Formaldehyde (HCHO) As a Hazardous Air Pollutant: Mapping Surface Air Concentrations from Satellite and Inferring Cancer Risks in the United States.

Formaldehyde (HCHO) is the most important carcinogen in outdoor air among the 187 hazardous air pollutants (HAPs) identified by the U.S. Environmental Protection Agency (EPA), not including ozone and particulate matter. However, surface observations of HCHO are sparse and the EPA monitoring network could be prone to positive interferences. Here we use 2005-2016 summertime HCHO column data from the OMI satellite instrument, validated with high-quality aircraft data and oversampled on a 5 × 5 km2 grid, to map surface air HCHO concentrations across the contiguous U.S. OMI-derived summertime HCHO values are converted to annual averages using the GEOS-Chem chemical transport model. Results are in good agreement with high-quality summertime observations from urban sites (-2% bias, r = 0.95) but a factor of 1.9 lower than annual means from the EPA network. We thus estimate that up to 6600-12 500 people in the U.S. will develop cancer over their lifetimes by exposure to outdoor HCHO. The main HCHO source in the U.S. is atmospheric oxidation of biogenic isoprene, but the corresponding HCHO yield decreases as the concentration of nitrogen oxides (NOx ≡ NO + NO2) decreases. A GEOS-Chem sensitivity simulation indicates that HCHO levels would decrease by 20-30% in the absence of U.S. anthropogenic NOx emissions. Thus, NOx emission controls to improve ozone air quality have a significant cobenefit in reducing HCHO-related cancer risks.

Hybrid Modeling Approach to Estimate Exposures of Hazardous Air Pollutants (HAPs) for the National Air Toxics Assessment (NATA).

A hybrid air quality model has been developed and applied to estimate annual concentrations of 40 hazardous air pollutants (HAPs) across the continental United States (CONUS) to support the 2011 calendar year National Air Toxics Assessment (NATA). By combining a chemical transport model (CTM) with a Gaussian dispersion model, both reactive and nonreactive HAPs are accommodated across local to regional spatial scales, through a multiplicative technique designed to improve mass conservation relative to previous additive methods. The broad scope of multiple pollutants capturing regional to local spatial scale patterns across a vast spatial domain is precedent setting within the air toxics community. The hybrid design exhibits improved performance relative to the stand alone CTM and dispersion model. However, model performance varies widely across pollutant categories and quantifiably definitive performance assessments are hampered by a limited observation base and challenged by the multiple physical and chemical attributes of HAPs. Formaldehyde and acetaldehyde are the dominant HAP concentration and cancer risk drivers, characterized by strong regional signals associated with naturally emitted carbonyl precursors enhanced in urban transport corridors with strong mobile source sector emissions. The multiple pollutant emission characteristics of combustion dominated source sectors creates largely similar concentration patterns across the majority of HAPs. However, reactive carbonyls exhibit significantly less spatial variability relative to nonreactive HAPs across the CONUS.

National review of ambient air toxics observations.

UNLABELLED: Ambient air observations of hazardous air pollutant (HAPs), also known as air toxics, derived from routine monitoring networks operated by states, local agencies, and tribes (SLTs), are analyzed to characterize national concentrations and risk across the nation for a representative subset of the 187 designated HAPs. Observations from the National Air Toxics Trend Sites (NATTS) network of 27 stations located in most major urban areas of the contiguous United States have provided a consistent record of HAPs that have been identified as posing the greatest risk since 2003 and have also captured similar concentration patterns of nearly 300 sites operated by SLTs. Relatively high concentration volatile organic compounds (VOCs) such as benzene, formaldehyde, and toluene exhibit the highest annual average concentration levels, typically ranging from 1 to 5 µg/m(3). Halogenated (except for methylene chloride) and semivolatile organic compounds (SVOCs) and metals exhibit concentrations typically 2-3 orders of magnitude lower. Formaldehyde is the highest national risk driver based on estimated cancer risk and, nationally, has not exhibited significant changes in concentration, likely associated with the large pool of natural isoprene and formaldehyde emissions. Benzene, toluene, ethylbenzene, and 1,3-butadiene are ubiquitous VOC HAPs with large mobile source contributions that continue to exhibit declining concentrations over the last decade. Common chlorinated organic compounds such as ethylene dichloride and methylene chloride exhibit increasing concentrations. The variety of physical and chemical attributes and measurement technologies across 187 HAPs result in a broad range of method detection limits (MDLs) and cancer risk thresholds that challenge confidence in risk results for low concentration HAPs with MDLs near or greater than risk thresholds. From a national monitoring network perspective, the ability of the HAPs observational database to characterize the multiple pollutant and spatial scale patterns influencing exposure is severely limited and positioned to benefit by leveraging a variety of emerging measurement technologies. IMPLICATIONS: Ambient air toxics observation networks have limited ability to characterize the broad suite of hazardous air pollutants (HAPs) that affect exposures across multiple spatial scales. While our networks are best suited to capture major urban-scale signals of ubiquitous volatile organic compound HAPs, incorporation of sensing technologies that address regional and local-scale exposures should be pursued to address major gaps in spatial resolution. Caution should be exercised in interpreting HAPs observations based on data proximity to minimum detection limit and risk thresholds.

Remote sensing of particulate pollution from space: have we reached the promised land?

The Critical Review of Hoff and Christopher, along with the discussants, provides an important perspective on the interface between satellite measurement science and air quality observations. A top-down picture of the usefulness of satellite observations in terms of air quality regulatory and technical support requirements can be summarized. The air quality requirements are (1) determination of compliance with the ambient air quality standards, (2) inference of human and ecosystem exposure, (3) identification of intra- and intercontinental events relevant to EE, (4) establishment of trends in ambient concentrations relevant to accountability, (5) regulatory and forecast model applications, and (6) extension of fundamental knowledge relevant to air quality. Each of these topics is important to air quality management, and each has detailed technical issues associated with spatial and temporal resolution, accuracy, and precision, etc. In any case, one can summarize the broad capabilities of measurement systems to address these requirements as listed in Table 1. From this rather superficial summary table, investigators should be encouraged to forward increased interaction between the various measurement communities and to facilitate the utility of a comprehensive portfolio of measurements and adjunct analyses for improved air quality applications. The Critical Review has done much to educate air quality scientists on the possibilities for using satellite remote sensing for various purposes. However, space scientists also need a better education on air quality science. Recently published reviews on PM air quality measurements are available that complement the Hoff-Christopher paper on this topic. The need for greater collaboration of air quality and space scientists is evident in an article published in the July issue of the journal. Al-Hamdan et al. provide an interesting and useful analysis of relationships between surface air quality and space-based satellite AOD to estimate human exposure. They obtain mostly urban PM data from EPA's Air Quality System (AQS), but they neglect the potentially more useful PM2.5 and chemical speciation data from the nonurban Interagency Monitoring of Protected Visual Environments (IMPROVE) and the Southeastern Aerosol Research and Characterization (SEARCH) networks. They correlate PM2.5 mass with optical depth, although visibility assessments show that light extinction is better represented by a weighted sum of PM2.5 sulfate, nitrate, organic carbon, elemental carbon, and soil dust. Their comparison of hourly measurements with filter measurements does not specify the source of the hourly values as TEOM or BAM. Spatial outliers for ground-level measurements are removed to improve the correlation of PM2.5 with AOD, although these "outliers" are probably real values that relate to human exposure or a nearby source effect. The point here is not to overly criticize a good publication that will be highly cited. The intent is to demonstrate the value of air quality and space scientists working together more closely on this topic. This is something the review authors alluded to in their review, but if, as they concluded, the "promised land" has not been reached, then perhaps it is an appropriate time for the atmospheric community to ask, "Can near-term satellite observations play a role in characterizing broad-based (outdoor) exposure to pollutants and consequently influence public health improvement?" and, if so, then, "What comprehensive, integrated system is needed if satellite observations are to be used together with ground-based observations and modeling to continue improving air quality management options?"

The national ambient air monitoring strategy: rethinking the role of national networks.

A current re-engineering of the United States routine ambient monitoring networks intended to improve the balance in addressing both regulatory and scientific objectives is addressed in this paper. Key attributes of these network modifications include the addition of collocated instruments to produce multiple pollutant characterizations across a range of representative urban and rural locations in a new network referred to as the National Core Monitoring Network (NCore). The NCore parameters include carbon monoxide (CO), sulfur dioxide (SO2), reactive nitrogen (NOy), ozone (O3), and ammonia (NH3) gases and the major fine particulate matter (PM2.5) aerosol components (ions, elemental and organic carbon fractions, and trace metals). The addition of trace gas instruments, deployed at existing chemical speciation sites and designed to capture concentrations well below levels of national air quality standards, is intended to support both long-term epidemiological studies and regional-scale air quality model evaluation. In addition to designing the multiple pollutant NCore network, steps were taken to assess the current networks on the basis of spatial coverage and redundancy criteria, and mechanisms were developed to facilitate incorporation of continuously operating particulate matter instruments.

Key scientific findings and policy- and health-relevant insights from the U.S. Environmental Protection Agency's Particulate Matter Supersites Program and related studies: an integration and synthesis of results.

In 1998, the U.S. Environmental Protection Agency (EPA) initiated a major air quality program known as the Particulate Matter (PM) Supersites Program. The Supersites Program was a multiyear, $27 million air quality monitoring program consisting of eight regional air quality projects located throughout the United States, each with differing atmospheric pollution conditions resulting from variations in source emissions and meteorology. The overall goal of the program was to elucidate source-receptor relationships and atmospheric processes leading to PM accumulation on urban and regional scales; thus providing the scientific underpinning for modeling and data analysis efforts to support State Implementation Plans and more effective risk management approaches for PM. The program had three main objectives: (1) conduct methods development and evaluation, (2) characterize ambient PM, and (3) support health effects and exposure research. This paper provides a synthesis of key scientific findings from the Supersites Program and related studies. EPA developed 16 science/policy-relevant questions in conjunction with state and other federal agencies, Regional Planning Organizations, and the private sector. These questions were addressed to the extent possible, even given the vast amount of new information available from the Supersites Program, in a series of papers published as a special issue of the Journal of Air & Waste Management Association (February 2008). This synthesis also includes discussions of: (1) initial Supersites Program support for air quality management efforts in specific locations throughout the United States; (2) selected policy-relevant insights, based on atmospheric sciences findings, useful to air quality managers and decision makers planning emissions management strategies to address current and future PM National Ambient Air Quality Standards (NAAQS) and network planning and implementation; (3) selected health-relevant insights interpreted from atmospheric sciences findings in light of future directions for health and exposure scientists planning studies of the effects of PM on human health; and (4) selected knowledge gaps to guide future research. Finally, given the scope and depth of research and findings from the Supersites Program, this paper provides a reference source so readers can glean a general understanding of the overall research conducted and its policy-relevant insights. Supporting details for the results presented are available through the cited references. An annotated table of contents allows readers to easily find specific subject matter within the text.

A FRAMEWORK FOR EVALUATING REGIONAL-SCALE NUMERICAL PHOTOCHEMICAL MODELING SYSTEMS.

This paper discusses the need for critically evaluating regional-scale (~200-2000 km) three-dimensional numerical photochemical air quality modeling systems to establish a model's credibility in simulating the spatio-temporal features embedded in the observations. Because of limitations of currently used approaches for evaluating regional air quality models, a framework for model evaluation is introduced here for determining the suitability of a modeling system for a given application, distinguishing the performance between different models through confidence-testing of model results, guiding model development, and analyzing the impacts of regulatory policy options. The framework identifies operational, diagnostic, dynamic, and probabilistic types of model evaluation. Operational evaluation techniques include statistical and graphical analyses aimed at determining whether model estimates are in agreement with the observations in an overall sense. Diagnostic evaluation focuses on process-oriented analyses to determine whether the individual processes and components of the model system are working correctly, both independently and in combination. Dynamic evaluation assesses the ability of the air quality model to simulate changes in air quality stemming from changes in source emissions and/or meteorology, the principal forces that drive the air quality model. Probabilistic evaluation attempts to assess the confidence that can be placed in model predictions using techniques such as ensemble modeling and Bayesian model averaging. The advantages of these types of model evaluation approaches are discussed in this paper.