Development of Company-Specific Emission Factors with Confidence Intervals for Natural Gas Customer Meters in Southern California

Methane is both a significant and short-lived greenhouse gas compared to CO2, and reducing methane emissions from natural gas distribution systems may offer cost-effective reduction opportunities. We report substantial new direct leak rate measurements from customer meter set assemblies (MSAs) in Southern California. In a novel way, emission factors are defined in terms of aboveground Hazardous and Nonhazardous leak categories, which take direct advantage of readily available industry leak data. We also studied leaks that were not detected as part of normal leak survey procedures. As a result, this yields company-specific emission factors that can be used to track progress in reducing methane emissions. This approach also has the advantage of explicitly accounting for the skewed or fat-tail distribution of leak rates by treating high flow rate MSA leaks separately from low flow rate MSA leaks. The Southern California Gas (SoCalGas) methane emission factors, based on 485 leak rate measurements by direct enclosure, were 4.55 (95% confidence interval: 2.32 to 7.14) kg/day for Hazardous leaks, 0.149 (0.119 to 0.183) kg/day for Nonhazardous leaks, and 0.0039 (0.0003 to 0.0198) kg/day for Non-Detected leaks. The percentage of surveyed meters with nondetected leaks was 29.1% (24.3 to 34.6%). Based on a robust Monte Carlo analysis, total leak emissions from MSAs for the SoCalGas system were reduced by 35% based on data from 2015 to 2022. These reductions were attributed to surveying a larger number of MSAs and accelerated leak repair rates. In traditional population-based emission inventories, an individual emission factor for a given asset category is multiplied by the total population of MSAs within the category. This approach simply cannot capture the reduction in leak numbers and methane emissions resulting from leak mitigation and prevention programs.

Operational bias correction for PM2.5 using the AIRPACT air quality forecast system in the Pacific Northwest

A bias correction scheme based on a Kalman filter (KF) method has been developed and implemented for the AIRPACT air quality forecast system which operates daily for the Pacific Northwest. The KF method was used to correct hourly rolling 24-h average PM_2.5 concentrations forecast at each monitoring site within the AIRPACT domain and the corrected forecasts were evaluated using observed daily PM_2.5 24-h average concentrations from 2017 to 2018. The evaluation showed that the KF method reduced mean daily bias from approximately -50% to ±6% on a monthly averaged basis, and the corrected results also exhibited much smaller mean absolute errors typically less than 20%. These improvements were also apparent for the top 10 worst PM_2.5 days during the 2017-2018 test period, including months with intensive wildfire events. Significant differences in AIRPACT performance among urban, suburban, and rural monitoring sites were greatly reduced in the KF bias correction forecasts. The daily 24-h average bias corrections for each monitoring site were interpolated to model grid points using three different interpolation schemes: cubic spline, Gaussian Kriging, and linear Kriging. The interpolated results were more accurate than the original AIRPACT forecasts, and both Kriging methods were better than the cubic spline method. The Gaussian method yielded smaller mean biases and the linear method yielded smaller absolute errors. The KF bias correction method has been implemented operationally using both Kriging interpolation methods for routine output on the AIRPACT website (http://lar.wsu.edu/airpact). This method is relatively easy to implement, but very effective to improve air quality forecast performance.Implications: Current chemical transport models, including CMAQ, used for air quality forecasting can have large errors and uncertainties in simulated PM_2.5 concentrations. In this paper, we describe a relatively simple bias correction scheme applied to the AIRPACT air quality forecast system for the Pacific Northwest. The bias correction yields much more accurate and reliable PM_2.5 results compared to the normal forecast system. As such, the operational bias corrected forecasts will provide a much better basis for daily air quality management by agencies within the region. The bias corrected results also highlight issues to guide further improvements to the normal forecast system.

Whole-House Emission Rates and Loss Coefficients of Formaldehyde and Other Volatile Organic Compounds as a Function of the Air Change Rate

Whole-house emission rates and indoor loss coefficients of formaldehyde and other volatile organic compounds (VOCs) were determined from continuous measurements inside a net-zero energy home at two different air change rates (ACHs). By turning the mechanical ventilation on and off, it was demonstrated that formaldehyde concentrations reach a steady state much more quickly than other VOCs, consistent with a significant indoor loss rate attributed to surface uptake. The first order loss coefficient for formaldehyde was 0.47 ± 0.06 h^-1 at 0.08 h^-1 ACH and 0.88 ± 0.22 h^-1 at 0.62 h^-1 ACH. Loss rates for other VOCs measured were not discernible, with the exception of hexanoic acid. A factor of 5.5 increase in the ACH increased the whole-house emission rates of VOCs but by varying degrees (factors of 1.1 to 3.8), with formaldehyde displaying no significant change. The formaldehyde area-specific emission rate (86 ± 8 μg m^-2 h^-1) was insensitive to changes in the ACH because its large indoor loss rate muted the impact of ventilation on indoor air concentrations. These results demonstrate that formaldehyde loss rates must be taken into account to correctly estimate whole-house emission rates and that ventilation will not be as effective at reducing indoor formaldehyde concentrations as it is for other VOCs.

PSXI-4 Composting management to reduce greenhouse gas and ammonia emissions from feedlot manure

Management of livestock manure may recycle nutrients and decrease greenhouse gas (GHG) and ammonia (NH3) emissions. The objectives were to ascertain effects of environmental conditions and turning on methane (CH4), nitrous oxide (N2O), and NH3 emissions and if treatment with 8.5 g of dicyandiamide (DCD), a denitrification agent, altered GHG emissions. Manure and bedding were collected from feedlot pens and used to construct 3 piles (~1.9 m3 volume) each in winter (WI) and spring (SP). WI piles were turned once, and SP piles were turned twice. Methane, N2O, and NH3 emissions were collected. Methane and N2O flux measurements were collected from SP piles using a static chamber (3.7m L x 2.2m W x 0.9m H). Initial dry matter and nitrogen contents were 33.2 and 30.0% and 20.1 and 17.7 g/kg in WI and SP piles, respectively. Average ambient temperatures and wind speeds were 0.3oC and 10.7oC and 1.76 m/s and 1.97 m/s during WI and SP, respectively. Internal temperatures reached 51±3.9oC on d 4–11 and gradually decreased. Normalized CH4 averaged 2.19 mg٠s٠m-4 and N2O emissions averaged 0.84 mg٠s٠m-4, and were not different between the WI and SP piles. Turning did not affect CH4 emissions from WI piles, but were 55% greater (P < 0.05) when SP piles were turned a second time. Emissions of N2O increased 51% when WI and SP piles were turned (P < 0.05). Ammonia emissions were 83.5% greater from WI piles due to their higher initial concentrations of NH4+-N (2.21 vs. 1.11 g/kg; P < 0.05). Turning did not influence CH4 and N2O fluxes. Addition of DCD at pile formation appears to decrease N2O emissions and fluxes 3 and 10 d later. Turning management and season impacted overall CH4, N2O, and NH3 emissions. Fine-tuning manure handling and management during different seasons may effectively reduce GHG and NH3 emissions.

N2O Emissions From Two Agroecosystems: High Spatial Variability and Long Pulses Observed Using Static Chambers and the Flux-Gradient Technique

With the addition of nitrogen (N), agricultural soils are the main anthropogenic source of N2O, but high spatial and temporal variabilities make N2O emissions difficult to characterize at the field scale. This study used flux-gradient measurements to continuously monitor N2O emissions at two agricultural fields under different management regimes in the inland Pacific Northwest of Washington State, USA. Automated 16-chamber arrays were also deployed at each site; chamber monitoring results aided the interpretation of the flux gradient results. The cumulative emissions over the six-month (1 April-30 September) monitoring period were 2.4 ± 0.7 and 2.1 ± 2 kg N2O-N/ha at the no-till and conventional till sites, respectively. At both sites, maximum N2O emissions occurred following the first rainfall event after N fertilization, and both sites had monthlong emission pulses. The no-till site had a larger N2O emission factor than the Intergovernmental Panel on Climate Change Tier 1 emission factor of 1% of the N input, while the conventional-till site's emission factor was close to 1% of the N input. However, these emission factors are likely conservative. We estimate that the global warming potential of the N2O emissions at these sites is larger than that of the no-till conversion carbon uptake. We recommend the use of chambers to investigate spatiotemporal controls as a complementary method to micrometeorological monitoring, especially in systems with high variability. Continued monitoring coupled with the use of models is necessary to investigate how changing management and environmental conditions will affect N2O emissions.

Vehicle-Based Methane Surveys for Finding Natural Gas Leaks and Estimating Their Size: Validation and Uncertainty

Managing leaks in urban natural gas (NG) distribution systems is important for reducing methane emissions and costly waste. Mobile surveying technologies have emerged as a new tool for monitoring system integrity, but this new technology has not yet been widely adopted. Here, we establish the efficacy of mobile methane surveys for managing local NG distribution systems by evaluating their ability to detect and locate NG leaks and quantify their emissions. In two cities, three-quarters of leak indications from mobile surveys corresponded to NG leaks, but local distribution companies' field crews did not find most of these leaks, indicating that the national CH₄ activity factor for leaks in local NG distribution pipelines is underestimated by a factor of 2.4. We found the median distance between mobile-estimated leak locations and actual leak locations was 19 m. A comparison of emission quantification methods (mobile-based, surface enclosure, and tracer ratio) found that the mobile method overestimated leak magnitude for the smallest leaks but accurately estimated size for the largest leaks that are responsible for the majority of total emissions. Across leak sizes, mobile methods adequately rank relative emission rates for repair prioritization, and they are easily deployed and offer efficient spatial coverage.

Impacts of prescribed fires and benefits from their reduction for air quality, health and visibility in the Pacific Northwest of the United States

Using a WRF-SMOKE-CMAQ modeling framework, we investigate the impacts of smoke from prescribed fires on model performance, regional and local air quality, health impacts, and visibility in protected natural environments using three different prescribed fire emission scenarios - 100% fire, no fire, and 30% fire. The 30% fire case reflects a 70% reduction in fire activities due to harvesting of logging residues for use as a feedstock for a potential aviation biofuel supply chain. Overall model performance improves for several performance metrics when fire emissions are included, especially for organic carbon, irrespective of the model goals and criteria used. This effect on model performance is more pronounced for the rural and remote IMPROVE sites for organic carbon and total PM2.5. A reduction in prescribed fire emissions (30% fire case) results in significant improvement in air quality in areas in western Oregon, northern Idaho and western Montana where most prescribed fires occur. Prescribed burning contributes to visibility impairment and a relatively large portion of protected class I areas will benefit from a reduced emission scenario. For the haziest 20% days, prescribed burning is an important source of visibility impairment and approximately 50% of IMPROVE sites in the model domain show a significant improvement in visibility for the reduced fire case. Using BenMAP, a health impact assessment tool, we show that several hundred additional deaths, several thousand upper and lower respiratory symptom cases, several hundred bronchitis cases, and more than 35,000 work day losses can be attributed to prescribed fires and these health impacts decrease by 25-30% when a 30% fire emission scenario is considered. Implications This study assesses the potential regional and local air quality, public health and visibility impacts from prescribed burning activities as well as benefits that can be achieved by a potential reduction in emissions for a scenario where biomass is harvested for conversion to biofuel. As prescribed burning activities become more frequent, they can be more detrimental for air quality and health. Forest residue based biofuel industry can be source of cleaner fuel with co-benefits of improved air quality, reduction in health impacts and improved visibility.

Assessment of methane emissions from the U.S. oil and gas supply chain

Methane emissions from the U.S. oil and natural gas supply chain were estimated by using ground-based, facility-scale measurements and validated with aircraft observations in areas accounting for ~30% of U.S. gas production. When scaled up nationally, our facility-based estimate of 2015 supply chain emissions is 13 ± 2 teragrams per year, equivalent to 2.3% of gross U.S. gas production. This value is ~60% higher than the U.S. Environmental Protection Agency inventory estimate, likely because existing inventory methods miss emissions released during abnormal operating conditions. Methane emissions of this magnitude, per unit of natural gas consumed, produce radiative forcing over a 20-year time horizon comparable to the CO₂ from natural gas combustion. Substantial emission reductions are feasible through rapid detection of the root causes of high emissions and deployment of less failure-prone systems.

Air Quality and Health Impacts of an Aviation Biofuel Supply Chain Using Forest Residue in the Northwestern United States

Forest residue is a major potential feedstock for second-generation biofuel; however, little knowledge exists about the environmental impacts of the development and production of biofuel from such a feedstock. Using a high-resolution regional air quality model, we estimate the air quality impacts of a forest residue based aviation biofuel supply chain scenario in the Pacific Northwestern United States. Using two potential supply chain regions, we find that biomass and biofuel hauling activities will add <1% of vehicle miles traveled to existing traffic, but the biorefineries will add significant local sources of NO _x and CO. In the biofuel production scenario, the regional average increase in the pollutant concentration is small, but 8-hr maximum summer time O₃ can increase by 1-2 ppb and 24-hr average maximum PM_2.5 by 2 μg/m³. The alternate scenario of slash pile burning increased the multiday average PM_2.5 by 2-5 μg/m³ during a winter simulation. Using BenMAP, a health impact assessment tool, we show that avoiding slash pile burning results in a decrease in premature mortality as well as several other nonfatal and minor health effects. In general, we show that most air quality and health benefits result primarily from avoided slash pile burning emissions.

The Indianapolis Flux Experiment (INFLUX): A test-bed for developing urban greenhouse gas emission measurements

The objective of the Indianapolis Flux Experiment (INFLUX) is to develop, evaluate and improve methods for measuring greenhouse gas (GHG) emissions from cities. INFLUX's scientific objectives are to quantify CO2 and CH4 emission rates at 1 km resolution with a 10% or better accuracy and precision, to determine whole-city emissions with similar skill, and to achieve high (weekly or finer) temporal resolution at both spatial resolutions. The experiment employs atmospheric GHG measurements from both towers and aircraft, atmospheric transport observations and models, and activity-based inventory products to quantify urban GHG emissions. Multiple, independent methods for estimating urban emissions are a central facet of our experimental design. INFLUX was initiated in 2010 and measurements and analyses are ongoing. To date we have quantified urban atmospheric GHG enhancements using aircraft and towers with measurements collected over multiple years, and have estimated whole-city CO2 and CH4 emissions using aircraft and tower GHG measurements, and inventory methods. Significant differences exist across methods; these differences have not yet been resolved; research to reduce uncertainties and reconcile these differences is underway. Sectorally- and spatially-resolved flux estimates, and detection of changes of fluxes over time, are also active research topics. Major challenges include developing methods for distinguishing anthropogenic from biogenic CO2 fluxes, improving our ability to interpret atmospheric GHG measurements close to urban GHG sources and across a broader range of atmospheric stability conditions, and quantifying uncertainties in inventory data products. INFLUX data and tools are intended to serve as an open resource and test bed for future investigations. Well-documented, public archival of data and methods is under development in support of this objective.

Direct and Indirect Measurements and Modeling of Methane Emissions in Indianapolis, Indiana

This paper describes process-based estimation of CH4 emissions from sources in Indianapolis, IN and compares these with atmospheric inferences of whole city emissions. Emissions from the natural gas distribution system were estimated from measurements at metering and regulating stations and from pipeline leaks. Tracer methods and inverse plume modeling were used to estimate emissions from the major landfill and wastewater treatment plant. These direct source measurements informed the compilation of a methane emission inventory for the city equal to 29 Gg/yr (5% to 95% confidence limits, 15 to 54 Gg/yr). Emission estimates for the whole city based on an aircraft mass balance method and from inverse modeling of CH4 tower observations were 41 ± 12 Gg/yr and 81 ± 11 Gg/yr, respectively. Footprint modeling using 11 days of ethane/methane tower data indicated that landfills, wastewater treatment, wetlands, and other biological sources contribute 48% while natural gas usage and other fossil fuel sources contribute 52% of the city total. With the biogenic CH4 emissions omitted, the top-down estimates are 3.5-6.9 times the nonbiogenic city inventory. Mobile mapping of CH4 concentrations showed low level enhancement of CH4 throughout the city reflecting diffuse natural gas leakage and downstream usage as possible sources for the missing residual in the inventory.

Reconciling divergent estimates of oil and gas methane emissions

Published estimates of methane emissions from atmospheric data (top-down approaches) exceed those from source-based inventories (bottom-up approaches), leading to conflicting claims about the climate implications of fuel switching from coal or petroleum to natural gas. Based on data from a coordinated campaign in the Barnett Shale oil and gas-producing region of Texas, we find that top-down and bottom-up estimates of both total and fossil methane emissions agree within statistical confidence intervals (relative differences are 10% for fossil methane and 0.1% for total methane). We reduced uncertainty in top-down estimates by using repeated mass balance measurements, as well as ethane as a fingerprint for source attribution. Similarly, our bottom-up estimate incorporates a more complete count of facilities than past inventories, which omitted a significant number of major sources, and more effectively accounts for the influence of large emission sources using a statistical estimator that integrates observations from multiple ground-based measurement datasets. Two percent of oil and gas facilities in the Barnett accounts for half of methane emissions at any given time, and high-emitting facilities appear to be spatiotemporally variable. Measured oil and gas methane emissions are 90% larger than estimates based on the US Environmental Protection Agency's Greenhouse Gas Inventory and correspond to 1.5% of natural gas production. This rate of methane loss increases the 20-y climate impacts of natural gas consumed in the region by roughly 50%.

Direct measurements show decreasing methane emissions from natural gas local distribution systems in the United States

Fugitive losses from natural gas distribution systems are a significant source of anthropogenic methane. Here, we report on a national sampling program to measure methane emissions from 13 urban distribution systems across the U.S. Emission factors were derived from direct measurements at 230 underground pipeline leaks and 229 metering and regulating facilities using stratified random sampling. When these new emission factors are combined with estimates for customer meters, maintenance, and upsets, and current pipeline miles and numbers of facilities, the total estimate is 393 Gg/yr with a 95% upper confidence limit of 854 Gg/yr (0.10% to 0.22% of the methane delivered nationwide). This fraction includes emissions from city gates to the customer meter, but does not include other urban sources or those downstream of customer meters. The upper confidence limit accounts for the skewed distribution of measurements, where a few large emitters accounted for most of the emissions. This emission estimate is 36% to 70% less than the 2011 EPA inventory, (based largely on 1990s emission data), and reflects significant upgrades at metering and regulating stations, improvements in leak detection and maintenance activities, as well as potential effects from differences in methodologies between the two studies.

Methane emissions from process equipment at natural gas production sites in the United States: liquid unloadings

Methane emissions from liquid unloadings were measured at 107 wells in natural gas production regions throughout the United States. Liquid unloadings clear wells of accumulated liquids to increase production, employing a variety of liquid lifting mechanisms. In this work, wells with and without plunger lifts were sampled. Most wells without plunger lifts unload less than 10 times per year with emissions averaging 21,000-35,000 scf methane (0.4-0.7 Mg) per event (95% confidence limits of 10,000-50,000 scf/event). For wells with plunger lifts, emissions averaged 1000-10,000 scf methane (0.02-0.2 Mg) per event (95% confidence limits of 500-12,000 scf/event). Some wells with plunger lifts are automatically triggered and unload thousands of times per year and these wells account for the majority of the emissions from all wells with liquid unloadings. If the data collected in this work are assumed to be representative of national populations, the data suggest that the central estimate of emissions from unloadings (270 Gg/yr, 95% confidence range of 190-400 Gg) are within a few percent of the emissions estimated in the EPA 2012 Greenhouse Gas National Emission Inventory (released in 2014), with emissions dominated by wells with high frequencies of unloadings.

Development of a regional-scale pollen emission and transport modeling framework for investigating the impact of climate change on allergic airway disease

Exposure to bioaerosol allergens such as pollen can cause exacerbations of allergenic airway disease (AAD) in sensitive populations, and thus cause serious public health problems. Assessing these health impacts by linking the airborne pollen levels, concentrations of respirable allergenic material, and human allergenic response under current and future climate conditions is a key step toward developing preventive and adaptive actions. To that end, a regional-scale pollen emission and transport modeling framework was developed that treats allergenic pollens as non-reactive tracers within the WRF/CMAQ air-quality modeling system. The Simulator of the Timing and Magnitude of Pollen Season (STaMPS) model was used to generate a daily pollen pool that can then be emitted into the atmosphere by wind. The STaMPS is driven by species-specific meteorological (temperature and/or precipitation) threshold conditions and is designed to be flexible with respect to its representation of vegetation species and plant functional types (PFTs). The hourly pollen emission flux was parameterized by considering the pollen pool, friction velocity, and wind threshold values. The dry deposition velocity of each species of pollen was estimated based on pollen grain size and density. An evaluation of the pollen modeling framework was conducted for southern California for the period from March to June 2010. This period coincided with observations by the University of Southern California's Children's Health Study (CHS), which included O₃, PM_2.5, and pollen count, as well as measurements of exhaled nitric oxide in study participants. Two nesting domains with horizontal resolutions of 12 km and 4 km were constructed, and six representative allergenic pollen genera were included: birch tree, walnut tree, mulberry tree, olive tree, oak tree, and brome grasses. Under the current parameterization scheme, the modeling framework tends to underestimate walnut and peak oak pollen concentrations, and tends to overestimate grass pollen concentrations. The model shows reasonable agreement with observed birch, olive, and mulberry tree pollen concentrations. Sensitivity studies suggest that the estimation of the pollen pool is a major source of uncertainty for simulated pollen concentrations. Achieving agreement between emission modeling and observed pattern of pollen releases is the key for successful pollen concentration simulations.

Predicting Dendroctonus pseudotsugae (Coleoptera: Curculionidae) antiaggregation pheromone concentrations using an instantaneous puff dispersion model

An instantaneous puff dispersion model was used to assess concentration fields of the Douglas-fir beetle, Dendroctonus pseudotsugae Hopkins, antiaggregation pheromone, 3-methylcyclohex-2-en-1-one (MCH), within a 1-ha circular plot. Several combinations of MCH release rate and releaser spacing were modeled to theoretically analyze optimal deployment strategies. The combinations of MCH release rate and releaser spacing used in the modeling exercise were based on results of previous field studies of treatment efficacy. Analyses of model results suggest that a release rate up to six times the initial standard, at a correspondingly wider spacing to keep the total amount of pheromone dispersed per unit area constant, may be effective at preventing Douglas-fir beetle infestation. The model outputs also provide a visual representation of pheromone dispersion patterns that can occur after deployment of release devices in the field. These results will help researchers and practitioners design more effective deployment strategies.

Modeling ozone and aerosol formation and transport in the pacific northwest with the community Multi-Scale Air Quality (CMAQ) modeling system

The Community Multi-Scale Air Quality (CMAQ) modeling system was used to investigate ozone and aerosol concentrations in the Pacific Northwest (PNW) during hot summertime conditions during July 1-15, 1996. Two emission inventories (El) were developed: emissions for the first El were based upon the National Emission Trend 1996 (NET96) database and the BEIS2 biogenic emission model, and emissions for the second El were developed through a "bottom up" approach that included biogenic emissions obtained from the GLOBEIS model. The two simulations showed that elevated PM2.5 concentrations occurred near and downwind of the Interstate-5 corridor along the foothills of the Cascade Mountains and in forested areas of central Idaho. The relative contributions of organic and inorganic aerosols varied by region, but generally organic aerosols constituted the largest fraction of PM2.5. In wilderness areas near the 1-5 corridor, organic carbon from anthropogenic sources contributed approximately 50% of the total organic carbon with the remainder from biogenic precursors, while in wilderness areas in Idaho, biogenic organic carbon accounted for 80% of the total organic aerosol. Regional analysis of the secondary organic aerosol formation in the Columbia River Gorge, Central Idaho, and the Olympics/Puget Sound showed that the production rate of secondary organic carbon depends on local terpene concentrations and the local oxidizing capacity of the atmosphere, which was strongly influenced by anthropogenic emissions. Comparison with observations from 12 IMPROVE sites and 21 ozone monitoring sites showed that results from the two El simulations generally bracketed the average observed PM parameters and that errors calculated for the model results were within acceptable bounds. Analysis across all statistical parameters indicated that the NW-AIRQUEST El solution performed better at predicting PM2.5, PM1, and beta(ext) even though organic carbon PM was over-predicted, and the NET96 El solution performed better with regard to the inorganic aerosols. For the NW-AIRQUEST El solution, the normalized bias was 30% and the normalized absolute error was 49% for PM2.5 mass. The NW-AIRQUEST solution slightly overestimated peak hourly ozone downwind of urban areas, while the NET96 solution slightly underestimated peak values, and both solutions over-predicted average 03 concentrations across the domain by approximately 6 ppb.

Intercomparison of the community multiscale air quality model and CALGRID using process analysis

This study was designed to examine the similarities and differences between two advanced photochemical air quality modeling systems: EPA Models-3/CMAQ and CALGRID/CALMET. Both modeling systems were applied to an ozone episode that occurred along the I-5 urban corridor in western Washington and Oregon during July 11-14, 1996. Both models employed the same modeling domain and used the same detailed gridded emission inventory. The CMAQ model was run using both the CB-IV and RADM2 chemical mechanisms, while CALGRID was used with the SAPRC-97 chemical mechanism. Outputfrom the Mesoscale Meteorological Model (MM5) employed with observational nudging was used in both models. The two modeling systems, representing three chemical mechanisms and two sets of meteorological inputs, were evaluated in terms of statistical performance measures for both 1- and 8-h average observed ozone concentrations. The results showed that the different versions of the systems were more similar than different, and all versions performed well in the Portland region and downwind of Seattle but performed poorly in the more rural region north of Seattle. Improving the meteorological input into the CALGRID/CALMET system with planetary boundary layer (PBL) parameters from the Models-3/CMAQ meteorology preprocessor (MCIP) improved the performance of the CALGRID/CALMET system. The 8-h ensemble case was often the best performer of all the cases indicating that the models perform better over longer analysis periods. The 1-h ensemble case, derived from all runs, was not necessarily an improvement over the five individual cases, but the standard deviation about the mean provided a measure of overall modeling uncertainty. Process analysis was applied to examine the contribution of the individual processes to the species conservation equation. The process analysis results indicated that the two modeling systems arrive at similar solutions by very different means. Transport rates are faster and exhibit greater fluctuations in the CMAQ cases than in the CALGRID cases, which lead to different placement of the urban ozone plumes. The CALGRID cases, which rely on the SAPRC97 chemical mechanism, exhibited a greater diurnal production/loss cycle of ozone concentrations per hour compared to either the RADM2 or CBIV chemical mechanisms in the CMAQ cases. These results demonstrate the need for specialized process field measurements to confirm whether we are modeling ozone with valid processes.

Characterization of urban pollutant emission fluxes and ambient concentration distributions using a mobile laboratory with rapid response instrumentation

A large and increasing fraction of the planet's population lives in megacities, especially in the developing world. These large metropolitan areas generally have very high levels of both gaseous and particulate air pollutants that have severe impacts on human health, ecosystem viability, and climate on local, regional, and even continental scales. Emissions fluxes and ambient pollutant concentration distributions are generally poorly characterized for large urban areas even in developed nations. Much less is known about pollutant sources and concentration patterns in the faster growing megacities of the developing world. New methods of locating and measuring pollutant emission sources and tracking subsequent atmospheric chemical transformations and distributions are required. Measurement modes utilizing an innovative van based mobile laboratory equipped with a suite of fast response instruments to characterize the complex and "nastier" chemistry of the urban boundary layer are described. Instrumentation and measurement strategies are illustrated with examples from the Mexico City and Boston metropolitan areas. It is shown that fleet average exhaust emission ratios of formaldehyde (HCHO), acetaldehyde (CH3CHO) and benzene (C6H6) are substantial in Mexico City, with gasoline powered vehicles emitting higher levels normalized by fuel consumption. NH3 exhaust emissions from newer light duty vehicles in Mexico City exceed levels from similar traffic in Boston. A mobile conditional sampling air sample collection mode designed to collect samples from intercepted emission plumes for later analysis is also described.

The influence of atmospheric pressure on landfill methane emissions

Landfills are the largest source of anthropogenic methane (CH4) emissions to the atmosphere in the United States. However, few measurements of whole landfill CH4 emissions have been reported. Here, we present the results of a multi-season study of whole landfill CH4 emissions using atmospheric tracer methods at the Nashua, New Hampshire Municipal landfill in the northeastern United States. The measurement data include 12 individual emission tests, each test consisting of 5-8 plume measurements. Measured emissions were negatively correlated with surface atmospheric pressure and ranged from 7.3 to 26.5 m3 CH4 min(-1). A simple regression model of our results was used to calculate an annual emission rate of 8.4 x 10(6) m3 CH4 year(-1). These data, along with CH4 oxidation estimates based on emitted landfill gas isotopic characteristics and gas collection data, were used to estimate annual CH4 generation at this landfill. A reported gas collection rate of 7.1 x 10(6) m3 CH4 year(-1) and an estimated annual rate of CH4 oxidation by cover soils of 1.2 x 10(6) m3 CH4 year(-1) resulted in a calculated annual CH4 generation rate of 16.7 x 10(6) m3 CH4 year(-1). These results underscore the necessity of understanding a landfill's dynamic environment before assessing long-term emissions potential.

The effect of oilseeds in diets of lactating cows on milk production and methane emissions

Thirty-six lactating multiparous Holstein cows were assigned to diets that contained 2.3, 4.0, and 5.6% fat for an entire lactation to determine the effect of oilseeds on milk composition, production, and methane emissions. The diets were formulated so that whole cottonseeds and canola oilseeds provided equal amounts of added fat. Methane emissions were measured every 3 mo from two replicates of four cows per treatment using a room tracer approach. Dry matter intakes and yields of milk and FCM were greater for cows fed the diets containing oilseeds. Although the concentration of protein in milk was reduced, yields of both protein and fat tended to be increased by the addition of fat. Within the milk fat, the concentrations of C10, C12, C14:0, and C16:0 were reduced and concentrations of C18, C18:1, and trans-C18:1 were increased in response to dietary oilseeds. In serum, urea-N was increased by the dietary oilseeds. Supplementation of diets with oilseeds did not affect methane emissions but tended to increase the efficiency of milk produced per unit of methane emitted. A 1.7% addition of fat to the control diet from a combination of oilseed types increased yields of milk without reducing methane emission rates. The strategy of using unsaturated fats from oilseeds to substantially reduce methane emissions was ineffective, although yield of milk was increased.