Ground-level Ozone Concentrations Research Articles

Field performance evaluation of Maxxam passive samplers for regional monitoring of ambient SO2, NO2 and O3 concentrations in Alberta, Canada

A field performance evaluation of Maxxam passive samplers was carried out for ambient concentrations of sulfur dioxide (SO2), nitrogen dioxide (NO2) and ground-level ozone (O3). Monthly passive and hourly continuous air monitoring data from four regional air monitoring networks in Alberta, Canada were evaluated over a 5-year period (2006–2010). Monthly concentrations were relatively low, ranging from 0.1 to 3.9 ppb, 0.2–18.1 ppb and 10.1–56.1 ppb for SO2, NO2 and O3, respectively. From duplicate passive sampling, geometric mean precision values were 17.9%, 14.8% and 4.7% for SO2, NO2 and O3, respectively. Geometric mean of the relative error (as a measure of accuracy) was 30% (median = 33%, interquartile range, IQR 15–63%) for SO2 and 32% (median = 40%, IQR = 25–64%) for NO2. O3 measurements had a better measure of accuracy with a geometic mean relative error of 12% (median = 17%, IQR = 8–27%) and met the acceptable level recommended by United States National Institute of Safety and Health (NIOSH) and the European Union (EU) Directive (±25%). From reduced major axis (RMA) analysis, bias (systematic error) is apparent in the Maxxam passive samplers in the field resulting in overestimation of ambient SO2 and O3 concentrations and underestimation of NO2 concentrations relative to continuous analyzers. Seasonal influences were observed for accuracy of passive SO2 and O3 measurements. A poor association was found between passive versus continuous concentrations for SO2 and O3 during the winter and the summer, respectively.

Development of PLS–path model for understanding the role of precursors on ground level ozone concentration in Gulfport, Mississippi, USA

Ground-level ozone (GLO) is produced by a complex chain of atmospheric chemical reactions that depend on precursor emissions from natural and anthropogenic sources. GLO concentration in a particular location is also governed by local weather and climatic factors. In this work an attempt was made to explore a Partial Least Squares Path Modeling (PLS–PM) approach to quantify the interrelationship between local conditions (weather parameters and primary air pollution) and GLO concentrations. PLS path modeling algorithm was introduced and applied to GLO concentration analyses at Gulfport, Mississippi, USA. In the present analysis, three latent variables were selected: PRC (photochemical reaction catalyst), MP (meteorological factor), and OPP (other primary air pollutants). The three latent variables included 14 indicators for the analysis; with PRC having two (extraterrestrial radiation on horizontal surface, and extraterrestrial radiation normal to the sun), MP having nine (temperature, dew point, relative humidity, pressure, visibility, maximum wind speed, average wind speed, precipitation, and wind direction) and OPP having three (NO2, PM2.5, and SO2) parameters. The resulting model revealed that PRC had significant direct impact on GLO concentration but very small overall effect. This is because PRC had significant indirect negative impact on GLO via MP. Thus, when both direct and indirect effects were taken into account, PRC emerged as having the weakest effect on GLO. The third variable (OPP) also had a positive impact on GLO concentration.

Detection of Changes in Ground-Level Ozone Concentrations via Entropy

Ground-level ozone concentration is a key indicator of air quality. Theremay exist sudden changes in ozone concentration data over a long time horizon, which may be caused by the implementation of government regulations and policies, such as establishing exhaust emission limits for on-road vehicles. To monitor and assess the efficacy of these policies, we propose a methodology for detecting changes in ground-level ozone concentrations, which consists of three major steps: data transformation, simultaneous autoregressive modelling and change-point detection on the estimated entropy. To show the effectiveness of the proposed methodology, the methodology is applied to detect changes in ground-level ozone concentration data collected in the Toronto region of Canada between June and September for the years from 1988 to 2009. The proposed methodology is also applicable to other climate data.

Diurnal variations of ground-level ozone in three port cities in Malaysia

The diurnal variations of ground-level ozone (O3) concentrations along a gradient of three major port cities (Klang, Perai, and Pasir Gudang) in Malaysia were evaluated. Annual monitoring records (2009) of O3, nitrogen dioxide (NO2), nitric oxide (NO), carbon monoxide (CO), sulfur dioxide (SO2), and particulate matter (PM10) were obtained. Weather-influencing parameters such as incoming solar radiation, temperature, relative humidity, and wind speed were also analyzed. Although an overwhelming majority (99.9 %) of the recorded data are below the prescribed levels in the Malaysian Ambient Air Quality Guidelines (MAAQG), a number of exceedances (0.1 %) (>100 ppb) have been recorded in Klang and Pasir Gudang. The annual hourly average concentrations of O3 were 20.3 ± 18.2, 15.4 ± 15.8, and 14.4 ± 13.1 ppb for Klang, Perai, and Pasir Gudang, respectively. The diurnal cycles of ground-level O3 concentrations and cluster analysis suggest that a unimodal peak occurs between 1 p.m. and 3 p.m., and the highest O3 concentrations were observed during the first quarter of 2009 as a result of the higher rate of local photochemical production. Results of principal component analysis showed that the contributions to O3 level variation by meteorological variables (UVB, temperature, relative humidity, and wind speed) are higher at 47.7, 39.5, and 18.2 % than those of primary air pollutants (NOx, CO, SO2, PM10) at 28.9, 32.6, and 45 % for Perai, Pasir Gudang, and Klang, respectively. The exposure of the population in the three port cities to the elevated levels of ozone during January–May months validated the increasing threat and risks that ozone presents to humans. Result indicated that the concentration of O3 in the three ports was still below the maximum permissible values prescribed by the MAAQG, and expansion in shipping industries is possible in exaggerating O3 problems especially in Klang.

Application of chemical dispersion model during a high ozone episode in South-West Poland

In this study, the Weather Research and Forecasting model with chemistry (WRF-Chem v3.5) is applied to the area of Poland, for a period of 03.07-03.08.2006, when high concentrations of ground level ozone were observed. The meteorological and chemistry simulations were initiated with the ERA-Interim reanalysis and the TNO MACC-II emissions database. Simulations were performed for three one-way nested domains. The results from the innermost domain were examined and compared to measurements of ozone concentrations and meteorological variables. The modelled results show a general underestimation of measured ozone concentrations. For urban and suburban sites it is significantly higher during day time. Domain-wide estimations of temperature were also underestimated, and relative humidity and wind speed were overpredicted. The results may be further improved by adjusting physical parameterisations and including a more detailed emission input data into the model.

Modelling Ozone-Temperature Slope under Atypically High Temperature in Arid Climatic Conditions of Makkah, Saudi Arabia

Ground level ozone concentration is dependent on its precursors, such as Nitrogen Oxides (NOx) and hydrocarbons (HCs) and meteorological parameters, most importantly air temperature. Positive ozone-temperature slope at average temperature is well-documented. However, how this relationship breaks at extremely high temperature in hotter climates is still debatable. As this could have implications for long term global modelling predictions, this paper explores evidence for a negative ozone-temperature slope during atypically high temperature events in Makkah, Saudi Arabia, where temperature levels as high as 50°C are recorded. At temperature levels (15–42°C) statistical analysis showed positive ozone-temperature slopes, however the slopes became negative at atypically high temperature levels (> 42°C). Using data when hourly mean temperature was greater than 42°C, Quantile Regression Model (QRM) showed negative ozone-temperature slopes. The negative slopes at quantile 0.2, 0.3, 0.4, 0.5, 0.6, 0.7, 0.8 and 0.9 were –1.88, –5.83, –7.89, –7.08, –11.11, –15.00, –18.28, and –28.57 µg/m3/°C, respectively. Mean slope determined by linear regression was –11.51 µg/m3/°C. Furthermore, the negative slopes were stronger at higher quantiles of ozone distribution, indicating non-linearities in the association of ozone and temperature. Reduction in the levels of ozone precursors, such as total hydrocarbons (THCs) and nitrogen dioxide (NO2) is probably the most likely reason for the negative ozone-temperature slope at extremely high temperature. Previously concerns have been expressed that under the warming climate scenario increasing temperature may further increase ozone levels, particularly in urban areas during pollution episodes, however this study suggests the opposite at extremely high temperature in hot arid climatic conditions.

Seasonal Variation in Surface Ozone Concentrations, Meteorology and Primary Pollutants in Coastal Mega City of Mumbai, India

In the present the study variation in ground level ozone (GLO) concentration with respect to availability of precursor pollutants and meteorological parameters in the tropical climatic conditions in Mumbai, India is discussed. The concentration of various pollutants and meteorological parameters have been monitored at the continuous air quality monitoring station of Maharashtra Pollution Control Board, located in Bandra (Mumbai) for two years. The analysis of the data indicates that the pattern of formation of GLO changes with change in season. The maximum concentration for GLO was experienced in the post monsoon season unlike any other study reported in the country. The study highlights that the post monsoon season experienced the highest number of hourly and eight hourly exceedances in the permissible limits prescribed by the Central Pollution Control Board. These high concentrations can be attributed to favorable climatic conditions and presence of precursor pollutants. This was proved by correlating GLO with precursor pollutants and meteorological parameters.

High Nighttime Ground-Level Ozone Concentrations in Kemaman: NO and NO2 Concentrations Attributions

ABSTRACTHigh nighttime ozone (O3) concentration levels were observed in Kemaman, Terengganu, and results were compared with those in other places in Malaysia. In this study, the contribution of precursors [nitric oxide (NO) and nitrogen dioxide (NO2)] and meteorological factors wind speed, and wind direction) toward long-term high nighttime O3 over the period of 1999 to 2010 was evaluated. During this period, the recorded highest nighttime O3 ground level was 89 ppb with more than 25% surpassing 20 ppb. Analysis shows that minimal decreasing trends were measured in Kemaman. Lower nitrogen oxide (NOx) concentrations restricted the sinking agents; thus, reducing the depletion rates allowed O3 to remain in the atmosphere. Minimal associations were observed between the O3 concentration level and the speed and direction of wind. Accordingly, the largest contributor toward high nighttime O3 ground level concentration in Kemaman was most probably NOx concentration.

Spatial and temporal variations in atmospheric VOCs, NO2, SO2, and O3 concentrations at a heavily industrialized region in Western Turkey, and assessment of the carcinogenic risk levels of benzene

Ambient concentrations of volatile organic compounds (VOCs), nitrogen dioxide (NO2), sulphur dioxide (SO2) and ground-level ozone (O3) were measured at 55 locations around a densely populated industrial zone, hosting a petrochemical complex (Petkim), a petroleum refinery (Tupras), ship-dismantling facilities, several iron and steel plants, and a gas-fired power plant. Five passive sampling campaigns were performed covering summer and winter seasons of 2005 and 2007. Elevated concentrations of VOCs, NO2 and SO2 around the refinery, petrochemical complex and roads indicated that industrial activities and vehicular emissions are the main sources of these pollutants in the region. Ozone concentrations were low at the industrial zone and settlement areas, but high in rural stations downwind from these sources due to NO distillation. The United States Environmental Protection Agency's positive matrix factorization receptor model (EPA PMF) was employed to apportion ambient concentrations of VOCs into six factors, which were associated with emissions sources. Traffic was found to be highest contributor to measured ∑VOCs concentrations, followed by the Petkim and Tupras.Median cancer risk due to benzene inhalation calculated using a Monte Carlo simulation was approximately 4 per-one-million population, which exceeded the U.S. EPA benchmark of 1 per one million. Petkim, Tupras and traffic emissions were the major sources of cancer risk due to benzene inhalation in the Aliaga airshed. Relative contributions of these two source groups changes significantly from one location to another, demonstrating the limitation of determining source contributions and calculating health risk using data from one or two permanent stations in an industrial area.

Association of short-term exposure to ground-level ozone and respiratory outpatient clinic visits in a rural location – Sublette County, Wyoming, 2008–2011

ObjectiveShort-term exposure to ground-level ozone has been linked to adverse respiratory and other health effects; previous studies typically have focused on summer ground-level ozone in urban areas. During 2008–2011, Sublette County, Wyoming (population: ~10,000 persons), experienced periods of elevated ground-level ozone concentrations during the winter. This study sought to evaluate the association of daily ground-level ozone concentrations and health clinic visits for respiratory disease in this rural county. MethodsClinic visits for respiratory disease were ascertained from electronic billing records of the two clinics in Sublette County for January 1, 2008–December 31, 2011. A time-stratified case-crossover design, adjusted for temperature and humidity, was used to investigate associations between ground-level ozone concentrations measured at one station and clinic visits for a respiratory health concern by using an unconstrained distributed lag of 0–3 days and single-day lags of 0 day, 1 day, 2 days, and 3 days. ResultsThe data set included 12,742 case-days and 43,285 selected control-days. The mean ground-level ozone observed was 47±8ppb. The unconstrained distributed lag of 0–3 days was consistent with a null association (adjusted odds ratio [aOR]: 1.001; 95% confidence interval [CI]: 0.990–1.012); results for lags 0, 2, and 3 days were consistent with the null. However, the results for lag 1 were indicative of a positive association; for every 10-ppb increase in the 8-h maximum average ground-level ozone, a 3.0% increase in respiratory clinic visits the following day was observed (aOR: 1.031; 95% CI: 0.994–1.069). Season modified the adverse respiratory effects: ground-level ozone was significantly associated with respiratory clinic visits during the winter months. The patterns of results from all sensitivity analyzes were consistent with the a priori model. ConclusionsThe results demonstrate an association of increasing ground-level ozone with an increase in clinic visits for adverse respiratory-related effects in the following day (lag day 1) in Sublette County; the magnitude was strongest during the winter months; this association during the winter months in a rural location warrants further investigation.

Natural selection? Picking the right trees for urban greening

Abstract Fast-track programs to plant millions of trees in cities around the world aim at the reduction of summer temperatures, increase carbon storage, storm water control, provision of space for recreation, as well as poverty alleviation. Although these multiple benefits speak positively for urban greening programs, the programs do not take into account the drastic differences between urban and natural systems. Elevated temperatures together with anthropogenic emissions of air and water pollutants distinguish the urban system. Although the potential for emissions of volatile organic compounds from urban vegetation combined with anthropogenic emissions to produce ozone has long been recognized, the municipalities actively enlarging their green spaces still generally either overlook or ignore this fact. Here we assess the scientific evidence of biogenic induction of ground-level ozone concentrations in urban and sub-urban areas and argue that it is feasible and beneficial to implement measures necessary to limit biogenic contributions to air pollution. With the example of biogenic induction of ground level ozone concentrations we demonstrate that interactions between plants and urban ambient conditions have to be taken into account in all efforts of creating “naturopolises”. We explore the mechanisms behind these interactions and propose a pathway to improve our understanding of these interactions.

Response of the summertime ground-level ozone trend in the Chicago area to emission controls and temperature changes, 2005–2013

Despite strenuous efforts to reduce the emissions of ozone precursors such as nitrogen oxides (NOx), concentrations of ground-level ozone (O3) still often exceed the National Ambient Air Quality Standard in U.S. cities in summertime, including Chicago. Furthermore, studies have projected a future increase in O3 formation due to global climate change. This study examines the response of summertime O3 to emission controls and temperature change in the Chicago area from 2005 to 2013 by employing observations of O3, O3 precursors, and meteorological variables. We find that meteorology explains about 53% of the O3 variance in Chicago. O3 mixing ratios over Chicago are found to show no clear decline over the 2005–2013 period. The summertime ground-level O3 trend consists of a decrease of 0.08 ppb/year between 2005 and 2009 and an increase of 1.49 ppb/year between 2009 and 2013. Emissions of NOx and concentrations of NO2 have been decreasing steadily from 2005 to 2013 in the Chicago area. Concentrations of volatile organic compounds (VOCs) in Chicago, however, have more than doubled since 2009, even though emission inventories suggest that VOC emissions have decreased. We believe that O3 production in Chicago became more sensitive to VOCs starting in 2008/2009 and may have switched from being NOx-limited to VOC-limited. The warmer climate since 2008 has also contributed to the increasing ozone trend in the Chicago area. Increased attention should be paid to improving the quantification of VOC sources, enhancing the monitoring of reactive VOC concentrations, and designing VOC mitigation measures.

Influence of local meteorology and NO2 conditions on ground-level ozone concentrations in the eastern part of Texas, USA.

The influence of local climatic factors on ground-level ozone concentrations is an area of increasing interest to air quality management in regards to future climate change. This study presents an analysis on the role of temperature, wind speed, wind direction, and NO2 level on ground-level ozone concentrations over the region of Eastern Texas, USA. Ozone concentrations at the ground level depend on the formation and dispersion processes. Formation process mainly depends on the precursor sources, whereas, the dispersion of ozone depends on meteorological factors. Study results showed that the spatial mean of ground-level ozone concentrations was highly dependent on the spatial mean of NO2 concentrations. However, spatial distributions of NO2 and ozone concentrations were not uniformed throughout the study period due to uneven wind speeds and wind directions. Wind speed and wind direction also played a significant role in the dispersion of ozone. Temperature profile in the area rarely had any effects on the ozone concentrations due to low spatial variations.

Simple atmospheric dispersion model to estimate hourly ground-level nitrogen dioxide and ozone concentrations at urban scale

Atmospheric nitrogen dioxide (NO2) and ozone (O3) present potential health risk at large urban centres worldwide. Modelling their ground-level concentrations is a fundamental part of urban air quality assessment studies. Simple atmospheric dispersion models are particularly useful in places lacking detailed input data to run complex models and for applications requiring a large number of simulations, also allowing high spatial and temporal resolution even for long-term calculations. The DAUMOD-GRS urban atmospheric dispersion model has been developed aiming to have these features. This work presents its performance evaluation considering hourly concentrations of NO2 and O3 measured at twenty sites across the Metropolitan Area of Buenos Aires (MABA), Argentina. Results show an acceptable model performance, with a small tendency to underestimate NO2 and to overestimate O3. By grouping the monitoring sites in regions having different emission conditions, it is found that the model reproduces well the observed urban-suburban concentration gradients.

Assessing exceedance of ozone standards: a space‐time downscaler for fourth highest ozone concentrations

The US Environmental Protection Agency is required to monitor, regulate, and set national ambient air quality standards for ozone. To investigate ozone exposure, the Environmental Protection Agency utilizes monitoring devices along with estimates of gridded ground level ozone concentration produced by a deterministic air quality model, the Community Multiscale Air Quality Model. These two sources of information enable inference regarding spatial exceedance of the National Ambient Air Quality Standard for ozone, which is given in terms of the level of the annual fourth highest ozone concentration.Here, we extend previous downscaling work to propose a spatial fourth highest extreme value downscaling model to assimilate annual fourth highest ozone concentration data at geo‐coded locations with estimates at grid cell level derived from the Community Multiscale Air Quality Model model output. The resulting inference enables us to make probabilistic statements, with associated uncertainty, about the spatial variation in the chance of exceeding the standard. We apply our approach to data in the Eastern USA during years 2001–2008 and compare its predictive performance to that of downscaler models based on Gaussian processes applied to daily data. Copyright © 2014 John Wiley & Sons, Ltd.

Proposal for estimating ground-level ozone concentrations at urban areas based on multivariate statistical methods

This study focuses on describing ozone patterns and estimating ozone concentrations in urban settings through the classification of an urban area into homogeneous typologies, according to hourly ozone concentrations, and the development of accurate estimation models for each typology. For these proposals, a hierarchical cluster analysis was conducted in order to define homogeneous subareas, and multiple linear regressions were subsequently applied with the aim of obtaining ozone predictions, employing chemical and meteorological variables as predictors. Seville metropolitan area (Spain) is a densely populated area of the Mediterranean Basin that exhibits environmental problems related to ozone pollution episodes. Ozone exceedances are a consequence of the combination of road traffic and industry emissions with hot temperatures and high solar radiation, mainly during anticyclonic events. Cluster analysis evince that this area can be divided into 3 categories according to hourly ozone concentration in summer. Cluster 1 is comprised of monitoring stations located in the outskirts of the city of Seville; Cluster 2 corresponds to monitoring stations located within the city of Seville; and Cluster 3 is comprised of a monitoring station specialized in traffic emissions. Multiple linear regression shows that the relative weight of meteorological variables decreases when moving from the urban periphery towards the urban center, whereas the weight of chemical variables increases. Coefficients of determination (R2) values were 0.885, 0.890 and 0.830 and root mean squared error (RMSE) were 11.226, 11.874 and 11.260 μg m−3 for Cluster 1, 2 and 3, respectively.

A Pilot Study to Identify Factors Affecting UV-B Radiation Exposure in Selected Microenvironments

A pilot study was conducted to test a protocol for collecting data useful for identifying local factors affecting exposure to ultraviolet-B radiation (UV-B). A trained technician followed a prepared script through a series of microenvironments representing varying conditions of overhead shielding and ground cover while collecting UV-B irradiance and related data on days selected to represent varying conditions of solar radiation, cloud cover, groundlevel ozone concentration, and fine particulate matter (PM2.5) concentration. The resulting data were combined with air pollution, UV-B, and meteorological data obtained from local fixed-site monitoring stations and analyzed to identify the principal factors affecting (1) UVI (UV Index) measured by the Safe Sun monitor and (2) fixed-site UV-B. Results of these analyses indicated that the best predictors of UVI were degree of shielding, solar angle, fixed-site UV-B, cloud cover, wind speed, time of day, and season. Although cloud cover was an important predictor of UVI, the clearest days did not correspond to the highest UVI values. Variations in cloud parameters can cause intraday UVI variations not reflected in a daily forecast. Residential outdoor microenvironments tended to have lower mean UVI values than outdoor recreation microenvironments (e.g., athletic field, pool), which may have implications for estimating total personal exposure to UV-B.

Ground level ozone effects in individual growth phases of central european submountain beech forests

AbstractWe observed ground level ozone concentrations on a series of five beech experimental plots, one representing the original stand and the other four generated and modified by cuts of graduated intensity. The study was carried out in a beech ecosystem in the Kremnické vrchy Mts, the Western Carpathian region, in years 1999-2008. The plots, established in 1989, were evaluated and compared statistically before and after the cutting modification in 2004. The level of significance of the effect of this intervention was 99% on the plot representing small-area clear-cut and on the plot treated with medium cut. Differences, though not significant, were also found in the other plots. Apart from the effects due to the stocking reduction, the whole post-intervention period was characterised with the influence of progressively increasing average air temperatures and similarly increasing ozone concentrations. Globally, the ozone concentrations on all plots were lower (average value 39 μg m

Canaries in the coal mine

Up until 30 years ago, coalminers relied on canaries as warning systems against harmful gases and pollutants underground. The miners listened for birdsong and if the birds fell silent, then they knew there was danger to their health and to take action. Today we have much more sophisticated information and reporting on the quality of air. We know precisely the levels and composition of pollutants in the air that are responsible for almost 500,000 deaths annually [1]. The problem is however, that nobody appears to be listening. The air we breathe reduces our life expectancy by on average 8.6 months in Europe (fig. 1) [2]. Fine particle pollution (particles with a 50% cut-off aerodynamic diameter of 2.5 µm) is estimated to account for some 5 million lost years of life in the European Economic Area (www.efta.int/eea) countries every year [3]. Exposure to ground-level ozone concentrations above critical health levels is associated with more than 20 000 premature deaths in the European Union (EU) annually [4]. Yet, 17 EU Member States are being taken to court by the European Commission …

Inverse modeling of Texas NO<sub>x</sub> emissions using space-based and ground-based NO<sub>2</sub> observations

Abstract. Inverse modeling of nitrogen oxide (NOx) emissions using satellite-based NO2 observations has become more prevalent in recent years, but has rarely been applied to regulatory modeling at regional scales. In this study, OMI satellite observations of NO2 column densities are used to conduct inverse modeling of NOx emission inventories for two Texas State Implementation Plan (SIP) modeling episodes. Addition of lightning, aircraft, and soil NOx emissions to the regulatory inventory narrowed but did not close the gap between modeled and satellite-observed NO2 over rural regions. Satellite-based top-down emission inventories are created with the regional Comprehensive Air Quality Model with extensions (CAMx) using two techniques: the direct scaling method and discrete Kalman filter (DKF) with decoupled direct method (DDM) sensitivity analysis. The simulations with satellite-inverted inventories are compared to the modeling results using the a priori inventory as well as an inventory created by a ground-level NO2-based DKF inversion. The DKF inversions yield conflicting results: the satellite-based inversion scales up the a priori NOx emissions in most regions by factors of 1.02 to 1.84, leading to 3–55% increase in modeled NO2 column densities and 1–7 ppb increase in ground 8 h ozone concentrations, while the ground-based inversion indicates the a priori NOx emissions should be scaled by factors of 0.34 to 0.57 in each region. However, none of the inversions improve the model performance in simulating aircraft-observed NO2 or ground-level ozone (O3) concentrations.