Response of Bean and Tobacco to Ozone: Effect of Light Intensity,Temperature and Relative Humidity

Pinto bean (Phaseolus vulgaris, L.) and Bel W₃ tobacco (Nicotiana tabacum, L.) were grown and exposed to 40 pphm ozone for 1 hr under a range of light intensities, temperatures, and relative humidities. Foliar injury to the more sensitive plant leaves was determined on the third day after exposure. Each atmospheric factor was independently assessed. Two significant three-way interactions were found: exposure light intensity by growth light intensity by species, and growth temperature by exposure temperature by species. Three significant two-way interactions were found for humidity: growth humidity by exposure humidity, growth humidity by species, and exposure humidity by species. The sensitivity of each species to ozone changed with changes in each environmental condition.     

Response to ambient ozone of two white clover (Trifolium repens L.cv. "Regal") clones, one resistant and one sensitive, grown in a Mediterranean environment

Two clones of white clover (Trifolium repens L.) differing in ozone tolerance were grown in southern Italy during 1997 and 1998 to study the effects of ambient ozone exposure on yield, leaf morphology and water use. Ambient ozone levels were high in both years with values exceeding the threshold for leaf injury reported in the literature. In both years ozone injury was observed on the sensitive clone (NC-S) but not on the resistant one (NC-R), and leaf and stolon dry matter production was significantly lower in NC-S than in NC-R. However, it cannot be excluded that other factors, such as high temperature, interacted with the effect of ozone on biomass production. The clones differed in morphological characteristics. Lower total leaf area in NC-S plants was due to a smaller number of leaves per plant, but the average area per leaf was higher in NC-S. Specific leaf weight and net assimilation rate were higher in the more productive clone (NC-R). Cumulative plant water use was higher in NC-R in each growth period because of the larger leaf area; by contrast, water use per unit leaf area was higher in NC-S, indicating higher leaf conductance to water vapour. The results suggest that ozone significantly reduces the yield of sensitive white clover plants under well-watered conditions, and that the difference in ozone tolerance between clover clones is related to differences in leaf morphology and water use.     

PLATIN (plant-atmosphere interaction) II: Co-occurrence of high ambient ozone concentrations and factors limiting plant absorbed dose

There is an ongoing debate as to which components of the ambient ozone (O3) exposure dynamics best explain adverse crop yield responses. A key issue is regarding the importance of peak versus mid-range hourly ambient O3 concentrations. While in this paper the importance of peak atmospheric O3 concentrations is not discounted, if they occur at a time when plants are conducive for uptake, the corresponding importance of more frequently occurring mid-range O3 concentrations is described. The probability of co-occurrence of high O3 concentrations and O3 uptake limiting factors is provided using coherent data sets of O3 concentration, air temperature, air humidity, mean horizontal wind velocity and global radiation measured at representative US and German air quality monitoring sites. Using the PLant-ATmosphere INteraction (PLATIN) model, the significance of the aforementioned meteorological parameters on ozone uptake is examined. In addition, the limitations of describing the O3 exposure for plants under ambient, chamberless conditions by SUM06, AOT40 or W126 exposure indices are discussed.     

Prediction of sulfur dioxide concentrations at a site near downtown Santiago,Chile

We have analyzed the possibility to predict hourly averages of sulfur dioxide concentrations in the atmosphere at a site not far from the downtown area in the city of Santiago, Chile. We have compared the forecasts produced assuming persistence, linear regressions and feed forward neural networks. The effect of meteorological conditions is included by using forecasted values of temperature, relative humidity and wind speed at the time of the intended prediction as inputs to the different models. The best predictions for hourly averages are obtained with a three-layer neural network that has hourly averages of sulfur dioxide concentrations every 6 h on the previous day plus the actual values of the meteorological variables as input. Training the network with 1995 data, error in 8 h in advance prediction for 1996 data is of the order of 30%.     

Selecting ozone exposure statistics for determining crop yield loss from air pollutants

Numerous ozone exposure statistics were calculated using hourly ozone data from crop yield loss experiments previously conducted for alfalfa, fresh market and processing tomatoes, cotton, and dry beans in an ambient ozone gradient near Los Angeles, California. Exposure statistics examined included peak (maximum daily hourly) and mean concentrations above specific threshold levels, and concentrations during specific time periods of the day. Peak and mean statistics weighted for ozone concentration and time period statistics weighted for hour of the day were also determined. Polynomial regression analysis was used to relate each of 163 ozone statistics to crop yield. Performance of the various statistics was rated by comparing residual mean square (RMS) values. The analyses demonstrated that no single statistic was best for all crop species. Ozone statistics with a threshold level performed well for most crops, but optimum threshold level was dependent upon crop species and varied with the particular statistics calculated. The data indicated that daily hours of exposure above a critical high-concentration threshold related well to crop yield for alfalfa, market tomatoes, and dry beans. The best statistic for cotton yield was an average of all daily peak ozone concentrations. Several different types of ozone statistics performed similarly for processing tomatoes. These analyses suggest that several ozone summary statistics should be examined in assessing the relationship of ambient ozone exposure to crop yield. Where no clear statistical preference is indicated among several statistics, those most biologically relevant should be selected.     

Estimating contribution of wildland fires to ambient ozone levels in National Parks in the Sierra Nevada, California

Data from four continuous ozone and weather monitoring sites operated by the National Park Service in Sierra Nevada, California, are used to develop an ozone forecasting model and to estimate the contribution of wildland fires on ambient ozone levels. The analyses of weather and ozone data pointed to the transport of ozone precursors from the Central Valley as an important source of pollution in these National Parks. Comparisons of forecasted and observed values demonstrated that accurate forecasts of next-day hourly ozone levels may be achieved by using a time series model with historic averages, expected local weather and modeled PM values as explanatory variables. Results on fire smoke influence indicated occurrence of significant increases in average ozone levels with increasing fire activity. The overall effect on diurnal ozone values, however, was small when compared with the amount of variability attributed to sources other than fire.     

Ozone differentially affects physiological and biochemical responses of two clover species; Trifolium repens and Trifolium pratense

The effect of acute ozone exposure (150 ppb for 3 h) on two clover species, white clover (Trifolium repens L.) and red clover (Trifolium pratense L.) was investigated through the analysis of 10 different physiological and biochemical parameters. Twenty-four hours after fumigation, visible symptoms of injury on leaves were observed only in red clover, but from the biochemical point of view, both species revealed significant ozone-induced modifications. A decrease in the photosynthetic efficiency as well as an increase in the de-epoxidation index and a decrease in the redox state of ascorbate were detected only in T. pratense leaves; no significant change in pigment content was found in either of the two species. On the other hand, both white and red clover showed, although to different extents, significant decreases in the activities of the antioxidant enzymes peroxidase and ascorbate peroxidase. Multivariate statistical analysis revealed not only that ozone affects both species, but also that they differentially respond to the pollutant, confirming the higher sensitivity of Trifolium pratense to ozone exposure.     

Issues with ozone attainment methodology for Houston, TX

To comply with the federal 8-hr ozone standard, the state of Texas is creating a plan for Houston that strictly follows the U.S. Environmental Protection Agency's (EPA) guidance for demonstrating attainment. EPA's attainment guidance methodology has several key assumptions that are demonstrated to not be completely appropriate for the unique observed ozone conditions found in Houston. Houston's ozone violations at monitoring sites are realized as gradual hour-to-hour increases in ozone concentrations, or by large hourly ozone increases that exceed up to 100 parts per billion/hr. Given the time profiles at the violating monitors and those of nearby monitors, these large increases appear to be associated with small parcels of spatially limited plumes of high ozone in a lower background of urban ozone. Some of these high ozone parcels and plumes have been linked to a combination of unique wind conditions and episodic hydrocarbon emission events from the Houston Ship Channel. However, the regulatory air quality model (AQM) does not predict these sharp ozone gradients. Instead, the AQM predicts gradual hourly increases with broad regions of high ozone covering the entire Houston urban core. The AQM model performance can be partly attributed to EPA attainment guidance that prescribes the removal in the baseline model simulation of any episodic hydrocarbon emissions, thereby potentially removing any nontypical causes of ozone exceedances. This paper shows that attainment of all monitors is achieved when days with observed large hourly variability in ozone concentrations are filtered from attainment metrics. Thus, the modeling and observational data support a second unique cause for how ozone is formed in Houston, and the current EPA methodology addresses only one of these two causes.     

A multi-variate statistical model integrating passive sampler and meteorology data to predict the frequency distributions of hourly ambient ozone (O3) concentrations

A multi-variate, non-linear statistical model is described to simulate passive O3 sampler data to mimic the hourly frequency distributions of continuous measurements using climatologic O3 indicators and passive sampler measurements. The main meteorological parameters identified by the model were, air temperature, relative humidity, solar radiation and wind speed, although other parameters were also considered. Together, air temperature, relative humidity and passive sampler data by themselves could explain 62.5-67.5% (R(2)) of the corresponding variability of the continuously measured O3 data. The final correlation coefficients (r) between the predicted hourly O3 concentrations from the passive sampler data and the true, continuous measurements were 0.819-0.854, with an accuracy of 92-94% for the predictive capability. With the addition of soil moisture data, the model can lead to the first order approximation of atmospheric O3 flux and plant stomatal uptake. Additionally, if such data are coupled to multi-point plant response measurements, meaningful cause-effect relationships can be derived in the future.     

Characterizing changes in surface ozone levels in metropolitan and rural areas in the United States for 1980–2008 and 1994–2008

In this analysis, we characterize urban and rural ozone (O₃) trends across the US for the periods 1980–2008 (29 years) and 1994–2008 (15 years) using three exposure metrics, which summarize daily O₃ concentrations to reflect different ways O₃ may affect human health and vegetation. We observe that a statistically significant trend at a specific monitoring site, using one exposure metric, does not necessarily result in a similar trend using the other two metrics. The two most common trends among the monitoring sites are either a continuation of negative trending over the 29-year period or a shift from negative to no trend status, indicating a leveling off of the trending. Very few sites exhibit statistically significant increases in the exposure indices. In characterizing the statistically significant changes in the distribution of hourly average O₃, we observe subtle statistically significant changes in the lower part of the distribution (i.e., below 50 ppb) that are not necessarily captured by the trending patterns associated with the three exposure metrics. Using multisite data from 12 metropolitan cities, we find that as the frequency of higher hourly average concentrations is reduced, the lower hourly average concentrations also move upward toward the mid-level values. The change in the number of the hourly average concentrations in the lower range is consistent with decreased NO scavenging. We recommend assessing possible subtle shifts in O₃ concentrations by characterizing changes in the distribution of hourly average concentrations by month. Identifying statistically significant monthly changes in the mid- and low-level hourly average concentrations may provide important information for assessing changes in physical processes associated with global climate change, long-range transport, and the efficacy of models used for emission and risk reductions. Our results indicate that it is important to investigate the change in the trending pattern with time (e.g., moving 15-year trending) in order to assess how year-to-year variability may influence the trend calculation.     

Ozone and grosswetterlagen

Meteorological conditions have a decisive impact on surface ozone concentrations. In this study, an empirical model is used to explain the interdependence of ozone and grosswetterlagen. Different meteorological parameters such as air temperature, global solar radiation, relative humidity, wind direction and wind speed are used. Additional nitric oxide (NO) was taken as a representative for the emission situation and ozone maximum of the preceding day in order to evaluate the development of the photochemical situation. The dataset includes data collected over a period of three years (1992–1994) from three stations outside of Munich and one in the center of Munich. All values become variables by calculating means, sums or maxima of the basic dataset consisting of half-hour means. Seasonal periodicity of data is detected with Fourier analysis and eliminated by a division method after computing a seasonal index. The dataset is divided into three different grosswetterlagen groups, depending on main wind direction. One mostly cyclonic (westerly winds), onemixed (alternating winds) and one onlyanticyclonic (easterly winds). The last is completed with one summertime group including values from April to August. Factor analysis is performed for each group to obtain independent linear variable combinations. Overall, relative humidity is the dominant parameter, a typical value indicating meteorological conditions during a grosswetterlage. Linear multiple regression analysis is performed using the factors obtained to reveal how the ozone concentrations are explained in terms of meteorological parameters and NO. The results improve from cyclonic to anticyclonic grosswetterlagen in conformance with the increasing significance of photochemistry, indicated by the high solar radiation and high temperature, and the low relative humidity and low wind speed. The explained variance r² reaches its maximum with more than 50 % of the time in Munich center. This empirical model is applicable to the forecasting of local ozone maximum concentrations with a total standard error deviation of 8.5 to 12.8 % and, if ozone concentrations exceed 80 ppb, with a standard error deviation of 5.4 to 9.5 %.     

Ozone and grosswetterlagen

Meteorological conditions have a decisive impact on surface ozone concentrations. In this study, an empirical model is used to explain the interdependence of ozone and grosswetterlagen. Different meteorological parameters such as air temperature, global solar radiation, relative humidity, wind direction and wind speed are used. Additional nitric oxide (NO) was taken as a representative for the emission situation and ozone maximum of the preceding day in order to evaluate the development of the photochemical situation. The dataset includes data collected over a period of three years (1992–1994) from three stations outside of Munich and one in the center of Munich. All values become variables by calculating means, sums or maxima of the basic dataset consisting of half-hour means. Seasonal periodicity of data is detected with Fourier analysis and eliminated by a division method after computing a seasonal index. The dataset is divided into three different grosswetterlagen groups, depending on main wind direction. One mostly cyclonic (westerly winds), one mixed (alternating winds) and one only anticyclonic (easterly winds). The last is completed with one summertime group including values from April to August. Factor analysis is performed for each group to obtain independent linear variable combinations. Overall, relative humidity is the dominant parameter, a typical value indicating meteorological conditions during a grosswetterlage. Linear multiple regression analysis is performed using the factors obtained to reveal how the ozone concentrations are explained in terms of meteorological parameters and NO. The results improve from cyclonic to anticyclonic grosswetterlagen in conformance with the increasing significance of photochemistry, indicated by the high solar radiation and high temperature, and the low relative humidity and low wind speed. The explained variance r² reaches its maximum with more than 50 % of the time in Munich center. This empirical model is applicable to the forecasting of local ozone maximum concentrations with a total standard error deviation of 8.5 to 12.8 % and, if ozone concentrations exceed 80 ppb, with a standard error deviation of 5.4 to 9.5 %.     

Sensitivity of ozone to summertime climate in the eastern USA: A modeling case study

The goal of this modeling study is to determine how concentrations of ozone respond to changes in climate over the eastern USA. The sensitivities of average ozone concentrations to temperature, wind speed, absolute humidity, mixing height, cloud liquid water content and optical depth, cloudy area, precipitation rate, and precipitating area extent are investigated individually. The simulation period consists of July 12–21, 2001, during which an ozone episode occurred over the Southeast. The ozone metrics used include daily maximum 8 h average O₃ concentration and number of grid cells exceeding the US EPA ambient air-quality standard. The meteorological factor that had the largest impact on both ozone metrics was temperature, which increased daily maximum 8 h average O₃ by 0.34 ppb K⁻¹ on average over the simulation domain. Absolute humidity had a smaller but appreciable effect on daily maximum 8 h average O₃ (−0.025 ppb for each percent increase in absolute humidity). While domain-average responses to changes in wind speed, mixing height, cloud liquid water content, and optical depth were rather small, these factors did have appreciable local effects in many areas. Temperature also had the largest effect on air-quality standard exceedances; a 2.5 K temperature increase led to a 30% increase in the area exceeding the EPA standard. Wind speed and mixing height also had appreciable effects on ozone air-quality standard exceedances.     

The Estimation of Personal Exposures to Air Pollutants for a Community-Based Study of Health Effects in Asthmatics—Exposure Model

Estimates of individual personal exposures to ozone, nitrogen dioxide, pollen, temperature, and relative humidity for a group of asthmatics participating In a health effects study were obtained by means of a modeling approach utilizing fixed site monitoring data, regression relationships between fixed site and indoor and outdoor micro-environment concentrations, study subject activity patterns, and study household characteristics. A considerable improvement in the accuracy of exposure assessment using the exposure model instead of fixed site measurements alone was demonstrated for ozone. This large refinement of ozone exposure estimates was achieved using a simplified approach which emphasized the large differences between Indoor and outdoor micro-environmental concentrations, and assumed relatively little heterogeneity in exposure within either of these two broad micro-environmental categories. Major sources of error in the exposure model for ozone Include: failure to Include Indoor microenvironments with no air conditioning in the development of the model, Inability to accurately apportion within-hour time spent in different microenvironments, and misclassification of hour-specific personal location by study subjects.     

Meteorologically adjusted long-term trend of ground-level ozone concentrations in Kaohsiung County,southern Taiwan

Since meteorological changes strongly affect ambient ozone concentrations, trends in concentrations of ozone upon the adjustment of meteorological variations are important of evaluating emission reduction efforts. The goal of this work is to study meteorological effects on the long-term trends of ozone concentration using a multi-variable additive model. Data on the hourly concentrations of ozone were collected from four air-quality stations from 1997 to 2006 in Kaohsiung County to determine the monthly, seasonal and annual average concentrations of ozone. The model incorporates seven meteorological parameters – pressure, temperature, relative humidity, wind speed, wind direction, duration of sunshine and cloud cover. The simulated results show that the long-term ozone concentration increases at 13.84% (or 13.06%) monthly (or annually) after meteorological adjustments, less than at 26.10% (or 23.80%) without meteorological adjustments. Wind speed, duration of sunshine and pressure are the three dominant factors that influence the ground-level ozone levels.     

Modelling stomatal ozone flux across Europe

A model has been developed to estimate stomatal ozone flux across Europe for a number of important species. An initial application of this model is illustrated for two species, wheat and beech. The model calculates ozone flux using European Monitoring and Evaluation Programme (EMEP) model ozone concentrations in combination with estimates of the atmospheric, boundary layer and stomatal resistances to ozone transfer. The model simulates the effect of phenology, irradiance, temperature, vapour pressure deficit and soil moisture deficit on stomatal conductance. These species-specific microclimatic parameters are derived from meteorological data provided by the Norwegian Meteorological Institute (DNMI), together with detailed land-use and soil type maps assembled at the Stockholm Environment Institute (SEI). Modelled fluxes are presented as mean monthly flux maps and compared with maps describing equivalent values of AOT40 (accumulated exposure over threshold of 40 ppb or nl l(-1)), highlighting the spatial differences between these two indices. In many cases high ozone fluxes were modelled in association with only moderate AOT40 values. The factors most important in limiting ozone uptake under the model assumptions were vapour pressure deficit (VPD), soil moisture deficit (for Mediterranean regions in particular) and phenology. The limiting effect of VPD on ozone uptake was especially apparent, since high VPDs resulting in stomatal closure tended to co-occur with high ozone concentrations. Although further work is needed to link the ozone uptake and deposition model components, and to validate the model with field measurements, the present results give a clear indication of the possible implications of adopting a flux-based approach for future policy evaluation.     

Assessing ozone-precursor relationships based on a smog production model and ambient data

A semi-empirical model, Johnson's smog production model (SPM), which relates precursor emissions to ozone levels and estimates the relative effectiveness of volatile organic compounds (VOC) and NOx emission controls, has been evaluated and a modified version of SPM has been introduced. Both versions have been applied to routine data from 1989-1991 in five areas in the United States. In particular, extent parameters, which reveal the relative merit of VOC and NOx controls in reducing high ozone levels, have been calculated. Preliminary applications of SPM reveal interesting features with respect to VOC vs. NOx controls in reducing high ozone levels. For hourly data with ozone > or =0.08 ppm, distributions of extent parameters resulting from the modified SPM show the effectiveness of VOC controls at more monitoring sites than those from Johnson's SPM; however, relative features between the two versions are similar. On the other hand, for hourly data with ozone > or =0.12 ppm, the two SPM versions show very similar relative effectiveness of VOC and NOx controls with chosen values of model parameters. To improve the credibility of SPM, the range of validity of relationships between maximum smog produced or maximum ozone and NOx concentrations must be determined, and the parameters in these relationships must be better determined for typical VOC mixtures. Another essential parameter, which determines the fractional loss of NOy (NO and its oxidation products) from the gas phase must be better determined.     

The effects of meteorology on ozone in urban areas and their use in assessing ozone trends

The United States Environmental Protection Agency issues periodic reports that describe air quality trends in the US. For some pollutants, such as ozone, both observed and meteorologically adjusted trends are displayed. This paper describes an improved statistical methodology for meteorologically adjusting ozone trends as well as characterizes the relationships between individual meteorological parameters and ozone. A generalized linear model that accommodates the nonlinear effects of the meteorological variables was fit to data collected for 39 major eastern US urban areas. Overall, the model performs very well, yielding R² statistics as high as 0.80. The analysis confirms that ozone is generally increasing with increasing temperature and decreasing with increasing relative humidity. Examination of the spatial gradients of these responses show that the effect of temperature on ozone is most pronounced in the north while the opposite is true of relative humidity. By including HYSPLIT-derived transport wind direction and distance in the model, it is shown that the largest incremental impact of wind direction on ozone occurs along the periphery of the study domain, which encompasses major NO_x emission sources.     

The global impact of ozone on agricultural crop yields under current and future air quality legislation

In this paper we evaluate the global impact of surface ozone on four types of agricultural crop. The study is based on modelled global hourly ozone fields for the year 2000 and 2030, using the global 1°×1° 2-way nested atmospheric chemical transport model (TM5). Projections for the year 2030 are based on the relatively optimistic “current legislation (CLE) scenario”, i.e. assuming that currently approved air quality legislation will be fully implemented by the year 2030, without a further development of new abatement policies. For both runs, the relative yield loss due to ozone damage is evaluated based on two different indices (accumulated concentration above a 40 ppbV threshold and seasonal mean daytime ozone concentration respectively) on a global, regional and national scale. The cumulative metric appears to be far less robust than the seasonal mean, while the seasonal mean shows satisfactory agreement with measurements in Europe, the US, China and Southern India and South-East Asia.Present day global relative yield losses are estimated to range between 7% and 12% for wheat, between 6% and 16% for soybean, between 3% and 4% for rice, and between 3% and 5% for maize (range resulting from different metrics used). Taking into account possible biases in our assessment, introduced through the global application of “western” crop exposure–response functions, and through model performance in reproducing ozone-exposure metrics, our estimates may be considered as being conservative.Under the 2030 CLE scenario, the global situation is expected to deteriorate mainly for wheat (additional 2–6% loss globally) and rice (additional 1–2% loss globally). India, for which no mitigation measures have been assumed by 2030, accounts for 50% of these global increase in crop yield loss. On a regional-scale, significant reductions in crop losses by CLE-2030 are only predicted in Europe (soybean) and China (wheat).Translating these assumed yield losses into total global economic damage for the four crops considered, using world market prices for the year 2000, we estimate an economic loss in the range $14–$26 billion. About 40% of this damage is occurring in China and India. Considering the recent upward trends in food prices, the ozone-induced damage to crops is expected to offset a significant portion of the GDP growth rate, especially in countries with an economy based on agricultural production.     

Aircraft measurement of ozone turbulent flux in the atmospheric boundary layer

In May 1995, the “Chimie-Creil 95” experiment was undertaken in the north of France. The field data are first used to validate the methodology for airborne measurement of ozone flux. A certain number of methodological problems due to the location of the fast ozone sensor inside the airplane are, furthermore discussed. The paper describes the instrumentation of the ARAT (Avion de Recherche Atmosphérique et de Télédétection), an atmospheric research and remote-sensing aircraft used to perform the airborne measurements, the area flown over, the meteorological conditions and boundary layer stability conditions. These aircraft measurements are then used to determine ozone deposition velocity and values are proposed for aerodynamic, bulk transfer coefficients (ozone and momentum). The paper also establishes the relationship between the normalised standard deviation and stability parameters (z/L) for ozone, temperature, humidity and vertical velocity. The laws obtained are then presented.