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    API PUBL 305-1991 Protecting Agricultural Crops from Ozone Exposures Key Issues and Future Research Directions《保护暴露臭氧农作物的主要问题今后的研究方向》.pdf

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    API PUBL 305-1991 Protecting Agricultural Crops from Ozone Exposures Key Issues and Future Research Directions《保护暴露臭氧农作物的主要问题今后的研究方向》.pdf

    1、PROTECTING AGRIGULTURAL CROPS FROM OZONE EXPOSURES KEY ISSUES AND FUTURE RESEARCH DIRECTIONS HEALTH AND ENVIRONMENTAL AFFAIRS API PUBLICATION NUMBER 305 AUGUST 1991 Ame rica n Pet roieum Institute 1220 L Street, Northwest 11 Washington, D.C. 20005 API PUBL*305 93 0732290 0554354 885 PROTECTING AGRIC

    2、ULTURAL CROPS FROM OZONE EXPOSURES KEYISSESANDFUTURERESEARCH DIRECTIONS Health and Environmental Affairs Department API PUBLICATION NUMBER 305 AUGUST 1991 PREPARED UNDER CONTRACT BY: ALLEN S. LEFOHN, PH.D. AND JANELL K. FOLEY A.S.L. Ms. Susan Spruill, Department of Statistics, North Carolina State U

    3、niversity, Raleigh, North Carolina, for providing the hourly ozone data for a subset of the NCLAN experiments; Mr. Douglas Shadwick, ManTech Environmental Technology, Inc., Research riangle Park, North Carol ina, for helpful suggestions, mathematical advice, and assistance; Ms. Phyllis E. Lefohn and

    4、 James Spence of A.S.L. many of the artificial regimes used by NCLAN contained the elevated hourly average concentrations that were reflected in the determination of the absolute values of the cumulative indices. Therefore, at many of the treatment levels, the magnitude of the SUMO6 index, calculate

    5、d using NCLAN protocols, appeared to be influenced by the peak exposures that correlated well with the observed growth reductions. We found, at the 20% yield reduction level, that there were O, A major concern about the use of any exposure index (e.g., cumulative or seasonal average concentration) i

    6、s whether the value of the index can be linked to a specific exposure regime. reflects only the mathematical calculation performed using hourly average O, concentrations. average concentrations (i.e., the upper tail of the distribution) is an important factor in affecting vegetation, then a single-p

    7、arameter exposure index, such as the SUMO6 or Wl26, in some instances, may not be specific enough to describe those important distributions that cause an O,-related effect. The absolute value of the index If we assume that the distribution of the highest hourly Although difficulties may exist for 1

    8、inking experimental exposure- response relationships with ambient air for predicting vegetation effects, s-7 API PUBLx305 91 0732290 0554LbB 37T single-parameter exposure indices have been used successfully for describing regional O3 exposure in the United States. Yet, given the fact that we have sh

    9、own that the magnitude of cumulative exposure indices, such as the W126 or SUMO6 exposure index, is not necessarily strongly associated with the occurrence of high hourly average O, concentrations, why is it possible to successfully describe regional exposures using single-parameter cumulative indic

    10、es? The O, exposures experienced at each site are influenced by a multitude of factors. sorptive capacity), as well as its latitude, may influence O, production and destruction of the absolute O, exposure value experienced at a specific site. Many of the O, monitors used in the kriging analyses were

    11、 situated near urban- oriented locations. concentrations may have been similar. monitoring sites may experience similar scavenging processes that result in 30% or more of the hourly average concentrations occurring below 0.015 ppm. In addition, the maximum hourly average concentrations experienced a

    12、t many of these sites were similar. Thus, with similar hourly average distribution patterns, it would be assumed that the magnitude of a cumulative exposure index, such as the W126 or SUM06, would order itself properly, with the higher value corresponding to the higher exposure. This appears to be w

    13、hat occurred. In addition to using cumulative exposure indices to describe regional O, exposures, a cumulative exposure index has been used in trends analysis. Trends for O3 exposures over 5- and 10-year periods (i.e., 1984-1988 and 1979- 1988) have been summarized for rural locations in the United

    14、States. The evidence for trends at each monitoring location was explored. The elevation of a specific site, its ground cover (i.e., Thus, the distribution of the hourly average For example, most of the urban-oriented Evidence for S-8 API PUBLW305 91 O732290 0554369 206 regional trends was based on s

    15、tudying the individual time trends observed for each of the sites in the region. The seasonal W126 cumulative exposure index was used to investigate trends. The results reported in the literature were consistent with the findings reported by the U.S. Environmental Protection Agency. The explanation

    16、for the successful application of the cumulative index in the trends analysis was similar to the one given for the kriging analysis. For a specific monitoring site, the hourly average distribution pattern was similar over the years studied. The scavenging processes remained the same over time at a s

    17、pecific site. index, at any one site over time, was reflected in changes in the distribution curve of the hourly average O, concentrations. upper end of the distribution curve were reflected in the magnitude of the W126 index. Thus, the difference in magnitude of the W126 Changes that occurred at th

    18、e For some purposes, the single-parameter index appears to work appropriately. However, the predictive power involving exposure-response relationships that use single-parameter exposure indices may not be as strong as desired. describe distribution patterns of hourly average concentrations. To impro

    19、ve the predictive capability that depends upon linking experimental exposure-response relationships with ambient air quality, it appears that indices, such as the SUMO6 or W126, will have to be combined with other exposure parameters in order to mathematically define unique distribution patterns of

    20、hourly average concentrations. A multiple-parameter index may be necessary to adequately Although moderate success has been achieved using the SUMO6 and W126 exposure indices, consistency is important so that experimental exposure- s-9 API PUBL*305 91 0732290 0554370 T28 response relationships can b

    21、e strongly linked with ambient exposures. consistency is not present, then it will be difficult to use any exposure index in the development of a secondary standard. If this For developing a secondary standard to protect vegetation, the combined exposure statistics should be selected based on the ob

    22、servation that high concentrations are expected to cause greater impact on vegetation than lower concentrations. It has been shown, when high hourly average concentrations are present in an exposure regime, that single-parameter cumulative indices can be used to relate O, exposures with vegetation g

    23、rowth reductions. However, when attempting to 1 ink experimental models with ambient air quality, it appears that the application of a single-parameter exposure index, in the form of a standard for protecting vegetation, will provide inconsistent results. indices are not appropriate for describing O

    24、, exposure. that cumulative indices, such as the SUMO6 and W126 indices, will have to be combined with other parameters to quantify accurately the occurrence of the high hourly average concentrations. This does not imply that all currently used Cumulative exposure Rather, it appears The possible com

    25、bination of exposure parameters, such as the (i) sigmoidally-weighted exposure index or (2) SUMO6 index, with other indices should provide sufficient means to describe those unique distribution curves that have the potential for eliciting an adverse effect. the NCLAN data provided us with evidence t

    26、hat summaries of distribution patterns provide important information concerning the relationships between exposure and response. quantification of the distribution of the hourly average concentrations. percentile distribution of the hourly average concentrations offers a way to Our reanalysis of Fut

    27、ure research efforts in this area point to the The s- 10 API PUBL*305 91 m 0732290 0554171 964 m characterize both high and low O, concentrations. the percentile distribution of O, one can infer that the values in the tail of the distribution represent peaks in the time plots of hourly O, concentrat

    28、ions. With high confidence, from In addition, percentile distributions offer the opportunity to differentiate exposures experienced at remote or isolated si tes from exposures experienced at sites influenced by urban sources. influence of local urban sources experience approximately 50-70 percent of

    29、 their hourly average O, concentrations above 0.015 ppm. Monitoring sites under the Al though we have discussed the possible combinations of parameters to better 1 ink experimental exposure-response models with ambient air qual i ty for predicting possible impacts on vegetation, at this time, inform

    30、ation is not available to identify the specific parameters that should be combined. However, the results of the NCLAN experiments provide researchers with the opportunity to better understand the level of exposures that result in agricultural yield reduction. hourly average concentrations that occur

    31、red in some of the NCLAN experiments. The characterized distributions reflected the importance of the upper end of the distribution curve in affecting crop yield reductions. additional information should assist researchers in identifying a multi- parameter exposure index that will properly relate am

    32、bient exposure to response. We have summarized the distribution of the We believe this A strong case has been made for selecting multi-parameter exposure indices for establishing a secondary standard to protect vegetation from high levels of O, exposure. an effort should be made to identify multi-pa

    33、rameter indices, it is important However, caution is urged. Although we believe that s-11 API PUBL*305 91 = 0732290 055Yl172 8TO to note that a consistent relationship between multi-parameter exposure indices and vegetation effects may not always exist. Based on the analysis described in this report

    34、, at this time, we believe that further research is required before any single-parameter exposure index is used in the standard- setting process to protect vegetation from O, exposure. s- 12 API PUBL*305 91 0732290 0554173 737 CHAPTER 1 INTRODUCTION 1.1 BACKGROUND The Clean Air Act requires the Admi

    35、nistrator of the U.S. Environmental Protection Agency to establish national ambient air quality standards. These standards are designed to protect the public health and welfare from any known or anticipated adverse effects associated with the presence of criteria air pollutants. effects on human hea

    36、lth, while secondary air quality standards are established to prevent adverse welfare effects (e.g., effects on vegetation, animals, deterioration of property materials, and visibility). Primary air quality standards are promulgated to prevent adverse The ubiquity and toxicity of ambient air O, is w

    37、ell documented (EPA, 1986, 1988a). Because O, is an omnipresent air pollutant that affects both human health and vegetation, the U.S. Environmental Protection Agency (EPA) has establ ished both primary and secondary standards. On April 30, 1971, in the Federal Register (36 FR 8186), the Environmenta

    38、l Protection Agency promulgated National Ambient Air Quality Standards (NAAQS) for photochemical oxidants. The scientific, technical, and medical bases for these standards were contained in the air quality criteria documents for photochemical oxidants, pub1 ished by the U.S. Department of Health, Ed

    39、ucation, and Welfare in March 1970. Both the primary and secondary standards were set at an hourly average level of 0.08 ppm, not to be exceeded more than once per year. Based the primary The revised on a reassessment of the available data, in 1979, EPA revised both and secondary standards for Photo

    40、chemical oxidants (i.e., O,). form of the standard (1) raised the primary standard to 0.12 ppm, 1-1 API PUBL*305 91 M O732290 0554374 673 W (2) raised the secondary standard to 0.12 ppm, and (3) changed the definition of the point at which the standard is attained to “when the expected number of day

    41、s per calendar year with maximum hourly average concentrations above 0.12 ppm is equal to or less than one.“ The phrase “expected number of days per calendar year“ differed from the previous NAAQS for photochemical oxidants, which simply stated a particular concentration “not to be exceeded more tha

    42、n once per year.“ The federal standard for O, is based on the second daily occurrence of a maximum hourly average concentration above 0.12 ppm and is designed to protect both human health and welfare effects. There is no requirement that the primary and secondary standards be identical, nor is there

    43、 any requirement that only a single expression of the standard be used (i.e., an average concentration for a single time period versus multiple exceedances or integrated exposures). secondary standard, whose form is different than the current form of the primary and secondary standard, implies that

    44、either (1) the current form is inappropriate for protecting the public welfare or (2) a more restrictive value of the current form of the standard is required. Any effort to propose a There have been indications reported in the literature (Lefohn et al., 1989; Lee et al., 1991) that the current form

    45、 of the standard may not be appropriate for protecting vegetation from O, exposures. Lee et al. (1991) reported that, although no single exposure index was best in describing the exposure-response re1 ationship for 49 case studies, the performance of the current form of the U.S. Federal standard was

    46、 considerably worse than other exposure indices used in their analysis. current form of the standard did not perform adequately because it (1) was The authors reported that the 1-2 API PUBL*305 91 0732270 0554375 50T Should one want measure of protection precise terms as poss potenti al for adverse

    47、to vegetation, it WOU ble, the relationship effects on vegetation poorly related to plant growth, (2) ignored exposure duration, and (3) placed too much emphasis on a single peak 1-h concentration. to develop an O, standard that provides an adequate d be necessary to define, in as between O, exposur

    48、es and the Although the form of the standard should be made as simple as possible, it is essential that the standard be related directly or indirectly to identifiable adverse effects. The U.S. EPA (1988b) has made a distinction between the relative importance of foliar injury to vegetation and reduc

    49、ed crop yield. Greater emphasis has been placed on damage or yield loss than on injury, where injury encompasses all measurable plant reactions, such as reversible changes in metabolism, reduced photosynthesis, leaf necrosis, leaf drop, altered quality, or reduced growth, that do not influence agronomic yield or reproduction and damage includes all effects that reduce the intended human use or value of the plant or ecosystem (Tingey et al., 1990). The purpose of this report is to identify and review some of the key issues related to assessing the effects of O, on vegetation. re


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