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.     

Alternate approaches for assessing impacts of oil sands development on air quality: A case study using the First Nation Community of Fort McKay

Previous analyses of continuously measured compounds in Fort McKay, an indigenous community in the Athabasca Oil Sands, have detected increasing concentrations of nitrogen dioxide (NO₂) and total hydrocarbons (THC), but not of sulfur dioxide (SO₂), ozone (O₃), total reduced sulfur compounds (TRS), or particulate matter (aerodynamic diameter <2.5 μm; PM_2.5). Yet the community frequently experiences odors, dust, and reduced air quality. The authors used Fort McKay’s continuously monitored air quality data (1998–2014) as a case study to assess techniques for air quality analysis that make no assumptions regarding type of change. Linear trend analysis detected increasing concentrations of higher percentiles of NO₂, nitric oxide (NO), and nitrogen oxides (NO_x), and THC. However, comparisons of all compounds between an early industrial expansion period (1998–2001) and current day (2011–2014) show that concentrations of NO₂, SO₂, THC, TRS, and PM_2.5 have significantly increased, whereas concentrations of O₃ are significantly lower. An assessment of the frequency and duration of periods when concentrations of each compound were above a variety of thresholds indicated that the frequency of air quality events is increasing for NO₂ and THC. Assessment of change over time with odds ratios of the 25th, 50th, 75th, and 90th percentile concentrations for each compound compared with an estimate of natural background variability showed that concentrations of TRS, SO₂, and THC are dynamic, higher than background, and changes are nonlinear and nonmonotonic. An assessment of concentrations as a function of wind direction showed a clear and generally increasing influence of industry on air quality. This work shows that evaluating air quality without assumptions of linearity reveals dynamic changes in air quality in Fort McKay, and that it is increasingly being affected by oil sands operations.

Implications: Understanding the nature and types of air quality changes occurring in a community or region is essential for the development of appropriate air quality management policies. Time-series trending of air quality data is a common tool for assessing air quality changes and is often used to assess the effectiveness of current emission management programs. The use of this tool, in the context of oil sands development, has significant limitations, and alternate air quality change analysis approaches need to be applied to ensure that the impact of this development on air quality is fully understood so that appropriate emission management actions can be taken.     

Wildfire and prescribed burning impacts on air quality in the United States

ABSTRACT

Air quality impacts from wildfires have been dramatic in recent years, with millions of people exposed to elevated and sometimes hazardous fine particulate matter (PM _2.5 ) concentrations for extended periods. Fires emit particulate matter (PM) and gaseous compounds that can negatively impact human health and reduce visibility. While the overall trend in U.S. air quality has been improving for decades, largely due to implementation of the Clean Air Act, seasonal wildfires threaten to undo this in some regions of the United States. Our understanding of the health effects of smoke is growing with regard to respiratory and cardiovascular consequences and mortality. The costs of these health outcomes can exceed the billions already spent on wildfire suppression. In this critical review, we examine each of the processes that influence wildland fires and the effects of fires, including the natural role of wildland fire, forest management, ignitions, emissions, transport, chemistry, and human health impacts. We highlight key data gaps and examine the complexity and scope and scale of fire occurrence, estimated emissions, and resulting effects on regional air quality across the United States. The goal is to clarify which areas are well understood and which need more study. We conclude with a set of recommendations for future research.     

北京市燃煤的空气质量影响及其控制研究

建立了2005年北京市燃煤污染源排放清单,利用MM5-CMAQ模型计算了各区县各行业燃煤对北京市空气质量的影响。研究表明,2005年1月北京市燃煤源对各监测站点SO_2浓度的贡献在70%以上,对PM_(10)和NO_x浓度的贡献约为20%～40%和10%～30%;7月本地燃煤源对SO_2浓度的贡献在40%～50%左右。1月采暖锅炉对空气质量影响最大,占50%～70%;7月电厂的影响最大。依据北京市奥运空气质量保障方案以及十一五期间能源规划,建立了2010年燃煤污染源大气排放的规划情景,并模拟了各规划措施对大气质量的改善效果。通过实施电厂脱硫脱硝除尘、炼焦工业停产、钢铁行业和水泥行业搬迁减产、供热锅炉改造、平房用煤改造等措施,与2005年相比,SO_2平均浓度下降30%左右,NO_x和PM_(10)浓度的下降幅度15%。     

Changes in extreme events and the potential impacts on human health

Extreme weather and climate-related events affect human health by causing death, injury, and illness, as well as having large socioeconomic impacts. Climate change has caused changes in extreme event frequency, intensity, and geographic distribution, and will continue to be a driver for change in the future. Some of these events include heat waves, droughts, wildfires, dust storms, flooding rains, coastal flooding, storm surges, and hurricanes. The pathways connecting extreme events to health outcomes and economic losses can be diverse and complex. The difficulty in predicting these relationships comes from the local societal and environmental factors that affect disease burden. More information is needed about the impacts of climate change on public health and economies to effectively plan for and adapt to climate change. This paper describes some of the ways extreme events are changing and provides examples of the potential impacts on human health and infrastructure. It also identifies key research gaps to be addressed to improve the resilience of public health to extreme events in the future.

Implications: Extreme weather and climate events affect human health by causing death, injury, and illness, as well as having large socioeconomic impacts. Climate change has caused changes in extreme event frequency, intensity, and geographic distribution, and will continue to be a driver for change in the future. Some of these events include heat waves, droughts, wildfires, flooding rains, coastal flooding, surges, and hurricanes. The pathways connecting extreme events to health outcomes and economic losses can be diverse and complex. The difficulty in predicting these relationships comes from the local societal and environmental factors that affect disease burden.     

Environmental impacts,human health,and energy consumption of nitrogen management for maize production in subtropical region

Environmental Science and Pollution Research - Over-application of fertilizers could not improve crop yield and agronomic efficiency, but result in increasing nitrogen (N) surplus and adverse...     

The effects of congestions tax on air quality and health

The “Stockholm Trial” involved a road pricing system to improve the air quality and reduce traffic congestion. The test period of the trial was January 3–July 31, 2006. Vehicles travelling into and out of the charge cordon were charged for every passage during weekdays. The amount due varied during the day and was highest during rush hours (20 SEK = 2.2 EUR, maximum 60 SEK per day). Based on measured and modelled changes in road traffic it was estimated that this system resulted in a 15% reduction in total road use within the charged cordon. Total traffic emissions in this area of NO_x and PM10 fell by 8.5% and 13%, respectively. Air quality dispersion modelling was applied to assess the effect of the emission reductions on ambient concentrations and population exposure. For the situations with and without the trial, meteorological conditions and other emissions than from road traffic were kept the same. The calculations show that, with a permanent congestion tax system like the Stockholm Trial, the annual average NO_x concentrations would be lower by up to 12% along the most densely trafficked streets. PM10 concentrations would be up to 7% lower. The limit values for both PM10 and NO₂ would still be exceeded along the most densely trafficked streets. The total population exposure of NO_x in Greater Stockholm (35 × 35 km with 1.44 million people) is estimated to decrease with a rather modest 0.23 μg m^?3. However, based on a long-term epidemiological study, that found an increased mortality risk of 8% per 10 μg m^?3 NO_x, it is estimated that 27 premature deaths would be avoided every year. According to life-table analysis this would correspond to 206 years of life gained over 10 years per 100 000 people following the trial if the effects on exposures would persist. The effect on mortality is attributed to road traffic emissions (likely vehicle exhaust particles); NO_x is merely regarded as an indicator of traffic exposure. This is only the tip of the ice-berg since reductions are expected in both respiratory and cardiovascular morbidity. This study demonstrates the importance of not only assessing the effects on air quality limit values, but also to make quantitative estimates of health impacts, in order to justify actions to reduce air pollution.     

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.     

Testing DayCent and DNDC model simulations of N2O fluxes and assessing the impacts of climate change on the gas flux and biomass production from a humid pasture

Simulation models are one of the approaches used to investigate greenhouse gas emissions and potential effects of global warming on terrestrial ecosystems. DayCent which is the daily time-step version of the CENTURY biogeochemical model, and DNDC (the DeNitrification–DeComposition model) were tested against observed nitrous oxide flux data from a field experiment on cut and extensively grazed pasture located at the Teagasc Oak Park Research Centre, Co. Carlow, Ireland. The soil was classified as a free draining sandy clay loam soil with a pH of 7.3 and a mean organic carbon and nitrogen content at 0–20 cm of 38 and 4.4 g kg^?1 dry soil, respectively. The aims of this study were to validate DayCent and DNDC models for estimating N₂O emissions from fertilized humid pasture, and to investigate the impacts of future climate change on N₂O fluxes and biomass production. Measurements of N₂O flux were carried out from November 2003 to November 2004 using static chambers. Three climate scenarios, a baseline of measured climatic data from the weather station at Carlow, and high and low temperature sensitivity scenarios predicted by the Community Climate Change Consortium For Ireland (C4I) based on the Hadley Centre Global Climate Model (HadCM₃) and the Intergovernment Panel on Climate Change (IPCC) A1B emission scenario were investigated. DayCent predicted cumulative N₂O flux and biomass production under fertilized grass with relative deviations of +38% and (?23%) from the measured, respectively. However, DayCent performs poorly under the control plots, with flux relative deviation of (?57%) from the measured. Comparison between simulated and measured flux suggests that both DayCent model’s response to N fertilizer and simulated background flux need to be adjusted. DNDC overestimated the measured flux with relative deviations of +132 and +258% due to overestimation of the effects of SOC. DayCent, though requiring some calibration for Irish conditions, simulated N₂O fluxes more consistently than did DNDC. We used DayCent to estimate future fluxes of N₂O from this field. No significant differences were found between cumulative N₂O flux under climate change and baseline conditions. However, above-ground grass biomass was significantly increased from the baseline of 33 t ha^?1 to 45 (+34%) and 50 (+48%) t dry matter ha^?1 for the low and high temperature sensitivity scenario respectively. The increase in above-ground grass biomass was mainly due to the overall effects of high precipitation, temperature and CO₂ concentration. Our results indicate that because of high N demand by the vigorously growing grass, cumulative N₂O flux is not projected to increase significantly under climate change, unless more N is applied. This was observed for both the high and low temperature sensitivity scenarios.     

Strategic environmental assessment of mining activities: A methodology for quantification of cumulative impacts on the air quality

Environmental impact assessments in Brazil have usually focused solely on project-related issues without considering the regional context. Although required by current environmental legislation, cumulative impact assessments have not been included in the overall environmental assessment of projects. However, in recent Strategic Environmental Assessment (SEA) studies of policies, plans, and programs undertaken on a voluntary basis in support of the decision-making process, this kind of assessment has been performed especially with respect to air quality. This paper presents the application of a methodology for the quantification of cumulative impacts on air quality under high uncertainty caused by various mining activities in a single region that is recommended for SEA studies. In this way, the methodology presented here is suitable for areas lacking detailed modeling information. The developed approach uses a relatively simplified mathematical model, lowering information gathering costs and requiring little processing time. The application of the methodology is illustrated in the case of a SEA of the Corumbá Mining and Industrial Complex Development Program. Despite the lack of data needed for a minimum characterization of conditions of the area surrounding the region modeled, the quantification of impact cumulativeness on air quality has played an important role in the context of the SEA.     

The use of air quality forecasts to assess impacts of air pollution on crops: Methodology and case study

It has been reported that ambient ozone (O₃), either alone or in concurrence with acid rain precursors, accounts for up to 90% of US crop losses resulting from exposure to all major air pollutants. Crop damage due to O₃ exposure is of particular concern as ambient O₃ concentrations remain high in many major food-producing regions. Assessing O₃ damage to crops is challenging due to the difficulties in determining the reduction in crop yield that results from exposure to surface O₃, for which monitors are limited and mostly deployed in non-rural areas. This work explores the potential benefits of using operational air quality forecast (AQF) data to estimate rural O₃ exposure. Using the results from the first nationwide AQF as a case study, we demonstrate how the O₃ data provided by AQF can be combined with concurrent crop information to assess O₃ damages to soybeans in the United States. We estimate that exposure to ambient O₃ reduces the US soybean production by 10% in 2005.     

Assessment of the emissions and air quality impacts of biomass and biogas use in California

It is estimated that there is sufficient in-state “technically” recoverable biomass to support nearly 4000 MW of bioelectricity generation capacity. This study assesses the emissions of greenhouse gases and air pollutants and resulting air quality impacts of new and existing bioenergy capacity throughout the state of California, focusing on feedstocks and advanced technologies utilizing biomass resources predominant in each region. The options for bioresources include the production of bioelectricity and renewable natural gas (NG). Emissions of criteria pollutants and greenhouse gases are quantified for a set of scenarios that span the emission factors for power generation and the use of renewable natural gas for vehicle fueling. Emissions are input to the Community Multiscale Air Quality (CMAQ) model to predict regional and statewide temporal air quality impacts from the biopower scenarios. With current technology and at the emission levels of current installations, maximum bioelectricity production could increase nitrogen oxide (NO_x) emissions by 10% in 2020, which would cause increases in ozone and particulate matter concentrations in large areas of California. Technology upgrades would achieve the lowest criteria pollutant emissions. Conversion of biomass to compressed NG (CNG) for vehicles would achieve comparable emission reductions of criteria pollutants and minimize emissions of greenhouse gases (GHG). Air quality modeling of biomass scenarios suggest that applying technological changes and emission controls would minimize the air quality impacts of bioelectricity generation. And a shift from bioelectricity production to CNG production for vehicles would reduce air quality impacts further. From a co-benefits standpoint, CNG production for vehicles appears to provide the best benefits in terms of GHG emissions and air quality.

Implications:?This investigation provides a consistent analysis of air quality impacts and greenhouse gas emissions for scenarios examining increased biomass use. Further work involving economic assessment, seasonal or annual emissions and air quality modeling, and potential exposure analysis would help inform policy makers and industry with respect to further development and direction of biomass policy and bioenergy technology alternatives needed to meet energy and environmental goals in California.     

A laboratory study of microalgae-based ammonia gas mitigation with potential application for improving air quality in animal production operations

Ammonia gas emission is a major concern in concentrated animal production operations. It not only reduces the manure value as fertilizer due to nitrogen loss, but also has considerable environmental consequences for both animals and ecosystem. In this work, a microalgae culture system was developed as an ammonia gas bioscrubber to reduce ammonia gas emission. The green algae Scenedesmus dimorphus was grown in a flat-panel photobioreactor aerated with ammonia-laden air. A continuous culture was performed at different operational conditions including dilution rate (D = 0.05, 0.1, 0.2, and 0.3 day^?1), ammonia gas loading rate (9.4, 19.3, 28.9, 39.9, 55.6 mg/L-day), and medium pH (5, 6, 7, and 8). The alga culture at 0.1 day^?1 dilution rate, 39.9 mg/L-day ammonia gas loading rate, and pH 7 resulted in the highest cell density and biomass productivity. In order to provide a wide spectrum evaluation of the algae-based ammonia mitigation system, four parameters were determined, including ammonia removal rate, overall ammonia gas removal efficiency, cellular ammonia consumption rate, and cell yield based on ammonia input. Depending on the operational conditions used, the maximum values of those four evaluative parameters were 50.92 ± 2.91 mg/L-day of ammonia removal rate, 94.90 ± 1.87% of ammonia removal efficiency, 0.0597 ± 0.0024 g NH₃/g cell-day of cellular ammonia consumption rate, and 19.40 ± 2.52 g cell/g NH₃ of cell yield based on ammonia. It was also found that the majority of nitrogen in the ammonia gas was assimilated by the algal cells. At D = 0.1 day^?1, 39.9 mg/L-day of ammonia gas loading rate and pH 7, algal biomass assimilated 98.6% of nitrogen contained in the ammonia gas input, with less than 5% of inlet ammonia gas was exhausted after the algal treatment.

Implications: This study demonstrated the effectiveness of using microalgae for mitigating ammonia gas emission from animal production operations. The results enabled us to better understand the mechanisms of ammonia assimilation by microalgae, the engineering design parameters for the process scale up, and the economic viability of the system. Eventually, it will lead to a novel, alternative method for mitigating ammonia gas emission from concentrated animal operations while producing biomass as high-quality feed ingredient.     

Confronting environmental pressure,environmental quality and human health impact indicators of priority air emissions

This paper evaluates the ranking of 21 priority air pollutants with three indicator schemes: environmental pressure indicator (EPI), environmental quality indicator (EQI), and human health effect indicator (HEI). The EPI and EQI compare the emissions and concentrations with the target emissions and target concentrations, respectively. The HEI comprehends the steps from cause (i.e. national emissions) to effect (i.e. human health effects), and is the total human health burden, expressed in Disability Adjusted Life Years per year of exposure (DALYs year^?1). We estimated a health burden in the Netherlands of 41 × 10³ DALYs year^?1 caused by Dutch air emissions of PM10 and its precursors in the year 2003. The burden due to 17 carcinogenic substances emitted to air, was much lower (140 DALYs year^?1). In contrast, when the same substances were evaluated regarding environmental pressure and environmental quality, carbon tetrachloride (pressure) and benzo[a]pyrene (quality) were of highest importance, whereas the importance of PM10 was substantially lower. This result is remarkable, because for the majority of substances evaluated, the target concentrations and target emissions are based on preventing human health damage. The differences in relevance are explained by the different weighting of interests in the indicators. The HEI is based on concentration–response relations, whereas the EPI and EQI also depend on other, policy-based, principles and on technical feasibility. Therefore, to effectively prioritize emission reduction measures in policy-making, substances should not only be evaluated as to whether emission targets and environmental quality targets are reached, but they should be evaluated regarding their human health impact as well. In this context, the HEI is a suitable indicator to evaluate the human health impact.     

Impact of emissions from natural gas production facilities on ambient air quality in the Barnett Shale area: A pilot study

Rapid and extensive development of shale gas resources in the Barnett Shale region of Texas in recent years has created concerns about potential environmental impacts on water and air quality. The purpose of this study was to provide a better understanding of the potential contributions of emissions from gas production operations to population exposure to air toxics in the Barnett Shale region. This goal was approached using a combination of chemical characterization of the volatile organic compound (VOC) emissions from active wells, saturation monitoring for gaseous and particulate pollutants in a residential community located near active gas/oil extraction and processing facilities, source apportionment of VOCs measured in the community using the Chemical Mass Balance (CMB) receptor model, and direct measurements of the pollutant gradient downwind of a gas well with high VOC emissions. Overall, the study results indicate that air quality impacts due to individual gas wells and compressor stations are not likely to be discernible beyond a distance of approximately 100 m in the downwind direction. However, source apportionment results indicate a significant contribution to regional VOCs from gas production sources, particularly for lower-molecular-weight alkanes (<C6). Although measured ambient VOC concentrations were well below health-based safe exposure levels, the existence of urban-level mean concentrations of benzene and other mobile source air toxics combined with soot to total carbon ratios that were high for an area with little residential or commercial development may be indicative of the impact of increased heavy-duty vehicle traffic related to gas production

ImplicationsRapid and extensive development of shale gas resources in recent years has created concerns about potential environmental impacts on water and air quality. This study focused on directly measuring the ambient air pollutant levels occurring at residential properties located near natural gas extraction and processing facilities, and estimating the relative contributions from gas production and motor vehicle emissions to ambient VOC concentrations. Although only a small-scale case study, the results may be useful for guidance in planning future ambient air quality studies and human exposure estimates in areas of intensive shale gas production.     

Pesticide and agro-ecological transition: assessing the environmental and human impacts of pesticides and limiting their use

Environmental Science and Pollution Research -     

Simulations of the impacts of building height layout on air quality in natural-ventilated rooms around street canyons

Numerical simulations were conducted to investigate the effects of building height ratio (i.e., HR, the height ratio of the upstream building to the downstream building) on the air quality in buildings beside street canyons, and both regular and staggered canyons were considered for the simulations. The results show that the building height ratio affects not only the ventilation fluxes of the rooms in the downstream building but also the pollutant concentrations around the building. The parameter, outdoor effective source intensity of a room, is then proposed to calculate the amount of vehicular pollutants that enters into building rooms. Smaller value of this parameter indicates less pollutant enters the room. The numerical results reveal that HRs from 2/7 to 7/2 are the favorable height ratios for the regular canyons, as they obtain smaller values than the other cases. While HR values of 5/7, 7/7, and 7/5 are appropriate for staggered canyons. In addition, in terms of improving indoor air quality by natural ventilation, the staggered canyons with favorable HR are better than those of the regular canyons.     

The impacts of combustion emissions on air quality and climate – From coal to biofuels and beyond

Combustion processes have inherent characteristics that lead to the release in the environment of both gaseous and particulate pollutants that have primary and secondary impacts on air quality, human health, and climate. The emissions from the combustion of fossil fuels and biofuels and their atmospheric impacts are reviewed here with attention given to the emissions of the currently regulated pollutant gasses, primary aerosols, and secondary aerosol precursors as well as the emissions of non-regulated pollutants. Fuels ranging from coal, petroleum, liquefied petroleum gas (LPG), natural gas, as well as the biofuels; ethanol, methanol, methyl tertiary-butyl ether (MTBE), ethyl tertiary-butyl ether (ETBE), and biodiesel, are discussed in terms of the known air quality and climate impacts of the currently regulated pollutants. The potential importance of the non-regulated emissions of both gasses and aerosols in air quality issues and climate is also discussed with principal focus on aldehydes and other oxygenated organics, polycyclic aromatic hydrocarbons (PAHs), and nitrated organics. The connection between air quality and climate change is also addressed with attention given to ozone and aerosols as potentially important greenhouse species.