Episodes Of Poor Air Quality Research Articles

153 Wildfire air pollution is associated with increased eczema, acne, and itch queries on Google

Wildfires are increasing in intensity and frequency, and wildfire smoke has been shown to exacerbate atopic dermatitis and itch for patients at one tertiary care medical center in San Francisco, California.We hypothesized that the effects of wildfire air pollution on the skin could impact a larger population, as detected by trends in online searches. Information seeking behaviors on the internet can reflect shifts in population-level interests related to short-term events, such as episodes of poor air quality during California wildfires.We obtained daily environmental data, including particulate matter (PM2.5) concentration and smoke plume density score (0-3), for San Francisco during the wildfire season from June through November 2020 and the same months in 2016, as a negative control.We also collected search data for common skin symptoms and conditions from Google Trends, which provides a daily Search Volume Index (SVI) ranging from 0 to 100 (most interest) for each term.

Source and Chemistry of Hydroxymethanesulfonate (HMS) in Fairbanks, Alaska.

Fairbanks, Alaska, is a subarctic city with fine particle (PM2.5) concentrations that exceed air quality regulations in winter due to weak dispersion caused by strong atmospheric inversions, local emissions, and the unique chemistry occurring under the cold and dark conditions. Here, we report on observations from the winters of 2020 and 2021, motivated by our pilot study that showed exceptionally high concentrations of fine particle hydroxymethanesulfonate (HMS) or related sulfur(IV) species (e.g., sulfite and bisulfite). We deployed online particle-into-liquid sampler–ion chromatography (PILS-IC) in conjunction with a suite of instruments to determine HMS precursors (HCHO, SO2) and aerosol composition in general, with the goal to characterize the sources and sinks of HMS in wintertime Fairbanks. PM2.5 HMS comprised a significant fraction of PM2.5 sulfur (26–41%) and overall PM2.5 mass concentration of 2.8–6.8% during pollution episodes, substantially higher than what has been observed in other regions, likely due to the exceptionally low temperatures. HMS peaked in January, with lower concentrations in December and February, resulting from changes in precursors and meteorological conditions. Strong correlations with inorganic sulfate and organic mass during pollution events suggest that HMS is linked to processes responsible for poor air quality episodes. These findings demonstrate unique aspects of air pollution formation in cold and humid atmospheres.

Air Quality and Active Transportation Modes: A Spatiotemporal Concurrence Analysis in Guadalajara, Mexico

The protection of pedestrians, cyclists, and public transportation passengers from environmental pollution is a global concern. This study fills the gap in the existing knowledge of temporal exposure to air pollution in Latin American metropolises. The paper proposes a methodology addressing the relationship between two objects of study, i.e., the users of active modes of transport and air quality. This new methodology assesses the spatiotemporal concurrence of both objects with statistical analysis of large open-access databases, to promote healthy and sustainable urban mobility. The application of the empirical methodology estimated the number of users of active transportation modes exposed to poor air quality episodes in the Guadalajara metropolitan area (Mexico) in 2019. The study considered two pollutants, ozone (O3) and particulate matter (PM10), and two active modes, cycling and bus rapid transit (BRT). Spatiotemporal analyses were carried out with geographic information systems, as well as with numeric computing platforms. First, big data were used to count the number of users for each mode within the area of influence of the air quality monitoring stations. Second, the number of air pollution episodes was obtained using the air quality index proposed by the Environmental Protection Agency (USA) on an hourly basis. Third, the spatiotemporal concurrence between air quality episodes and active mode users was calculated. In particular, the air quality monitoring data from the Jalisco Atmospheric Monitoring System were compared to users of the public bicycle share system, known as MiBici, and of a bus rapid transit line, known as Mi Macro Calzada. The results showed that the number of cyclists and BRT passengers exposed to poor air quality episodes was considerable in absolute terms, that is, 208,660 users, while it was marginal when compared to the total number of users exposed to better air quality categories in the study area, who represented only 10%. To apply the results at the metropolitan scale, the spatial distribution of the air quality monitoring system should be improved, as well as the availability of data on pedestrians and conventional bus passengers.

The Negative Impact of Biomass Burning and the Orinoco Low-Level Jet on the Air Quality of the Orinoco River Basin

Biomass burning (BB) is a common activity in developing countries and has been identified as a serious air pollution threat. The present work evaluates the air quality of the largest town in the extensive Colombian savannas (250,000 km2) for the first time, from measurements over three consecutive years (2017-2020). Although the air quality in Villavicencio is good in terms of PM10 and O3 for most of the year, the pollution levels for both pollutants exceed the World Health Organization recommended limits during the dry season (February to April). The combination of the Orinoco low-level jet (OLLJ) with the BB emissions from the Venezuelan and the Colombian savannas was identified as the main cause of the poor air quality episodes during the dry season in this city. Organic carbon derived from reanalysis was identified as the main component of the high PM10 concentrations during the dry season. However, mineral dust and sea salt particles were also found to play an important role in the poor air quality observed in Villavicencio and likely along the Orinoco river basin region. Finally, between November and March, the OLLJ was found to be an efficient mechanism for the transport of air pollutants from the Atlantic Ocean and the savannas regions in the Orinoco River Basin in Venezuela and Colombia towards southern regions of Colombia, and in some cases, Ecuador.

Using Digital Technology to Protect Health in Prolonged Poor Air Quality Episodes: A Case Study of the AirRater App during the Australian 2019–20 Fires

In the southern hemisphere summer of 2019–20, Australia experienced its most severe bushfire season on record. Smoke from fires affected 80% of the population, with large and prolonged exceedances of the Australian National Air Quality Standard for fine particulate matter (PM2.5) recorded in all major population centers. We examined if AirRater, a free smartphone app that reports air quality and tracks user symptoms in near real-time, assisted those populations to reduce their smoke exposure and protect their health. We distributed an online survey to over 13,000 AirRater users to assess how they used this information during the 2019–20 bushfire season, and why it was helpful to aid decision-making in reducing personal smoke exposure. We received responses from 1732 users (13.3%). Respondents reported the app was highly useful, supporting informed decision-making regarding daily activities during the smoke-affected period. Commonly reported activities supported by information provided through the app were staying inside (76%), rescheduling or planning outdoor activities (64%), changing locations to less affected areas (29%) and informing decisions on medication use (15%). Innovative and easy-to-use smartphone apps such as AirRater, that provide individual-level and location-specific data, can enable users to reduce their exposure to environmental hazards and therefore protect their health.

413 Wildfire-associated air pollution impacts clinic visits for itch and atopic dermatitis

With climate change, the frequency and intensity of wildfires are expected to increase, leading to episodes of poor air quality that could exacerbate patients’ pre-existing dermatoses. To assess the effects of exposure to wildfire-associated air pollution on skin, we investigated if the 2018 California Camp Fire led to detectable increases in clinic visits for atopic dermatitis (AD) or itch at dermatology clinics 175 miles from the origin of the fire. We collected data from 2015-2019 on particulate matter (PM2.5) concentration and smoke plume density in San Francisco and the number of outpatient dermatology visits for AD or itch symptoms at an academic medical center. Data were analyzed using Poisson regression with empirical standard errors, and the models included exposure lags and covariates: patient age and sex, temperature, and humidity. We found that the rates of weekly pediatric AD clinic visits, adult AD clinic visits, and pediatric itch symptoms during the Camp Fire were respectively 1.75 (95% CI: 1.21, 2.50), 1.28 (1.08, 1.51), and 2.10 (1.44, 3.00) times the rate for non-fire weeks for a 0-week lag, adjusted for time of year and confounders. Every 10 μg/m3 increase in average weekly PM2.5 concentration was associated with an adjusted rate ratio of 1.08 (95% CI: 1.04, 1.12) for weekly pediatric AD clinic visits. Thus, there was increased use of dermatology services for AD associated with exposure to air pollution from the Camp Fire, particularly for the pediatric population. With an impaired skin barrier function, AD patients may be at increased risk of adverse skin reactions following pollution exposure, which can negatively impact quality of life. Understanding the effects of air pollution on patients’ skin health can inform how dermatologists counsel patients and expand comprehension of the broader health effects of climate change.

Location of areas of emission of pollutants when poor urban air quality is detected

Air pollution constitutes an environmental risk, evidenced in large urban centres. This work applies a methodology capable of detecting the areas of emission of pollutants when episodes of poor urban air quality are observed. This is carried out coupling air quality indices proposed by United States Environmental Protection Agency with the receptor model known as Nonparametric Trajectory Analysis. As a control case, observed concentrations (2013-2015) in Bahia Blanca (Argentina) were analysed, highlighting particulate matter as a dominant pollutant for episodes of poor air quality. Likewise, the application of the methodology allowed to reduce the number of possible stationary emission sources by 75%, and to highlight the implication of nearby linear sources. The strength of the methodology lies in visualising in real time, or in diagnostic mode, the potential areas of emission and their significance.

Location of areas of emission of pollutants when poor urban air quality is detected

Air pollution constitutes an environmental risk, evidenced in large urban centres. This work applies a methodology capable of detecting the areas of emission of pollutants when episodes of poor urban air quality are observed. This is carried out coupling air quality indices proposed by United States Environmental Protection Agency with the receptor model known as Nonparametric Trajectory Analysis. As a control case, observed concentrations (2013-2015) in Bahia Blanca (Argentina) were analysed, highlighting particulate matter as a dominant pollutant for episodes of poor air quality. Likewise, the application of the methodology allowed to reduce the number of possible stationary emission sources by 75%, and to highlight the implication of nearby linear sources. The strength of the methodology lies in visualising in real time, or in diagnostic mode, the potential areas of emission and their significance.

Spatiotemporal Variation and Chemical Fingerprints of Marine Fine Particles (PM2.5) at the Matsu Islands in Northern Taiwan Strait

This study characterized the PM2.5 in terms of its spatial distribution, chemical composition, and seasonal/diurnal variation on the Matsu Islands in the northern Taiwan Strait. The PQ-200 samplers were employed to conduct simultaneous 24-h seasonal measurements of PM2.5 on four offshore islands, viz., Nankan Island (Site NK), Beigan Island (Site BG), Dongyin Island (Site DY), and Chiukung Island (Site CK) as well as 12-h diurnal measurements for both regular and intensive samplings, and 24-h episodic measurements at one of the locations (Site NK). Additionally, the chemical signatures of PM2.5 collected at six predominant local sources were established via chemical analysis, which coordinated as source profiles for chemical mass balance (CMB) receptor model to resolve the source apportionment of PM2.5. Of the four seasons, summer exhibited the lowest average PM2.5 concentration. In winter and spring, the level of PM2.5 significantly rose under the influences of Asian Northeastern Monsoons (ANEMs). Furthermore, the spatial distribution of PM2.5 across the islands showed a tendency to gradually decrease from the west to the east, with the Site NK always displaying the highest value regardless of the season. In general, the chemical composition primarily consisted of water-soluble ions (WSIs) owing to the abundancy of secondary inorganic aerosol (SIA) which accounted for 69.8% of the WSIs and 45.5% of the PM2.5. Crustal elements dominated the metallic components, although the content of trace metals increased in both concentrations and proportion during the ANEMs. Organic carbon (OC) dominated the carbonaceous content of PM2.5 in all seasons, with OC/EC values ranging from 1.64 to 3.78. During the episodes of poor air quality, the majority of incoming air masses followed a northern transport route (N-route) or an anticyclonic outflow route (AO-route) transported from the continent to the islands. The CMB receptor modeling results showed that the major sources of PM2.5 on the Matsu Islands were road dust, industrial boilers, secondary aerosols, vehicular exhausts, and sea salts. Overall, the PM2.5 pollution was originated from both local and remote sources, with 28~68% of the PM2.5 concentrations arising from long-range transport.

Chinese Consumers’ Perceptions of Functional Foods: A Netnography Study of Foods that Help the Immune System Recover from Air Pollution

ABSTRACTIn China, persistent and severe episodes of poor air quality have raised the population’s awareness of the deleterious impact that air pollution can have on their health and lead many people to explore physical means to limit their exposure to air pollution and therapies to help their immune system cope with this stress. Using a netnographic approach we explored Chinese consumers’ understandings of the impacts on their health caused by air pollution, and the key attributes (expected benefits, forms, and patterns of consumption) they expect of functional foods designed to help them recover from the pollution-driven impact. Relevant Chinese consumers’ discussions were selected from two Community Question Answering websites, “Zhihu” and “Baidu Knows”. The impact of pollution on the respiratory system was considered to be of the most concern and homemade TCM therapies and diet adjustment were the main forms of remedies discussed online. Results from this study will support the commercial success of functional food products designed to help Chinese consumers recover from the impact of air pollution on their health.

Termite Fly Optimization Algorithm towards Measuring and Predicting Air Pollution in California

Termite Fly Optimization Algorithm towards Measuring and Predicting Air Pollution in California

A dynamic multiple equation approach for forecasting PM[formula omitted] pollution in Santiago, Chile

This paper proposes a methodology based on a system of dynamic multiple linear equations that incorporates hourly, daily and annual seasonal characteristics for predicting hourly pm2.5 pollution concentrations for 11 meteorological stations in Santiago, Chile. It is demonstrated that the proposed model has the potential to match or even surpass the accuracy of competing nonlinear forecasting models in terms of both fit and predictive ability. In addition, the model is successful at predicting various categories of high concentration events, between 53% and 76% of mid-range events, and around 90% of extreme-range events on average across all stations. This forecasting model is considered a useful tool for helping government authorities to anticipate critical episodes of poor air quality so as to avoid the detrimental economic and health impacts of extreme pollution levels.

Characteristics and temporal variations of organic and elemental carbon aerosols in a high–altitude, tropical Latin American megacity

Bogota is a Latin American megacity located at an average altitude of 2600 m in the tropical Andes. It registers frequent episodes of poor air quality due to high PM10 concentrations. The carbonaceous fraction is the main PM10 component (>50%), but there is a lack of specific studies analyzing the characteristics and temporal variability of organic carbon (OC) and elemental carbon (EC) aerosols. In this study, daily samples (24±1h) were collected from June 2015 to May 2016 (a total of 308 samples) at an urban background site during an El Niño year, and the quartz filters were analyzed using a thermal-optical method. Results showed that EC and organic matter accounted for ~60% of the PM10 mass. The OC and EC averages were 8.92 ± 4.52 μg/m3 and 3.25 ± 1.59 μg/m3, respectively. The months with the highest average OC values were January to March, while EC concentrations were relatively constant throughout the year. Regarding daily values, the highest mean concentrations of OC (10.2 ± 5.13 μg/m3) and EC (3.73 ± 1.74 μg/m3) were obtained on Thursdays, and the lowest on Sundays (OC = 6.67 ± 3.04 μg/m3 and EC = 2.46 ± 0.94 μg/m3). The OC/EC ratio ranged from 1.66 (June) to 4.88 (March), with an annual average of 3.16 ± 2.01. The secondary organic carbon (SOC) contributions, measured using the EC-tracer method, accounted for 45% of the total OC. The effective carbon ratio, which indicates an association between carbonaceous particles and climate change, ranged from 0.12 (July) to 0.74 (May). The study of air-mass origins revealed that days with air mass from E + NE registered the highest OC concentrations. This research provides new data on the variability of carbonaceous aerosols over the course of a year. It also highlights forest fires as a significant source of OC and EC, and indicates the high impact of SOC on OC concentration at the sampling site.

Aerosol optical properties and radiative effects: Assessment of urban aerosols in central China using 10-year observations

Poor air quality episodes are common in central China. Here, based on 10 years of ground-based sun-photometric observations, aerosol optical and radiative forcing characteristics were analyzed in Wuhan, the biggest metropolis in central China. Aerosol optical depth (AOD) in the last decade declined significantly, while the Ångström exponent (AE) showed slight growth. Single scattering albedo (SSA) at 440 nm reached the lowest value (0.87) in winter and highest value (0.93) in summer. Aerosol parameters derived from sun-photometric observations were used as input in a radiative transfer model to calculate aerosol radiative forcing (ARF) on the surface in ultraviolet (UV), visible (VIS), near-infrared (NIR), and shortwave (SW) spectra. ARFSW sustained decreases (the absolute values) over the last 10 years. In terms of seasonal variability, due to the increases in multiple scattering effects and attenuation of the transmitted radiation as AOD increased, ARF in summer displayed the largest value (−73.94 W/m2). After eliminating the influence of aerosol loading, the maximum aerosol radiative forcing efficiency in SW range (ARFESW) achieved a value of −64.5 W/m2/AOD in April. The ARFE change in each sub-interval spectrum was related to the change in SSA and effective radius of fine mode particles (Refff), that is, ARFE increased with the decreases in SSA and Refff. The smallest contribution of ARFENIR to ARFESW was 34.11% under strong absorbing and fine particle conditions, and opposite results were found for the VIS range, whose values were always over 51.82%. Finally, due to the serious air pollution and frequency of haze day, aerosol characteristics in haze and clear days were analyzed. The percentage of ARFENIR increased from 35.71% on clear-air days to 37.63% during haze periods, while both the percentage of ARFEUV and ARFENIR in ARFESW kept decreasing. The results of this paper should help us to better understand the effect of aerosols on solar spectral radiation and to develop improved the aerosol models over central China.

Meteorological Influences on Tropospheric Ozone over Suburban Washington, DC

During the NASA DISCOVER-AQ (Deriving Information on Surface conditions from Column and Vertically Resolved Observations Relevant to Air Quality) campaign conducted in July 2011 across metropolitan Washington, DC, 25 daytime ozonesondes were launched from the Howard University Beltsville Campus (HUBC), representing the highest temporal density of measurements ever taken over the region. Time-height depiction of ozone concentration reveals considerable variability near the surface and in the mid/upper troposphere. Meteorological influences are assessed using the synoptic and mesoscale information, which revealed that periodic stratospheric intrusion of ozone-rich air was the main mechanism for elevated levels in the upper troposphere. It is also shown that high concentrations of ozone prevalent in the free troposphere were due to a combination of advection and aged air masses, which accounted for over 40% of the total budget. Poor air quality episodes with high surface concentration were due local emissions of precursors and associated synoptic-scale conditions. Breaks in the elevated ozone concentrations in the boundary layer and free troposphere occurred from frontal passages and accompanying storms. In the most unusual case (26 July, 2011), the combined effect of storms followed by two frontal passages and high pressure positioned west of the region led to decrease column ozone as much as 70%. The unusually deep extent of the reduction appears to be related to the temporary cutoff of air advected from fire locations and polluted regions, which dominated the upper troposphere throughout the period.

Chemical composition and source apportionment of PM10 at an urban background site in a high–altitude Latin American megacity (Bogota, Colombia)

Bogota registers frequent episodes of poor air quality from high PM10 concentrations. It is one of the main Latin American megacities, located at 2600m in the tropical Andes, but there is insufficient data on PM10 source contribution. A characterization of the chemical composition and the source apportionment of PM10 at an urban background site in Bogota was carried out in this study. Daily samples were collected from June 2015 to May 2016 (a total of 311 samples). Organic carbon (OC), elemental carbon (EC), water soluble compounds (SO42-, Cl-, NO3-, NH4+), major elements (Al, Fe, Mg, Ca, Na, K, P) and trace metals (V, Cd, Pb, Sr, Ba, among others) were analyzed. The results were interpreted in terms of their variability during the rainy season (RS) and the dry season (DS). The data obtained revealed that the carbonaceous fraction (∼51%) and mineral dust (23%) were the main PM10 components, followed by others (15%), Secondary Inorganic Compounds (SIC) (11%) and sea salt (0.4%). The average concentrations of soil, SIC and OC were higher during RS than DS. However, peak values were observed during the DS due to photochemical activity and forest fires. Although trace metals represented <1% of PM10, high concentrations of toxic elements such as Pb and Sb on RS, and Cu on DS, were obtained. By using a PMF model, six factors were identified (∼96% PM10) including fugitive dust, road dust, metal processing, secondary PM, vehicles exhaust and industrial emissions. Traffic (exhaust emissions+road dust) was the major PM10 source, accounting for ∼50% of the PM10. The results provided novel data about PM10 chemical composition, its sources and its seasonal variability during the year, which can help the local government to define control strategies for the main emission sources during the most critical periods.

Developing and validating a new national remote health advice syndromic surveillance system in England.

Public Health England (PHE) coordinates a suite of real-time national syndromic surveillance systems monitoring general practice, emergency department and remote health advice data. We describe the development and informal evaluation of a new syndromic surveillance system using NHS 111 remote health advice data. NHS 111 syndromic indicators were monitored daily at national and local level. Statistical models were applied to daily data to identify significant exceedances; statistical baselines were developed for each syndrome and area using a multi-level hierarchical mixed effects model. Between November 2013 and October 2014, there were on average 19 095 NHS 111 calls each weekday and 43 084 each weekend day in the PHE dataset. There was a predominance of females using the service (57%); highest percentage of calls received was in the age group 1-4 years (14%). This system was used to monitor respiratory and gastrointestinal infections over the winter of 2013-14, the potential public health impact of severe flooding across parts of southern England and poor air quality episodes across England in April 2014. This new system complements and supplements the existing PHE syndromic surveillance systems and is now integrated into the routine daily processes that form this national syndromic surveillance service.

The impact of communicating information about air pollution events on public health

Short-term exposure to air pollution has been associated with exacerbation of asthma and chronic obstructive pulmonary disease (COPD). This study investigated the relationship between emergency hospital admissions for asthma, COPD and episodes of poor air quality in an English city (Southampton) from 2008–2013. The city's council provides a forecasting service for poor air quality to individuals with respiratory disease to reduce preventable admissions to hospital and this has been evaluated. Trends in nitrogen dioxide, ozone and particulate matter concentrations were related to hospital admissions data using regression analysis. The impacts of air quality on emergency admissions were quantified using the relative risks associated with each pollutant. Seasonal and weekly trends were apparent for both air pollution and hospital admissions, although there was a weak relationship between the two. The air quality forecasting service proved ineffective at reducing hospital admissions. Improvements to the health forecasting service are necessary to protect the health of susceptible individuals, as there is likely to be an increasing need for such services in the future.

Elastic lidar measurements of summer nocturnal low level jet events over Baltimore, Maryland

Elastic lidar (532 nm) measurements were carried out by the Atmospheric Lidar Group at the University of Maryland, Baltimore County (UMBC, 39.25° N, 76.70° W) during meteorological conditions that favored the formation of the nocturnal low level jet (NLLJ) over the United States Mid-Atlantic region. The lidar timeseries from three case studies showed the intrusion of the NLLJ air mass into the nocturnal boundary layer (NBL) and the subsequent displacement of aerosols that were used for tracing atmospheric motion. Three distinctive regions were identified in the timeseries: 1) a wedging zone within the residual layer, that was heavily laden with aerosols, at the onset of the NLLJ, 2) a lofted layer of particulates above the “clean” jet core, and 3) a region where the lofted layer collapsed that was conterminous with the diminishing NLLJ below, and characterized by downward mixing analogous to turbulent wake regions. The National Oceanic and Atmospheric Administration’s (NOAA) Rapid Update Cycle (RUC, grid 252) model was used to analyze the horizontal extent and vertical structure of the NLLJ and to compare with observations acquired during these events. A conceptual model is proposed to highlight the role of the NLLJ, during similar weather patterns, in the regional transport of pollutants and their impact on poor air quality episodes in the Mid-Atlantic United States.

Air quality modelling using the Met Office Unified Model (AQUM OS24-26): model description and initial evaluation

Abstract. The on-line air quality model AQUM (Air Quality in the Unified Model) is a limited-area forecast configuration of the Met Office Unified Model which uses the UKCA (UK Chemistry and Aerosols) sub-model. AQUM has been developed with two aims: as an operational system to deliver regional air quality forecasts and as a modelling system to conduct air quality studies to inform policy decisions on emissions controls. This paper presents a description of the model and the methods used to evaluate the performance of the forecast system against the automated UK surface network of air quality monitors. Results are presented of evaluation studies conducted for a year-long period of operational forecast trials and several past cases of poor air quality episodes. The results demonstrate that AQUM tends to over-predict ozone (~8 μg m−3 mean bias for the year-long forecast), but has a good level of responsiveness to elevated ozone episode conditions – a characteristic which is essential for forecasting poor air quality episodes. AQUM is shown to have a negative bias for PM10, while for PM2.5 the negative bias is much smaller in magnitude. An analysis of speciated PM2.5 data during an episode of elevated particulate matter (PM) suggests that the PM bias occurs mainly in the coarse component. The sensitivity of model predictions to lateral boundary conditions (LBCs) has been assessed by using LBCs from two different global reanalyses and by comparing the standard, single-nested configuration with a configuration having an intermediate European nest. We conclude that, even with a much larger regional domain, the LBCs remain an important source of model error for relatively long-lived pollutants such as ozone. To place the model performance in context we compare AQUM ozone forecasts with those of another forecasting system, the MACC (Monitoring Atmospheric Composition and Climate) ensemble, for a 5-month period. An analysis of the variation of model skill with forecast lead time is presented and the insights this provides to the relative sources of error in air quality modelling are discussed.