Top PDF Evaluating urban surface water quality in Luton

Evaluating urban surface water quality in Luton

Evaluating urban surface water quality in Luton

Received: 19 June 2018 / Accepted: 25 January 2019 / Published online: 9 February 2019 # The Author(s) 2019 Abstract Using a single numerical value to indicate the quality of water, a so-called Water Quality Index (WQI) is a well-established way of rating the overall water quality status of a given water body. During the last few years, researchers in the water sector have devel- oped different such indices to address their specific needs. In this study, we attempt to obtain a WQI formula suited for evaluating the water quality of the River Lea. We have selected four different sites on the River Lea and explore the possibility of monitoring using a mini- mum number of parameters only. The results obtained are very encouraging and provide a strong indication that only three parameters are enough to indicate water quality of a water body.
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Comparative Study Of Surface And Ground Water Quality, Nyeri County Urban-Rural Surroundings, Kenya

Comparative Study Of Surface And Ground Water Quality, Nyeri County Urban-Rural Surroundings, Kenya

Fe, Cd, and Pb). Water samples were collected along the Chania River and boreholes within the catchment area. Sampling point were selected based on the dominant human activity, accessibility of the sampling point and safety. This was done over two seasons that is wet and dry season. The physiochemical parameter were determined insitu by use of a portable 3505 multi-parameter meter while the nutrients load was determined by use of UV-Vis 1800 Shimadzu spectrophotometer and the concentration of each heavy metals determined by using the AAS-6200 Shimadzu instrument against the standard calibration curve. The results displayed that for the physiochemical expect for one of the boreholes for the pH and two boreholes and the surface water for the turbidity all the others were below the recommended WHO values in both seasons. For nutrients load both surface and ground water recorded values below the WHO recommended values for both seasons though the values were generally higher during the dry seasons than wet seasons. For heavy metals both surface and ground water recorded higher values than the WHO values for lead, chromium and cadmium although all values for iron were below the WHO standards but copper had some values higher for two boreholes and three points on the river. There was no significant difference between the surface and ground water.
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Evaluating the importance of catchment hydrological parameters for urban surface water flood modelling using a simple hydro-inundation model

Evaluating the importance of catchment hydrological parameters for urban surface water flood modelling using a simple hydro-inundation model

water. The minimum time step that satisfies the FCFL condition for all the wet cells is used as the global 132 time step for this iteration. Comparison with the ATS scheme using the analytical solution of floodplain 133

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The impact of urban groundwater upon surface water quality : Birmingham - River Tame study, UK

The impact of urban groundwater upon surface water quality : Birmingham - River Tame study, UK

4.4 Surface water quality sampling. Surface water samples were obtained along the 23.8 km section of the River Tame between Bescot and Water Orton gauging stations (Figure 4.1, Appendix 10). A series of ~40 samples were taken to form a longitudinal profile along the river, and this was repeated four times during the project. Daily variations in water quality were examined at one site by repeat sampling through the course of a day. On four occasions surface water samples were taken in conjunction with river discharge measurements to enable estimates of total mass flux within the river to be made. Surface water sampling was conducted only during periods of dry weather flow with no rainfall having occurred within the preceding three days. A sampling device was constructed to allow representative samples to be collected from the approximate mid-depth of the river. A weighted ceramic jar with a cork seal was lowered on a string into the river and the seal removed only when the required depth was attained to prevent sample bias (e.g. volatilisation) which may occur close to the river surface. Samples for volatile organic compound (VOC) analyses were placed directly into the sample vial without filtration. A series of samples were taken from different positions in the river channel at the same time to determine the degree of variation in concentration across the channel. As part of a comparative study a total of three surface water samples and two samples of spring water were taken from Sutton Park.
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Impacts of urbanisation on hydrological and water quality dynamics, and urban water management : a review

Impacts of urbanisation on hydrological and water quality dynamics, and urban water management : a review

2.2 Metrics of measure for urban areas The transformation from undeveloped spaces into urban environments results in marked alterations to the landscape, with spatial and temporal dynamics of change varying between developed and developing countries. Impacts are observed through the alteration of the topography and sur- faces as a result of new construction, demolition and redeve- lopment and occur at a range of scales. Anthropogenic alteration of landscapes to expedite construction of buildings and infrastructure will impact on the dominant runoff-gen- erating processes and key flowpaths, having a substantial impact on catchment boundaries and drainage pathways (Rodriguez et al. 2013 ). Modification to slopes, elevations, soils and vegetation coverage all impact on the way rainfall is captured, stored and released in hydrological systems. Conversely, the removal of natural gradients via the smooth- ing of surfaces (e.g. during the construction of roads and walkways) results in the development of simplified drainage structures to transfer water from urban surfaces as quickly as possible. Individual buildings alter the way water is captured, stored and transferred, where variables such as building mate- rial, infrastructure (e.g. drainage) and aspect are significant. In addition, major infrastructure projects (such as the devel- opment of road and rail networks) result in modifications to the natural landscape via the development of embankments and creation of sloped, impervious surfaces that are designed to streamline transportation and prevent the build-up of sur- face water, respectively. In flat landscapes, roads are often raised or realigned to prevent flooding and rising water tables during storm events, creating an artificial gradient and sub- sequent runoff pathway. The input of crossfalls (or cambers) is governed by road-building standards, where an angle (usually 3% for a paved road) is built into the carriageway design to aid water mobilisation off the road surface by the shortest path which consequently alters topography. The development of the Olympic Park at Stratford in London required excavation and removal of land to provide a suitable surface for the development of large buildings, sport arenas and open public access areas (Webster 2013 ). Much of the surrounding area of Stratford was desolate land that sat
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Impacts of urbanisation on hydrological and water quality dynamics, and urban water management : a review

Impacts of urbanisation on hydrological and water quality dynamics, and urban water management : a review

Large-scale conventional stormwater drainage systems are constrained by a design capacity, where pluvial events that exceed these design thresholds result in inundation of drai- nage networks. Upgrading of large infrastructure is both expensive and disruptive, requiring large-scale excavation of surface areas including main road networks, so implementa- tion of increasingly sustainable methods that capture storm- water runoff are favoured (Houston et al. 2011). Individual buildings or new development complexes increasingly incor- porate local stormwater management techniques to reduce the volumes of rainfall being converted into runoff during pluvial events. Rainwater harvesting systems are increasingly being adopted to provide a supplementary water supply to mains supplies (Domenech and Sauri 2011). Rainwater har- vesting captures rainfall that has directly fallen onto a relevant surface where it is subsequently transferred to storage tanks or routed into drainage networks. Such systems reduce the localised impacts of pluvial events by removing water from the wider urban cycle. The most common mechanism of collecting rainfall is the establishment of “ roof catchments ” , which collect rainfall into conventional gutters that is then piped into storage tanks near buildings (Singh et al. 2013). Increasingly, incentives are being developed at regional and national scales worldwide, with many new developments being equipped with rainwater harvesting technology (Herrmann and Schmida 1999, Domenech and Sauri 2011). Such systems not only provide a clean alternative in water- scarce areas (particularly in developing countries), but also translate water from being viewed as a risk into a resource. In addition, vegetated rooftops provide a multifunctional method of reducing the environmental impact of the built environment by reducing roof surface temperature, increas- ing urban biodiversity and retention of stormwater during pluvial events (Carter and Keeler 2007). They capture, retain and evapotranspire rainfall back into the atmosphere, thus reducing the volume that is converted into runoff. Effectiveness of vegetated roof structures is a product of antecedent conditions, temperature and moisture retention capacity of vegetation retention, and water reduction rates of 34% and 69% have been reported (Teemusk and Mander 2007, Simmons et al. 2008, Gregoire and Clausen 2011). Shuster et al. (2013) assessed the impacts of installing 174 rain barrels and 85 rain gardens at the individual property (or parcel) scale, noting that these added detention capacity at even small scales, impacting overall runoff peak and the rising limb dynamics.
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Vulnerability assessment of surface water quality with an innovative integrated multi-parameter water quality index (IMWQI)

Vulnerability assessment of surface water quality with an innovative integrated multi-parameter water quality index (IMWQI)

Generally, WQI is a dimensionless number that combines multiple water quality factors into a single number by normalizing values to subjective rating curves and enabling easy interpretation of monitoring data (Miller et al., 1986). Conventionally, normalization of variables such as dissolved oxygen (DO), pH, biological oxygen demand (BOD), chemical oxygen demand (COD), Escherichia coli (E. coli), temperature, nutrients (nitrogen and phosphorus), etc., has been used for evaluating the quality of water separately, depending upon the designated water uses of the water body and local preferences (Chaturvedi and Bassin, 2010). In addition, the use of traditional approaches in the evaluation ofriver water quality are usually based on the comparison of the parameter values monitored with the local normative (Cude, 2001). The analysis, including one or few parameters grouped according to a common feature, may give partial information on the overall quality of water. The incorporation of many parameters into a single number is difficult via traditional approaches for grading the water quality of a watershed (Debels et al., 2005). Although mathematical-computational modeling of river water quality is useful for the assessment of the overall quality, the applications of the models were often restricted by the prerequisite knowledge of hydrodynamics and extensive validation (Rauch et al., 1998).
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Determine of Surface Water Quality Index in Iran

Determine of Surface Water Quality Index in Iran

The results of comparison between the IFWQI and the conventional IRWQI for some sampling sites of the Siminehrood basin between 2012 and 2013 are illustrated in Table 1. By examining the respective distribution of these results by quality classes, it is obvious that difference between the two indices appear throughout all of the quality classes, particular in the lower ones. The water of has a good quality upstream and becomes gently polluted downstream near urban areas, due to urban evacuation. It can also be noticed in Table 1 and 2 that, when conventional and fuzzy indices do not produce a similar evaluation, the gap between the qualities classes is usually of a single class. These disagreements are observed at sites where a single index is always problematic. The water of Barfejin has good quality most of the time. Here again it can be seen that the quality class obtained with the fuzzy index was lower for 42% of the sampled sites. Not surprisingly, the proposed fuzzy index revealed some disagreement between the Iran water quality indicator and the other surface water quality standards. The fuzzy indicator is more efficient in the sense that it is more precise in detecting water pollution because it appeases between water quality ranges as prescribed by the two water regulative legislation, namely the Iran legislation and that of Quebec, which is considered to be stricter. Given the nature of the two indices and quality thresholds used for their computing, this is quite usual. Fecal coliforms and total phosphorus are appraised more harshly with the Quebec.
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Compost Improves Urban Soil and Water Quality

Compost Improves Urban Soil and Water Quality

to a depth that was level with the surface of the plot. Gaps present along this border were packed with soil excavated during the installation. Runoff from out- side the plot was directed to two additional troughs located on each side of the center trough and was discarded. The runoff was measured every minute, and steady state conditions were assumed to have been established when runoff rates were constant for four consecutive minutes. Then runoff was collected every five minutes using a 30 s subsample. If the container became full before 30 s, the ex- act amount of time required to fill the container was recorded. Soil cores mea- suring 1.9-cm diameter × 30-cm length were collected to determine antecedent and post-rainfall soil water content for each plot. The soil cores for antecedent water content were taken adjacent to each plot, and for the post-rainfall soil were taken within each plot. This rainfall simulation was conducted on the lower west end of the plots where there was fill material that was darker than that on the lawn area than the compost/prairie grass area.
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Environmetric Data Interpretation to Assess Surface Water Quality

Environmetric Data Interpretation to Assess Surface Water Quality

Cluster 1 includes the indicators OSat, DO and AR and forms a pattern showing the impact of anthropogenic sources (e.g. industrial wastes) causing the oxida- tion properties of the water body. Cluster 2 contains another three parameters (P, NO3 and NH4) which probably get into one group of similarity due to their com- mon origin, e.g. agricultural and farming activities. The last identified cluster 3 unites the rest of the water quality parameters. This clustering resembles the role of the physical parameters on the water quality (temperature, conductivity) and, thus, the formation of possible seasonal patterns. Additionally, the biological impact of urban wastes (characterized by the correlation between BOD, COD and non-dissolved matter) contributes to the complete assessment of the river water quality and the creation of the respective water quality pattern.
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Analysis and modelling of surface water quality in river basins

Analysis and modelling of surface water quality in river basins

Water is very vital for human beings and the health of its ecosystem. Thus quality of water is extremely important. The surface water quality is a very sensitive issue and is also a great environmental concern worldwide. Surface water pollution by chemical, physical, microbial and biological contaminants can cause epidemic problems, at times all over the world. Fish survival / growth and other biodiversity, conservation activities, recreational activities like swimming and boating, industrial / municipal water supply, agricultural uses such as irrigation and livestock watering, waste disposal and all other water uses are affected by the physical, chemical, microbial and biological conditions that exist in the water courses and also in subsurface aquifers. The surface water systems are naturally open to the atmosphere, such as lakes, rivers, estuaries, reservoirs and coastal waters. A natural process such as changes in erosion, precipitation, weathering of crustal material as well as any anthropogenic influences such as urban, industrial and agricultural activities, increasing rate of consumption of water resources, degrade in the quality and quantity of surface water and make it unsuitable for domestic uses. Industrial waste water, runoff over the agricultural lands and municipal sewage disposal are the most vulnerable for water pollution (Singh 2005). The concentration of biological available nutrients in excess and concentration of toxic chemicals leads to diverse problems such as toxic algal blooms, loss of oxygen in water, fish kill loss of biodiversity and loss of aquatic plants and coral reefs (Vousta et al., 2001).
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Multi Criteria Framework for Surface Water Quality Management

Multi Criteria Framework for Surface Water Quality Management

Edku Lake, the third largest in the system of the northern coastal wetlands in Egypt, situated on the west part of Nile Delta, is considered as an important fishing area in Egypt. The lake suffers from high levels of aquatic vegetation and from the expansion in fish farming and agricultural discharges. To solve lake water quality problems, the study aims to develop the multi-criteria analysis (MCA) framework capable of evaluating the proposed lake water quality improvement scenarios. The work tasks were divided into two phases. In the first phase, many proposed scenarios involved on primary, secondary, surface wetland, biological biofilm, and adding a new artificial inlet were proposed by applying Surface-water Modeling System (SMS) with two di- mensional hydrodynamic. The second phase involved in developing the re- quired hierarchical MCA based on an integrated technical, environmental, economic and socio-community indicators. The main results of MCA showed that the water quality management scenario focusing on combination of ap- plying biological biofilm technique for drain effluents and also adding a new artificial inlet at the northern lake region can represent the optimum scenario for solving the lake water quality problems.
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Evaluating the multiple benefits of a Blue-Green Vision for urban surface water management

Evaluating the multiple benefits of a Blue-Green Vision for urban surface water management

acknowledged by all involved and the opportunities exploited from managing water in a way that brings it more into the open within green and blue spaces. As an example, the Philadelphia Water Department has developed a Green Infrastructure Vision designed to protect and enhance their watersheds by managing stormwater runoff with innovative green stormwater infrastructure throughout the City, while also maximizing economic, social, and environmental benefits for the wider Philadelphia area (Philadelphia Water Department, 2015). Portland, Oregon, has a similar vision centred on using green infrastructure for stormwater management, illustrated by the $55 million ‘Grey to Green’ project (2008 -2013) which included citywide construction of green streets, installation of eco-roofs, purchasing land to create green assets, removing culverts, planting thousands of street trees and educating local residents and communities about the functioning and benefits of green assets (BES, 2010, 2015).
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The Impact of Urban Flooding on Surface Water Quality of Awka Town

The Impact of Urban Flooding on Surface Water Quality of Awka Town

which end up in these ponds. The computation of the average of the values of those parameters in the four ponds during and after the rain (Table 2) confirms that. Those parameters which were higher even before the rain were probably so because of their accumulation over the years. At 95% confidence level, the F critical (2.05963) was greater than the F calculated (0.383372), hence we accept the null hypothesis which is consistent with the observation earlier made that the flood has significantly affected the water quality of these ponds (Table 3).

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Source characterisation of urban road surface pollutants for enhanced water quality predictions

Source characterisation of urban road surface pollutants for enhanced water quality predictions

data variance with high component loadings on Al, V, Mn and Fe while Mg, Cr, Co, Zn, Ba and Pb have moderate levels of loadings. Metals such as Mg, Al, Mn, Fe and Pb are primarily originating from natural soil (Mostert, et al., 2010). Enrichment factor analysis also recognised Mg, Al, Mn, Fe and Pb as minimum to moderate enriched metals in road build-up suggesting a significant contribution from soil. However, the other metals associated with component 1, namely, V, Cr, Co, Zn and Ba usually have anthropogenic sources of origin. These elements can originate from road surface abrasion due to vehicular activities. The signatures identified in the asphalt sample tested in this study consist of dominant elements Na, Ca, Mg, Fe and Al while Co, Cr, Zn, Ba and V are in significant quantities (Section 5.4.4 in Chapter 5). Kennedy and Gadd (2000) also investigated the elemental composition of road asphalt in Auckland, New Zealand and reported similar observations (Kennedy and Gadd, 2000). Moreover, Pb and Cr can also originate from road paint which can contribute to road build-up via road surface abrasion (Adachi and Tainosho, 2004). This indicates the possibility of involving two sources in component 1, which are soil and asphalt wear. Though Zn and V which are considered as tracer metals of vehicle emissions are associated with component 1, assigning component 1 as vehicle emissions can be misleading due to the absence of tracer elements such as Ni, and the presence of elements such as Pb. Pb cannot originate from vehicle emissions as Pb is currently not in use as a fuel additive. Therefore, component 1 is likely to be soil and asphalt wear. Due to similarities in signatures associated with soil and asphalt wear, PCA was unable to distinguish the two sources in separate components.
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Surface water quality

Surface water quality

BMPs and SUDS are increasingly required by planning authorities as a condition of development consent. In the UK, for example, local planning policy is driven by national water management policies designed to address surface water quality objectives and flood risk. However, whilst BMPs are rightly considered essential, it is unlikely that they will lead to the restoration of urban river quality just yet. There are several reasons for this. Firstly, the rate of SUDS implementation remains low. For example, a 2009 survey indicated that in Greater Manchester, England, an area of 1100 km 2 with a population of 2.5 million people, there were only 36 SUDS sites in operation (White and Alacon, 2009). Second, where SUDS are installed the primary motivation is usually mitigation of flood risk, which poses the greater threat to human well being. SUDS installed specifically for water quality reasons tend to be installed only to protect the most sensitive receiving waters. Third, SUDS are being implemented principally in a new urban development scheme which does nothing to combat the legacy effects of the existing built environment. Building stock renewal in developing countries is typically less than 1 % a year, so most homes we will be inhabiting in 2050 are already here, hence there is a strong need to retrofit SUDS in the existing built environment. This is more challenging than for new build, but ongoing research and case studies indicates it is feasible (SNIFFER, 2006). Even high density neighbourhoods offer opportunity for SUDS retrofit, through green roofs and devices such as infiltration trenches that occupy little surface space. Of course, funds for retrofit are limited, so knowing where to install SUDS for the greatest benefit is a key requirement.
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Water quality index to determine the surface water quality of Sankey tank and Mallathahalli lake, Bangalore urban district, Karnataka, India c

Water quality index to determine the surface water quality of Sankey tank and Mallathahalli lake, Bangalore urban district, Karnataka, India c

Abstract The present work aims at assessing the water quality index (WQI) in the surface water of Sankey tank and Mallathahalli lake situated in Bangalore Urban district by monitoring three sampling locations within Sankey tank (viz., A, B and C) and Mallathahalli lake (viz., Inlet, Centre and outlet) for a period of 3 months from March to May 2012. The surface water samples were subjected to com- prehensive physico-chemical analysis involving major cations (Ca 2? , Mg 2? , Na ? , K ? , Fe 2? ), anions (HCO 3 - , Cl - , SO 4 2- , NO 3 - , F - , PO 4 3- ) besides general parameters (pH, EC, TDS, alkalinity, total hardness, DO, BOD, COD, CO 2 , SiO 2 , colour, turbidity). For calculating the WQI, 14 parameters namely, pH, electrical conductivity, total dis- solved solids, total hardness, alkalinity, calcium, magne- sium, sodium, potassium, chloride, sulphate, nitrate, fluorides and iron were considered. SAR values indicated that both Sankey tank and Mallathahalli lake waters are excellent (S1) for irrigation, while electrical conductivity values classified these lake water, respectively under medium salinity (C2) and high (C3) salinity category. Correlation between SAR and electrical conductivity revealed that Sankey tank water is C2S1 (medium salinity- low sodium) type while Mallathahalli lake water is C3S1 (high salinity-low sodium) type. Sankey tank and Malla- thahalli lake water were, respectively hard and very hard in nature. Further, it is apparent from WQI values that Sankey tank water belongs to good water class with WQI values ranging from 50.34 to 63.38. The Mallathahalli lake water with WQI value ranging from 111.69 to 137.09, fall under poor water category.
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Surface water flood forecasting for urban communities

Surface water flood forecasting for urban communities

Verifying a probabilistic forecast system rigorously requires running the system over a long period of time and good quality observed data to test against. Although this was not possible for the Pilot Study due to its short duration and the challenges of collating comprehensive impact data, there was still much to gain from analysing specific case studies including borderline or non-events. This analysis benefited from a concerted effort during the Pilot Study to collate any relevant impact information from across the stakeholders, responders and anecdotally immediately after any event. Whilst the weather during the Commonwealth Games was largely fine, there were occasions when the additional surface water guidance provided a real benefit to the organisers and responders. This took two forms, firstly enabling the SFFS to advise that, although heavy rainfall was forecast in the wider West Central Scotland region, flooding impacts in Glasgow itself were unlikely. Secondly, as was the case on the last weekend of the Games, providing information on the timing, likely impacts and possibility of flooding in Glasgow. The performance over the Pilot Study in terms of these two benefit scenarios demonstrates its suitability and value for use as a surface water alerting tool for urban areas. A brief summary of the performance of the tool during three different case study events follows.
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Community cohesion in Luton

Community cohesion in Luton

5. Luton was not, however, one of the towns in which racial hostility erupted into violence during the summer of 2001 and, though there is certainly some racism in the town, the various communities live, for the most part, in reasonable harmony with each other. A variety of reasons for this were suggested: firstly, the leadership of the minority communities is more effective than in some other towns and cities and tends to seek agreement when problems arise; secondly, though Luton has its share of disadvantage, it does not have the deep and widespread poverty that afflicts some larger cities; thirdly, the policy of community policing is thought to have been effective in reducing tension; and fourthly, the town is relatively compact. The communities cannot, even if they wished to, avoid each other. A recent Home Office report on community cohesion (The Cantle Report) quoted a muslim of Pakistani origin as saying,
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Luton International College

Luton International College

Tuition fees should be paid directly to the College by cheque, credit card, bankers draft or telegraphic transfer. Bankers drafts should be made payable to LIC and sent by courier or registered post to ensure security. When sending funds by telegraphic transfer, the sending bank will require the LIC bank account details shown below. When paying the tuition fees, always quote your full name, your application number if you have one and the course you are going to study. Some of our approved representatives overseas may accept Bank Drafts made payable to Luton International College, which they will forward to us, but not cash. With this exception you should not pay tuition fees to anyone else but the college. Please do not send money to us by post.
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