The application of regenerable sorbents for mercury capture in gas phase

Mercury is a well-known toxic element, and flue gas streams emitted from coal-fired utilities are one of the largest anthropogenic sources of this element. This study briefly reviews the proposed technologies for reducing mercury emissions from coal combustion, focusing on an emerging process which involves the use of regenerable sorbents and especially those loaded with noble metals. Among the mercury species formed during coal combustion, elemental mercury is the most difficult to remove from the flue gases due to its low reactivity and insolubility in water. The widespread interest in using regenerable sorbents with metals is due to their ability to retain elemental mercury. With this technology, not only can efficiencies of 100 % be reached in the retention of elemental mercury but also a way to avoid the generation of new wastes loaded with mercury. This study considers the main aspects that must be taken into account when developing effective regenerable sorbents for mercury capture, with special attention to sorbents containing noble metals. The characteristics of this process are compared with those of other processes in a more advanced state of development.     

Comparison of real-time instruments and gravimetric method when measuring particulate matter in a residential building

This study used several real-time and filter-based aerosol instruments to measure PM_2.5 levels in a high-rise residential green building in the Northeastern US and compared performance of those instruments. PM_2.5 24-hr average concentrations were determined using a Personal Modular Impactor (PMI) with 2.5 µm cut (SKC Inc., Eighty Four, PA) and a direct reading pDR-1500 (Thermo Scientific, Franklin, MA) as well as its filter. 1-hr average PM_2.5 concentrations were measured in the same apartments with an Aerotrak Optical Particle Counter (OPC) (model 8220, TSI, Inc., Shoreview, MN) and a DustTrak DRX mass monitor (model 8534, TSI, Inc., Shoreview, MN). OPC and DRX measurements were compared with concurrent 1-hr mass concentration from the pDR-1500. The pDR-1500 direct reading showed approximately 40% higher particle mass concentration compared to its own filter (n = 41), and 25% higher PM_2.5 mass concentration compared to the PMI_2.5 filter. The pDR-1500 direct reading and PMI_2.5 in non-smoking homes (self-reported) were not significantly different (n = 10, R² = 0.937), while the difference between measurements for smoking homes was 44% (n = 31, R² = 0.773). Both OPC and DRX data had substantial and significant systematic and proportional biases compared with pDR-1500 readings. However, these methods were highly correlated: R² = 0.936 for OPC versus pDR-1500 reading and R² = 0.863 for DRX versus pDR-1500 reading. The data suggest that accuracy of aerosol mass concentrations from direct-reading instruments in indoor environments depends on the instrument, and that correction factors can be used to reduce biases of these real-time monitors in residential green buildings with similar aerosol properties.

Implications: This study used several real-time and filter-based aerosol instruments to measure PM_2.5 levels in a high-rise residential green building in the northeastern United States and compared performance of those instruments. The data show that while the use of real-time monitors is convenient for measurement of airborne PM at short time scales, the accuracy of those monitors depends on a particular instrument. Bias correction factors identified in this paper could provide guidance for other studies using direct-reading instruments to measure PM concentrations.     

Source apportionment of PM2.5 for supporting control strategies in the Monterrey Metropolitan Area,Mexico

The Monterrey Metropolitan Area (MMA) in Northeast Mexico has shown high PM_2.5 concentrations since 2003. The data shows that the annual average concentration exceeds from 2 to 3 times the Mexican PM_2.5 annual air quality standard of 12 µg/m³. In a previous work we studied the chemical characterization of PM_2.5 in two sites of the MMA during the winter season. Among the most important components we found ammonium sulfate and nitrate, elemental and organic carbon, and crustal matter. In this work we present the results of a second chemical characterization study performed during the summer time and the application of the chemical mass balance (CMB) model to determine the source apportionment of air pollutants in the region. The chemical analysis results show that the chemical composition of PM_2.5 is similar in both sites and periods of the year. The results of the chemical analysis and the CMB model show that industrial, traffic, and combustion activities in the area are the major sources of primary PM_2.5 and precursor gases of secondary inorganic and organic aerosol (SO₂, NOx, NH₃, and volatile organic compounds [VOCs]). We also found that black carbon and organic carbon are important components of PM_2.5 in the MMA. These results are consistent with the MMA emission inventory that reports as major sources of particles and SO₂ a refinery and fuel combustion, as well as nitrogen oxides and ammonium from transportation and industrial activities in the MMA and ammonium form agricultural activities in the state. The results of this work are important to identify and support effective actions to reduce direct emissions of PM_2.5 and its precursor gases to improve air quality in the MMA. Implications: The Monterrey Metropolitan Area (MMA) has been classified as the most air-polluted area in Mexico by the World Health Organization (WHO). Effective actions need to be taken to control primary sources of PM_2.5 and its precursors, reducing health risks on the population exposed and their associated costs. The results of this study identify the main sources and their estimated contribution to PM_2.5 mass concentration, providing valuable information to the local environmental authorities to take decisions on PM_2.5 control strategies in the MMA.     

Present and future climate conditions for winegrowing in Spain

This study deals with the question of how winegrowing in Spain may be altered by anthropogenic climate change. The present state and expected future development of three bioclimatic indices relevant for winegrowing were assessed by observation, and four regional climate models from the EU-ENSEMBLES project were investigated. When comparing the 2061–2090 scenario period to the 1961–1990 reference period, the models unanimously indicate a significant increase in the mean of the two considered thermal indices over the entire study region. However, for the index based on temperature and precipitation, the models are heavily biased when verified against observations and generally disagree on the size of the projected future change. For this index, unanimous model agreement was only found for northwestern Spain where all models indicated a significant decrease in the mean. From these results, regional climate change is expected to negatively affect the quality of wine in the growing regions of central and southern Spain, and the Ebro valley, whereas positive effects should be expected in the northwest. No significant changes in the risk of mildew infestation are to be expected except for the northwest, where this risk is projected to decrease.     

Climate change,multiple stressors and human vulnerability: a systematic review

We systematically reviewed current climate change literature in order to examine how multiple processes that affect human vulnerability have been studied. Of the 125 reviewed articles, 79 % were published after 2009. There are numerous concepts that point out to stressors other than climate change that were used in reviewed studies. These different concepts were used interchangeably, and they illustrate processes that act on different scales. Most widely used concepts included non-climatic (40 % of the articles), multiple stressors (38 %) and other factors (37 %). About 75 % of the studies either acknowledged or carefully analyzed the social and environmental context in which vulnerability is experienced. One-third of the studies recognized climate change-related stressors as the most important, one-third argued that stressors other than climate are more important, and the rest of the studies did not analyze the relative importance of the different processes. Interactions between different stressors were mentioned in 76 % and analyzed explicitly in 28 % of the articles. Our review shows that there are studies that analyze the social context of vulnerability within climate change-related literature and this literature is rapidly expanding. Reviewed studies point out that there are multiple interacting stressors, whose interlinkages need to be carefully analyzed and targeted by policies, which integrate adaptation to climate change and other stressors. In conclusion, we suggest that future studies should include analytical frameworks that reflect dissimilarities between different types of stressors, methodological triangulation to identify key stressors and analysis of interactions between multiple stressors across different scales.     

A review of potential physical impacts on harbours in the Mediterranean Sea under climate change

Regional Environmental Change - The potential impact of climate change on port operations and infrastructures has received much less attention than the corresponding impact for beach systems....     

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.     

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.