Differences in responses to urban air pollutants by Ligustrum lucidum Ait. and Ligustrum lucidum Ait. f. tricolor (Rehd.) Rehd.

EnvironmentalPollution, Vol. 93. No. Pll:

S0269-749

I (96)000

I 4-0

2, pp. 211 218, 1996 Copyright 4;) 1996 Elsevier Science Ltd Printed in Great Britain. All rights reserved 0269-7491/96 S15.00 + 0.00

ELSEVIER

DIFFERENCES IN RESPONSES TO U R B A N AIR POLLUTANTS BY L I G U S T R U M L U C I D U M AIT. A N D L I G U S T R U M L U C I D U M AIT. F. TRICOLOR (REHD.) REHD. Hebe A. Carreras, Martha S. Cafias & Maria L. Pignata C6tedra de Qulmica General, Facultad de Ciencias Exactas, Fisicasy Naturales, UniversidadNacional de C6rdoba, A vda V(lez S6rs.fieM299, 5000 C6rdoba, Argentina

(Received 15 March 1995; accepted 29 December 1995)

Determination of the chemical composition of plants is one of the most frequently used methods of monitoring environmental pollution. The sulfur content in leaves is a useful indication of SO2 pollution levels (Materna, 1982; Legge et al., 1988; Dmuchowski & Bytnerowicz, 1995). Thus, the impact of emissions on forests through the deposition of fossil fuel derived sulfur from the atmosphere has been studied extensively in recent decades (Cape et al., 1988). A large number of biological parameters have been used to assess the damage to plants caused by pollution, including visible foliar injury (Davis & Wilhour, 1976), leaf conductance (Winner, 1981), membrane permeability (Farooq & Beg, 1980), ascorbic acid (Keller & Schwager, 1977), relative water content (Rao, 1979) and chlorophyll content (Bell & Mudd, 1976; Reich, 1983). Different plant species vary considerably in their susceptibility to air pollutants. The identification and categorization of plants into sensitive and tolerant groups is important because the former can serve as indicators and the latter as sinks for the abatement of air pollution in urban and industral habitats (Singh et al., 1991). Biochemical markers can be used to detect early alterations in plants that occur before the appearance of visible injury or a decline in yield. However, the lack of specificity regarding the action of general plant stress upon a single marker creates a need for simultaneous screening of several biochemical markers or the use of more specific markers, currently undefined (Peters et al., 1989). Studies using lower levels of ozone have shown decreases in chlorophyll and carotenoids over periods of days rather than hours but no difference in relative rates of breakdown between chlorophyll a and b (Price et al., 1990). In spruce, loss of pigment is very evident from older needles when experimental fumigations with nonfiltered air and added ozone have been continued over a number of years (Wallin et al., 1990). Studies of the responses of plants to ozone have also suggested that dry matter partitioning may be strongly affected. Walmsley et al. (1980) suggested that changes in allocation of assimilates occurred only after the

Abstract This study examined the chemical response of Ligustrum lucidum Ait. and Ligustrum lucidum Ait. f. tricolor (Rehd.) Rehd. when exposed to different sources of atmospheric pollutants. Dr), weight/fresh weight ratio, specific leaf area ( SLA ), sulfur content, chlorophyll concentration, carotenoids, soluble proteins, malondialdehyde ( M D A ) and hydropero.vy conjugated dienes ( H P C D ) were determined Jbr leaf samples taken .from different sites in the city of C6rdoba, Argentina. These sites were categorized in terms of their trqffic levels and industrial levels. Both L. lucidum as well as L. lucidum f. tricolor accumulated sulfur in their leaves in sites with high traffic' levels, the.former being the most sensitive to this type of pollution. Ligustrum lucidum exhibited significantly low concentrations of soluble proteins, in sites with high industrial pollution levels. Ligustrum lucidum f. tricolor did not exhibit a significant response to industrial pollution. Copyright 6;) 1996 Elsevier Science Ltd

Keywords: Air pollution, Ligustrum lucidum Ait., Ligustrum lucidum Ait. f. tricolor (Rehd.) Rehd., pigments, sulfur accumulation.

INTRODUCTION

The impact of atmospheric pollutants on vegetation is a widely documented phenomenon (Takemoto et al., 1988; Robinson & Wellburn, 1991; Wolfenden & Mansfield, 1991; Wolfenden & Wellburn, 1991; Polle et al., 1992; Strand, 1993). One important method for studying plant-pollutant interaction in the field is through in situ experiments, performed through quantifying the measurable impacts of air pollutants on plants growing in their natural habitats (Pandey & Agrawal, 1994). The main atmospheric pollutants in urban and industrialized areas are ozone, PAN, nitrogen oxides and sulfur oxides. These compounds produce a wide range of harmful effects on plants, characterized by a series of complex biochemical and physiological events (Heath, 1980; Koziol & Whatley, 1984; Winner et al., 1985). 211

212

H. A. Carreras et al.

pollutant had initially caused a reduction in leaf dry weight. This suggested that compensatory growth had occurred to increase the relative size of the assimilatory area, making up for the inhibition of photosynthesis by ozone. Thus a change in assimilate distribution might be seen as a secondary effect of ozone, subsequent to the primary effect on photosynthesis (Wolfenden & Mansfield, 1991). With regards to the effects o f nitrogen oxides, Heil (1989) maintains that chronic exposure to large concentrations of atmospheric NO2 causes serious nutritional imbalances and physiological disorders in many plant species. Wellburn et al. (1981) mention significant dry weight reduction in gramineous leaves due to the synergistic effects of NO2 and SO2 combinations in the air, thus indicating a toxic effect by these gases on biochemical parameters and growth of these plants. On the other hand, air pollutants (03, NO2) are potent catalysts of the peroxidation of membrane lipids (Menzel, 1976). In biological systems, the presence of oxidation products such as malondialdehyde is directly related to the beginning of peroxidation of unsaturated fatty acids (Mehelman & Borek, 1987) Every type of membrane is sensitive to oxidation processes generated by free radicals and nitrogen oxides. Ozone and sulfur oxides can be included among the atmospheric pollutants that can initiate these reactions (Mead, 1987). During lipid peroxidation, conjugation of the ethylenic groups of polyunsaturated fatty acids is observed by measurement of the ultraviolet absorption spectrum (Heath & Packer, 1968) Thus, the process of lipid peroxidation is accompanied in the first step, by a rearrangement of the double bonds in natural unsaturated fatty acids leading to diene conjugation which results in an increase in absorption at 233-234 nm (Slater, 1972; Menzel, 1976) Cbrdoba is one of the most polluted cities in Argentina Emission of pollutants into the atmosphere grew by 50% in the 10 years between 1973-1983, reaching 287 metric tons of total pollutants/day (Servicio Meteorol6gico Nacional de la Repfiblica Argentina, 1986) Although the situation is critical, there are no data on the quantity or quality of pollutants discharged over the last 12 years, and all indicators seem to point to a worsening situation The thousands of tons of toxic compounds released into the atmosphere actually produce smog clouds more frequently and for longer periods than ever before. In spite of the absence of official records, it can be assumed that the level of pollutants in the atmosphere is high enough to be a health threat While the effects of air pollution on plant growth in urban areas have attracted attention (Young & Matthews, 1981; Ali, 1993), no research work on this important subject has been performed in Argentina Consequently, the objective of the present study was to establish differences in the sensitivity/tolerance level to air pollutants in two varieties of L. lucidum, both of which are widespread in Argentina and used in urban plantings

MATERIALS AND METHODS Area of study and sampling sites C6rdoba city, capital of C6rdoba Province, is in the center of the Argentine Republic, latitude 31024' S, longitude 64°11' W. It is 440 m above sea level; with a population of 1 189 000 inhabitants (according to a 1991 census). The city has an irregular topography. Its general structure is funnel-shaped with a growing positive slope from the center towards the surrounding areas. This somewhat concave formation reduces air circulation and causes frequent thermal inversions in autumn and winter. The climate is sub-humid, with an average annual precipitation of 790 mm, concentrated principally in summer. Mean annual temperature is 17.4°C and prevailing winds originate in the NE and SE. Natural vegetation belongs to the Espinal Phytogeographical Province (Cabrera, 1976) which consists of low thorny woodlands. Because of man's activities, natural vegetation has almost been eliminated and replaced mostly by exotic trees, mainly species of Fraxinus, ,4cer, Ligustrum, Melia, Platanus, Ulmus, Populus, etc and some native genera belonging to different phytogeographical units like Jacaranda, Tabebuia, etc The study was carried out in the SE sector of the city. The industries located in the corresponding sector are small and medium sized, predominantly tanneries and metallurgical, such as sheet metal workshops and body shops, carpentries, etc Sampling sites were selected and categorized as stationary or mobile emission sources (Fig. 1). In spite of the homogeneity of the sector, it was possible to differentiate zones exhibiting the effects of one of the emission sources from those in which one proved to be

Ilia

Study° area

16IA

~//

21I A

81A

22IA 14IA

251A 23IA

20IA

19 t71I& IA

13IA I0 IA

~

2

"

"

24--

m

Fig. 1. Study area for Ligustrum lucidum and L. lucidum f. tricolor in C6rdoba city Sample sites were categorized as traffic level (I low; • high) and industrial level (A low; • high)

The impact of atmospheric air pollutants on vegetation stronger than the other. Categorization of the sampling sites was based on: (1) vehicular traffic level (characterized as 'high' when consisting of automobiles, city public transit, and cargo transit; and 'low' when there was little vehicular circulation). High vehicular traffic sites for L. lucidum were 10, 14, 17, 18, 19, 21 and 22, while low traffic sites were 5, 20, 23, 24, and 25. High traffic sites for L. lucidum f. tricolor were 8, 10, 11, 13, 14, 16 and 17; low sites were 1, 2, 3, 4,5,6,7,9,12and15. (2) industrial level (characterized as 'high' when the sampling site was located at the entrance to the industry). This was characterized as such since none of the industries in the sector have emission stacks for gaseous pollutants. Sampling sites corresponding to areas of high industrial level for L. lucidum were 5, 17, 19 and 20; low industrial level sites were 10, 14, 18, 21, 22, 23, 24, and 25. Sites of high industrial level for L. lucidum f. tricolor were 1, 3, 4, 5, 6, 7, 8, 13, 15 and 17, while those for low industrial level areas were 2, 9, 10, 11, 12, 14 and 16. Once the sampling sites were categorized, trees were selected at sites corresponding to each extreme category for traffic and industry levels and each sampling point was represented by one tree.

Plant material and collection samples Two evergreen forms of Ligustrum were used to carry out the work. Both L. lucidum Ait. and L. lucidum Ait. f. tricolor (Rehd.) Rehd. are common ornamental street trees in the study area. Ligustrum lucidum has shiny dark green leaves, while L. lucidum f. tricolor has variegated yellw/green leaves. Newly emerging leaves are reddish in color (Dimitri & Parodi, 1988). Preparation of samples Leaf samples were placed in paper bags and immediately transferred to the laboratory. The samples were rinsed with distilled water for about 1 min to remove materials deposited on foliar surfaces so that the results of chemical analysis of samples collected in various sites could be compared. After washing, leaves were dried for 24 h at room temperature. Then, samples were stored in hermetically sealed containers at -15°C in darkness until chemically analyzed. Only leaves free of petioles were chosen for chemical analysis. Dry weight/fresh weight ratio The dry weight/fresh weight (DW/FW) ratio of the samples was determined by storing 1 g of fresh leaves at 60 + 2°C until constant weight. The results were expressed in g DW g-i FW of plant material. Specific leaf area Specific leaf area (SLA) was determined for the samples by calculating the area of three leaf discs, whose weight

213

was then averaged (Martin & Coughtrey, 1982). The results were expressed in m 2 g-~ DW of plant material.

Chlorophyll and carotenoid Five hundred mg of leaves were ground with glass in a mortar and homogenized in 15 ml of ETOH at 96% v/v. Extraction took place over a 24 h period in darkness. Subsequently, the supernatant was separated. Absorbance (665, 649 and 470 nm) was measured with a spectrophotometer Beckman DU 7000, and chlorophyll (chl a, b and total) and carotenoid concentrations were calculated on a dry weight basis (Lichtenthaler & Wellburn, 1983). Soluble protein After leaves had been frozen and subsequently made into a powder in a Polytron grinder, soluble proteins (sol prot) were extracted with Na phosphate buffer 0.1 M; pH 7.0. Protein determination was carried out according to the Biuret colorimetric method (Gornall et al., 1949). Absorption was recorded in a Bausch and Lomb Spectronic 21 spectrophotometer. The concentration was expressed in mg g-1 DW. Sulfur content Five ml of Mg(NO3)2 saturated solution was added to 1 g of ground plant material and dried in an electric heater. Subsequently, the sample was heated in an oven for 30 min at 500°C. The ashes were then suspended in 10 ml of 6M HCI, filtered, and the resulting solution boiled for 3 min. The solution was brought to 50 ml with distilled water. The amount of SO42- in the solution was determined by the acidic suspension method with barium chloride (Toennies & Bakay, 1953) which subsequently allowed for the calculation of sulfur content in each sample. The concentration was expressed in mg of total sulfur g-~ DW. Peroxidation product estimation Malondialdehyde (MDA) was measured by a colorimetric method (Heath & Packer, 1968). The amount of MDA present was calculated from the extinction coefficient of 155 mM -1 cm -1 (Kosugi et al., 1989). Results were expressed in #mol g-I DW. Hydroperoxy conjugated dienes (HPCD) were extracted by homogenization of the plant material in 96% v/v ethanol at a ratio of 1:50 FW/v with an Ultra Turrax homogenizer. The absorption was measured in the supernatant at 234 nm and its concentration was calculated by means of e.=2.65×i04 M i cm I (Boveris et al., 1980). Results were expressed as #mol g-1 DW. Statistical analysis The experimental design was a bifactorial. The significance of the main treatment effects (traffic level and industrial level) and the first order interaction effect of (traffic level × industrial level) on the reference parameters were assessed by ANOVA techniques. Within each combined treatment, individual plants were the

214

H . A . Carreras et al.

experimental units for statistical analysis, and plant-toplant variability was included in the ANOVA error term. For each tree, pigments and peroxidation product estimation were carried out in triplicate, and the results were expressed as means + standard deviation. Pearson's coefficients of correlation were used to evaluate the degree of correlation among variables. Results were considered significant when p < 0.05. No significant results were indicated in the tables as ns.

RESULTS AND DISCUSSION Table I shows the variables quantified in L. lucidum while Table 2 shows those corresponding to L. lucidum f. tricolor. From comparisons of both, it is apparent that only the pigment concentrations were greater in L. lucidum than L. lucidum f. tricolor. L. lucidum as well as L. lucidum f. tricolor leaves accumulated sulfur at high traffic sites (Tables 3 and 4). It should be noted that, although this relationship between sulfur accumulation and traffic has already been mentioned for lichens in Argentina (Levin & Pignata, 1995), it has not been previously reported in higher plants. Even though the absence of any differentiation of different forms (e.g. organic versus inorganic) of sulfur limits the interpretation of the results, we believe that this accumulation could be reflecting high concentrations of SO2 in the air. Sulfur dioxide is a primary pollutant emitted mainly by anthropogenic sources (Lefohn & Benkovitz, 1990). Ambient SO2 concentrations result largely from stationary source coal and oil combustion (US EPA, 1989). In urban environments, one of the principal sources of SO2 pollution comes from automotive fuel combustion, and particularly from those vehicles that run on diesel fuel (del Giorgio, 1977; van Ek & Draaijers, 1991). This is consistent with the observations noted by Kaiser et al. (1993) for Norway spruce needles, in which they pointed out that sulfur accumulation would indicate the presence of SO2, as well as with those cited by Materna (1982), who mentions that Scots pine needles are a useful indication of SO2 pollution levels. In L. lucidum this was accompanied by a decrease in pigment concentrations (chl a, total chi and carotenoid) and by an increase in SLA. Reduction in pigment concentration has been noted as an indicator of leaf damage produced by pollution (Mehlhorn et al., 1988; Wedler et al., 1995; Amundson et al., 1986; Robinson & Weilburn, 1991). Legge et al. (1976, 1978) observed a decrease in photosynthesis in Pinus contorta and P. banksiana due to the effects of sulfur gas emissions. The increase in foliar area can be related to Wolfenden & Mansfield (1991) observations for ozone pollution, who noted that compensatory growth may occur in order to increase the relative size of the assimilatory area, making up for the inhibition of photosynthesis by ozone. Except for sulfur accumulation, no significant differences were found in the variables quantified with respect to traffic levels for L. lucidum f. tricolor.

No significant correlations were detected upon analysis of the correlation between sulfur and the other variables quantified in L. lucidum samples taken from high traffic areas. Positive correlations were observed between sulfur and chl a (r=0.771, p<0.05) and sulfur and carotenoids (r = 0.754, p < 0.05) in L. lucidum f. tricolor. If these results are related with those obtained for the analysis of variance, we can infer a differential response to traffic among the varieties studied, where L. lucidum f. tricolor is probably more tolerant. In terms of the different industrial levels tested, L. lucidum showed significantly lower soluble protein concentrations in high industrial level conditions. This coincides with the findings of Rabe and Kreeb (1979) who suggest that a decrease in protein content in leaves is also a suitable indicator of pollution level. It has also been noted that soluble protein concentration may diminish in the presence of pollutants due to the inhibition of de novo synthesis and/or an increase in amino acid degradation (Godzik & Linskens, 1974). The remaining variables quantified did not show significant differences with respect to industrial levels for either of the two varieties (Tables 3 and 4). Nor were significant differences found for any of the variables in either of the varieties upon comparison of sampling sites located near tanneries with those in the vicinity of other industries (data not shown). Nevertheless, we believe that the response of these trees to industrial pollution may be masked by the proximity among the sampling sites, which would probably attribute a large degree of homogeneity to the sector. In spite of this last observation, foliar sulfur accumulation was observed at high traffic sites, revealing a response to this type of pollution. The results presented lead us to infer that: (I) the industries present in the selected area of study produce no apparent harmful effects on L. lucidum; (2) a base level concentration of atmospheric pollutants may exist in the area, over which an additional response to traffic can be detected.

CONCLUSION With regard to differences in sensitivity/tolerance, this study revealed that L. lucidum f. tricolor was more tolerant to traffic-related pollution, the largest single source of pollution in our city. This conclusion is based on the fact that we observed no significant reductions in pigment concentrations for this variety in the samples taken from high traffic sites, which could be interpreted as a tolerance mechanism, as noted by Polle et ai. (1992) and Singh et al. (1991) for other species. In light of the observations above, and the ability of L. lucidum f. tricolor to accumulate sulfur in its leaves without any visible signs of damage or chemical alterations that would indicate foliar injury on a physiological level, we think that the use of this variety in urban

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17

Chl b mg g i DW

Mean S.D. 3.92+0.50 2.86±0.11 2.32±0.01 1.77±0.00 1.28±0.29 0.62±0.31 2.79±0.03 1.80±0.00 1.05±0.21 1.50±0.61 2.07±0.63 4.63±0.74

Chl a mg g-i DW

Mean S.D. 3.79±0.12 3.07±0.06 3.25±0.25 3.61 ±0.00 2.05±0.19 1.48±0.24 4.17± 1.04 2.18±0.00 2.25±0.20 2.59±0.44 3.43±0.15 3.56±0.04

Mean S.D. 7.72±0.37 5.93+0.05 5.57±0.25 5.384.0.00 3.344-0.10 2.104-0.07 6.974- 1 . 0 7 3.994-0.00 3.304-0.01 4.09±0.17 5.50±0.78 8.19±0.79

Total Chl mg g i DW Mean S.D. 1.60+0.03 1.26+0.01 1.26±0.15 1.16±0.01 0.654-0.01 0.37±0.06 i.69±0.41 0.71 ±0.01 0.58±0.08 0.85±0.13 0.99±0.04 1.55±0.11

Carotenoids mg g-i DW Mean S.D. 23.15+ 1 . 5 1 26.50±0.98 24.72± !.01 37.78±3.60 28.58±0.00 30.32± 1.69 20.05± 1.79 27.64±0.41 35.49±3.15 25.07± !.85 56.404-4.46 21.06±0.00

HPCD #mol g i DW Mean S.D. 3.66±0.30 6.03±0.87 6.95±0.16 8.29±2.51 4.32±0.41 6.00±0.04 3.35±0.27 4.08±0.07 4.77±0.18 6.52±2.60 5.98±0.16 2.37±0.52

MDA #mol g i DW

64.58 80.48 63.49 49.42 81.79 59.53 28.66 75.14 96.48 62.45 85.62 112.16

Sol Prot mg g i DW

0.97 .74 .59 .26 .62 .37 .08 .13 .81 .18 L96 .13

Sulfur mg g i DW

1.02

1.38 0.97

1.97

1.85

1.45

.23 .63 .65 .17 .73 .73

SLA x 10 -' m2g i DW

3.59 3.48 4.33 3.55 3.89 3.85 3.49 4.23 4.15 3.84 3.16 3.58

D W / F W × 10-i g g-i FW

Chl b mg g-I DW

Mean S.D. 1.68+0.11 0.89+0.11 1.27+0.02 0.75±0.01 1.82±0.06 1.47 ±0.03 1.28±0.19 1.59±0.32 1.42 ±0.15 0.954.0.15 1.164.0.09 1.95±0.16 1.68 4- 0.04 2.024-0.20 1.41 ±0.11 2.46+0.29 1.944-0.11

Chl a mg g-i DW

Mean S.D. 1.65+0.09 0.78±0.12 1.16-4-0.01 0.71 4-0.01 1.864.0.03 1.454-0.01 1.234-0.22 1.43+0.28 1.31 ±0.20 0.87±0.17 1.084.0.08 1.68±0.01 1.88 ± 0.05 1.76±0.17 1.194-0.01 2.18±0.19 1.75±0.06

Mean S.D. 3.33-4-0.19 1.67+0.22 2.43+0.01 1.47-4-0.04 3.68±0.02 2.91 ±0.03 2.51 ±0.41 3.02±0.61 2.73-4-0.35 1.82+0.30 2.254-0.17 3.624-0.17 3.57 4- 0.03 3.78±0.36 2.604-0.12 4.644-0.48 3.694-0.16

Total Chl mg g i DW Mean S.D. 0.75+0.04 0.35+0.05 0.46±0.01 0.29±0.03 0.72 ± 0.07 0.62+0.01 0.55+0.04 0.56 ± 0.05 0.53±0.07 0.39±0.06 0.494-0.08 0.764-0.01 0.74 ± 0.02 0.74±0.07 0.51 4-0.01 0.904-0.06 0.71±0.02

Carotenoids mg g-i DW Mean S.D. 35.93+0.85 34.36+0.70 24.94±0.04 34.254. 1.17 21.574.1.43 23.804-0.31 31.904-0.07 30.004-2.18 24.474. 1.26 21.50± 1.39 28.174- 1.44 30.75± 1.34 27.43 4- 0.32 23.45± 1.79 24.26±0.38 25.51 ±0.04 26.62±2.16

HPCD #mol g-i DW Mean S.D. 4.34+0.47 3.37+0.25 3.45±0.18 4.44±0.71 3.824.0.11 3.24+0.25 3.40 ± 0.02 4.21 ± 1.03 2.95±0.02 5.03 ± 0.01 8.19±0.27 5.08±0.84 3.84 ± 0.41 4.64±0.73 3.894-0.07 3.634-0.25 4.53±0.57

MDA #mol g-1 DW

62.74 66.04 85.17 76.27 55.91 65.31 73.75 82.31 75.44 58.97 61.03 56.54 68.41 59.64 87.71 53.50 51.62

Sol Prot mg g-t DW

0.97 1.06 1.21 0.96 1.15 1.79 0.85 !.18 !.08 1.14 1.12 0.91 2.53 1.81 1.04 2.05 1.34

Sulfur mg g-i DW

1.27 0.92 1.02 1.52 1.18 1.00 1.46 0.98 1.30 1.24 1.35 1.79 1.39 0.89 1.25 0.89 0.75

SLA x 10-2 m 2 g-i DW

3.59 3.07 3.09 3.07 3.29 2.97 3.11 3.06 3.26 3.17 3.46 3.54 3.52 3.17 3.52 3.20 3.12

D W / F W x 10-I g g-1 F W

Table 2. Mean values ( ± standard deviation) of parameters quantified in leaves of Ligustrum lucidum f. tricolor corresponding to the 17 sampling sites in the city of C6rdoba

Sample points

5 10 14 17 18 19 20 21 22 23 24 25

Sample points

Table I. Mean values ( ± standard deviation) of parameters quantified in leaves of Ligustrum lucidum corresponding to the ! 2 sampling sites in the city of C6rdoba

"~

e~

.4,

e~

2.984.0.58 1.674.0.29

2.194.0.40 2.284-0.70

ns ns ns

2.804.0.21 3.26:t:0.60

* ns ns

Chl b mgglDW

3.51 4.0.26 2.56+0.29

Chl a mggIDW

* ns ns

4.994.0.58 5.544- 1.25

6.494-0.75 4.234.0.54

Total Chl mgg-lDW

ns ns ns

0.76±0.09 0.654-0.14

0.84+0.14 0.644-0.07

Chl b/Chl a

* ns ns

0.98 + 0.12 1.204-0.30

1.34+0.17 0.854-0.14

Carotenoids mggtDW

ns ns ns

30.684.3.95 27.824-3.95

29.154-6.87 30.154-1.81

HPCD #molg-tDW

ns ns ns

5.13 4-0.54 5.33+ 1.15

4.384-0.80 5.784.0.57

MDA #molg-lDW

ns * ns

82.204-5.83 50.554.7.95

70.69+13.81 72.334- 6.00

Sol P r o t mgg-lDW

* ns ns

1.404.0.11 1.174-0.09

1.074.0.04 1.504-0.09

Sulfur mgg-lDW

* ns ns

1.524.0.13 1.394.0.13

1.21 4.0.09 1.67+0.09

ns ns ns

3.834.0.14 3.62+0.08

3.534.0.11 3.924-0.12

SLA x 10-2 D W / F W x 10-t m 2g i DW gg-IFW

1.39:1:0.12 1.694-0.19

1.55+0.23 1.494-0.11

ns ns ns

1.304-0.12 1.564-0.17

1.38+0.19 1.434-0.12

ns ns ns

Chl b m g g-i D W

ns ns ns

2.934.0.42 2.92±0.22

2.69+0.23 3.254-0.36

Total Chl m g g-~ D W

ns ns ns

1.12+0.01 1.054.0.02

1.084-0.02 1.084-0.03

Chl b/Chl a

ns ns ns

0.59+0.08 0.594.0.05

0.55±0.05 0.644-0.07

Carotenoids mg g i D W

a Results o f the A N O V A : ns = n o t significant at p < 0.05; * = significant at p < 0.05.

Traffic level (TL) low high Industrial level (IL) low high ANOVA Effect TL IL TL x I t

Chl a mg g-i D W

ns ns ns

26.894. 1.70 28.074- 1 . 5 1

28.624-1.69 26.104. 1.09

HPCD # m o l g-1 D W

ns ns ns

4.704.0.66 3.924- 1.14

3.804.0.21 4.874.0.58

MDA # m o l g-i D W

ns ns ns

61.594.2.73 70.924-3.88

70.494-3.49 62.21 4.3.93

Sol P r o t m g g-~ D W

* ns ns

1.31 4.0.16 1.304.0.16

1.104.0.08 1.604-0.21

Sulfur m g g-i D W

ns ns ns

1.204-0.12 1.184.0.08

1.274-0.08 1.074-0.09

SLA x 10-2 m 2 g-~ D W

ns ns ns

3.274.0.06 3.23+0.07

3.254.0,07 3.24±0.07

D W / F W x 10-j g g i FW

Table 4. Comparison of means ( + standard error) of reference parameters in Ligustrum lucidum f. tricolor and their significancea between different traffic levels and industrial levels

Results o f the A N O V A : ns = not significant at p < 0.05; * = significant at p < 0.05.

Treatment Variable

a

Traffic level (TL) low high Industrial level (IL) low high ANOVA Effect TL IL TL x IL

Treatment Variable

Table 3. Comparison of means (4. standard error) of reference parameters in Ligustrum lucidum and their significance* between different traffic levels and industrial levels

",t

m O~

The impact o f atmospheric air pollutants on vegetation plantings would be recommended. This study leads us to infer that the relative performance for sensitivity to SO2 and urban pollutants will allow for the selection of trees for planting in polluted areas.

ACKNOWLEDGEMENTS We are grateful to Nela von MOiler for the identification of plant material, and to the Friedrich Ebert Foundation for financial support.

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