Re-construction of the shut-down PM10 monitoring stations for the reliable assessment of PM10 in Berlin using fuzzy modelling and data transformation

A dense monitoring network is vital for the reliable assessment of PM10 in different parts of an urban area. In this study, a new idea is employed for the re-construction of the 20 shut-down PM10 monitoring stations of Berlin. It endeavours to find the non-linear relationship between the hourly PM10 concentration of both the still operating and the shut-down PM10 monitoring stations by using a fuzzy modelling technique, called modified active learning method (MALM). In addition, the simulations were performed by using not only raw PM10 databases but also log-transformed PM10 databases for skewness reduction. According to the results of hourly PM10 simulation (root mean square error about 13.0 μg/m³, correlation coefficient 0.88), the shut-down stations have been appropriately simulated and the idea of dense monitoring network development by the re-construction of the shut-down stations was realised. The results of simulations using raw and log-transformed databases showed that data transformation has no significant effect on the performance of MALM in the simulation of shut-down PM10 stations. By the combination of the 11 still operating stations and the 20 re-constructed stations, a dense monitoring network was generated for Berlin and was utilised for the calculation of the reliable monthly and mean annual PM10 concentration for five different PM10 zones in Berlin (the suburban-background, urban-background, urban-traffic, rural-background and suburban-traffic areas). The results showed that the mean annual concentration of PM10 at the five zones increased by about 13.0% in 2014 (26.3 μg/m³) in comparison with 2013 (23.3 μg/m³). Furthermore, the mean annual concentration of PM10 in the traffic lanes of the suburban (2013 25.0 μg/m³, 2014 26.9 μg/m³) and urban (2013 27.7 μg/m³, 2014 31.3 μg/m³) areas is about 14 and 20% higher than the PM10 concentration of suburban-background (2013 21.3 μg/m³, 2014 24.5 μg/m³) and urban-background (2013 23.0 μg/m³, 2014 26.1 μg/m³) areas, respectively.     

Electro-oxidation of the dye azure B: kinetics,mechanism, and by-products

In this work, the electrochemical degradation of the dye azure B in aqueous solutions was studied by electrochemical advanced oxidation processes (EAOPs), electro-Fenton, and anodic oxidation processes, using Pt/carbon-felt and boron-doped diamond (BDD)/carbon-felt cells with H₂O₂ electrogeneration. The higher oxidation power of the electro-Fenton (EF) process using BDD anode was demonstrated. The oxidative degradation of azure B by the electrochemically generated hydroxyl radicals (^?OH) follows a pseudo-first-order kinetics. The apparent rate constants of the oxidation of azure B by ^?OH were measured according to pseudo-first-order kinetic model. The absolute rate constant of azure B hydroxylation reaction was determined by competition kinetics method and found to be 1.19?×?10⁹ M^?1 s^?1. It was found that the electrochemical degradation of the dye leads to the formation of aromatic by-products which are then oxidized to aliphatic carboxylic acids before their almost mineralization to CO₂ and inorganic ions (sulfate, nitrate, and ammonium). The evolution of the TOC removal and time course of short-chain carboxylic acids during treatment were also investigated.     

Physicochemical fingerprinting of thermal waters of Beira Interior region of Portugal

Mineral natural waters and spas have been used for therapeutic purposes for centuries, with Portugal being a very rich country in thermal waters and spas that are mainly distributed by northern and central regions where Beira Interior region is located. The use of thermal waters for therapeutic purposes has always been aroused a continuous interest, being dependent on physicochemical fingerprinting of this type of waters the indication for a treatment in a specific pathological condition. In the present work, besides a literature review about the physicochemical composition of the thermal waters of the Beira Interior region and its therapeutic indications, it was carried out an exhaustive multivariate analysis—principal component analysis and cluster analysis—to assess the correlation between different physicochemical parameters and the therapeutic indications claims described for these spas and thermal waters. These statistical methods used for data analysis enables classification of thermal waters compositions into different groups, regarding to the different variable selected, making possible an interpretation of variables affecting water compositions. Actually, Monfortinho and Longroiva are clearly quite different of the others, and Cró and Fonte Santa de Almeida appear together in all analysis, suggesting a strong resemblance between these waters. Thereafter, the results obtained allow us to demonstrate the role of major components of the studied thermal waters on a particular therapeutic purpose/indication and hence based on compositional and physicochemical properties partially explain their therapeutic qualities and beneficial effects on human health. This classification agreed with the results obtained for the therapeutic indications approved by the Portuguese National Health Authority and proved to be a valuable tool for the regional typology of mineral medicinal waters, constituting an important guide of the therapeutic armamentarium for well and specific-oriented pathological disturbs.     

Optimal Policy Mechanism Design for Cross-Sector and Multi-Stage Pollution Control with a Bilevel Model: Application to SO<Subscript>2</Subscript> Emission in China

In this paper, we construct a multi-stage coordinated programming model under tax system to control SO₂ emission. The model is based on an explicitly formulated SO₂ abatement cost function created under Chinese condition. Analysis of the effectiveness and impact on the economy of the model is carried out with consideration of game theory. By solving the model, theoretical results show that the volume-based multi-stage SO₂ tax system has two properties: effectiveness and equal-rate. Based on these theoretical results, empirical study is also performed using Chinese historical data. Compared with yearly single-stage programming model, the tax rate generated by the coordinated multi-stage programming model is time-invariant and rather moderate in scale. The total abatement cost among planning years in our model is 21.03 % less than the actual number and 6.68 % less than that in the single-stage situation. The tax payment suggested by our model is 10.62 % less than by the single-stage model. In general, a coordinated multi-stage programming model helps reduce the overall costs of environmental protection while achieving the same emission control target with less burden added to the economy.     

Sustainable forest management in a mountain region in the Central Western Carpathians,northeastern Slovakia: the role of climate change

European forestry is facing many challenges, including the need to adapt to climate change and an unprecedented increase in forest damage. We investigated these challenges in a Norway spruce-dominated mountain region in Central Europe. We used the model Sibyla to explore forest biomass production to the year 2100 under climate change and under two alternative management systems: the currently applied management (CM), which strives to actively improve the forest’s adaptive capacity, and no management (NM) as a reference. Because biodiversity is thought to have mostly positive effects on the adaptive capacity of forests and on the quality of ecosystem services, we explored how climate change and management affect indicators of biodiversity. We found a differential response across the elevation-climatic gradient, including a drought-induced decrease in biomass production over large areas. With CM, the support of non-spruce species and the projected improvement of their growth increased tree species diversity. The promotion of species with higher survival rates led to a decrease in forest damage relative to both the present conditions and NM. NM preserved the high density of over-matured spruce trees, which caused forest damage to increase. An abundance of dead wood and large standing trees, which can increase biodiversity, increased with NM. Our results suggest that commercial spruce forests, which are not actively adapted to climate change, tend to preserve their monospecific composition at a cost of increased forest damage. The persisting high rates of damage along with the adverse effects of climate change make the prospects of such forests uncertain.     

Effects of sediment burial disturbance on macro and microelement dynamics in decomposing litter of <Emphasis Type="Italic">Phragmites australis</Emphasis> in the coastal marsh of the Yellow River estuary,China

From April 2008 to November 2009, a field decomposition experiment was conducted to investigate the effects of sediment burial on macro (C, N) and microelement (Pb, Cr, Cu, Zn, Ni, and Mn) variations in decomposing litter of Phragmites australis in the coastal marsh of the Yellow River estuary. Three one-off sediment burial treatments [no sediment burial (0 mm year^?1, S₀), current sediment burial (100 mm year^?1, S₁₀), and strong sediment burial (200 mm year^?1, S₂₀)] were laid in different decomposition sites. Results showed that sediment burials showed significant influence on the decomposition rate of P. australis, in the order of S₁₀ (0.001990 day^?1)?≈?S₂₀ (0.001710 day^?1)?>?S₀ (0.000768 day^?1) (p?<?0.05). The macro and microelement in decomposing litters of the three burial depths exhibited different temporal variations except for Cu, Zn, and Ni. No significant differences in C, N, Pb, Cr, Zn, and Mn concentrations were observed among the three burial treatments except for Cu and Ni (p?>?0.05). With increasing burial depth, N, Cr, Cu, Ni, and Mn concentrations generally increased, while C, Pb, and Zn concentrations varied insignificantly. Sediment burial was favorable for C and N release from P. australis, and, with increasing burial depth, the C release from litter significantly increased, and the N in litter shifted from accumulation to release. With a few exceptions, Pb, Cr, Zn, and Mn stocks in P. australis in the three treatments evidenced the export of metals from litter to environment, and, with increasing burial depth, the export amounts increased greatly. Stocks of Cu and Ni in P. australis in the S₁₀ and S₂₀ treatments were generally positive, evidencing incorporation of the two metals in most sampling times. Except for Ni, the variations of C, N, Pb, Cr, Cu, Zn, and Mn stocks in P. australis in the S₁₀ and S₂₀ treatments were approximated, indicating that the strong burial episodes (S₂₀) occurred in P. australis marsh in the future would have little influence on the stocks of these elements. With increasing burial depths, the P. australis was particularly efficient in binding Cu and Ni and releasing C, N, Pb, Cr, Zn, and Mn, implying that the potential eco-toxic risk of Pb, Cr, Zn, and Mn exposure might be very serious. This study emphasized the effects of different burials on nutrient and metal cycling and mass balance in the P. australis marsh of the Yellow River estuary.     

Vegetation response to hydrologic and geomorphic factors in an arid region of the Baja California Peninsula

Remotely sensed imageries were used to analyze the response of desert vegetation to physiographic factors and accumulated precipitation in drier and wetter years within a region of >16,500 km² sampled with 5,000 random pixels of 30 m. Vegetation development was indexed by the annual maximum values for greenness (SAVI) and canopy water content (NDII). Precipitation was interpolated from the 0.25° grid of the Tropical Rainfall Measurement Mission satellite-based estimates, showing a regional average of ～55 mm in the wetter year. The vegetation indices were only weakly related to total precipitation, often in a negative sense. Terrain factors that most often affected the vegetation indices, in multiple regression models, were Topographic Wetness Index, elevation, and slope gradient; these often had different signs for SAVI and for NDII. Models for NDII on intrusive igneous rocks gave better results than on extrusive igneous rocks. The strongest patterns in vegetation development were the contrast among Pacific coast, Cordillera, and Gulf coast subregions and the generally stronger results for NDII than SAVI.     

Tolerance values of benthic macroinvertebrates for stream biomonitoring: assessment of assumptions underlying scoring systems worldwide

Tolerance values (TVs) based on benthic macroinvertebrates are one of the most widely used tools for monitoring the biological impacts of water pollution, particularly in streams and rivers. We compiled TVs of benthic macroinvertebrates from 29 regions around the world to test 11 basic assumptions about pollution tolerance, that: (1) Arthropoda are < tolerant than non-Arthropoda; (2) Insecta < non-Insecta; (3) non-Oligochaeta < Oligochaeta; (4) other macroinvertebrates < Oligochaeta + Chironomidae; (5) other macroinvertebrate taxa < Isopoda + Gastropoda + Hirudinea; (6) Ephemeroptera + Plecoptera + Trichoptera (EPT) < Odonata + Coleoptera + Heteroptera (OCH); (7) EPT < non-EPT insects; (8) Diptera < Insecta; (9) Bivalvia < Gastropoda; (10) Baetidae < other Ephemeroptera; and (11) Hydropsychidae < other Trichoptera. We found that the first eight of these 11 assumptions were supported despite regional variability. In addition, we examined the effect of Best Professional Judgment (BPJ) and non-independence of TVs among countries by performing all analyses using subsets of the original dataset. These subsets included a group based on those systems using TVs that were derived from techniques other than BPJ, and groups based on methods used for TV assignment. The results obtained from these subsets and the entire dataset are similar. We also made seven a priori hypotheses about the regional similarity of TVs based on geography. Only one of these was supported. Development of TVs and the reporting of how they are assigned need to be more rigorous and be better described.     

Feature extraction using Hough transform for solid waste bin level detection and classification

This paper deals with the solid waste image detection and classification to detect and classify the solid waste bin level. To do so, Hough transform techniques is used for feature extraction to identify the line detection based on image’s gradient field. The feedforward neural network (FFNN) model is used to classify the level content of solid waste based on learning concept. Numbers of training have been performed using FFNN to learn and match the targets of the testing images to compute the sum squared error with the performance goal met. The images for each class are used as input samples for classification. Result from the neural network and the rules decision are used to build the receiver operating characteristic (ROC) graph. Decision graph shows the performance of the system waste system based on area under curve (AUC), WS-class reached 0.9875 for excellent result and WS-grade reached 0.8293 for good result. The system has been successfully designated with the motivation of solid waste bin monitoring system that can applied to a wide variety of local municipal authorities system.