 12.7 2.9 ± 2.5 17.7 ± 13.2
19.9 ± 11.8 23.3 ± 13.1 3.4 ± 2.3 16.6 ± 10.4
12.6 ± 10.6 16.3 ± 10.8 3.7 ± 2.0 28.9 ± 18.8
7.3 ± 5.2 9.1 ± 5.3 1.9 ± 1.1 25.0 ± 16.1
a b c d e
Fall: 25 September30 November 2015. Winter: 1 December 2015e31 January 2016. Spring: 24 March15 April 2016. Summer: 23 June8 August 2016. DNO2: NO2*-NO2.
Fig. 4. The DNO2/NO*2 ratios as a function of NO*2 concentrations during (a) fall, (b) winter, (c) spring, and (d) summer. DNO2 is the difference between the NO*2 and NO2 concentrations.
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interference of the photolytic converter was assumed to be ~10% according to the field study by Villena et al. (2012). The manufacturer of AQD BLC2 photolytic converter provided the change in conversion efficiency of NO2 due to the back titration of NO with ambient O3 (AQD, 2015). The percent change of conversion efficiency of the photolytic converter is less than 1% when O3 concentration is lower than 100 ppbv with a 1 s residence time. Because the flowrate of the photolytic converter was maintained as ~0.7 L min1, residence time was calculated as ~1.5 s. Thus, decrease in conversion efficiency of the photolytic converter for 1.5 s residence time was determined to be less than 1.8% when O3 concentration is less than 100 ppbv. Thermal decomposition of PAN type species inside the photolytic converter can overestimate NO2 concentration (Reed et al., 2016). This effect is significant in pristine environments and at high elevation where NOx concentration is low (less than 1 ppbv). Because the measurement site in this study was located in a suburban area, it was expected that thermal decomposition of PAN type species inside the photolytic converter might be less significant for the NO2 measurement compared to pristine environment. The model simulation showed that the monthly maximum positive interference of NO2 by the photolytic converter estimated to be 1e5% over the Korean Peninsula (Reed et al., 2016). From the negative and positive interferences discussed above, the measurement uncertainty of NO2 by the photolytic converter was determined to be less than 11.5%.
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3. Results and discussion 3.1. Intercomparison of two NOx analyzers (molybdenum vs. photolytic converters) The NO concentrations measured using the two NOx analyzers were compared to check for consistency between the two methods. Fig. 2 shows scatter plots of the NO concentrations measured using the NOx analyzer equipped with the photolytic converter versus that equipped with the molybdenum converter during fall, winter, spring, and summer of 2015e2016. The highest NO concentrations were observed during winter, followed by fall, spring, and summer (Fig. 2). Excellent correlations of NO concentrations were observed between the two NOx analyzers with slopes of 0.99e1.01 and R2 values of 0.99e1.0. These results indicate that the sensitivity of the NOx analyzers will not influence the evaluation of the NO2 measurement artifacts associated with the molybdenum converter. Because no converters were applied in both NOx analyzers for the NO measurement, NO comparison results can represent the combined precision errors of the two NOx analyzers. The combined precision errors of the two NOx analyzers for the NO measurement was determined to ±1% from regression slopes in Fig. 2. Fig. 3 shows scatter plots of the NO2 concentrations measured by the two NOx analyzers. The NO*2 concentrations were higher than those obtained from the photolytic converter (NO2) during the entire measurement period. Good correlations were observed between NO*2 and NO2 (R2 ¼ 0.96e0.98; Fig. 3). Regression slopes of
Fig. 5. Diurnal variations in the NO*2and NO2 concentrations during (a) fall, (b) winter, (c) spring, and (d) summer.
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NO2 versus NO*2 ranged from 1.0 to 1.11 with intercepts at 1.2e3.7 ppbv. The average NO2 levels were 15.8 ± 11.3, 19.9 ± 11.8, 12.6 ± 10.6, and 7.3 ± 5.2 ppbv during fall, winter, spring, and summer, respectively, whereas the average NO*2 values were 18.7 ± 12.7, 23.3 ± 13.1, 16.3 ± 10.8, and 9.1 ± 5.3 ppbv, respectively (Table 2). The annual average NO2 concentration was 14.6 ± 11.3 ppbv, which was 20.4 ± 14.7% lower than the annual average NO*2 concentration (17.6 ± 12.5 ppbv). 3.2. Seasonal and diurnal variations in the NO2 artifact (DNO2) The NO2 measurement artifact (DNO2) was determined from the difference between the NO*2 and NO2 concentrations. Most NOz can be quantified using chemiluminescence apparatus equipped with a molybdenum converter but some NOz species such as HNO3 can be sticking on the surface of the inlet. Thus, even though most DNO2 is caused by NOz, it doesn't represent total NOz. The annual average DNO2 was 2.9 ± 2.2 ppbv, which equates to 20.4 ± 14.7% of NO*2. DNO2 showed a clear seasonal pattern (Table 2), with higher values during winter (3.4 ± 2.3 ppbv) and spring (3.7 ± 2.0 ppbv), followed by fall (2.9 ± 2.5 ppbv) and summer (1.9 ± 1.1). However, the contribution of DNO2 to NO*2 showed a different seasonal pattern, with higher values during spring (28.9 ± 18.8%) and summer (25.0 ± 16.1%), followed by fall (17.7 ± 13.2%) and winter (16.6 ± 10.4%). The higher interferences during spring and summer were attributed to the higher photochemistry of the atmosphere leading to higher NOz formation. Fig. 4 shows the DNO2/NO*2 ratios as a function of NO*2 concentration. Ratios are expressed as percentages throughout. Generally, decreasing DNO2/NO*2 ratios were observed as NO*2 concentration increased, especially during spring and summer. The average DNO2/ NO*2 ratio during spring increased to 38.9 ± 21.5% when NO*2 was less than 10 ppbv but then decreased to 6.7 ± 2.4% when NO*2 was greater than 50 ppbv. Fig. 4d shows that a similar pattern also developed during the summer. However, the DNO2/NO*2 ratios were relatively insensitive to the changing NO*2 concentration during fall and winter (Fig. 4a and b). The average DNO2/NO*2 ratios during fall and winter varied between 10% and 20%. Fig. 5 shows the diurnal variations in the NO2 and NO*2 concentrations during the four seasons. The NO2 and NO*2 concentrations show similar diurnal patterns, with peak values during morning and nighttime that can be related mainly to rush hour traffic and the low boundary layer height, respectively. The mean values during the morning rush hour NO2 peak were similar to those of the nighttime peaks during fall, winter, and summer. However, the morning rush hour NO2 peak was dominant during spring (Fig. 5c). The mean NO2 values during the morning rush hour reached 19.4, 23.3, 23.5, and 10.0 ppbv during fall, winter, spring and summer, respectively. The diurnal minimum NO2 values in the afternoon fell to 8.5, 13.8, 4.7, and 3.8 ppbv during fall, winter, spring and summer, respectively, which are almost 2 lower than the morning rush hour peaks. Diurnal variations of NO*2 were slightly higher than those of NO2 during the four seasons. Fig. 6 shows the DNO2 concentration, DNO2/NO*2 ratio, and O3 levels. Typically, a sharp increase in DNO2 concentrations occurred between 0 600 and 0 900 LT and reached peak values around 0 900 to 1 000 LT After the peak, there was a gradual decrease in DNO2 (Fig. 6a). Interestingly, in addition to the morning DNO2 peaks, an additional afternoon DNO2 peak was observed during spring. The DNO2/NO*2 ratio shows a clear diurnal pattern, with peak values around 1 400e1 600 LT that correspond to the diurnal O3 peak in the afternoon. The relatively high DNO2/NO*2 ratio in the afternoon can be partially explained by lower NO2 concentration in the afternoon caused by the stronger vertical mixing. Relatively high diurnal maxima of DNO2/NO*2 ratios were observed during spring
Fig. 6. Diurnal variations in (a) the DNO2, (b) DNO2/NO*2 ratio, and (c) O3 levels during the four seasons.
and summer, with mean values of 48.1% and 41.6%, respectively, whereas relatively low values were observed during fall (29.8%) and winter (20.4%). These seasonal variations in the diurnal maximum DNO2/NO*2 ratio were consistent with those of O3, with the highest O3 values being recorded during spring (63.7 ppbv) and summer (47.4 ppbv), followed by fall (35.2 ppbv) and winter (22.9 ppbv). These results imply that DNO2 formation in the afternoon is closely related to O3 formation. 3.3. Relationship between the NO2 artifact and PM2.5 mass and O3 levels Fig. 7 shows the temporal variations in the PM2.5 mass concentration and the DNO2 concentration. Interestingly, Fig. 7a and b shows similar temporal variations for PM2.5 mass and DNO2 during
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Fig. 7. Temporal variations in the PM2.5 mass concentration and DNO2 during (a) fall, (b) winter, (c) spring, and (d) summer.
Fig. 8. Scatter plots of the PM2.5 mass concentration versus DNO2 during (a) fall, (b) winter, (c) spring, and (d) summer.
fall and winter. However, different temporal patterns were observed during the latter half of spring and the first half of summer (Fig. 7c and d). Fig. 8 shows scatter plots of DNO2 versus PM2.5 mass concentrations. As already indicated in Fig. 7a and b, there is a good correlation between DNO2 and PM2.5 mass concentration
during fall and winter, with R2 values of 0.59 and 0.54, respectively (Fig. 8a and b). The regression slopes between DNO2 and PM2.5 mass concentration were 0.095 and 0.105 ppbv/(mg/m3), during fall and winter, respectively. Even though the R2 values between DNO2 and the PM2.5 mass concentration were low during spring and
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summer (Fig. 8c and d), the associated regression slopes were similar to those during fall and winter. It is well known that most NOz species are secondarily formed via photochemical reaction in atmosphere. Similarly, more than half of PM2.5 mass at a suburban site in Korea was also secondarily formed via photochemical reaction in atmosphere (Jung et al., 2016). Consequently, good correlation between NOz and PM2.5 mass can be expected. This result can explain the similarity of the temporal variations in DNO2 and PM2.5 mass during fall and winter. Similar diurnal patterns have been observed linking DNO2 and O3 at urban sites in China (Xu et al., 2013) and Japan (Suzuki et al., 2011). A positive correlation was observed between DNO2 and O3 at urban sites in Chile (Villena et al., 2012) and China (Sun et al., 2011). In contrast to these previous studies, even though similar diurnal variations are apparent for the DNO2/NO*2 ratio and O3 concentration in Fig. 6, there is a poor correlation between DNO2 and O3 concentrations during all seasons (Fig. 9).
NO2 at two rural sites in Switzerland.
DNO2 NO*2 NO2 ¼ a,NO*2 þ b,O3 þ c,factorðmonthÞ
þ d,factor
day night
þe
Xu et al. (2013) applied a similar correction model at four urban sites in China by adding the term NO/NO*x to reflect the age of air.
NO þd NO*x
DNO2 NO*2 NO2 ¼ a,NO*2 þ b,O3 þ c,
As shown in Figs. 8 and 9, there is a relatively good correlation between DNO2 and PM2.5, but a poor correlation between DNO2 and O3. Therefore, we propose a simple correction model based on the PM2.5 mass concentration as follows.
DNO2 NO*2 NO2 ¼ a,PM2:5 3.4. Correction of the NO2 artifact As most national monitoring sites in Korea use a chemiluminescence detector equipped with a molybdenum converter to measure NO2, we have developed a correction model to retrieve the true NO2 levels from the molybdenum NO*2 measurements. Similar correction models were suggested by Steinbacher et al. (2007) and Xu et al. (2013). They used the O3 concentration as the main parameter in their correction models. For example, Steinbacher et al. (2007) applied the following correction model to retrieve
Here, a represents the regression slope between the DNO2 and the PM2.5 mass concentrations (Fig. 8) of 0.095 and 0.105 ppbv/(mg/m3) for fall and winter, respectively. Fig. 10 compares the measured and modeled DNO2 values for fall and winter. The modeled DNO2 describes well the temporal variations in the measured DNO2. We found that the modeled DNO2 can explain approximately 88% of the measured DNO2 during fall and winter. The NO2 levels measured using a molybdenum converter were corrected using the calculated DNO2 and then compared with the NO2 levels obtained from the
Fig. 9. Scatter plots of the O3 mass concentration versus DNO2 during (a) fall, (b) winter, (c) spring, and (d) summer.
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photolytic converter (Fig. 11). The regression slopes and intercepts during fall and winter were close to 1 and 0, respectively (Fig. 11), indicating that our correction model can be used to retrieve the true NO2 levels from previously measured NO*2. The simple correction model suggested in this study is site-specific. Thus, the simple correction model can only be applied for the present field site. 4. Summary and conclusions NO2 measurements made using chemiluminescence detectors equipped with two different converters at a suburban site in Korea showed that the molybdenum converter significantly overestimates the actual NO2 concentration, with an annual average overestimate of 20.4%. There were well-defined seasonal variations, with the highest NO2 artifacts occurring during spring (28.9%) and summer (25.0%), followed by fall (17.7%) and winter (16.6%). These results indicate that only 71%e83% of NO2 measurements made by the molybdenum converter could be attributed to real NO2 at our suburban study site in Korea. Because most NOz and a large fraction
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of PM2.5 mass are secondarily formed via photochemical reaction in atmosphere and NO2 artifacts are caused mostly by NOz, good correlations between NO2 artifacts and PM2.5 mass during fall and winter imply that the NO2 measurement artifact can be corrected using PM2.5 mass. Thus, we suggest a simple correction model for the present field site using the PM2.5 mass concentration. The fraction of NO2 artifact in NO2 measured by the molybdenum converter showed a peak value in the afternoon that corresponds to the diurnal O3 peak. These results imply that DNO2 formation in the afternoon is closely related to O3 formation. The chemiluminescence technique is currently the most widely used method of online continuous monitoring of NO2 because of its stability. Molybdenum converters are commonly used with the chemiluminescence technique due to their stability and good NO2 to NO conversion efficiency. In Korea, over 300 national monitoring sites use chemiluminescence monitors equipped with molybdenum converters for NO2 measurement. This study found that only between 71% (spring) and 83% (winter) of the NO2 levels obtained using the molybdenum converter could be attributed to the actual NO2 concentration in the air samples. In other words, the NO2
Fig. 10. Temporal variations in the measured and modeled DNO2 during (a) fall and (b) winter.
Fig. 11. Scatter plots of the measured and modeled DNO2 during (a) fall and (b) winter.
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values reported from the national monitoring sites in Korea have been overestimated over the last few decades. The NO2 to NO conversion efficiency of photolytic converters has been improved considerably. For example, in this study, the NO2 to NO conversion efficiency of the BLC2 photolytic converter reached approximately 95% at ambient NO2 levels (<100 ppbv). Therefore, we suggest that the use of artifact-free NO2 monitors for long-term online monitoring and climate research should be considered. Acknowledgements This work was supported by a grant (2016001870001) from the Ministry of Environment (Korea) under the Green Patrol ProjectDevelopment of automated instruments for measuring hazardous chemicals (CO, SO2, NOx, O3) in ambient and workplace and also by a grant (17011010) from the Korea Research Institute of Standards and Science (KRISS) under the Basic R&D Project of Establishment of National Gas Analysis Measurement Standards and Improvements of Calibration and Measurement Capabilities. References AQD, 2015. 42i BLC upgrade: manual. Air Quality Design, Inc.. Golden, CO. www. airqualitydesign.com. Dunlea, E.J., et al., 2007. Evaluation of nitrogen dioxide chemiluminescence monitors in a polluted urban environment. Atmos. Chem. Phys. 7, 2691e2704. Flores, E., et al., 2012. Final report on international comparison CCQM-K74: nitrogen dioxide, 10 mmol/mol. Metrologia 49 (1A), 08005. http://dx.doi.org/10.1088/ 0026-1394/49/1A/08005. Gehrig, R., Baumann, R., 1993. Comparison of 4 Different Types of Commercially Available Monitors for Nitrogen Oxides with Test Gas Mixtures of NH3, HNO3, PAN and VOC and in Ambient Air. Paper Presented at EMEP Workshop on Measurements of Nitrogen-Containing Compounds. EMEP/CCC Report 1/93. Les Diablerets, Switzerland. Grosjean, D., Harrison, J., 1985. Response of chemiluminescence NOx analyzers and ultraviolet ozone analyzers to organic air pollutants. Environ. Sci. Technol. 19, 862e865. IMPROVE, 2006. Spatial and Seasonal Patterns and Temporal Variability of Haze and its Constituents in the United States. Report IV. Available from: http://vista.cira. colostate.edu/improve/Publications/Reports/2006/2006.htm. Jung, J., Yu, J., Lyu, Y., Lee, M., Hwang, T., Lee, S., 2016. Ground based characterization of spectral optical properties of haze and Asian dust episodes under Asian continental outflow during winter 2014. Atmos. Chem. Phys. Discuss. http:// dx.doi.org/10.5194/acp-2016-961. Katsoulis, M., Dimakopoulou, K., Pedeli, X., Trichopoulos, D., Gryparis, A., Trichopoulou, A., Katsouyanni, K., 2014. Long-term exposure to traffic-related air pollution and cardiovascular health in a Greek cohort study. Sci. Total Environ. 490, 934e940.
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