Impact of dry deposition of semi-volatile organic compounds on secondary organic aerosols

Dry deposition of semi-volatile organic compounds (SVOC) is not currently treated in most chemical transport models of air quality and this omission has been identified as a possible major source of uncertainty. The effect of dry deposition of SVOC on the concentration of secondary organic aerosols (SOA) is investigated in summertime with the chemical transport model CHIMERE that simulates SOA concentrations by means of molecular SOA surrogate species. Omitting dry deposition could overestimate SOA concentrations by as much as 50%. This overestimation is larger during nighttime due to higher relative humidity.     

Forest plantations, water availability, and regional climate change: controversies surrounding Acacia mearnsii plantations in the upper Palnis Hills, southern India

Plantation forests not only impact carbon and water cycles, but also affect biodiversity, livelihoods, and shape regional economies. Each of these impacts differs across varying scales of analysis. This paper illustrates how forest, climate change and hydrology debates play out in the context of the forest plantations of Australian black wattle (Acacia mearnsii) in the upper Palni hills of southern India. We outline the contradictory perspectives of different local groups regarding the impact of plantations on catchment hydrology and water availability, and examine these in relation to changes in the regional economy and rainfall patterns. Our analysis indicates that changes in these two factors have played a more significant role than existing wattle plantations in affecting local and regional water availability. We suggest that ongoing debates regarding forest plantation–hydrology–climate change relationships need to broaden their scope to include changes in regional rainfall patterns and shifts in regional economic activity. This approach is likely to provide a more realistic assessment of plantation forests in a dynamic regional context, and offer more resilient strategies for regional landscape and catchment management under conditions of high variability in rainfall patterns.     

Assessing computer waste generation in Chile using material flow analysis

The quantities of e-waste are expected to increase sharply in Chile. The purpose of this paper is to provide a quantitative data basis on generated e-waste quantities. A material flow analysis was carried out assessing the generation of e-waste from computer equipment (desktop and laptop PCs as well as CRT and LCD-monitors). Import and sales data were collected from the Chilean Customs database as well as from publications by the International Data Corporation. A survey was conducted to determine consumers’ choices with respect to storage, re-use and disposal of computer equipment. The generation of e-waste was assessed in a baseline as well as upper and lower scenarios until 2020.The results for the baseline scenario show that about 10,000 and 20,000 tons of computer waste may be generated in the years 2010 and 2020, respectively. The cumulative e-waste generation will be four to five times higher in the upcoming decade (2010–2019) than during the current decade (2000–2009). By 2020, the shares of LCD-monitors and laptops will increase more rapidly replacing other e-waste including the CRT-monitors. The model also shows the principal flows of computer equipment from production and sale to recycling and disposal. The re-use of computer equipment plays an important role in Chile. An appropriate recycling scheme will have to be introduced to provide adequate solutions for the growing rate of e-waste generation.     

Belowground effects of enhanced tropospheric ozone and drought in a beech/spruce forest (Fagus sylvatica L./Picea abies [L.] Karst)

The effects of experimentally elevated O₃ on soil respiration rates, standing fine-root biomass, fine-root production and δ¹³C signature of newly produced fine roots were investigated in an adult European beech/Norway spruce forest in Germany during two subsequent years with contrasting rainfall patterns. During humid 2002, soil respiration rate was enhanced under elevated O₃ under beech and spruce, and was related to O₃-stimulated fine-root production only in beech. During dry 2003, the stimulating effect of O₃ on soil respiration rate vanished under spruce, which was correlated with decreased fine-root production in spruce under drought, irrespective of the O₃ regime. δ¹³C signature of newly formed fine-roots was consistent with the differing g_s of beech and spruce, and indicated stomatal limitation by O₃ in beech and by drought in spruce. Our study showed that drought can override the stimulating O₃ effects on fine-root dynamics and soil respiration in mature beech and spruce forests.     

Using multivariate regression modeling for sampling and predicting chemical characteristics of mixed waste in old landfills

Municipal solid waste landfills pose a threat on environment and human health, especially old landfills which lack facilities for collection and treatment of landfill gas and leachate. Consequently, missing information about emission flows prevent site-specific environmental risk assessments. To overcome this gap, the combination of waste sampling and analysis with statistical modeling is one option for estimating present and future emission potentials. Optimizing the tradeoff between investigation costs and reliable results requires knowledge about both: the number of samples to be taken and variables to be analyzed.This article aims to identify the optimized number of waste samples and variables in order to predict a larger set of variables. Therefore, we introduce a multivariate linear regression model and tested the applicability by usage of two case studies. Landfill A was used to set up and calibrate the model based on 50 waste samples and twelve variables. The calibrated model was applied to Landfill B including 36 waste samples and twelve variables with four predictor variables.The case study results are twofold: first, the reliable and accurate prediction of the twelve variables can be achieved with the knowledge of four predictor variables (Loi, EC, pH and Cl). For the second Landfill B, only ten full measurements would be needed for a reliable prediction of most response variables. The four predictor variables would exhibit comparably low analytical costs in comparison to the full set of measurements. This cost reduction could be used to increase the number of samples yielding an improved understanding of the spatial waste heterogeneity in landfills.Concluding, the future application of the developed model potentially improves the reliability of predicted emission potentials. The model could become a standard screening tool for old landfills if its applicability and reliability would be tested in additional case studies.     

Investigation into the effect of high concentrations of volatile fatty acids in anaerobic digestion on methanogenic communities

A study was conducted to determine whether differences in the levels of volatile fatty acids (VFAs) in anaerobic digester plants could result in variations in the indigenous methanogenic communities. Two digesters (one operated under mesophilic conditions, the other under thermophilic conditions) were monitored, and sampled at points where VFA levels were high, as well as when VFA levels were low. Physical and chemical parameters were measured, and the methanogenic diversity was screened using the phylogenetic microarray ANAEROCHIP. In addition, real-time PCR was used to quantify the presence of the different methanogenic genera in the sludge samples. Array results indicated that the archaeal communities in the different reactors were stable, and that changes in the VFA levels of the anaerobic digesters did not greatly alter the dominating methanogenic organisms. In contrast, the two digesters were found to harbour different dominating methanogenic communities, which appeared to remain stable over time. Real-time PCR results were inline with those of microarray analysis indicating only minimal changes in methanogen numbers during periods of high VFAs, however, revealed a greater diversity in methanogens than found with the array.     

Road traffic impact on urban water quality: a step towards integrated traffic,air and stormwater modelling

Methods for simulating air pollution due to road traffic and the associated effects on stormwater runoff quality in an urban environment are examined with particular emphasis on the integration of the various simulation models into a consistent modelling chain. To that end, the models for traffic, pollutant emissions, atmospheric dispersion and deposition, and stormwater contamination are reviewed. The present study focuses on the implementation of a modelling chain for an actual urban case study, which is the contamination of water runoff by cadmium (Cd), lead (Pb), and zinc (Zn) in the Grigny urban catchment near Paris, France. First, traffic emissions are calculated with traffic inputs using the COPERT4 methodology. Next, the atmospheric dispersion of pollutants is simulated with the Polyphemus line source model and pollutant deposition fluxes in different subcatchment areas are calculated. Finally, the SWMM water quantity and quality model is used to estimate the concentrations of pollutants in stormwater runoff. The simulation results are compared to mass flow rates and concentrations of Cd, Pb and Zn measured at the catchment outlet. The contribution of local traffic to stormwater contamination is estimated to be significant for Pb and, to a lesser extent, for Zn and Cd; however, Pb is most likely overestimated due to outdated emissions factors. The results demonstrate the importance of treating distributed traffic emissions from major roadways explicitly since the impact of these sources on concentrations in the catchment outlet is underestimated when those traffic emissions are spatially averaged over the catchment area.     

Ozone Formation in California's San Joaquin Valley: A Critical Assessment of Modeling and Data Needs

ABSTRACT

Data from the 1990 San Joaquin Valley Air Quality Study/ Atmospheric Utility Signatures, Predictions, and Experiments (SJVAQS/AUSPEX) field program in California's San Joaquin Valley (SJV) suggest that both urban and rural areas would have difficulty meeting an 8-hr average O₃ standard of 80 ppb. A conceptual model of O₃ formation and accumulation in the SJV is formulated based on the chemical, meteorological, and tracer data from SJVAQS/ AUSPEX. Two major phenomena appear to lead to high O₃ concentrations in the SJV: (1) transport of O₃ and precursors from upwind areas (primarily the San Francisco Bay Area, but also the Sacramento Valley) into the SJV, affecting the northern part of the valley, and (2) emissions of precursors, mixing, transport (including long-range transport), and atmospheric reactions within the SJV responsible for regional and urban-scale (e.g., downwind of Fresno and Bakersfield) distributions of O₃. Using this conceptual model, we then conduct a critical evaluation of the meteorological model and air quality model. Areas of model improvements and data needed to understand and properly simulate O₃ formation in the SJV are highlighted.     

Current Status of Air Quality Models for Particulate Matter

ABSTRACT

The current status of the mathematical modeling of atmospheric particulate matter (PM) is reviewed in this paper. Simulating PM requires treating various processes, including the formation of condensable species, the gas/ particle partitioning of condensable compounds, and in some cases, the evolution of the particle size distribution. The algorithms available to simulate these processes are reviewed and discussed. Eleven 3-dimensional (3-D) Eulerian air quality models for PM are reviewed in terms of their formulation and past applications. Results of past performance evaluations of 3-D Eulerian PM models are presented. Currently, 24-hr average PM_2.5 concentrations appear to be predicted within 50% for urban-scale domains. However, there are compensating errors among individual particulate species. The lowest errors tend to be associated with SO₄ ^2-, while NO₃ ^-, black carbon (BC), and organic carbon (OC) typically show larger errors due to uncertainties in emissions inventories and the prediction of the secondary OC fraction. Further improvements and performance evaluations are recommended.     

An Assessment of the Emissions Inventory Processing Systems EMS-2001 and SMOKE in Grid-Based Air Quality Models

Abstract

In the United States, emission processing models such as Emissions Modeling System-2001 (EMS-2001), Emissions Preprocessor System-Version 2.5 (EPS2.5), and the Sparse Matrix Operator Kernel Emissions (SMOKE) model are currently being used to generate gridded, hourly, speciated emission inputs for urban and regional-scale photochemical models from aggregated pollutant inventories. In this study, two models, EMS-2001 and SMOKE, were applied with their default internal data sets to process a common inventory database for a high ozone (O₃) episode over the eastern United States using the Carbon Bond IV (CB4) chemical speciation mechanism. A comparison of the emissions processed by these systems shows differences in all three of the major processing steps performed by the two models (i.e., in temporal allocation, spatial allocation, and chemical speciation). Results from a simulation with a photochemical model using these two sets of emissions indicate differences on the order of ±20 ppb in the predicted 1-hr daily maximum O₃ concentrations. It is therefore critical to develop and implement more common and synchronized temporal, spatial, and speciation cross-reference systems such that the processes within each emissions model converge toward reasonably similar results. This would also help to increase confidence in the validity of photochemical grid model results by reducing one aspect of modeling uncertainty.