Optimal and suboptimal control of anaerobic digesters

Anaerobic digester failure due to entry of inhibitors or sudden changes in the feed substrate concentration may be encompassed beneficially by applying optimal control theory. An almost proportional relationship between the dilution rate and the methane production rate leads to a simple suboptimal control law with only minor loss in performance, after the occurrence of the above mentioned events.     

Parameter values to model the soil ingestion pathway

Soil ingestion is an important exposure pathway for contaminants that are not otherwise very mobile in the environment. Health of both humans and animals can be affected. This paper summarizes the literature and recommends models and probabilistic parameter values for risk assessment applications. Models of the pathway require estimates of the amounts of soil ingested, the concentration of contaminants relative to the original soil, and the bioavailability in the gut of the contaminants ingested with soil. Using a lead-contaminated sandbox as an example, the modelling recommendations suggest that a child typically may consume 50 mg d^–1 of the sandbox soil, the soil ingested will have a tenfold higher lead concentration than the original soil, and the lead will be as bioavailable as if ingested as inorganic lead in water.The Canadian Government right to retain a non-exclusive, royalty free licence in and to any copyright is acknowledged.     

The analysis of monitoring data with the aid of time-series analysis

Methods derived from time-series analysis are proposed for processing monitoring data. The necessity for the use of these methods is demonstrated. In a case study time-series analysis was applied to assess the impact of the closure of the Grevelingen estuary (S. W. Netherlands) in 1971 on a local wintering population of Oystercatchers (Haematopus ostralegus) in the adjacent Oosterschelde estuary.Communication No. 328 of the Delta Institute for Hydrobiological Research.     

Characterization and removal of odors from refuse material

Odorous gases emitted from refuse wastes were scrubbed through activated carbon columns until odor breakthrough occured. Refuse air samples were collected at the influent and effluent ports of the columns for analysis on a gas chromatograph-mass spectrometric system and for odor determination by dynamic olfactometry. Chromatographic profiles of the gases emitted from refuse material were obtained and volatiles identified included carboxylic acids and some sulphur compounds. Organoleptic tests with a dynamic olfactometer revealed that the odor concentration of refuse air averaged about 50 sou m^–3. The adsorption capacities of four commercial grades of activated carbon for refuse odor were evaluated and compared. Results indicated that chemically impregnated activated carbons that are commonly used for odor control at sewerage facilities were less cost effective than non-chemically impregnated carbons.     

Quantitative PCR analysis of house dust can reveal abnormal mold conditions

Indoor mold concentrations were measured in the dust of moldy homes (MH) and reference homes (RH) by quantitative PCR (QPCR) assays for 82 species or related groups of species (assay groups). About 70% of the species and groups were never or only rarely detected. The ratios (MH geometric mean : RH geometric mean) for 6 commonly detected species (Aspergillus ochraceus, A. penicillioides, A. unguis, A. versicolor, Eurotium group, and Cladosporium sphaerospermum) were >1 (Group I). Logistic regression analysis of the sum of the logs of the concentrations of Group I species resulted in a 95% probability for separating MH from RH. These results suggest that it may be possible to evaluate whether a home has an abnormal mold condition by quantifying a limited number of mold species in a dust sample. Also, four common species of Aspergillus were quantified by standard culturing procedures and their concentrations compared to QPCR results. Culturing underestimated the concentrations of these four species by 2 to 3 orders of magnitude compared to QPCR.     

Examples of the role of analytical chemistry in environmental risk management research

Analytical chemistry is an important tier of environmental protection and has been traditionally linked to compliance and/or exposure monitoring activities for environmental contaminants. The adoption of the risk management paradigm has led to special challenges for analytical chemistry applied to environmental risk analysis. Namely, methods developed for regulated contaminants may not be appropriate and/or applicable to risk management scenarios. This paper contains examples of analytical chemistry applied to risk management challenges broken down by the analytical approach and analyte for some selected work in our laboratory. Specific techniques discussed include stable association complex electrospray mass spectrometry (cESI-MS), gas chromatography-mass spectrometry (GC-MS), split-flow thin cell (SPLITT) fractionation and matrix-assisted laser desorption time of flight mass spectrometry (MALDI-ToF-MS). Specific analytes include haloacetic acids (HAA9), perchlorate, bromate, triazine degradation products, metal-contaminated colloids and Cryptosporidium parvum oocysts.     

Monitoring atmospheric metal pollution: a review of the use of mosses as indicators

This article reviews the literatureon the use of mosses for monitoring atmospheric metalpollution. It discusses the nature of mosses, themechanisms for moss uptake of metals from the air andwet precipitation, the various forms in which mossesare used for this purpose, and cases in which mosseshave been used for monitoring local hot spots ofpollution, and regional patterns of metal pollution.Also highlighted are the questions of uptake of metalsfrom the substrates, interspecies differences, and acomparison of the effectiveness of mosses with otherindicator materials, among other issues.     

Forest Area in Costa Rica: A Comparative Study of Tropical Forest Cover Estimates over Time

Forest area figures, at a given point in time and for a given region of interest, differ considerably, affecting the calculation of deforestation rates and thus confuse the political and scientific discussion on the state and change of the resource forest. This article discusses the variation of published forest cover figures, using Costa Rica as an example. A list of published figures on the forest cover of Costa Rica from 1940 onwards is analyzed. Reasons for the differences are hypothesized and discussed. These differences are mainly in the definition of forest and forest classes included, in the type of the studies conducted (mapping and/or sampling), in the precision of the estimates, and in the information sources used. It is concluded that part of the problem is inherent in the nature of the resource `forest'. Quality and completeness of the presentation of the forest cover estimates are a clue to their correct understanding and interpretation. The latter point being especially relevant, as forest cover data have both a technical-scientific and a political meaning and are used as relevant arguments in many discussions. In the example of Costa Rica, a general downward trend is observed up to about 1985/1990, whereas after that forest area figures are on the average at a markedly higher level. Some hypotheses for this change in the trend are discussed.     

Application of intrawell testing of RCRA groundwater monitoring data when no upgradient well exists

A statistical quality control approachto detect changes in groundwater quality from aregulated waste unit is described. The approachapplies the combined Shewhart-CUSUM control chartmethodology for intrawell comparison of analyteconcentrations over time and does not require anupgradient well. A case study from the U.S.Department of Energy's Hanford Site is used forillustration purposes. This method is broadlyapplicable in groundwater monitoring programs wherethere is no clearly defined upgradient location, thegroundwater flow rate is exceptionally slow, or wherea high degree of spatial variability exists inparameter concentrations. This study also indicatesthat the use of the Data Quality Objectives (DQO)process can assist in designing an efficient andcost-effective groundwater monitoring plan to achievethe optimum goal of both low false positive and lowfalse negative rates (high power).