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.     

Mind the gap: Coping with delay in environmental governance

Ambio - Gaps between public policy goals and the state of the environment are often significant. However, while goal failures in environmental governance are studied in a number of disciplines, the...     

A framework for error analysis of a long-range transport model with emphasis on parameter uncertainty

A comprehensive framework for model error analysis is applied to the EMEP-W model of longrange transport of sulfur in Europe. This framework includes a proposed taxonomy of model uncertainties. Parameter uncertainties were investigated by Monte Carlo simulation of two source-receptor combinations. A 20% input parameter uncertainty (expressed as a coefficient of variation = standard deviation/mean) yielded a 15–22% output error of total sulfur deposition. The relationship between output error and input uncertainty was approximately proportional. Covariance between parameters can have an important effect on computed model error, and can either exaggerate or reduce errors compared to the uncorrelated case. Of the model state variables, SO₂ air concentration and wet deposition had the highest error, and total sulfur deposition the lowest. It was also found that it is more important to specify the dispersion of the input parameter frequency distributions than their shape. The results of the model error analysis were applied to routine calculations of deposition in Europe. An error (coefficient of variation) of 20% for transfer coefficients throughout Europe yielded spatial variations in the order of a few tens to a few hundreds of km in computed deposition isolines of 2 and 5 g sulfur m⁻²a⁻¹.     

Nitrate toxicity to aquatic animals: a review with new data for freshwater invertebrates

Published data on nitrate (NO3-) toxicity to freshwater and marine animals are reviewed. New data on nitrate toxicity to the freshwater invertebrates Eulimnogammarus toletanus, Echinogammarus echinosetosus and Hydropsyche exocellata are also presented. The main toxic action of nitrate is due to the conversion of oxygen-carrying pigments to forms that are incapable of carrying oxygen. Nitrate toxicity to aquatic animals increases with increasing nitrate concentrations and exposure times. In contrast, nitrate toxicity may decrease with increasing body size, water salinity, and environmental adaptation. Freshwater animals appear to be more sensitive to nitrate than marine animals. A nitrate concentration of 10 mg NO3-N/l (USA federal maximum level for drinking water) can adversely affect, at least during long-term exposures, freshwater invertebrates (E. toletanus, E. echinosetosus, Cheumatopsyche pettiti, Hydropsyche occidentalis), fishes (Oncorhynchus mykiss, Oncorhynchus tshawytscha, Salmo clarki), and amphibians (Pseudacris triseriata, Rana pipiens, Rana temporaria, Bufo bufo). Safe levels below this nitrate concentration are recommended to protect sensitive freshwater animals from nitrate pollution. Furthermore, a maximum level of 2 mg NO3-N/l would be appropriate for protecting the most sensitive freshwater species. In the case of marine animals, a maximum level of 20 mg NO3-N/l may in general be acceptable. However, early developmental stages of some marine invertebrates, that are well adapted to low nitrate concentrations, may be so susceptible to nitrate as sensitive freshwater invertebrates.     

Coping with Complexity,Uncertainty and Ambiguity in Risk Governance: A Synthesis

The term governance describes the multitude of actors and processes that lead to collectively binding decisions. The term risk governance translates the core principles of governance to the context of risk-related policy making. We aim to delineate some basic lessons from the insights of the other articles in this special issue for our understanding of risk governance. Risk governance provides a conceptual as well as normative basis for how to cope with uncertain, complex and/or ambiguous risks. We propose to synthesize the breadth of the articles in this special issue by suggesting some changes to the risk governance framework proposed by the International Risk Governance Council (IRGC) and adding some insights to its analytical and normative implications.     

A coupled simulation-optimization approach for groundwater remediation design under uncertainty: An application to a petroleum-contaminated site

This study provides a coupled simulation–optimization approach for optimal design of petroleum-contaminated groundwater remediation under uncertainty. Compared to the previous approaches, it has the advantages of: (1) addressing the stochasticity of the modeling parameters in simulating the flow and transport of NAPLs in groundwater, (2) providing a direct and response-rapid bridge between remediation strategies (pumping rates) and remediation performance (contaminant concentrations) through the created proxy models, (3) alleviating the computational cost in searching for optimal solutions, and (4) giving confidence levels for the obtained optimal remediation strategies. The approach is applied to a practical site in Canada for demonstrating its performance. The results show that mitigating the effects of uncertainty on optimal remediation strategies (through enhancing the confidence level) would lead to the rise of remediation cost due to the increase in the total pumping rate.     

Validation and global uncertainty of a gas chromatographic with mass spectrometry method for fenamidone analysis in grapes and wines

Fenamidone is an imidazolinone fungicide recently introduced in viticulture practices. This work reports the validation and assessment of global uncertainty of a gas chromatographic with mass spectrometry method to analyze fenamidone in grapes and wines. This method consists in a simple and fast liquid-liquid extraction step followed by chromatographic determination. Limits of detection for fenamidone in grapes and wines were, respectively, 0.05 mg/kg and 0.06 mg/L, precision was below 9.4% and average recovery was 89 +/- 5%. In the concentration range from 0.05 to 1.00 mg/kg (or mg/L) of fenamidone, global uncertainty calculated following the EURACHEM/CITAC rules, and also by the Horwitz function, was below 25%. The EURACHEM/CITAC global uncertainty budget used gave lower estimates than those obtained from the Horwitz function.     

Validation and global uncertainty of a gas chromatographic with mass spectrometry method for fenamidone analysis in grapes and wines

Fenamidone is an imidazolinone fungicide recently introduced in viticulture practices. This work reports the validation and assessment of global uncertainty of a gas chromatographic with mass spectrometry method to analyze fenamidone in grapes and wines. This method consists in a simple and fast liquid-liquid extraction step followed by chromatographic determination. Limits of detection for fenamidone in grapes and wines were, respectively, 0.05 mg/kg and 0.06 mg/L, precision was below 9.4% and average recovery was 89 ± 5%. In the concentration range from 0.05 to 1.00 mg/kg (or mg/L) of fenamidone, global uncertainty calculated following the EURACHEM/CITAC rules, and also by the Horwitz function, was below 25%. The EURACHEM/CITAC global uncertainty budget used gave lower estimates than those obtained from the Horwitz function.     

A comparison of DEMETRA individual QSARs with an index for evaluation of uncertainty

Quantitative structure-activity relationships (QSARs) urgently need to be applied in regulatory programs. Many QSAR models can predict the effect of a wide range of substances to different endpoints, particularly in the case of ecotoxicity, but it is difficult to choose the most appropriate model on the basis of the requirements of the application. During the EC-funded project DEMETRA (www.demetra-tox.net) a huge number of QSAR models have been developed for the prediction of different ecotoxicological endpoints. DEMETRA individual models on rainbow trout LC50 after 96 h, water flea LC50 after 48 h and honey bee LD50 after 48 h have been used as a QSAR database to test the advantages of a new index for evaluating model uncertainty. This index takes into consideration the number of outliers (weighted on the total number of compounds) and their root mean square error. Application on the DEMETRA QSAR database indicated that the index can identify the models with the best performance with regard to outliers, and can be used, together with other classical statistical measures (e.g., the squared correlation coefficient), to support the evaluation of QSAR models.     

Mutatox test: a new test for monitoring environmental genotoxic agents

In this study, Yamaska River water and Milli-Q water and organically extracted sediment extracts were used to evaluate the sensitivity of a new genotoxicity screening test, the Mutatox test. Also in this study, the samples were tested for acute and chronic toxicity using the following screening test procedures: Microtox, Daphnia magna, Ceriodaphnia reticulata and ATP-TOX Systems. The Mutatox test is based on the use of a dark mutant strain of Photobacterium phosphoreum and is sensitive to chemicals which are (1) DNA damaging agents (2) DNA intercalating agents, (3) DNA synthesis inhibitors and (4) direct mutagens. In this study, the Mutatox test was found to be a simple-to-perform sensitive procedure which added greater scope to the battery of tests approach. Preliminary indications are that this procedure may prove to be one of the more responsive and valuable tests in the 'battery of tests' approach to environmental screening.     

Modeling oil price uncertainty effects on economic growth in Mexico: a sector-level analysis

This paper analyzes the impact of international oil price uncertainty on the different economic sectors (primary, secondary, and tertiary) in Mexico in the period 1993:1–2020:4 through a bivariate structural vector autoregressive (VAR) model with a generalized autoregressive conditional heteroskedasticity (GARCH) in mean to capture the impact of oil volatility on economic growth at the sectoral level of economic activity. The results show that the uncertainty of the international price of oil has a differentiated effect on the different sectors of economic activity in Mexico since it does not influence the primary sector; it negatively impacts the secondary sector, and there is mixed evidence in the tertiary sector. Additionally, evidence is provided that both positive and negative shocks to the international oil price have asymmetric effects at the sectoral level in Mexico. The results highlight the need to implement public policies, at the country level, that help mitigate the effect of uncertainty in the oil market and promote economic stability at the sector level.

     

Contaminant transport in a municipal drinking water supply: a steady-state approach to estimate rate and uncertainty

Contaminant transport is generally considered to be a key factor when assessing and classifying the environmental risk of polluted areas. In the study presented here, a steady-state approach was applied to obtain estimates of the transit time and concentration of the pesticide metabolite BAM (2,6-dichlorobenzoamide) at a site where it is contaminating a municipal drinking water supply. A Monte Carlo simulation technique was used to quantify the uncertainty of the results and to evaluate the sensitivity of the used parameters. The adopted approach yielded an estimated median transit time of 10 y for the BAM transport from the polluted site to the water supply. Soil organic carbon content in the unsaturated zone and the hydraulic conductivity in the saturated zone explained 44% and 23% of the uncertainty in the transit time estimate, respectively. The sensitivity analysis showed that the dilution factor due to regional groundwater flow and the soil organic carbon content at the polluted site explained 53% and 31% of the uncertainty of concentration estimates, respectively. In conclusion, the adopted steady-state approach can be used to obtain reliable first estimates of transit time and concentration, but to improve concentration predictions of degrading contaminants, a dynamic model is probably required.     

重金属污染土壤植物修复及进展

土壤污染是当今面临的一个重要环境问题。常规的土壤污染物理化学治理技术 ,如客土换土法、冲洗法、热处理、固化、玻璃化、动电修复法等 ,由于其技术要求高或经济成本高昂 ,对土壤结构的扰动破坏较严重 ,因而 ,大规模推广应用存在较大问题。重金属超累积植物的不断发现 ,使人们认识到有可能利用植物于土壤污染的治理修复。自 2 0世纪 90年代起 ,植物修复成为环境污染治理研究领域的一个前沿性课题。研究表明 ,通过植物的吸收、挥发、根滤、稳定等作用 ,可以净化土壤或水体中金属污染物 ,达到净化环境的目的。近 10年来 ,在超累积植物的找寻培育、植物根际微生物共存体系研究、植物对重金属的耐忍性、超量吸收及其解毒机制以及植物修复的工艺技术方面已有不少研究 ,并取得长足的进展 ,现代分子生物学的发展以及基因工程技术的应用有可能使植物修复技术取得根本性的突破。     

Estimation of measurement uncertainty associated to the determination of pesticide residues: a case study

In the analytical analysis the measurement uncertainty is a quantitative indicator of the confidence describing the range around a reported or experimental result within which the true value can be expected. Several approaches can be used to estimate the measurement uncertainty associated to the analysis of pesticide residues: a) the top-down, the estimation can be referred to default values; b) the bottom-up the estimation is related to the uncertainty sources. Concerning the bottom-up approach, the following contributions have been investigated: weight of sample, calibration solutions, final volume of sample and intermediate repeatability studies. The commodity/residue combination selected in this study was celery/tau-fluvalinate pesticide. Tau-fluvalinate is a broad-spectrum insecticide in the pyrethroid class of pesticides. The Maximum Residue Limit (MRL) of tau-fluvalinate in celery has been set at 0.01 mg/kg. The tau- Fluvalinate showed two chromatographic peaks. Since the individual standards are not available, the two peaks were integrated separately and the instrumental responses were added. The total residue was calculated on the basis of resulted peaks. The present work aims to compare the uncertainty estimated by experimental data using repeated analysis (n = 12) of a real sample and a spiked sample. The relative expanded uncertainty for two data set, incurred and spiked, was 22 % and 20 %, respectively. No differences were observed from repeated determinations of real samples and spiked samples.     

Methods for quantifying variability and uncertainty in AP-42 emission factors: case studies for natural gas-fueled engines

Quantitative methods for characterizing variability and uncertainty were applied to case studies of oxides of nitrogen and total organic carbon emission factors for lean-burn natural gas-fueled internal combustion engines. Parametric probability distributions were fit to represent inter-engine variability in specific emission factors. Bootstrap simulation was used to quantify uncertainty in the fitted cumulative distribution function and in the mean emission factor. Some methodological challenges were encountered in analyzing the data. For example, in one instance, five data points were available, with each data point representing a different market share. Therefore, an approach was developed in which parametric distributions were fitted to population-weighted data. The uncertainty in mean emission factors ranges from as little as approximately +/-10% to as much as -90 to +180%. The wide range of uncertainty in some emission factors emphasizes the importance of recognizing and accounting for uncertainty in emissions estimates. The skewness in some uncertainty estimates illustrates the importance of using numerical simulation approaches that do not impose restrictive symmetry assumptions on the confidence interval for the mean. In this paper, the quantitative method, the analysis results, and key findings are presented.     

Comparison of a new Eulerian model with a modified Lagrangian approach for particle distribution and deposition indoors

Understanding of aerosol dispersion characteristics has many scientific and engineering applications. It is recognized that Eulerian or Lagrangian approach has its own merits and limitations. A new Eulerian model has been developed and it adopts a simplified drift–flux methodology in which external forces can be incorporated straightforwardly. A new near-wall treatment is applied to take into account the anisotropic turbulence for the modified Lagrangian model. In the present work, we present and compare both Eulerian and Lagrangian models to simulate particle dispersion in a small chamber. Results reveal that the standard k–ε Lagrangian model over-predicts particle deposition compared to the present turbulence-corrected Lagrangian approach. Prediction by the Eulerian model agrees well with the modified Lagrangian model.