A New and Simple Visual Technique Based on Indigo Dye for Determination of Ozone in Ambient Air

A New and Simple Visual Technique Based on Indigo Dyefor Determination of Ozone in Ambient Air

Gabriel Garcia & Andrew George Allen &

Arnaldo Alves Cardoso

Received: 21 August 2013 /Accepted: 4 December 2013 /Published online: 3 January 2014# Springer Science+Business Media Dordrecht 2014

Abstract Episodes of pollution resulting from highconcentrations of environmental ozone frequently occurin different parts of the world. The ozone can affecthuman health, natural vegetation, and agricultural pro-ductivity. The monitoring of ozone concentrations isessential to aid investigation of its effects and it is alsorequired to assess progress in public management of thispollutant. A new effective and simple technique is pre-sented for the determination of ambient ozone concen-trations using a visual procedure. The method is basedon the reaction between the dye indigo and ozone, withthe formation of colorless products. The bleaching in-tensity is proportional to the amount of ozone. Anindigo color standard scale was developed with theutilization of digital image-based (DIB) calibration andprinted as a wheel-chart test kit. Ozone sampling isperformed using a passive sampler containing a filterimpregnated with indigo. The amount of reacted ozonecan be determined by visual comparison using thewheel-chart test kit. The method enables determinationof ozone concentrations from 2 to 97 ppb, with intervalsof 3 ppb. It does not require an energy source or anypost-sampling chemical treatment or analysis, and theozone concentration can be known immediately, in situ,at the end of the sampling period. The method offers

substantial advantages in large-scale mapping and mon-itoring of ozone or measurements concerning occupa-tional exposure to ozone.

Keywords Ozone . Ozone determination . Passivesampling . Indigo blue . Visual method

1 Introduction

In the lower troposphere, ozone is formed during pho-tochemical reactions involving volatile organic com-pounds and oxides of nitrogen. Ozone production oc-curs when NO2 is photolyzed at wavelengths <400 nm(Kley et al. 1999; Finlayson-Pitts and Pitts 2000). Am-bient ozone concentrations frequently show a distinctdiurnal cycle, with low levels in the early morning and apeak around noon. Background outdoor ozone concen-trations appear to be increasing in many parts of theworld, mainly due to increased emissions of ozoneprecursors from road transport (Janach 1989; Colbeckand Mackenzie 1994; Varotsos et al. 2013). Outdoorozone is the major source of indoor ozone, althoughsources such as ozone generators, electrostatic aircleaners, photocopiers, and laser printers can be respon-sible for elevated indoor ozone concentrations (Cox2003; Caballero et al. 2007).

Ozone is a powerful oxidant, and human exposure tothe gas can cause respiratory irritation and interferencein the body’s defense mechanisms. Wider environmen-tal impacts associated with high ozone levels includereductions in crop yields and damage to natural

Water Air Soil Pollut (2014) 225:1836DOI 10.1007/s11270-013-1836-2

G. Garcia :A. G. Allen :A. A. Cardoso (*)Departamento de Química Analítica, Instituto de Química,Universidade Estadual Paulista-UNESP,Rua Professor Francisco Degni 55, Quitandinha, Araraquara,Sao Paulo 14800-900, Brazile-mail: [email protected]

vegetation and other materials (Gouveia and Fletcher2000; Salmon, et al. 2000; Bell et al. 2004; Gravanoet al. 2004; Tagner et al. 2005; Weschler 2006). Thenational ambient air quality guidelines established bythe US EPA stipulate a primary standard of 75 ppb forground-level ozone, and the WHO Air Quality Guide-lines 2005 global update sets the guideline value forozone at 100 μg m−3 (about 47 ppb) for a daily maxi-mum 8-h mean (WHO Regional Office for Europe2006). In Brazil, CONAMA (the Brazilian NationalCouncil of the Environment) has set an ozone standardof 75 ppb, with only one annual exceedence allowed(Brasil 1990).

The monitoring of ozone concentrations is essen-tial to aid investigation of its effects on humans andmaterials. It is also required to assess progress inpublic management of this pollutant. The availabil-ity of suitable analytical methods for ozone deter-mination is therefore of considerable importance.Analyzers based on ultraviolet light absorptionand chemiluminescence are widely used to measurelow concentrations of ozone at ground level. Al-though these methods enable determination ofozone concentrations in real time, the instrumentsemployed tend to be large, heavy, and expensive.Chemical methods are an alternative for low-costmonitoring, and normally involve the oxidation of areagent and measurement of the product formed(Koutrakis et al. 1993). Common drawbacks ofchemical techniques are interferences from otheroxidant species, as well as poor sensitivity formeasurements at ambient ozone concentrations.Long-term observations are often employed tomap the behavior of pollutants in a given area,and here passive samplers can offer advantagesincluding small size and weight, low cost, andminimal maintenance. The absence of any needfor a power source during sample collection enablesexpansion in the number of sampling sites and thusthe area studied (Górecki and Namiesnik 2002,Esteve-Turrilhas et al. 2007, Yu et al. 2008, Tuduriet al. 2012).

A few chemical methods were recently developedwith ozone determination based on its reaction withdyes such as indigo and orange I (Maruo et al. 2009,2010, Adema et al. 2012). In recent work, we developeda new passive sampler for ground-level ozone determi-nation, based on the discoloration of indigotrisulfonatedye. In this reaction, ozone adds itself across the C = C

double bond of the dye molecule, resulting in cleavageof the bond and the formation of yellow and colorlessproducts. Therefore, the degree of indigo discolorationis directly proportional to the concentration of ozoneconcentration. The use of this particular system enablesozone measurements to be made over periods as short asa few hours, permitting characterization of diurnal con-centration trends (Garcia et al. 2010).

All of these chemical methods, supported by passivesampling, rely on the advantages of electricity-free sam-pling to be successfully and easily applied for outdoor orindoor measurements, and also for assessments of per-sonal exposure to ozone. However, the measurementsrequire analytical procedures, necessitating electricity,laboratory facilities, and trained personnel, as well asconsiderable care during sample preparation. In thepresent work, we propose an alternative determinationprocedure to the previously developed passive sampler,with the direct visual determination of the ozone con-centration after sampling, supported by digital imageanalysis.

Image processing and analysis has been used sincethe 1960s in areas such as geology, agriculture, biology,and medicine. Image analysis in chemical applicationsis a more recent development, and has been mainlyassociated with microscopy techniques (Geladi 1992).In the last decade, new methods have been reported forchemical analysis involving color measurementsemploying digital image-based (DIB) procedures. Dig-ital images can be easily acquired using CCD cameras(Maleki et al. 2004; Gaião et al. 2006; Safavi et al.2007), flatbed scanners (Bennett et al. 2012), and cellphones (Iqbal and Bjorklund 2011). The 24-bit red,green, and blue (RGB) color system can provide up to16.7 million color variations, enabling digital imageanalysis to be used in a variety of quantitative determi-nations. These include measurements of metal ion con-centrations and acidity in aqueous solutions as well as ina wide spectrum of complex matrices such as physio-logical serum, antidepressant drugs, iron meteorites, andwines (Lyra et al. 2009; Tôrres et al. 2011; Zamora et al.2011; Díaz et al. 2012; Lopez-Molinero et al. 2013).

The objective of the present study was therefore todevelop a method for the in situ quantification ofground-level ozone collected using indigo dye-basedpassive samplers (Garcia et al. 2010). The ozone con-centration was obtained by visual comparison of thecolor of sample filters with a standard scale constructedby image processing.

1836, of 9 Water Air Soil Pollut (2014) 225:1836

2 Materials and Methods

2.1 Passive Samplers Experimental Protocol

Passive samplers were constructed using sections of38 mm polycarbonate filter holders (Millipore), withPTFE membrane filters employed as turbulence barriers(0.45 μm pore size, 175 μm thickness, 38 mm diameter,Millipore). The diffusion path length was 11.0 mm. Thesorbent supports were Whatman no. 41 cellulose filters(Garcia et al. 2010).

The indigo coating solution was prepared by adding12.4 mg of potassium indigotrisulfonate (CAS number67627-18-3, Aldrich) to a 10 mL volumetric flask con-taining 5 mL of ethylene glycol, with stirring, anddiluting to 10 mL. Working solutions were preparedon a daily basis. Each cellulose filter was impregnatedusing an 80.0 μL aliquot of 2.0×10−3 mol L−1 indigosolution, applied dropwise to the center of the filter, withthe solution spreading throughout the filter by capillaryaction. The experimental protocol has been described indetail by Garcia et al. (2010).

2.2 Principle of Ozone Determination Using the PassiveSamplers

Three passive samplers and one field blank were used foreach measurement of ambient ozone, with an exposureperiod of 8 h. The field blank was a passive sampler thatwas kept sealed during the sampling period. The concen-tration of ozone was determined from the degree of dis-coloration of the indigo reagent present in the filter, calcu-lated using Ini–Inf , where Ini is the amount of indigo (inmoles) in the field blank and Inf is the mean of the amountof indigo (in moles) in the three replicate filters.

The mean ozone concentration during sampling can beobtained based on Fick’s first law of diffusion, as follows:

Coz ¼ Inoz z=Doz air πr2t

� �; ð1Þ

where Coz is the ozone concentration in ambient air (inmoles per cubic centimeter), Inoz is the amount of ozone(inmoles) that reactedwith the dye, Doz air is the coefficientof diffusion of ozone in air, 0.144 cm2 s−1 (Weast 1974),πr2 is the cross-sectional area of the passive sampler (insquare centimeters), z is the diffusion path (in centimeters),and t is the sampling time (in seconds). The passivesampler has a well-defined geometry, with πr2=11.34 cm2 and z=1.1 cm. Considering the equimolar

stoichiometry of the reaction (1 mol of indigo: 1 mol ofozone), Eq. (1) can be rewritten as follows:

Coz ¼ 8:0� 10−10Inozt: ð2ÞAmbient ozone concentrations are frequently

expressed in terms of parts per billion by volume. Since1 mol of a gas occupies 24.45 L at 1.0 atm and 298 K,the ozone concentration (Coz, in moles per cubic centi-meter) could be converted to volume units using thefollowing expression:

Coz ppbv ¼ 2:0� 104Inozt: ð3ÞThe sampler was calibrated using field measure-

ments made over a period of 1 year in parallelwith a commercial ozone analyzer (Garcia et al.2010). A linear relationship was obtained, de-scribed as follows:

Coz ppbv ¼ 0:88 O3½ �uv þ 1:66; ð4Þwhere Coz ppbv is the ozone concentration mea-

sured using the passive samplers, and [O3]uv is theconcentration obtained from the photometric ozoneanalyzer. Equations (3) and (4) can be readilycombined to give:

O3½ � ¼ 2:72� 104Inoz t–1:89 ð5Þ

Table 1 Intensity of color for indigo standards at 30 levels (1 gTunit=5.25×10−9 mol of indigo)

gT nin (mol) gT nin (mol)

1 5.25×10−9 16 8.40×10−8

2 1.05×10−8 17 8.93×10−8

3 1.58×10−8 18 9.45×10−8

4 2.10×10−8 19 9.98×10−8

5 2.63×10−8 20 1.05×10−7

6 3.15×10−8 21 1.10×10−7

7 3.68×10−8 22 1.16×10−7

8 4.20×10−8 23 1.21×10−7

9 4.73×10−8 24 1.26×10−7

10 5.25×10−8 25 1.31×10−7

11 5.78×10−8 26 1.37×10−7

12 6.30×10−8 27 1.42×10−7

13 6.83×10−8 28 1.47×10−7

14 7.35×10−8 29 1.52×10−7

15 7.88×10−8 30 1.58×10−7

Water Air Soil Pollut (2014) 225:1836 of 9, 1836

Equation (5) can then be used to determine the con-centration of ambient ozone (in parts per billion byvolume) for a passive sampler exposed for a samplingperiod of t seconds.

2.3Mathematical Construction of Indigo Standard Scale

The cellulose filter was impregnated with 80 μLof 2.0×10−3 mol L−1 indigo solution (equivalent to1.6×10−7 mol of indigo). Considering the equimo-lar reaction stoichiometry, the amount of indigothat has reacted at the end of sampling is givenas follows:

Inoz ¼ ΔgT ¼ Ini–In f ; ð6Þwhere gT is the color intensity of the filter, Ini is the

amount of indigo (in moles) in the field blank filter, andInf is the amount of unreacted indigo (in moles) presentin the filter after sampling.

Indigo dye can lose part of its color during exposurein the field, as a result of adverse environmental condi-tions such as strong sunlight and heat. This meant that itwas not feasible to use filters containing the dye directlyas color standards in visual comparisons. To resolve this

Fig. 1 Digital images of the triplicates prepared in the laboratoryfor each gT color intensity level (1 to 8, 10, 12, 14, 16, 18, 20, 22,and 24)

Table 2 Average RGB code values, and standard deviations (SD), obtained by analysis of digital images of the triplicates prepared for eachgT level of the indigo standard color scale

gT Red Green Blue

Average SD Average SD Average SD

1 235.0 3.701 248.3 2.9 253.7 0.8

2 227.9 3.672 246.7 3.1 254.1 0.3

3 221.0 1.938 244.1 1.7 254.2 0.1

4 214.0 1.521 241.0 1.8 254.2 0.1

5 204.8 1.671 235.0 2.0 254.2 0.1

6 197.8 1.066 230.2 0.6 254.0 0.3

7 194.3 1.188 231.5 0.7 254.2 0.01

8 190.0 1.966 229.7 1.7 254.1 0.03

10 181.3 1.663 224.2 1.3 254.2 0.01

12 172.5 2.718 219.2 2.1 254.1 0.04

14 157.1 5.498 208.3 3.4 253.9 0.07

16 153.6 1.246 206.6 0.3 253.9 0.1

18 152.3 1.908 205.1 0.9 253.8 0.2

20 143.8 1.406 198.0 0.7 253.3 0.5

22 137.8 4.765 193.0 3.0 252.3 1.8

24 132.2 3.022 189.4 1.2 251.3 1.7


problem, the colors of the filters containing indigo werereproduced as printable digital images. A set of filterswere prepared containing different amounts of indigo inthe range from 1.6×10−7 to 5.25×10−9 mol (close to theminimum measurable amount of dye). Each filter wasassigned a color intensity (gT) proportional to theamount of dye present in the filter (one gT unit=5.25×10−9 mol).

A total of 30 different levels of indigo wereemployed, starting at 5.25×10−9 mol and increasing inincrements of 5.25×10−9 mol, up to a maximum of1.58×10−7 mol. The values of the resulting indigo stan-dard scale are shown in Table 1.

3 Experimental Procedures and Results

3.1 DIB Calibration of Indigo Standard Color Scale

In the laboratory, filters were prepared at 16 differentindigo intensity (gT) levels (1 to 8, 10, 12, 14, 16, 18,20, 22, and 24). These filters were prepared in triplicateby impregnation of the cellulose with the amounts ofindigo indicated in Table 1, obtained using dilutions of a0.001905mol L−1 indigo stock solution. The filters werearranged in two columns, with the triplicates for eachlevel indicated by the level number at the left side ofeach column, and then scanned using a Hewlett Packard

a b

Fig. 2 Relationships obtained between the red (a) and green (b) color code values and the amount of indigo impregnated in the filters

Table 3 RGB code values calculated for each gT color intensity level from the analytical calibration curves (1 gT unit=5.25×10−9 mol)

gT Red Green Blue gT Red Green Blue

1 237 245 254 16 156 207 254

2 228 242 254 17 152 204 254

3 220 240 254 18 149 202 254

4 212 237 254 19 146 199 254

5 206 235 254 20 143 197 254

6 200 232 254 21 141 194 254

7 194 230 254 22 138 192 254

8 189 227 254 23 135 189 254

9 184 224 254 24 133 187 254

10 179 222 254 25 131 184 254

11 175 219 254 26 128 182 254

12 170 217 254 27 126 179 254

13 167 214 254 28 124 177 254

14 163 212 254 29 122 174 254

15 159 209 254 30 120 171 254


a

b

Fig. 3 Wheel-chart test kitdesigned for in situ visualozone determination. a Indi-go standard color scale with30 gT levels, printed on thelower paper disk; b Instruc-tions for use and calibrationtable printed on the upperpaper disk


Model G4050 scanner. The digital image acquired isshown in Fig. 1.

A DIB calibration was performed to obtain calibra-tion curves for RGB color codes from the indigo stan-dards impregnated in the cellulose filters. Image J soft-ware was used to determine the average values of thethree RGB color codes that together described the meancolor of each set of filters prepared in triplicate. Thesevalues are presented in Table 2, together with the corre-sponding standard deviations. Values for the B (blue)code showed little variation among the different levels,with a small decay (less than 2%) at the end of the scale,so the B code value was considered to be constant at 254(the mean value). Analytical curves were constructed byplotting the R and G coordinates against gT level inten-sity. These curves employed 16 points (n=3 for eachintensity level) in the nin range from 5.25×10−9 to 1.58×10−7 mol of indigo dye. Figure 2 illustrates the relation-ships obtained between the color code values and theamounts of indigo impregnated in the filters (nin), andEqs. (7) and (8) describe the R and G calibration curves,respectively.

R ¼ 156:4 e −nin=1:351� 10−8� �þ 19:52 e −nin=2:092� 10−8

� �þ 71:44

ð7Þ

G ¼ 247:2–4:805� 108nin ð8Þ

3.2 Digitalization of the Indigo Standard Color Scale

Considering the B coordinate to be constant and equal to254, and the R and G coordinates to be described byEqs. (5) and (6), it was possible to determine the R, G,and B values corresponding to the gT color intensity forany amount of indigo. The color intensity was calculat-ed as R, G, and B coordinates for the 30 levels of gTranging from 5.25×10−9 to 1.58×10−7 mol of indigo(Table 3). CorelDrawX5 software was then used to printa color scale chart with the same colors shown by thefilters containing the different amounts (nin) of indigo.The printed scale could be used to determine nin (moleof indigo in a filter) by comparison between the colorintensity of the filter and the colors of the printed scale.

3.3 Visual Ozone Determination Procedures

As described previously (Garcia et al. 2010), the amountof indigo consumed by reaction with ozone duringsampling was defined as the difference between theamounts of indigo remaining in the field blank and theexposed filter papers. The quantity of consumed indigowas then used to calculate the average ozone concentra-tion. The visual ozone determination technique present-ed here followed the same procedure.

Using visual comparison, it was first necessary toidentify the gT levels that matched the colors of the fieldblank filter (gTb) and the exposed sample filter (gTs).Each level was associated with a specific amount ofindigo (Table 3), and subtraction gave the value of Inoz,the amount of dye consumed by ozone, described byEq. 9. Then, the concentration of ozone can be calculat-ed applying Inoz (the amount of reacted indigo) inEq. (5).

Inoz ¼ ΔgT � 5:25� 10−9 ¼ gTb field blankð Þ–gTs exposed sampleð Þð9Þ

3.4 Development of Wheel-Chart Test Kit

CorelDraw X5 software was used to design a wheel-chart test kit (shown in Fig. 3) for in situ visual deter-mination of ozone concentrations according to the pro-cedure described previously. The kit included a printed

Table 4 Comparison of ambient ozone concentrations measuredusing visual and spectrophotometric techniques

Ozone concentration (ppbv)

Spectrophotometric Visual

9.3 8

21.6 22

23.2 22

24.6 22

28.8 29

32.9 29

37.8 39

39.8 39

49.2 46

54.9 56


indigo color scale (Fig. 3a) and instructions for thecorrect visual determination of average ozone concen-trations (Fig. 3b) with employment of Eqs. 9 and 5,allowing application of any sampling time in the ozoneanalysis by the passive sampling.

3.5 Comparison of Spectrophotometric and VisualDeterminations

The application of the visual ozone determinationtechnique employing the proposed test kit wasevaluated in ten measurements of ambient ozoneconcentrations with the passive sampler, for 8-hsampling time periods, between April and Septem-ber 2011. The measurements were performed un-der different environmental conditions (in terms ofsolar radiation and humidity) in order to samplethe widest possible range of ozone levels. Eachozone measurement was made using both determi-nations. At first, the filters resulting from ozonereaction were submitted to the new visual tech-nique, carefully handled to avoid losses of theremaining dye. Then, the same filters were submit-ted to the spectrophotometric determination (Garciaet al. 2010). Thus, two average ozone concentra-tions were obtained for the same collection, usingdifferent techniques. The results (Table 4) werethen statistically compared by application of thepaired t test. Since the calculated t value (1.74)was less than the critical t value corresponding to9 degrees of freedom (2.262), at a 95 % confidencelevel, the two methods were considered statisticallyindistinguishable.

4 Conclusions

A new highly effective and simple technique is present-ed for the determination of ambient ozone concentra-tions using a visual procedure. The wheel-chart test kitdeveloped is inexpensive, straightforward, compact, andeasily deployed for indoor or outdoor measurements. Itdoes not require an energy source, and no sample treat-ment or chemical analysis is necessary post-sampling,so that the ozone concentration can be known immedi-ately, in situ, at the end of the sampling period. The newtechnique also complies with the concentrationrange for ozone measurements, as laid out in the WHOGlobal Update of 2005. Therefore, the method offers

substantial advantages in applications such as large-scale mapping and monitoring of ozone, especially inremote areas that lack installed infrastructure or energysupplies, and assessments of indoor and outdoor airquality, including occupational exposure to ozone. Animportant consideration is that technicians with special-ized chemical knowledge are not required during themeasurements. The visual technique could be extendedto ozone measurements using active sampling withanalysis based on the indigo reaction (Felix et al.2006). The digital image-based calibration procedurewould also permit the development of software de-signed to perform ozone determinations using imagesacquired by cell phone cameras.

Acknowledgments The authors gratefully acknowledge the fi-nancial support of CNPq (Brazilian National Council for Scientificand Technological Development) and FAPESP (State of São PauloResearch Foundation).

References

Adema, E. H., Heeres, P., Rahajuningsih, H. A., & Rineksa, S.(2012). The determination of ozone in ambient air with freehanging filters as passive samplers. Water, Air, and SoilPollution, 223, 5719–5725.

Bell, M. L., McDermott, A., Zeger, S. L., Samet, J. M., &Dominici, F. (2004). Ozone and short-term mortality in 95US urban communities, 1987–2000. Journal of the AmericanMedical Association, 292(19), 2372–2378.

Bennett, W. W., Teasdale, P. R., Welsh, D. T., Panther, J. G., &Jolley, D. F. (2012). Optimization of colorimetric DET tech-nique for the in situ, two-dimensional measurement ofiron(II) distributions in sediment porewaters. Talanta, 88,490–495.

Brasil (1990). Resolução no. 003, Conselho Nacional de MeioAmbiente—CONAMA. http://www.mma.gov.br/port/conama/res/res90/res0390.html. Accessed 17 April 2013

Caballero, S., Galindo, N., Pastor, C., Varea, M., & Crespo, J.(2007). Estimated tropospheric ozone levels on the southeastSpanish Mediterranean coast. Atmospheric Environment,41(13), 2881–2886.

Colbeck, I., & Mackenzie, A. R. (1994). Air pollution by photo-chemical oxidants: air quality monographs. Amsterdam:Elsevier.

Cox, M. R. (2003). The use of passive sampling to monitor forestexposure to O3, NO2, and SO2: a review and some casestudies. Environmental Pollution, 126(3), 301–311.

Díaz, A. N., Sánchez, F. G., Baro, E. N., Díaz, A. F. G., Aguilar,A., & Algarra, M. (2012). Sensitive chemiluminescent im-munoassay of triclopyr by digital image analysis. Talanta, 97,42–47.


http://www.mma.gov.br/port/conama/res/res90/res0390.html

http://www.mma.gov.br/port/conama/res/res90/res0390.html

Esteve-Turrilhas, F. A., Pastor, A., Yusa, V., & de la Guardia, M.(2007). Using semi-permeable membrane devices as passivesamplers. Trends in Analytical Chemistry, 26(7), 703–712.

Felix, E. P., Souza, K. A. D., Dias, C. M., & Cardoso, A. A.(2006). Measurements of ambient ozone using indigo blue-coated filters. Journal of AOAC International, 89(2), 480–485.

Finlayson-Pitts, B. J., & Pitts, J. N., Jr. (2000). Chemistry of theupper and lower atmosphere: theory, experiments, and ap-plications. San Diego: Academic.

Gaião, E. N., Martins, V. L., Lyra, W. S., Almeida, L. F., Silva, E.C., &Araújo,M. C. U. (2006). Digital image-based titrations.Analytica Chimica Acta, 570(2), 283–290.

Garcia, G., Allen, A. G., & Cardoso, A. A. (2010). Developmentof a sensitive passive sampler using indigotrisulfonate for thedetermination of tropospheric ozone. Journal ofEnvironmental Monitoring, 12(6), 1325–1329.

Geladi, P. (1992). Some special topics in multivariate image analysis.Chemometrics and Intelligent Laboratory Systems, 14, 375–390.

Górecki, T., & Namiesnik, J. (2002). Passive sampling. Trends inAnalytical Chemistry, 21(4), 276–291.

Gouveia, N., & Fletcher, T. (2000). Respiratory diseases in chil-dren and outdoor air pollution in São Paulo, Brazil: a timeseries analysis. Occupational and Environmental Medicine,57(7), 477–483.

Gravano, E., Bussotti, F., Strasser, R. J., Schaub, M., Novak, K.,Skelly, J., et al. (2004). Ozone symptoms in leaves of woodyplants in open-top chambers: ultrastructural and physiologi-cal characteristics. Physiologia Plantarum, 121(4), 620–633.

Iqbal, Z., & Bjorklund, R. B. (2011). Colorimetric analysis ofwater and sand samples performed on a mobile phone.Talanta, 84(4), 1118–1123.

Janach, W. E. (1989). Surface ozone: trend details, seasonal vari-ations, and interpretation. Journal of Geophysical Research,94(D15), 18289–18295.

Kley, D., Kleinmann, M., Sanderman, H., & Krupa, S. (1999).Photochemical oxidants: state of the science. EnvironmentalPollution, 100, 19–42.

Koutrakis, Koutrakis, P., Wolfson, J. M., Bunyaviroch, A. Q.,Froehlich, S. E., Hirano, K., et al. (1993). Measurement ofambient ozone using a nitrite coated filter. AnalyticalChemistry, 112, 209–214.

Lopez-Molinero, A., Cubero, V. T., Irigoyen, R. D., & Piazuelo, D.S. (2013). Feasibility of digital image colorimetry—applica-tion for water calcium hardness determination. Talanta, 103,236–244.

Lyra, W. S., dos Santos, V. B., Dionízio, A. G. G., Martins, V. L.,Almeida, L. F., Gaião, E. N., et al. (2009). Digital image-basedflame emission spectrometry. Talanta, 77(5), 1584–1589.

Maleki, M., Safavi, A., & Sedaghatpour, F. (2004). Single-stepcalibration, prediction, and real samples data acquisition for

artificial neural network using a CCD camera. Talanta, 64(4),830–835.

Maruo, Y. Y., Kunioka, T., Akaoka, K., & Nakamura, J.(2009). Development and evaluation of ozone detectionpaper. Sensors and Actuators B: Chemical, 135, 575–580.

Maruo, Y. T., Akaoka, K., & Nakamura, J. (2010). Developmentand performance evaluation of ozone detection paper usingazo dye orange I: effect of pH. Sensors and Actuators B:Chemical, 143, 487–493.

Safavi, A., Maleki, M., Rostamzadeh, A., & Maesum, S. (2007).CCD camera full range pH sensor array. Talanta, 71(1), 498–501.

Salmon, L. G., Cass, G. R., Bruckman, K., & Haber, J. (2000).Ozone exposure inside museums in the historic central dis-trict of Krakow, Poland. Atmospheric Environment, 34(22),3823–3832.

Tagner, I. B., Balmes, J., Lurmann, F., Ngo, L., Alcorn, S., &Kunzli, N. (2005). Chronic exposure to ambient ozone andlung function in young adults. Epidemiology, 16(6), 751–759.

Tôrres, A. R., Lyra, W. S., Andrade, S. I. E., Andrade, R. A. N.,Silva, E. C., Araújo, M. C. U., et al. (2011). Digital image-based method for determining of total acidity in red winesusing acid–base titration without indicator. Talanta, 84(3),601–606.

Tuduri, L., Millet, M., Briand, O., & Montury, M. (2012). Passiveair sampling of semi-volatile organic compounds. Trends inAnalytical Chemistry, 31, 38–49.

Varotsos, K. V., Giannakopoulos, C., & Tombrou, M. (2013).Assessment of the impact of climate change on Europeanozone levels.Water, Air, and Soil Pollution, 224, 1596–1609.

Weast, R. C. (1974). Handbook of chemistry and physics: a readyreference book of chemical and physical data. Cleveland:CRC.

Weschler, C. J. (2006). Ozone’s Impact on public health: contri-butions from indoor exposures to ozone and products ofozone-initiated chemistry. Environmental HealthPerspectives, 114(10), 1489–1496.

WHO Regional Office for Europe (2006). Air Quality Guidelines:Global Update 2005. World Health Organization. http://www.euro.who.int/__data/assets/pdf_file/0005/78638/E90038.pdf. Accessed 05 April 2013

Yu, C. H., Morandi, M. T., & Weisel, C. P. (2008). Passivedosimeters for nitrogen dioxide in personal/indoor air sam-pling: a review. Journal of Exposure Science andEnvironmental Epidemiology, 18, 441–451.

Zamora, L. L., López, P. A., Fos, G. M. A., Algarra, R. M.,Romero, A. M. M., & Calatayud, J. M. (2011). Quantitativecolorimetric-imaging analysis of nickel in iron meteorites.Talanta, 83(5), 1575–1579.


http://www.euro.who.int/__data/assets/pdf_file/0005/78638/E90038.pdf



A New and Simple Visual Technique Based on Indigo Dye for Determination of Ozone in Ambient Air

Documents

Transcript of A New and Simple Visual Technique Based on Indigo Dye for Determination of Ozone in Ambient Air