EPA-450/3-73-008
September 1973
GUIDELINES
FOR THE DEVELOPMENT
OF AN AIR QUALITY
DATA SYSTEM
U.S. ENVIRONMENTAL PROTECTION AGENCY
Office of Air and Water Programs
Office of Air Quality Planning and Standards
Research Triangle Park, North Carolina 27711
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EPA-450/3-73-008
GUIDELINES
FOR THE DEVELOPMENT
OF AN AIR QUALITY
DATA SYSTEM
by
Charles Zimmer, Eugene Forte and Robert Braley
Fed co-Environmental
Suite 8 Atkinson Square
Cincinnati, Ohio 45246
Contract No. 68-02-0044
EPA Project Officer: Gerald Nehls
Prepared for
ENVIRONMENTAL PROTECTION AGENCY
Office of Air and Water Programs
Office of Air Quality Planning and Standards
Research Triangle Park, N. C. 27711
September 1973
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This report is issued by the Environmental Protection Agency to
report technical data of interest to a limited number of readers..
Copies are available free of charge to Federal employees, current
contractors and grantees, and nonprofit organizations - as supplies
permit - from the Air Pollution Technical Information Center,
Environmental Protection Agency, Research Triangle Park, North Carolina
27711, or from the National Technical Information Service, 5285
Port Royal Road, Springfield, Virginia 22151.
This report was furnished to the Environmental Protection Agency by
Pedco-Environmental, Suite 8 Atkinson Square, Cincinnati, Ohio, in
fulfillment of Contract No. 68-02-0044. The contents of this report
are reproduced herein as received from Pedco-Environmental. The
opinions, findings, and conclusions expressed are those of the author
and not necessarily those of the Environmental Protection Agency.
Mention of company or product names is not to be considered as an
endorsement by the Environmental Protection Agency.
Publication No. EPA-450/3-73-008
ii
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ACKNOWLEDGEMENT
Many individuals and organizations have been helpful
in developing this guideline; for their contributions the
project management extends its sincere gratitude.
The contributions of Messrs. Eugene Ermenc and Robert
Shaw of the City of Cincinnati Air Pollution Control Division,
Robert Callahan and Justin Fisher of the City of Cincinnati
and Hamilton County Regional Computer Center were of particular
significance.
Mr. Gerald Nehls, Environmental Protection Agency and
Mr. Charles Schumann, City of Cincinnati Air Pollution Control
Division served as project officers for their respective .
organizations. Mr. Charles Zimmer, PEDCo-Environmental
Specialists, Inc., the project manager, was assisted by
Eugene Forte and Robert Braley.
111
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This report was furnished to the Environmental Protection
Agency tğy PEDCo-Environmental Specialists, Inc. in fulfillment
of a contract with the City of Cincinnati, Ohio which was
supported in part by funds contributed to the City of Cincinnati,
Ohio by the Environmental Protection Agency. The contents of
this report are reproduced herein as received from the contractor.
The opinions, findings, and conclusions are those of the authors
and are not necessarily those of the Environmental Protection
Agency. Mention of company or product names does not constitute
endorsement by the Environmental Protection Agency.
IV
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TABLE OF CONTENTS
PAGE
1.0 INTRODUCTION 1
1.1 Background 1
1.1.1 Requirements of the Clean Air Act i
1.1.2 Cincinnati Experience 2
1.2 Purpose of this Report 3
1.2.1 System Guideline Document 3
1.2.2 Definition of Future Data
Acquisition Requirements 3
1.2.3 Personnel Requirements 3
2.0 SURVEY DATA HANDLING REQUIREMENTS 5
2.1 Existing Procedures 5
2.1.1 Manual Procedures 5
2.1i2 Automated Procedures 5
2.1.3 Data Handling - Cincinnati 5
2.2 Constraints Imposed by State and Federal
Data Systems 6
2.3 Interstate Agreements g
3.0 DESIGN INPUT DATA FORMATS 9
3.1 Coding 9
3.1.1 Station Identification 9
3.1.2 Parameter Identification 11
3.1.3 Monitoring Period 13
3.2 Data Recording Formats 13
3.2.1 Continuous Monitoring 16
3.2.2 Intermittent Data 19
3.3 Cincinnati's Data Input Formats 24
3.3.1 Continuous Monitors 24
3.3.2 Intermittent Data 31
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TABLE OF CONTENTS
(continued)
PAGE
4.0 OUTPUT DATA FORMATS 34
4.1 Survey Users Requirements 34
4.2 Clarity of Content 35
4.3 Cincinnati Formats 35
4.3.1 Data Listings 35
4.3.2 Monthly Report 37
4.3.3 Summary Report of Intermittent Data 44
4.3.4 Data Analysis 45
4.3.5 Submit Data to NADIS 45
5.0 DATA STORAGE 53
5.1 Storage Media 53
5.1.1 Data Record Forms 53
5.1.2 Punched Paper Tape 53
5.1.3 Punched Cards 53
5.1.4 Magnetic Tape 54
5.1.5 Direct Access Storage 55
5.1.6 Selection of a Storage Media 55
5.2 Information Management 56
5.2.1 Data Storage 57
5.2.2 Record Formats 58
5.3 Structure of the Cincinnati Files 59
5.3.1 Use of Secondary Storage Media 59
5.3.2 Record Format - Disk File 59
5.3.3 Record Format 68
VI
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1.0 INTRODUCTION
1.1 BACKGROUND
1.1.1 Requirements of the Clean Air Act
The Clean Air Act of 1970 has had a profound effect upon
all aspects of local, State, and Federal air pollution control
programs. Following the adoption of National Ambient Air
Quality Standards for selected air contaminants, each State has
submitted its plan for the implementation of these Standards.
The availability of aerometric data has been and will continue
ft
to be a very critical part of each implementation plan.
Information relative to existing air quality and meteoro-
logical conditions is of paramount importance in the determina-
tion of specific emission control regulations required to insure
the attainment of the air quality standards. Air quality data
are essential for the evaluation of the effectiveness of such
regulations. Once the air quality standards have been achieved,
air quality data will provide the information base needed for
maintenance of these standards.
Most State and local control agencies anticipate a sig-
nificant expansion in their air quality and meteorological
monitoring programs. Expansion of these programs will greatly
increase the quantity of data to be handled. As a result, most
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agencies will find it necessary to expand existing, and develop
new, data handling systems. All of the State agencies and many
local agencies will find it necessary to use computer oriented
data storage and retrieval systems.
1.1.2 Cincinnati Experience
The Ohio Air Pollution Control Board has delegated to the
City of Cincinnati, Division of Air Pollution Control (DAPC),
responsibility for providing most control agency functions to
the four-county Ohio portion of the Cincinnati Interstate Air
Quality Region. Included among these responsibilities is that
of air quality and meteorological monitoring. The DAPC is
responsible for the installation, operation, and maintenance of
all monitoring stations. By 1975 this network will be comprised
of 40 stations, of which as many as nine will be equipped with
one or more continuous pollutant and/or meteorological moni-
toring devices. The balance of the stations will be equipped
with one or more devices for collecting 24-hour pollutant
samples.
In line with this expansion of aerometric monitoring
activities, the DAPC has recently designed, and is now imple-
menting, a computer oriented data handling system. This auto-
mated system will provide the data summaries and statistical
analyses required by management to carry out an effective
control program.
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1.2 PURPOSE OF THIS REPORT
1.2.1 System Guideline Document
In the development of the Cincinnati Aerometric Data
Handling System, many problems had to be solved and decisions
had to be made by management, relative to the scope and com-
plexity of the system. This experience provides a body of
information which can be of significant value to other control
agencies. This document is intended to serve as a guideline
for the design of aerometric data storage and retrieval
systems.
1.2.2 Definition of Future Data Acquisition Requirements
At the present time, most control agencies are not com-
pletely aware of the importance of aerometric data in their
day-to-day activities. Because of this, many agencies have not
formulated a policy on the use of real-time data acquisition
systems. It is most important that a control agency avoid
"overkill" in its approach to data handling. To this extent,
the approach taken by Cincinnati is to develop a data handling
system which operates in a batch mode, that is to say data are
physically taken from the field monitoring station to the
laboratory and then to the computer. Once this system is
operational, it may be expedient to incorporate a real-time
link between the continuous monitoring device and the computer.
This additional level of complexity involving telemetry can
easily be incorporated into the data system.
1.2.3 Personnel Requirements
The design and implementation of an aerometric data han-
dling system requires specialized personnel resources. It is
3
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unlikely that most control agencies will have such individuals
on their staffs. On the other hand, most control agencies have
access to a computer facility operated by some other entity
within the government. The systems analysts and computer pro-
grammers available from a .central computer services group will
find it extremely difficult to design the data system without
the assistance of air pollution specialists. Thus, most
agencies will find it necessary to designate an air pollution
specialist to work with the computer systems analyst and pro-
grammer. Thus, in effect, a team approach is used in the
design and implementation of the system.
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2.0 SURVEY DATA HANDLING REQUIREMENTS
2.1 EXISTING PROCEDURES
The first step in the design of an aerometric data system
is to review the data handling procedures now in use by the
agency. This review should provide the details of data re-
cording formats, coding techniques, method of data storage, and
the types of reports which are prepared from the data. Addi-
tionally, this review should include an estimate of the volume
ft
of data being handled by the system.
2.1.1 Manual Procedures
Historically, many control agencies have been collecting
limited amounts of 24-hour pollutant concentration data. Some
agencies may also obtain 2-hour soiling index measurements from
one or two stations. For the most part, the control agencies
have tended toward manual procedures for this type of data.
Preparation of a data flow diagram, and documentation of input
and output formats used to handle such data, is generally quite
easy.
2.1.2 Automated Procedures
Tt is most important that existing automated procedures be
carefully reviewed. Where automated procedures are being used,
input data formats, coding techniques, record formats, file
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structures and data retrieval formats may already be well
established. These existing procedures should not necessarily
constrain the design of the total aerometric data system.
However, where practical, they should be incorporated into the
new system.
2.1.3 Data Handling - Cincinnati
Air quality data has been collected in Cincinnati for 25
years. This data has resulted from-programs supported entirely
by the resources of the local agency and from cooperative
studies with EPA (and its predecessors). The EPA studies in-
cluded such long term air monitoring activities as the National
Air Sampling Network, the National Gas Sampling Network, the
Continuous Air Monitoring Program, and related studies. For
the most part, the local agencies have not been required to de-
velop data handling procedures for the EPA cooperative studies.
The volume of data resulting from locally supported pro-
grams was of such quantity that manual data handling was ade-
quate. The local agency developed data recording forms for
measurements of monthly dust fall, weekly wind blown particu-
lates, 24-hour suspended particulates and gases, and 2-hour
soiling index. No special numerical coding was developed which
in any way imposed a constraint on the development of the auto-
mated data handling system.
2.2 CONSTRAINTS IMPOSED BY STATE AND FEDERAL DATA SYSTEMS
-Local control agencies are required to submit air quality
data to the State agency. Likewise, Federal regulations require
the State agency to submit such data to EPA. The requirements
for such data should be carefully considered in the design of a
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data handling .system. It is generally true , that the agency re-
sponsible for the operation of the air sampling network requires
the most detail, in so far as data is concerned. Thus, with a
local agency, if its own requirements are satisfied, there
should be no trouble in supplying the level of detail required
by the State and EPA.
The record format and coding used by EPA need not neces-
sarily be used in the design of a local or State data system.
The important thing is that the data input include all of the
data elements required by the higher echelon. Fundamentally,
the data should be identified as follows:
Agency Collecting the Data
Project Code, i.e., routine sampling or special sampling
Location of Sampling Station
Pollutant Name
Method of Sampling and Analysis
Units of Recording Measurements
Sample Averaging Time, (i.e. 1 hr, 2 hr, etc.)
Data and Time of Sample
Decimal Point Location
Actual Data Values
Included in the aerometric data system would be the neces-
sary information to transform data elements to the coding
specified by EPA (or the State).
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2.3 INTERSTATE AGREEMENTS
Within Interstate Air Quality Control Regions, it is neces-
sary to interchange data between control agencies in two or
more States. Representatives of all States involved in an
Interstate AQCR should meet and discuss their mutual require-
ments for data. If at all feasible, an attempt should be made
to standardize on station identification and coding techniques.
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3.0 DESIGN INPUT DATA FORMATS
3.1 CODING
As was previously noted, each data element entered in a
data storage and retrieval system must be uniquely identified.
With a manual system, all pertinent information can be entered
on a data form which is then placed in a filing cabinet. When
a computer oriented data system is used, it is impractical to
rğ
store all identifying information in its original form. In
order to maintain efficiency and minimize the cost of data input
and storage, the number of characters of identifying information
should be kept to a minimum. This can be accomplished with the
use of numerical codes for descriptive information such as
station identification, method of determination, units of measure-
ment, date of collection, etc.
It is worthy of note at this point, that while coding is
efficient in terms of the computer, coding is most inefficient
from the point of view of the user. Thus, it is always desir-
able to restore information to its original form when data is
retrieved from the computer file.
3.1.1 Station Identification
A numerical code is most often used for station identifi-
cation. The structure of this code is dependent upon the way
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in which data must be locateable for retrieval by the user.
In its most simple form the individual stations are numbered
from 1 to N, with the value of N sufficiently large to accommo-
date some reasonably expected increase in the air monitoring
activities. For most local agencies a two-digit code is suf-
ficient since up to 99 stations are possible. Station numbers
are assigned sequentially as new ones are added.
As the scope of an aerometric monitoring network expands,
it is usually desirable to retrieve data by various subsets of
stations. For example, a state agency may maintain a data bank
consisting of data from a large number of political jurisdic-
tions. In this situation, it may be necessary to use a hierar-
chial code in which Air Quality Control Region, City and/or
County, as well as sampling site, is identified, such as:
AQCR xx
City/County xx
Station No. xx
A hierarchial code is particularly useful in retrieving data
from the file. To retrieve data for a given sampling site, the
AQCR, City/County, and Station numbers are specified. To re-
trieve the data for all sampling sites in a city, specify the
AQCR and city numbers. To retrieve data for all cities/counties
in an AQCR, specify only the AQCR number. Finally, to retrieve
all data in the file, the AQCR, City/County, and station numbers
are all left blank (or insert zero's).
10
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A nine (9) digit is used by SAROAD for station identifica-
tion as follows:
State xx
Area (City or County) xxxx
Site xxx
The SAROAD station coding used by EPA is necessarily dif-
ferent from that which may be desirable for use by a State or
local air pollution control agency. Because State and local
agencies are required to submit air quality data to EPA, it is
desirable to include in the data retrieval programs, the ability
to convert station identification codes to the SAROAD code.
It is necessary to exercise judgement in the development
of the station I.D. code which is used with data being entered
into the system. As an example, it may appear to be desirable
to develop the station I.D. code on the basis of grid coordi-
nates. To do so with the Universal Transverse Mercator System
(UTM) may require as many as 17 digits for zone as well as
Easting and Northing coordinates. Since the station I.D. must
be included as part of the input with new data, the number of
characters used should be minimized.
3.1.2 Parameter Identification
The parameter identification must include; the parameter
name, method of determination, units of measurement, and
decimal point location.
3.1.2.1 Parameter Name - The code for parameter can be either
a sequential number or a hierarchial number code. Since most
control agencies routinely collect data on no more than 10-15
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parameters, a sequential two-digit code may be desirable. If
it becomes necessary to structure the computer files according
to either meteorological or air quality parameters, and the air
quality parameters are further classified in some manner, it
may be necessary to use a hierarchial number code. SAROAD
employs a five-digit code to provide maximum flexibility in the
assignment of parameter codes. This code provides the ability
to retrieve data for individual pollutants or selected cate-
gories of pollutants with a single request to the data base.
Again it is desirable to include in the computerized system
a procedure for converting the parameter code to the SAROAD code.
3.1.2.2 Method of Determination - For many air pollutants there
are several methods of sample collection and analysis currently
being used. In some instances, there is sufficient evidence to
indicate that the results from the several methods are not
directly comparable. Because of this, it is desirable to de-
velop a code for method of determination. For the most part,
a one-digit numerical code is sufficient to handle the number
of different methods being used by an agency for a given pol-
lutant. The SAROAD code is two digits to maintain adequate
flexibility. ^
3.1.2.3 Units of Measurement - When data is retrieved from a
computerized storage media, it is important that units of mea-
surement be included on the printed copy. The units of measure-
ment can be stored with the data element or be included as a
table of constants in each computer program which is written to
retrieve data. If the units of measurement are stored with the
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data, it is necessary that it be included with the input data.
Because of the extreme flexibility in data input desired for
SAROAD, a two-digit code is used by EPA (Table 1).
3.1.3 Monitoring Period
3.1.3.1 Date and Time - The monitoring period is identified by
date and time of day. It is recommended that the beginning of
the period be recorded by year, month, day, hour, and minute.
For monitoring periods of one hour or more, it is good to begin
on the hour, in which case it is not necessary to record minutes.
Since many agencies use the period midnight-to-midnight for
24-hour measurements, the beginning hour can also be deleted.
When a data acquisition system is used with continuous moni-
toring equipment, it is expedient to record year, Julian day,
hour and minutes at the beginning of the monitoring period.
With most computer installations, algorithms to convert from
Julian day to month and day are readily available.
3.1.3.2 Time Interval - The time interval over which a specific
parameter is measured must be associated with each data element.
This can be accomplished in two ways; (1) include a code for
time interval with the identification information for each data
element, and (2) structure the file by time interval so that all
24-hour data is maintained in one file, 2-hour data in another
file, etc. The time interval code used for the submission of
data in SAROAD format is shown in Table 2.
3.2 DATA RECORDING FORMATS
Aerometric data is generated in two basic ways; (1) with
continuous monitoring devices, and (2) with intermittent moni-
toring devices. The output from a continuous monitor is
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TABLE 1. UNITS
Code
number
01
02
03
04
05
06
07
08
09
10
11
12
13
14
20
30
31
32
33
34
35
50
70
80
81
90
91
92
98
99
Units
micrograms/cubic meter (25° C, 1013 millibars)
micrograms/cubic meter (0° C, 1013 millibars)
nanograms/cubic meter (25° C, 1013 millibars)
nanograms/cubic meter (0° C, 1013 millibars)
milligrams/cubic meter (25° C, 1013 millibars)
milligrams/cubic meter (0° C, 1013 millibars)
parts per million (volume/volume)
parts per billion (volume/volume)
COHS/1000 linear feet
RUDS/10,000 linear feet
meters/second
miles/hour
knots
degrees
microns
picocuries/cubic meter
microcuries/cubic meter
picocuries/square meter
microcuries/square meter
picocuries/cubic centime'ter
picocuries/gram
number of threshold levels
milligrams F/100 square centimeters-day
milligrams S03/100 square centimeters-day
micrograms S02/square meter-day
tons/square mile-month3
mi 11i grams/square centi meter-month3
micrograms/cubic meter-month3
milligrams SO^square centimeters-30 days
milligrams/square centimeters-30 days
On a calendar-month basis.
Source: SAROAD Users Manual
Office of Air Programs Publication
NO. APTD-0663
14
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TABLE 2. TIME INTERVAL
Code
1
2
3
4
5
6
7
8
9
A
B
C
D-Z
Data observed over a period of:
1 hour
2 hours
4 hours
6 hours
8 hours
12 hours
24 hours
1 month
3 months
1 week
3 hours
Composite data
For future expansion
Source: SAROAD Users Manual
Office of Air Programs
Publication No. APTD-0663
15
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recorded either in the field on a strip chart, paper tape, or
magnetic tape, or is telemetered to a central station for
immediate computer processing. With intermittent monitoring
devices, a sample is collected in the field and then sent to
a laboratory for analysis. Typically, results from the labora-
tory are recorded on an appropriate form -for subsequential
data handling.
3.2.1 Continuous Monitoring
3.2.1.1 Strip Chart Data Reduction - The reduction of data from
strip charts can be done entirely manually or semi-automatically
with the use of a chart reader. When charts are read manually,
hourly measurements are "eye-balled" and the results recorded
in engineering units on a data record form. A very convenient
form for recording hourly data is the one used by SAROAD
(Figure 1). This form provides for all the necessary identifica-
tion and permits recording up to 4 digits for each parameter.
The form is designed for direct keypunching and is sufficiently
flexible to handle a wide range of parameters from many differ-
ent monitoring stations.
A chart reader can be used to minimize the manual effort
involved in reading strip charts. Typically, hourly data values
are reduced from the charts and automatically printed by an
on-line typewriter; or preferably, entered through a keypunch
on to punched cards. In either case, the output from the chart
reader can be formatted similarly to that shown in Figure 1.
3.2.1.2 Data Acquisition Systems - The inclusion of a data
acquisition system in a continuous monitoring program can mini-
mize the manpower requirements for data handling. Output from
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LESS THAN 24-HOUR SAMPLING INTERVAL
1
Agency
City Name
Site Address
ENVIRONMENTAL PROTECTION AGENCY
National Aerometrlc Data Bank
P. 0. Box 12055
Research Triangle Park
North Carolina 27711
State
Area
Site
5 6 7 8 9 TIT
Parameter observed
Method
Agency | Project Time Year Month
TT 12 13 1U 15 16 17 18
Parameter code Method Units DP
Time interval of obs. Units of obs. I I I I 1 I I I I I I 1 f~)
23 21. 25 26 27 28 29 30 31 32
Day
19 20
St Hr]
21 22
Project
Rdg 1
33 31* 35 36
-
,
Rdg 2
37 3& 39 iğ0
-
Rdg 3
Ml 42 43 44
...
Rdg 4
4546 47 48
*
Rdg 5
49 50 51 52
Rdg 6
53 54 55 56
Rdg 7
57 58 59 60
Rdg 8
61 62 63 64
Z3 24 2b
Rdg 9
65 66 67 68
2b 27 2
Rdg 10
69 70 71 72
8 29 i
Rdg 11
73 7475 76
J 31 32
1 Rdg 12
77 78 79 60
-H
i i
i
r
, .
Figure 1ğ SAROAD Hourly Data Form.
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the data acquisition system may be recorded on an intermediate
storage media, or processed on-line by a computer.
A data acquisition system digitizes the analog signal from
the sensor, usually converts the data element to engineering
units and records the data pn tape, or transmits it to a com-
puter. When there are a number of sensors at a station, the
data from all sensors may be multiplexed and assembled into
single message units. Included in such a message unit is the
identification information for the station and the sensor, as
well as code indicating the status of each sensor.
There are two ways in which the data acquisition system
can handle the analog signal from a sensor; (1) record instan-
taneous pulses, and (2) through the use of an electronic inte-
grator, record time-averaged values. The frequency of recording
instantaneous values and the length of time for integration is
determined by the way in which the data are used in decision
making and planning. Most agencies find that data values
averaged over 30 to 60 minutes satisfy most of their requirements.
Current practice by most agencies is to record instantaneous
data values and use the computer to determine time-averaged
values. Basically, this makes the computer the integrator.
The frequency of recording instantaneous data values determines
the precision with which a time-averaged value can be computed.
Frequencies of recording now being used range from one per minute
to four per hour. A recording frequency of 12 per hour (every
5 minutes) is used for the Continuous Air Monitoring Program
(CAMP). When hourly averages are of primary concern, the
recording of instantaneous values at 5-minute intervals is a
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good compromise between maintaining reasonable precision of the
average value and the cost of data handling.
3.2.1.3 Station Activity Record - With continuous monitoring
devices, it is important that all pertinent information regarding
station operation be available to the individual responsible
for data validation. When data is reduced from strip charts,
it is convenient for the station operator to enter comments
directly onto the chart. With an automated data system, the
operator must have another mechanism for transmitting informa-
tion to the computer. A most convenient way to accomplish this
is through the use of an operator's log. An example of such a
log is the one used by CAMP (Figure 2). The log provides a
means to invalidate data for periods when it is known that a
sensor was malfunctioning. Also, the operator can record neces-
sary information concerning instrument zero and span checks, etc.
3.2.2 Intermittent Data
Intermittent data is primarily associated with air quality
parameters. Typically, a sampling media (filter paper or
reagent) is prepared by the laboratory and sent to the field
station where it is exposed for the appropriate time. After
the sampling period, the media is returned to the laboratory
for analysis. Finally, the pollutant concentration is deter-
mined and recorded for subsequent use.
A record must be maintained throughout the period from
media preparation to recording the pollutant concentration.
Initially, the laboratory determines and records the weight of
each filter for the hi-volume sampler. In the field, the
operator records the necessary station identification, start
19
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Figure.2
SEC 468
(REV 10-61)
STATION
MO.
8
9
RECORD OP OPERATOR'S LOG
DATE! to
r
12345
DA.
10
11
YR.
12
13
D*
14
ITEM
15
16
17
START
18
19
20
21
STOP
22
23
24
25
PURGE
27
28
29
30
OPERATOR
m
6 7
COMMENTS
* Day of WĞĞk.
20
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time, stop time, and air flow rate. A typical example of a
field sample form is shown in Figure 3. Finally, the labora-
tory performs the requisite analysis and computes the pollutant
concentration.
The output from the laboratory can be in one of two forms;
(1) pollutant concentration in engineering units, or (2) inter-
mediate results prepared for computer calculation of concen-
tration.
3.2.2.1 Pollution Concentration in Engineering Units - The
laboratory analyst performs all necessary calculations to deter-
mine the concentration of the parameter in micrograms per cubic
meter or other appropriate units. Results are verified to
insure their reliability, and the final data value is recorded
on an appropriate form.
If the data are to be entered into a computer storage and
retrieval system, the data record form should be designed for
computer input. An example of a form designed for direct key-
punching is the one used with SAROAD (Figure 4). If an agency
has the necessary hardware available at its computer center,
the need for keypunching can be eliminated through the use of
optical character recognition forms and readers. It is recom-
mended that the computer center be consulted prior to selecting
the method to be used for computer data input.
3.2.2.2 Laboratory Reports Intermediate Results - As in other
situations involving highly repetitive tasks, some functions of
the laboratory can be automated if the volume of work is suf-
ficiently large. For the purpose of this report, only automation
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SAMPLE NO.
STATION NO.
DATE
TIME
FLOW RATE
START OF SAMPLING
FINISH OF SAMPLING
DATE
FILTER WEIGHT
ROOM TEMPERATURE
RELATIVE HUMIDITY
TOTAL VOLUME SAMPLED_
TOTAL WEIGHT GAINED^
DUST LOADING
CUBIC METERS
_MILLIGRAMS
HGMS/M3
STATION OPERATOR__
WEIGHING OPERATOR
BAAPCD
WS:fm
10/8/70
Source: Bay Area Air Pollution Control District
Figure ;3. Particulate sampling record.
22
-------
Figure 4
ENVIRONMENTAL PROTECTION AGENCY
National Aerometric Data Bank
Research Triangle Park. N. C. 27711
SAROAD Daily Data Form
24-hour or greater sampling interval
m
OMB No. 158-R0012
Approval expires 6/30/76
1
Agency
City Name
Site Address
Project
Name
PARAMETER
Code
23 24 25 26 2
Method Units
Day
19 20
0
0
0
0
0
0
0
0
0
1
1
1
1
1
1
1
1
1
1
2
2
2
2
2
2
2
2
2
2
3
3
1
2
3
4
5
6
7
8
9
0
1
2
3
4
5
6
7
8
9
0
1
2
3
4
5
6
7
8
9
0
1
St Hr
21 22
DP-ğ
28
i
29 30 31
33 34 35 3
3
2
7
DP
D
32
6
1
0
Time Interval
Name
PARAMETER
Code
37 38
Method
42
t
43
47
39 40 41
Units DP
44 45 46
48 49 50
32 0-
23
State
2 3
Agency
,11
Area
1
Site
1
45678
Project Time
m n
12 13 14
Name
PARAMETER
Code
51
Met
D
56
i
52
hod
5
61 6
1
3 54 55
Units
58 59
2 63 64
3
DP
60
2 1 0
9 10
Year
Month
15 16 17 18
Name
PARAMETER
Code
65
Met
D
70
t
66 6
hod
D
71
75 7
7 68 6
Units
I
72 73
6 77 7
t 3
9
DP
n
74
8
2 1
0
-------
of the routine computations to determine pollutant concentra-
tions is treated.
When the laboratory analyst completes the analytical work,
it is necessary to perform some rather simple arithmetic to
determine pollutant concentration. These calculations can be
handled with extreme speed on a computer. With the appropri-
ately designed data form, the field operator initiates the
transaction by recording the necessary station identification,
date, sampling time, air flow rates, etc. In the laboratory,
the analyst records the proper weight, meter reading, etc.
Next, the form is keypunched, and finally the data is processed
by the computer. The computer enters data into a file and pre-
pares a listing of all transactions which can be used in data
validation. Finally, the laboratory validates the computed
data and prepares the necessary transaction to change or delete
invalid data which has already been stored in the computer file.
Before attempting to initiate this procedure, careful
thought should be given to the following:
1. Additional steps are being added which take time
to execute, introduce the need for additional
checking, and increase the elapsed time in
processing samples.
2. Special computer programs must be written and
maintained.
3. There is a continuing cost for the computer.
4. Relieving the analyst of the responsibility for
the final result may introduce a lack of concern
over the validity of results.
3.3 CINCINNATI'S DATA INPUT FORMATS
3.3.1 Continuous Monitors
Data acquisition hardware is included at each continuous
24
-------
monitoring station. The system is designed for a maximum of 16
air quality or meteorological sensors. Instantaneous values for
each parameter are recorded on magnetic tape at 5-minute inter-
vals. Data values plus pertinent identification information are
written in a 156 character record as shown in Figure 5.
The input format permits a maximum of 99 stations. Each
station may have from 1 to 16 parameter sensors. In the present
design, the system requires that the parameters be recorded in
the same order at each station. Because of the fixed record
length of 156 characters, the system automatically writes no
data codes for sensors which are not operative at a given station.
The Station Status Code (Ref. No. 4 - Figure 5) provides a
.means of checking the validity of the signal from each sensor.
Under normal operating conditions this status code = 0. Once
each day the system automatically checks the low calibration
(10% of scale), Code = 1, and the high calibration (70% of scale),
Code = 2, for each sensor. This information is used by the com-
puter as a validity check of the signal from each sensor. Should
either the low or high calibration differ by more than 5 percent
from its correct value, the computer is programmed to invalidate
the data for that parameter for the preceding 24 hours.
Under normal operation (Station Status Code = 0) a two-point
validity check is made on the electronics of the data acquisition
system each time a record is written on tape. The use of a two-
point check (i.e. ZERO and SPAN) provides reasonable assurance
that a drift in the electronics, which would otherwise result in
spurious data, will not go undetected. The DVM Zero Check (Ref.
No. 5) is set to emit a constant + 0000 and the DVM Span Check
25
-------
Figure 5. File Layout - Field Magnetic Tape
PAGE.
X 1
II
NPUT !
EFERENCE |
PROGRAM NUMBER(S)
SEQUENCE
DEVICE DESCRIPTION
Magnetic Tape
OUTPUT SYSTEM NAME
DATE
INTERMEDIATE Continuous Data
FILE NAME
Raw Data
FREQUENCY DISPOSITION
RECORD NAME
Five Minute Data
NO. OF RECORDS
PEAK: NORMAL:
PRINT/PUNCH DOCUMENT
SUE. WIDE X LONG NO. OF COPIES
REMARKS
REF.
NO.
1
2
3
4
5
6
7
8
9
10
11
DATA ELEMENT
Station No.
Date
Year
Day
Time
Hour
Minutes
Station Calibrate Status
DVM Zero Check
Channel Status
Channel (
101
Polarity
Value
DVM Span Check
Channel Status
Channel 01
Polarity
Value
Nitroqen Dioxide
Channel Status
Channel 02
Polarity
Value
Sulfur Dioxide
Channel Status
Channel 03
Polarity
Value
Methane
Channel Status
Channel 04
Polarity
Value
Total Hydrocarbon
Chennel Status
Channel 05
Polarity
Value
Total Oxidants
Channel Status
Channel 06
Polarity
Value
TOTAL NUMBER OF CHARACTERS
NUMBER OF
CHARS
2
5
2
3
4
2
2.
1
8
1
2
1
4
8
1
2
1
4
8
1
2
1
4
8
1
2
1
4
8
1
2
1
4
8
1
2
1
4
8
1
2
1
4
DEC
BYTES
A AN
P B
N
N
N
N
N
N
N
N
N
N
N
N
N
N
N
N
N
N
N
N
N
N
N
N
N
N
N
N
N
N
N
N~
N
N
N
N
N
N
N
N
N
N
N
SOURCE
01-0Q
>72
001-366
00-23
00-59
0.1.2
0.1,2.3
Always 00
+ or -
0,1,2,3
Always 01
+ or -
0,1,2,3
Always 02
+ or -
01,2,3
Always 03
+ or -
0,1,2,3
Always 04
+ or -
0,1,2,3
Always 05
+ or -
0,1.2,3
Always 06
+ or -
RELATIVE
LOCATION
1-2
3-7
3-4
5-7
8-11
8-9
10-11
12
13-20
13
14-15
16
17-20
21-28
21
22-23
24
25-28
29-36
29
30-31
32
33-36
37-44
37
38-39
40
41-44
45-52
45
46-47
48
49-52
53-60
53
54-55
56
57-60
61-68
61
62-63
64
65-68
26
-------
File Layout
PAGE.
X
1
NPUT
IEFERENCE
PROGRAM NUMBER(S)
OUTPUT
INTERMEDIATE
SEQUENCE
DEVICE DESCRIPTION
REMARKS
REF.
NO.
12
13
14
15
16
17
18
19
20
SYSTEM NAME
FILE NAME
FREQUENCY
DISPOSITION
DATE
RECORD NAME
NO. OF RECORDS
PEAK: NORMAL:
PRINT/PUNCH DOCUMENT
SIZE: WIDE X LONG NO. OF COPIES
DATA ELEMENT
Carbon Monoxide
Channel Status
Channel 07
Polarity
Value
Nitric Oxide
Channel Status
Channel 08
Polarity
Value
Soiling
Index
Channel Status
Channel 09
Polarity
Value
DEW Point
Channel Status
Channel 10
Polarity
Value
Temperature
Channel Status
Channel 11
Polarity
Value
V SIN 9
Channel Status
Channel 12
Polarity
Value
VCOS 6
Channel Status
Channel 13
Polarity
Value
Wind Speed
Channel Status
Channel 14
Polarity
Value
Wind Direction
Channel Status
Channel 15
Polarity
Value
TOTAL NUMBER OF CHARACTERS
NUMBER OF
CHARS
8
1
2
1
4
8
1
2
1
4
8
1
2
1
4
8
1
2
i
4
8
1
2
1
4
8
1
2
1
4
8
1
2
1
4
8
1
2
1
4
8
1
2
1
4
DEC
BYTES
A AN
P B
N
N
N
N
N
N
N
N
N
N
N
N
N
N
N
N
N
N
N
N
N
N
N
N
N
N
N
N
N
N
N
N
N
N
N
N
N
N
N
N
N
N
N
N
N
SOURCE
0,1,2,3
Always 07
+ or -
0,1,2,3
Always 08
+ or -
0,1,2,3
Always 09
+ or -
0,1,2,3
Always 10
+ or -
0,1,2,3
Always 11
+ or
0,1,2,3
Always 12
+ or -
0,1,27.3
Always 13
+ or -
0,1,2,3
Always 14
+ or -
0,1,2,3
Always 15
+ or -
RELATIVE
LOCATION
69-76
69
70-71
72
73-76
77-84
77
78-79
80
81-84
85-92
85
86-87
88
89-92
93-100
93
94-95
96
97-100
101-108
101
102-103
104
105-108
109-116
109
110-111
112
113-116
117-124
117
118-119
120
121-124
125-132
125
126-127
128
129-132
133-140
133
134-135
136
137-140
27
-------
File Layout
PAGE.
1
R
NPUT
EFERENCE
OUTPUT
INTERMEDIATE
PROGRAM NUMBER(S)
SEQUENCE
DEVICE DESCRIPTION
SYSTEM NAME
FILE NAME
FREQUENCY
DISPOSITION
RECORD NAME
DATE
NO. OF RECORDS
PEAK: NORMAL:
PRINT/PUNCH DOCUMENT
SIZE WIDE X LONG NO. OF COPIES
REMARKS
REF.
NO.
21
22
DATA ELEMENT
Additional
Parameter
No. 1
Channel Status
Channel 16
Polarity
Value
Additional
Parameters No. 2
Channel Status
Channel 17
Polarity
Value
Interrecord Gap
TOTAL
NUMBER OF CHARACTERS
NUMBER OF
CHARS
8
1
2
1
4
8
1
2
1
4
156
DEC
BVTES
f
A AN
P B
N
N
N
N
N
N
N
N
N
N
SOURCE
0,1,2,3
Always 16
+ or -
0,1,2,3
Always 17
+ or -
RELATIVE
LOCATION
141-148
141
142-143
144
145-148
149-156
149
150-151
152
153-156
28
-------
(Ref. No. 6) is set to emit a constant + 1600. When the com-
puter processes the data, if either check is outside of the
prescribed limits (DVM Zero -0005 to +0005, DVM Span + 1520 to
+ 1680) the data for all parameters for that particular 5 minutes
is declared invalid.
The system provides independent operation of each sensor.
The status of each sensor is included in the 8 characters of
information recorded for the 18 channels in the system. Under
normal operation, the channel status Code = 0. When a sensor
is undergoing calibration (either automatic or manual) the
status Code = 1. The computer is programmed to check the value
which is recorded for the zero calibration of each sensor.
When the zero calibration is outside of preset limits, an
error message is printed when the data is processed by the
computer. Since the various pollutant sensors are expected
to operate with essentially no drift in the zero position, the
computer is not programmed to adjust for a zero drift, as in
the CAMP system. Should experience with the instrument system
indicate that excessive drift is occurring, it will be necessary
to modify the computer program to make drift corrections.
The station operator is required to maintain a Station
Activity Record (SAR) Figure 6. All pertinent information
concerning station operation which is not recorded by the data
acquisition system must be entered on the SAR. To begin with,
the operator records the precise start and stop time of the
data contained on a magnetic tape (Action = 1). In addition,
the operator uses the SAR to signal the computer to invalidate
29
-------
Figure 6
CINCINNATI AIR MONITORING SYSTEM
STATION ACTIVITY RECORD
Station No.
T 2
Date
to
Operator
Sen
No
START
MO.
Day
Yr.
Time
Mo.
_STQP_
Dav
Yr.
Time
Remarks
3 4
6 7
1011
120:314
15161
18L920212223I2425
Sensor No. 00 = All
= Duration of Data
Action
1
2
3
4
Invalid Data
No Data
Calibration
30
-------
segments of data when it is apparent that some sensor (or the
entire station) is malfunctioning (Action = 2).
3.3.2 Intermittent Data
Measurements of the 24-hour ambient concentration of sus-
pended particulates, sulfur dioxide, and nitrogen dioxide,
are being made at nearly 40 stations throughout the Cincinnati
AQCR. Under normal circumstances, measurements are made on an
every six day basis. During periods of potentially high air
pollution and actual episodes, samples may be collected on a
daily basis.
Intermittent data is sent to the computer center for
processing on a monthly basis. New data is stored on a disk
file for rapid access, for a period of three months, after which
the data is transferred to the permanent data file which is
maintained on magnetic tape.
In developing the procedures for handling intermittent data,
two possibilities were considered; (1) recording laboratory
measurements which would be converted to concentration values by
a computer program, and (2) recording actual concentrations com-
puted manually by the laboratory analyst. The decision was made
to use the latter. It was agreed that spurious values are most
likely to be detected when the analyst records the actual con-
centrations for a sample.
Because of the decision to process the intermittent data
by the computer on a monthly basis, a monthly data record form
was developed (Figure 6-A). Data for the three pollutants pre-
viously mentioned from one station is recorded on a single page.
The form can easily be expanded to accommodate additional
31
-------
FIGURE 6-A CINCINNATI AIR MONITORING SYSTEM
24-HOUR SAMPLES
CONCENTRATION IN yg/m3
CAPO NO. _
1
STATION NO.
YEAR
4 5
2 T
MONTH
6 7
CO
to
n?
8
0
0
3
tf
9
1
2
1
:*
SUi
10
3P.
11
PA
12
RT
13
14
£
15
30 2
16
17
18
NO
19'
20
21
ACTION
80
ACTION: 1 = NEW DATA 2 = CORRECT DATA NOW ON FILE
-------
pollutants if necessary. At the end of the month, the data
forms for all stations are forwarded to the computer center for
keypunching.
As the intermittent data is read by the computer, the
position of the data on the punched card signifies the pollutant.
Pollutant codes are then attached to the data as they are stored
in the data file.
33
-------
4.0 OUTPUT DATA FORMATS
4.1 SURVEY USERS REQUIREMENTS
The only contact most users have with an air quality data
system are the various data listings, reports, statistical
summaries, etc., which the system is capable of providing. Thus,
users will tend to judge the value of the system on the basis of
its responsiveness to their needs. In order to satisfy the
requirements of the users, it is important that most of these
requirements be known at the time the system is being designed.
A necessary first step in determining user requirements is
to identify the potential users of the system. While the list
of users may vary somewhat from one agency to another, it will
generally include the following:
A. Individuals and groups within the Control Agency.
B. Other governmental agencies at the local level.
C. State and Federal Agencies such as Department of
Health and Environmental Protection Agency.
D. News media.
E. University and other researchers.
F. Trade associations.
G. Conservation groups.
H. Private citizens.
34
-------
Potential users of the system should be provided with
detailed information about the proposed data base, including
procedures for requesting the retrieval of data and samples of
output formats already developed. Users should be given suffi-
cient time to evaluate the completeness of the system in terms
of their own requirements. Finally, each user should be pro-
vided an opportunity to submit specifications for additional
outputs and schedules for preparation consistent with their own
needs and deadlines.
4.2 CLARITY OF CONTENT
In the design of retrieval formats for air quality data,
special attention should be given to keeping the information
easily understandable by the user. For example, each output
format should clearly identify the name of the agency, the
parameter(s) presented,,where and when the data was collected,
the method of determination, and the units of measurement. The
use of codes are to be avoided whenever possible since most
readers may find it necessary to refer to other sources of
information to de-code the information.
4.3 CINCINNATI FORMATS
4.3.1 Data Listings
4.3.1.1 Continuous Data - Each week, as new data is processed
and added to the disk file, a tabulation of the individual
5-minute values is prepared (Figure 7). The computer program
used to prepare this listing also performs a data validation
function. Each 5-minute value exceeding an estimated maximum
at that sampling station is flagged. Likewise, each time
35
-------
DIVISION
0 F
Figure
A I R
7
POLL
STATION STN01 CHESTERDALE AVE.
CINCINNATI
METHANE HYDROCARBONS
UTIQN CONTROL
OHIO
CONCENTRATION IN P.P.M.
FOOTNOTES -
* PERCENT CHANCE LARGE
48
** EXCEEDS EXPECTED MA
PACE
MINUTES
HOURS
0
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
0
I
2
3
$
>
6
7
$
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
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45
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50
xx.x
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SEPT
xx.x
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55
xx.x
xx.x
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XX, X
xx.x
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30 1971
xx.x
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XX, X
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xx.x
-------
successive values differ by a predetermined value, a flag is
pointed. Should these flagged values (and other values) be
determined invalid, an appropriate transaction to delete the
data from the file is initiated by the data validation clerk.
4.3.1.2 Intermittent Data - Measurements of 24-hour pollutant
concentration are added to the disk file on a monthly basis.
A tabulation of the data is prepared as a part of the file up-
dating (Figure 8). Again, the primary function of this tabula-
tion is for data validation purposes. A second computer program
is used to read user request cards calling for a listing of
24-hour data for bne or more pollutants at one or more stations
for a selected period of time.
4.3.2 Monthly Report
When the 5-minute pollutant concentration measurements for
an entire month have been processed and validated, a monthly
report is prepared (Figure 9). The basic entry in this report
is the hourly average of the 5-minute data. Daily averages and
the monthly average are computed from the hourly averages. Be-
cause there may be missing values in the 5-minute data, it is
necessary to establish a procedure for computing an average for
a time period based upon some minimum acceptable number of data
values. Without such a procedure, an hourly average might be
based upon one 5-minute value, or a daily average might be based
upon one hourly average. The purpose in computing an average is
to obtain a single value which is representative of a larger body
of data.
The procedure adopted for the Cincinnati aerometric data
/
system is to require that more than 75 percent of the possible
37
-------
PEDCo COMPUTER SERVICES, INC.
Cincinnati, Ohio
Figure 8 PREPARED: (MONTH) XX 197X
DIVISION OF AIR POLLUTION CONTROL
STATION ADDRESS 24-HOUR MEASUREMENTS
POLLUTANT NAME CONCENTRATION IN MICROGRAMS PER CUBIC METER
JAN FEB MAR APR MAY JUN JUL AUG SEP OCT NOV DEC N
DA -
01 XXXX XXXX XXXX XXXX XXXX XXXX XXXX XXXX XXXX XXXX XXXX XXXX XX
02 I
03
04
05
06
07
08
09
10
26
27
28
29
30
31
n
MIN
MAX
AVE
-------
PEDCo COMPUTER SERVICES, INC.
Cincinnati, Ohio FORMAT A
Figure 9 Format A
DIVISION OF AIR POLLUTION CONTROL
CINCINNATI, OHIO
STATION XXXX YYYYYYYYYYYYYYY PARAMETER NAME UNITS OF MEASURE MONTH 197X
A.M. P.M. MAX. DAY
HRO 1 2 3 4 5 67 8 9 10 11 12 1 2 3 4 5 6 7 8 9 10 11 5 AVE
DA MIN.
1 XXXX XXXX XXXX XXXX XXXX XXXX XXXX XXXX XXXX XXXX XXXX XXXX XXXX XXXX XXXX XXXX XXXX XXXX XXXX XXXX XXXX XXXX XXXX XXXX XXXX XX
2
3
4
5
6
7
8
9
10
26
27
28
29
30
31
N XX XX NN
AV XXXX XXXX XXXX
MONTHLY AVERAGE XXXX
NO OF
VALID DATA XXX
-------
PEDCO COMPUTER SERVICES, INC.
Cincinnati, Ohio FORMAT B
Figure 9 Format B
DIVISION OF AIR POLLUTION CONTROL
CINCINNATI, OHIO
STATION XXXX YYYYYYYYYYYYYYYY SOILING INDEX COHS PER 1000 ft MONTH 197X
A.M.
HR 0 2
DA
1 XX. X XX. X
2
3
4
5
6
7
8
9
10
P.M. MAX DAY
4 6 8 10 12 2 4 6 8 10 2HR. AVE
XX. X XX. X XX. X XX. X XX. X XX. X XX. X XX. X XX. X XX. X XX. X XX. X
26
27
28
29
30
31
N XX XX XX
AV XX.X XX.X XX.X
MONTHLY AVERAGE XX.X
NO. OF
VALID DATA XXX
-------
number of data values for an averaging time be valid. Thus an
hourly average is computed if there are more than 9 valid
5-minute values. Likewise a daily average is computed only
if more than 18 hourly averages are valid and the monthly
average (as well as the averages for individual hours for the
entire month) is computed only if there are more than 23 valid
daily averages.
As the hourly averages are computed, they.are tabulated in
the format of Figure 9 and also stored in a master file. When
a valid hourly average cannot be computed, a no data code (9999)
is written in the master file and the entry on the tabulation
is left blank.
* Note: A 5-minute value recorded as zero signifies
a concentration of less than a minimally
detectable amount, and is handled as a valid
value in computing averages (arithmetic only).
Monthly Report Formats
FORMAT A
OPTION 1: Monthly report of parameters in primary units of
measurement used for all parameters except:
a. Methane Hydrocarbons
b. Total Hydrocarbons
c. Non-Methane Hydrocarbons
d. V sin 9 - no report printed
e. V cos 6 - no report printed
41
-------
OPTION 2 : Monthly report of hydrocarbons in primary units
of measurement. Replace 5 min. with 6-9 A.M.
Ave. Use this format for:
a. Methane Hydrocarbons
b. Total Hydrocarbons
c. Non-Methane Hydrocarbons
OPTION 3 : Monthly report of gaseous pollutants with concen-
tration reported in micrograms per cubic meter
(except carbon monoxide in milligrams per cubic
meter) . Do not use for the three hydrocarbons.
OPTION 4 : Monthly report of hydrocarbons with concentration
in micrograms per cubic meter; otherwise the same
as OPTION 2.
OPTION 5: Monthly report of moving averages. Compute 3-hour
moving averages of S02 concentration in micrograms
per cubic meter. Compute 8-hour moving averages
of CO concentration in milligrams per cubic meter.
FORMAT B Monthly Report of Soiling Index
Finally, a monthly average is computed if valid daily
averages are available for more than 23 days during the month.
The monthly report program also computes hourly average
concentrations of non-methane hydrocarbons.
Hourly average non-methane: X.-. = XTHC - XCH
where XTH_, = hourly average Total Hydrocarbon
X_H = hourly average Methane
(a) Compute
only if X c and X are both valid.
4
42
-------
(b) If either XTHC or X are invalid, enter no
data codes.
(c) If Xmur, - XOTI negative, enter no data codes.
In the computation of the 6-9 A.M. average for Total Hydro-
carbons, methane and non-methane, it is necessary to consider
the fact that the sampling stations operate on Standard time
throughout the year. To compensate for the time change to
Daylight Savings Time, the 5-8 A.M. average is calculated for
the months May-October.
The monthly report program will print pollutant concentra-
tions in parts per million (ppm) or micrograms per cubic meter
* (ug/m ) . Also, the program computes three hour moving average
concentrations for sulfur dioxide and eight hour moving averages
for carbon monoxide. A minimum of two valid hours is required
for the three hour and 6 hours for the 8 hour moving averages .
This program also computes an hourly average wind direction
from the hourly average V sin 9 and V cos 9. The procedure for
determining wind direction on a 16-point compass is as follows:
Wind Direction:
a. If hourly average wind speed <0010 (1.0 mph) record
0017 (CALM)..
b. If hourly average wind speed >0010, determine
direction on 16 point compass as follows:
(1) Compute hourly average V sin 9
(ħ V sin 9 and V cos 9 (ħ V cos 9).
(2) Comp sin 9 and V cos 9
V
(3) Look up value of sin 9 in the following table,
then select proper direction depending upon
the algebraic sign of V cos 9.
43
-------
NOTE: Compute V sin 9 and V cos 9 for those 5 minutes
during the hour when V sin 9 and V cos 9 were
both valid. Hourly averages must be based upon
more than 8 valid 5-minute pairs of data.
DETERMINATION OF HOURLY WIND DIRECTION
ON 16 POINT COMPASS
sin 9
V cos 9
-0100
-0098
-0083
-0055
-0019
+0020
+0056
+0084
+0099
0099
0084
0056
0020
- +0019
- +0055
- +0083
- +0098
- +0100
13
14
15
16
1
2
3
4
5
13
12
11
10
9
8
7
6
5
CONVERSION TABLE FOR WIND DIRECTION
Code Direction
0001
0002
0003
0004
0005
0006
0001
0009
0010
0011
0012
0013
0014
0015
0016
0011
N
NNE
NE
ENE
E
ESE
SE
SSE
S
SSW
SW
WSW
W
WNW
NW
NNW
CALM
4.3.3 Summary Report of Intermittent Data
An annual summary of 24-hour concentration data is prepared
for each pollutant (Figure 8). In addition to tabulating indi-
vidual values, the program also computes monthly averages.
44
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4.3.4 Data Analysis
A statistical analysis of the hourly, two-hour, or 24-hour
data for any period of time (i.e. monthly, quarterly, annually,
etc.) can be requested (Figure 10). The user prepares a request
card which specifies the sampling station(s), parameter, and
begin and end dates (Figure 11). A single request card can be
used to retrieve data for one station or all stations in the
monitoring network.
Equations and methods used to generate the statistical
analysis are presented at the end of Section 4.0 (pp 52-55).
4.3.5 Submit Data to NADB
On a quarterly basis, air quality data is submitted through
*
the State Environmental Protection Agency to the U. S. EPA for
inclusion in the National Aerometric Data Bank (NADB). The
hourly averages, a 2-hour soiling index, and 24-hour pollutant
concentration data are written on a magnetic tape in punched card
images in SAROAD format (Figures 12 and 13).
Air Quality Data Analysis
Equations Used in Computations
No. of Samples = N, the number of measurements made during the
time period specified
MIN = Minimum concentration of N measurements
MAX = Maximum concentration of N measurements
Frequency Distribution-Percentile: 10, 30, 50, 70, 90, 99
There are two methods for determining the concentrations
associated with the above points on the percent cumulative
frequency distribution.
45
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ADDRESS
xxxxxxxxxxxxxxx
PEDCo COMPUTER SERVICES, INC.
Cincinnati, Ohio
Figure 10
DIVISION OF AIR POLLUTION CONTROL
PREPARED:(MONTH) XX 197X
POLLUTANT NAME
UNITS OK MEASURE
METHOD OF ANALYSIS SAMPLING INTERVAL XX-HR
FROM TO NO. FREQUENCY DISTRIBUTION-PERCENTILE ARITH STD GEO GEO
YR/MO/DA YR/MO/DA SAMPLES MIN 10 30 50 70 90 99 MAX MEAN DEV MEAN STDV
xx/xx/xx xx/xx/xx xxxx xxxx xxxx xxxx xxxx xxxx xxxx xxxx xxxx xxxx xxxx xxxx xxxx
-------
Figure 11.
DATA ANALYSIS PROGRAM
CONTROL CARD
No. Name Columns
1 Station 1-2
2 Parameter 3-4
3 Year (Begin) 5-6
4 Month (Begin) 7-8
5 Day (Begin) 9-10
6 Year (End) 11-12
7 Month (End) 13-14
8 Day (End) 15-16
Note: Station Number = 00 causes data for this
parameter to be analyzed individually for
all stations.
47
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Figure 12
PUNCHED CARD IMAGE
FOR
SUBMITTING DATA TO NADB
(TIME CODE 7)
DATA ELEMENT COLUMNS
NO .! NAME : FROM : THRU TOTAL REMARKS
1
2
3
4
5
6
7
8
9
10
11
12
14
15
16
17
18
19
20
21
22
23
24
25
Card No.
State Code (See SAROAD)
Area (Same as City No.)
Site Code
Zero
Site No.
Agency
F = State (1)
G = County (2)
H = City (3)
Project (See Code)
Time
Year
Month
Day
Start Hr.
PARTICULATES
Parameter Code
Method Code
Units
Decimal Point
1
2
1 i 1
3 2
I
4
8
8
7 4
10
3
Constant 2
Constant NN
Numeric
Numeric
8 1 Constant 0
9 10
11 11
12
14
2
1
i
'13 2
14
1
15
17 ;
19
21
23
28
30
32
Value 33
I
NITROGEN DIOXIDE
Parameter Code
Method Code
37
42
Units 44
i
Decimal Point 46
Value I 47
SULFUR DIOXIDE
Parameter 51
Method Code
Units
26 Decimal Point
27
Value
56
58
60
61
1
16 2
18 2
20
22
27
29
31
32
36
41
43
45
46
50
55
57
59
60
64
Numeric
Alpha
Numeric
Constant 7
Numeric
Numeric
2 i Numeric
2
5
2
2
2
4
(-
2
2
2
4
5
2
2
1
4
Constant 00
Constant 11101
Numeric
Numeric
Numeric
.Numeric
Constant 42602
Numeric
Numeric
Numeric
Numeric
Constant 42401
Numeric
Numeric
Numeric
Numeric
48
-------
Figure 13
PUNCHED CARD IMAGE
FOR
SUBMITTING DATA TO NADB
(TIME CODES 1 and 2)
DATA ELEMENT COLUMNS
NO, NAME ! FROM THRU TOTAL REMARKS
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
' Card No. -1
State Code (See SAROAD) 2
Area (Same as City No.) ' 4
Site Code 8
Zero
Site No.
Agency
F = State (1)
G = County (2)
H = City (3)
Project (See Code)
1 i 1 , Constant 1
3 2 Numeric (Constant NN)
7 4 Numeric
10 3 i Numeric
8 8 1
9 ' 10 2
Constant 0
Numeric
11 i 11 1 Alpha
12
i
13
Time . 14 i 14
1 I
Year
Month
Day
Start Hour 00 = AM
12 = PM
Parameter Code (See Code)
Method Code
UNITS Code
Decimal Point
Reading 1
Reading 2
15
17
2
1
16 2
.18
19 20
2
2
: 1
21
22
23 27
28
30
32
33
37
Reading 3 41
Reading 4 45
Reading 5 1 49
Reading 6 ; 53
Reading 7 57
Reading 8 61
Reading 9
Reading 10
26 j Reading 11
1
27 : Reading 12
65
69
73
77
29
31
32
36
40
44
48
52
56
60
64
68
72
76
80
5
2
2
1
4
4
4
4
4
4
4
4
4
4
4
4
Numeric
Numeric 1 or 2
Numeric
Numeric
Numeric
Numeric
Numeric
Numeric
01, 09
Numeric
Numeric
Numeric
Numeric
Numeric
Numeric
Numeric
Numeric
Numeric
Numeric
Numeric
Numeric
Numeric
49
-------
(1) Sort the N individual values (X.)
such that X,
-------
concentration. As each concentration is read from
the air quality data file, a count of 1 is added
into the appropriate counter.
NOTE: The maximum concentrations of the pollutants
now being considered should not exceed a value of
0700. In the event that any value does exceed 0700,
a final counter for greater than 700 should be pro-
vided. If this counter should exceed 1, the program
should indicate with an error message that it is not
possible to compute a cumulative frequency distribu-
tion.
After all values have been read and the frequency
distribution is completed, compute the cumulative
frequency distribution. This is done by replacing
each count (f.) with the value F. where
fħ
thus
F = F + f
2 1 2
For each percentile (p = 10, .30, 50, 70, 90, 99)
compute: F-
Now do a table look up and find F. >_ F . T^igg; concen-
tration of the pth percentile is the concentration
associated with the ith interval.
51
-------
let p = 30th percentile
F =
p
100
F - 30(34) =
ju 100 j.u
13 >. 10
concentration of 30th percentile = 0003
Arith Mean = arithmetic mean
Ni=l
Std. Dev. = standard deviation
N
N
,N
1/2
Geo. Mean =
L N (N-l)
Geometric Mean
1 ' N
ant i log = ( Z log, X.)
" j n i
Geo. Std. Dev. = Geometric Standard Deviation
2
= antilog
N
log
log Xħ)
1/2
N(N-l)
NOTE: In the computation of the geometric mean and
geometric standard deviation, a data value of
zero cannot be used. Substitute for the zero
value a constant equal to one-half the minimum
detectable limit for the method (e.g. if the
minimum detectable value is 0.01 ppm, substitute
0.005 ppm.
52
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5.0 DATA STORAGE
5.1 STORAGE MEDIA
5.1.1 Data Record Forms
The basic storage media is the record form on which the
data was initially recorded. It is generally advisable to
maintain all data record forms in an easily accessible file
for a period of time. Record forms for data which are main-
tained in a computer oriented data base can be removed to a
dead storage area relatively quickly. Data for a special
short term, and special studies, as well as calibration data,
may be best maintained on record form in a filing cabinet.
To retain confidentiality, proprietary information may be
ğ
required to be held in a filing cabinet. Retrieval of large
quantities of data from data record forms is inefficient.
5.1.2 Punched Paper Tape
Punched paper tape is often used as an intermediate
storage media with continuous monitoring systems equipped
with data logging devices. Typically the punched paper
tapes are processed by a computer and transferred to some
other storage media. Problems associated with tearing and
aging make paper tape undesirable for permanent storage.
5.1.3 Punched Cards
Most computer systems utilize punched cards as a primary
media for data input. Punched cards are not well suited for
permanent storage with large data bases. First, as card
volume increases, the storage space allocation for them must
53
-------
also increase. Secondly, as the cards are handled repeatedly
for data retrieval, some damage is inevitable which may result
in card jams in the card reader. Finally, because card read-
ing is a slow process with most computers, continual re-
reading of punched cards is both inefficient and expensive.
5.1.4 Magnetic Tape
Magnetic tape is widely used as a media for the perma-
nent storage of data. The physical space requirements for
maintaining a data base on magnetic tape is less than that
of most other storage media. Data that would require several
hundred thousand punched cards for storage can be written on
one 2,400 foot reel of 1,600 bits per inch (BPI) magnetic
tape. Next, because of the high speed tape drivers now
available, data can be read into the computer very rapidly.
Likewise, magnetic tapes can be read repeatedly with a very
low probability of damage. The sequential nature of air
quality data is ideally suited to storage on magnetic tape.
Some care in the storage and handling of magnetic tape
is necessary. Ideally magnetic tapes should be stored in a
fireproof vault. Lacking a suitable vault, a room with
controlled temperature and humidity can be used. In this
situation it is advisable to maintain a second copy of each
..'* "
tape in a separate room, so that a. fire or other calamity
will not destroy the data base. Another reason for maintain-
ing two copies of each tape is the ever present problem of
human error. Even though there are means of protecting a
54
-------
tape once information has been written on it, all computer
centers have experienced mistakes in tape handling. The
use of more than one tape is especially important with file
updating, in which data must be transferred from one tape
to another as new data becomes available.
5.1.5 Direct Access Storage
The ultimate in storage media are the direct access
devices such as magnetic-disk, magnetic drums, and data
cells. Devices such as this are ideally suited for use with
a data base which is constantly being accessed. The speeds
at which data are transferred into and out of direct access
storage devices provide for more efficient operation from
the standpoint of the use of the Central processor of the
computer system. The cost of a direct access storage device
is much greater than that of a magnetic tape device.
Because of the differential cost, direct access storage
must be justified on the basis of savings in computer
processing costs.
5.1.6 Selection of a Storage Media
The use of data record forms, paper tape, and punched
cards as permanent storage media for air quality data is to
be avoided in all but very specialized situations. Deter-
mining whether to use magnetic tape or direct access storage
requires some additional considerations.
A magnetic tape can be purchased for about $20.00. A
disk, capable of storing about twice the quantity of data
that can be written on a magnetic taps costs about $500.
55
-------
The differential cost can be very quickly offset through
the savings in computer processing cost if the data is
being frequently accessed. Since air quality data are
being added continually, the data base may be accessed in
a daily or weekly basis for file updating. Additionally,
as the new data are validated, the file must be accessed
to make changes in data already on the file. After data
have been on the file for a period of time, the frequency
of access very quickly decreases.
The selection of the storage media is of course depen-
dent upon the hardward configuration of the computer system.
If the system has both tape and disk drives, some combi-
nation of the two should probably be considered. The system
adopted by Cincinnati utilizes both magnetic disk and
magnetic tape. New data are stored on a disk file for a
period of 3-months, and afterwards are transferred to
magnetic tape for permanent storage. This procedure takes
advantage of the high speed associated with direct access
storage and the lower cost of sequential storage for histor-
ical files.
5.2 INFORMATION MANAGEMENT
The term "information management," refers to the over-
all process of datahandling, both into and out of a computer
system. To aid in the understanding of the"data management
processes, a discussion of some of the pertinent terminology
is presented below.
56
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5.2.1 Data Storage
In discussing data storage a differentiation is made
between units of storage and units of data. Basically,
units of storage relate to the computer hardware, whereas
units of data are dependent upon the software programs and
the user's requirements for accessing data in storage. The
basic unit of addressable storage in the main storage (i.e.
core) of the computer is the 8-bit byte. A byte can hold
one character of information or two decimal digits. The
basic unit of secondary storage is a sector on a disk, or
the portion of a magnetic tape between gaps.
In main storage, a unit of data is termed a field,
which consists of a fixed or floating point number, a packed
decimal number, or a series of one or more bytes. Related
fields, when grouped together, form a logical record (e.g.
a logical record might be the necessary identification
information and the 5-minute data values for one hour, for
a specific pollutant). The interchange of information
between main storage and secondary storage is by blocks
composed of one or more logical records. A block is
referred to as a physical record in secondary storage.
The effectiveness of a data management system is
determined by the way in which data storage facilities are
used. For example, on a magnetic tape there is a fixed
length gap of 3/4" between each logical record. The use of
57
-------
long physical records minimizes the portion of the total
tape which is taken up by record gaps.
5.2.2 Record Formats
Logical records are grouped to form a file. The
individual records can be constructed according to one of
four formats; fixed length records, variable length records,
undefined length records, and spanned records. The first
two are most commonly used and are discussed below.
The size (i.e. number of characters or bytes) of a
fixed length record is constant for all records in a file.
They may be stored blocked or unblocked. Blocking of logical
records is often used to create large physical records to
minimize number of record gaps in the file. Computer
programmers tend toward the use of fixed length records
because they are more easily handled in sorting and
computation.
Variable length records provide for more flexible
storage of data in secondary storage. It is necessary to
include the record length (1) as part of the logical record,
preceding the data. Variable length records tend to maximize
the efficiency of secondary storage.
In a situation where missing data may occur, space
must be provided for the missing data in a fixed length
record. The use of variable length records permits the use
of a smaller record size and usually results in a more efficient
use of secondary storage.
58
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5.3 STRUCTURE OF THE CINCINNATI FILES
5.3.1 Use of Secondary Storage Media
The system being implemented by the City of Cincinnati
makes use of both disk and magnetic tape as secondary storage
media. Data from the continuous air monitors are added to the
data base on a weekly basis, whereas intermittent data are
entered on a monthly basis. As the new data are entered, they are
processed and stored on disk for up to 100 days. During
the initial storage period, the data are readily accessible
for corrections and immediate reporting purposes. At monthly
intervals the older data on the disk file are transferred to
magnetic tape for permanent storage.
The method of utilizing both disk and tape storage
provides both the efficiency of immediate access by the computer
and the less expensive cost per unit of long term storage
associated with magnetic tape.
5.3.2 Record Format - Disk File
The records in the disk file are all fixed length. The
decision to use fixed length records was based upon software
associated with the computer and the ways in which the data
were to be accessed. There are three types of records used
with the disk files (i.e. a file information record, data
pointer records, and data records).
5.3.2.1 File Information Record - The 7200 byte file
information record contains the identification of all
sampling stations and parameters are being measured. Elements
included in this record are as follows:
59
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NO. OF BYTES
smax
pmax
emax
dmax
cr.date
update
nsta
npar
last data
hrly addr
smax
pmax
update
nsta
npar
int. data
STATE
Area
site
agey
DESCRIPTION
Title of File 10
CONTINUOUS DATA
Maximum number of continuous 2
stations = 4
Maximum number of continuous 2
parameters =18
Maximum number of pointer records 2
per pollutant per station = 23
Maximum number of days in 2
disk = 100
Creation data ^ beginning of 4
100 day period
Date of last update 4
Number of continuous stations 2
in use
Number of parameters in use 2
Disk address of last piece of data 4
Disk address where hourly 4
averages start
INTERMITTENT DATA ;
Maximum number of intermittent 2
stations = 40
Maximum number of intermittent 2
parameters =11
Date of last update 4
Number of intermittent stations 2
in use
Number of intermittent parameters 2
in use
Disk address where the inter- 4
mittent data starts
SAROAD
SAROAD code for Ohio 2
SAROAD code for Cincinnati 4
LOCATION OF CONTINUOUS STATIONS
Sampling station number 3
Agency code number = H 1
60
60
-------
NAME
proj
list
station
address
DESCRIPTION NO .
SAROAD Project Classification,
01, $1, 03
16 Switches-Parameters Measured
Address of first sampling
station
Repeat above for second station
Repeat -above for third station
Repeat above for fourth station
OF BYTES
2
2
24
32
32
32
128
IDENTIFICATION OF CONTINUOUS PARAMETERS
par am id
sti
meth
unit
dec 1.
st. hr.
p.c.
par am name
site
agcy
proj
list
station
address
SAROAD Code for first parameter
SAROAD Code for time interval = 0
SAROAD Code of method
SAROAD Code for units
Code for decimal point location
Start Hour
Parameter Control (see note)
First parameter name
Repeat previous 40 bytes for 2nd
through 18th parameters
LOCATION OF INTERMITTENT STATIONS
Sampling station number
Agency code number = 4
SAROAD project classification,
01, 02, 03
11 Switches-Parameters Measured
Address of Sampling Station
Repeat previous 32 bytes for 2nd
through 40th station
5
1
2
2
2
2
2
24
680
3
1
2
2
24
1248
720
param id
st i
meth
unit
IDENTIFICATION OF INTERMITTENT
PARAMETERS
SAROAD Code for first parameter 5
SAROAD Code for time interval =7 1
SAROAD Code for method 2
SAROAD Code for unit 2
1280
61
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NAME DESCRIPTION NO. OF BYTES
dec 1 Code for decimal point 2
location
st. hr Start hour 2
parameter First parameter name 24
name
Repeat previous 38 bytes for
2nd through llth parameter 380
418
Format code arrays 4594
7200
Note: The two byte parameter control is used to identify
changes in the parameter list between the 5-minute and
hourly average data as follows:
a. Enter the parameter two digit parameter code
(Table 3 Process Continuous Data Program) if 5-
minute and hourly averages are stored for the
parameter.
b. Enter 00 for parameter (Sensor) number 11 = Vsin
6 and 12 = VCos 9 since no hourly averages are
stored.
c. Enter 11 for 17th parameter. This will cause
hourly wind direction to be stored as the llth
parameter in the hourly average file.
d. Enter 12 for the 18th parameter. This will
cause hourly non-methane hydrocarbons to be
stored as the 12th parameter in the hourly
average file.
62
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5.3.2.2 Data Pointer Record - Two types of data pointer
records are used to maintain an inventory of the Aerometric
Data Disk File. Separate data pointer records are maintained
for the continuous and intermittent data files. A pointer
record is written each time new data is added to the file.
It is assumed that updates will be on a weekly basis. On
this basis 14 updates would occur in 100 days. The file
structure allows a maximum of 23 updates during a 100 day
period. A 240 byte pointer record is used for each continuous
parameter at each station. One 7200 character pointer record
is used for all of the stations with intermittent data.
NAME DESCRIPTION NO. OF BYTES
CONTINUOUS DATA
num Number of pointer fields in 2
record
1st Pointer Field-Station 1
Parameter 1
trk Track number 2
rec Record number 2
yr Year 1
day Day 2
hr Hour 1
Igth Length of data record pointed 2
Repeat previous 10 bytes for 2nd
through 23rd pointer fields for
Station 1 - Parameter 1
Blank 8
~240~
Note: Hourly average data is accessed directly by
calculating a displacement from the disk file
starting address which is maintained in the
file information record.
63
-------
NAME DESCRIPTION NO. OF BYTES
INTERMITTENT DATA
Station 1 Parameter 1
trk Track number 2
byte Number of Bytes 2
yr Year 1
day Day of Year 2
hr Hour 1
Igth Length of Data Record Pointed 2
Repeat above 10 bytes for Station 1
Parameter 2 through Station 40
parameter 11 4390
4400
Blank 3800
7200
64
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5.3.2.3 Data Records - Three different types of data
records are used; (1) continuous data - 7200 bytes per
record, (2) hourly data - 5400 bytes per record and (3) inter-
mittent data - 204 bytes per record. A description of each
record format is presented below.
Continuous Data
The 5-minute parameter values are written in 7200 byte
records each containing the data for 257 hours plus 4 unused
bytes at the end of the record. The data for a single hour
requires 28 bytes used as follows:
No. of Bytes
Year 1
Day . 2
Hour 1
Value Minute 00 2
Value Minute 05 2
Value Minute 55 2
Hourly Data
The hourly averages compute' for each parameter are
written in 5400 byte records. The record contains the
hourly data for 100 days. Each day requires 54 bytes used
as follows:
65
-------
No. of Bytes
Constant 0 . 1
Year 1
Day 2
Value Hour 00 2
Value Hour 01 2
Value Hour 23 2
Max 5 Min Value 2
Since soiling index is retained on the hourly average
file as 2-hour values, these values are recorded in the
positions for Hour 00, 02, 04, etc. Enter no data codes for
hours 01, 03, 05, etc.
Intermittent Data
The 24-hour pollutant concentration data is written in
204 byte records. The record contains up to 100 data values.
The 204 bytes are used as follows:
No. of Bytes
Constant 0 1
Year , 1
Day (Begin) 2
Value Day 1 2
Value Day 2 2
Value Day 100 2
66
-------
ANNUAL AEROMETRIC DATA FILE
Field
No.
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
46
47
RECORD
Data
Element
Blank
Agency Code
Project Code
State Code
Area Code
Site Code
Parameter Code
Method Code
Unit Code
Time Code
Start Hour
Year
Month
Day
Decimal Point Code
Data Field 1
Data Field 2
Data Field 3
Data Field 31
Blank
FORMAT
No. of
Characters
2
1
2
2
'4
3
5
2
2
1
2
2
2
2
1
4
4
4
4
3
Position
In Output
Record
1 :
3
4 1
6 1
8 1
12 1
15 1
20 1
22 1
24
25 1
27 :
29 ]
31 1
33 1
34 !
38 :
42 :
154 i
158
PROJECT CODE
Long-term surveillance codes
01 Population-oriented surveillance
02 Source-oriented ambient surveillance
03 Background surveillance
Type of
Data
Blank
Alpha,Always 4
Num, 01, 02, 03
Num, Saroad Code
Num, Saroad Code
Num
Num, Saroad Code
Num, Saroad Code
Num, Saroad Code
Num, Saroad Code
Num
Num
Num
Num
Num
Num
Num
Num
Num
Blank
Figure 14.
67
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5.3.3 Record Format
At monthly intervals, the hourly, 2-hour, and 24-hour
data are removed from the disk and transferred to a magnetic
tape -file for permanent storage. Data for the most current
two months is retained on the disk. The 5-minute data is
deleted from the disk file and is not retained on the
permanent magnetic tape file.
Data is written on tape as 160 character, fixed-length,
logical records. The logical records are written on tape with
20 records per block. The logical record format is identical
to that .used by EPA (Figure 14). The decision to use the
EPA format for the historical file was influenced in part by
the fact that it would simplify the submittal of data to the
National Aerometric Data Bank.
For hourly data, the start hour is normally 00 and the
24 values for a day are stored in data fields 1 through 24.
Data fields 25 through 31 .are blank.
For 2-hour soiling index data, the start hour is
normally 00 and the 12 values for a day are stored in data
fields 1 through 12. Data fields 13 through 31 are blank".
For 24-hour data, the start hour is normally 00 and
the values for each day are stored on the day of the month
on which the sample was collected. Since 24-hour samples
are normally collected on an every sixth day basis, most
of the data fields in the record will be blank.
The 160 character records are written on the tape as
shown in the attached Magnetic Tape Format (Figure 15).
68
-------
Figure 15
Aerometric Data File
Magnetic Tape Format
Station
Parameter No.
January
Ğ o e
December
Parameter No. 02
January
December
Parameter No. 01
January
December
Parameter No. 02
January
00*
December
Parameter No. 01
January
December
Parameter NO. 02
January
December
1 Hour Data
2 Hour Data
A basic record in this
file contains the data for
one month for a parameter
measured over a given
sample averaging time at
a given sampling station.
The sort key for the file
is:
Major: County
City
Site
Sample averaging time
Parameter
Minor: Month
A reel of magnetic tape
will contain data from
only 1 year.
24 Hour Data
69
-------
BIBLIOGRAPHIC DATA '" R">°£$-450/3-73-008 [*
4. Title and Subtitle
"Guidelines for the Development of An Air Quality Data System'
7. Author(s)
Pedco Environmental
9. Performing Organization Name and Address
Pedco-Envi ronmental Specialists
Suite 8 Atkinson Square
Cincinnati, Ohio 45246
12. Sponsoring Organization Name and Address
EPA.OAQPS.MDAD.NADB
Research Triangle Park, N. C. 27711
15. Supplementary Notes
3. Recipient's Accession No.
5> Report Date
September 1973
6.
8- Performing Organization Rept.
No.
10. Project/Task/Work Unit No.
11. Contract/Grant No.
Contract No. 68-02-004'
13. Type of Report It Period
Covered
Final 1/11/72-Present
14.
16. Abstracts
This report defines the steps to take in analyzing aerometric data requirement!
and defining a data handling system. It illustrates various decisions which
were made and the reasons for them in the data handling system of the city of
Cincinnati. It includes the steps which are necessary to computerize the
system and designing input and output formats. Files are addressed briefly
with a general description of file types and media.
17. Key Words and Document Analysis. 17o. Descriptors
Management Information System
Computers
ADP (Automatic Data Processing)
Air Quality Data System
Air Pollution
Ambient Air Data
Aerometric Data
Sysyem
Guideline
17b, Identifiers/Open-Ended Terms
17e- COSATI Field/Group 135
18. Availability Statement 19. Security
Report)
Release Unlimited UNCL
20* Security
Page
WCl
Class (This 21. No. of Pages
-ASSIFIgp 7fi
Class (This 22. Price
-ASSIFIED
FORM NTII-SB (REV. 3-721
71
USCOMM-DC I4M2-P72
-------
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Guidelines to Format Standards for Scientific and Technical Reports Prepared by or for the Federal Government,
PB-180 600).
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organization or provided by the sponsoring organization. Use uppercase letters and Arabic numerals only. Examples
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2. Leave blank.
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6- Performing Organization Code. Leave blank.
7. Author(ğ). Give name(s) in conventional order (e.g., John R. Doe, or J.Robert Doe). List author's affiliation if it differs
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an organizational hierarchy. Display the name of the organization exactly as it should appear in Government indexes such
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11. Contract/Grant Number. Insert contract or grant number under which report was prepared.
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If the report contains a significant bibliography or literature survey, mention it here.
17. Key Words and Document Analysis, (a). Descriptors. Select from the Thesaurus of Engineering and Scientific Terms the
proper authorized terms that identify the major concept of the research and are sufficiently specific and precise to be used
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(b). Identifiers and Open-Ended Terms. Use identifiers for project names, code names, equipment designators, etc. Use
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FORM NTIS-3S (REV. 3-72) _ USCOMM-DC
72 * X> ^
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