NSW Air Quality Monitoring Network: Quality Assurance Procedures

Transcription

1 NSW Air Quality Monitoring Network: Quality Assurance Procedures

2 Copyright State of NSW and Office of Environment and Heritage With the exception of photographs, the State of NSW and Office of Environment and Heritage are pleased to allow this material to be reproduced in whole or in part for educational and non-commercial use, provided the meaning is unchanged and its source, publisher and authorship are acknowledged. Specific permission is required for the reproduction of photographs. The Office of Environment and Heritage (OEH) has compiled this guideline in good faith, exercising all due care and attention. No representation is made about the accuracy, completeness or suitability of the information in this publication for any particular purpose. OEH shall not be liable for any damage which may occur to any person or organisation taking action or not on the basis of this publication. Readers should seek appropriate advice when applying the information to their specific needs. Every effort has been made to ensure that the information in this document is accurate at the time of publication. However, as appropriate, readers should obtain independent advice before making any decision based on this information. Published by: Office of Environment and Heritage NSW 59 Goulburn Street, Sydney NSW 2000 PO Box A290, Sydney South NSW 1232 Phone: (02) (switchboard) Phone: (environment information and publications requests) Phone: (national parks, climate change and energy efficiency information, and publications requests) Fax: (02) TTY: (02) Website: Report pollution and environmental incidents Environment Line: (NSW only) or See also ISBN OEH 2014/0754 October 2014

3 Contents Introduction 1 What is being measured in the NSW Air Quality Monitoring Network? 1 How can we be sure the data posted by OEH are reliable? 1 Why are there sometimes gaps in the data or no results on the website? 2 How is the quality of air quality monitoring data provided by the network assured? 3 How are air quality monitoring data validated? 3 Automated validation 3 Manual validation 5

4

5 Introduction The purpose of this guideline is to outline the quality assurance procedures used by the Climate and Atmospheric Science branch within the Office of Environment and Heritage (OEH) to ensure the validity and integrity of air quality data measured in the Air Quality Monitoring Network (AQMN). What is being measured in the NSW Air Quality Monitoring Network? Monitoring stations in the AQMN report on gaseous parameters (ozone, sulfur dioxide, carbon monoxide, oxides of nitrogen), fine particles (as PM 10 and PM 2.5 ), visibility, wind speed, wind direction, temperature and relative humidity. Figure 1 outlines the basic design of this system for collecting and reporting on NSW air quality monitoring data. Figure 1. NSW OEH air Quality Monitoring network and database system How can we be sure the data posted by OEH are reliable? It is important that the monitoring equipment used is appropriately accredited (e.g. compliance with local or international standards), properly installed and regularly calibrated and serviced to make sure it provides accurate and reliable data. NSW Air Quality Monitoring Network: Quality Assurance Procedures 1

6 The instruments used by OEH meet the relevant Australian Standards and international guidelines (e.g. United States Environmental Protection Agency Federal Equivalent Methods). OEH is accredited by NATA (the National Association of Testing Authorities) for the operation and maintenance of its air quality monitoring network and associated equipment. In accordance with the accreditation process, the monitoring network is periodically subjected to an independent review of operating, calibration and quality assurance and data validation procedures. Why are there sometimes gaps in the data or no results on the website? Because of the need for regular maintenance and calibration the AQMN is not online 100% of the time, although the network is operated to maximize online time. For gaseous instruments the target online time is 95%: about 5% of time is lost through routine maintenance and calibration. For instruments other than gaseous ones the online target is above 95%. Maintenance and calibration schedules comply with the requirements of the relevant Standards and operating procedures for servicing the equipment. Gaps in data can occur because of: 1. Scheduled maintenance and calibration in cases where the following are done on a regular basis: Gaseous instruments o Overnight: zero and span checks (1 hour) o Monthly: sample inlet cleaning; filter replacement; leak check (1 to 2 hours) o Quarterly: multi-point audit calibration to check linearity (1 to 2 hours) Particulate instruments o Quarterly: cleaning of sample head and inlet and replacement of filters; leak check (1 to 2 hours) o 6-monthly: flow audit (1 to 2 hours) o Annually: software (1 to 2 hours) and hardware (1 to 2 hours) calibration; zero stability check (at least 8 hours); site audit (1 to 2 hours) Meteorological instruments o Quarterly: cleaning, checking and alignment of wind direction/wind speed sensors (1 hour) o Annually: calibration of temperature and relative humidity sensors (1 to 2 hours). 2. On-site equipment failure or failure of communications between instrument and data logger (periodic): Data are lost permanently for either of these reasons; this results in gaps in the database and on the web. 3. On-site power outages (periodic): Data are lost when equipment is powered off during outages. 4. Telecommunications problems (periodic): Data are not loaded on to the web site during this period. However, these data are not lost but downloaded to the database and uploaded to the web once communication is re-established. 5. Website maintenance (periodic): Data are not lost, as they are stored locally until the website is up and running again. 2 NSW Air Quality Monitoring Network: Quality Assurance Procedures

7 6. Data validation: After collection, all data are subjected to routine validation performed by accredited air quality scientists from OEH s Quality Systems and Reporting (QSR) unit. On occasion, the data may be invalidated as a result of the inspection of calibration data, data records, instruments and site-operation logs. How is the quality of air quality monitoring data provided by the network assured? The Quality Systems and Reporting (QSR) unit is part of the Climate and Atmospheric Science branch. QSR is responsible for maintaining the validity of data collected from the AQMN. Maintenance and operation of instrumentation are the primary responsibilities of the air quality monitoring field officers, but QSR staff are responsible for ensuring that all data are flagged appropriately in the AQMN database for eventual reporting. Data flagged as valid must meet the goals set by the policies outlined in the Climate and Atmospheric Science quality manual. They must be: Precise: The data conform to set guidelines for precision. Precision is tested through daily calibration checks. Accurate. The data are accurate. Accuracy is determined by regular multi-point calibration and depends on the linearity of the instrument response. Representative. The data collected from each site are typical with respect to time of day, siting and meteorological conditions. Comparable. The data are comparable to data collected by other institutions using similar collection protocols. How are air quality monitoring data validated? The data validation procedure is outlined below and also shown in Figure 2. Automated validation Data validation step 1 Air quality data are retrieved from instrumentation by an on-site data logger and stored on site as raw data files. Instruments are also set up to provide alarm information if the instrument operates outside standard control parameters. The data logger detects this alarm information and flags the associated raw data as invalid. Data validation step 2 The raw data files are transmitted from the monitoring sites to a central location. Raw data are then loaded into the air quality database; a database loading program takes a raw hourly record and (on the basis of overnight calibration data) may correct and/or reflag this record, storing it in the database with a flag denoting the record as production data. The database loading program performs correction and reflagging according to a set of validation rules stored in the database. NSW Air Quality Monitoring Network: Quality Assurance Procedures 3

8 Figure 2. Data correction and flagging protocol. WDR, wind direction; WSP, wind speed; SD1, sigma theta 4 NSW Air Quality Monitoring Network: Quality Assurance Procedures

9 Once the data have been corrected and flagged, plausibility checks and value checking rules are applied to the data still flagged as valid to this point. Plausibility checks are applied on a site and parameter basis and may include: checks for outliers above or below pre-set thresholds (e.g. ozone values >20 pphm [parts per hundred million] or temperature values below 10 C are flagged as invalid) step change checks where data values show abrupt changes from one hour to the next and maintain the level of change. Value checking rules include: Internal consistency checking for NO X, NO 2 and NO values: if one of these is invalid, all are marked as invalid. If (NO X tolerance NO + NO 2 ) or (NO X + tolerance NO + NO 2 ), then all three values are invalidated. (Note: The tolerance value allows for instrumental uncertainty.) If collocated PM 2.5 > PM 10 + tolerance, then both are invalidated for further investigation. Manual validation Data validation step 3 If, after all validation and data quality checks have been done, data need to be invalidated, this must be done by using applications that provide an audit trail of all affected data within the database. Production data are the only records in the database that can be edited by QSR staff. If a production record is edited, a mandatory transaction record is created in the database; this record contains information on the user who edited the record, the date of the transaction, the time range of the data edited, the site and parameter, the old data value and the old status flag. It also contains comments as to why the change was made. Data validation step 4 Data irregularities are identified from data requests and data analysis reports or from stakeholder feedback. NSW Air Quality Monitoring Network: Quality Assurance Procedures 5