Characterization and sources assignation of PM2.5 organic aerosol in a rural area of Spain

The results from a year-long study of the organic composition of PM2.5 aerosol collected in a rural area influenced by a highway of Spain are reported. The lack of prior information related to the organic composition of PM2.5 aerosol in Spain, concretely in rural areas, led definition of the goals of this study. As a result, this work has been able to characterize the main organic components of atmospheric aerosols, including several compounds of SOA, and has conducted a multivariate analysis in order to assign sources of particulate matter. A total of 89 samples were taken between April 2004 and April 2005 using a high-volume sampler. Features and abundance of n-alkanes, polycyclic aromatic hydrocarbons (PAHs), alcohols and acids were separately determined using gas chromatography/mass spectrometry and high performance liquid chromatography analysis. The Σn-alkane and ΣPAHs ranged from 3 to 81 ng m^?3 and 0.1 to 6 ng m^?3 respectively, with higher concentrations during colder months. Ambient concentrations of Σalcohols and Σacids ranged from 21 to 184 ng m^?3 and 39 to 733 ng m^?3, respectively. Also, several components of secondary organic aerosol have been quantified, confirming the biogenic contribution to ambient aerosol. In addition, factor analysis was used to reveal origin of organic compounds associated to particulate matter. Eight factors were extracted accounting more than 83% of the variability in the original data. These factors were assigned to a typical high pollution episode by anthropogenic particles, crustal material, plant waxes, fossil fuel combustion, temperature, microbiological emissions, SOA and dispersion of pollutants by wind action. Finally, a cluster analysis was used to compare the organic composition between the four seasons.     

Assessing spatial variability of SO2 field as detected by an air quality network using Self-Organizing Maps,cluster, and Principal Component Analysis

In Bilbao (Spain), an air quality network measures sulphur dioxide levels at 4 locations. The objective of this paper is to develop a practical methodology to identify redundant sensors and evaluate a network's capability to correctly follow and represent SO₂ fields in Bilbao, in the frame of a continuous network optimization process.The methodology is developed and tested at this particular location, but it is general enough to be useable at other places as well, since it is not tied neither to the particular geographical characteristics of the place nor to the phenomenology of the air quality over the area.To assess the spatial variability of SO₂ measured at 4 locations in the area, three different techniques have been used: Self-Organizing Maps (SOMs), cluster analysis (CA) and Principal Component Analysis (PCA). The results show that the three techniques yield the same results, but the information obtained via PCA can be helpful not only for that purpose but also to throw light on the major mechanisms involved. This might be used in future network optimization stages. The main advantage of cluster analysis and SOMs is that they provide readily interpretable results. All the calculations have been carried out using the freely available software R.     

Atmospheric nitrogen deposition in south-east Scotland: Quantification of the organic nitrogen fraction in wet,dry and bulk deposition

Water soluble organic nitrogen (WSON) compounds are ubiquitous in precipitation and in the planetary boundary layer, and therefore are a potential source of bioavailable reactive nitrogen. This paper examines weekly rain data over a period of 22 months from June 2005 to March 2007 collected in 2 types of rain collector (bulk deposition and “dry + wet” deposition) located in a semi-rural area 15 km southwest of Edinburgh, UK (N55°51′44″, W3°12′19″). Bulk deposition collectors are denoted in this paper as “standard rain gauges”, and they are the design used in the UK national network for monitoring precipitation composition. “Dry + wet” deposition collectors are flushing rain gauges and they are equipped with a rain detector (conductivity array), a spray nozzle, a 2-way valve and two independent bottles to collect funnel washings (dry deposition) and true wet deposition. On average, for the 27 weekly samples with 3 valid replicates for the 2 types of collectors, dissolved organic nitrogen (DON) represented 23% of the total dissolved nitrogen (TDN) in bulk deposition. Dry deposition of particles and gas on the funnel surface, rather than rain, contributed over half of all N-containing species (inorganic and organic). Some discrepancies were found between bulk rain gauges and flushing rain gauges, for deposition of both TDN and DON, suggesting biological conversion and loss of inorganic N in the flushing samplers.     

Removal of an anionic dye (Acid Blue 92) by coagulation–flocculation using chitosan

Chitosan (a biopolymer) is an aminopolysaccharide that can be used for the treatment of colored solutions by coagulation–flocculation (as an alternative to more conventional processes such as sorption). Acid Blue 92 (a sulfonic dye) was selected as a model dye for verifying chitosan's ability to treat textile wastewater. A preliminary experiment demonstrated that chitosan was more efficient at color removal in tap water than in demineralized water, and that a substantially lower concentration of chitosan could be used with tap water. Dye removal reached up to 99% under optimum concentration; i.e., in terms of the acidic solutions and the stoichiometric ratio between the amine groups of the biopolymer and the sulfonic groups in the dye. The flocs were recovered and the dye was efficiently removed using alkaline solutions (0.001–1 M NaOH solutions) and the biopolymer, re-dissolved in acetic acid solution, was reused in a further treatment cycle.     

The whole relationship between environmental variables and firm performance: Competitive advantage and firm resources as mediator variables

The examination of the possible direct link between environmental protection and firm performance in the literature has generally produced mixed results. The present paper contributes to the literature by using the resource-based view as a mediating process in this relationship. The study specifically tests whether or not the resource-based view of the firm mediates the positive relationships of proactive environmental management and improved environmental performance with competitive advantage, which also has consequences for financial performance. We also check the possible link between the adoption of a pioneering approach and good environmental management practices. Our findings support that early investment timing and intensity in environmental issues impact on the adoption of a proactive environmental management, which in turn helps to improve environmental performance. The findings also show that a firm's resources and competitive advantage act as mediator variables for a positive relationship between environmental protection and financial performance. This contribution is original because the present paper develops a comprehensive whole picture of this path process, which has previously only been partially discussed in the literature. In addition, this study clarifies a relevant point in the literature, namely that the effect of environmental protection on firm performance is not direct and can vary depending on the sector considered. Whereas competitive advantage in relation to costs influences financial performance in the IPPC law sector, the relevant influence in the hotel sector comes from competitive advantage through differentiation.     

Balancing environmental and industry sustainability: A case study of the US gold mining industry

Mandatory insurance requirements and/or mitigation fees (royalties) for mining companies may help reduce environmental risk exposure for the federal government. Mining is examined since the Environmental Protection Agency (EPA) Toxic Release Inventory reveals that this sector produces more hazardous waste than any other industrial sector. Although uncommon, environmental expense can exceed hundreds of millions of dollars per development. Of particular concern is the potential for mines to become unfunded Superfund sites. Monte Carlo simulation of risk exposure is used to establish a plausible range of unfunded federal liabilities associated with cyanide-leach gold mining. A model is developed to assess these costs and their impact on both the federal budget and corporate profitability (i.e., industry sustainability), particularly if such costs are borne by offending firms.     

Determination of direct and fugitive PM emissions in a Mediterranean harbour by means of classic and novel tracer methods

Remodelling works are frequent in harbour areas, given that they must adapt to rapidly changing market requirements. Depending on their nature (construction, demolition, etc.), these works may be carried out during long periods of time and thus exert a significant impact on the air quality at the harbours and their surroundings. The air quality at the Valencia harbour was studied during an enlargement project. Four sampling stations aimed to cover the major dust-emitting activities in the harbour. In addition, a sampling campaign was carried out to collect dust materials at their emission sources (e.g., loading and unloading of clinker and petroleum coke, as well as the enlargement works). Differences obtained between PM levels at the monitoring sites were correlated with the distance between sampling stations and enlargement works and/or harbour operations, as well as with the preferential wind direction. In all cases, the days with the highest PM_10 levels were linked to wind directions coinciding with the location of the enlargement works or the clinker and petroleum coke stocks. Classic source apportionment methodologies (PCA and CMB) were applied to the data, but their interpretation was complex due to the similar chemical signatures of PM originating from direct and fugitive emissions from stocked materials (e.g., clinker), and the enlargement works. To overcome this difficulty, a novel non-statistical approach was used to obtain quantitative estimations of the contributions from sources (petroleum coke and clinker), based on the correlation between specific PM components (e.g., carbonaceous species) and source tracers (e.g., V). Finally, a qualitative test using phenolphthalein was devised to identify the presence of clinker on the filters, which provided positive results. This novel tracer approach is thus recommended for harbour authorities.     

Predictive models of turbidity and water depth in the Doñana marshes using Landsat TM and ETM+ images

We have used Landsat-5 TM and Landsat-7 ETM+ images together with simultaneous ground-truth data at sample points in the Doñana marshes to predict water turbidity and depth from band reflectance using Generalized Additive Models. We have point samples for 12 different dates simultaneous with 7 Landsat-5 and 5 Landsat-7 overpasses. The best model for water turbidity in the marsh explained 38% of variance in ground-truth data and included as predictors band 3 (630–690 nm), band 5 (1550–1750 nm) and the ratio between bands 1 (450–520 nm) and 4 (760–900 nm). Water turbidity is easier to predict for water bodies like the Guadalquivir River and artificial ponds that are deep and not affected by bottom soil reflectance and aquatic vegetation. For the latter, a simple model using band 3 reflectance explains 78.6% of the variance. Water depth is easier to predict than turbidity. The best model for water depth in the marsh explains 78% of the variance and includes as predictors band 1, band 5, the ratio between band 2 (520–600 nm) and band 4, and bottom soil reflectance in band 4 in September, when the marsh is dry. The water turbidity and water depth models have been developed in order to reconstruct historical changes in Doñana wetlands during the last 30 years using the Landsat satellite images time series.