Alfalfa nutritive quality for ruminant livestock as influenced by ambient air quality in west-central Alberta

Alfalfa (Medicago sativa) nutritive quality response to ambient ozone (O(3)), sulfur dioxide (SO(2)) and oxides of nitrogen (NO(x)) were assessed at three locations in west-central Alberta, Canada (1998-2002). Yield data were segregated into high and low relative to overall median yield. Ozone concentrations (hourly median and 95th-percentile) and precipitation (P) contributed 69 and 29%, respectively, to the variability in crude protein (CP) concentration in low-yielding alfalfa, whereas mean temperature (T) and relative humidity (RH) collectively influenced 98% of the variation in CP in high-yielding alfalfa. Three-fourths of the accounted variation in relative feed value (RFV) of low-yielding alfalfa was attributable to P, T and RH, whereas median and 95th-percentile hourly O(3) concentrations and SO(2) and NO(x) exposure integrals contributed 25%. In contrast, air quality, (mainly O(3)) influenced 86% of the accounted variation in RFV of high-yielding alfalfa, and T and P collectively contributed 14%.     

A numerical analysis of the combined open-top chamber data from the USA and Europe on ambient ozone and negative crop responses

Statistical analysis was performed using selected sets of combined data from the US National Crop Loss Assessment Network and the European Open-Top Chambers Programme to examine the relationships between the occurrences of hourly ambient ozone (O3) concentrations and adverse crop yield responses. The results suggest that the frequency of occurrences of relatively low hourly O3 concentrations ( approximately <35 ppb) are not as important as moderate to higher concentrations in eliciting negative crop biomass responses. They also suggest that daily peak (highest) hourly O3 values ( approximately >90 ppb) may not be as critical, most likely because they frequently do not occur during time periods when conditions that promote atmospheric conductivity (O3 deposition) and plant uptake (O3 absorption) are in coherence.     

Ambient ozone (O3) and adverse crop response: a unified view of cause and effect

This paper presents a cohesive view of the dynamics of ambient O(3) exposure and adverse crop response relationships, coupling the properties of photochemical O(3) production, flux of O(3) from the atmosphere into crop canopies and the crop response per se. The results from two independent approaches ((a) statistical and (b) micrometeorological) were analyzed for understanding cause-effect relationships of the foliar injury responses of tobacco cv Bel-W3 to the exposure dynamics of ambient O(3) concentrations. Similarly, other results from two independent approaches were analyzed in: (1) establishing a micrometeorological relationship between hourly ambient O(3) concentrations and their vertical flux from the air into a natural grassland canopy; and (2) establishing a statistical relationship between hourly ambient O(3) concentrations in long-term, chronic exposures and crop yield reductions. Independent of the approach used, atmospheric conditions appeared to be most conducive and the crop response appeared to be best explained statistically by the cumulative frequency of hourly ambient O(3) concentrations between 50 ppb and 90 ppb (100 and 180 microg m(-3)). In general, this concentration range represents intermediate or moderately enhanced hourly O(3) values in a polluted environment. Further, the diurnal occurrence of this concentration range (often approximately between 0900 and 1600 h in a polluted, agricultural environment) coincided with the optimal CO(2) flux from the atmosphere into the crop canopy, thus high uptake. The frequency of occurrence of hourly O(3) concentrations > 90 ppb (180 microg m(-3)) appeared to be of little importance and such concentrations in general appeared to occur during atmospheric conditions which did not facilitate optimal vertical flux into the crop canopy, thus low uptake. Alternatively, when > 90 ppb (180 microg m(-3)) O(3) concentrations occurred during the 0900-1600 h window, their frequency of occurrence was low in comparison to the 50-90 ppb (100-180 microg m(-3)) range. Based on the overall results, we conclude that if the cumulative frequency of hourly ambient O(3) concentrations between 50-62 ppb (100-124 microg m(-3)) occurred during 53% of the growing season and the corresponding cumulative frequency of hourly O(3) concentrations between 50-74 ppb (100-148 microg m(-3)) occurred during 71% of the growing season, then yield reductions in sensitive crops could be expected, if other factors supporting growth, such as adequate soil moisture are not limiting.     

Ambient ozone and crop loss: establishing a cause-effect relationship

This paper provides the results of a retrospective mathematical analysis of the US NCLAN (National Crop Loss Assessment Network) open-top chamber data. Some 77% of the 73 crop harvests examined, showed no statistically significant yield differences between NF (non-filtered open-top chamber) and AA (chamberless, ambient air) treatments (no easily discernable chamber effects on yield). However, among these cases only seven acceptable examples showed statistically significant yield reductions in NF compared to the CF (charcoal filtered open-top chamber) treatment. An examination of the combined or cumulative hourly ambient O3 frequency distribution for cases with yield loss in NF compared to a similar match of cases without yield loss showed that the mean, median and the various percentiles were all higher (>/= 3 X) in the former in contrast to the latter scenario. The combined frequency distribution of hourly O3 concentrations for the cases with yield loss in NF were clearly separated from the corresponding distribution with no yield loss, at O3 concentrations > 49 ppb. Univariate linear regressions between various O3 exposure parameters and per cent yield losses in NF showed that the cumulative frequency of occurrence of O3 concentrations between 50 and 87 ppb was the best predictor (adjusted R2 = 0.712 and p = 0.011). This analysis also showed that the frequency distribution of hourly concentrations up to 87 ppb O3 represented a critical point, since the addition of the frequency distributions of > 87 ppb O3 did not improve the R2 values. In fact as the frequency of hourly O3 concentrations included in the regression approached 50-100 ppb, the R2 value decreased substantially and the p value increased inversely. Further, univariate linear regressions between the frequencies of occurrence of various O3 concentrations between 50 and 90 ppb and: (a) cases with no yield difference in NF and (b) cases with yield increase in NF compared to the CF treatment (positive effect) provided no meaningful statistical relationship (adjusted R2 = 0.000) in either category. These results support the basis that additional evaluation of the frequency of occurrence of hourly O3] concentrations between 50 and 87 ppb for cases with the yield reductions could provide a meaningful ambient O3 standard, objective or guideline for vegetation.     

The use of kriging to estimate monthly ozone exposure parameters for the Southeastern United States

This paper explores the feasibility of (1) using kriging to predict the monthly mean of daily 7-h mean (0900-1559) O3 concentrations, (2) using kriging to estimate the per cent of hourly mean O3 concentrations equal to or greater than 0.07 ppm (137 microg m(-3)) for a specific month, and (3) developing a quantitative relationship between the monthly mean of the daily 7-h (0900-1559) average O3 concentration and the monthly number of hourly concentrations > or = 0.08p ppm (157 microg m(-3)). We found that kriging can be used to estimate the (1) monthly mean of daily 7-h mean O3 concentrations and (2) the percentage of hourly concentrations for a given month > or = 0.07 ppm when sufficient spatial coverage was available. However, the per cent > or = 0.07 ppm parameter exhibited much greater relative variability than the monthly 7-h exposure index. A strong statistical association was found between the monthly number of occurrences > or = 0.08 ppm and monthly 7-h mean concentrations above 0.05 ppm (98 microg m(-3)). Because of the variability that cumulative indices, such as the monthly percentage of hourly concentrations > or = 0.07 ppm , exhibit from site to site, it appears that whether kriging techniques or mathematical regressions are used to estimate the number of elevated O3 hourly concentrations above selected thresholds, large uncertainties associated with the predicted values will exist. These large uncertainties will make it difficult to accurately estimate vegetation effects caused by ambient levels of O3. However, if a generalized quantitative relationship between repeated occurrences of hourly mean concentrations > or = 0.07 ppm or > or = 0.08 and vegetation effects can be developed, it may be possible, using kriged monthly values accompanied with confidence intervals, to identify those areas where vegetation may be at risk. However, before it will be possible to implement such an approach, researchers will have to better quantify the relationship between realistic O3 exposures and vegetation effects.     

Ozone effects on growth and assimilate partitioning in alfalfa, Medicago sativa L

Alfalfa (Medicago sativa L.) were exposed to O(3) concentrations varying between 118 x 10(-6) microg cm(-3) (0.06 ppm) and 157 x 10(-6) microg cm(-3) (0.08 ppm) for 6 h per day 5 days per week for several weeks. Typical plants were sacrificed weekly, and growth parameters were measured. O(3) reduced overall growth, relative growth rates and unit leaf rates in alfalfa before it was cut, indicating that O(3) had reduced photosynthesis. However, after the alfalfa was cut, these same parameters indicated that in some cases, O(3)-stressed plants had greater photosynthetic rates than controls during regrowth. O(3) also altered dry matter partitioning. Roots were most affected, followed by leaves and stems, respectively. In general, O(3) reduced photosynthate production and reduced the proportion of photosynthate partitioned to roots relative to leaves and stems. This could reduce starch reserves in alfalfa, and be detrimental to stand longevity. However, the post-cutting study indicated that at least some alfalfa cultivars may be able to acclimate to O(3)-stress, though plants did not fully recover from pre-cutting differences.     

Ozone and other air quality-related variables affecting visibility in the southeast United States

An analysis of ozone (O3) concentrations and several other air quality-related variables was performed to elucidate their relationship with visibility at five urban and semi-urban locations in the southeast United States during the summer seasons of 1980-1996. The role and impact of O3 on aerosols was investigated to ascertain a relationship with visibility. Regional trend analysis over the 1980s reveals an increase in maximum O3 concentration coupled with a decrease in visibility. However, a similar analysis for the 1990s shows a leveling-off of both O3 and visibility; in both cases, the results were not statistically significant at the 5% level. A case study of site-specific trends at Nashville, TN, followed similar trends. To better understand the relationships between O3 concentration and visibility, the analysis was varied from yearly through daily to hourly averaged values. This increased temporal resolution showed a statistically significant inverse relationship between visibility and O3. Site-specific hourly r2 values ranged from 0.02 to 0.43. Additionally, by performing back-trajectory analysis, it was found that the visibility degraded by air mass migration over polluted areas.     

Assessment of a regulatory model's performance relative to large spatial heterogeneity in observed ozone in Houston, Texas

In Houston, some of the highest measured 8-hr ozone (O3) peaks are characterized by sudden increases in observed concentrations of at least 40 ppb in 1 hr or 60 ppb in 2 hr. Measurements show that these large hourly changes appear at only a few monitors and span a narrow geographic area, suggesting a spatially heterogeneous field of O3 concentrations. This study assessed whether a regulatory air quality model (AQM) can simulate this observed behavior. The AQM did not reproduce the magnitude or location of some of the highest observed hourly O3 changes, and it also failed to capture the limited spatial extent. On days with measured large hourly changes in O3 concentrations, the AQM predicted high O3 over large regions of Houston, resulting in overpredictions at several monitors. This analysis shows that the model can make high O3, but on these days the predicted spatial field suggests that the model had a different cause. Some observed large hourly changes in O3 concentrations have been linked to random releases of industrial volatile organic compounds (VOCs). In the AQM emission inventory, there are several emission events when an industrial point source increases VOC emissions in excess of 10,000 mol/hr. One instance increased predicted downwind O3 concentrations up to 25 ppb. These results show that the modeling system is responsive to a large VOC release, but the timing and location of the release, and meteorological conditions, are critical requirements. Attainment of the O3 standard requires the use of observational data and AQM predictions. If the large observed hourly changes are indicative of a separate cause of high O3, then the model may not include that cause, which might result in regulators enacting control strategies that could be ineffective.     

A statistical approach to estimate O3 uptake of ponderosa pine in a mediterranean climate

In highly polluted sites, stomatal behavior is sluggish with respect to light, vapor pressure deficit, and internal CO2 concentration (Ci) and poorly described by existing models. Statistical models were developed to estimate stomatal conductance (gs) of 40-year-old ponderosa pine at three sites differing in pollutant exposure for the purpose of calculating O3 uptake. Gs was estimated using julian day, hour of day, pre-dawn xylem potential and photosynthetic photon flux density (PPFD). The median difference between estimated and observed field gs did not exceed 10 mmol H2O m(-2) s(-1), and estimated gs within 95% confidence intervals. 03 uptake was calculated from hourly estimated gs, hourly O3 concentration, and a constant to correct for the difference in diffusivity between water vapor and 03. The simulation model TREGRO was also used to calculate the cumulative 03 uptake at all three sites. 03 uptake estimated by the statistical model was higher than that simulated by TREGRO because gas exchange rates were proportionally higher. O3 exposure and uptake were significantly correlated (r2>0.92), because O3 exposure and gs were highly correlated in both statistical and simulation models.     

Effects of ozone on yield, growth, and root starch concentrations of two alfalfa (Medicago sativ A L.) cultivars

Ozone (O3) is considered to be a major air pollutant that affects the yield of several sensitive crop species. Its concentration may reach phytotoxic levels several times during the growing season in Eastern Canada. This study was initiated to evaluate the O3 effects on alfalfa, a major crop species. The objective was to compare the yield and growth parameters of the main alfalfa cultivar used in Québec, Apica, to a cultivar more tolerant to O3, Team. Effects on root starch concentrations were also examined as this parameter is an important indicator of alfalfa perennity. The results obtained have shown that the forage yield of Apica was more reduced by O3 during two growing seasons than the yield of Team. For O3 concentrations of 20 to 40 nl liter(-1), yield reductions were 14-26% for Apica and 0-20% for Team. Whereas Apica could be considered more susceptible to O3 than Team, the latter has shown contrasting responses from year to year. This fact suggests that the mechanisms involved in O3-tolerance could be modulated by environmental conditions. At low O3 levels, Apica has shown reduced root growth in terms of dry matter and length. However, contrary to the current hypothesis that O3 would affect more root than shoot growth, we were unable to show a consistent alteration of the biomass allocation between the two. Ozone seems to reduce globally the growth of the whole plants. The greater O3-tolerance of Team could partly be associated to its capacity to maintain more leaves, to delay their senescence, or to keep a larger leaf:stem ratio under increasing levels of O3. At the end of the two growing seasons, the amount of starch reserves stored below ground was shown to be reduced by the current O3 levels. This reduction was mainly associated with a decrease in root biomass under O3 stress. This result support the hypothesis that O3 may accelerate alfalfa decline under field conditions.     

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.     

Day-of-Week behavior of atmospheric ozone in three U.S. cities

The weekly cycles of atmospheric ozone (O3) are of interest because they provide information about the response of O3 to changes in anthropogenic emissions from weekdays to weekends. The weekly behavior of O3 in Chicago, IL; Philadelphia, PA; and Atlanta, GA, is contrasted. In Chicago and Philadelphia, maximum 1-hr average O3 increases on weekends. In Atlanta, O3 builds up from Mondays to Fridays and declines during weekends. In all three areas, volatile organic compound (VOC)/nitrogen oxides (NOx) ratios are higher during weekends, resulting from greater than proportionate decreases in NOx relative to VOC emissions. The VOC/NOx ratios correlate with maximum 1-hr O3 concentrations in Chicago, a response consistent with a VOC-sensitive airshed. A weak correlation between O3 concentrations and VOC/NOx ratios in Philadelphia suggests the impact of transported O3, which is formed in upwind VOC-sensitive locations that may be hundreds of kilometers away. Ozone concentrations in Atlanta do not correlate with VOC/NOx ratios but with concentrations of NOx and total reactive nitrogen (NOy) carried over from the previous day. When data from 1986-1990 and 1995-1999 are compared, only small differences in the weekly behavior of O3 are observed in Chicago and Philadelphia. The day-of-week differences in O3 are amplified in the more recent period in Atlanta, a possible result of urban growth.     

The influence of ozone exposure dynamics on the growth and yield of kidney bean

A field experiment was conducted in open-top chambers to assess the importance of peak exposure concentration and exposure frequency on the responses of kidney bean plants to O3. There were five treatments in the study: charcoal-filtered air, constant exposure to 0.05 ppm O3 (131 microg m(-3)) daily. fluctuating exposure to 0.08 ppm O3 on three alternate days, cluster exposure to 0.08 ppm O3 on three consecutive days, and peak exposure to 0.12 ppm O3 on two consecutive days. Exposures lasted 4 h and produced an average weekly exposure-period concentration of approximately 0.05 ppm in the O3-addition treatments and 0.025 ppm in the charcoal-filtered treatment. Exposures began on June 23 and terminated on September 8. Plants were harvested weekly and assessed for the number, area, and dry mass of leaves; dry mass of stems; dry mass of roots; the number of pods; and the incidence of foliar O3 injury. Yield was assessed at the end of the study. There were no consistent differences between the plants receiving charcoal-filtered air and those receiving O3 exposure. Significant differences were detected among the treatments for several of the growth variables assessed at the interim harvests, but in the final two harvests these differences had mostly disappeared. There were no significant effects of the O3-addition treatments on yield when compared to the plants receiving charcoal-filtered air. This indicates that there were no cumulative impacts on plants exposed to 0.12 ppm O3 for 4 h on two consecutive days followed by filtered air compared to plants receiving charcoal-filtered air. The seasonal 7-h average concentrations of O3 in the peak and filtered air treatments were approximately 0.040 and 0.025 ppm, respectively.     

Crop loss assessment for California: modeling losses with different ozone standard scenarios

Crop yield losses were estimated for ambient O3 concentrations and for a series of potential O3 air quality standards for California, including the current statewide 1-h oxidant (O3) standard of 0.10 ppm (196 microg m(-3)), 12-h growing season averages, and other models. A model for statewide losses was developed using hourly O3 data for all sites in the State, county crop productivity data, and available O3 concentration-yield loss equations to determine potential yield losses for each crop in each county in California for 1984. Losses were based on comparison to an estimated background filtered air concentration of 0.025 or 0.027 ppm, for 12 or 7 h, respectively. Potential losses due to ambient air in 1984 were estimated at 19% to 25% for dry beans, cotton, grapes, lemons, onions, and oranges. Losses of 5% to 9% were estimated for alfalfa and sweet corn. Losses of 4% or less were estimated for barley, field corn, lettuce, grain sorghum, rice, corn silage, spinach, strawberries, sugar beets, fresh tomatoes, processing tomatoes, and wheat. Implementation of either a modified rollback to meet the current 1 h California O3 standard (0.10 ppm) or a three-month, 12-h growing season average of 0.045 ppm was necessary to produce large reductions in potential crop losses.     

Use of passive ambient ozone (O3) samplers in vegetation effects assessment

A stochastistic, Weibull probability model was developed and verified to simulate the underlying frequency distributions of hourly ozone (O3) concentrations (exposure dynamics) using the single, weekly mean values obtained from a passive (sodium nitrite absorbent) sampler. The simulation was based on the data derived from a co-located continuous monitor. Although at the moment the model output may be considered as being specific to the elevation and location of the study site, the results were extremely good. This effort for the approximation of the O3 exposure dynamics can be extended to other sites with similar data sets and in developing a generalized understanding of the stochastic O3 exposure-plant response relationships, conferring measurable benefits to the future use of passive O3 samplers, in the absence of continuous monitoring.     

Air quality modeling in the South Coast Air Basin of California: what do the numbers really mean?

This study evaluates air quality model sensitivity to input and to model components. Simulations are performed using the California Institute of Technology (CIT) airshed model. Results show the impacts on ozone (O3) concentration in the South Coast Air Basin (SCAB) of California because of changes in: (1) input data, including meteorological conditions (temperature, UV radiation, mixing height, and wind speed), boundary conditions, and initial conditions (ICs); and (2) model components, including advection solver and chemical mechanism. O3 concentrations are strongly affected by meteorological conditions and, in particular, by temperature. ICs also affect O3 concentrations, especially in the first 2 days of simulation. On the other hand, boundary conditions do not significantly affect the absolute peak O3 concentration, although they do affect concentrations near the inflow boundaries. Moreover, predicted O3 concentrations are impacted considerably by the chemical mechanism. In addition, dispersion of pollutants is affected by the advection routine used to calculate its transport. Comparison among CIT, California Photochemical Grid Model (CALGRID), and Urban Airshed Model air quality models suggests that differences in O3 predictions are mainly caused by the different chemical mechanisms used. Additionally, advection solvers contribute to the differences observed among model predictions. Uncertainty in predicted peak O3 concentration suggests that air quality evaluation should not be based solely on this single value but also on trends predicted by air quality models using a number of chemical mechanisms and with an advection solver that is mass conservative.     

Evaluation of the Mesoscale Meteorological Model (MM5)-Community Multi-Scale Air Quality Model (CMAQ) performance in hindcast and forecast of ground-level ozone

This paper presents the first attempt to apply the Mesoscale Meteorological Model (MM5)-Community Multi-Scale Air Quality Model (CMAQ) model system to simulate ground-level ozone (O3) over the continental Southeast Asia (CSEA) region for both hindcast and forecast purposes. Hindcast simulation was done over the CSEA domain for two historical O3 episodes, January 26-29, 2004 (January episode, northeast monsoon) and March 24-26, 2004 (March episode, southwest monsoon). Experimental forecast was done for next-day hourly O3 during January 2006 over the central part of Thailand (CENTHAI). Available data from 20 ambient monitoring stations in Thailand and 3 stations in Ho Chi Minh City, Vietnam, were used for the episode analysis and for the model performance evaluation. The year 2000 anthropogenic emission inventory prepared by the Center for Global and Regional Environmental Research at the University of Iowa was projected to the simulation year on the basis of the regional average economic growth rate. Hourly emission in urban areas was prepared using ambient carbon monoxide concentration as a surrogate for the emission intensity. Biogenic emissions were estimated based on data from the Global Emissions Inventory Activity. Hindcast simulations (CSEA) were performed with 0.5 degree x 0.5 degree resolution, whereas forecast simulations (CENTHAI) were done with 0.1 degree x 0.1 degree hourly emission input data. MM5-CMAQ model system performance during the selected episodes satisfactorily met U.S. Environmental Protection Agency criteria for O3 for most simulated days. The experiment forecast for next-day hourly O3 in January 2006 yielded promising results. Modeled plumes of ozone in both hindcast and forecast cases agreed with the main wind fields and extended over considerable downwind distances from large urban areas.     

Stochastic model to forecast ground-level ozone concentration at urban and rural areas

Stochastic models that estimate the ground-level ozone concentrations in air at an urban and rural sampling points in South-eastern Spain have been developed. Studies of temporal series of data, spectral analyses of temporal series and ARIMA models have been used. The ARIMA model (1,0,0) x (1,0,1)24 satisfactorily predicts hourly ozone concentrations in the urban area. The ARIMA (2,1,1) x (0,1,1)24 has been developed for the rural area. In both sampling points, predictions of hourly ozone concentrations agree reasonably well with measured values. However, the prediction of hourly ozone concentrations in the rural point appears to be better than that of the urban point. The performance of ARIMA models suggests that this kind of modelling can be suitable for ozone concentrations forecasting.     

On the Evaluation of Predictions from a Gaussian Plume Model

The performance of a CRSTER equivalent Gaussian plume model (CEQM) is examined using data from the EPRI Plume Model Validation study at the Klncaid, Illinois site. Four-way comparisons are made on the ordered statistics or the cumulative frequency distribution (CFD) of maximum hourly observed and predicted concentrations. Using the uniform random distribution and the lognormal random distribution as simple predictive schemes without any physical context, it Is found that the CEQM predicts a concentration CFD which matches the observed CFD significantly closer than the CFD predicted by the uniform random distribution. The two-parameter lognormal random distribution predicts the concentration CFD better than the CEQM over all concentration ranges; however, the CEQM fits the upper range of the concentration distribution better than the lognormal random distribution,, despite the fact that the predictions are generated using dispersion conditions entirely different from those of the observations. The nature of this ergodicity of distribution is probed by exercising CEQM using randomized input based on the observed frequency distributions of the Input parameters instead of feeding the hour-by-hour model input matched by time into CEQM as is customarily done. The exercise of the model by uncoupling the time linkage in model Input has no systematic effect on the predicted cumulative frequency distribution of concentrations. Only at the highest concentration range (99.5% or higher) do the two sets of predictions begin to diverge.