Search

Ethylene oxide (EtO) is a known carcinogen and mutagen associated with increased incidence of breast and blood cancers. The largest medical sterilization facility in Michigan had been assessed by the U.S. Environmental Protection Agency as imposing an additional cancer risk greater than one in one thousand in nearby neighborhoods. This prompted the Michigan Department of Environmental Quality (now referred to as the Department of Environment, Great Lakes, and Energy) to conduct an air quality modeling study of the ambient EtO impacts of the sterilization facility, followed by 24 h Summa canister sampling and TO-15 analysis in two phases. Inverse modeling of the measured 24 h EtO concentrations during the second phase yielded estimates of 594 lbs/year for the facility&rsquo, s total emissions of EtO and 0.247 &micro, g/m3 for the urban background concentration. The inverse-modeled emissions are similar to reported emissions by the facility operator based on indoor air measurements and simple mass balance assumptions, while the inferred background concentration agrees with estimates from other field investigations. The estimated peak 24 h exposure to EtO caused by the sterilization facility in nearby neighborhoods was 1.83 &mu, g/m3 above the background level, corresponding to an additional cancer risk of approximately one in one hundred, if assumed to represent annual mean exposure.

During the Benzene and other Toxics Exposure (BEE-TEX) study, a remote sensing network based on long path Differential Optical Absorption Spectroscopy (DOAS) was set up in the Manchester neighborhood beside the Ship Channel of Houston, Texas in order to perform Computer Aided Tomography (CAT) scans of hazardous air pollutants. On 18–19 February 2015, the CAT scan network detected large nocturnal plumes of toluene and xylenes most likely associated with railcar loading and unloading operations at Ship Channel petrochemical facilities. The presence of such plumes during railcar operations was confirmed by a mobile laboratory equipped with a Proton Transfer Reaction—Mass Spectrometer (PTR-MS), which measured transient peaks of toluene and C 2 -benzenes of 50 ppb and 57 ppb respectively around 4 a.m. LST on 19 February 2015. Plume reconstruction and source attribution were performed using the 4D variational data assimilation technique and a 3D micro-scale forward and adjoint air quality model based on both tomographic and PTR-MS data. Inverse model estimates of fugitive emissions associated with railcar transfer emissions ranged from 2.0 to 8.2 kg/hr for toluene and from 2.2 to 3.5 kg/hr for xylenes in the early morning of 19 February 2015.

Aromatic hydrocarbons are well known air toxics which are regulated by the US EPA and other air quality agencies. Accurate, long-term monitoring of these compounds at low part-per-billion levels, as well as identifying emission point sources is therefore crucial to protect human health in neighborhoods near large emission sources. Here we present a new long-path differential optical absorption spectroscopy (LP-DOAS) instrument specifically designed to monitor aromatic hydrocarbons. The system is based on a novel dual - light emitting diode (LED) light source, which eliminates the requirement to suppress spectrometer stray light. This light source, together with a high stability fiber-based sending/receiving telescope, allows the measurement of aromatic hydrocarbons on once-folded absorptions paths of 200–1200 m length. The new instrument shows very good agreement with simultaneous in-situ measurements if inhomogeneities of the trace gas spatial distributions are considered. The new instrument performed well during a three-month field test as an automated fence-line monitor at a refinery, successfully distinguishing upwind background levels of ∼1 ppb from emissions reflected in elevated mixing ratios of 3–4 ppb. A two-dimensional measurement network based on two identical LP-DOAS instruments operating on seven crossed light paths was operated successfully in Houston, TX. Qualitative and quantitative analysis of two events with toluene and xylene plumes demonstrate how this setup can be used to derive the spatial distribution of aromatic hydrocarbons, and identify point sources.

The electric system is experiencing rapid growth in the adoption of a mix of distributed renewable and fossil fuel sources, along with increasing amounts of off-grid generation. New operational regimes may have unforeseen consequences for air quality. A three-dimensional microscale chemical transport model (CTM) driven by an urban wind model was used to assess gaseous air pollutant and particulate matter (PM) impacts within ~10 km of fossil-fueled distributed power generation (DG) facilities during the early afternoon of a typical summer day in Houston, TX. Three types of DG scenarios were considered in the presence of motor vehicle emissions and a realistic urban canopy: (1) a 25-MW natural gas turbine operating at steady state in either simple cycle or combined heating and power (CHP) mode; (2) a 25-MW simple cycle gas turbine undergoing a cold startup with either moderate or enhanced formaldehyde emissions; and (3) a data center generating 10 MW of emergency power with either diesel or natural gas-fired backup generators (BUGs) without pollution controls. Simulations of criteria pollutants (NO2, CO, O3, PM) and the toxic pollutant, formaldehyde (HCHO), were conducted assuming a 2-hr operational time period. In all cases, NOx titration dominated ozone production near the source. The turbine scenarios did not result in ambient concentration enhancements significantly exceeding 1 ppbv for gaseous pollutants or over 1 µg/m(3) for PM after 2 hr of emission, assuming realistic plume rise. In the case of the datacenter with diesel BUGs, ambient NO2 concentrations were enhanced by 10-50 ppbv within 2 km downwind of the source, while maximum PM impacts in the immediate vicinity of the datacenter were less than 5 µg/m(3).Plausible scenarios of distributed fossil generation consistent with the electricity grid's transformation to a more flexible and modernized system suggest that a substantial amount of deployment would be required to significantly affect air quality on a localized scale. In particular, natural gas turbines typically used in distributed generation may have minor effects. Large banks of diesel backup generators such as those used by data centers, on the other hand, may require pollution controls or conversion to natural gas-fired reciprocal internal combustion engines to decrease nitrogen dioxide pollution.

An explosive growth in natural gas production within the last decade has fueled concern over the public health impacts of air pollutant emissions from oil and gas sites in the Barnett and Eagle Ford shale regions of Texas. Commonly acknowledged sources of uncertainty are the lack of sustained monitoring of ambient concentrations of pollutants associated with gas mining, poor quantification of their emissions, and inability to correlate health symptoms with specific emission events. These uncertainties are best addressed not by conventional monitoring and modeling technology, but by increasingly available advanced techniques for real-time mobile monitoring, microscale modeling and source attribution, and real-time broadcasting of air quality and human health data over the World Wide Web. The combination of contemporary scientific and social media approaches can be used to develop a strategy to detect and quantify emission events from oil and gas facilities, alert nearby residents of these events, and collect associated human health data, all in real time or near-real time. The various technical elements of this strategy are demonstrated based on the results of past, current, and planned future monitoring studies in the Barnett and Eagle Ford shale regions.Resources should not be invested in expanding the conventional air quality monitoring network in the vicinity of oil and gas exploration and production sites. Rather, more contemporary monitoring and data analysis techniques should take the place of older methods to better protect the health of nearby residents and maintain the integrity of the surrounding environment.

A mobile laboratory equipped with a proton transfer reaction mass spectrometer (PTR-MS) operated in Galena Park, Texas, near the Houston Ship Channel during the Benzene and other Toxics Exposure Study (BEE-TEX). The mobile laboratory measured transient peaks of benzene of up to 37 ppbv in the afternoon and evening of February 19, 2015. Plume reconstruction and source attribution were performed using the four-dimensional (4D) variational data assimilation technique and a three-dimensional (3D) micro-scale forward and adjoint air quality model based on mobile PTR-MS data and nearby stationary wind measurements at the Galena Park Continuous Air Monitoring Station (CAMS). The results of inverse modeling indicate that significant pipeline emissions of benzene may at least partly explain the ambient concentration peaks observed in Galena Park during BEE-TEX. Total pipeline emissions of benzene inferred within the 16-km(2) model domain exceeded point source emissions by roughly a factor of 2 during the observational episode. Besides pipeline leaks, the model also inferred significant benzene emissions from marine, railcar, and tank truck loading/unloading facilities, consistent with the presence of a tanker and barges in the Kinder Morgan port terminal during the afternoon and evening of February 19. Total domain emissions of benzene exceeded corresponding 2011 National Emissions Inventory (NEI) estimates by a factor of 2-6.Port operations involving petrochemicals may significantly increase emissions of air toxics from the transfer and storage of materials. Pipeline leaks, in particular, can lead to sporadic emissions greater than in emission inventories, resulting in higher ambient concentrations than are sampled by the existing monitoring network. The use of updated methods for ambient monitoring and source attribution in real time should be encouraged as an alternative to expanding the conventional monitoring network.

The 2009 Study of Houston Atmospheric Radical Precursors (SHARP) field campaign had several components that yielded information on the primary vehicular emissions of formaldehyde (HCHO) and nitrous acid (HONO), in addition to many other species. Analysis of HONO measurements at the Moody Tower site in Houston, TX, yielded emission ratios of HONO to the vehicle exhaust tracer species NOx and CO of 14 pptv/ppbv and 2.3 pptv/ppbv, somewhat smaller than recently published results from the Galleria site, although evidence is presented that the Moody Tower values should be upper limits to the true ratios of directly emitted HONO, and are consistent with ratios used in current standard emissions models. Several other Moody Tower emission ratios are presented, in particular a value for HCHO/CO of 2.4 pptv/ppbv. Considering only estimates of random errors, this would be significantly lower than a previous value, though the small sample size and possible systematic differences should be taken into account. Emission factors for CO, NOx, and HCHO, as well as various volatile organic compounds (VOCs), were derived from mobile laboratory measurements both in the Washburn Tunnel and in on-road exhaust plume observations. These two sets of results and others reported in the literature all agree well, and are substantially larger than the CO, NOx, and HCHO emission factors derived from the emission ratios reported from the Galleria site.Emission factors for the species measured in the various components of the 2009 SHARP campaign in Houston, TX, including HCHO, HONO, CO, CO2, nitrogen oxides, and VOCs, are needed to support regional air quality monitoring. Components of the SHARP campaign measured these species in several different ways, each with their own potential for systematic errors and differences in vehicle fleets sampled. Comparisons between data sets suggest that differences in sampling place and time may result in quite different emission factors, while also showing that different vehicle mixes can yield surprisingly similar emission factors.

This chapter provides a brief history of unconventional oil and gas development, including the role of horizontal drilling and hydraulic fracturing technologies in the shale gas revolution. A survey of the environmental and public health literature related to oil and gas development is also included, with an emphasis on air quality and climate change impacts. The main environmental aspects covered are the greenhouse gas footprint of shale gas compared to coal, ozone nonattainment in urban shale plays (e.g., the Barnett Shale of Texas), hazardous air pollutants such as formaldehyde and benzene, and the likely underestimate of emissions from oil and gas activities in official emission inventories.

This chapter summarizes various technologies and practices for the control of emissions from oil and gas sources, including the US EPA’s updated New Source Performance Standards (NSPS). Control options for fugitive sources include leak detection and repair (LDAR), the use of low-bleed controllers and electricity-driven pumps, suppression and/or recovery of storage tank vapors, green completions, plunger lift systems for liquids unloading, and the use of composite wraps and flexible plastic liners for natural gas pipelines. Control options for combustion sources include automatic air-to-fuel ratio controllers in gas-fired stationary internal combustion (IC) engines, catalytic emission control systems, diesel particulate filters (DPFs), and flare minimization. A 40% reduction in on-shore methane emissions from the natural gas supply chain is achievable with existing technologies at a net total cost of $0.66/MCF of methane reduced, or less than $0.01/MCF of gas produced. This would save the US economy over $100 million per year.

This chapter explains the physics of climate change, including the greenhouse effect and climate feedbacks, as a prelude to discussing assessments of global warming by the Intergovernmental Panel on Climate Change (IPCC). The critical importance of methane leakage by the oil and gas industry to near-term climate change mitigation is discussed, including estimates of site-specific, regional, and global leakage rates based on observational studies using both top-down and bottom-up measurement approaches. The role of super-emitting facilities in quantifying methane leakage is emphasized. Efforts by the World Bank to reduce global flaring of natural gas associated with oil production, and the possible contribution of the oil and gas industry to increased radiative forcing by tropospheric ozone are also discussed.

This chapter presents the US National Ambient Air Quality Standard (NAAQS) for particulate matter (PM) and the human health, visibility, climate, and ecological problems that may arise from emissions of PM by oil and gas activities, including the use of crystalline silica sand as a proppant in shale rock. Typical PM emissions estimates are presented for the Marcellus Shale in the eastern United States. The current understanding of secondary aerosol formation is also discussed, along with its importance to the oil and gas industry due to the possible contribution of alkane emissions to fine aerosol mass via organic nitrate formation. The ecological implications of PM pollution include impacts on vegetation and mammals due to surface deposition of acids, nitrogen, and polycyclic aromatic hydrocarbon-coated soot particles.

This chapter demonstrates the need for multiscale modeling of ozone and other air quality impacts stemming from emissions from the oil and gas industry. This need is illustrated in the context of possible ozone nonattainment in the metropolitan region of San Antonio, Texas due to oil and gas development in the Eagle Ford Shale (EFS). The conclusions of a coarse-grid regional air quality modeling study are discussed, along with results from a micro-scale ozone impact assessment using the HARC chemical transport model (CTM). Suggestions are provided on how micro-scale and regional modeling approaches can be blended in future ozone attainment demonstrations beyond the use of computationally intensive nested grids. These include the parameterization of micro-scale influences through artificial source terms in regional models and pattern recognition methods such as Principal Component Analysis (PCA).

This chapter discusses methods for measuring ambient concentrations and emissions of air pollutants, with an emphasis on real-time methods. Three general monitoring applications are discussed: (1) mapping and surveying, (2) baseline and trend monitoring, and (3) source attribution and emissions quantification. Various strategies are then recommended to overcome the undersampling problem, namely: (1) mobile platforms with real-time sensors, (2) passive and active remote sensing, and (3) distributed sensor networks. Several advanced measurement technologies to implement these strategies are available based on optical, ionization, and chemical separation techniques. These methods include optical gas imaging (OGI), the use of lasers and light emitting diodes (LEDs) for in situ measurements and open path remote sensing, computer aided tomography (CAT), passive infrared (IR) and solar radiation-based techniques, chemical ionization and membrane inlet mass spectrometry, and microfluidics.

This chapter provides real-life examples of oil and gas industry emission events leading to transient, high ambient concentrations of hazardous air pollutants, including the largest natural gas leak in US history at Aliso Canyon, and pipeline leaks of benzene in an industrial fence line community near the Houston Ship Channel. These emission events demonstrate the dilemma of how to measure emissions of toxic pollutants that vary greatly in both time and space, and the flaws of conventional monitoring studies of the environmental health impacts of oil and gas development. Difficulties in health risk assessment are compounded by secondary pollution from chemically reactive primary emissions and by complex mixtures in ambient air that can generate health effects due to the combination of pollutants, including cancer and immune system damage. Alleged health effects from oil and gas development also include endocrine disruption and birth defects.

This chapter describes the gas phase photochemical reactions that control the formation of ozone and the degradation of pollutants in the atmosphere, with an emphasis on near-source chemistry. For the purpose of illustration, the HARC chemical mechanism, chemical solver, and chemical adjoint are presented in detail. The HARC forward and adjoint, micro-scale chemical transport model is then used to demonstrate the application of the adjoint method to inverse modeling of reactive species such as formaldehyde. Two examples in the context of historical field studies are presented. The first study quantified primary formaldehyde and accompanying sulfur dioxide emissions from one of the largest refineries in the United States during the 2009 SHARP/FLAIR campaign. The second study examined the role of oil and gas site emissions in producing wintertime ozone in the Uinta Basin of Utah, which included primary formaldehyde emissions comparable to the output of a large refinery.

This chapter summarizes the spectrum of emissions to the atmosphere from oil and gas industry supply chains, with an emphasis on upstream and midstream activities. Major categories of emissions include: (1) exploration and production; (2) gathering and processing; (3) combustion; (4) storage and transmission; and (5) waste disposal. Exploration and production emissions include those from well site preparation, drilling, hydraulic fracturing, well completion, and production fugitive releases. Gathering and processing emissions arise from several steps, including gas and liquid separation, glycol dehydration, gas sweetening, and sulfur or hydrocarbon recovery. Combustion emissions are produced by reciprocal internal combustion engines and turbines, boilers and heaters, and flares. Storage, transport, or transmission of oil, gas, and production chemicals can lead to fugitive emissions from storage tanks, pipeline leaks and maintenance, and loading losses. Lastly, waste pits and landfarming are two major sources of disposal emissions.

This chapter describes bottom-up methods for estimating emissions from oil and gas sources. Specific examples are provided for four types of approaches: source sampling, emission factors, computer models, and engineering calculations. Source sampling is illustrated by leak detection results from the City of Fort Worth Natural Gas Air Quality Study conducted in 2010. Flare emission factors from the US EPA’s AP-42 database are used to compute CO and NOx emission rates from the combustion of natural gas. Emissions estimation software is exemplified by the American Petroleum Institute’s E&P TANK model for working, standing, and flashing emissions from petroleum production field storage tanks. Blowdown emissions are computed by means of the displacement equation. Techniques for extrapolating site-specific emissions estimates to the basin scale, and for projection of emission inventories to future years, are also presented. Lastly, the role of permitting programs in facilitating emissions estimates for midstream point sources is discussed.

We have developed a novel approach for ambient measurements of nitrous acid (HONO) using ion drift-chemical ionization mass spectrometry (ID-CIMS). HONO is ionized using the sulfur hexafluoride anion, representing the first application of this reagent ion under humid tropospheric conditions. During the 2009 Study of Houston Atmospheric Radical Precursors (SHARP) Field Campaign, HONO measurements were continuously conducted from 1 May to 1 June at a site located on the campus of the University of Houston. Diurnally, HONO concentration accumulates in the late afternoon, reaches a nighttime maximum, and declines rapidly after sunrise. The nighttime HONO peaks show close correlations with the NO 2 concentration, particle surface area, and soot mass concentration, indicating that the aerosol-phase chemistry likely contributes to HONO formation. A higher nighttime HONO peak concentration typically precedes a higher and earlier ozone peak concentration of the following day, by about 20 ppb higher and four hours earlier than those with a lower preceding HONO peak concentration. Because of its high detection sensitivity and fast-responding time, the ID-CIMS method described in this work may greatly facilitate HONO detection under typical tropospheric conditions.

The Study of Houston Atmospheric Radical Precursors (SHARP) was a field campaign developed by the Houston Advanced Research Center on behalf of the Texas Environmental Research Consortium. SHARP capitalized on previous research associated with the Second Texas Air Quality Study and the development of the State Implementation Plan (SIP) for the Houston-Galveston-Brazoria (HGB) ozone nonattainment area. These earlier studies pointed to an apparent deficit in ozone production in the SIP attainment demonstration model despite the enhancement of simulated emissions of highly reactive volatile organic compounds in accordance with the findings of the original Texas Air Quality Study in 2000. The scientific hypothesis underlying the SHARP campaign was that there are significant undercounted primary and secondary sources of the radical precursors, formaldehyde, and nitrous acid, in both heavily industrialized and more typical urban areas of Houston. These sources, if properly taken into account, could increase the production of ozone in the SIP model and the simulated efficacy of control strategies designed to bring the HGB area into ozone attainment. This overview summarizes the precursor studies and motivations behind SHARP, as well as the overall experimental design and major findings of the 2009 field campaign. These findings include significant combustion sources of formaldehyde at levels greater than accounted for in current point source emission inventories; the underestimation of formaldehyde and nitrous acid emissions, as well as CO/NOx and NO2/NOx ratios, by mobile source models; and the enhancement of nitrous acid by atmospheric organic aerosol.

[1] The Aerodyne Research Inc. mobile laboratory performed real-time in-situ measurements of volatile organic compounds, nitrogen oxides, and formaldehyde in Texas City, Texas on 7 May 2009 during the Formaldehyde and olefins from Large Industrial Releases experiment of the 2009 Study of Houston Atmospheric Radical Precursors (SHARP) campaign. Our goal was to identify and quantify emission sources within the largest industrial facility in Texas City most likely responsible for measured concentrations of benzene, an important VOC and hazardous air pollutant. The Houston Advanced Research Center inverse air quality model has been used to infer benzene emission rates from all potential source locations that could account for the benzene concentrations measured by the mobile lab in the vicinity of the facility. A Positive Matrix Factorization receptor model was also applied to the concentrations measured by the mobile lab, the results of which strongly supported the source attribution specified by the inverse model. The two independent source apportionment techniques both implicated flare, storage tank, and ultraformer units in the facility as significant contributors to emission plumes of elevated benzene concentrations observed by the mobile lab. The emissions of some of the flare and tank units were found to be greater than reported in emission inventories by about an order of magnitude.

[1] During the 2006 Second Texas Air Quality Study (TexAQS II) field study, ambient mixing ratios of formaldehyde (HCHO) up to 52 ppbv were observed at Lynchburg Ferry in the Houston Ship Channel on the morning of 27 September 2006. These elevated mixing ratios coincided with a flare event during a sequential planned shutdown of a petrochemical facility ~8 km from the monitoring site. An adjoint version of the Houston Advanced Research Center (HARC) neighborhood air quality model was used to perform 4-D variational inverse modeling of industrial emissions of HCHO and other ozone precursors based on Lynchburg Ferry observations. The simulation employed a horizontal domain size and grid resolution of 8 km × 8 km and 400 m, and was conducted for a 1.5 h period (8–9:30 A.M.) during which the highest HCHO concentrations were recorded. The event emissions of ethene and propene computed by the inverse model are consistent with the largest estimated emissions for the facility in question derived from the Solar Occultation Flux technique during TexAQS II. Moreover, the computed peak flare emissions of HCHO during the shutdown event were around 282 kg/h, which is less than but comparable in magnitude to the largest area-wide total (primary plus secondary) formaldehyde flux from the Houston Ship Channel measured by Differential Optical Absorption Spectroscopy during TexAQS II. The estimated flare event emissions of primary formaldehyde are roughly 50 times larger than HCHO emissions from flares used in routine operations, as inferred from remote sensing and/or real-time in situ measurements during the 2009 SHARP campaign.

Contemporary developments in spectroscopic remote sensing and real time monitoring have opened up new possibilities for the detection and measurement of hazardous air pollutants, especially when environmental justice is at stake. This special issue documents how such developments have been applied in a novel field campaign in the Houston Ship Channel region of Texas known as the Benzene and other Toxics Exposure (BEE-TEX) study. BEE-TEX was first conceived in 2007 as a means to demonstrate the potential of Computer Aided Tomography (CAT) using Differential Optical Absorption Spectroscopy (DOAS), which was previously attempted only once by Laepple et al.1 in Germany to measure mobile source plumes. However, funding and implementation of BEE-TEX were postponed several times by events beyond the participants’ control, a delay which fortuitously enhanced the end result of the campaign, owing to many technical developments between 2007 and the ultimate performance period of the experiment in February 2015. These developments included the marriage of new tools for micro-scale air quality modeling and real-time measurement in a series of papers by Olaguer and various collaborators2–7, the enhancement of Web technologies to enable real-time data broadcasting (Olaguer, this issue), the development of new Light Emitting Diode (LED) sources for remote sensing applications by Prof. Jochen Stutz and collaborators at UCLA, and the invention of a new in vitro technique to measure the response of living human lung cells to ambient air pollution (Vizuete et al., this issue). All these technologies were wed together in what proved to be a much richer experiment than the original one conceived in 2007. There are three papers in this special issue documenting the design, implementation, and early results of the BEE-TEX study. The first is a general overview by Olaguer, including a discussion of the role of real time data broadcasting and source attribution in the field experiment. Unfortunately, a separate paper intended to discuss the specifics of the CAT scan implementation was never submitted due to the personal circumstances of the main author, Dr Stutz, so some details of this are provided in the overview. The second paper is a contribution by Aerodyne Research, Inc. (Yacovitch et al.) discussing mobile real-time measurements of various volatile organic compounds, including observed concentrations of 1,3-butadiene routinely exceeding the U.S. Environmental Protection Agency’s E-5 lifetime cancer risk level in the Manchester neighborhood of Houston. The third paper is the contribution by Vizuete et al. noted earlier, which discusses the results of the first field trials of the cultured human lung cell exposure technique, including interesting genetic changes accompanying observed pollution events. Together, these three papers demonstrate how air quality monitoring and modeling, and their application to the assessment of human health impacts, may be revolutionized by the latest technologies.

Increased drilling in urban areas overlying shale formations and its potential impact on human health through decreased air quality make it important to estimate the contribution of oil and gas activities to photochemical smog. Flares and compressor engines used in natural gas operations, for example, are large sources not only of NOx but also offormaldehyde, a hazardous air pollutant and powerful ozone precursor We used a neighborhood scale (200 m horizontal resolution) three-dimensional (3D) air dispersion model with an appropriate chemical mechanism to simulate ozone formation in the vicinity ofa hypothetical natural gas processing facility, based on accepted estimates of both regular and nonroutine emissions. The model predicts that, under average midday conditions in June, regular emissions mostly associated with compressor engines may increase ambient ozone in the Barnett Shale by more than 3 ppb beginning at about 2 km downwind of the facility, assuming there are no other major sources of ozone precursors. Flare volumes of 100,000 cubic meters per hour ofnatural gas over a period of 2 hr can also add over 3 ppb to peak 1-hr ozone somewhatfurther (8 km) downwind, once dilution overcomes ozone titration and inhibition by large flare emissions of NOx. The additional peak ozone from the hypothetical flare can briefly exceed 10 ppb about 16 km downwind. The enhancements of ambient ozone predicted by the model are significant, given that ozone control strategy widths are of the order of a few parts per billion. Degrading the horizontal resolution of the model to 1 km spuriously enhances the simulated ozone increases by reducing the effectiveness of ozone inhibition and titration due to artificial plume dilution.

Large petrochemicalflares, common in the Houston Ship Channel (the Ship Channel) and other industrialized areas in the Gulfof Mexico region, emit hundreds to thousands of pounds per hour of highly reactive volatile organic compounds (HRVOCs). We employedfine horizontal resolution (200 mx200 m) in a three-dimensional (3D) Eulerian chemical transport model to simulate two historical Ship Channel flares. The model reasonably reproduced the observed ozone rise at the nearest monitoring stations downwind of the flares. The larger of the two flares had an olefin emission rate exceeding 1400 lb/hr. In this case, the model simulated a rate of increase in peak ozone greater than 40 ppb/hr over a 12 kmx12 km horizontal domain without any unusual meteorological conditions. In this larger flare, formaldehyde emissions typically neglected in official inventories enhanced peak ozone by as much as 16 ppb and contributed over 10 ppb to ambient formaldehyde up to approximately 8 km downwind of the flare. The intense horizontal gradients in large flare plumes cannot be simulated by coarse models typically used to demonstrate ozone attainment. Moreover even the relatively dense monitoring network in the Ship Channel may not be able to detect many transient high ozone events (THOEs) caused by industrial flare emissions in the absence of stagnant air recirculation or stalled sea breeze fronts, even though such conditions are unnecessary for the occurrence of THOEs.

A new mathematical optimization method is presented for reconstructing pollution plume concentrations from tomographic remote sensing measurements on neighborhood scales (about 1 km × 1 km) using Differential Optical Absorption Spectroscopy (DOAS). The new method, called CAT–4Dvar, combines Computer Aided Tomography (CAT) and 4D variational (4Dvar) data assimilation. The objective of the method is to produce accurate reconstructions compared to the Algebraic Reconstruction Technique (ART) and other non-variational methods with only a small number of DOAS telescopes. A forward and adjoint 3D grid dispersion model was developed based on advection and diffusion solvers commonly used in air quality modeling. The adjoint model optimizes the model emissions and horizontal diffusion coefficient based on the difference between tomographic DOAS observations and ray path-integrated concentrations predicted by the forward model. It also updates the corresponding error covariances based on the Hessian of the cost function. An enhanced reconstruction is obtained from the forward model with optimized parameter values. In a synthetic experiment involving two hypothetical DOAS instruments, the CAT–4Dvar method yielded excellent results compared to ART, reducing the overall nearness index from 57% to 11%.

An online data repository known as the Air Research Information Infrastructure (ARII) was used to discriminate large industrial sources of formaldehyde (HCHO) from mobile and secondary formaldehyde sources in Houston. Analysis of continuous online measurements at one urban and two industrial sites obtained during the summer of 2006 enabled us to isolate and evaluate major source factors associated with formaldehyde. The contribution of industrial sources to total atmospheric formaldehyde at the urban Houston site is estimated to be 17%, compared to 23% for mobile sources, 36% secondary formation, and 24% biogenic sources. The potential industrial sources include flares from petrochemical plants and refineries in the Port of Houston. The relative contribution of industrial source factors to ambient HCHO at the urban site increased to about 66% on some mornings, coinciding with the HCHO peak concentration. Secondary formation of HCHO during the day and night resulted from reactions of industrial olefins and other VOCs with OH or ozone. Some peak HCHO concentrations can also be linked to emission events of other VOCs, while a significant portion remains unexplained by the reported events. It is likely, based on the results from the SHARP campaign and our analysis, that some episodic emission events releasing primary HCHO are unreported to the Texas Commission on Environmental Quality (TCEQ).

In this paper, we discuss the theory of adjoint sensitivity analysis and the method of 4D-Var data assimilation in the context of the Sulfur Transport Eulerian Model (STEM). The STEM atmospheric Chemical Transport Model (CTM) is used to perform adjoint sensitivity analysis and data assimilation over the State of Texas. We first demonstrate the use of adjoint sensitivity analysis for a receptor located at ground level in the Dallas Fort Worth (DFW) area. Simulations are carried out for three 36-h intervals in July 2004. One set of simulations focuses on a passive tracer, and illustrates the influence of meteorological conditions. The other results show the areas of influence associated with DFW ground level ozone, i.e. the areas where changes in precursors (O3, NO2, and HCHO) have the maximum impact on DFW ozone. Next, we employ data assimilation to optimize initial conditions of chemical fields and ground level emissions. We optimize the initial conditions for two episodes on 1 and 16 July 2004. Data assimilation makes use of AirNow ground level observations (for both episodes) and SCHIAMACHY NO2 and HCHO observations from ENVISAT (for the 16 July episode). The re-analyzed chemical fields show considerable improved agreement with AirNow observations for non-initial conditions. We also perform inverse modeling of ground level emissions using data assimilation under an additional smoothness constraint. The results indicate higher NO2 emission levels than in the current emission inventory in the DFW area, and lower emission levels in eastern Texas. The formaldehyde emissions are found to be larger than reported in a localized area near the Gulf Coast, and about at the reported level elsewhere. While the results obtained with the current state-of-the-art tools can help guide tuning of emission inventories, better constraints on the inverse problem are needed to obtain more rigorous quantitative estimates.

Dichloromethane, perchloroethylene, and trichloroethylene are commercially important chlorinated solvents whose health and environmental impacts are under scrutiny in the industrial world. Their distributions in the global atmosphere have been computed based on data from the Reactive Chlorine Emissions Inventory (RCEI) project using the Global Balance Environment (GLOBE) model, a 3-D radiative-dynamical-chemical model. Their atmospheric lifetimes, scaled to an observed methyl chloroform lifetime of 4.8 years, are 158 days, 105 days, and 4.3 days, respectively. They have strong interhemispheric gradients, with maximum zonal mean surface concentrations in the winter mid-latitude northern hemisphere of approximately 40 ppt, 9 ppt, and 2.5 ppt, respectively. Their spatial distributions show significant seasonal variability, and are sensitive to vertical mixing by cumulus convection and horizontal mixing by synoptic-scale turbulence. While the model interhemispheric exchange time (1.0 years) and computed atmospheric lifetimes are very sensitive to sub-grid scale diffusion, interhemispheric gradients of the chlorinated solvents are not. The simulated results suggest a greater importance for oceanic emissions of perchloroethylene and trichloroethylene than has previously been assumed.

To comply with the federal 8-hr ozone standard, the state of Texas is creating a plan for Houston that strictly follows the U.S. Environmental Protection Agency's (EPA) guidance for demonstrating attainment. EPA's attainment guidance methodology has several key assumptions that are demonstrated to not be completely appropriate for the unique observed ozone conditions found in Houston. Houston's ozone violations at monitoring sites are realized as gradual hour-to-hour increases in ozone concentrations, or by large hourly ozone increases that exceed up to 100 parts per billion/hr. Given the time profiles at the violating monitors and those of nearby monitors, these large increases appear to be associated with small parcels of spatially limited plumes of high ozone in a lower background of urban ozone. Some of these high ozone parcels and plumes have been linked to a combination of unique wind conditions and episodic hydrocarbon emission events from the Houston Ship Channel. However, the regulatory air quality model (AQM) does not predict these sharp ozone gradients. Instead, the AQM predicts gradual hourly increases with broad regions of high ozone covering the entire Houston urban core. The AQM model performance can be partly attributed to EPA attainment guidance that prescribes the removal in the baseline model simulation of any episodic hydrocarbon emissions, thereby potentially removing any nontypical causes of ozone exceedances. This paper shows that attainment of all monitors is achieved when days with observed large hourly variability in ozone concentrations are filtered from attainment metrics. Thus, the modeling and observational data support a second unique cause for how ozone is formed in Houston, and the current EPA methodology addresses only one of these two causes.

The radiative balance of the stratosphere is examined in the light of the possible sensitivity of tracers to small changes in the diabatic heating. A comprehensive radiative transfer algorithm is developed on the basis of accurate and efficient methods for use in coupled stratospheric models of chemistry, dynamics, and radiative transfer, and the individual components of the code are validated against available line-by-line calculations. Finally, the results of different approximations commonly employed in radiative transfer algorithms are compared, and their effects on tracer transport are evaluated using a 2D ozone model.

The Texas Environmental Research Consortium (TERC) funded significant components of the Second Texas Air Quality Study (TexAQS II), including the TexAQS II Radical and Aerosol Measurement Project (TRAMP) and instrumented flights by a Piper Aztec aircraft. These experiments called attention to the role of short-lived radical sources such as formaldehyde (HCHO) and nitrous acid (HONO) in increasing ozone productivity. TRAMP instruments recorded daytime HCHO pulses as large as 32 parts per billion (ppb) originating from upwind industrial activities in the Houston Ship Channel, where in situ surface monitors detected HCHO peaks as large as 52 ppb. Moreover, Ship Channel petrochemical flares were observed to produce plumes of apparent primary HCHO. In one such combustion plume that was depleted of ozone by large emissions of oxides of nitrogen (NOx), the Piper Aztec measured a ratio of HCHO to carbon monoxide (CO) 3 times that of mobile sources. HCHO from uncounted primary sources or ozonolysis of underestimated olefin emissions could significantly increase ozone productivity in Houston beyond previous expectations. Simulations with the CAMx model show that additional emissions of HCHO from industrial flares or mobile sources can increase peak ozone in Houston by up to 30 ppb. Other findings from TexAQS II include significant concentrations of HONO throughout the day, well in excess of current air quality model predictions, with large nocturnal vertical gradients indicating a surface or near-surface source of HONO, and large concentrations of nighttime radicals (approximately30 parts per trillion [ppt] HO2). HONO may be formed heterogeneously on urban canopy or particulate matter surfaces and may be enhanced by organic aerosol of industrial or motor vehicular origin, such as through conversion of nitric acid (HNO3). Additional HONO sources may increase daytime ozone by more than 10 ppb. Improving the representation of primary and secondary HCHO and HONO in air quality models could enhance the simulated effectiveness of control strategies.

A zonally averaged two-dimensional model for chemical species in the atmosphere (Olaguer et al., 1990), with coupled dynamics, radiation transfer, and chemistry, is used to study the present-day atmospheric ozone, odd nitrogen, chlorine, other species. The model utilizes all zonally averaged physical equations of momentum, energy, and mass and determines self-consistently the advective and diffusive tranasport parameters from the temperature specific to the period of observation. A comparison of the model results with observations showed good agreement.

A diagnostic study of Eliassen-Palm flux divergence and isentropic mixing coefficient (Kyy) in the stratosphere is performed for different seasons and for both hemispheres, based on the nongeostrophic theory of zonally averaged circulation of Tung (1986). An easily implementable procedure is described which yields a Kyy field that is consistent with advective transport. It is shown that the resultant time- and space-varying structure of Kyy leads to improved simulation of stratospheric species whose distributions are affected by dynamical transport. In particular, it is shown that the simulation of nitric acid is more satisfactory than previous model calculations.

[1] An adjoint version of the Houston Advanced Research Center (HARC) neighborhood air quality model with 200 m horizontal resolution, coupled offline to the Quick Urban & Industrial Complex (QUIC-URB) fast response urban wind model, was used to perform 4-D variational (4Dvar) inverse modeling of an industrial release of formaldehyde (HCHO) and sulfur dioxide (SO2) in Texas City, Texas during the 2009 Study of Houston Atmospheric Radical Precursors (SHARP). The source attribution was based on real-time observations by the Aerodyne mobile laboratory and a high resolution 3-D digital model of the emitting petrochemical complex and surrounding urban canopy. The inverse model estimate of total primary HCHO emitted during the incident agrees very closely with independent remote sensing estimates based on both Imaging and Multi-Axis Differential Optical Absorption Spectroscopy (DOAS). Whereas a previous analysis of Imaging DOAS data attributed the HCHO release to a Fluidized Catalytic Cracking Unit (FCCU), the HARC model attributed most of the HCHO event emissions to both the FCCU and desulfurization processes. Fugitives contributed significantly to primary HCHO, as did combustion processes, whereas the latter accounted for most SO2 event emissions. The inferred HCHO-to-SO2 molar emission ratio was similar to that computed directly from ambient air measurements during the release. The model-estimated HCHO-to-CO molar emission ratio for combustion units with significant inferred emissions ranged from 2% to somewhat less than 7%, consistent with other observationally-based estimates obtained during SHARP. A model sensitivity study demonstrated that the inclusion of urban morphology has a significant, but not critical, impact on the source attribution.

[1] During the field campaign of the Study of Houston Atmospheric Radical Precursors/Surface-Induced Oxidation of Organics in the Troposphere (SHARP/SOOT) in Houston, Texas, a suite of aerosol instruments was deployed to directly measure a comprehensive set of aerosol properties, including the particle size distribution, effective density, hygroscopicity, and light extinction and scattering coefficients. Those aerosol properties are employed to quantify the mixing state and composition of ambient particles and to gain a better understanding of the formation and transformation of fine particulate matter in this region. During the measurement period, aerosols are often internally mixed, with one peak in the effective density distribution at 1.55 ± 0.07 g cm−3, consistent with a population composed largely of sulfates and organics. Episodically, a second mode below 1.0 g cm−3 is identified in the effective density distributions, reflecting the presence of freshly emitted black carbon (BC) particles. The measured effective density demonstrates a clear diurnal cycle associated with primary emissions from transportation and photochemical aging, with a minimum during the morning rush hour, increasing from 1.4 to 1.5 g cm−3 on average over 5 h, and remaining nearly constant throughout the afternoon. The average BC concentration derived from light-absorption measurements is 0.31 ± 0.22 µg m−3, and the average measured particle single scattering albedo is 0.94 ± 0.04. When elevated BC concentrations are observed, typically during the morning rush hours, single scattering albedo decreases, with a smallest measured value of about 0.7. Aerosol hygroscopicity measurements indicate that larger particles (e.g., 400 nm) are more hygroscopic than smaller particles (e.g., 100 nm). The measurements also reveal discernable meteorological impacts on the aerosol properties. After a frontal passage, the average particle effective density decreases, the average BC concentration increases, and the aerosol size distribution is dominated by new particle formation.

A study of irreversible reactions involving molecular nitrogen on Jupiter indicates that vertical motions are sufficiently rapid in the deep atmosphere to transport large amounts of N2 from the 900°–1700°K levels where it is stable up to the cold visible regions. Both homogeneous gas-phase and heterogeneous iron-catalyzed reactions between N2 and H2 were considered. We predict N2 mixing ratios of 0.6–3 ppmv if catalysis is effective and up to 10 ppmv if it is not. Thus N2 may be the most abundant nonequilibrium species in Jupiter's troposphere and potentially detectable by the neutral mass spectrometer which will be on board the 1986 Galileo Entry Probe.