In situ experimental study of carbon monoxide generation by gasoline-powered electric generator in an enclosed space

On the basis of currently available data, approximately 97% of generator-related carbon monoxide (CO) fatalities are caused by operating currently marketed, carbureted spark-ignited gasoline-powered generators (not equipped with emission controls) in enclosed spaces. To better understand and to reduce the occurrence of these fatalities, research is needed to quantify CO generation rates, develop and test CO emission control devices, and evaluate CO transport and exposure when operating a generator in an enclosed space. As a first step in these efforts, this paper presents measured CO generation rates from a generator without any emission control devices operating in an enclosed space under real weather conditions. This study expands on previously published information from the U.S. Consumer Product Safety Commission. Thirteen separate tests were conducted under different weather conditions at half and full generator load settings. It was found that the CO level in the shed reached a maximum value of 29,300 +/- 580 mg/m3, whereas the oxygen (O2) was depleted to a minimum level of 16.2 +/- 0.02% by volume. For the test conditions of real weather and generator operation, the CO generation and the O2 consumption could be expressed as time-averaged generation/consumption rates. It was also found that the CO generation and O2 consumption rates can be correlated to the O2 levels in the space and the actual load output from the generator. These correlations are shown to agree well with the measurements.     

Improvements to lawn and garden equipment emissions estimates for Baltimore, Maryland

Lawn and garden equipment are a significant source of emissions of volatile organic compounds (VOCs) and other pollutants in suburban and urban areas. Emission estimates for this source category are typically prepared using default equipment populations and activity data contained in emissions models such as the U.S. Environmental Protection Agency's (EPA) NONROAD model or the California Air Resources Board's (CARB) OFFROAD model. Although such default data may represent national or state averages, these data are unlikely to reflect regional or local differences in equipment usage patterns because of variations in climate, lot sizes, and other variables. To assess potential errors in lawn and garden equipment emission estimates produced by the NONROAD model and to demonstrate methods that can be used by local planning agencies to improve those emission estimates, this study used bottom-up data collection techniques in the Baltimore metropolitan area to develop local equipment population, activity, and temporal data for lawn and garden equipment in the area. Results of this study show that emission estimates of VOCs, particulate matter (PM), carbon monoxide (CO), carbon dioxide (CO2), and nitrogen oxides (NO(x)) for the Baltimore area that are based on local data collected through surveys of residential and commercial lawn and garden equipment users are 24-56% lower than estimates produced using NONROAD default data, largely because of a difference in equipment populations for high-usage commercial applications. Survey-derived emission estimates of PM and VOCs are 24 and 26% lower than NONROAD default estimates, respectively, whereas survey-derived emission estimates for CO, CO2, and NO(x) are more than 40% lower than NONROAD default estimates. In addition, study results show that the temporal allocation factors applied to residential lawn and garden equipment in the NONROAD model underestimated weekend activity levels by 30% compared with survey-derived temporal profiles.     

Inferring chemical effects on carbon flows in aquatic food webs: Methodology and case study

The majority of ecotoxicological enclosure experiments monitor species abundances at different chemical concentrations. Here, we present a new modelling approach that estimates changes in food web flows from such data and show that population- and food web level effects are revealed that are not apparent from abundance data alone. For the case of cypermethrin in freshwater enclosures, photosynthesis and excretion (d⁻¹) of phytoplankton at 3.643 μg L⁻¹ cypermethrin were 30% lower and 100% higher than in the control, respectively. The ingestion rate of mesozooplankton (d⁻¹) was 6 times higher in the treated enclosures than in the control as food concentration increased with insecticide exposure. With increasing cypermethrin concentrations, nanoflagellates progressively relied on phytoplankton as their main food source, which rendered the food web less stable. We conclude that this tool has excellent potential to analyse the wealth of enclosure data as it only needs species abundance and general constraints.     

Monod kinetics rather than a first-order degradation model explains atrazine fate in soil mini-columns: Implications for pesticide fate modelling

Pesticide transport models commonly assume first-order pesticide degradation kinetics for describing reactive transport in soil. This assumption was assessed in mini-column studies with associated batch degradation tests. Soil mini-columns were irrigated with atrazine in two intermittent steps of about 30 days separated by 161 days application of artificial rain water. Atrazine concentration in the effluent peaked to that of the influent concentration after initial break-through but sharply decreased while influx was sustained, suggesting a degradation lag phase. The same pattern was displayed in the second step but peak height and percentage of atrazine recovered in the effluent were lower. A Monod model with biomass decay was successfully calibrated to this data. The model was successfully evaluated against batch degradation data and mini-column experiments at lower flow rate. The study suggested that first-order degradation models may underestimate risk of pesticide leaching if the pesticide degradation potential needs amplification during degradation.     

Implications of high altitude desert dust transport from Western Sahara to Nile Delta during biomass burning season

The air over major cities and rural regions of the Nile Delta is highly polluted during autumn which is the biomass burning season, locally known as black cloud. Previous studies have attributed the increased pollution levels during the black cloud season to the biomass or open burning of agricultural waste, vehicular, industrial emissions, and secondary aerosols. However, new multi-sensor observations (column and vertical profiles) from satellites, dust transport models and associated meteorology present a different picture of the autumn pollution. Here we show, for the first time, the evidence of long range transport of dust at high altitude (2.5-6 km) from Western Sahara and its deposition over the Nile Delta region unlike current Models. The desert dust is found to be a major contributor to the local air quality which was previously considered to be due to pollution from biomass burning enhanced by the dominant northerly winds coming from Europe.     

Dietary exposure of juvenile common sole (Solea solea L.) to polybrominated diphenyl ethers (PBDEs): Part 2. Formation, bioaccumulation and elimination of hydroxylated metabolites

The uptake, elimination and transformation of six PBDE congeners (BDE-28, -47, -99, -100, -153, -209) were studied in juvenile common sole (Solea solea L.) exposed to spiked contaminated food over a three-month period, and then depurated over a five-month period. Methoxylated (MeO-) and hydroxylated (OH-) PBDEs were determined in fish plasma exposed to PBDEs and compared to those obtained in control fish. While all MeO- and some OH- congeners identified in fish plasma were found to originate from non-metabolic sources, several OH- congeners, i.e., OH-tetraBDEs and OH-pentaBDEs, were found to originate from fish metabolism. Among these, 4′-OH-BDE-49 was identified as a BDE-47 metabolite. Congener 4′-OH-BDE-101, identified here for the first time, may be the result of BDE-99 metabolic transformation. Our results unequivocally showed that PBDEs are metabolised in juvenile sole via the formation of OH- metabolites. However, this was not a major biotransformation route compared to biotransformation through debromination.     

Benzyl-penicillin (Penicillin G) transformation in aqueous solution at low temperature under controlled laboratory conditions

Antibiotics are released into the environment in a variety of ways: via wastewater effluent as a result of incomplete metabolism in the body after use in human therapy, as runoff after use in agriculture, through improper disposal by private households or hospitals or through insufficient removal by water treatment plants. Unlike in most European countries, in Arctic regions effluents are not suitably treated prior to their release into the aquatic environment. Also, many of the scattered human settlements in remote regions of the Arctic do not possess sewage treatment facilities and pharmaceutical residues therefore enter the aqueous environment untreated. Only limited data are available on the biodegradation of antibiotics under Arctic conditions. However, such information is needed to estimate the potential harm of antibiotics for the environment. Pen-G is used in this study since it is a widely prescribed antibiotic compound whose environmental properties have not yet been investigated in detail. Thus, for a very first assessment, the OECD approved biodegradation Zahn-Wellens test (ZWT, OECD 302 B) was used to study biodegradation and non-biotic elimination of the antibiotic Benzyl-penicillin (Pen-G) at different temperatures (5°C, 12.5°C and 20°C). The testing period was extended from the OECD standard of 28-42d. In addition to dissolved organic carbon (DOC), Pen-G levels and major transformation products were recorded continuously by LC-ion-trap-MS/MS. DOC monitoring revealed considerable temperature dependence for the degradation process of Pen-G. DOC loss was slowest at 5°C and considerably faster at 12.5°C and 20°C. In the initial step of degradation it was found that Pen-G was hydrolyzed. This hydrolyzed Pen-G was subsequently further degraded by decarboxylation, the result of which was 2-(5,5-dimethyl-1,3-thiazolidin-2-yl)-2-(2-phenylacetamido)acetic acid. Furthermore, direct elimination of 2-phenyl-acetaldehyde from the hydrolyzed and decarboxylated Pen-G also led to the formation of 2-[amino(carboxy)methyl]-5,5-dimethyl-1,3-thiazolidone-4-carboxylic acid. Since biodegradation slows down considerably at a low temperature, the resulting transformation products had considerably longer residence times at 5°C compared to higher temperature conditions within the 42-d experiment. The results presented here clearly demonstrate that a risk assessment for pharmaceuticals present in low ambient temperature environments (i.e. the Arctic) cannot be based on test results obtained under standard laboratory conditions (i.e. 20°C ambient temperatures).     

Variation in biogenic volatile organic compound emission pattern of Fagus sylvatica L. due to aphid infection

Volatile organic compounds (VOCs) have been the focus of interest to understand atmospheric processes and their consequences in formation of ozone or aerosol particles; therefore, VOCs contribute to climate change. In this study, biogenic VOCs (BVOCs) emitted from Fagus sylvatica L. trees were measured in a dynamic enclosure system. In total 18 compounds were identified: 11 monoterpenes (MT), an oxygenated MT, a homoterpene (C₁₄H₁₈), 3 sesquiterpenes (SQT), isoprene and methyl salicylate. The frequency distribution of the compounds was tested to determine a relation with the presence of the aphid Phyllaphis fagi L. It was found that linalool, (E)-β-ocimene, α-farnesene and a homoterpene identified as (E)-4,8-dimethyl-1,3,7-nonatriene (DMNT), were present in significantly more samples when infection was present on the trees. The observed emission spectrum from F. sylvatica L. shifted from MT to linalool, α-farnesene, (E)-β-ocimene and DMNT due to the aphid infection. Sabinene was quantitatively the most prevalent compound in both, non-infected and infected samples. In the presence of aphids α-farnesene and linalool became the second and third most important BVOC emitted. According to our investigation, the emission fingerprint is expected to be more complex than commonly presumed.     

Comparison of land-use regression models between Great Britain and the Netherlands

Land-use regression models have increasingly been applied for air pollution mapping at typically the city level. Though models generally predict spatial variability well, the structure of models differs widely between studies. The observed differences in the models may be due to artefacts of data and methodology or underlying differences in source or dispersion characteristics. If the former, more standardised methods using common data sets could be beneficial. We compared land-use regression models for NO₂ and PM_10, developed with a consistent protocol in Great Britain (GB) and the Netherlands (NL).Models were constructed on the basis of 2001 annual mean concentrations from the national air quality networks. Predictor variables used for modelling related to traffic, population, land use and topography. Four sets of models were developed for each country. First, predictor variables derived from data sets common to both countries were used in a pooled analysis, including an indicator for country and interaction terms between country and the identified predictor variables. Second, the common data sets were used to develop individual baseline models for each country. Third, the country-specific baseline models were applied after calibration in the other country to explore transferability. The fourth model was developed using the best possible predictor variables for each country.A common model for GB and NL explained NO₂ concentrations well (adjusted R² 0.64), with no significant differences in intercept and slopes between the two countries. The country-specific model developed on common variables for NL but not GB improved the prediction.The performance of models based upon common data was only slightly worse than models optimised with local data. Models transferred to the other country performed substantially worse than the country-specific models. In conclusion, care is needed both in transferring models across different study areas, and in developing large inter-regional LUR models.