Air Emission Inventories in North America: A Critical Assessment

Abstract

Although emission inventories are the foundation of air quality management and have supported substantial improvements in North American air quality, they have a number of shortcomings that can potentially lead to ineffective air quality management strategies. Major reductions in the largest emissions sources have made accurate inventories of previously minor sources much more important to the understanding and improvement of local air quality. Changes in manufacturing processes, industry types, vehicle technologies, and metropolitan infrastructure are occurring at an increasingly rapid pace, emphasizing the importance of inventories that reflect current conditions. New technologies for measuring source emissions and ambient pollutant concentrations, both at the point of emissions and from remote platforms, are providing novel approaches to collecting data for inventory developers. Advances in information technologies are allowing data to be shared more quickly, more easily, and processed and compared in novel ways that can speed the development of emission inventories. Approaches to improving quantitative measures of inventory uncertainty allow air quality management decisions to take into account the uncertainties associated with emissions estimates, providing more accurate projections of how well alternative strategies may work. This paper discusses applications of these technologies and techniques to improve the accuracy, timeliness, and completeness of emission inventories across North America and outlines a series of eight recommendations aimed at inventory developers and air quality management decision-makers to improve emission inventories and enable them to support effective air quality management decisions for the foreseeable future.     

Modeling of mercury emission,transport and deposition in North America

Most studies on the atmospheric behaviour of mercury in North America have excluded a detailed treatment of natural mercury emissions. The objective of this work is to report a detailed simulation of the atmospheric mercury in a domain that covers a significant part of North America and includes not only anthropogenic mercury emissions but also those from natural sources including vegetation, soil and water.The simulations were done using a natural mercury emission model coupled with the US EPA's SMOKE/CMAQ modelling system. The domain contained 132×90 grid cells at a resolution of 36 km, covering the continental United States, and major parts of Canada and Mexico. The simulation was carried out for 2002, using boundary conditions from a global mercury model. Estimated total natural mercury emission in the domain was 230 tonnes (1 tonne=1000 kg) and the ratio of natural to anthropogenic emissions varied from 0.7 in January to 3.2 in July. Average total gaseous mercury (TGM) concentration ranged between 1 and 4 ng m⁻³. Good agreement was found between the modelled results and measurements at three Ontario sites for ambient mercury concentrations, and at 72 mercury deposition network sites in the domain for wet deposition. The correlation coefficient between the simulated and the measured values of the daily average TGM at three monitoring sites varied between 0.48 and 0.64. When natural emissions were omitted, the correlation coefficients dropped to between 0.15 and 0.40. About 335 tonnes of mercury were deposited in the domain during the simulation period but overall, it acted as a net source of mercury and contributed about 21 tonnes to the global pool. The net deposition of mercury to the Great Lakes was estimated to be about 2.4 tonnes. The estimated deposition values were similar to those reported by other researchers.     

BETR North America: a regionally segmented multimedia contaminant fate model for North America

We present the Berkeley-Trent North American contaminant fate model (BETR North America), a regionally segmented multimedia contaminant fate model based on the fugacity concept. The model is built on a framework that links contaminant fate models of individual regions, and is generally applicable to large, spatially heterogeneous areas. The North American environment is modeled as 24 ecological regions, within each region contaminant fate is described using a 7 compartment multimedia fugacity model including a vertically segmented atmosphere, freshwater, freshwater sediment, soil, coastal water and vegetation compartments. Inter-regional transport of contaminants in the atmosphere, freshwater and coastal water is described using a database of hydrological and meteorological data compiled with Geographical Information Systems (GIS) techniques. Steady-state and dynamic solutions to the 168 mass balance equations that make up the linked model for North America are discussed, and an illustrative case study of toxaphene transport from the southern United States to the Great Lakes Basin is presented. Regionally segmented models such as BETR North America can provide a critical link between evaluative models of long-range transport potential and contaminant concentrations observed in remote regions. The continent-scale mass balance calculated by the model provides a sound basis for evaluating long-range transport potential of organic pollutants, and formulation of continent-scale management and regulatory strategies for chemicals.     

Primary sources of selected POPs: regional and global scale emission inventories

During the last decade, a number of studies have been devoted to the sources and emissions of Persistent Organic Pollutants (POPs) at regional and global scales. While significant improvements in knowledge have been achieved for some pesticides, the quantitative understanding of the emission processes and emission patterns for "non-pesticide" POPs are still considered limited. The key issues remaining for the non-pesticide POPs are in part determined by their general source classification. For industrial chemicals, such as the polychlorinated biphenyls (PCBs), there is considerable uncertainty with respect to the relative importance of atmospheric emissions from various source categories. For PCBs, temperature is discussed as a potential key factor influencing atmospheric emission levels and patterns. When it comes to the unintentional by-products of combustion and industrial processes (PCDD/Fs), there is still a large uncertainty with respect to the relative contribution of emissions from unregulated sources such as backyard barrel burning that requires further consideration and characterisation. For hexachlorobenzene (HCB), the relative importance of primary and secondary atmospheric emissions in controlling current atmospheric concentrations remains one of the key uncertainties. While these and other issues may remain unresolved, knowledge concerning the emissions of POPs is a prerequisite for any attempt to understand and predict the distribution and fate of these chemicals on a regional and global scale as well as to efficiently minimise future environmental burdens.     

Assessing the uncertainty associated with national greenhouse gas emission inventories:: a case study for Austria

The uncertainty associated with the Austrian Greenhouse Gas emission inventory has been determined for the gases CO₂, CH₄ and N₂O and for the overall greenhouse potential. Expert interviews were conducted to obtain uncertainties in inventory input data. Based on these interviews, error distributions were developed and combined using Monte-Carlo analysis. Results for all sources and gases combined indicate an overall uncertainty between 10.5% and 12% depending on the base year considered. Excluding emissions and the uncertainty associated with forest sinks and natural sources, overall uncertainty decreased by 2% points. The mere ‘random error’, which is considered the level of uncertainty to be achieved with the current methodology (excluding all systematic errors) is 5% points lower. Detailed evaluation shows that much of the overall uncertainty derives from a lack of understanding the processes associated with N₂O emissions from soils. Other important contributors to GHG emission uncertainties are CH₄ from landfills and forests as CO₂ sinks. The uncertainty of the trend has been determined at near 5% points, with solid waste production (landfills) having the strongest contribution. Theoretical considerations do not permit a decrease of the trend uncertainty—even when forest sinks are not considered—below 3% points.     

Estimation of vehicular emission inventories in China from 1980 to 2005

Multi-year inventories of vehicular emissions at a high spatial resolution of 40 km×40 km were established in China using the GIS methodology for the period 1980–2005, based on provincial statistical data from yearbooks regarding vehicles and roads, and on the emission factors for each vehicle category in each province calculated by COPERT III program. Results showed that the emissions of CH₄, CO, CO₂, NMVOC, NO_x, PM₁₀, and SO₂ increased from 5, 1066, 19 893, 169, 174, 26, and 16 thousand tons in 1980 to 377, 36 197, 674 629, 5911, 4539, 983, and 484 thousand tons in 2005 at an annual average rate of 19%, 15%, 15%, 15%, 14%, 16%, and 15%, respectively. Statistical analysis of vehicular emissions and GDP showed that they were well positively correlated, which revealed that increase of pollutant emissions has been accompanying the growth of GDP. Spatial distribution of pollutant emissions was rather unbalanced: over three-quarters of the total emissions concentrated in developed regions of China's southeastern, northern and central areas covering only 35.2% of China's territory, while the remaining emissions were distributed over the southwestern, northwestern and northeastern regions covering as much as 64.8% of the territory. In 2005, the Beijing–Tianjin–Hebei region, the Yangtze River Delta, and the Pearl River Delta covering only 2.3%, 2.2%, and 1.9%, respectively, of the territory, generated about 10%, 19%, and 12%, respectively, of the total emissions. Since 1990, motorcycles have been the major contributors to the CH₄, CO, NMVOC, and PM₁₀ emissions, due to the large population. Heavy-duty vans were the major contributors to the NO_x and SO₂ emissions because of high emission factors. Passenger cars contributed about one third of the emissions of each pollutant. Contributions of vehicle categories to emissions varied from province to province, due to the diversity of vehicle compositions among provinces.     

Tree decline in North America

Air-borne, phytotoxic pollutants are known to adversely affect forest tree growth in North America. On a local scale, exposure to high concentrations of toxic gases, such as sulphur dioxide and fluoride, result in foliar injury, branch dieback, reduced radial growth and increased mortality in a variety of tree species. On a regional scale, the photochemical oxidant, ozone, is responsible for growth decline of pollutant-sensitive eastern white pine genotypes in the eastern United States, and of ponderosa and Jeffrey pines in the mountains of southern and central California. The etiology associated with the reported declines of high elevation red spruce in the Appalachian Mountains and of sugar maple in the northeastern United States and southeastern Canada is incompletely known at present. A complex of predisposing and inciting factors, including temperature and moisture stress, edaphic conditions, aluminium toxicity, insect depredation, and air-borne pollutants are probably involved in these declines.     

The role of bio-mechanical treatments of waste in the dioxin emission inventories

PCDD/Fs are one of the most studied molecules in the world because of their toxicity. In the last years the toxicity of these compounds has been analyzed in details. For years PCDD/F inventories have pointed out the significant role of municipal solid waste (MSW) incinerators in the overall balance. Recently, thanks to new regulations on PCDD/F emissions, in a few countries this scenario is changing: it can be demonstrated that modern MSW incinerators can play a secondary role even if the percentage of MSW sent to combustion has increased. In the latest inventories an unconventional source of PCDD/F has appeared: in nineties some biogas characterizations have demonstrated that there is a release of PCDD/F from MSW sanitary landfills. In addition, the combustion of collected biogas can generate not negligible amounts of PCDD/F. A new question can be put: does the MSW contribute with other management options to the overall balance of PCDD/F? The present work points out that a detailed inventory should take into account also the PCDD/F release from bio-mechanical treatment plants (both composting and bio-drying/bio-stabilization plants). However the contribution from this option is secondary when it is compared with the one from old MSW incinerators.     

Forest health conditions in North America

Some of the greatest forest health impacts in North America are caused by invasive forest insects and pathogens (e.g., emerald ash borer and sudden oak death in the US), by severe outbreaks of native pests (e.g., mountain pine beetle in Canada), and fires exacerbated by changing climate. Ozone and N and S pollutants continue to impact the health of forests in several regions of North America. Long-term monitoring of forest health indicators has facilitated the assessment of forest health and sustainability in North America. By linking a nationwide network of forest health plots with the more extensive forest inventory, forest health experts in the US have evaluated current trends for major forest health indicators and developed assessments of future risks. Canada and Mexico currently lack nationwide networks of forest health plots. Development and expansion of these networks is critical to effective assessment of future forest health impacts.     

Improving the accuracy of emission inventories with a machine-learning approach and investigating transferability across cities

ABSTRACT

This study presents a novel method for integrating the output of a microscopic emission modeling approach with a regional traffic assignment model in order to achieve an accurate greenhouse gas (GHG, in CO_2-eq) emission estimate for transportation in large metropolitan regions. The CLustEr-based Validated Emission Recalculation (CLEVER) method makes use of instantaneous speed data and link-based traffic characteristics in order to refine on-road GHG inventories. The CLEVER approach first clusters road links based on aggregate traffic characteristics, then assigns representative emission factors (EFs), calibrated using the output of microscopic emission modeling. In this paper, cluster parameters including number and feature vector were calibrated with different sets of roads within the Greater Toronto Area (GTA), while assessing the spatial transferability of the algorithm. Using calibrated cluster sets, morning peak GHG emissions in the GTA were estimated to be 2,692 tons, which is lower than the estimate generated by a traditional, average speed approach (3,254 tons). Link-level comparison between CLEVER and the average speed approach demonstrates that GHG emissions for uncongested links were overestimated by the average speed model. In contrast, at intersections and ramps with more congested links and interrupted traffic flow, the average speed model underestimated GHG emissions. This proposed approach is able to capture variations in traffic conditions compared to the traditional average speed approach, without the need to conduct traffic simulation.

Implications: A reliable traffic emissions estimate is necessary to evaluate transportation policies. Currently, accuracy and transferability are major limitations in modeling regional emissions. This paper develops a hybrid modeling approach (CLEVER) to bridge between computational efficiency and estimation accuracy. Using a k-means clustering algorithm with street-level traffic data, CLEVER generates representative emission factors for each cluster. The approach was validated against the baseline (output of a microscopic emission model), demonstrating transferability across different cities .     

Comparison of models used for national agricultural ammonia emission inventories in Europe: Litter-based manure systems

Six N-flow models, used to calculate national ammonia (NH₃) emissions from agriculture in different European countries, were compared using standard data sets. Scenarios for litter-based systems were run separately for beef cattle and for broilers, with three different levels of model standardisation: (a) standardized inputs to all models (FF scenario); (b) standard N excretion, but national values for emission factors (EFs) (FN scenario); (c) national values for N excretion and EFs (NN scenario). Results of the FF scenario for beef cattle produced very similar estimates of total losses of total ammoniacal-N (TAN) (±6% of the mean total), but large differences in NH₃ emissions (±24% of the mean). These differences arose from the different approaches to TAN immobilization in litter, other N losses and mineralization in the models. As a result of those differences estimates of TAN available at spreading differed by a factor of almost 3. Results of the FF scenario for broilers produced a range of estimates of total changes in TAN (±9% of the mean total), and larger differences in the estimate of NH₃ emissions (±17% of the mean). The different approaches among the models to TAN immobilization, other N losses and mineralization, produced estimates of TAN available at spreading which differed by a factor of almost 1.7. The differences in estimates of NH₃ emissions decreased as estimates of immobilization and other N losses increased. Since immobilization and denitrification depend also on the C:N ratio in manure, there would be advantages to include C flows in mass-flow models. This would also provide an integrated model for the estimation of emissions of methane, non-methane VOCs and carbon dioxide. Estimation of these would also enable an estimate of mass loss, calculation of the N and TAN concentrations in litter-based manures and further validation of model outputs.     

Organic acidity in precipitation of North America

Organic anions were measured in 16 precipitation events sampled in central Virginia between 25 April and 1 October 1983. Formic and acetic acids contributed 16% of volume weighted free acidity. The decrease in free acidity in stored aliquots was directly proportional to the disappearance of dissociated HCOO⁻ and CH₃COO⁻. The loss of free acidity between pH measured at field sites and at central laboratories was used to estimate dissociated organic acidity in samples collected by the National Atmospheric Deposition Program (NADP) and the MAP3S Precipitation Chemistry Project. Based on the arithmetic means of the volume weighted averages for each site, we estimate that organic acids contributed 18–35% of free acidity in NADP samples and 16% of free acidity in MAP3S samples. The loss of free acidity in MAP3S samples was three times greater during the growing season than it was during the rest of the year. Because they are rapidly assimilated by microbes, organic acids are unimportant in the long-term acidification of the environment.     

Temporal and spatial distribution of atmospheric antimony emission inventories from coal combustion in China

A multiple-year inventory of atmospheric antimony (Sb) emissions from coal combustion in China for the period of 1980-2007 has been calculated for the first time. Specifically, the emission inventories of Sb from 30 provinces and 4 economic sectors (thermal power, industry, residential use, and others) are evaluated and analyzed in detail. It shows that the total Sb emissions released from coal combustion in China have increased from 133.19 t in 1980 to 546.67 t in 2007, at an annually average growth rate of 5.4%. The antimony emissions are largely emitted by industrial sector and thermal power generation sector, contributing 53.6% and 26.9% of the totals, respectively. At provincial level, the distribution of Sb emissions shows significant variation. Between 2005 and 2007, provinces always rank at the top five largest Sb emissions are: Guizhou, Hunan, Hebei, Shandong, and Anhui.     

Sensor transition failure in the high flow sampler: Implications for methane emission inventories of natural gas infrastructure

Quantification of leaks from natural gas (NG) infrastructure is a key step in reducing emissions of the greenhouse gas methane (CH₄), particularly as NG becomes a larger component of domestic energy supply. The U.S. Environmental Protection Agency (EPA) requires measurement and reporting of emissions of CH₄ from NG transmission, storage, and processing facilities, and the high-flow sampler (or high-volume sampler) is one of the tools approved for this by the EPA. The Bacharach Hi-Flow Sampler (BHFS) is the only commercially available high-flow instrument, and it is also used throughout the NG supply chain for directed inspection and maintenance, emission factor development, and greenhouse gas reduction programs. Here we document failure of the BHFS to transition from a catalytic oxidation sensor used to measure low NG (~5% or less) concentrations to a thermal conductivity sensor for higher concentrations (from ~5% to 100%), resulting in underestimation of NG emission rates. Our analysis includes both our own field testing and analysis of data from two other studies (Modrak et al., 2012; City of Fort Worth, 2011). Although this failure is not completely understood, and although we do not know if all BHFS models are similarly affected, sensor transition failure has been observed under one or more of these conditions: (1) Calibration is more than ~2 weeks old; (2) firmware is out of date; or (3) the composition of the NG source is less than ~91% CH₄. The extent to which this issue has affected recent emission studies is uncertain, but the analysis presented here suggests that the problem could be widespread. Furthermore, it is critical that this problem be resolved before the onset of regulations on CH₄ emissions from the oil and gas industry, as the BHFS is a popular instrument for these measurements.

Implications: An instrument commonly used to measure leaks in natural gas infrastructure has a critical sensor transition failure issue that results in underestimation of leaks, with implications for greenhouse gas emissions estimates as well as safety.     

Organic nitrogen in precipitation over Eastern North America

A measurement technique was developed to reliably quantify organic nitrogen (ON) in ambient, wet-only precipitation. Samples were frozen during collection and subsequently divided into two aliquots. One set was stored at −170°C and analyzed for total N (TN) via high-temperature combustion to NO and detection by chemiluminescence; the other set was sterilized with CHCl₃, stored refrigerated, and analyzed for NH₄⁺ by automated colorimetry and for NO₃⁻, and NO₂⁻ by ion chromatography. ON was inferred by difference. Analysis of paired, untreated aliquots stored for 30 and 41 days at different temperatures revealed substantial conversion of NH₄⁺ to ON at room temperature and significant losses (16% and 23%) of NH₄⁺ (presumably to biota growing on bottle walls) in refrigerated samples. Analytes in frozen and sterilized samples were stable. Volume-weighted ON concentrations for precipitation sampled at Charlottesville, Virginia (VA), Newark, Delaware (DE), and New Castle, New Hampshire (NH; 3.1, 4.2, and 0.6 μM N, respectively) and corresponding contributions to volume-weighted TN (6.5%, 7.8%, and 2.6%, respectively) are at the lower limit of published values for eastern North America and elsewhere. Methodological differences contribute to the apparent variability among these reported sample statistics. Volume-weighted ON concentrations were generally highest during spring and were lowest during summer. Due to the combined influence of unmeasured ON and loss of NH₄⁺ from inadequately preserved samples, current estimates for the wet deposition of atmospheric N to eastern North America based on data from national networks may be underestimated by 10–20%.     

Quantification of variability and uncertainty in air pollutant emission inventories: method and case study for utility NOx emissions

The quality of stationary source emission factors is typically described using data quality ratings, which provide no quantification of the precision of the emission factor for an average source, nor of the variability from one source to another within a category. Variability refers to actual differences caused by differences in feedstock composition, design, maintenance, and operation. Uncertainty refers to lack of knowledge regarding the true emissions. A general methodology for the quantification of variability and uncertainty in emission factors, activity factors, and emission inventories (EIs) is described, featuring the use of bootstrap simulation and related techniques. The methodology is demonstrated via a case study for a selected example of NOx emissions from coal-fired power plants. A prototype software tool was developed to implement the methodology. The range of interunit variability in selected activity and emission factors was shown to be as much as a factor of 4, and the range of uncertainty in mean emissions is shown to depend on the interunit variability and sample size. The uncertainty in the total inventory of -16 to +19% was attributed primarily to one technology group, suggesting priorities for collecting data and improving the inventory. The implications for decision-making are discussed.     

Spatial disaggregation of traffic emission inventories in large cities using simplified top–down methods

Simple, inexpensive and accurate methods for assessing the spatial distribution of traffic emissions are badly needed for the environmental management in South American cities. In this study, various spatial disaggregation methods of traffic emissions of carbon monoxide are presented and evaluated for a large city (Santiago de Chile). Previous methods have used a simplified road network as a proxy for deriving spatial patterns of emissions. However, these approaches resulted in underestimation of emissions in urban centers, industrial zones and highly loaded roads, as well as overestimation in residential zones. Here we modify these methods by adding data correlated with the emissions (e.g. traffic counts, vehicles mean speed, road capacity) solving partially or completely the indicated problems. After an accuracy-simplicity analysis two methodologies stand out over the others: using traffic count classification and using a land use map, both combined with a simplified road network. Both are top–down approaches that correlate well (0.9) with the reference emissions and capture emission peaks (within 30% relative error). Hence the proposed changes allow an improved balance between accuracy and costs (monetary, availability of data and time to obtain data).