Estimated crop yield losses due to surface ozone exposure and economic damage in India

In this study, we estimate yield losses and economic damage of two major crops (winter wheat and rabi rice) due to surface ozone (O₃) exposure using hourly O₃ concentrations for the period 2002–2007 in India. This study estimates crop yield losses according to two indices of O₃ exposure: 7-h seasonal daytime (0900–1600 hours) mean measured O₃ concentration (M7) and AOT40 (accumulation exposure of O₃ concentration over a threshold of 40 parts per billion by volume during daylight hours (0700–1800 hours), established by field studies. Our results indicate that relative yield loss from 5 to 11 % (6–30 %) for winter wheat and 3–6 % (9–16 %) for rabi rice using M7 (AOT40) index of the mean total winter wheat 81 million metric tons (Mt) and rabi rice 12 Mt production per year for the period 2002–2007. The estimated mean crop production loss (CPL) for winter wheat are from 9 to 29 Mt, account for economic cost loss was from 1,222 to 4,091 million US$ annually. Similarly, the mean CPL for rabi rice are from 0.64 to 2.1 Mt, worth 86–276 million US$. Our calculated winter wheat and rabi rice losses agree well with previous results, providing the further evidence that large crop yield losses occurring in India due to current O₃ concentration and further elevated O₃ concentration in future may pose threat to food security.     

Exposure to hazardous air pollutants along Oba Akran road, Lagos-Nigeria

We measured toxic air pollutants along Oba Akran road in Lagos to evaluate pedestrian exposure. PM₁₀, CO, O₃, NO₂, SO₂, CH₄, noise, wind velocity and temperature were measured simultaneously with portable analyzers. Our results showed that pedestrian exposure to PM₁₀ (with an average of 274.6 μg m⁻³ for all samples) and CO (with an average of 19.27 ppm for all samples) was relatively high. CO is a traffic-related pollutant, so the influence of the local traffic emissions on CO levels is strong. The high concentration of the PM₁₀ measured at the three environments also suggests that the traffic is a major source of ultrafine particles. The overall average concentrations for the 72-day experimental period for SO₂, NO₂ and O₃ are 101.2, 62.5 and 0.32 ppb respectively, all of which are below the US national ambient air quality standards. Strong traffic impacts can be observed from the concentrations of some of these pollutants measured in these three environments. Most clear is a reflection of diesel truck traffic activity rich in black carbon concentrations. The diurnal variation of O₃ and NO₂ also showed that NO₂ was depleted by photochemically formed O₃ during the day and replenished at night as O₃ was destroyed. A multivariate statistical analysis (Principal Component Analysis, Factor Analysis) has been applied to a set of data in order to determine the contribution of different sources. It was found that the main principal components, extracted from the air pollution data, were related to gasoline combustion, oil combustion and ozone interactions.     

Concentrations of mobile source air pollutants in urban microenvironments

Human exposures to criteria and hazardous air pollutants (HAPs) in urban areas vary greatly due to temporal-spatial variations in emissions, changing meteorology, varying proximity to sources, as well as due to building, vehicle, and other environmental characteristics that influence the amounts of ambient pollutants that penetrate or infiltrate into these microenvironments. Consequently, the exposure estimates derived from central-site ambient measurements are uncertain and tend to underestimate actual exposures. The Exposure Classification Project (ECP) was conducted to measure pollutant concentrations for common urban microenvironments (MEs) for use in evaluating the results of regulatory human exposure models. Nearly 500 sets of measurements were made in three Los Angeles County communities during fall 2008, winter 2009, and summer 2009. MEs included in-vehicle, near-road, outdoor, and indoor locations accessible to the general public. Contemporaneous 1- to 15-min average personal breathing zone concentrations of carbon monoxide (CO), carbon dioxide (CO₂), volatile organic compounds (VOCs), nitric oxide (NO), nitrogen oxides (NO_x), particulate matter (<2.5 μm diameter; PM_2.5) mass, ultrafine particle (UFP; <100 nm diameter) number, black carbon (BC), speciated HAPs (e.g., benzene, toluene, ethylbenzene, xylenes [BTEX], 1,3-butadiene), and ozone (O₃) were measured continuously. In-vehicle and inside/outside measurements were made in various passenger vehicle types and in public buildings to estimate penetration or infiltration factors. A large fraction of the observed pollutant concentrations for on-road MEs, especially near diesel trucks, was unrelated to ambient measurements at nearby monitors. Comparisons of ME concentrations estimated using the median ME/ambient ratio versus regression slopes and intercepts indicate that the regression approach may be more accurate for on-road MEs. Ranges in the ME/ambient ratios among ME categories were generally greater than differences among the three communities for the same ME category, suggesting that the ME proximity factors may be more broadly applicable to urban MEs.

Implications:Estimates of population exposure to air pollutants extrapolated from ambient measurements at ambient fixed site monitors or exposure surrogates are prone to uncertainty. This study measured concentrations of mobile source air toxics (MSAT) and related criteria pollutants within in-vehicle, outdoor near-road, and indoor urban MEs to provide multipollutant ME measurements that can be used to calibrate regulatory exposure models.     

Ambient air pollution and term birth weight in Texas from 1998 to 2004

Previous studies have explored the association between air pollution levels and adverse birth outcomes such as lower birth weight. Existing literature suggests an association, although results across studies are not consistent. Additional research is needed to confirm the effect, investigate the exposure window of importance, and distinguish which pollutants cause harm.

We assessed the association between ambient pollutant concentrations and term birth weight for 1,548,904 births in TX from 1998 to 2004. Assignment of prenatal exposure to air pollutants was based on maternal county of residence at the time of delivery. Pollutants examined included particulate matter with aerodynamic diameter ≤10 and ≤2.5 µm (PM₁₀ and PM_2.5), sulfur dioxide (SO₂), nitrogen dioxide (NO₂), carbon monoxide (CO), and ozone (O₃). We applied a linear model with birth weight as a continuous variable. The model was adjusted for known risk factors and region. We assessed pollutant effects by trimester to identify biological exposure window of concern, and explored interaction due to race/ethnicity.

An interquartile increase in ambient pollutant concentrations of SO₂ and O₃ was associated with a 4.99-g (95% confidence interval [CI], 1.87–8.11) and 2.72-g (95% CI, 1.11–4.33) decrease in birth weight, respectively. Lower birth weight was associated with exposure to O₃ in the first and second trimester, whereas results were not significant for other pollutants by trimester. A positive association was exhibited for PM_2.5 in the first trimester. Effects estimates for PM₁₀ and PM_2.5 were inconsistent across race/ethnic groups.

Current ambient air pollution levels may be increasing the risk of lower birth weight for some pollutants. These risks may be increased for certain racial/ethnic groups. Additional research including consideration of improved methodology is needed to investigate these findings. Future studies should examine the influence of residual confounding.

Implications: This is one of the most comprehensive studies examining criteria air pollutants and lower birth weight in Texas. Our findings confirm results found previously for adverse effects of the air pollutant SO₂ on lower birth weight. Results from our study suggest that adverse pregnancy outcomes such as lower birth weight can occur even while maintaining air pollution levels below regulatory standards. Future studies should incorporate the assessment of differential pollutant exposure as well as effect estimates by race/ethnicity with individual and community-level social factors in order to enhance our understanding of how physical, social, and host factors influence birth outcomes.

Supplemental Materials: Supplementary information relating to characteristics of excluded births, distribution of air pollutant monitors by pollutant, and correlation coefficients of the air pollutants is available in the publisher's online edition of the Journal of the Air & Waste Management Association.     

Characterization of air manganese exposure estimates for residents in two Ohio towns

This study was conducted to derive receptor-specific outdoor exposure concentrations of total suspended particulate (TSP) and respirable (d_ae ≤ 10 µm) air manganese (air-Mn) for East Liverpool and Marietta (Ohio) in the absence of facility emissions data, but where long-term air measurements were available. Our “site-surface area emissions method” used U.S. Environmental Protection Agency’s (EPA) AERMOD (AMS/EPA Regulatory Model) dispersion model and air measurement data to estimate concentrations for residential receptor sites in the two communities. Modeled concentrations were used to create ratios between receptor points and calibrated using measured data from local air monitoring stations. Estimated outdoor air-Mn concentrations were derived for individual study subjects in both towns. The mean estimated long-term air-Mn exposure levels for total suspended particulate were 0.35 μg/m³ (geometric mean [GM]) and 0.88 μg/m³ (arithmetic mean [AM]) in East Liverpool (range: 0.014–6.32 μg/m³) and 0.17 μg/m³ (GM) and 0.21 μg/m³ (AM) in Marietta (range: 0.03–1.61 μg/m³). Modeled results compared well with averaged ambient air measurements from local air monitoring stations. Exposure to respirable Mn particulate matter (PM₁₀; PM <10 μm) was higher in Marietta residents.

Implications: Few available studies evaluate long-term health outcomes from inhalational manganese (Mn) exposure in residential populations, due in part to challenges in measuring individual exposures. Local long-term air measurements provide the means to calibrate models used in estimating long-term exposures. Furthermore, this combination of modeling and ambient air sampling can be used to derive receptor-specific exposure estimates even in the absence of source emissions data for use in human health outcome studies.     

An investigation of widespread ozone damage to the soybean crop in the upper Midwest determined from ground-based and satellite measurements

Elevated concentrations of ground-level ozone (O₃) are frequently measured over farmland regions in many parts of the world. While numerous experimental studies show that O₃ can significantly decrease crop productivity, independent verifications of yield losses at current ambient O₃ concentrations in rural locations are sparse. In this study, soybean crop yield data during a 5-year period over the Midwest of the United States were combined with ground and satellite O₃ measurements to provide evidence that yield losses on the order of 10% could be estimated through the use of a multiple linear regression model. Yield loss trends based on both conventional ground-based instrumentation and satellite-derived tropospheric O₃ measurements were statistically significant and were consistent with results obtained from open-top chamber experiments and an open-air experimental facility (SoyFACE, Soybean Free Air Concentration Enrichment) in central Illinois. Our analysis suggests that such losses are a relatively new phenomenon due to the increase in background tropospheric O₃ levels over recent decades. Extrapolation of these findings supports previous studies that estimate the global economic loss to the farming community of more than $10 billion annually.     

The co-occurrence of potentially phytotoxic concentrations of various gaseous air pollutants

Studies on impacts of air pollutants on vegetation have focused primarily on individual pollutants: ozone, sulfur dioxide and nitrogen dioxide. The impacts of pollutant combinations have not been extensively studied and there has been no concerted effort to ensure that experimental regimes for combined pollutant exposures are representative of ambient pollutant concentration, frequency, duration and time intervals between events. Most studies concerning the impact of pollutant combinations on vegetation have used concentrations of 0.05 ppm and greater. Therefore, co-occurrence was defined as the simultaneous occurrence of hourly averaged concentrations of 0.05 ppm or greater for pollutant pairs (SO₂/NO₂, O₃/SO₂, or O₃/NO₂). Air quality information from three data bases (EPA-SAROAD, EPRI-SURE and TVA) was analyzed to determine the frequency of co-occurrence for pollutant pairs. Ambient air quality data representing a diverse range of monitoring sites (e.g. rural, remote, city center, urban, near urban, etc.) were used in the analysis. Results showed that at most sites (1) the co-occurrence of two-pollutant mixtures lasted only a few hours per episode, (2) the time interval between episodes was generally large (weeks, sometimes months) and (3) most studies have used more intense exposure regimes than occurred at most monitored sites. When designing vegetation experiments for assessing pollutant mixture effects, it may be desirable to give greater emphasis to sequential patterns of exposure. It is suggested that future work is required before a reliable estimate can be made of the environmental significance of pollutant mixtures on vegetation.     

Cumulative effects and threshold levels in air pollution mortality: Data analysis of nine large US cities using the NMMAPS dataset

We examined the existence of thresholds, cumulative effects and the homogeneity of five air pollutants on the relative risk of three mortality outcomes using data from nine major US cities using data from NMMAPS. Overall, PM₁₀ (usually 200-day accumulation) and ozone (3-day accumulation) were the two important predictors of outcome but their effect was not uniform across the nine cities. Many models exhibited thresholds (25–45 μm g/m³ for PM₁₀, and 10–45 ppb for O₃). Our preliminary exploratory analyses suggest that the use of a linear, no threshold, model for pollution studies is not consistent with the observed data. The heterogeneity in the risk estimates across the nine cities suggests combining the local risk estimates to obtain a national risk estimate may not be justifiable and the estimate is likely to be confounded.     

Evaluation of air quality zone classification methods based on ambient air concentration exposure

Air quality zones are used by regulatory authorities to implement ambient air standards in order to protect human health. Air quality measurements at discrete air monitoring stations are critical tools to determine whether an air quality zone complies with local air quality standards or is noncompliant. This study presents a novel approach for evaluation of air quality zone classification methods by breaking the concentration distribution of a pollutant measured at an air monitoring station into compliance and exceedance probability density functions (PDFs) and then using Monte Carlo analysis with the Central Limit Theorem to estimate long-term exposure. The purpose of this paper is to compare the risk associated with selecting one ambient air classification approach over another by testing the possible exposure an individual living within a zone may face. The chronic daily intake (CDI) is utilized to compare different pollutant exposures over the classification duration of 3 years between two classification methods. Historical data collected from air monitoring stations in Kuwait are used to build representative models of 1-hr NO₂ and 8-hr O₃ within a zone that meets the compliance requirements of each method. The first method, the “3 Strike” method, is a conservative approach based on a winner-take-all approach common with most compliance classification methods, while the second, the 99% Rule method, allows for more robust analyses and incorporates long-term trends. A Monte Carlo analysis is used to model the CDI for each pollutant and each method with the zone at a single station and with multiple stations. The model assumes that the zone is already in compliance with air quality standards over the 3 years under the different classification methodologies. The model shows that while the CDI of the two methods differs by 2.7% over the exposure period for the single station case, the large number of samples taken over the duration period impacts the sensitivity of the statistical tests, causing the null hypothesis to fail. Local air quality managers can use either methodology to classify the compliance of an air zone, but must accept that the 99% Rule method may cause exposures that are statistically more significant than the 3 Strike method.

Implications: A novel method using the Central Limit Theorem and Monte Carlo analysis is used to directly compare different air standard compliance classification methods by estimating the chronic daily intake of pollutants. This method allows air quality managers to rapidly see how individual classification methods may impact individual population groups, as well as to evaluate different pollutants based on dosage and exposure when complete health impacts are not known.     

Exploring relationships between outdoor air particulate-associated polycyclic aromatic hydrocarbon and PM2.5: A case study of benzo(a)pyrene in California metropolitan regions

Polycyclic aromatic hydrocarbons (PAHs) and particulate matter (PM) are co-pollutants emitted as by-products of combustion processes. Convincing evidence exists for PAHs as a primary toxic component of fine PM (PM_2.5). Because PM_2.5 is listed by the US EPA as a “Criteria Pollutant”, it is monitored regularly at sites nationwide. In contrast, very limited data is available on measured ambient air concentrations of PAHs. However, between 1999 and 2001, ambient air concentrations of PM_2.5 and benzo(a)pyrene (BaP) are available for California locations. We use multivariate linear regression models (MLRMs) to predict ambient air levels of BaP in four air basins based on reported PM_2.5 concentrations and spatial, temporal and meteorological variables as variates. We obtain an R² ranging from 0.57 to 0.72 among these basins. Significant variables (p<0.05) include the average daily PM_2.5 concentration, wind speed, temperature and relative humidity, and the coastal distance as well as season, and holiday or weekend. Combining the data from all sites and using only these variables to estimate ambient BaP levels, we obtain an R² of 0.55. These R²-values, combined with analysis of the residual error and cross validation using the PRESS-statistic, demonstrate the potential of our method to estimate reported outdoor air PAH exposure levels in metropolitan regions. These MLRMs provide a first step towards relating outdoor ambient PM_2.5 and PAH concentrations for epidemiological studies when PAH measurements are unavailable, or limited in spatial coverage, based on publicly available meteorological and PM_2.5 data.     

An Evaluation of the Kriging Method to Predict 7-h Seasonal Mean Ozone Concentrations for Estimating Crop Losses

Using kriging, a statistical technique, the National Crop Loss Assessment Network (NCLAN) program estimated growing season 5-month (May-September) ambient 7-h mean O₃ concentrations for each of the major crop growing areas of the United States for 1978-1982. The O₃ estimates were used to predict economic benefits anticipated by lowering O₃ levels in the United States. This paper reviews NCLAN’s use of kriging to estimate 7-h seasonal mean O₃ concentrations for crop growing regions. Although the original kriging program used by NCLAN incorrectly calculated the diagonal elements of the kriging equations, this omission did not result in significant errors in the predicted estimates. Most of the data used in estimating the 7-h seasonal values were obtained from urban areas; the use of these data tended to underestimate the 7-h seasonal O₃ concentrations in rural areas. It is recommended that only O₃ data that are representative of agricultural areas and have been collected under accepted quality assurance programs be used In future kriging efforts.     

An Air Quality Data Analysis System for Interrelating Effects,Standards, and Needed Source Reductions: Part 10. Potential Ambient O3 Standards to Limit Soybean Crop Reduction

Soybean percent crop reduction was estimated as a function of ambient O₃ concentrations for each of 80 agricultural sites in the National Aerometric Data Bank (NADB) for each available year of data for years 1981-1985. Fourteen O₃ concentration statistics were calculated for each of the resulting 320 site-years of data. The two statistics that correlated best with estimated crop reduction were an effective mean O₃ concentration (1 percent of variance unexplained) and an arithmetic mean O₃ concentration (4 percent unexplained). The worst correlation of the 14 was for the statistic used in the present O₃ National Ambient Air Quality Standard (NAAQS), the second highest daily maximum 1-h O₃ concentration (42 percent unexplained). The number of site-years for estimated percent soybean yield reductions was plotted versus increasing O₃ concentrations for each of the 14 O₃ statistics. A maximum crop reduction line was drawn on each plot. These lines were used to estimate (and list) potential ambient O₃ standards for each of the 14 statistics that would limit soybean crop reduction at agricultural. NADB sites to 5, 10, 15, or 20 percent.     

Vegetation exposure to ozone over the continental United States: Assessment of exposure indices by the Eta-CMAQ air quality forecast model

The main use of air quality forecast (AQF) models is to predict ozone (O₃) exceedances of the primary O₃ standard for informing the public of potential health concerns. This study presents the first evaluation of the performance of the Eta-CMAQ air quality forecast model to predict a variety of widely used seasonal mean and cumulative O₃ exposure indices associated with vegetation using the U.S. AIRNow O₃ observations. These exposure indices include two concentration-based O₃ indices, M7 and M12 (the seasonal means of daytime 7-h and 12-h O₃ concentrations, respectively), and three cumulative exposure-based indices, SUM06 (the sum of all hourly O₃ concentrations ≥ 0.06 ppm), W126 (hourly concentrations weighed by a sigmoidal weighting function), and AOT40 (O₃ concentrations accumulated over a threshold of 40 ppb during daylight hours). During a three-month simulation (July–September 2005), the model over predicted the M7 and M12 values by 8–9 ppb, or a NMB value of 19% and a NME value of 21%. The model predicts a central belt of high O₃ extending from Southern California to Middle Atlantic where the seasonal means, M7 and M12 (the seasonal means of daytime 7-h and 12-h O₃ concentrations), are higher than 50 ppbv. In contrast, the model is less capable of reproducing the observed cumulative indices. For AOT40, SUM06 and W126, the NMB and NME values are two- to three-fold of that for M7, M12 or peak 8-h O₃ concentrations. The AOT40 values range from 2 to 33 ppm h by the model and from 1 to 40 ppm h by the monitors. There is a significantly higher AOT40 value experienced in the United States in comparison to Europe. The domain-wide mean SUM06 value is 14.4 ppm h, which is about 30% higher than W126, and 40% higher than AOT40 calculated from the same 3-month hourly O₃ data. This suggests that SUM06 and W126 represent a more stringent standard than AOT40 if either the SUM06 or the W126 was used as a secondary O₃ standard. Although CMAQ considerably over predicts SUM06 and W126 values at the low end, the model under predicts the extreme high exposure values (>50 ppm h). Most of these extreme high values are found at inland California sites. Based on our analysis, further improvement of the model is needed to better capture cumulative exposure indices.     

Use of Plants for Air Pollution Monitoring

Leaf injury data from acute and chronic exposure studies of Dare soybean were regressed against the logarithms of exposure time and O₃ and SO₂ concentrations to develop a new two-pollutant leaf injury model (which explains 88% of the variance) and to calculate the parameters of best fit for this new model and a previously developed one-pollutant model. Using the calculated parameters, the percentage of leaf surface Injured over a growing season by O₃, SO₂, or both simultaneously was estimated for an ambient air sampling site located 2 miles from a coal burning power plant. For this site, the one- and two-pollutant models predicted that SO₂ effects would be negligible If SO₂ concentrations never exceeded the National Ambient Air Quality Standard (NAAQS) of 0.50 ppm, averaged over 3 h. However, calculations suggest that O₃ may injure up to 24% of Dare soybean leaf surface over a growing season even though the O₃ NAAQS of 0.12 ppm, averaged over 1 h, is never exceeded. Because the 3 h SO₂ standard is exceeded at very few places, the O₃ model is usually sufficient to estimate Dare soybean leaf Injury. Leaf injury is estimated by taking the logarithm of the summation of each daytime hour’s exponentiated O₃ concentration (c) measured at an ambient air sampling site over a growing season. This is expressed as: z = -0.0828 + 0.4876 in (Σco₃ ^2.618), where z is the Gaussian transform of percent leaf injury. The methods developed in this paper, using Dare soybean data as an example, may apply to other plants.     

Effects of ozone on growth, yield and leaf gas exchange rates of two Bangladeshi cultivars of wheat (Triticum aestivum L.)

To clarify the effects of O₃ on crop plants cultivated in Bangladesh, two Bangladeshi wheat cultivars (Sufi and Bijoy) were grown in plastic boxes filled with Andisol and exposed daily to charcoal-filtered air or O₃ at 60 and 100 nl l⁻¹ (10:00-17:00) from 13 March to 4 June 2008. The whole-plant dry mass and grain yield per plant of the two cultivars at the final harvest were significantly reduced by the exposure to O₃. Although there was no significant effect of O₃ on stomatal diffusive conductance to H₂O of flag leaf, net photosynthetic rate of the leaf was significantly reduced by the exposure to O_3. The sensitivity of growth, yield, yield components and leaf gas exchange rates to O₃ was not significantly different between the two cultivars. The results obtained in the present study suggest that ambient levels of O₃ may detrimentally affect wheat production in Bangladesh.     

Variation of ozone concentrations in the ambient air of Baghdad

Measurements of ozone concentration in the ambient air of the city of Baghdad were carried out for the period October 1983 to October 1984. The O₃, probably of local origin, showed a typical diurnal and seasonal variation. Maximum daily 1-h O₃ concentrations higher than the international ambient air quality standards were observed regularly during the summer months. High O₃ concentrations during the night were also observed. Scatter diagrams were used to relate the O₃ concentrations with temperature, solar radiation and humidity.     

Controls on hourly variations in urban background air pollutant concentrations

Average 21st century concentrations of urban air pollutants linked to cardiorespiratory disease are not declining, and commonly exceed legal limits. Even below such limits, health effects are being observed and may be related to transient daytime peaks in pollutant concentrations. With this in mind, we analyse >52,000 hourly urban background readings of PM₁₀ and pollutant gases throughout 2007 at a European town with legal annual average concentrations of common pollutants, but with a documented air pollution-related cardiorespiratory health problem, and demonstrate the hourly variations in PM₁₀, SO₂, NO_x, CO and O₃. Back-trajectory analysis was applied to track the arrival of exotic PM₁₀ intrusions, the main controls on air pollutants were identified, and the typical hourly pattern on ambient concentrations during 2007 was profiled. Emphasis was placed on “worst case” data (>90th percentile), when health effects are likely to be greatest. The data show marked daytime variations in pollutants result from rush-hour traffic-related pollution spikes, midday industrial SO₂ maxima, and afternoon O₃ peaks. African dust intrusions enhance PM₁₀ levels at whatever hour, whereas European PM incursions produce pronounced evening peaks due to their transport direction (across an industrial traffic corridor). Transient peak profiling moves us closer to the reality of personal outdoor exposure to inhalable pollutants in a given urban area. We argue that such an approach to monitoring data potentially offers more to air pollution health effect studies than using only 24 h or annual averages.     

DNA damage in Populus tremuloides clones exposed to elevated O3

The effects of elevated concentrations of atmospheric tropospheric ozone (O₃) on DNA damage in five trembling aspen (Populus tremuloides Michx.) clones growing in a free-air enrichment experiment in the presence and absence of elevated concentrations of carbon dioxide (CO₂) were examined. Growing season mean hourly O₃ concentrations were 36.3 and 47.3 ppb for ambient and elevated O₃ plots, respectively. The 4th highest daily maximum 8-h ambient and elevated O₃ concentrations were 79 and 89 ppb, respectively. Elevated CO₂ averaged 524 ppm (+150 ppm) over the growing season. Exposure to O₃ and CO₂ in combination with O₃ increased DNA damage levels above background as measured by the comet assay. Ozone-tolerant clones 271 and 8L showed the highest levels of DNA damage under elevated O₃ compared with ambient air; whereas less tolerant clone 216 and sensitive clones 42E and 259 had comparably lower levels of DNA damage with no significant differences between elevated O₃ and ambient air. Clone 8L was demonstrated to have the highest level of excision DNA repair. In addition, clone 271 had the highest level of oxidative damage as measured by lipid peroxidation. The results suggest that variation in cellular responses to DNA damage between aspen clones may contribute to O₃ tolerance or sensitivity.     

Ground-level ozone in the Pearl River Delta region: Analysis of data from a recently established regional air quality monitoring network

The ambient air quality monitoring data of 2006 and 2007 from a recently established Pearl River Delta (PRD) regional air quality monitoring network are analyzed to investigate the characteristics of ground-level ozone in the region. Four sites covering urban, suburban, rural and coastal areas are selected as representatives for detailed analysis in this paper. The results show that there are distinct seasonal and diurnal cycles in ground-level ozone across the PRD region. Low ozone concentrations are generally observed in summer, while high O₃ levels are typically found in autumn. The O₃ diurnal variations in the urban areas are larger than those at the rural sites. The O₃ concentrations showed no statistically significant difference between weekend and weekdays in contrast to the findings in many other urban areas in the world. The average ozone concentrations are lower in urban areas compared to the sites outside urban centers. Back trajectories are used to show the major air-mass transport patterns and to examine the changes in ozone from the respective upwind sites to a site in the center of the PRD (Wanqingsha). The results show higher average ozone concentrations at the upwind sites in the continental and coastal air masses, but higher 1 h-max O₃ concentrations (by 8–16 ppbv) at the center PRD site under each of air-mass category, suggesting that the ozone pollution in the PRD region exhibits both regional and super-regional characteristics.     

An Air Quality Data Analysis System for Interrelating Effects,Standards, and Needed Source Reductions: Part 8. An Effective Mean O3 Crop Reduction Mathematical Model

A plant injury mathematical model, applied previously to acute and chronic leaf injury data, is used here to model National Crop Loss Assessment Network (NCLAN) data for 15 cultivars and to calculate species parameters from the cultivar analyses. Percent crop yield reduction is estimated as a function of a new parameter, the effective mean O₃ concentration: m_e = [(Σ c_h ^?1/v)/n]^?v, where c_h is the hourly average ambient O₃ concentration for each daytime hour (defined here as 9:00 A.M.–4:00 P.M., always standard time) of data available at an air sampling site for summer (defined here as June 1–August 31), n is the total number of such available hours, and v is an exposure time-concentration parameter, calculated here to be approximately –0.376. Crop yield reduction for soybean is calculated here as z = 0.478 In (tm_e ^2-66) – 0.42, where z is the Gaussian transform of percent crop reduction, t is the hours of exposure (525 h is used here; 7 h/day for 75 days), and In indicates that the natural logarithm is taken of the quantity within parentheses. Crop yield reductions for seven plant species are estimated with similar equations for each of the 1824 site-years of 1981–1983 hourly O₃ concentration data available in the National Aerometric Data Bank (NADB). County-average effective mean O₃ concentrations are indicated by shading on a U.S. map. State-average O₃ parameters and estimated percent crop yield reductions are tabulated. The National Ambient Air Quality Standard (NAAQS) for O₃ specifies that, on the average, the second highest daily maximum 1-h average O₃ concentration in a year shall not exceed 0.12 ppm. For years 1981-1983,71% of the NADB sites recorded annual second highest daily maximum 1-h average O3 concentrations below 0.125 ppm (for summer daytime hours). Ambient O₃ concentrations reduced the total U.S. crop yield an estimated 5% for years 1981–1983. (Summer, daytime, and all acronyms are always used herein as defined above.)