924 resultados para Dry days
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Atmospheric deposition is one of the most important pollutant pathways for urban stormwater pollution. Atmospheric deposition can be in the form of dry and wet depositions which have distinct characteristics in terms of pollutant types, pollutant sources and influential parameters. This paper discusses the outcomes of a comprehensive study undertaken to identify the characteristics of wet and dry deposition of pollutants. Sample collection was undertaken at eight study sites with distinct characteristics. Four sites were close to road sites with varying traffic characteristics, whilst the other four sites had different land use characteristics. Dry deposition samples were collected for different antecedent dry days and wet deposition samples were collected immediately after rainfall events. The dry deposition was found to increase with the antecedent dry days and consisted of relatively coarser particles (greater than 1 µm) when compared to wet deposition. The wet deposition showed a strong affinity to rainfall depth, but was not related to the antecedent dry period. It was also found that smaller size particles (less than 1 µm) travel much longer distances from the source and deposit mainly with the wet deposition
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Rapid urbanisation and resulting continuous increase in traffic has been recognised as key factors in the contribution of increased pollutant loads to urban stormwater and in turn to receiving waters. Urbanisation primarily increases anthropogenic activities and the percentage of impervious surfaces in urban areas. These processes are collectively responsible for urban stormwater pollution. In this regard, urban traffic and land use related activities have been recognised as the primary pollutant sources. This is primarily due to the generation of a range of key pollutants such as solids, heavy metals and PAHs. Appropriate treatment system design is the most viable approach to mitigate stormwater pollution. However, limited understanding of the pollutant process and transport pathways constrains effective treatment design. This highlights necessity for the detailed understanding of traffic and other land use related pollutants processes and pathways in relation to urban stormwater pollution. This study has created new knowledge in relation to pollutant processes and transport pathways encompassing atmospheric pollutants, atmospheric deposition and build-up on ground surfaces of traffic generated key pollutants. The research study was primarily based on in-depth experimental investigations. This thesis describes the extensive knowledge created relating to the processes of atmospheric pollutant build-up, atmospheric deposition and road surface build-up and establishing their relationships as a chain of processes. The analysis of atmospheric deposition revealed that both traffic and land use related sources contribute total suspended particulate matter (TSP) to the atmosphere. Traffic sources become dominant during weekdays whereas land use related sources become dominant during weekends due to the reduction in traffic sources. The analysis further concluded that atmospheric TSP, polycyclic aromatic hydrocarbons (PAHs) and heavy metals (HMs) concentrations are highly influenced by total average daily heavy duty traffic, traffic congestion and the fraction of commercial and industrial land uses. A set of mathematical equation were developed to predict TSP, PAHs and HMs concentrations in the atmosphere based on the influential traffic and land use related parameters. Dry deposition samples were collected for different antecedent dry days and wet deposition samples were collected immediately after rainfall events. The dry deposition was found to increase with the antecedent dry days and consisted of relatively coarser particles (greater than 1.4 ìm) when compared to wet deposition. The wet deposition showed a strong affinity to rainfall depth, but was not related to the antecedent dry period. It was also found that smaller size particles (less than 1.4 ìm) travel much longer distances from the source and deposit mainly with the wet deposition. Pollutants in wet deposition are less sensitive to the source characteristics compared to dry deposition. Atmospheric deposition of HMs is not directly influenced by land use but rather by proximity to high emission sources such as highways. Therefore, it is important to consider atmospheric deposition as a key pollutant source to urban stormwater in the vicinity of these types of sources. Build-up was analysed for five different particle size fractions, namely, <1 ìm, 1-75 ìm, 75-150 ìm, 150-300 ìm and >300 ìm for solids, PAHs and HMs. The outcomes of the study indicated that PAHs and HMs in the <75 ìm size fraction are generated mainly by traffic related activities whereas the > 150 ìm size fraction is generated by both traffic and land use related sources. Atmospheric deposition is an important source for HMs build-up on roads, whereas the contribution of PAHs from atmospheric sources is limited. A comprehensive approach was developed to predict traffic and other land use related pollutants in urban stormwater based on traffic and other land use characteristics. This approach primarily included the development of a set of mathematical equations to predict traffic generated pollutants by linking traffic and land use characteristics to stormwater quality through mathematical modelling. The outcomes of this research will contribute to the design of appropriate treatment systems to safeguard urban receiving water quality for future traffic growth scenarios. The „real world. application of knowledge generated was demonstrated through mathematical modelling of solids in urban stormwater, accounting for the variability in traffic and land use characteristics.
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Stormwater bioretention basins are subjected to spontaneous intermittent wetting and drying, unlike water treatment filter systems that are subjected to continuous feed. Drinking water filters when constructed new or after back-wash, are subjected to a phase of stabilization. Experiments show that bioretention basins are similarly impacted by intermittent wetting and drying. The common parameter monitored in the stabilisation of filters is the concentration of total solids in the outflow. Filter media in bioretention basins however, consists of a mix of particulate organic matter and fine sand. Organic carbon and solids are therefore needed to be monitored. Four Perspex bioretention filter columns of 94 mm (ID) were packed with a filter layer (800 mm), transition layer and a gravel layer and operated with synthetic stormwater in the laboratory. The filter layer contained 8% organic material by weight. A free board of 350 mm provided detention storage and head to facilitate infiltration. Synthetic stormwater was prepared by adding NH4NO3 (ammonium nitrate) and C2H5NO2 (glycine) and a mixture of kaolinite and montmorillonite clay, to tapwater. The columns were fed with synthetic stormwater with different Antecedent Dry Days (ADD) (0 – 25 day) and constant inflow concentration (2 ppm: nitrate-nitrogen, 1.5 ppm: ammonium-nitrogen, 2.5 ppm: organic-nitrogen 100 ppm: total suspended solids and 7 ppm: organic carbon) at a feed rate of 100mL.min (85.7cm/h). Samples were collected from the outflow at different time intervals between 2 – 150 min from the start of outflow and were tested for Total Suspended Solids (TSS) and Total Organic Carbon (TOC). Both TSS and TOC concentrations in the outflow were observed to be much higher than the concentration of both the parameters in the inflow during the stabilisation period indicating a phase of wash-off (first flush) which lasted for approximately 30 min for both parameters at the beginning of each storm event. The wash-off of TSS and TOC were found to be highly variable depending on the age of the filter and the number of antecedent dry days. The duration of stabilisation phase in the experiments is significant compared with many of the stormwater events. A computational analysis on total mass of each pollutant further affirmed the significance of the first flush of an event on removal of these pollutants. Therefore, the kinetics of the first flush in the stabilisation phase needs to be considered in the performance analysis of the systems.
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Nitrogen is an important nutrient that can impact the quality of aquatic environments when present in high concentration. Even though low concentration levels of ammonium-nitrogen have been observed in laboratory studies in bioretention basins, poor removal or even the production of nitrate-nitrogen within the filter is often recorded in such studies. Ten Perspex biofilter columns of 94 mm (internal diameter) were packed with a filter layer, transition layer and a gravel layer. While the filter layer was packed to a height of 800 mm, transition and gravel layers were packed to a composite height of 220 mm and operated with simulated stormwater in the laboratory. The filter layer contained 8% organic material by weight. A free board of 350 mm provided detention storage and head to facilitate infiltration. The columns were operated with different antecedent dry days (0 d to 21 d) and constant inflow concentration at a feed rate of 100 mL/min. Samples were collected from the outflow at different time intervals, between 2 min and 150 min from the start of outflow, and were tested for nitrate-nitrogen and total organic carbon. Washoff of organic carbon from the filter layer was observed to occur for 30 min of outflow. This indicated washoff of organic carbon from the filter itself. At the same time, a very low concentration of nitrate-nitrogen was recorded at the beginning of the outflow, indicating the effective removal of nitrate-nitrogen. We conclude that the removal of nitrate-nitrogen is insignificant during the wetting phase of a rainfall event and the process of denitrification is more pronounced during the drying phase of a rainfall event. Thus intermittent wetting and drying is crucial for the removal of nitrate-nitrogen in bioretention basins.
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This research study comprehensively analyses the dynamics of nitrogen and suspended solids removal in stormwater biofilters. The study focuses on pollutant removal during an event with time, rather than the conventional event-mean analysis. Antecedent dry days (number of days in between rainfall) during which biofilters remain dry and the inflow concentration of pollutants were two other important variables analysed in this study. The research outcome highlights the significance of dry-phase processes and the process of stabilization on filter performance and sets a paradigm shift from the current approach towards an innovative way of performance analysis of biofilters.
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Ripening period refers to a phase of stabilization in sand filters in water treatment systems that follows a new installation or cleaning of the filter. Intermittent wetting and drying, a unique property of stormwater biofilters, would similarly be subjected to a phase of stabilization. Suspended solids, is an important parameter that is often used to monitor the stabilization of sand filters in water treatment systems. Stormwater biofilters however, contain organic material that is added to the filter layer to enhance nitrate removal, the dynamics of which is seldom analysed in stabilization of stormwater biofilters. Therefore, in this study of stormwater biofiltration in addition to suspended solids (Turbidity), organic matter (TOC, DOC, TN and TKN) was also monitored as a parameter for stabilization of the stormwater biofilter. One Perspex bioretention column (94 mm internal diameter) was fabricated with filter layer that contained 8% organic material and fed with tapwater with different antecedent dry days (0 – 40 day) at 100 mL/min. Samples were collected from the outflow at different time intervals between 2 – 150 minutes and were tested for Total Organic Carbon, Dissolved Organic Carbon, Total Nitrogen, Total Kjeldhal Nitrogen and Turbidity. The column was observed to experience two phases of stabilization, one at the beginning of each event that lasted for 30 minutes while the other phase was observed across subsequent events that related to the age of filter.
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High concentrations of nitrate-nitrogen degrade the quality of aquatic environments. The primary mechanism by which nitrate-nitrogen is removed (denitrification) requires anoxic conditions and electron donors. While removal of total and ammonium-nitrogen is often high in stormwater biofilters, poor removal or even the release of nitrate-nitrogen in the outflow has often been observed. Five Perspex biofilter columns (94 mm internal diameter) were fabricated with a filter layer that contained 8% organic material. Columns were operated at 875 mm/h 875 mm/h and fed with simulated stormwater with different antecedent dry days (ADDs) and concentrations of nitrate-nitrogen. Samples were collected from the outflow at different time intervals between 2 and 150 min and were tested for nitrate-nitrogen. The removal of nitrate-nitrogen varied during an event from a high removal percentage (60–90%) in the initial outflow that gradually decreased in the first 30 min and settled at 0–15% removal thereafter. This remained consistent during all simulated events independent of the number of ADDs or inflow concentrations. ADDs and previous event feed concentrations affected the outflow nitrate-nitrogen concentration in the first 30 min of the current event. Therefore, from this study it is concluded that denitrification within stormwater biofilters occurs mainly during drying periods rather than wetting periods.
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Heavy metals build-up on urban road surfaces is a complex process and influenced by a diverse range of factors. Although numerous research studies have been conducted in the area of heavy metals build-up, limited research has been undertaken to rank these factors in terms of their influence on the build-up process. This results in limitations in the identification of the most critical factor/s for accurately estimating heavy metal loads and for designing effective stormwater treatment measures. The research study undertook an in-depth analysis of the factors which influence heavy metals build-up based on data generated from a number of different geographical locations around the world. Traffic volume was found to be the highest ranked factor in terms of influencing heavy metals build-up while land use was ranked the second. Proximity to arterial roads, antecedent dry days and road surface roughness has a relatively lower ranking. Furthermore, the study outcomes advances the conceptual understanding of heavy metals build-up based on the finding that with increasing traffic volume, total heavy metal build-up load increases while the variability decreases. The outcomes from this research study are expected to contribute to more accurate estimation of heavy metals build-up loads leading to more effective stormwater treatment design.
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The coarse spacing of automatic rain gauges complicates near-real- time spatial analyses of precipitation. We test the possibility of improving such analyses by considering, in addition to the in situ measurements, the spatial covariance structure inferred from past observations with a denser network. To this end, a statistical reconstruction technique, reduced space optimal interpolation (RSOI), is applied over Switzerland, a region of complex topography. RSOI consists of two main parts. First, principal component analysis (PCA) is applied to obtain a reduced space representation of gridded high- resolution precipitation fields available for a multiyear calibration period in the past. Second, sparse real-time rain gauge observations are used to estimate the principal component scores and to reconstruct the precipitation field. In this way, climatological information at higher resolution than the near-real-time measurements is incorporated into the spatial analysis. PCA is found to efficiently reduce the dimensionality of the calibration fields, and RSOI is successful despite the difficulties associated with the statistical distribution of daily precipitation (skewness, dry days). Examples and a systematic evaluation show substantial added value over a simple interpolation technique that uses near-real-time observations only. The benefit is particularly strong for larger- scale precipitation and prominent topographic effects. Small-scale precipitation features are reconstructed at a skill comparable to that of the simple technique. Stratifying the reconstruction method by the types of weather type classifications yields little added skill. Apart from application in near real time, RSOI may also be valuable for enhancing instrumental precipitation analyses for the historic past when direct observations were sparse.
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In this study, change in rainfall, temperature and river discharge are analysed over the last three decades in Central Vietnam. Trends and rainfall indices are evaluated using non-parametric tests at different temporal levels. To overcome the sparse locally available network, the high resolution APHRODITE gridded dataset is used in addition to the existing rain gauges. Finally, existing linkages between discharge changes and trends in rainfall and temperature are explored. Results are indicative of an intensification of rainfall (+15%/decade), with more extreme and longer events. A significant increase in winter rainfall and a decrease in consecutive dry days provides strong evidence for a lengthening wet season in Central Vietnam. In addition, trends based on APHRODITE suggest a strong orographic signal in winter and annual trends. These results underline the local variability in the impacts of climatic change at the global scale. Consequently, it is important that change detection investigations are conducted at the local scale. A very weak signal is detected in the trend of minimum temperature (+0.2°C/decade). River discharge trends show an increase in mean discharge (31 to 35%/decade) over the last decades. Between 54 and 74% of this increase is explained by the increase in precipitation. The maximum discharge also responds significantly to precipitation changes leading to a lengthened wet season and an increase in extreme rainfall events. Such trends can be linked with a likely increase in floods in Central Vietnam, which is important for future adaptation planning and management and flood preparedness in the region. Copyright © 2012 John Wiley & Sons, Ltd.
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Global controls on month-by-month fractional burnt area (2000–2005) were investigated by fitting a generalised linear model (GLM) to Global Fire Emissions Database (GFED) data, with 11 predictor variables representing vegetation, climate, land use and potential ignition sources. Burnt area is shown to increase with annual net primary production (NPP), number of dry days, maximum temperature, grazing-land area, grass/shrub cover and diurnal temperature range, and to decrease with soil moisture, cropland area and population density. Lightning showed an apparent (weak) negative influence, but this disappeared when pure seasonal-cycle effects were taken into account. The model predicts observed geographic and seasonal patterns, as well as the emergent relationships seen when burnt area is plotted against each variable separately. Unimodal relationships with mean annual temperature and precipitation, population density and gross domestic product (GDP) are reproduced too, and are thus shown to be secondary consequences of correlations between different controls (e.g. high NPP with high precipitation; low NPP with low population density and GDP). These findings have major implications for the design of global fire models, as several assumptions in current models – most notably, the widely assumed dependence of fire frequency on ignition rates – are evidently incorrect.
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The Land surface Processes and eXchanges (LPX) model is a fire-enabled dynamic global vegetation model that performs well globally but has problems representing fire regimes and vegetative mix in savannas. Here we focus on improving the fire module. To improve the representation of ignitions, we introduced a reatment of lightning that allows the fraction of ground strikes to vary spatially and seasonally, realistically partitions strike distribution between wet and dry days, and varies the number of dry days with strikes. Fuel availability and moisture content were improved by implementing decomposition rates specific to individual plant functional types and litter classes, and litter drying rates driven by atmospheric water content. To improve water extraction by grasses, we use realistic plant-specific treatments of deep roots. To improve fire responses, we introduced adaptive bark thickness and post-fire resprouting for tropical and temperate broadleaf trees. All improvements are based on extensive analyses of relevant observational data sets. We test model performance for Australia, first evaluating parameterisations separately and then measuring overall behaviour against standard benchmarks. Changes to the lightning parameterisation produce a more realistic simulation of fires in southeastern and central Australia. Implementation of PFT-specific decomposition rates enhances performance in central Australia. Changes in fuel drying improve fire in northern Australia, while changes in rooting depth produce a more realistic simulation of fuel availability and structure in central and northern Australia. The introduction of adaptive bark thickness and resprouting produces more realistic fire regimes in Australian savannas. We also show that the model simulates biomass recovery rates consistent with observations from several different regions of the world characterised by resprouting vegetation. The new model (LPX-Mv1) produces an improved simulation of observed vegetation composition and mean annual burnt area, by 33 and 18% respectively compared to LPX.
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Precipitation and temperature climate indices are calculated using the National Centers for Environmental Prediction/National Center for Atmospheric Research (NCEP/NCAR) reanalysis and validated against observational data from some stations over Brazil and other data sources. The spatial patterns of the climate indices trends are analyzed for the period 1961-1990 over South America. In addition, the correlation and linear regression coefficients for some specific stations were also obtained in order to compare with the reanalysis data. In general, the results suggest that NCEP/NCAR reanalysis can provide useful information about minimum temperature and consecutive dry days indices at individual grid cells in Brazil. However, some regional differences in the climate indices trends are observed when different data sets are compared. For instance, the NCEP/NCAR reanalysis shows a reversal signal for all rainfall annual indices and the cold night index over Argentina. Despite these differences, maps of the trends for most of the annual climate indices obtained from the NCEP/NCAR reanalysis and BRANT analysis are generally in good agreement with other available data sources and previous findings in the literature for large areas of southern South America. The pattern of trends for the precipitation annual indices over the 30 years analyzed indicates a change to wetter conditions over southern and southeastern parts of Brazil, Paraguay, Uruguay, central and northern Argentina, and parts of Chile and a decrease over southwestern South America. All over South America, the climate indices related to the minimum temperature (warm or cold nights) have clearly shown a warming tendency; however, no consistent changes in maximum temperature extremes (warm and cold days) have been observed. Therefore, one must be careful before suggesting an), trends for warm or cold days.
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The Brazilian Northeast is the most vulnerable region to climatic variability risks. For the Brazilian semi-arid is expected a reduction in the overall rates of precipitation and an increase in the number of dry days. These changes predicted by the IPCC (2007) will intensify the rainfall and droughts period that could promote the dominance of cyanobacteria, thus affecting the water quality of reservoirs, that are most used for water supply, in the semi-arid. The aim of this study was to evaluate the effects of increasing temperature combined with nutrient enrichment on the functional structure of the phytoplankton community of a mesotrophic reservoir in the semi-arid, in the worst case scenario of climate change predicted by the IPCC (2007). Two experiments were performed, one in a rainy season and another in the dry season. In the water sampled, nutrients (nitrate and orthophosphate) were added in different concentrations. The microcosms were submitted to two different temperatures, five-year average of air temperature in the reservoir (control) and 4°C above the control temperature (warming). The results of this study showed that warming and nutrient enrichment benefited mainly the functional groups of cyanobacteria. During the rainy season it was verified the increasing biomass of small functional groups of unicellular and opportunists algae such as F (colonial green algae with mucilage) and X1 (nanoplanktonic algae of eutrophic lake systems). It was also observed an increasing in total biomass, in the richness and diversity of the community. In the dry season experiment there was a greater contribution in the relative biomass of filamentous algae, with a replacement of the group S1 (non-filamentous cyanobacteria with heterocytes) for H1 (filamentous cyanobacteria with heterocytes) in nutrient- enriched treatments. Moreover, there was also loss in total biomass, species richness and diversity of the community. The effects of temperature and nutrients manipulation on phytoplankton community of reservoir Ministro João Alves provoked changes in species richness, the diversity of the community and its functional composition, being the dry period which showed the highest susceptibility to the increase in the contribution of potentially toxic cyanobacteria with heterocytes
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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)