Carbonyl sulphide in and over seawater: summer data from the northeast Atlantic Ocean

Carbonyl sulphide (COS) concentrations in air and dissolved in seawater were determined during a cruise in summer 1997 in the northeast Atlantic Ocean. Seawater characteristics and meteorological parameters were monitored. Dissolved COS concentrations throughout the entire cruise exhibited a strong diel cycle with maximum concentrations in late afternoon and minimum concentrations at sunrise. This is in good agreement with the theory that COS is photochemically produced from dissolved organic matter during the day and removed by hydrolysis. The overall mean concentration of dissolved COS was 23.6 pmol dm^-3; the daily mean varied according to water mass characteristics and was highest in upwelling areas owing to increased dissolved organic matter. Atmospheric COS concentrations, varying from about 450 to 800 pptv with an average value of 657 pptv, showed some dependency on air mass history and local COS flux from the sea surface. The exchange of COS between the ocean and the atmosphere depended on dissolved COS concentrations and wind speed. The daily integrated flux was always from the sea into the air, and the average was 1.3±0.8 g COS km^-2 d^-2. The collected data were used to test a mixed layer box model and a one-dimensional model, both describing the behaviour of COS in seawater. We found that the one-dimensional model simulates the data more closely, especially during the night.     

Impact of downward-mixing ozone on surface ozone accumulation in southern Taiwan

The ozone that initially presents in the previous day's afternoon mixing layer can remain in the nighttime atmosphere and then be carried over to the next morning. Finally, this ozone can be brought to the ground by downward mixing as mixing depth increases during the daytime, thereby increasing surface ozone concentrations. Variation of ozone concentration during each of these periods is investigated in this work. First, ozone concentrations existing in the daily early morning atmosphere at the altitude range of the daily maximum mixing depth (residual ozone concentrations) were measured using tethered ozonesondes on 52 experimental days during 2004-2005 in southern Taiwan. Daily downward-mixing ozone concentrations were calculated by a box model coupling the measured daily residual ozone concentrations and daily mixing depth variations. The ozone concentrations upwind in the previous day's afternoon mixing layer were estimated by the combination of back air trajectory analysis and known previous day's surface ozone distributions. Additionally, the relationship between daily downward-mixing ozone concentration and daily photochemically produced ozone concentration was examined. The latter was calculated by removing the former from daily surface maximum ozone concentration. The measured daily residual ozone concentrations distributed at 12-74 parts per billion (ppb) with an average of 42 +/- 17 ppb are well correlated with the previous upwind ozone concentration (R2 = 0.54-0.65). Approximately 60% of the previous upwind ozone was estimated to be carried over to the next morning and became the observed residual ozone. The daily downward-mixing ozone contributes 48 +/- 18% of the daily surface maximum ozone concentration, indicating that the downward-mixing ozone is as important as daily photochemically produced ozone to daily surface maximum ozone accumulation. The daily downward-mixing ozone is poorly correlated with the daily photochemically produced ozone and contributes significantly to the daily variation of surface maximum ozone concentrations (R2 = 0.19). However, the contribution of downward-mixing ozone to daily ozone variation is not included in most existing statistical models developed for predicting daily ozone variation. Finally, daily surface maximum ozone concentration is positively correlated with daily afternoon mixing depth, attributable to the downward-mixing ozone.     

Impacts of some meteorological parameters on SO2 and TSP concentrations in Erzurum, Turkey

The air pollution is the one of the most important environmental problems in Erzurum, situated in the eastern of Turkey, during winter periods. The unfavorable climate as well as the city’s topography, and inappropriate urbanization cause serious air pollution problems. The air pollutant concentrations in a city have a close relationship with its meteorological parameters. In the present study, the relationship between daily average total suspended particulate (TSP) and sulphur dioxide (SO₂) concentrations with meteorological factors, such as wind speed, temperature, relative humidity, pressure and precipitation, in 1995–2002 winter seasons was statistically analyzed using the stepwise multiple linear regression analysis. According to the results obtained through analysis, higher TSP and SO₂ concentrations are strongly related to colder temperatures, lower wind speed, higher pressure system and weakly lower precipitation and higher relative humidity. The statistical models of SO₂ and TSP including meteorological parameters gave R² of 0.74 and 0.88, respectively. Furthermore, the correlation between the previous day’s SO₂, TSP concentrations and actual concentrations of these pollutants on that day was investigated and found as 0.84 and 0.53, respectively. In order to develop this model, previous day’s SO₂ and TSP concentrations were added to the equations. The new model for SO₂ enhanced considerably (R² = 0.92), but for TSP new model was not enhanced (R² = 0.89).     

A neural network-based approach for the prediction of urban SO2 concentrations in the Istanbul metropolitan area

A three-layer Artificial Neural Network (ANN) model was developed to forecast air pollution levels. The subsequent SO₂ concentration (24-hour averaged) being the output parameter of this study was estimated by seven input parameters such as preceding SO₂ concentrations (24-hour averaged), average daily temperature, sea-level pressure, relative humidity, cloudiness, average daily wind speed and daily dominant wind direction. After Backpropagation training combined with Principal Component Analysis (PCA), the proposed model predicted subsequent SO₂ values based on measured data. ANN testing outputs were proven to be satisfactory with correlation coefficients of about 0.770, 0.744 and 0.751 for the winter, summer and overall data, respectively.     

Defining the photochemical contribution to particulate matter in urban areas using time-series analysis

The objective of this project is to demonstrate how the ambient air measurement record can be used to define the relationship between O3 (as a surrogate for photochemistry) and secondary particulate matter (PM) in urban air. The approach used is to develop a time-series transfer-function model describing the daily PM10 (PM with less than 10 microm aerodynamic diameter) concentration as a function of lagged PM and current and lagged O3, NO or NO2, CO, and SO2. Approximately 3 years of daily average PM10, daily maximum 8-hr average O3 and CO, daily 24-hr average SO2 and NO2, and daily 6:00 a.m.-9:00 a.m. average NO from the Aerometric Information Retrieval System (AIRS) air quality subsystem are used for this analysis. Urban areas modeled are Chicago, IL; Los Angeles, CA; Phoenix, AZ; Philadelphia, PA; Sacramento, CA; and Detroit, MI. Time-series analysis identified significant autocorrelation in the O3, PM10, NO, NO2, CO, and SO2 series. Cross correlations between PM10 (dependent variable) and gaseous pollutants (independent variables) show that all of the gases are significantly correlated with PM10 and that O3 is also significantly correlated lagged up to two previous days. Once a transfer-function model of current PM10 is defined for an urban location, the effect of an O3-control strategy on PM concentrations is estimated by calculating daily PM10 concentrations with reduced O3 concentrations. Forecasted summertime PM10 reductions resulting from a 5 percent decrease in ambient O3 range from 1.2 microg/m3 (3.03%) in Chicago to 3.9 microg/m3 (7.65%) in Phoenix.     

Amelioration of Indian urban air pollution phytotoxicity in Beta vulgaris L. by modifying NPK nutrients

Air pollution levels are increasing at an alarming rate in many developing countries, including India and causing a potential threat to crop production. Field experiments were conducted to examine the impact of urban air pollutants on biomass (yield) and some physiological and biochemical parameters of palak (Beta vulgaris L. var. All Green) that grew from germination to maturity at seven periurban sites of Allahabad city having different concentrations of air pollutants under different levels of nutrients. The 6h daily mean NO2, SO2 and O3 concentrations varied from 2.5 to 42.5, 10.6 to 65 and 3.5 to 30.8 microg m(-3), respectively at different locations. Levels of air pollution showed significant negative correlations with photosynthetic pigments, protein, ascorbic acid and starch contents and catalase activity of palak leaves. A significant negative correlation was found for total biomass with SO2 (r=-0.92), NO2 (r=-0.85) and O3 (r=-0.91) concentrations. The increased fertilizer application (N, P and K) over the recommended dose resulted in a positive response by reducing losses in photosynthetic pigments and total biomass. This study proved that ambient air pollution of Allahabad city is influencing negatively to the growth and yield of palak plants.     

Prediction of carbon monoxide acute air pollution episodes. Model formulation and first application in Lombardy

This paper describes a method to forecast the exceedance probability of a fixed threshold for a certain air pollutant concentration. This general approach has been applied in the case of carbon monoxide on 35 traffic monitoring stations in the Lombardy Region. The implemented model has been called FOREPOLL (Forecast Pollution).The model structure, consisting in three basic modules (the deterministic, the stochastic and the Bayesian one), has been thought to be adjustable to different stations of an air quality network and to various pollutants. Forepoll uses the last biennium data set of the station in exam (pollutants and micrometeorological parameters) as a moving learning time and also needs the forecasted synoptic weather type. In the first module the daily maxima of the hourly measured pollutant concentrations are checked in order to eliminate some known physical dependencies, such as the temperature dependence of the emissions. Then the data are divided into subgroups depending on the weather type and in each group fitted by a different Weibull distribution. To provide a first a priori exceedance probability, this distribution is daily rebuilt by taking into account the forecasted parameters. In the last module this probability is enhanced or reduced using simple, experience based, bayesian rules providing the a posteriori exceedance probability.Model validation trials have been carried out on a year of CO forecasted concentrations in different air quality stations; the first results are quite good particularly for the metropolitan areas, because the model seems to work better in case of stronger and more diffuse pollution.     

Pollution Control by Locational Change and Technological Abatement

In recent years, there has been a downward trend in sulfur dioxide concentrations in downtown St. Louis. This paper examines the contribution to this trend from locational changes of polluting sources and from technological abatement. A simple diffusion model is used to relate annual average concentrations to annual emission data. The results suggest that, had there been no abatement activity, the changes in location of sources that occurred between 1963 and 1970 have more or less offset a 40% increase in annual emissions over that period. However, the abatement activity, essentially the consequence of air pollution regulations, may possibly be credited with a decline of 35% in the annual average concentration.     

Climate change impacts on the leaching of a heavy metal contamination in a small lowland catchment

The Keersop catchment (43km(2)) in the south of The Netherlands has been contaminated by the emissions of four zinc ore smelters. The objective of this study was to assess the effects of future projected climate change on the hydrology and the leaching of heavy metals (i.e. Cd and Zn) in the catchment. The numerical, quasi-2D, unsaturated zone Soil Water Atmosphere Plant model was used with 100-year simulated daily time series of precipitation and potential evapotranspiration. The time series are representative of stationary climates for the periods 1961-1990 ("baseline") and 2071-2100 ("future"). The time series of future climate were obtained by downscaling the results of eight regional climate model (RCM) experiments, driven by the SRES A2 emissions scenario, using change factors for a series of climate statistics and applying them to stochastic weather generator models. The time series are characterized by increased precipitation in winter, less precipitation in summer, and higher air temperatures (between 2°C and 5°C) throughout the year. Future climate scenarios project higher evapotranspiration rates, more irrigation, less drainage, lower discharge rates and lower groundwater levels, due to increased evapotranspiration and a slowing down of the groundwater system. As a result, lower concentrations of Cd and Zn in surface water are projected. The reduced leaching of heavy metals, due to drying of the catchment, showed a positive impact on a limited aspect of surface water quality.     

Ozone predictions in Atlanta, Georgia: analysis of the 1999 ozone season

Ozone prediction has become an important activity in many U.S. ozone nonattainment areas. In this study, we describe the ozone prediction program in the Atlanta metropolitan area and analyze the performance of this program during the 1999 ozone-forecasting season. From May to September, a team of 10 air quality regulators, meteorologists, and atmospheric scientists made a daily prediction of the next-day maximum 8-hr average ozone concentration. The daily forecast was made aided by two linear regression models, a 3-dimensional air quality model, and the no-skill ozone persistence model. The team's performance is compared with the numerical models using several numerical indicators. Our analysis indicated that (1) the team correctly predicted next-day peak ozone concentrations 84% of the time, (2) the two linear regression models had a better performance than a 3-dimensional air quality model, (3) persistence was a strong predictor of ozone concentrations with a performance of 78%, and (4) about half of the team's wrong predictions could be prevented with improved meteorological predictions.     

An assessment of the impact of California's Phase 2 Reformulated Gasoline on ozone air quality

California's Phase 2 Reformulated Gasoline (CaRFG), introduced early in 1996, represents an important step toward attainment of ozone standards. Studies of vehicle emissions and ambient air quality data have reported substantial reductions of ozone precursors due to CaRFG. This study uses daily measurements of regional ozone and meteorology to estimate the effect of CaRFG on ozone concentrations in three areas of California. In each area, a regression model was used to partially account for the daily effects of meteorology on area-wide ozone maxima for May-October. The statistical models are based on combinations of air temperature aloft (approximately 5000 ft), surface air temperatures, and surface wind speeds. Estimated ozone benefits were attributed to CaRFG after accounting for meteorology, which improved the precision of the estimates by approximately 37-57% based on a resampling analysis. The ozone benefits were calculated as the difference in ozone times the proportion of the reductions of hydrocarbons and nitrogen oxides attributed to CaRFG by the best available emission inventories. Ozone benefits attributed to CaRFG (with approximately 90% confidence) are 8-13% in the Los Angeles area, -2-6% in the San Francisco Bay area overall with greater benefits in two major subregions, and 3-15% in the Sacramento area.     

Statistical Modelling of CO and NO2 Concentrations in the Athens Area - Evaluation of Emission Abatement Policies (7 pp)

- DOI: http://dx.doi.org/10.1065/espr2006.04.299 Goal, Scope and Background This paper describes a statistical modelling approach, suggested as a policy tool in the Athens area for the assessment of the emissions reduction level required to meet the air quality standards for two criteria air pollutants, namely CO and NO2. Methods. More than ten years of hourly CO and NOx-NO2 concentration data measured by the monitoring network of the Hellenic Ministry for the Environment, Physical Planning and Public Works were analyzed and the original dataset has been reduced using a data evaluation procedure. Results and Discussion Seasonal pollutant concentration trends suggested that the reduction of CO and NOx concentrations observed in the beginning of the '90s is almost entirely attributed to the increase of the catalyst-equipped cars during this period. The numerical parameters of an empirical model relating EU standard exceedances with mean annual concentrations were defined and the model was validated using datasets from years that were not used for the estimation of these parameters. This model was used in conjunction with a roll-back equation as a policy tool for the assessment of the effect of different CO and NOx emissions reduction scenarios on air quality standard compliance for CO and NO2. Results predicted with this empirical modelling approach were assessed with monitored data averaged over a 3-year period, giving satisfactory results. Conclusion A methodology suggested for assessing the effects of different emissions reduction scenarios on air quality standard attainment was successfully applied for CO and NO2 in the Athens area. Recommendation and Perspective The proposed methodology can provide a useful tool for the evaluation of policies already in progress as well as the development of future policies for emissions reduction in urban areas with similar characteristics, aiming at air quality standard compliance on a timely manner. Such a methodology could be applied in other urban areas of Greece characterized by dense traffic, therefore assisting the development of national policies in relation to air pollutants for which standard exceedances occur.     

Analysis and prediction of global climate temperature change based on multiforced observational statistics

The response of the climate system to increasing greenhouse gases was simulated by a number of climate model projections. There is an urgent need to verify or falsify these projections against observational climate data. Therefore, in this contribution, surface air temperature data are considered covering on a global average the period 1861-1990 and on a northern hemisphere average 1670-1990 (including proxy data). Based on a multiple correlation and coherence analysis a regression model is evaluated which is simultaneously forced by the observed or reconstructed atmospheric CO(2) or equivalent CO(2) concentration increase, volcanic activity, solar variations, and the ENSO (El Ni?o/southern oscillation) mechanism including phase shifts between cause and effect. This model reveals a greenhouse-gas-induced mean global temperature rise of 0.6-0.8 K since preindustrial time (c. 1800-1990). Following the IPCC business-as-usual scenario (trend extrapolation) this would lead to a hypothetical 3.8 K temperature rise in 2100 (best estimate, uncertainty + 0.7/-0.4 K compared to the 1985 value.     

Increasing risk for negative ozone impacts on vegetation in northern Sweden

Trends were found for increasing surface ozone concentrations during April-September in northern Sweden over the period 1990-2006 as well as for an earlier onset of vegetation growing season. The highest ozone concentrations in northern Sweden occurred in April and the ozone concentrations in April showed a strong increasing trend. A model simulation of ozone flux for Norway spruce indicated that the provisional ozone flux based critical level for forests in Europe is exceeded in northern Sweden. Future climate change would have counteracting effects on the stomatal conductance and needle ozone uptake, mediated on the one hand by direct effect of increasing air temperatures and on the other through increasing water vapour pressure difference between the needles and air. Thus, there is a substantial and increasing risk for negative impacts of ozone on vegetation in northern Sweden, related mainly to increasing ozone concentrations and an earlier onset of the growing season.     

Ozone Predictions in Atlanta,Georgia: Analysis of the 1999 Ozone Season

ABSTRACT

Ozone prediction has become an important activity in many U.S. ozone nonattainment areas. In this study, we describe the ozone prediction program in the Atlanta metropolitan area and analyze the performance of this program during the 1999 ozone-forecasting season. From May to September, a team of 10 air quality regulators, meteorologists, and atmospheric scientists made a daily prediction of the next-day maximum 8-hr average ozone concentration. The daily forecast was made aided by two linear regression models, a 3-dimensional air quality model, and the no-skill ozone persistence model. The team's performance is compared with the numerical models using several numerical indicators. Our analysis indicated that (1) the team correctly predicted next-day peak ozone concentrations 84% of the time, (2) the two linear regression models had a better performance than a 3-dimensional air quality model, (3) persistence was a strong predictor of ozone concentrations with a performance of 78%, and (4) about half of the team's wrong predictions could be prevented with improved meteorological predictions.     

Spatiotemporal Features of Severe Air Pollution in Northern Taiwan (8 pp)

Background, Aims and Scope This research attempted to identify the dominant factors simultaneously affecting the airborne concentrations of five air pollutants with principal component analysis and to determine the meteorologically related parameters that cause severe air-pollution events. According to the definition of subPSI and PSI values through the U.S. EPA, the historical raw data of five criteria air pollutants, SO2, CO, O3, PM10 and NO2, were calculated as daily subPSI values. In addition to the airborne concentrations, this study simultaneous collected the surface meteorological parameters of the Taipei meteorological station, established by the Central Weather Bureau. Methods Principal component analysis was conducted to screen severe air pollution scenarios for five air pollutants: SO2, CO, O3, PM10 and NO2. The concentrations of various air pollutants measured at 17 air-quality stations in northern Taiwan from 1995 to 2001 were transformed into daily subPSI values. The correlation analysis of the five air pollutants and four meteorological parameters (wind speed, temperature, mixing height and ventilation rate) were included in this research. After screening severe air pollution scenarios, this study recognized the synoptic patterns easily causing the severe air-pollution events. Results and Discussion Analytical results showed that the eigenvalues of the first two principal components for SO2, CO, O3, PM10 and NO2 were greater than 1. The first component of five air pollutants explained 64, 64, 67, 76 and 63% of subPSI variance for SO2, CO, O3, PM10 and NO2, respectively. Only the correlation coefficient of NO2 and CO had statistically significant positive values (0.82); other pollutant pairs presented medium (0.4 to 0.7) or low (0 to 0.4) positive values. The correlation coefficients for air pollutants and three meteorological parameters (wind speed, mixing height and ventilation index) were medium or low negative values. In northern Taiwan, spring was most likely induced high concentrations and the component scores of the first component for SO2, CO, PM10 and NO2; summer was the worst season that caused high O3 episodes. Consequently, the analytical results of factor loadings for the first principal component and emission inventory of various sources revealed that mobile sources were dominant factors affecting ambient air quality in northern Taiwan. Conclusion According to the results of principal component analysis for the five air pollutants, the first two of 17 components were cited as major factors and explained 71% of subPSI variance. Based on the inventory of NOx emissions and the isopleth diagram of factor loading for the first component, mobile sources in the southwest Taipei City accounted for the highest factor loading values and emission inventory values. Synoptic analysis and principal component analysis demonstrated that three types of weather patterns (high-pressure recirculation, prefrontal warm sector and the southwesterly wind system) easily caused the severe air-pollution scenarios. In summary, if severe air-pollution days occurred, the average meteorological parameters experienced adverse conditions for diffusing air pollutants; that is, the average values of wind speed, mixing height and ventilation index were lower than 2.1 ms-1, 360 m and 800 m2s-1, respectively. If one of the three synoptic patterns were to occur in combination with adverse meteorological conditions, severe air-pollution events would be developed. Recommendation and Outlook By utilizing synoptic patterns, this work found three weather systems easily caused severe air-pollution events over northern Taiwan. Analytical results showed, respectively, the wind speed and mixing height were less than 2.1 m/s and 360 m during severe air-pollution events.     

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.     

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

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

Single and interactive effects of low levels of O3, SO2 and NO2 on the growth and yield of spring rape

During three consecutive seasons (1987-1989), the effects of low-levels of O3, SO2 and NO2 singly and in all possible combinations (NO2 in 1988 and 1989 only) on growth and yield of potted plants of spring rape (Brassica napus L. var. napus, 'callypso') were investigated by means of factorial fumigation experiments in open-top chambers. Plants were exposed from the early vegetative stage of development until seed harvest, to charcoal-filtered air (CF; control) and CF which was supplemented for 8-h per day (8.00-16.00) with O3, for 16-h per day with NO2 (16.00-8.00) and continuously with SO2. Including the controls, the 24-h daily mean concentrations [microg m(-3)] ranged between 6-44 (O3), 9-88 (SO2) and 10-43 (NO2). The corresponding daily mean concentrations during the time of fumigation were 10-121 and 11-60 microg m(-3) for O3 and NO2, respectively. Single effects of O3 on growth and yield parameters were mostly negative and the magnitude of this effect was dependent on the season. O3 reduced plant dry weight by 11.3-18.6% and yield of seeds by 11.4-26.9%. While medium levels of SO2 stimulated the weight of pods up to 33%, higher concentrations (88 microg m(-3)) caused a decline of yield of 12.3%. From the significant interactive effects which were observed, it could be established that SO2 and NO2 alone mostly acted positively, but that their interaction with each other and especially with O3 was antagonistic, as some of the detrimental effects of O3 were mitigated by these pollutants. An important antagonistic effect between SO2 and O3 or NO2 was observed on yield. While 56 microg m(-3) SO2 increased yield by 9.9% compared to the control treatment, it aggravated the yield loss caused by O3 from -16.18% to -21.4%, and it reduced the yield stimulation caused by NO2 from +11.8% to +4.2%. Leaf area was the only parameter which was negatively affected by all pollutants, their joint action being synergistic.     

Short-term effects of gaseous pollutants on cause-specific mortality in Wuhan, China

In Asia, limited studies have been published on the association between daily mortality and gaseous pollutants of nitrogen dioxide (NO2), ozone (O3), and sulfur dioxide (SO2). Our previous studies in Wuhan, China, demonstrated long-term air pollution effects. However, no study has been conducted to determine mortality effects of air pollution in this region. This study was to determine the acute mortality effects of the gaseous pollutants in Wuhan, a city with 7.5 million permanent residents during the period from 2000 to 2004. There are approximately 4.5 million residents in Wuhan who live in the city's core area of 201 km2, where air pollution levels are highest, and pollution ranges are wider than the majority of the cities in the published literature. We used the generalized additive model to analyze pollution, mortality, and covariate data. We found consistent NO2 effects on mortality with the strongest effects on the same day. Every 10-microg/m3 increase in NO2 daily concentration on the same day was associated with an increase in nonaccidental (1.43%; 95% confidence interval [CI]: 0.87-1.99%), cardiovascular (1.65%; 95% CI: 0.87-2.45%), stroke (1.49%; 95% CI: 0.56-2.43%), cardiac (1.77%; 95% CI: 0.44-3.12%), respiratory (2.23%; 95% CI: 0.52-3.96%), and cardiopulmonary mortality (1.60%; 95% CI: 0.85-2.35%). These effects were stronger among the elderly than among the young. Formal examination of exposure-response curves suggests no-threshold linear relationships between daily mortality and NO2, where the NO2 concentrations ranged from 19.2 to 127.4 microg/m3. SO2 and O3 were not associated with daily mortality. The exposure-response relationships demonstrated heterogeneity, with some curves showing nonlinear relationships for SO2 and O3. We conclude that there is consistent evidence of acute effects of NO2 on mortality and suggest that a no-threshold linear relationship exists between NO2 and mortality.