Inherent uncertainty in air quality modeling

This paper summarizes the discussions of a working group that was charged with the task of examining inherent uncertainty in air quality modeling. The major topics of the paper are:

• 1.1. Definition of inherent uncertainty in air quality models;
• 2.2. Determination of inherent uncertainty;
• 3.3. Role of inherent uncertainty in model evaluation.

The concepts introduced here are illustrated through a numerical simulation with Gifford's fluctuating plume model.     

Skill and uncertainty of a regional air quality model ensemble

Recently several regional air quality projects were carried out to support the negotiation under the Clean Air For Europe (CAFE) programme by predicting the impact of emission control policies with an ensemble of models. Within these projects, CITYDELTA and EURODELTA, the fate of air quality at the scale of European cities or that of the European continent was studied using several models. In this article we focus on the results of EURODELTA. The predictive skill of the ensemble of models is described for ozone, nitrogen dioxide and secondary inorganic compounds, and the uncertainty in air quality modelling is examined through the model ensemble spread of concentrations.For ozone daily maxima the ensemble spread origin differs from one region to another. In the neighbourhood of cities or in mountainous areas the spread of predicted values does not span the range of observed data, due to poorly resolved emissions or complex-terrain meteorology. By contrast in Atlantic and North Sea coastal areas the spread of predicted values is found to be larger than the observations. This is attributed to large differences in the boundary conditions used in the different models. For NO₂ daily averages the ensemble spread is generally too small compared with observations. This is because models miss highest values occurring in stagnant meteorology in stable boundary layers near cities. For secondary particulate matter compounds the simulated concentration spread is more balanced, observations falling nearly equiprobably within the ensemble, and the spread originates both from meteorology and aerosol chemistry and thermodynamics.     

The Valley of Mexico: summary of observational studies on its air quality and effects on vegetation

Present day Mexico City was established on the banks of the now dead Lake Texcoco by Aztec Indians in a.d. 1325. Over time, increasing population growth, urbanization, vehicular traffic and the number of diverse stationary sources, coupled with its topography and the resultant frequency of prevalent stagnant air masses make Mexico City one of the most polluted areas in the world. Use of biological indicator plants since the early 1970s has shown the critical nature of phytotoxic photochemical oxidants in the region. More recent empirical studies with bean, soybean and pine species confirm these observations and raise concern regarding the geographic magnitude of the problem. Surface measurements of air quality in the region are inadequate and require much additional support. Ultimately, ambient air quality measurements must be coupled with the observations on responses of sensitive vegetation. While the results presented in this paper are primarily observational or qualitative, they hopefully serve the purpose of bringing attention to a critical air quality issue in a developing country.     

Traffic and meteorological impacts on near-road air quality: summary of methods and trends from the Raleigh Near-Road Study

A growing number of epidemiological studies conducted worldwide suggest an increase in the occurrence of adverse health effects in populations living, working, or going to school near major roadways. A study was designed to assess traffic emissions impacts on air quality and particle toxicity near a heavily traveled highway. In an attempt to describe the complex mixture of pollutants and atmospheric transport mechanisms affecting pollutant dispersion in this near-highway environment, several real-time and time-integrated sampling devices measured air quality concentrations at multiple distances and heights from the road. Pollutants analyzed included U.S. Environmental Protection Agency (EPA)-regulated gases, particulate matter (coarse, fine, and ultrafine), and air toxics. Pollutant measurements were synchronized with real-time traffic and meteorological monitoring devices to provide continuous and integrated assessments of the variation of near-road air pollutant concentrations and particle toxicity with changing traffic and environmental conditions, as well as distance from the road. Measurement results demonstrated the temporal and spatial impact of traffic emissions on near-road air quality. The distribution of mobile source emitted gas and particulate pollutants under all wind and traffic conditions indicated a higher proportion of elevated concentrations near the road, suggesting elevated exposures for populations spending significant amounts of time in this microenvironment. Diurnal variations in pollutant concentrations also demonstrated the impact of traffic activity and meteorology on near-road air quality. Time-resolved measurements of multiple pollutants demonstrated that traffic emissions produced a complex mixture of criteria and air toxic pollutants in this microenvironment. These results provide a foundation for future assessments of these data to identify the relationship of traffic activity and meteorology on air quality concentrations and population exposures.     

Effects of air quality on foliar injury, growth, yield, and quality of muskmelon

An evaluation of the effects of ambient ozone (O3) on muskmelon was conducted with the use of open-top chambers (OTCs). 'Superstar' muskmelons grown in charcoal-filtered (CF) chambers compared to those grown in nonfiltered (NF) chambers showed significant differences in the severity of visible foliar O3 injury. Furthermore, plants grown in NF conditions had significantly less (21.3%) marketable fruit weight and fewer (20.9%) marketable fruit number than those from CF chambers. No differences were found in early biomass production, leaf area, or number of nodes after 3 weeks of exposure to treatment conditions. Ambient O3 did not affect soluble solids content of mature fresh fruit nor foliage fresh weight at final harvest. Results indicate that ambient concentrations of O3 in southwestern Indiana caused significant foliar injury and yield loss to muskmelons.     

Urban air quality

Since 1950 the world population has more than doubled, and the global number of cars has increased by a factor of 10. In the same period the fraction of people living in urban areas has increased by a factor of 4. In year 2000 this will amount to nearly half of the world population. About 20 urban regions will each have populations above 10 million people.Seen over longer periods, pollution in major cities tends to increase during the built up phase, they pass through a maximum and are then again reduced, as abatement strategies are developed. In the industrialised western world urban air pollution is in some respects in the last stage with effectively reduced levels of sulphur dioxide and soot. In recent decades however, the increasing traffic has switched the attention to nitrogen oxides, organic compounds and small particles. In some cities photochemical air pollution is an important urban problem, but in the northern part of Europe it is a large-scale phenomenon, with ozone levels in urban streets being normally lower than in rural areas. Cities in Eastern Europe have been (and in many cases still are) heavily polluted. After the recent political upheaval, followed by a temporary recession and a subsequent introduction of new technologies, the situation appears to improve. However, the rising number of private cars is an emerging problem. In most developing countries the rapid urbanisation has so far resulted in uncontrolled growth and deteriorating environment. Air pollution levels are here still rising on many fronts.Apart from being sources of local air pollution, urban activities are significant contributors to transboundary pollution and to the rising global concentrations of greenhouse gasses. Attempts to solve urban problems by introducing cleaner, more energy-efficient technologies will generally have a beneficial impact on these large-scale problems. Attempts based on city planning with a spreading of the activities, on the other hand, may generate more traffic and may thus have the opposite effect.     

Effect of climate change on air quality

Air quality is strongly dependent on weather and is therefore sensitive to climate change. Recent studies have provided estimates of this climate effect through correlations of air quality with meteorological variables, perturbation analyses in chemical transport models (CTMs), and CTM simulations driven by general circulation model (GCM) simulations of 21st-century climate change. We review these different approaches and their results. The future climate is expected to be more stagnant, due to a weaker global circulation and a decreasing frequency of mid-latitude cyclones. The observed correlation between surface ozone and temperature in polluted regions points to a detrimental effect of warming. Coupled GCM–CTM studies find that climate change alone will increase summertime surface ozone in polluted regions by 1–10 ppb over the coming decades, with the largest effects in urban areas and during pollution episodes. This climate penalty means that stronger emission controls will be needed to meet a given air quality standard. Higher water vapor in the future climate is expected to decrease the ozone background, so that pollution and background ozone have opposite sensitivities to climate change. The effect of climate change on particulate matter (PM) is more complicated and uncertain than for ozone. Precipitation frequency and mixing depth are important driving factors but projections for these variables are often unreliable. GCM–CTM studies find that climate change will affect PM concentrations in polluted environments by ±0.1–1 μg m^?3 over the coming decades. Wildfires fueled by climate change could become an increasingly important PM source. Major issues that should be addressed in future research include the ability of GCMs to simulate regional air pollution meteorology and its sensitivity to climate change, the response of natural emissions to climate change, and the atmospheric chemistry of isoprene. Research needs to be undertaken on the effect of climate change on mercury, particularly in view of the potential for a large increase in mercury soil emissions driven by increased respiration in boreal ecosystems.     

Floristic summary of plant species in the air pollution literature

A floristic summary and analysis was performed on a list of the plant species that have been studied for the effects of gaseous and chemical air pollutants on vegetation in order to compare the species with the flora of North America north of Mexico. The scientific names of 2081 vascular plant species were extracted from almost 4000 journal articles stored in two large literature databases on the effects of air pollutants on plants. Three quarters of the plant species studied occur in North America, but this was only 7% of the total North American flora. Sixteen percent and 56% of all North American genera and families have been studied. The most studied genus is Pinus with 70% of the North American species studied, and the most studied family is the grass family, with 12% of the species studied. Although Pinus is ranked 86th in the North American flora, the grass family is ranked third, indicating that representation at the family level is better than at the genus level. All of the top ten families in North America are represented in the top 20 families in the air pollution effects literature, but only one genus (Lupinus) in the top ten genera in North America is represented in the top thirteen genera in the air pollution literature.     

Assessment of air quality benefits from national air pollution control policies in China. Part II: Evaluation of air quality predictions and air quality benefits assessment

Following the meteorological evaluation in Part I, this Part II paper presents the statistical evaluation of air quality predictions by the U.S. Environmental Protection Agency (U.S. EPA)’s Community Multi-Scale Air Quality (Models-3/CMAQ) model for the four simulated months in the base year 2005. The surface predictions were evaluated using the Air Pollution Index (API) data published by the China Ministry of Environmental Protection (MEP) for 31 capital cities and daily fine particulate matter (PM_2.5, particles with aerodiameter less than or equal to 2.5 μm) observations of an individual site in Tsinghua University (THU). To overcome the shortage in surface observations, satellite data are used to assess the column predictions including tropospheric nitrogen dioxide (NO₂) column abundance and aerosol optical depth (AOD). The result shows that CMAQ gives reasonably good predictions for the air quality.The air quality improvement that would result from the targeted sulfur dioxide (SO₂) and nitrogen oxides (NO_x) emission controls in China were assessed for the objective year 2010. The results show that the emission controls can lead to significant air quality benefits. SO₂ concentrations in highly polluted areas of East China in 2010 are estimated to be decreased by 30–60% compared to the levels in the 2010 Business-As-Usual (BAU) case. The annual PM_2.5 can also decline by 3–15 μg m^?3 (4–25%) due to the lower SO₂ and sulfate concentrations. If similar controls are implemented for NO_x emissions, NO_x concentrations are estimated to decrease by 30–60% as compared with the 2010 BAU scenario. The annual mean PM_2.5 concentrations will also decline by 2–14 μg m^?3 (3–12%). In addition, the number of ozone (O₃) non-attainment areas in the northern China is projected to be much lower, with the maximum 1-h average O₃ concentrations in the summer reduced by 8–30 ppb.     

Association between air quality and quality of life

Air quality—or its converse, air pollution—is a significant risk factor for human health. Recent studies have reported association between air pollution and human health. There are numerous diseases that may be caused by air pollution such as respiratory infection, lung cancer, cardiovascular disease, chronic obstructive pulmonary disease, and asthma. In this study, the relationship between air quality and quality of life was examined by using canonical correlation analysis. Data of this study was collected from 27 countries. WHO statistics were used as the main source of quality of life data set (Y variables set). European Environment Agency statistics and (for outdoor air-PM10) WHO statistics were used as the main source of air quality data set (X variables set). It is found that there are significant positive correlation between air quality and quality of life.     

Comment on regression analysis of air quality data

A simple numerical experiment demonstrates that the reduced major axis regression, rather than standard linear regression, is likely to be the method of choice for the regression analysis of air quality datasets. The case used for illustration is that of determining equivalence of alternative PM10 measurement systems.     

interpretation of air quality data with respect to the national ambient air quality standards

San Diego Gas &; Electric has developed a quality assurance program for continuous emission monitors (CEM). Extractive, rather than in situ, monitors were selected as a result of an in-house evaluation program. Two extractive systems have been certified and a good operating and maintenance record has been established on these systems. A successful program requires the involvement and support of all affected personnel. It is desirable to have one or two key personnel coordinate the development of the program. It is also highly desirable to have good in-house source testing capabilities.     

Evaluation of air quality zone classification methods based on ambient air concentration exposure

Air quality zones are used by regulatory authorities to implement ambient air standards in order to protect human health. Air quality measurements at discrete air monitoring stations are critical tools to determine whether an air quality zone complies with local air quality standards or is noncompliant. This study presents a novel approach for evaluation of air quality zone classification methods by breaking the concentration distribution of a pollutant measured at an air monitoring station into compliance and exceedance probability density functions (PDFs) and then using Monte Carlo analysis with the Central Limit Theorem to estimate long-term exposure. The purpose of this paper is to compare the risk associated with selecting one ambient air classification approach over another by testing the possible exposure an individual living within a zone may face. The chronic daily intake (CDI) is utilized to compare different pollutant exposures over the classification duration of 3 years between two classification methods. Historical data collected from air monitoring stations in Kuwait are used to build representative models of 1-hr NO₂ and 8-hr O₃ within a zone that meets the compliance requirements of each method. The first method, the “3 Strike” method, is a conservative approach based on a winner-take-all approach common with most compliance classification methods, while the second, the 99% Rule method, allows for more robust analyses and incorporates long-term trends. A Monte Carlo analysis is used to model the CDI for each pollutant and each method with the zone at a single station and with multiple stations. The model assumes that the zone is already in compliance with air quality standards over the 3 years under the different classification methodologies. The model shows that while the CDI of the two methods differs by 2.7% over the exposure period for the single station case, the large number of samples taken over the duration period impacts the sensitivity of the statistical tests, causing the null hypothesis to fail. Local air quality managers can use either methodology to classify the compliance of an air zone, but must accept that the 99% Rule method may cause exposures that are statistically more significant than the 3 Strike method.

Implications: A novel method using the Central Limit Theorem and Monte Carlo analysis is used to directly compare different air standard compliance classification methods by estimating the chronic daily intake of pollutants. This method allows air quality managers to rapidly see how individual classification methods may impact individual population groups, as well as to evaluate different pollutants based on dosage and exposure when complete health impacts are not known.     

Studies of air quality predictors based on neural networks

In recent years, urban air pollution has emerged as an acute problem because of its negative effect on health and living conditions. Regional air quality problems, in general, are linked to violations of specified air quality standards. The current study aims to find neural network based air quality predictors, which can work with a limited number of datasets and are robust enough to handle data with noise and errors. A number of available variations of neural network models, such as the Recurrent Network Model (RNM), the Change Point Detection Model with RNM (CPDM), the Sequential Network Construction Model (SNCM), the Self Organising Feature Model (SOFM), and the Moving Window Model (MWM), were implemented using MATLAB software for predicting air quality. Developed models were run to simulate and forecast based on the annual average data for 15 years from 1985 to 1999 for seven parameters, viz. VOC, NO_x, CO, SO₂, PM₁₀, PM_2.5 and NH₃ for one county of California, USA. The models were fitted with first nine years of data to predict data for remaining six years. The models, in general, could predict air quality patterns with modest accuracy. However, the SOFM model performed extremely well in comparison with the other models for predicting long-term (annual) data.     

Impacts of Russian biomass burning on UK air quality

Unusually high levels of PM₁₀ were observed in the UK in May 2006 and September 2002. This paper investigates the possible contribution of long-range transport of smoke from widespread agricultural burning and forest fires in western Russia to these air pollution episodes. The Lagrangian dispersion model NAME is run in both forwards and backwards modes to determine the transport and sources of the polluted air masses for the two incidents. Comparison of the model results to satellite data and ground observations from across Europe demonstrates good agreement for both the timing and magnitude of the episodes and suggests that fires in western Russia were the primary cause of both incidents. Secondary contributions to the 2006 episode may have come from European anthropogenic pollution and pollen released in northern Europe. The occurrence and timing of both pollution episodes were strongly controlled by the meteorological situation at the time. Scaling of model results to observations suggests that 0.5–0.7 Mtonnes of biomass per day could have been burnt during periods when winds reaching the UK were from the east. The newly reported 2006 episode means that Russian fires have affected UK air quality at least twice since 2000 and it is suggested that, without changes in current practice, such events are likely to occur again in the future with implications for UK and European air quality.