DSpace at VNU: Indirect prediction of surface ozone concentration by plant growth responses in East Asia using mini-open...
Environ Monit Assess (2013) 185:2755–2765 DOI 10.1007/s10661-012-2746-2 Indirect prediction of surface ozone concentration by plant growth responses in East Asia using mini-open top chambers Yoshihisa Kohno & Hideyuki Matsumura & Makoto Miwa & Tetsushi Yonekura & Keiji Aihara & Chanin Umponstira & Vo Thanh Le & Nguyen Thuy Ngoc & Phanm Hung Viet & Ma Wei Received: 23 January 2012 / Accepted: 14 June 2012 / Published online: July 2012 # Springer Science+Business Media B.V 2012 Abstract We developed small and mobile open top chambers (mini-OTC) measuring 0.6 m (W)×0.6 m (D)×1.2 m (H) with an air duct of 0.6 m (W)×0.23 m (D)×1.2 m (H) The air duct can be filled with activated charcoal to blow charcoal filtered air (CF) into the chamber, as opposed to non-filtered ambient air (NF) Ozone sensitive radish Raphanus sativus cv Y Kohno (*) : H Matsumura Central Research Institute of Electric Power Industry (CRIEPI), 1646 Abiko, Abiko, Chiba 270-1194, Japan e-mail: yoshihisakohno@gmail.com URL: http://criepi.denken.or.jp Red Chime and rosette pakchoi Brassica campestris var rosularis cv ATU171 were exposed to NF and CF in mini-OTCs at different locations in East Asia A total of 29 exposure experiments were conducted at nine locations, Shanghai, China, Ha Noi, Vietnam, Lampang, Phitsanulok and Pathumtani, Thailand, and Hiratsuka, Kisai, Abiko and Akagi, Japan K Aihara Kanagawa Environmental Research Center (KERC), 1-3-39 Shinomiya, Hiratsuka, Kanagawa 254-0014, Japan e-mail: kjaihara@ezweb.ne.jp URL: http://www.k-erc.pref.kanagawa.jp/en_hp/en_center/ en_center.htm Y Kohno e-mail: kohno@criepi.denken.or.jp H Matsumura e-mail: matz@criepi.denken.or.jp URL: http://criepi.denken.or.jp M Miwa : T Yonekura Center for Environmental Science in Saitama (CESS), 914 Kamitanedare, Kazo, Saitama 347-0115, Japan M Miwa e-mail: miwa.makoto@pref.saitama.lg.jp URL: http://www.kankyou.pref.saitama.lg.jp/web/eng/ cess_eng.html T Yonekura e-mail: yonekura.tetsushi@pref.saitama.lg.jp URL: http://www.kankyou.pref.saitama.lg.jp/web/eng/ cess_eng.html C Umponstira Department of Natural Resources and Environment, Naresuan University (NU), Phitsanulok, Thailand 60005 e-mail: umpons@hotmail.com URL: http//www.nu.ac.th/english/ V T Le : N T Ngoc : P H Viet Center for Environment and Technology for Sustainable Development (CETASD), Ha Noi University of Science, 334 Nguyen Trai, Thanh Xuan, Ha Noi, Vietnam V T Le e-mail: vothanhle76@yahoo.com URL: http://www.hus.edu.vn/?portal0home&cache0eDY3 +duB3Fyv9m2pL2sErKQhVEiSe3/yx6 +E7qa46VS23e48alvZMwiiaFhT5eGN 2756 Although no significant relationships between the mean concentrations of ambient O3 during the experimental period and the growth responses were observed for either species, multiple linear regression analysis suggested a good relationship between the biomass responses in each species and the O3 concentration, temperature, and relative humidity The cumulative daily mean O3 (ppb/day) could be indirectly predicted by NF/CF based on the dry weight ratio of biomass, mean air temperature, and relative air humidity Keywords Indicator plant Dose–response relationship Multiple linear regression analysis East Asia Abbreviations AIC Akaike information criteria CDMO Cumulative daily mean ozone (ppb/day) CF Charcoal filtered air DW Dry weight NF Non-filtered air O3 Ozone OTC Open-top chamber ppb Parts per billion (nL/L) RH Relative humidity (%) T Temperature in Celsius VPD Vapor pressure deficit (kPa) N T Ngoc e-mail: ngthngoc@yahoo.com URL: http://www.hus.edu.vn/?portal0home&cache0eDY3 +duB3Fyv9m2pL2sErKQhVEiSe3/yx6 +E7qa46VS23e48alvZMwiiaFhT5eGN P H Viet e-mail: vietph@hn.vnn.vn URL: http://www.hus.edu.vn/?portal0home&cache0eDY3 +duB3Fyv9m2pL2sErKQhVEiSe3/yx6 +E7qa46VS23e48alvZMwiiaFhT5eGN? M Wei School of Life Science and Technology, Shanghai Jiao Tong University (SJTU), 1954 Hua Shan Rd., Shanghai 200030, People’s Republic of China e-mail: wma@stju.edu.cn URL: http//en.sjtu.edu.cn/ Environ Monit Assess (2013) 185:2755–2765 Introduction Tropospheric ozone (O3) has been gradually and steadily increasing worldwide and is thus an environmental issue of great concern to both scientists and the public (Akimoto 2003; Emberson et al 2003; Ashmore et al 2006) Kohno (2005) reported that the daytime accumulated exposure over a threshold of 40 ppb of ozone (AOT40 ) for months in 1981 was about ppmh in Japan; however, it reached 13 ppmh in 2003 Nitrogen oxide (NOx) emissions in East Asia have rapidly increased in the recent years, surpassing those in North America and Europe (Akimoto 2003) This will affect the regional distribution of tropospheric O3 and its potential detrimental effects on vegetation Many O3 exposure experiments have suggested that ground level O3 is a potential threat to agricultural production, forest tree growth, and natural vegetation However, continuous monitoring and impact assessments of O3 in East Asia are far behind those of developed countries Heagle et al (1995) proposed that a smaller biomass ratio of an O3 sensitive variety (NC-S) of white clover (Trifolium repens L.) compared with a tolerant variety (NC-R) indicates that the plants were subject to high O3 stress However, Ball et al (1998) reported that simple linear regression had a low correlation coefficient for the dose responses in these cultivars applied in Europe, and they found that vapor pressure deficit (VPD) and temperature played important roles in the dose responses In contrast, Mills et al (2000) suggested that VPD and harvest interval were excluded by multiple linear regression analysis, but that NOx improved plant responses to O3 dose Although white clover is an important forage and cover crop in relatively cool temperate zones such as those found in North America and Europe, it is not native to tropical and warm temperate regions of Asia Additionally, white clover develops runners and continues to grow during its life cycle, which makes it difficult to measure dry matter production by the plant Therefore, it is necessary to examine alternative indicator plants to determine if they are applicable for assessment of the effects of O3 on local vegetation in Asia In this study, we described a simple O3 monitoring system for Asian countries from the Far East to southeastern Asian regions and attempted to generate a model for prediction of O3 concentrations in the field using Raphanus and Brassica Environ Monit Assess (2013) 185:2755–2765 Methods Cultivation materials A total of 29 varieties of four species of plants (Raphanus sativus, Brassica campestris, Phaseolus vulgaris, and Lactuca sativa) were exposed to SO2 or O3 in large open top chamber systems under natural light conditions at the Akagi Testing Center of the Central Research Institute of Electric Power Industry (CRIEPI) A large reduction in the relative biomass during the vegetative stage was found to be a sensitive indicator of O3 exposure when compared with clean air However, some species were also sensitive to SO2 As a result, we screened, radish R sativus cv Red Chime and rosette pakchoi or Chinese flat cabbage Brassica campestris var rosularis cv ATU171 as O3 sensitive indicator plants (those were not responsive to SO2) in 2003 (Kohno 2005) Apparent view of plants grown in OTC was shown in Fig Cultivation materials such as seeds (Takii Seed Co., Kyoto, Japan), fertilized soil mix (growers potting and bedding compost, 100 % 0–10 mm peat, N–P2O5– K2O0192–224–384 g/m3, pH 6.0, Sakata Seed Co., Japan imported from William Sinclair Horticulture Ltd., UK) and L white plastic pots with a drainage mesh (height011.5 cm, top diameter012.3 cm, bottom diameter08.5 cm) were distributed by CRIEPI to collaborative institutions to maintain uniformity of the basic experimental conditions Experimental plants were seeded in pots filled with a fertilized soil mix and then covered with a thin layer of soil mix to maintain ideal moisture conditions for Raphanus 2757 germination Two or three days after seeding, pots were introduced into mini-OTCs as described below Plants were thinned to two per pot at week after seeding and then to one plant per pot after another week Plants were harvested 2–4 weeks after introducing pots to the chambers depending on the different growing conditions in the locations After seeding or germination, a granular insecticide (5 % acephate) was spread on the surface of the pots A total of eight pots for each cultivar were arrayed in each chamber with three replicates each, giving a total of 24 plants for each experiment The leaves and edible roots of R sativus and the above ground portion of B campestris were harvested individually In this study, the total dry biomass of R sativus and top dry biomass of B campestris grown in charcoal filtered air (CF) and those grown in nonfiltered air (NF) were weighed and their dry weight ratios (NF/CF) were calculated A total of 29 experiments were conducted at nine locations: Japan (4 sites), China (1), Vietnam (1), and Thailand (3) in 2005 and 2006 Experimental sites Experiments in Japan were conducted at the CRIEPI Abiko campus, Abiko Chiba, and the CRIEPI Akagi Testing Center, Maebashi, Gunma, as well as at the campuses of the Kanagawa Environmental Research Center (KERC), Hiratsuka, Kanagawa and the Center for Environmental Science in Saitama (CESS), Kazo, Saitama Naresuan University conducted experiments at three different sites, the campus of Naresuan University at Phitsanulok, the campus of Rice Research Institute at Pathumtani, and a site close to a large stationary emission source at Lampang, Thailand Ha Noi University (CETASD) and Shanghai Jiao Tong University (SJTU) conducted experiments on the roofs of buildings at their institutions due to space limitations and security issues The climatic conditions, experimental periods, and experimental repetitions are summarized in Table Each location installed six chambers (three charcoal filtered (CFs) and three non-filtered (NFs) chambers) Brassica Mini-open top chamber (mini-OTC) system Fig View of Raphanus sativus cv Red Chime and Brassica campestris var rosularis cv ATU171 grown in OTC Open-top chamber (OTC) systems are commonly used to conduct exposure experiments for assessment of the effects of ambient air quality on plants Different types 269 Lampang VPD: vapor pressure deficit T: temperature in Celsius –: No data Pathumthani 45 Phitsanulok Thailand 17 Ha Noi Vietnam Shanghai 12 Hiratsuka, Kanagawa (KERC) China 12 540 Akagi, Gunma (CRIEPI) Kazo, Saitama CESS) 21 Abiko, Chiba (CRIEPI) Japan Elevation (m) Location Country 2006.03.08.–03.21 2006.03.21.–04.02 2006.03.13.–03.27 2006.02.22.–03.08 2006.02.28.–03.13 2006.02.15.–02.28 2006.01.31.–02.14 2006.01.09.–01.21 2006.03.03.–03.28 2005.12.14.–12.26 2006.02.08.–03.03 2005.10.22.–11.28 2005.09.06.–10.03 2005.09.20.–10.17 2005.08.24.–09.15 2005.09.13.–10.07 2005.08.19.–09.09 2005.09.16.–10.05 2005.07.29.–08.19 2005.09.01.–09.20 2005.08.11.–08.31 2005.09.17.–10.05 2005.07.15.–08.02 2005.08.13.–08.31 2005.07.15.–08.02 2005.09.15.–10.13 2005.06.17.–07.05 2005.08.11.–09.09 2005.07.13.–08.02 Experimental period Experiment Table Environmental condition in the experimental sites 12 13 14 14 13 13 13 12 12 25 23 27 37 27 22 24 28 21 25 20 20 18 18 18 18 18 28 29 20 Days 32.9 32.4 31.9 33.0 31.4 29.4 28.0 25.4 23.2 20.8 17.6 29.8 21.8 25.3 27.7 24.3 28.0 30.0 22.1 26.5 27.7 28.0 19.3 24.8 25.0 24.2 21.4 27.8 28.7 Mean temperature T (°C) 54.6 68.8 68.7 44.2 47.1 54.1 69.0 55.2 54.8 86.8 82.8 79.0 55.2 59.4 68.7 73.3 76.8 72.9 73.9 73.8 76.1 73.3 83.8 83.4 76.7 85.6 77.2 75.0 73.5 Mean relative humidity RH (%) 395 421 447 462 408 382 364 305 278 520 405 805 807 683 609 583 784 630 553 530 554 504 347 446 450 436 599 806 574 T x days (°C days) 1.66 2.12 2.15 1.34 1.50 1.84 2.46 2.17 2.36 4.17 4.70 2.65 2.53 2.35 2.48 3.02 2.74 2.43 3.34 2.78 2.75 2.62 4.34 3.36 3.07 3.54 3.61 2.70 2.56 RH/T (%/°C) 4.090 3.434 3.466 4.480 4.268 3.550 2.835 1.669 1.337 0.569 0.477 1.093 1.427 1.307 1.427 0.956 1.421 1.110 0.861 0.814 1.166 1.422 0.396 0.289 0.535 0.938 0.990 1.677 2.495 VPD kPa 0.3 0.4 1.1 0.2 7.7 1.5 2.0 3.5 0.3 4.0 2.3 2.1 5.1 3.1 2.4 3.8 3.5 4.0 0.4 0.4 0.1 0.2 0.3 0.5 0.8 0.6 0.5 0.3 0.2 Mean SO2 (ppb) 8.9 7.1 14.5 2.9 4.2 3.4 8.9 15.7 8.4 11.1 9.5 22.0 34.2 23.9 21.0 36.4 30.3 24.3 11.6 9.2 8.4 9.8 28 27 48 39 49 33 24 23 24 11 15 21 13 11 24 22 29 16 23 20 27 29 36 – 7.5 46 48 – 3.1 18 20 23 Mean O3 (ppb) 17.0 11.0 7.1 Mean NOx (ppb) 2.33 2.04 3.46 2.76 3.76 2.54 1.85 1.94 2.01 0.44 0.67 0.78 0.25 0.48 0.50 1.01 0.78 1.39 0.65 1.17 0.99 1.51 1.60 1.99 2.56 2.66 0.65 0.70 1.15 Cumulative mean daily O3 (ppb/day) 2758 Environ Monit Assess (2013) 185:2755–2765 Environ Monit Assess (2013) 185:2755–2765 120 CF NF 100 80 Ozone (ppb) and sizes of OTC systems have been developed in North American and European countries as well as in Japan We developed a mini-OTC modified and simplified from Aihara's model (Aihara and Takeda 2004) that was mobile and easy to set up Specifically, we replaced the DC type wind fan with a high static pressure electric fan (MRS18V2-D for 200 V or MRS18V2-B for 100 V; Oriental Motor Co Ltd., Japan) with an adjustable wind speed The chamber size was 60 cm (W)×60 cm (D)×120 cm (H), with an air duct of 22.5 cm (D)×60 cm (W)×120 cm (H) The air duct of the chamber was separated into three parts The top part was 45 cm high for filtering introduced air by passing it through packed layers of activated charcoal pellets The second portion, which was also 45 cm tall, contained a fan The bottom 30 cm consisted of a mixing and buffering space The entire system is shown in Fig 2759 60 CF= 8.2± 5.9 ppb NF= 80.6± 13.3 ppb Removal=89.8% 40 20 15 19 23 11 15 19 23 Time 11 15 19 23 11 Fig Comparison of O3 concentration in the charcoal filtered (CF) and non-filtered (NF) chamber after months of operation at Abiko, CRIEPI, Chiba, Japan The volume of the wind fan can be controlled and the maximum speed is 12 m per second; therefore, the air exchange rate varied from 3.1 to 5.8 times per minute At a wind speed of m per second, the air exchange rate was times per minute The air intake space of the charcoal filter chamber (CF) was packed with 10 kg of activated charcoal pellets with a to mesh size The efficiency for the removal of O3 after months of operation at the Abiko, CRIEPI, Japan site was 89.8 % (Fig 3) No charcoal filters were added to the NF chambers All parts used to build the mini-OTCs, weather monitoring devices and passive sampling systems were prepared and distributed by CRIEPI with the cultivation materials Active O3 (ppb, 24h) 60 50 40 30 20 y = 0.8486x + 1.9583 R² = 0.9283 10 0 10 20 30 40 50 60 70 Passive O3 (ppb) Fig View of mini-open top chamber system (1) air intake duct, (2) activated charcoal filter layer, (3) electric fan The arrows indicate air flow Fig Relationship between active and passive measurement of O3 during the experiments 2760 Environ Monit Assess (2013) 185:2755–2765 Table Dry biomass of Raphanus sativus and Brassica campestris grown in mini-OTCs at different locations Country Location Japan China Elevation Experiment Experimental (m) period Abiko, Chiba (CRIEPI) 21 Akagi, Gunma (CRIEPI) 540 Kazo, Saitama CESS) 12 Hiratsuka, Kanagawa (KERC) 12 Shanghai Vietnam Ha Noi 17 Thailand Phitsanulok 45 Lampang Pathumthani 269 3 4 3 3 3 2005.07.13.–08.02 2005.08.11.–09.09 2005.09.15.–10.13 2005.06.17.–07.05 2005.07.15.–08.02 2005.08.13.–08.31 2005.09.17.–10.05 2005.07.15.–08.02 2005.08.11.–08.31 2005.09.01.–09.20 2005.09.16.–10.05 2005.07.29.–08.19 2005.08.19.–09.09 2005.09.13.–10.07 2005.08.24.–09.15 2005.09.20.–10.17 2005.10.22.–11.28 2005.09.06.–10.03 2006.02.08.–03.03 2006.03.03.–03.28 2005.12.14.–12.26 2006.01.09.–01.21 2006.01.31.–02.14 2006.02.15.–02.28 2006.02.28.–03.13 2006.03.13.–03.27 2006.02.22.–03.08 2006.03.08.–03.21 2006.03.21.–04.02 Days Raphanus sativus 20 29 28 18 18 18 18 18 20 20 25 21 28 24 22 27 37 27 23 25 12 12 13 13 13 14 14 13 12 Brassica campestris var rosularis Dry NF/ biomass CF g/plant g/g p Dry NF/ biomass CF g/plant g/g p 1.012 0.731 1.877 0.866 1.149 0.415 0.324 0.290 0.056 0.168 0.417 0.696 0.185 0.715 0.472 0.268 0.472 0.444 0.574 0.896 – – – – – – – – – 0.396 0.052 0.001 0.968 0.006 0.266 0.702 0.008 0.783 0.098 0.316 0.185 0.575 0.476 0.685 0.270 0.524 0.918 0.423 0.290 – – – – – – – – – 0.553 0.551 0.970 0.396 0.379 0.178 0.185 0.221 0.016 0.172 0.238 0.667 0.128 0.538 0.294 0.156 0.205 0.297 0.420 0.504 0.483 0.183 1.428 0.599 0.252 0.252 0.301 0.423 0.095 0.221 0.922 0.692 0.081 0.515 0.309 0.426 0.558 0.002 0.011 0.058 0.128 0.950 0.197 0.401 0.421 0.115 0.324 0.058 0.049 0.001 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.954 0.766 0.779 0.996 0.899 0.925 1.019 0.628 0.964 0.923 1.038 0.909 0.935 1.055 1.034 1.090 0.953 0.991 0.963 0.952 – – – – – – – – – 0.868 0.987 0.955 0.870 0.929 0.954 0.908 1.059 0.750 0.884 0.920 0.891 0.992 1.095 0.922 1.064 0.883 0.828 0.907 0.870 0.768 0.814 0.798 0.673 0.750 0.813 0.751 0.757 0.526 Cultivar: Red Chime in Raphanus sativus and ATU171 in Brassica campestris var rosularis Dry biomass: total of top and hypocotyl for Raphanus and top for Brassica grown in char-coal filtered air (CF) Chamber replication was with plants in a chamber for each cultivar at any sites p: Significance between dry biomass in plant grown in char-coal filtered air (CF) and that in non-filtered air (NF) –: No data Measurements of climatic conditions and air quality Temperature and relative humidity were recorded using a data logger (Model TR/72U with a TR-3110 temperature and humidity sensor, T & D Corporation, Nagano, Japan) inside the chamber during the experiment The sensor was set in the out-flow air after the fan in the bottom of the chamber and was protected from direct solar radiation and water An Ogawa passive sampler (Model 3300, Ogawa Co., Kobe, Japan), which has a holder for two filters at both ends, was set inside the wall above the plants to collect air quality data during the experiment The O3, SO2, NO, and NOx (NO+NO2) were measured Environ Monit Assess (2013) 185:2755–2765 in all chambers All passive sampling filters were collected after the exposure experiments and sent to CRIEPI for chemical analysis of sulfate and nitrate by an ion chromatography and nitrite by a spectrophotometry to calculate concentrations of O3, SO2, NO, and NO2 (Hirano et al 2002) The active hourly ozone concentration was monitored with a UV absorption O3 analyzer (Model 12106, Dylec Co., Japan) and passive data was monitored by an Ogawa passive sampler at Abiko, Akagi, and Kazo in Japan The relationship between active and passive O3 data for the experimental period shown in Fig indicated a good correlation (Varns et al 2001; Delgado-Saborit and Esteve-Cano 2008) In this study, the concentrations of O3 from passive samplers in China, Thailand, and Vietnam were corrected based on this relationship 2761 observed in Thailand during the dry and hot season than at other sites Plant responses As shown in Table 2, plant biomass and responses as expressed by dry weight ratios of the NF/CF for both Raphanus and Brassica to ambient O3 varied greatly under the different weather conditions The maximum growth reduction of Raphanus was 37 % at CESS, in Kazo, Japan, while that of Brassica was 33 % in Lampang, Thailand Significant differences in dry biomass were observed between NF and CF However, there were many cases in which no significant differences were observed For 1.20 NFDW /CFDW (g/g) Statistics Excel add-in statistical software (Esumi Co Ltd., Tokyo, Japan) was used for statistical data analysis The significance of differences in dry biomass between CF and NF at the sites was analyzed by Tukey's t test Multivariate Statistics ver 6.0 was applied for multiple linear regression analysis Raphanus sativus cv Red Chime 1.40 Abiko 1.00 Akagi 0.80 Kisai Hiratsuka 0.60 Shanghai Ha Noi 0.40 0.20 0.00 10 20 30 40 50 60 Mean O3 (ppb) Results and discussion Brassica campestris var rosularis cv ATU171 1.40 Ambient conditions Abiko The mean temperature (T), relative humidity (RH), vapor pressure deficit (VPD), and air quality data including the concentrations of O3, SO2, and NOx are shown in Table As experimental sites were distributed from the temperate to the tropical zone, these variables varied greatly The mean concentrations of O3 ranged from to 49 ppb, and Akagi, Japan, and Lampang and Pathumtani, Thailand had higher O3 concentrations than the other sites In contrast, the concentrations of SO2 were below ppb at all sites and presumably had no effect on plant growth performance (Spranger et al 2004) The concentrations of NOx at the Shanghai and Ha Noi sites were higher than those at other sites Because high temperatures with low relative humidity caused a large VPD, greater VPD values were NFDW /CFDW (g/g) 1.20 Akagi Kisai 1.00 Hiratsuka 0.80 Shanghai Ha Noi 0.60 Phitsanulok 0.40 Lampang Pathumthani 0.20 0.00 10 20 30 40 50 60 Mean O3 (ppb) Fig Plant responses to ozone concentration expressed by dry biomass weight ratio in Raphanus sativus and Brassica campestris var rosularis NFDW: sum of dry weight in the tops and hypocotyls of Raphanus or tops of Brassica grown in nonfiltered air chambers (NF) CFDW: sum of dry weight in the tops and hypocotyls of Raphanus or tops of Brassica grown in activated charcoal-filtered air chambers (CF) DW: dry weight (g/plant) 2762 Environ Monit Assess (2013) 185:2755–2765 example, at Akagi, only one case of R sativus and no cases of B campestris differed significantly In contrast, B campestris showed significant differences at all locations investigated in Thailand Since none of the individual experimental data collected from any locations differed significantly, poor relationships was observed between the NF/CF ratio and mean O3 concentration at all sites (Fig 5) These findings are similar to those of studies of white clover conducted in Europe and the United States These results likely reflect the fact that the plant response to O3 can be modified by environmental conditions such as air temperature and relative humidity (Ball et al 1998; Heagle et al 1995; Heagle and Stefanski 2000) Multiple linear regression analysis Since single linear regression analysis failed to show a good correlation between the mean O3 concentration during the exposure experiments and plant growth responses, we applied multiple linear regression analysis to the data set of plant growth responses expressed by the dry biomass weight ratio of NF/CF and environmental conditions Using a round-robin combination of parameters, we attempted to identify combinations of parameters showing smaller values of AIC (Akaike 1974) with higher significance As shown in Table 3, increasing the number of parameters generated a higher correlation coefficient of the equation for predicting the cumulative daily mean O3 (CDMO, ppb/day) In contrast, statistical significance was reduced as the number of parameters investigated decreased Ball et al (1998) pointed out that VPD was important; however, Mills et al (2000) reported the opposite Our analysis suggested that RH/T (mean relative humidity/mean temperature during the cultivation period) could be a simple parameter that could be used in place of complicated VPD calculations Table Results of multiple linear regression analysis Plant Cumulative daily mean O3 (CDMO, ppb/day) AIC R2 p 29.9 0.6448 0.1540 Raphanus 5.5991−0.9503*(NF/CF)−0.0031*(TxDays)−1.1628*(RH/T)−0.0032*NOx(ppb)+0.0091*SO2 (ppb)−0.3468*VPD−0.0559*T+0.0466*RH 6.0702−1.1266*(NF/CF)−0.0028*(TxDays)−0.5838*(RH/T)−0.0076*NOx(ppb)−0.0141*SO2 (ppb)−0.4221*VPD 5.2647−1.0278*(NF/CF)−0.0033*(TxDays)−0.4252*(RH/T)−0.0057*NOx(ppb)+0.0056*SO2 (ppb) 5.2435−1.0193*(NF/CF)−0.0033*(TxDays)−0.4221*(RH/T)−0.0049*NOx(ppb) 27.5 0.5167 0.0386 5.4410−0.6262*(NF/CF)−0.0041*(TxDays)−0.4269*(RH/T)−0.0467*SO2(ppb) 38.2 0.5017 0.0256 6.1019−0.7117*(NF/CF)−0.0035*(TxDays)−0.5660*(RH/T)−0.0704*SO2(ppb)−0.3965*VPD 38.4 0.5445 0.0339 Brassica 28.7 0.5852 0.0818 29.5 0.5168 0.0840 6.1127−1.1465*(NF/CF)−0.0028*(TxDays)−0.5896*(RH/T)−0.0095*NOx(ppb)−0.4170*VPD 26.7 0.5846 0.0390 6.6551−1.0578*(NF/CF)−0.0041*(TxDays)−0.5880*(RH/T)−0.3414*VPD 37.2 0.5268 0.0181 3.7830−1.0447*(NF/CF)−0.0030*(TxDays)−0.0061*VPD 40.7 0.3765 0.0508 5.8903−0.8756*(NF/CF)−0.0044*(TxDays)−0.4557*(RH/T) 36.5 0.4936 0.0107 −0.1797+0.8027*(NF/CF)−0.0034*(TxDays)−0.0513*(RH/T)−0.0184*NOx(ppb)+0.0996*SO2 50.3 0.7944 0.0001 (ppb)+0.1104*VPD+0.1095*T−0.0061*RH 50.2 0.7617 0.0000 3.0841+0.6435*(NF/CF)−0.0028*(TxDays)−0.3558*(RH/T)−0.0228*NOx(ppb)+0.0767*SO2 (ppb)+0.2360*VPD 4.7293+0.0906*(NF/CF)−0.0028*(TxDays)−0.5971*(RH/T)−0.0301*NOx(ppb)+0.0931*SO2(ppb) 50.7 0.7388 0.0000 4.9901+0.0075*(NF/CF)−0.0030*(TxDays)−0.6222*(RH/T)−0.0180*NOx(ppb) 51.3 0.7130 0.0000 5.2408−0.3009*(NF/CF)−0.0040*(TxDays)−0.5180*(RH/T)+0.0233*SO2(ppb) 60.7 0.6372 0.0000 3.3436+0.4594*(NF/CF)−0.0038*(TxDays)−0.2627*(RH/T)+0.0177*SO2(ppb)+0.2482*VPD 60.5 0.6641 0.0001 3.0325−0.6644*(NF/CF)−0.0030*(TxDays)−0.3378*(RH/T)−0.0120*NOx(ppb)+0.2733*VPD 50.1 0.7448 0.0000 3.3285+0.4944*(NF/CF)−0.0037*(TxDays)−0.2668*(RH/T)+0.2515*VPD 58.6 0.6630 0.0000 2.2036+0.4902*(NF/CF)−0.0034*(TxDays)+0.3966*VPD 58.0 0.6466 0.0000 5.2547−0.2682*(NF/CF)−0.0039*(TxDays)−0.5280*(RH/T) 58.9 0.6352 0.0000 AIC: Akaike Information Criteria (Akaike 1974) Environ Monit Assess (2013) 185:2755–2765 2763 Mills et al (2000) also introduced NOx into the equation for the dose response of white clover to assess ambient air quality; however, this was not a significant factor for the prediction model used in the present study The use of field grown white clover containing contrasting genotypes with different sensitivities to O3 is a feasible system for O3 analysis as it does not require any specific mechanical monitoring devices Plants grown in mini-OTCs with charcoal filtered air and non-filtered air will provide more accurate data regarding the responses to air quality If several parameters for air quality and weather conditions are monitored, the system becomes even more effective for assessing the effects of ambient air quality Considering the state of ambient air quality monitoring in developing Raphanus sativus cv Red Chime 3.50 Calculated CDMO (ppb/day) 3.00 y = 0.4917x + 0.5655 R² = 0.4936 2.50 2.00 1.50 1.00 0.50 0.00 0.00 0.50 1.00 1.50 2.00 2.50 3.00 Observed CDMO (ppb/day) Brassica campestris var rosularis cv ATU171 3.50 3.00 Calculated CDMO (ppb/day) Fig Relationship between observed and predicted values of cumulative daily mean O3 (CDMO, ppb/day) for Raphanus sativus and Brassica campestris var rosularis countries, such a simple system could be very useful for expanding monitoring activities The equations provided below generated by multiple linear regression analysis have been simplified as much as possible and include only the lowest possible number of parameters Specifically, they include the dry weight ratio of plants in the NF to CF, mean temperature (T) and mean relative air humidity (RH) during cultivation (Table 3) As shown in Fig 6, the correlation coefficient and statistical significance for the Raphanus was lower than that for Brassica This was because there was a smaller number of observed data for Raphanus, as no data were obtained from Thailand due to unfavorable growth conditions Therefore, we omitted the cultivation experiments conducted in Thailand from the analyses 2.50 2.00 1.50 1.00 y = 0.6331x + 0.5743 R² = 0.6352 0.50 0.00 0.00 0.50 1.00 1.50 2.00 2.50 Observed CDMO (ppb/day) 3.00 3.50 4.00 2764 Environ Monit Assess (2013) 185:2755–2765 CDMO (ppb/day) 2.00 Brassica campestris Fig Correlation between estimated values of cumulative daily mean O3 (CDMO, ppb/day) of Raphanus sativus and those of Brassica campestris var rosularis 1.50 1.00 y = 0.8199x + 0.2039 R² = 0.923 0.50 0.00 0.00 0.50 1.00 1.50 2.00 2.50 Raphanus sativus CDMO ppb=dayị ẳ 5:8903 0:8756 NFDW =CFDW ị 0:0044 Â ðT Â DayÞ À 0:4557 Â ðRH =T Þ ðR2 ¼ 0:4936; p ¼ 0:0107Þ for Raphanus sativus cv: Red Chime 1ị CDMO ppb=dayị ẳ 5:2547 0:2682 Â ðNFDW =CFDW Þ À 0:0039 Â ðT Â DayÞ 0:5280 RH =T ị R2 ẳ 0:6352; p ¼ 0:0000Þ for Brassica campestris var: rosularis cv: ATU171 ð2Þ where CDMO (cumulative daily mean ozone) NFDW CFDW DW Day RH T daily mean O3 concentration (ppb)/experimental period (days) dry biomass of plants grown in the non-filtered air chamber (NF) dry biomass of plants grown in the activated charcoalfiltered air chamber (CF) total dry weight in Raphanus and top in Brassica total days after the placement of pots in the chamber to harvest mean relative humidity (%) for cultivation of plants grown in the chamber mean temperature (°C) for cultivation of plants grown in the chamber The values predicted using either the equation from Raphanus (Eq 1) or Brassica (Eq 2) can be converted to the other using the equation shown in Fig To evaluate this simple prediction model, calculation of CDMO was applied to the data set of white clover generated by Heagle and Stefanski (2000), assuming that the maximum temperature would be equivalent to T and the midday relative humidity equivalent to RH The O concentration (ppb) was calculated from SUM00 (accumulated dose of O3) for 28 days during the white clover cultivation period, and the forage ratio (percent) was the same as the dry weight ratio Multiple linear regression reproduced similar results for the white clover and Raphanus or Brassica Conclusions Multiple linear regression analysis generated effective equations for predicting the O3 concentration from the mini-OTC experiment using the O3 sensitive cultivars of R sativus and B campestris The method requires determination of the dry weights of R sativus cv Red Chime or B campestris var rosularis cv ATU171 grown in a non-filtered air chamber (NF) and an activated charcoal filtered air chamber (CF) and recording only the mean temperature and relative humidity Either Eq (1) for Raphanus or (2) for Brassica will be able to predict the mean concentration of O3 Environ Monit Assess (2013) 185:2755–2765 from the cumulative daily mean O3 (CDMO) (ppb/day) However, more extensive evaluation experiments are necessary to increase the accuracy of the mean O3 concentration predicted by this model Acknowledgments This research was conducted with financial support from the Global Environmental Research Fund (C-7), Ministry of the Environment, Japan We greatly appreciate the collaboration and arrangements with Dr Tran Thi Ngoc Lan, University of Natural Sciences, Ho Chih Minh City, Vietnam, and Dr Yasuaki Maeda, JICA Expert, Ministry of the Natural Resources and Environment, Ha Noi, Vietnam We also appreciate Mr Ideta, Techno Systems Co Ltd., Tokyo, Japan for his chemical analysis of air quality samples Additionally, we thank the students and staff of the universities and CERES Inc at Akagi Testing Center, CRIEPI for their support with the experiments Finally, we thank Dr M Frei, University of Bonn, for his critical review and editorial suggestions regarding this manuscript References Aihara, K., & Takeda, M (2004) Development of portable open top chamber Bulletin of Kanagawa Environmental Research Center, 27, 77–81 (in Japanese) Akaike, H (1974) A new look at the statistical model identification IEEE Transactions on Automatic Control, 19(6), 716–723 Akimoto, H (2003) Global air quality and pollution Science, 302, 1716–1719 Ashmore, M., Toet, S., & Emberson, L (2006) Ozone—a significant threat to future world food production? 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