Uncertainties In Emission Factors Research Articles

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.

Uncertainty in estimating and mitigating industrial related GHG emissions

Global climate change has been one of the challenging environmental concerns facing policy makers in the past decade. The characterization of the wide range of greenhouse gas emissions sources and sinks as well as their behavior in the atmosphere remains an on-going activity in many countries. Lebanon, being a signatory to the Framework Convention on Climate Change, is required to submit and regularly update a national inventory of greenhouse gas emissions sources and removals. Accordingly, an inventory of greenhouse gases from various sectors was conducted following the guidelines set by the United Nations Intergovernmental Panel on Climate Change (IPCC). The inventory indicated that the industrial sector contributes about 29 percent to the total greenhouse gas emissions divided between industrial processes and energy requirements at 12 and 17 percent, respectively. This paper describes major mitigation scenarios to reduce emissions from this sector based on associated technical, economic, environmental, and social characteristics. Economic ranking of these scenarios was conducted and uncertainty in emission factors used in the estimation process was emphasized. For this purpose, theoretical and experimental emission factors were used as alternatives to default factors recommended by the IPCC and the significance of resulting deviations in emission estimation is presented.

Long-term continuous measurements of air pollutant concentrations, meteorology and traffic on a rural motorway and a model validation

Air concentrations of carbon monoxide (CO), nitrogen oxide (NO) and nitrogen dioxide (NO 2) were continuously monitored at a rural motorway site in Sweden for the period February–December 1990. In addition, local meteorology and traffic parameters were measured in order to validate a dispersion model. Even close to the motorway, the concentrations of CO and NO 2 were well below Swedish air quality guidelines. For long-term averages the regional background contributed significantly to the downwind levels. The atmospheric reaction between primary emitted NO and background ozone (O 3) tends to be a major source of downwind NO 2, also fairly close to the road (10 m from the road shoulder), where the average NO 2/NO x ratio was approximately 0.4. The validated model employs a percentile analysis on the basis of the HIWAY-2 and CALINE4 models and a separate emission model. The agreement between measured and modelled data, as refered to the 98th percentile, was good for NO 2 but moderate for CO. This is probably partly caused by uncertainties in emission factors for CO for heavy vehicles. Since a good agreement was observed between measured and calculated NO x concentrations, problems in adequately modelling NO 2 are probably associated with uncertainties as to NO 2/NO x ratios in the exhaust, or the modelling of the O 3 reaction.