Meteorological Adjustment Research Articles

Quantitative impacts of dominant large-scale circulation systems on surface ozone pollution in China

Tropospheric ozone pollution has been worsened over most regions of China, adversely affecting human health and ecosystems. The long-term ozone concentration depends largely upon atmospheric circulations. Here, we conducted meteorological adjustment to quantitatively assess the influences of meteorological factors on the ozone evolution in China's seven city clusters during the warm season (April to October) from 2013 to 2020. Our analysis indicated that northern and eastern regions experienced ozone increases driven by emission changes. Southern regions, particularly the Pearl River Delta (PRD), exhibited ozone rise primarily due to meteorological conditions despite emission changes. In the Sichuan Basin (SCB) and Central Yangtze River Plain (CYP), where ozone levels decreased, meteorological conditions played a significant role in suppressing the ascent of ozone. Empirical orthogonal functions (EOF) analyses suggested that the spatiotemporal trend of meteorology-associated ozone was strongly correlated with the variation of East Asian Trough (EAT), South Asian High (SAH) and the western Pacific subtropical high (WPSH). The top three EOF patterns explained 33.4 %, 21.8 %, and 16.0 % of the total variance in meteorology-associated ozone. Absolute principal component scores-multiple linear regression (APCS-MLR) analyse quantitatively identified that enhanced EAT and SAH with a northward location of WPSH were favourable to surface ozone formation in central and eastern regions, but unfavourable to ozone formation in edge regions such as SCB.

Spatial-temporal Variation and Driving Factors of Ozone in China from 2019 to 2021 Based on EOF Technique and KZ Filter

Based on the hourly O3 concentration data of 337 prefectural-level divisions and simultaneous surface meteorological data in China, we applied empirical orthogonal function (EOF) analysis to analyze the main spatial patterns, variation trends, and main meteorological driving factors of O3 concentration in China from March to August in 2019-2021. In this study, a KZ (Kolmogorov-Zurbenko) filter was used to decompose the time series of O3 concentration and simultaneous meteorological factors into corresponding short-term, seasonal, and long-term components in 31 provincial capitals.Then, the stepwise regression was used to establish the relationship between O3 and meteorological factors. Ultimately, the long-term component of O3 concentration after "meteorological adjustment" was reconstructed. The results indicated that the first spatial patterns of O3 concentration showed a convergent change, that is, the volatility of O3 concentration was weakened in the high-value region of variability and enhanced in the low-value region.Before and after the meteorological adjustment, the variation trend of O3 concentration in different cities was different to some extent. The adjusted curve was "flatter" in most cities. Among them, Fuzhou, Haikou, Changsha, Taiyuan, Harbin, and Urumqi were greatly affected by emissions. Shijiazhuang, Jinan, and Guangzhou were greatly affected by meteorological conditions. Beijing, Tianjin, Changchun, and Kunming were greatly affected by emissions and meteorological conditions.

Episode based air quality assessment

Air pollution naturally comes in episodes due to the repetition of the meteorological processes that remove and accumulate the pollutants. We present an episodic air quality assessment approach that consists of two steps. The first step selects the pollution episodes via a data driven algorithm that controls the wind conditions after a thorough removal process. The second step analyzes the episodic average and total pollution loading with respect to the within episode and prior episode meteorological conditions via the linear and random forest regression. A meteorological adjustment is conducted to remove the yearly meteorological variation in the estimated episodic air quality measures. Empirical analyses using the episode based assessment on four site clusters in three North China cities revealed that it offered sharper analysis and different perspectives on the underlying air quality than those based on the conventional full sample method due to the proper control in the episode selection.

Analysis of the meteorological impact on PM2.5 pollution in Changchun based on KZ filter and WRF-CMAQ

During the “13th Five Year Plan” period, the nationwide mean concentration of PM2.5 in 2020 decreased by 28.8% compared to that in 2015. Exploring the relative impact of anthropogenic emission control and meteorological conditions to the reduction in PM2.5 concentration is a key step in further ensuring the accuracy of plans for the control of atmospheric environmental problems. In this study, the KZ filter and WRF-CMAQ model were used to quantitatively evaluate the relative impact of anthropogenic emission control and meteorological conditions to the decline in PM2.5 concentration. The KZ filter results show that the changes in PM2.5 concentration in Changchun were mainly caused by the short-term (45.95%–54.74%) and seasonal (31.62%–42.65%) fluctuations of pollution precursor emissions and meteorological conditions, and the average decline rate for the PM2.5 concentration after meteorological adjustment (3.36) is lower than that of the original data (3.74). Based on the KZ filter results, the relative impact proportions of meteorological conditions and anthropogenic emission control to the decline in PM2.5 concentration in Changchun are 11.36% and 88.64%, respectively, while the numerical simulation results of the WRF-CMAQ model show values of 14.79% and 85.21%, respectively. The results of both methods indicate that, although both meteorological conditions and anthropogenic emission control are conducive to the improvement of the atmospheric environment, anthropogenic emission control played a major role in the decline in PM2.5 in Changchun from 2015 to 2020, and the impact of meteorological conditions is relatively limited.

A revised dry deposition scheme for land–atmosphere exchange of trace gases in ECHAM/MESSy v2.54

Abstract. Dry deposition to vegetation is a major sink of ground-level ozone and is responsible for about 20 % of the total tropospheric ozone loss. Its parameterization in atmospheric chemistry models represents a significant source of uncertainty for the global tropospheric ozone budget and might account for the mismatch with observations. The model used in this study, the Modular Earth Submodel System version 2 (MESSy2) linked to the fifth-generation European Centre Hamburg general circulation model (ECHAM5) as an atmospheric circulation model (EMAC), is no exception. Like many global models, EMAC employs a “resistance in series” scheme with the major surface deposition via plant stomata which is hardly sensitive to meteorology, depending only on solar radiation. Unlike many global models, however, EMAC uses a simplified high resistance for non-stomatal deposition which makes this pathway negligible in the model. However, several studies have shown this process to be comparable in magnitude to the stomatal uptake, especially during the night over moist surfaces. Hence, we present here a revised dry deposition in EMAC including meteorological adjustment factors for stomatal closure and an explicit cuticular pathway. These modifications for the three stomatal stress functions have been included in the newly developed MESSy VERTEX submodel, i.e. a process model describing the vertical exchange in the atmospheric boundary layer, which will be evaluated for the first time here. The scheme is limited by a small number of different surface types and generalized parameters. The MESSy submodel describing the dry deposition of trace gases and aerosols (DDEP) has been revised accordingly. The comparison of the simulation results with measurement data at four sites shows that the new scheme enables a more realistic representation of dry deposition. However, the representation is strongly limited by the local meteorology. In total, the changes increase the dry deposition velocity of ozone up to a factor of 2 globally, whereby the highest impact arises from the inclusion of cuticular uptake, especially over moist surfaces. This corresponds to a 6 % increase of global annual dry deposition loss of ozone resulting globally in a slight decrease of ground-level ozone but a regional decrease of up to 25 %. The change of ozone dry deposition is also reasoned by the altered loss of ozone precursors. Thus, the revision of the process parameterization as documented here has, among others, the potential to significantly reduce the overestimation of tropospheric ozone in global models.

P6392Under the weather: acute myocardial infarction and subsequent case fatality with influenza burden - a nationwide observational study

Abstract Background Influenza may precipitate cardiovascular disease but influenza typically peaks in winter coinciding with other triggers of myocardial infarction (MI) such as low air temperature, high wind velocity, low air pressure and short sunshine duration. We aimed to study week-to-week variation in influenza cases and acute MI after meteorological confounder adjustment in a nationwide setting. Methods Weekly laboratory-confirmed influenza case reports were obtained from the Public Health Agency of Sweden from 2009 to 2016 and merged with the nationwide SWEDEHEART MI registry. Weekly counts of MI were studied with regard to influenza cases stratified into tertiles, 0–16, 17–164 and >164 influenza cases/week. Incidence rate ratios were calculated for each category and compared to a reference period of the year with no influenza. A negative binomial regression model was applied to adjust for weather parameters. Results A total of 133 562 MIs were reported to the registry during the study period of which 44 055 were ST-elevation MIs. Weeks with influenza cases were associated with higher risk of MI. For 0–16 influenza cases/week the unadjusted incidence rate ratio (IRR) for MI was 1.04 (95% confidence interval [CI] 1.01–1.07, p=0.007); for 17–163 cases/week the IRR=1.07 (95% CI 1.04–1.10, p≤0.001) and for ≥164 cases/week the IRR=1.08 (95% CI 1.05–1.11, p≤0.001). Results were consistent across a large range of subgroups and after adjusting for confounders. In addition, all-cause mortality was higher in weeks with highest reported rates of influenza cases. Conclusion In this nationwide observational study, we found an association between occurrence of MI and number of influenza cases beyond what could be explained by meteorological factors.

Trends of surface maximum ozone concentrations in Switzerland based on meteorological adjustment for the period 1990–2014

We investigate the temporal trends of peak ozone in Switzerland for the 1990–2014 time period. The meteorological conditions have a large influence on ozone formation and drive a large part of the variability in ozone observations. Therefore, the influence of meteorology on ozone was estimated using generalized additive models and removed from the ozone observations. A variable selection method was used for model building allowing the detection of the meteorological variables that have the largest effect on the variability of daily maximum ozone at each considered station. It was found that peak concentrations of ozone have been reducing in most of the stations, indicating a positive effect of implemented air pollution control measures on locally produced ozone. In the remote, high alpine site of Jungfraujoch a small upward trend of peak ozone was observed, most likely due to influence of hemispheric background ozone. In the most polluted traffic sites, peak ozone has for a different reason also been increasing until around 2003, when this trend started to level off. In traffic sites the increasing ozone concentrations due to reduced titration by nitrogen monoxide was the dominating process. One of the advantages of meteorological correction of ozone observations for trend estimation is that the uncertainty in the calculated trends is reduced. In addition, trend estimation based on meteorologically corrected ozone is less influenced by exceptional meteorological events during a specific time period, such as heat waves or by temporal changes in meteorological variables.

CMAQ-pollen 모델을 이용한 참나무 꽃가루 확산 고해상도 수치모의 및 검증

The aim of this study is to evaluate the accuracy and variability of the oak pollen concentrations over the Seoul metropolitan region (SMR) simulated by the Community Multiscale Air Quality (CMAQ)-based pollen dispersion model, which is the CMAQ-pollen model integrated with the improved oak pollen emission model (PEM-oak). The PEM-oak model developed is based on hourly emission flux parameterization that includes the effects of plantspecific release, meteorological adjustment, and diurnal variations of oak pollen concentrations. A 33 day-run for oak pollen simulation was conducted by the CMAQ-pollen model with a 3 ㎞ spatial resolution for the SMR during the 2014 spring pollen season. Modeled concentrations were evaluated against the hourly measurements at three Burkard sampling sites. Temporal variations of oak concentrations were largely well represented by the model, but the quantitative difference between simulations and measurements was found to be significant in some periods. The model results also showed that large variations in oak pollen concentrations existed in time and space and high concentrations in the SMR were closely associated with the regional transport under strong wind condition. This study showed the effective application of the CMAQ-pollen modeling system to simulate oak pollen concentration in the SMR. Our results could be helpful in providing information on allergenic pollen exposure. Further efforts are needed to further understand the oak pollen release characteristics such as interannual variation of the oak pollen productivity and its spatio-temporal flowering timing.

Analysis of observed surface ozone in the dry season over Eastern Thailand during 1997–2012

This study analyzed observed surface ozone (O3) in the dry season over a long-term period of 1997–2012 for the eastern region of Thailand and incorporated several technical tools or methods in investigating different aspects of O3. The focus was the urbanized and industrialized coastal areas recently recognized as most O3-polluted areas. It was found that O3 is intensified most in the dry-season months when meteorological conditions are favorable to O3 development. The diurnal variations of O3 and its precursors show the general patterns of urban background. From observational O3 isopleth diagrams and morning ratios of non-methane volatile organic compounds (NMVOC) and nitrogen oxides (NOx), the chemical regime of O3 formation was identified as VOC-sensitive, and the degree of VOC sensitivity tends to increase over the years, suggesting emission control on VOC to be suitable for O3 management. Both total oxidant analysis and back-trajectory modeling (together with K-means clustering) indicate the potential role of regional transport or influence in enhancing surface O3 level over the study areas. A meteorological adjustment with generalized linear modeling was performed to statistically exclude meteorological effects on the variability of O3. Local air-mass recirculation factor was included in the modeling to support the coastal application. The derived trends in O3 based on the meteorological adjustment were found to be significantly positive using a Mann–Kendall test with block bootstrapping.

Statistical evaluation of the impact of shale gas activities on ozone pollution in North Texas

Over the past decade, substantial growth in shale gas exploration and production across the US has changed the country's energy outlook. Beyond its economic benefits, the negative impacts of shale gas development on air and water are less well known. In this study the relationship between shale gas activities and ground-level ozone pollution was statistically evaluated. The Dallas–Fort Worth (DFW) area in north-central Texas was selected as the study region. The Barnett Shale, which is one the most productive and fastest growing shale gas fields in the US, is located in the western half of DFW. Hourly meteorological and ozone data were acquired for fourteen years from monitoring stations established and operated by the Texas Commission on Environmental Quality (TCEQ). The area was divided into two regions, the shale gas region (SGR) and the non-shale gas (NSGR) region, according to the number of gas wells in close proximity to each monitoring site. The study period was also divided into 2000–2006 and 2007–2013 because the western half of DFW has experienced significant growth in shale gas activities since 2007. An evaluation of the raw ozone data showed that, while the overall trend in the ozone concentration was down over the entire region, the monitoring sites in the NSGR showed an additional reduction of 4% in the annual number of ozone exceedance days than those in the SGR. Directional analysis of ozone showed that the winds blowing from areas with high shale gas activities contributed to higher ozone downwind. KZ-filtering method and linear regression techniques were used to remove the effects of meteorological variations on ozone and to construct long-term and short-term meteorologically adjusted (M.A.) ozone time series. The mean value of all M.A. ozone components was 8% higher in the sites located within the SGR than in the NSGR. These findings may be useful for understanding the overall impact of shale gas activities on the local and regional ozone pollution.

Analysis of long-term ozone trend over Delhi and its meteorological adjustment

Present study deals with the statistical analysis of long-term ground level ozone (O3) trend and the influence of meteorological variables on its variation over Delhi, India. Daily mean and maximum of O3 and meteorological data, obtained from India Meteorological Department, were arranged for the period of 9 years (1998–2006). Based on the preliminary correlation study of all the data with O3, six variables viz. daily maximum temperature, daily average relative humidity, dew point, wind speed, visibility, and total sunshine were selected. Classical additive time series decomposition technique was used to obtain seasonally adjusted long-term trend. To analyze the masking effect of meteorology, adjustment was made using Kolmogorov–Zurbenko filters followed by stepwise regression analysis to the smoothed series of O3 maximum and meteorological variables, which showed that long-term trend was independent of sunshine duration. Results indicate a significant increasing trend with annual increase of 1.13 % for O3 mean and 3 % for O3 maximum. Annual deseasonalized trend for seasonal cycle shows bimodal oscillations. About 43 % of O3 variation was explained by the selected meteorological factors and rest of variation attributed to factors like emission of precursor gases, pollutant transport, policy changes, etc. Among the three tested regression models, performance of Model 2 with variable temperature, wind speed, and visibility was found to be best that resulted in lowering of O3 trend. Large variability (23 %) was explained by the variable visibility depicted that the emission of primary pollutants not only provides the precursor gases but also control the local photochemical reactions.

Estimation of Ozone Trend in Central Greece, Based on Meteorologically Adjusted Time Series

Data referring to an approximately 8-year period (1999–2007) are analyzed in order to estimate the trend of the daily maximum hourly value of ozone concentration at the east coast of central Greece, where the summer background ozone concentration is high. A Kolmogorov–Zurbenko filter is applied to remove the short-term component from the raw time series of ozone and meteorological variables. Regression models are developed in order to produce meteorologically adjusted ozone time series, involving the noise-free temperature, relative humidity, and wind speed as independent variables. The analysis verifies that the meteorological adjustment provides better results on estimating ozone’s trend, which is found to be increasing (α = 0.001) with an annual rate of 1.34 ± 0.07 μg/m3. This trend could mainly be attributed to policy and changes in the emissions of ozone’s precursors. Additionally, the short-term component of ozone concentration is also meteorologically adjusted and its impact on the trend is examined. The analysis shows that its contribution is of minor importance when the ozone trend is adjusted by temperature, relative humidity, and wind speed. Moreover, the sea breeze circulation system that is frequently developed in the area influences the short-term and seasonal ozone variation, and therefore, it should be taken into account when producing meteorologically adjusted time series. The study’s conclusions could be exploited by environmental and agricultural authorities in order to develop their long-term strategies towards the air quality management.

Influence of meteorology on PM<sub>10</sub> trends and variability in Switzerland from 1991 to 2008

Abstract. Measurements of airborne particles with aerodynamic diameter of 10 μm or less (PM10) and meteorological observations are available from 13 stations distributed throughout Switzerland and representing different site types. The effect of all available meteorological variables on PM10 concentrations was estimated using Generalized Additive Models. Data from each season were treated separately. The most important variables affecting PM10 concentrations in winter, autumn and spring were wind gust, the precipitation rate of the previous day, the precipitation rate of the current day and the boundary layer depth. In summer, the most important variables were wind gust, Julian day and afternoon temperature. In addition, temperature was important in winter. A "weekend effect" was identified due to the selection of variable "day of the week" for some stations. Thursday contributes to an increase of 13% whereas Sunday contributes to a reduction of 12% of PM10 concentrations compared to Monday on average over 9 stations for the yearly data. The estimated effects of meteorological variables were removed from the measured PM10 values to obtain the PM10 variability and trends due to other factors and processes, mainly PM10 emissions and formation of secondary PM10 due to trace gas emissions. After applying this process, the PM10 variability was much lower, especially in winter where the ratio of adjusted over measured mean squared error was 0.27 on average over all considered sites. Moreover, PM10 trends in winter were more negative after the adjustment for meteorology and they ranged between −1.25 μg m−3 yr−1 and 0.07 μg m−3 yr−1. The adjusted trends for the other seasons ranged between −1.34 μg m−3 yr−1 and −0.26 μg m−3 yr−1 in spring, −1.40 μg m−3 yr−1 and −0.28 μg m−3 yr−1 in summer and −1.28 μg m−3 yr−1 and −0.11 μg m−3 yr−1 in autumn. The estimated trends of meteorologically adjusted PM10 were in general non-linear. The two urban street sites considered in the study, Bern and Lausanne, experienced the largest reduction in measured and adjusted PM10 concentrations. This indicates a verifiable effect of traffic emission reduction strategies implemented during the past two decades. The average adjusted yearly trends for rural, urban background and urban street stations were −0.37, −0.53 and −1.2 μg m−3 yr−1 respectively. The adjusted yearly trends for all stations range from −0.15 μg m−3 yr−1 to −1.2 μg m−3 yr−1 or −1.2% yr−1 to −3.3% yr−1.

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

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

Temporal trends and weekend–weekday differences for benzene and 1,3-butadiene in Houston, Texas

Temporal trends and weekend–weekday differences in benzene and 1,3-butadiene concentrations were investigated at a number of sites in the Houston, Texas area using monitoring data collected by the Texas Commission on Environmental Quality (TCEQ). The dataset included two networks, the Community Air Toxics Monitoring Network (CATMN), which has 24-h measurements every six days, and the Photochemical Assessment Monitoring System (PAMS), which includes hourly measurements. The period for data analysis was 1997–2004. The CATMN network had the larger number of stations. Over this time period, the network average benzene concentration at the CATMN stations was 0.93 ppb with individual stations ranging within a factor of about two of this network average. The network average 1,3-butadiene concentration was 0.57 ppb with most individual stations ranging within a factor of about six of this network average. These ranges suggest more spatial variability for 1,3-butadiene concentrations compared to benzene concentrations. Variations in meteorology can influence benzene and 1,3-butadiene concentrations making it difficult to examine the true concentration trends. Therefore, a generalized additive model (GAM) was used in a time-series analysis to adjust the benzene and 1,3-butadiene concentrations for variations caused by daily differences in meteorology. The analysis revealed very little difference in the weekend–weekday concentrations, except for a block of time during the morning rush hour where weekday concentrations were slightly higher. The GAM analysis showed that there was a significant decrease in the benzene and 1,3-butadiene concentrations throughout the trend period of 1997–2004. The average annual percent decrease across the sites was 1.7% for benzene for a meteorologically adjusted model (MA model) and 3.2% for a model without meteorological adjustment (raw trend or RT model). For 1,3-butadiene, there was a 3.7% annual decrease for MA model and 5.1% annual decrease for the RT model. For the five stations with data for each of the 8-year period, the mean overall benzene reduction over the 8-year trend period was 20% for the MA models and 29% for the RT models. For 1,3-butadiene, the reduction was 30% for the MA models and 35% for the RT models.

Changes of daily surface ozone maxima in Switzerland in all seasons from 1992 to 2002 and discussion of summer 2003

Abstract. An Analysis of Covariance (ANCOVA) was used to derive the influence of the meteorological variability on the daily maximum ozone concentrations at 12 low-elevation sites north of the Alps in Switzerland during the four seasons in the 1992–2002 period. The afternoon temperature and the morning global radiation were the variables that accounted for most of the meteorological variability in summer and spring, while other variables that can be related to vertical mixing and dilution of primary pollutants (afternoon global radiation, wind speed, stability or day of the week) were more significant in winter. In addition, the number of days after a frontal passage was important to account for ozone build-up in summer and ozone destruction in winter. The statistical model proved to be a robust tool for reducing the impact of the meteorological variability on the ozone concentrations. The explained variance of the model, averaged over all stations, ranged from 60.2% in winter to 71.9% in autumn. The year-to-year variability of the seasonal medians of daily ozone maxima was reduced by 85% in winter, 60% in summer, and 50% in autumn and spring after the meteorological adjustment. For most stations, no significantly negative trends (at the 95% confidence level) of the summer medians of daily O3 or Ox (O3+NO2) maxima were found despite the significant reduction in the precursor emissions in Central Europe. However, significant downward trends in the summer 90th percentiles of daily Ox maxima were observed at 6 sites in the region around Zürich (on average −0.73 ppb yr-1 for those sites). The lower effect of the titration by NO as a consequence of the reduced emissions could partially explain the significantly positive O3 trends in the cold seasons (on average 0.69 ppb yr-1 in winter and 0.58 ppb yr-1 in autumn). The increase of Ox found for most stations in autumn (on average 0.23 ppb yr-1) and winter (on average 0.39 ppb yr-1) could be due to increasing European background ozone levels, in agreement with other studies. The statistical model was also able to explain the very high ozone concentrations in summer 2003, the warmest summer in Switzerland for at least ~150 years. On average, the measured daily ozone maximum was 15 ppb (nearly 29%) higher than in the reference period summer 1992–2002, corresponding to an excess of 5 standard deviations of the summer means of daily ozone maxima in that period.

Trends in Meteorologically Adjusted Ozone Concentrations in Six Kentucky Metro Areas, 1998–2002

Meteorologically adjusted ozone (O3) concentrations during five recent O3 seasons (1998-2002) were computed for six Kentucky metro areas using a nonlinear regression model originally developed for forecasting ground-level O3 concentrations. The meteorological adjustment procedure was based on modifying actual measured O3 concentrations according to model-predicted responses to climate departures with respect to a reference year. For all six Kentucky metro areas, meteorologically adjusted O3 concentrations declined over the five-year period. The linear best-fit rate of decline in mean adjusted O3 concentrations ranged from 0.9 to 2.6 ppb/yr for these metro areas; the average rate of decline was 1.6 ppb/yr. The rates of decline in meteorologically adjusted extreme value (e.g., 95th percentile) concentrations were approximately the same, but there is greater statistical uncertainty concerning the extreme value trends.

A review of statistical methods for the meteorological adjustment of tropospheric ozone

A variety of statistical methods for meteorological adjustment of ozone have been proposed in the literature over the last decade for purposes of forecasting, estimating ozone time trends, or investigating underlying mechanisms from an empirical perspective. The methods can be broadly classified into regression, extreme value, and space–time methods. We present a critical review of these methods, beginning with a summary of what meteorological and ozone monitoring data have been considered and how they have been used for statistical analysis. We give particular attention to the question of trend estimation, and compare selected methods in an application to ozone time series from the Chicago area. We conclude that a number of approaches make useful contributions to the field, but that no one method is most appropriate for all purposes and all meteorological scenarios. Methodological issues such as the need for regional-scale analysis, the nonlinear dependence of ozone on meteorology, and extreme value analysis for trends are addressed. A comprehensive and reliable methodology for space–time extreme value analysis is attractive but lacking.

Associations between ambient ozone, hydrocarbons, and childhood wheezy episodes: a prospective observational study in south east London

OBJECTIVESTo explore the hypothesis that hydrocarbon species and other air pollutants which accumulate at low and high concentrations of ozone are more directly associated with childhood wheezy episodes than ozone.METHODSProspective...

An analysis of trends in oxidant air quality in the south coast air basin of California

Previous approaches for meteorological adjustment of oxidant trends were based on establishing a statistical or deterministic model between oxidant concentrations and meteorological parameters. This model was then used to remove the influence of meteorology. However, because of the simplistic forms of the models, they are not capable of removing meteorological effects for all years. To circumvent this problem, the daily peak oxidant trends have been determined based on fixed ranges of meteorological parameters, as well as on fixed parameter values using year-specific statistical models. Trends were determined for regional maxima, and at two specific sites Azusa and San Bernardino, over the high oxidant season from 1971 to 1979. The parameters selected to characterize the oxidant concentrations are the daily values of El Monte upperlevel temperature, maximum Ontario surface temperature, relative humidity, mixing height and wind speed. Fixed ranges or values of these parameters were further classified according to their high, moderate and low oxidant formation potential. Oxidant trends were determined for each classification. Between 1971 and 1979, for days with high oxidant formation potential, the oxidant trends are flat for Azusa, for San Bernardino and basinwide. For days with moderate and low oxidant formation potential, the trends are essentially flat, with minor variations depending on which approach is used to determine the trend.