Humic acid in ice: Photo-enhanced conversion of nitrogen dioxide into nitrous acid

Laboratory studies on the heterogeneous conversion of nitrogen dioxide into nitrous acid on irradiated ice films containing humic acid are described. It was found that the presence of light in the visible range of the solar spectrum significantly enhances the rate of nitrous acid release from a humic acid doped ice film. This process might contribute to observed HONO production in snow, where the NO₂ is thought to originate from nitrate photolysis. Analysis of the experimental data based on the Langmuir Hinshelwood model framework allowed quantification of the observed dependencies of the nitrous acid production rate on nitrogen dioxide concentration. The observed dependencies on the humic acid concentration as well as on the irradiation intensity were used to estimate light-driven HONO fluxes for environmental snow covers.     

Dealing with disjunct concentration measurements in eddy covariance applications: A comparison of available approaches

Using proton transfer reaction mass spectrometry equipped with a quadrupol mass analyser to quantify the biosphere-atmosphere exchange of volatile organic compounds (VOC), concentrations of different VOC are measured sequentially. Depending on how many VOC species are targeted and their respective integration times, each VOC is measured at repeat rates on the order of a few seconds. This represents an order of magnitude longer sample interval compared to the standard eddy covariance (EC) method (5–20 Hz sampling rates). Here we simulate the effect of disjunct sampling on EC flux estimates by decreasing the time resolution of CO₂ and H₂O concentrations measured at 20 Hz above a temperate mountain grassland in the Austrian Alps. Fluxes for one month are calculated with the standard EC method and compared to fluxes calculated based on the disjunct data (1, 3 and 5 s sampling rates) using the following approaches: i) imputation of missing concentrations based on the nearest neighbouring samples (iDEC_nn), ii) imputation by linear interpolation (iDEC_li), and iii) virtual disjunct EC (vDEC), i.e. flux calculation based solely on the disjunct concentrations. It is shown that the two imputation methods result in additional low-pass filtering, longer lag times (as determined with the maximum cross-correlation method) and a flux loss of 3–30% as compared to the standard EC method. A novel procedure, based on a transfer function approach, which specifically corrects for the effect of data treatment, was developed, resulting in improved correspondence (to within 2%). The vDEC method yields fluxes which approximate the true (20 Hz) fluxes to within 3–7% and it is this approach we recommend because it involves no additional empirical corrections. The only drawback of the vDEC method is the noisy nature of the cross-correlations, which poses problems with lag determination – practical approaches to overcome this limitation are discussed.     

Comparison of Stream Invertebrate Response Models for Bioassessment Metrics1

Waite, Ian R., Jonathan G. Kennen, Jason T. May, Larry R. Brown, Thomas F. Cuffney, Kimberly A. Jones, and James L. Orlando, 2012. Comparison of Stream Invertebrate Response Models for Bioassessment Metrics. Journal of the American Water Resources Association (JAWRA) 48(3): 570-583. DOI: 10.1111/j.1752-1688.2011.00632.x Abstract: We aggregated invertebrate data from various sources to assemble data for modeling in two ecoregions in Oregon and one in California. Our goal was to compare the performance of models developed using multiple linear regression (MLR) techniques with models developed using three relatively new techniques: classification and regression trees (CART), random forest (RF), and boosted regression trees (BRT). We used tolerance of taxa based on richness (RICHTOL) and ratio of observed to expected taxa (O/E) as response variables and land use/land cover as explanatory variables. Responses were generally linear; therefore, there was little improvement to the MLR models when compared to models using CART and RF. In general, the four modeling techniques (MLR, CART, RF, and BRT) consistently selected the same primary explanatory variables for each region. However, results from the BRT models showed significant improvement over the MLR models for each region; increases in R² from 0.09 to 0.20. The O/E metric that was derived from models specifically calibrated for Oregon consistently had lower R² values than RICHTOL for the two regions tested. Modeled O/E R² values were between 0.06 and 0.10 lower for each of the four modeling methods applied in the Willamette Valley and were between 0.19 and 0.36 points lower for the Blue Mountains. As a result, BRT models may indeed represent a good alternative to MLR for modeling species distribution relative to environmental variables.     

A land use regression model for predicting ambient volatile organic compound concentrations in Toronto,Canada

More than 25 studies have employed land use regression (LUR) models to estimate nitrogen oxides and to a lesser extent particulate matter indicators, but these methods have been less commonly applied to ambient concentrations of volatile organic compounds (VOCs). Some VOCs have high plausibility as sources of health effects and others are specific indicators of motor vehicle exhaust. We used LUR models to estimate spatial variability of VOCs in Toronto, Canada. Benzene, n-hexane and total hydrocarbons (THC) were measured from July 25 to August 9, 2006 at 50 locations using the TraceAir organic vapor monitors. Nitrogen dioxide (NO₂) was also sampled to assess its spatial pattern agreement with VOC exposures. Buffers for land use, population density, traffic density, physical geography, and remote sensing measures of greenness and surface brightness were also tested. The remote sensing measures have the highest correlations with VOCs and NO₂ levels (i.e., explains >36% of the variance). Our regression models explain 66–68% of the variance in the spatial distribution of VOCs, compared to 81% for the NO₂ model. The ranks of agreement between various VOCs range from 48 to 63% and increases substantially – up to 75% – for the top and bottom quartile groups. Agreements between NO₂ and VOCs are much smaller with an average rank of 36%. Future epidemiologic studies may therefore benefit from using VOCs as potential toxic agents for traffic-related pollutants.     

Impact of a Community‐Based Payment for Environmental Services Intervention on Forest Use in Menabe,Madagascar

Abstract: Despite the growing interest in conservation approaches that include payments for environmental services (PES), few evaluations of the influence of such interventions on behaviors of individuals have been conducted. We used self‐reported changes in six legal and illegal forest‐use behaviors to investigate the way in which a PES for biodiversity conservation intervention in Menabe, Madagascar, influenced behavior. Individuals (n =864) from eight intervention communities and five control communities answered questions on their forest‐use behaviors before and after the intervention began, as well as on their reasons for changing and their attitudes to various institutions. The payments had little impact on individuals’ reported decisions to change behaviors, but it had a strong impact on individuals’ attitudes. Payments appeared to legitimize monitoring of behaviors by the implementing nongovernmental organization (NGO), but did not act as a behavioral driver in their own right. Although there were no clear differences between changes in behaviors in the intervention and control communities, the intervention did influence motivations for change. Fear of local forest associations and the implementing NGO were strong motivators for changing behavior in communities with the PES intervention, whereas fear of the national government was the main reason given for change in control communities. Behavioral changes were most stable where fear of local organizations motivated the change. Our results highlight the interactions between different incentives people face when making behavioral decisions and the importance of considering the full range of incentives when designing community‐based PES interventions.     

Carbon accumulation through ecosystem recovery

A market has emerged for carbon sequestered through reforestation. The opportunity to restore ecosystems through this market rather than establish plantations is demonstrated by an Australian case study. In the state of Queensland there are vast areas that have been cleared relatively recently and could be restored to ecosystems with high resilience and important biodiversity values with appropriate management. In order to foster opportunities for carbon accumulation through ecosystem recovery spatially explicit information on sequestration rates, management recommendations, and clear definitions of ancillary biodiversity benefits need to be defined.     

Study of lead phytoavailability for atmospheric industrial micronic and sub-micronic particles in relation with lead speciation

Particles from channelled emissions of a battery recycling facility were size-segregated and investigated to correlate their speciation and morphology with their transfer towards lettuce. Microculture experiments carried out with various calcareous soils spiked with micronic and sub-micronic particles (1650 ± 20 mg Pb kg⁻¹) highlighted a greater transfer in soils mixed with the finest particles. According to XRD and Raman spectroscopy results, the two fractions presented differences in the amount of minor lead compounds like carbonates, but their speciation was quite similar, in decreasing order of abundance: PbS, PbSO₄, PbSO₄·PbO, α-PbO and Pb⁰. Morphology investigations revealed that PM_2.5 (i.e. Particulate Matter 2.5 composed of particles suspended in air with aerodynamic diameters of 2.5 μm or less) contained many Pb nanoballs and nanocrystals which could influence lead availability. The soil-plant transfer of lead was mainly influenced by size and was very well estimated by 0.01 M CaCl₂ extraction.     

Bioaccessibility of trace elements as affected by soil parameters in smelter-contaminated agricultural soils: a statistical modeling approach

An investigation was undertaken to identify the most significant soil parameters that can be used to predict Cd, Pb, and Zn bioaccessibility in smelter-contaminated agricultural soils. A robust model was established from an extended database of soils by using: (i) a training set of 280 samples to select the main soil parameters, to define the best population to be taken into account for the model elaboration, and to construct multivariate regression models, and (ii) a test set of 110 samples to validate the ability of the regression models. Total carbonate, organic matter, sand, P(2)O(5), free Fe-Mn oxide, and pseudototal Al and trace element (TE) contents appeared as the main variables governing TE bioaccessibility. The statistical modeling approach was reasonably successful, indicating that the main soil factors influencing the bioaccessibility of TEs were taken into account and the predictions could be applicable for further risk evaluation in the studied area.