Deposition of ozone to a mature spruce forest: measurements and comparison to models

Removal of ozone at terrestrial surfaces provides a major sink for tropospheric ozone and, therefore, a constraint on the peak concentrations achieved during photochemical episodes. This study reports results from 5 years of almost continuous measurements of vertical profiles of ozone and related meteorological variables over a mature spruce forest in Bavaria. Deposition velocities calculated from flux/gradient and eddy correlation flux measurements have been compared with estimates based on a resistance model and yield satisfactory agreement during fine weather conditions. The results also suggest that biogenic emissions of reactive hydrocarbons from the forest influence the vertical profile of ozone.     

Modeling and direct sensitivity analysis of biogenic emissions impacts on regional ozone formation in the Mexico-U.S. border area

A spatially and temporally resolved biogenic hydrocarbon and nitrogen oxides (NOx) emissions inventory has been developed for a region along the Mexico-U.S. border area. Average daily biogenic non-methane organic gases (NMOG) emissions for the 1700 x 1000 km2 domain were estimated at 23,800 metric tons/day (62% from Mexico and 38% from the United States), and biogenic NOx was estimated at 1230 metric tons/day (54% from Mexico and 46% from the United States) for the July 18-20, 1993, ozone episode. The biogenic NMOG represented 74% of the total NMOG emissions, and biogenic NOx was 14% of the total NOx. The CIT photochemical airshed model was used to assess how biogenic emissions impact air quality. Predicted ground-level ozone increased by 5-10 ppb in most rural areas, 10-20 ppb near urban centers, and 20-30 ppb immediately downwind of the urban centers compared to simulations in which only anthropogenic emissions were used. A sensitivity analysis of predicted ozone concentration to emissions was performed using the decoupled direct method for three dimensional air quality models (DDM-3D). The highest positive sensitivity of ground-level ozone concentration to biogenic volatile organic compound (VOC) emissions (i.e., increasing biogenic VOC emissions results in increasing ozone concentrations) was predicted to be in locations with high NOx levels, (i.e., the urban areas). One urban center--Houston--was predicted to have a slight negative sensitivity to biogenic NO emissions (i.e., increasing biogenic NO emissions results in decreasing local ozone concentrations). The highest sensitivities of ozone concentrations to on-road mobile source VOC emissions, all positive, were mainly in the urban areas. The highest sensitivities of ozone concentrations to on-road mobile source NOx emissions were predicted in both urban (either positive or negative sensitivities) and rural (positive sensitivities) locations.     

Natural emissions for regional modeling of background ozone and particulate matter and impacts on emissions control strategies

Natural emissions adopted in current regional air quality modeling are updated to better describe natural background ozone and PM concentrations for North America. The revised natural emissions include organosulfur from the ocean, NO from lightning, sea salt, biogenic secondary organic aerosol (SOA) precursors, and pre-industrial levels of background methane. The model algorithm for SOA formation was also revised. Natural background ozone concentrations increase by up to 4 ppb in annual average over the southeastern US and Gulf of Mexico due to added NO from lightning while the revised biogenic emissions produced less ozone in the central and western US. Natural PM_2.5 concentrations generally increased with the revised natural emissions. Future year (2018) simulations were conducted for several anthropogenic emission reduction scenarios to assess the impact of the revised natural emissions on anthropogenic emission control strategies. Overall, the revised natural emissions did not significantly alter the ozone responses to the emissions reductions in 2018. With revised natural emissions, ozone concentrations were slightly less sensitive to reducing NOx in the southeastern US than with the current natural emissions due to higher NO from lightning. The revised natural emissions have little impact on modeled PM_2.5 responses to anthropogenic emission reductions. However, there are substantial uncertainties in current representations of natural sources in air quality models and we recommend that further study is needed to refine these representations.     

Impact of biogenic VOC emissions on a tropical cyclone-related ozone episode in the Pearl River Delta region,China

For quantitative estimate of biogenic volatile organic compound emissions (BVOCs) in South China and their impact on the regional atmospheric chemistry, a 3-day tropical cyclone-related ozone episode was modeled using chemical transport model CMAQ, which was driven by the mesoscale meteorological model MM5. Hourly biogenic emission inventories were constructed using the Sparse Matrix Operator Kernel Emissions (SMOKE) model. The simulation results show good agreement with observation data in air temperature, ozone and NO_x levels. The estimated biogenic emissions of isoprene, terpene, and other reactive VOCs (ORVOCs) during this tropical cyclone-related episode are 8500, 3400, and 11 300 ton day⁻¹, respectively. The ratio of isoprene to the total BVOCs was 36.4%. Two test runs were carried out with one incorporated biogenic emissions and the other without. The simulations show that Guangdong province, particularly the Pearl River Delta (PRD) region, was the area most reactive to biogenic emissions in South China. More ozone was produced in all layers under 1500 m when biogenic emissions were included in comparison to that without BVOCs. The net formation of ozone from 9:00 to 15:00 h was the highest near the surface and could reach 38 ppb, which include 4 ppb attributed to biogenic impact. The enhanced ozone due to biogenic emissions first appeared in the PRD region and slowly spread to a greater area in South China. Process analysis indicated that the surface ozone budget was dominated by the vertical transport and dry deposition. The horizontal transport and gas-phase chemical production were relatively small in the surface layer. Presumably, ozone was produced in upper layers within the atmospheric boundary layer and convected down to surface where it is destroyed. When BVOCs was included, apart from the enhancement of gas-phase chemical production of ozone, both the surface deposition and vertical transport were also augmented.     

Extreme value modeling for the analysis and prediction of time series of extreme tropospheric ozone levels: a case study

The occurrence of high concentrations of tropospheric ozone is considered as one of the most important issues of air management programs. The prediction of dangerous ozone levels for the public health and the environment, along with the assessment of air quality control programs aimed at reducing their severity, is of considerable interest to the scientific community and to policy makers. The chemical mechanisms of tropospheric ozone formation are complex, and highly variable meteorological conditions contribute additionally to difficulties in accurate study and prediction of high levels of ozone. Statistical methods offer an effective approach to understand the problem and eventually improve the ability to predict maximum levels of ozone. In this paper an extreme value model is developed to study data sets that consist of periodically collected maxima of tropospheric ozone concentrations and meteorological variables. The methods are applied to daily tropospheric ozone maxima in Guadalajara City, Mexico, for the period January 1997 to December 2006. The model adjusts the daily rate of change in ozone for concurrent impacts of seasonality and present and past meteorological conditions, which include surface temperature, wind speed, wind direction, relative humidity, and ozone. The results indicate that trend, annual effects, and key meteorological variables along with some interactions explain the variation in daily ozone maxima. Prediction performance assessments yield reasonably good results.     

Modeling the influence of biogenic volatile organic compound emissions on ozone concentration during summer season in the Kinki region of Japan

Tropospheric ozone adversely affects human health and vegetation, and biogenic volatile organic compound (BVOC) emission has potential to influence ozone concentration in summer season. In this research, the standard emissions of isoprene and monoterpene from the vegetation of the Kinki region of Japan, estimated from growth chamber experiments, were converted into hourly emissions for July 2002 using the temperature and light intensity data obtained from results of MM5 meteorological model. To investigate the effect of BVOC emissions on ozone production, two ozone simulations for one-month period of July 2002 were carried out. In one simulation, hourly BVOC emissions were included (BIO), while in the other one, BVOC emissions were not considered (NOBIO). The quantitative analyses of the ozone results clearly indicate that the use of spatio-temporally varying BVOC emission improves the prediction of ozone concentration. The hourly differences of monthly-averaged ozone concentrations between BIO and NOBIO had the maximum value of 6 ppb at 1400 JST. The explicit difference appeared in urban area, though the place where the maximum difference occurred changed with time. Overall, BVOC emissions from the forest vegetation strongly affected the ozone generation in the urban area.     

Increase in summer European ozone amounts due to climate change

The local and regional distribution of pollutants is significantly influenced by weather patterns and variability along with the spatial patterns of emissions. Therefore, climatic changes which affect local meteorological conditions can alter air quality. We use the regional air quality model CHIMERE driven by meteorological fields from regional climate change simulations to investigate changes in summer ozone mixing ratios over Europe under increased greenhouse gas (GHG) forcing. Using three 30-year simulation periods, we find that daily peak ozone amounts as well as average ozone concentrations substantially increase during summer in future climate conditions. This is mostly due to higher temperatures and reduced cloudiness and precipitation over Europe and it leads to a higher number of ozone events exceeding information and warning thresholds. Our results show a pronounced regional variability, with the largest effects of climate change on ozone concentrations occurring over England, Belgium, Germany and France. The temperature-driven increase in biogenic emissions appears to enhance the ozone production and isoprene was identified as the most important chemical factor in the ozone sensitivity. We also find that summer ozone levels in future climate projections are similar to those found during the exceptionally warm and dry European summer of 2003. Our simulations suggest that in future climate conditions summer ozone might pose a much more serious threat to human health, agriculture and natural ecosystems in Europe, so that the effects of climate trends on pollutant amounts should be considered in future emission control measures.     

Uncertainties in predicted ozone concentrations due to input uncertainties for the UAM-V photochemical grid model applied to the July 1995 OTAG domain

The photochemical grid model, UAM-V, has been used by regulatory agencies to make decisions concerning emissions controls, based on studies of the July 1995 ozone episode in the eastern US. The current research concerns the effect of the uncertainties in UAM-V input variables (emissions, initial and boundary conditions, meteorological variables, and chemical reactions) on the uncertainties in UAM-V ozone predictions. Uncertainties of 128 input variables have been estimated and most range from about 20% to a factor of two. 100 Monte Carlo runs, each with new resampled values of each of the 128 input variables, have been made for given sets of median emissions assumptions. Emphasis is on the maximum hourly-averaged ozone concentration during the 12–14 July 1995 period. The distribution function of the 100 Monte Carlo predicted domain-wide maximum ozone concentrations is consistently close to log-normal with a 95% uncertainty range extending over plus and minus a factor of about 1.6 from the median. Uncertainties in ozone predictions are found to be most strongly correlated with uncertainties in the NO₂ photolysis rate. Also important are wind speed and direction, relative humidity, cloud cover, and biogenic VOC emissions. Differences in median predicted maximum ozone concentrations for three alternate emissions control assumptions were investigated, with the result that (1) the suggested year-2007 emissions changes would likely be effective in reducing concentrations from those for the year-1995 actual emissions, that (2) an additional 50% NO_x emissions reductions would likely be effective in further reducing concentrations, and that (3) an additional 50% VOC emission reductions may not be effective in further reducing concentrations.     

Impact of biogenic emission uncertainties on the simulated response of ozone and fine particulate matter to anthropogenic emission reductions

The role of emissions of volatile organic compounds and nitric oxide from biogenic sources is becoming increasingly important in regulatory air quality modeling as levels of anthropogenic emissions continue to decrease and stricter health-based air quality standards are being adopted. However, considerable uncertainties still exist in the current estimation methodologies for biogenic emissions. The impact of these uncertainties on ozone and fine particulate matter (PM2.5) levels for the eastern United States was studied, focusing on biogenic emissions estimates from two commonly used biogenic emission models, the Model of Emissions of Gases and Aerosols from Nature (MEGAN) and the Biogenic Emissions Inventory System (BEIS). Photochemical grid modeling simulations were performed for two scenarios: one reflecting present day conditions and the other reflecting a hypothetical future year with reductions in emissions of anthropogenic oxides of nitrogen (NOx). For ozone, the use of MEGAN emissions resulted in a higher ozone response to hypothetical anthropogenic NOx emission reductions compared with BEIS. Applying the current U.S. Environmental Protection Agency guidance on regulatory air quality modeling in conjunction with typical maximum ozone concentrations, the differences in estimated future year ozone design values (DVF) stemming from differences in biogenic emissions estimates were on the order of 4 parts per billion (ppb), corresponding to approximately 5% of the daily maximum 8-hr ozone National Ambient Air Quality Standard (NAAQS) of 75 ppb. For PM2.5, the differences were 0.1-0.25 microg/m3 in the summer total organic mass component of DVFs, corresponding to approximately 1-2% of the value of the annual PM2.5 NAAQS of 15 microg/m3. Spatial variations in the ozone and PM2.5 differences also reveal that the impacts of different biogenic emission estimates on ozone and PM2.5 levels are dependent on ambient levels of anthropogenic emissions.     

Application of OMI observations to a space-based indicator of NOx and VOC controls on surface ozone formation

We investigated variations in the relative sensitivity of surface ozone formation in summer to precursor species concentrations of volatile organic compounds (VOCs) and nitrogen oxides (NO_x) as inferred from the ratio of the tropospheric columns of formaldehyde to nitrogen dioxide (the “Ratio”) from the Aura Ozone Monitoring Instrument (OMI). Our modeling study suggests that ozone formation decreases with reductions in VOCs at Ratios <1 and NO_x at Ratios >2; both NO_x and VOC reductions may decrease ozone formation for Ratios between 1 and 2. Using this criteria, the OMI data indicate that ozone formation became: 1. more sensitive to NO_x over most of the United States from 2005 to 2007 because of the substantial decrease in NO_x emissions, primarily from stationary sources, and the concomitant decrease in the tropospheric column of NO₂, and 2. more sensitive to NO_x with increasing temperature, in part because emissions of highly reactive, biogenic isoprene increase with temperature, thus increasing the total VOC reactivity. In cities with relatively low isoprene emissions (e.g., Chicago), the data clearly indicate that ozone formation became more sensitive to NO_x from 2005 to 2007. In cities with relatively high isoprene emissions (e.g., Atlanta), we found that the increase in the Ratio due to decreasing NO_x emissions was not obvious as this signal was convolved with variations in the Ratio associated with the temperature dependence of isoprene emissions and, consequently, the formaldehyde concentration.     

Closing Remarks

Considerable attention has been paid in recent years to photochemical smog pollution close to the earth's surface and to stratospheric ozone depletion. There is reason to suspect that the next round of scientific concern will be devoted to the perturbations in the “free troposphere.” Tropospheric ozone has been building up in many regions of the northern hemisphere. Ozone changes in the upper troposphere will exert a considerable impact on global warming. This could affect moisture levels, cloud amount and distribution, precipitation, and atmospheric dynamics on different scales.

This paper analyzes: (1) the physical and chemical processes contributing to changes in tropospheric ozone concentration; (2) the observational evidence of previous ozone change; and (3) results drawn from computer modelling of past and future radiative forcing caused by rising ozone concentrations in the upper troposphere.

The solar and longwave radiative model developed by Wang et al. (1991) was used for calculating the change in radiative forcing to the troposphere-surface system that can be ascribed to changing concentrations in ozone and other greenhouse gases. Nitric oxide emission from aircraft are a prime suspect for the observed increases in upper tropospheric ozone. The inference can be drawn that a radiative forcing of 0.2 to 0.35 Wm^-2 will result from a doubling of aircraft emissions over the next two decades. This will amount to 10 to 25 percent of the radiative forcing attributable to CO₂ alone for the same period. The effect of doubling aircraft emissions will increase as stratospheric ozone concentrations recover from the recent buildup of harmful chlorofluorocarbons. A large fraction of the radiative forcing that occurred during the 1970 to 1990 period can be attributed to increases in tropospheric ozone as opposed to increases in other greenhouse gases.     

Understanding the contributions of anthropogenic and biogenic sources to CO enhancements and outflow observed over North America and the western Atlantic Ocean by TES and MOPITT

We investigate the effects of anthropogenic and biogenic sources on tropospheric CO enhancements and outflow over North America and the Atlantic during July–August 2006, the 3rd warmest summer on record. The analysis is performed using the 3D Regional chEmical trAnsport Model (REAM), satellite data from TES on the Aura satellite, MOPITT on the Terra satellite and surface monitor data from the SEARCH network. The satellite measurements of CO provide insight into the location of regional CO enhancements along with the ability to resolve vertical features. Satellite and surface monitor data are used to compare with REAM, illustrating model's ability to reproduce observed CO concentrations. The REAM model used in this study features CO emissions reduced by 50% from the 1999 EPA NEI and biogenic VOC emissions scaled by EPA-observed isoprene concentrations (20% reduction). The REAM simulations show large variations in surface CO, lower tropospheric CO and column CO, which are also observed by the surface observations and satellite data. Over the US, during July–August 2006, the model estimates monthly CO production from anthropogenic sources (5.3 and 5.1 Tg CO) is generally larger than biogenic sources (4.3 and 3.5 Tg CO). However, the model shows that for very warm days, biogenic sources produce as much CO as anthropogenic sources, a result of increased biogenic production due to warmer temperatures. The satellite data show CO outflow occurs along the East Coast of the US and Canada in July and is more broadly distributed over the Atlantic in August. REAM results show the longitudinally exported CO enhancements from anthropogenic sources (3.3 and 3.9 Tg CO) are larger than biogenic sources (2.8 and 2.7 Tg CO) along the eastern boundary of REAM for July–August 2006. We show that when compared with the impacts of both sources on increasing tropospheric CO exports, the relative impacts in August are greater than in July because of preferable outflow transport.     

Contribution of anthropogenic pollutants to the increase of tropospheric ozone levels in the Oporto Metropolitan Area, Portugal since the 19th century

The main purpose of this study was to evaluate the contribution of anthropogenic pollutants to the increase of tropospheric ozone levels in the Oporto Metropolitan Area (Portugal) since the 19th century. The study was based on pre-industrial and recent data series, the results being analyzed according to the atmospheric chemistry. The treatment of ozone and meteorological data was performed by classical statistics and by time-series analysis. It was concluded that in the 19th century the ozone present in the troposphere was not of photochemical origin, being possible to consider the respective concentrations as reference values. For recent data a cycle of 8h for ozone concentrations could be related to traffic. Compared to the 19th century, the current concentrations were 147% higher (252% higher in May) due to the increased photochemical production associated with the increased anthropogenic emissions.     

3D-air quality model evaluation using the Lidar technique

This paper reports on a model investigation of a particular episode of tropospheric ozone formation in the city of Lyon, France. A large-scale measurement campaign involving ground-based analyzers, sampling, Sodars and Lidars has been used to validate the model results. Based on validated meteorological data and primary pollutant concentrations, the numerical model has been run to obtain 3D ozone concentration profiles during the whole campaign (22–25 June 1999). The results are compared to the ozone Lidar vertical profiles. Good agreement between Lidar data and model predictions is first obtained on 22 June (but not on the following days). On 23 and 24 June, ozone concentrations are significantly underestimated by the model. The ozone Lidar measurements allowed identifying large import processes from high altitudes that explain the difference. In a second model simulation, these imports are taken into account as new boundary conditions. This yielded good agreement between the experimental data and the predicted ozone concentrations over the whole period. The evidence of high altitude ozone intrusion is confirmed by back-trajectories calculations.     

Meteorologically adjusted trends of daily maximum ozone concentrations in Taipei,Taiwan

The meteorological conditions exert large impacts on ozone concentrations, and may mask the long-term trends in ozone concentrations resulting from precursor emissions. Estimation of long-term trends of ozone concentrations due to the changes in precursor emissions is important for corresponding control strategy. Multiple linear regression (method I), multilayer perceptron (MLP) neural network (method II) and Komogorov-Zurbenko (KZ) filter method plus MLP methodology (method III), are used to estimate the meteorologically adjusted long-term trends of daily maximum ozone concentrations by removing the masking effects of meteorological conditions in this study. The daily maximum ozone concentrations and relative meteorological variables were extracted from six air-monitoring stations in Taipei area from 1994 to 2001. The data collected during 1994–2000 period were used as modeling set and utilized to estimate the meteorologically adjusted trends, and the data of 2001 were used as the validation data. The meteorologically adjusted trends of ozone for these three methods were calculated and compared. The results show that both MLP and KZ filter +MLP models are more suitable than multiple linear regression for estimating the long-term trends of ozone in Taipei, Taiwan. The long-term linear trends of meteorologically adjusted ozone concentrations due to the precursor emissions show an increase trend at all stations, and the percent changes per year range from 1.0% to 2.25% during the modeling period in Taipei area.     

Estimation of the Natural Background of Ozone Present at Surface Rural Locations

The natural background in the ozone concentration at rural locations in the United States and western Europe has been estimated by use of several approaches. The approaches utilized include the following: (1) historical trends in ozone concentration measurements, (2) recent ozone measurements at remote sites, (3) use of tracers of air originating in the stratosphere or upper troposphere and (4) results from applications of tropospheric photochemical models. While each of these approaches has its own limitations it appears that the natural background of ozone during the warmer months of the year is in the range of 10 to 20 ppb. Most of the ozone originating in the lower stratosphere or upper troposphere is lost by chemical or physical removal processes as well as undergoing dilution by air in the lower troposphere before reaching ground level rural locations. Lower tropospheric photochemical processes, those below 5 km, are likely to account for most of the ozone measured at rural locations during the warmer months of the year.

A key aspect to improved quantitation of the contributions from lower tropospheric photochemical processes to ozone concentrations continues to be more extensive atmospheric measurements of the distribution of reactive species of nitrogen. The emission densities of anthropogenic sources of NO_x are known to be highly variable over populated areas of continents as well as between continental areas and the oceans. The emission densities of biogenic sources of NO_x are small, likely to be highly variable, but poorly quantitated. These wide variations indicate the need for use of three dimensional tropospheric photochemical models over large continental regions.

Available results do indicate higher efficiencies for ozone formation at lower NO_x concentrations, especially below 1 ppb.     

MNEQA,an emissions model for photochemical simulations

This study focuses on a new emissions model, Numerical Emissions Model for Air Quality (MNEQA), to be used in photochemical simulations and emission control strategies relating to tropospheric ozone pollutants. MNEQA processes available local information from external files and is easily adaptable to any desired spatial resolution. Top-down and bottom-up methodologies are combined to calculate emissions at the required resolution for photochemical simulations. It was used in conjunction with the MM5-CMAQ air quality modelling system and was applied to an episode of high ozone levels in June 2003. Emission results are widely analysed showing a difference of ?8.8% with EMEP NOx emissions, and ?18.7% with EMEP VOC emissions. Related to ozone simulations, comparative results between measurements and simulations indicated good behaviour of the model in reproducing diurnal ozone concentrations, as statistical values fall within the EPA and EU regulatory frameworks.     

Comparison of regional and global land cover products and the implications for biogenic emission modeling

Accurate estimates of biogenic emissions are required for air quality models that support the development of air quality management plans and attainment demonstrations. Land cover characterization is an essential driving input for most biogenic emissions models. This work contrasted the global Moderate Resolution Imaging Spectroradiometer (MODIS) land cover product against a regional land cover product developed for the Texas Commissions on Environmental Quality (TCEQ) over four climate regions in eastern Texas, where biogenic emissions comprise a large fraction of the total inventory of volatile organic compounds (VOCs) and land cover is highly diverse. The Model of Emissions of Gases and Aerosols from Nature (MEGAN) was utilized to investigate the influences of land cover characterization on modeled isoprene and monoterpene emissions through changes in the standard emission potential and emission activity factor, both separately and simultaneously. In Central Texas, forest coverage was significantly lower in the MODIS land cover product relative to the TCEQ data, which resulted in substantially lower estimates of isoprene and monoterpene emissions by as much as 90%. Differences in predicted isoprene and monoterpene emissions associated with variability in land cover characterization were primarily caused by differences in the standard emission potential, which is dependent on plant functional type. Photochemical modeling was conducted to investigate the effects of differences in estimated biogenic emissions associated with land cover characterization on predicted ozone concentrations using the Comprehensive Air Quality Model with Extensions (CAMx). Mean differences in maximum daily average 8-hour (MDA8) ozone concentrations were 2 to 6 ppb with maximum differences exceeding 20 ppb. Continued focus should be on reducing uncertainties in the representation of land cover through field validation.

Implications: Uncertainties in the estimation of biogenic emissions associated with the characterization of land cover in global and regional data products were examined in eastern Texas. Misclassification between trees and low-growing vegetation in central Texas resulted in substantial differences in isoprene and monoterpene emission estimates and predicted ground-level ozone concentrations. Results from this study indicate the importance of land cover validation at regional scales.     

Artificial neural network-derived trends in daily maximum surface ozone concentrations

Interannual variability in meteorological conditions can confound attempts to identify changes in ozone concentrations driven by reduced precursor emissions. In this paper, a technique is described that attempts to maximize the removal of meteorological variability from a daily maximum ozone time series, thereby revealing longer term changes in ozone concentrations with increased confidence. The technique employs artificial neural network [multilayer perceptron (MLP)] models, and is shown to remove more of the meteorological variability from U.S. ozone data than does a Kolmogorov-Zurbenko (KZ) filter and conventional regression-based technique.