Slow Sand Filter
(Biological Filter)
• Elements of a slow sand filter
1. Supernatant or raw water
2. Bed of graded sand (on a support of gravel)
3. Under – drainage system
4. A system of filter control valves
1. Supernatant water:
• Depth varies from 1 - 1.5meters
• Serves two important purposes:
a) Provides a constant head of water
• This overcomes the resistance of the filter bed and promote downward flow of water through the sand bed
Safe & Wholesome Water
Water intended for human consumption should be both safe and wholesome.
This has been defined as water that is –
a. free from pathogenic agents
b. free from harmful chemical substances
c. pleasant to the taste, i.e., free from colour and odour; and
d. usable for domestic purposes
Water is said to be polluted or contaminated when it does not fulfil the above criteria
Without ample and safe drinking water, we cannot provide health care to the community
Free chlorine combines with ammonia and nitrogen of organic matter to form ‘Chloramines’
Chloramines are not efficient residual disinfectants
Yet these get included in the Total chlorine content of the water to be tested
We intend to measure only the ‘free residual chlorine ’ as this only will provide protection from subsequent contamination
We can measure ‘free chlorine ’ using OT test 10 seconds reading
We can measure ‘total chlorine ’ using OT test 5 minutes reading
‘Combined chlorine ’ = total chlorine - free chlorine
Disinfecting Heavily Polluted Water
The membrane processes have been in use for industrial or pharmaceutical applications, and now being applied to the treatment of drinking water
These do not provide residual disinfection hence a need to add small amount of persistent disinfectant like chlorine as a preservative during distribution.
The pore size of the membrane is smallest in RO and is in the following order:
RO < Nano filter < Ultra filter < Micro filter
The membrane processes of most significance in water treatment are:
High Pressure Processes
Reverse Osmosis
Tabulation
• Tabulation is the first step before the data is used for analysis or interpretation.
• A table can be simple or complex, depending upon the number or measurement of single set or multiple sets of items.
• Whether simple or complex, there are certain general principles which should be borne in mind in designing tables:
– The tables should be numbered e.g. Table 1, Table 2 etc.
– A title must be given to each table. The title must be brief and self-explanatory.
Tabulation
• Tabulation is the first step before the data is used for analysis or interpretation.
• A table can be simple or complex, depending upon the number or measurement of single set or multiple sets of items.
• Whether simple or complex, there are certain general principles which should be borne in mind in designing tables:
– The tables should be numbered e.g. Table 1, Table 2 etc.
– A title must be given to each table. The title must be brief and self-explanatory.
– The headings of columns and rows should be clear and concise
• A ‘Bar graph’ is a way to visually represent qualitative data.
• They enable visual comparison of frequencies in the categories.
– The length of each bar is proportional to the frequency to be represented. Hence a suitable scale is to be used.
– Bars may be vertical or horizontal.
– All the bars in a graph should be of the same width.
– The bars must be separated by appropriate spaces for clarity
• It has been suggested that the spacing between the bars should be half of the width of the bars
• Tabulation is the first step before the data is used for analysis or interpretation.
• A table can be simple or complex, depending upon the number or measurement of single set or multiple sets of items.
• Whether simple or complex, there are certain general principles which should be borne in mind in designing tables:
– The tables should be numbered e.g. Table 1, Table 2 etc.
– A title must be given to each table. The title must be brief and self-explanatory.
– The headings of columns and rows should be clear and concise
Normal Distribution concerns quantitative variable e.g. systolic BP, birth weights, age at menarche etc.
Summary values of quantitative data are:
Mean and Standard deviation (SD),
Mode and
Median
Standard deviation (SD) summarizes the variation of a large sample
Variable is mostly distributed normally if:
The sample is fairly large and
The sample units have been chosen randomly i.e. the sample is a ‘random sample’
Normal Distribution (Gaussian Distribution)
