Daniel S. Cohan

Convective injection and photochemical decay of peroxides in the tropical upper troposphere: Methyl iodide as a tracer of marine convection

The convective injection and subsequent fate of the peroxides H2O2 and CH3OOH in the upper troposphere is investigated using aircraft observations from the NASA Pacific Exploratory Mission-Tropics A (PEM-Tropics A) over the South Pacific up to 12 km altitude. Fresh convective outflow is identified by high CH3I concentrations; CH3I is an excellent tracer of marine convection because of its relatively uniform marine boundary layer concentration, relatively well-defined atmospheric lifetime against photolysis, and high sensitivity of measurement. We find that mixing ratios of CH3OOH in convective outflow at 8–12 km altitude are enhanced on average by a factor of 6 relative to background, while mixing ratios of H2O2 are enhanced by less than a factor of 2. The scavenging efficiency of H2O2 in the precipitation associated with deep convection is estimated to be 55–70%. Scavenging of CH3OOH is negligible. Photolysis of convected peroxides is a major source of the HOx radical family (OH + peroxy radicals) in convective outflow. The timescale for decay of the convective enhancement of peroxides in the upper troposphere is determined using CH3I as a chemical clock and is interpreted using photochemical model calculations. Decline of CH3OOH takes place on a timescale of a 1–2 days, but the resulting HOx converts to H2O2, so H2O2 mixing ratios show no decline for ∼5 days following a convective event. The perturbation to HOx at 8–12 km altitude from deep convective injection of peroxides decays on a timescale of 2–3 days for the PEM-Tropics A conditions.

Meta-analysis of the association between short-term exposure to ambient ozone and respiratory hospital admissions

Ozone is associated with health impacts including respiratory outcomes; however, results differ across studies. Meta-analysis is an increasingly important approach to synthesizing evidence across studies. We conducted meta-analysis of short-term ozone exposure and respiratory hospitalizations to evaluate variation across studies and explore some of the challenges in meta-analysis. We identified 136 estimates from 96 studies and investigated how estimates differed by age, ozone metric, season, lag, region, disease category, and hospitalization type. Overall results indicate associations between ozone and various types of respiratory hospitalizations; however, study characteristics affected risk estimates. Estimates were similar, but higher, for the elderly compared to all ages and for previous day exposure compared to same day exposure. Comparison across studies was hindered by variation in definitions of disease categories, as some (e.g., asthma) were identified through ≥3 different sets of ICD codes. Although not all analyses exhibited evidence of publication bias, adjustment for publication bias generally lowered overall estimates. Emergency hospitalizations for total respiratory disease increased 4.47% (95% interval 2.48, 6.50%) per 10ppb 24-hr ozone among the elderly without adjustment for publication bias and 2.97% (1.05, 4.94%) with adjustment. Comparison of multi-city study results and meta-analysis based on single-city studies further suggested publication bias.

Extension and evaluation of sensitivity analysis capabilities in a photochemical model

The decoupled direct method in three dimensions (DDM-3D) provides an efficient and accurate approach for probing the sensitivity of atmospheric pollutant concentrations to various changes in photochemical model inputs. The implementation of DDM-3D for the widely used Community Multiscale Air Quality (CMAQ) model was updated to account for recent changes in the base model and to include additional chemical mechanisms and advection schemes. The capabilities of CMAQ-DDM-3D were extended to enable execution using multiple processors in parallel and the computation of sensitivities to chemical reaction rate constants. The resulting direct sensitivity modeling system was tested for statistical agreement with the traditional difference method for calculating sensitivities, considering a summer episode in a domain covering the continental United States. Sensitivities to domain-wide and sector specific emissions, initial/boundary conditions, and chemical reaction rates were compared and found to be in good correlation for both primary and secondary air pollutants. The scalability of CMAQ-DDM-3D to the number of processors used in parallel was also examined. Sensitivity calculations were found to scale in a similar way to the base model, where the benefit to model runtime of adding more processors diminished for simulations that used more than eight processors.

Anthropogenic emissions of highly reactive volatile organic compounds in eastern Texas inferred from oversampling of satellite (OMI) measurements of HCHO columns

Satellite observations of formaldehyde (HCHO) columns provide top-down constraints on emissions of highly reactive volatile organic compounds (HRVOCs). This approach has been used previously in the US to estimate isoprene emissions from vegetation, but application to anthropogenic emissions has been stymied by lack of a discernable HCHO signal. Here we show that temporal oversampling of HCHO data from the Ozone Monitoring Instrument (OMI) for 2005–2008 enables detection of urban and industrial plumes in eastern Texas including Houston, Port Arthur, and Dallas/Fort Worth. By spatially integrating the HCHO enhancement in the Houston plume observed by OMI we estimate an anthropogenic HCHO source of 250±140 kmol h �1 . This implies that anthropogenic HRVOC emissions in Houston are 4.8±2.7 times higher than reported by the US Environmental Protection Agency inventory, and is consistent with field studies identifying large ethene and propene emissions from petrochemical industrial sources.

Uncertainty Analysis of Ozone Formation and Response to Emission Controls Using Higher-Order Sensitivities

Abstract Understanding ozone response to its precursor emissions is crucial for effective air quality management practices. This nonlinear response is usually simulated using chemical transport models, and the modeling results are affected by uncertainties in emissions inputs. In this study, a high ozone episode in the southeastern United States is simulated using the Community Multiscale Air Quality (CMAQ) model. Uncertainties in ozone formation and response to emissions controls due to uncertainties in emission rates are quantified using the Monte Carlo method. Instead of propagating emissions uncertainties through the original CMAQ, a reduced form of CMAQ is formulated using directly calculated first- and second-order sensitivities that capture the nonlinear ozone concentration-emission responses. This modification greatly reduces the associated computational cost. Quantified uncertainties in modeled ozone concentrations and responses to various emissions controls are much less than the uncertainties in emissions inputs. Average uncertainties in modeled ozone concentrations for the Atlanta area are less than 10% (as measured by the inferred coefficient of variance [ICOV]) even when emissions uncertainties are assumed to vary between a factor of 1.5 and 2. Uncertainties in the ozone responses generally decrease with increased emission controls. Average uncertainties (ICOV) in emission-normalized ozone responses range from 4 to 22%, with the smaller being associated with controlling of the relatively certain point nitrogen oxide (NOx) emissions and the larger resulting from controlling of the less certain mobile NOx emissions. These small uncertainties provide confidence in the model applications, such as in performance evaluation, attainment demonstration, and control strategy development.

Atmospheric methyl iodide at Cape Grim, Tasmania, from AGAGE observations

Atmospheric mixing ratios of methyl iodide (CH3I) and other methyl halides have been measured at Cape Grim, Tasmania (41°S, 145°E), since early 1998 as part of the Advanced Global Atmospheric Gases Experiment (AGAGE). This paper analyses about 1700 ambient air CH3I measurements from the 14-month period (March 1998–April 1999). Mixing ratios peaked during the summer, despite faster photolytic loss, suggesting local oceanic emissions were about 2.2–3.6 times stronger in summer than in winter. Back trajectories show that CH3I levels are strongly dependent on air mass origin, with highest mixing ratios in air from the Tasman Sea/Bass Strait region and lowest levels in air originating from the Southern Ocean at higher latitudes. CH3I mixing ratios were not well correlated with other methyl halides in unpolluted marine air. The large variations with season and air mass origin suggest that high frequency, continuous data from key locations will make a significant contribution to the understanding of sources and sinks of this important short-lived atmospheric species.

Single-Source Impact Analysis Using Three-Dimensional Air Quality Models

Abstract Isolating the effects of an individual emissions source on secondary air pollutants such as ozone and some components of particulate matter must incorporate complex nonlinear processes, be sensitive to small emissions perturbations, and account for impacts that may occur hundreds of kilometers away. The ability to evaluate these impacts is becoming increasingly important for efficient air quality management. Here, as part of a recent compliance enforcement action for a violation of the Clean Air Act and as an evaluation of ozone response to single-source emissions plumes, two three-dimensional regional photochemical air quality models are used to assess the impact on ozone from approximately 2000 to 3000 excess t/month of nitrogen oxides emitted from a single power plant in Ohio. Periods in May, July, and August are evaluated. Two sensitivity methods are applied: the “brute-force” (B-F) method and the decoupled direct method (DDM). Using DDM, maximum 1-hr averaged ozone concentrations are found to increase by up to 1.8, 1.3, and 2.2 ppbv during May, July, and August episodes, respectively, and concentration increases greater than 0.5 ppbv occur in Ohio, Pennsylvania, Maryland, New York, West Virginia, Virginia, and North and South Carolina. B-F results for the August episode show a maximum 1-hr averaged ozone concentration increase of 2.3 ppbv. Significant localized decreases are also simulated, with a maximum of 3.6 ppbv in Ohio during the August episode and decreases of 0.50 ppbv and greater in Ohio, Pennsylvania, Maryland, West Virginia, and Virginia. Maximum increases are compared with maximum decreases for the August period using second-order DDM and are found, in aggregate, to be greater in magnitude by 42%. When evaluated during hours when ozone concentrations exceed 0.060 ppm, the maximum increases in ozone are higher than decreases by 82%. The spatial extent of ozone increase in both cases is about triple that of reduction.

Contributions of inter- and intra-state emissions to ozone over Dallas-Fort Worth, Texas

Simulation of CMAQ with the high-order direct decoupled method (HDDM) for two 2005 episodes was used to assess the impacts of local emissions and regional transport on ozone concentrations in the Dallas-Fort Worth (DFW) region of Texas. The episodes featured east-northeasterly winds conducive to interstate transport of air pollutants. The study revealed that local, intrastate, and neighbouring state emissions of nitrogen oxides (NO x ) all contributed significantly to daytime ozone in DFW. Local NO x emissions exerted the strongest impact on local ozone, though the impact was highly variable temporally and spatially within the region. NO x emissions from Texas areas outside DFW contributed on average about 10 ppb to daytime DFW ozone. Neighbouring states (Oklahoma, Arkansas, Louisiana, and Mississippi) in total also contributed about 10 ppb to DFW ozone. Anthropogenic VOC emissions from outside the DFW region yielded negligible impact on DFW ozone. DFW ozone is shown to respond more nonlinearly to local NO x than to other NO x emission reductions. The CMAQ-HDDM results indicate that for these episodes, a 4 ppb reduction in average DFW 8 h ozone could be achieved by either a 40% reduction in DFW NO x , a 70% reduction in intrastate NO x , or a 50% reduction in NO x from the four neighbouring states.

Efficient Characterization of Pollutant-Emission Response under Parametric Uncertainty

An essential requirement of modeling for air quality management is to accurately simulate the responses of pollutant concentrations to changes in emissions. Uncertain model input parameters such as emission rates and reaction rate constants lead to uncertainty in model responses. However, traditional methods for characterizing parametric uncertainty are exceedingly computationally intensive. This paper presents methods for using high-order sensitivity coefficients in analytical equations to efficiently represent how the responsiveness of pollutants to emission reductions in the underlying photochemical model varies with simultaneous perturbations in multiple model input parameters. Separate approaches are introduced for characterizing the parametric uncertainty of pollutant response to a fixed or a variable amount of emission reduction. The approaches are demonstrated for an air pollution episode used in recent attainment planning in Georgia. For hypothetical scenarios in which domain-wide emission rates and photolysis rates are perturbed simultaneously by 50%, the reduced form models yield highly accurate predictions of the ozone impacts due to 50% reductions in nitrogen-oxide emissions in Atlanta (normalized mean bias 6.0%, normalized mean error 9.7%, R2=0.992) and inorganic particulate responses to Atlanta sulfur-dioxide emissions (-2.9% bias, 3.7% error, R2=1.000). Similar accuracy is achieved for pollutant responses to power plant emission controls.

Cost-Benefit Analysis in the Selection of Efficient Multipollutant Strategies

Abstract Pollution control efforts are motivated by the desire to protect human health and the environment. Often, those efforts involve selecting among multiple options for attaining air quality objectives. For example, state and local decision-makers must choose the mix of control strategies for meeting the requirements of the National Ambient Air Quality Standards (NAAQS) and the Regional Haze Rule. We demonstrate that including assessments of the human health and environmental benefits when evaluating alternative strategies may help decision-makers to identify multipollutant attainment strategies that achieve greater net benefits than would accrue under strategies optimized for cost alone. This paper presents a conceptual framework that decision-makers could use to choose among alternative multipollutant control strategies, accounting for the benefits and the costs of different types and locations of emissions reductions.