Case studies

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Case Study COVID-19 lockdown action temporarily reduces emissions

Pushan Shah, South Australian Environment Protection Authority

Jason Choi, Environment Protection Authority Victoria

The beginning of 2020 brought COVID-19, an unexpected global pandemic that caused normal activities to cease with government directives to stay at home. These directives were termed ‘lockdowns’, with many businesses forced to close and everyday movements restricted. The restrictions manifested themselves in different ways in Australia’s capital cities, but all impacted airborne emissions. Here, the evidence of emissions reductions is examined through ambient pollutant concentrations measured in Adelaide, Brisbane, Melbourne and Sydney during these lockdown periods.


On 12 March 2020, the South Australian Government implemented lockdown measures, lasting until the end of April. The measures were expected to reduce air pollution due to a decrease in noncommercial vehicle traffic, and in industrial and commercial activity. The average reduction in traffic volume was 40% during the peak of the restrictions, before returning to near-normal levels at the end of July (Figure 1).

Figure 1 (a) Traffic volume and (b) CO concentration across metropolitan Adelaide, March–July 2020

CO =carbon monoxide; ppm = parts per million

Source: Traffic data, South Australian Department of Infrastructure and Transport

There are no roadside monitoring stations in Adelaide to observe the impacts of these reductions directly, but the reduction in people travelling to Adelaide central business district (CBD) is observed from the centrally positioned station in the CBD. In Adelaide CBD, levels of carbon monoxide (CO) decreased by 40% in accordance with the traffic volumes, compared with measurements taken during the same period (March–April) in the 5 years before the COVID-19 lockdowns (Figure 2). Evidence of decreases in nitrogen oxides (NOx) and fine particulate matter (PM2.5) is harder to observe. Five years of data were used for the pre-pandemic period to reduce the influence that large-scale events, such as bushfires and land burns, can have on estimates of ambient pollutant concentrations. Although there was a small reduction in NOx levels, PM2.5 levels continued to be influenced by bushfire smoke in the early part of 2020 and remained very similar to past averages. Overall, an improvement in air quality was recorded, with 20–40% reduction in all pollutants during March and April 2020.

Figure 2 CO, NOx and PM2.5 levels during the initial peak COVID-19 restrictions in Adelaide compared with the previous 2015–19 average and the rest of 2020

CO = carbon monoxide; µg/m3 = microgram per cubic metre; NOx = nitrogen oxides; PM2.5 = fine particulate matter; ppm = parts per million

Source: South Australian Environment Protection Authority


Numbers of coronavirus cases in Brisbane were much lower than elsewhere in Australia in early 2020, so restrictions were less strict. Still, many people chose to work from home, and this is reflected in a 13% decrease in nitrogen dioxide (NO2) levels in Brisbane compared with the 10-year average (Welchman et al. 2020). However, the Katestone report notes that the impact of meteorology (e.g. stagnant, pollutant-trapping conditions) may have masked the level of reductions that might otherwise have occurred in Brisbane.


Lockdown measures in Melbourne were introduced on 17 March 2020. Traffic flows began decreasing immediately, to a minimum of 30% in the week of 12 April 2020, compared with pre-lockdown flows. Traffic began resuming steadily and by the beginning of June had reached 80% of normal levels. This was curbed again in August when very strict lockdown measures were in place for more than 100 days. The impact of the traffic reductions is most easily seen in the NO2 columns (Figure 3). Comparing the 2020 profile on 10 April with the profiles calculated from the preceding 5 years shows a 24% reduction in NO2 in the area surrounding the city of Melbourne.

Figure 3 (a) Fifteen-day running mean total column NO2 on 10 April 2020, (b) as an average of the same time across 2015–19 and (c) as the difference between the 2 plots

cm2 = square centimetre; NO2 = nitrogen dioxide

Source: NASA Aura OMI satellite, originally published in Air Quality and Climate Change, publication of the Clean Air Society of Australia and New Zealand

Air quality data collected at all Environment Protection Authority Victoria monitoring stations in Melbourne between 17 March and 12 May for 6 years (2015–20) were examined, separating out 2020 to assess the impacts of the lockdowns. The average diurnal columns over these periods also show a 25% decrease in NO2 during the lockdowns (Figure 4), similar to the NO2 reduction calculated by Ryan et al. (2021). At the same time, there was a 3% increase in ozone. This increasing ozone effect has been observed all over the world and tends to be greater in cities where the lockdown measures were strictest (Gkatzelis et al. 2021). Although NOx compounds are involved in the chemical production and removal of ozone, a direct link between decreasing NO2 and increased ozone cannot be made without considering other ozone-forming chemicals such as volatile organic compounds (VOCs), and the impact of temperature.

Reductions in other pollutants such as carbon monoxide (CO) and PM2.5 during the lockdown period in Melbourne were more difficult to observe, as reductions were also observed in February and early March. This might be caused by reduced tourism to the area following the severe summer 2019–20 bushfires. Post-lockdown, there were increases in CO levels during 2020 beyond those from the previous 5 years. This was caused by smoke from wood heaters being used more prolifically when evening temperatures decreased well below 10 °C.

Figure 4 NO2 and ozone levels during the peak COVID-19 restrictions across all Melbourne air quality stations compared with the previous 2015–19 average for the same period

NO2 = nitrogen dioxide; ppb = parts per billion

Note: Solid line represents the mean; shaded area represents the data range.

Source: Environment Protection Authority Victoria, originally published in Air Quality and Climate Change, publication of the Clean Air Society of Australia and New Zealand


Traffic volumes decreased by 19–44% across Sydney as the lockdowns started to take effect from 16 March 2020 (Duc et al. 2021). Duc et al. (2021) examined the raw air quality data and observed decreases in concentrations of NO2 (–18%), CO (–13%) and PM2.5 (–13%), while ozone levels increased (+1.5%). However, by detrending the air quality data for meteorological effects, Ryan et al. (2021) estimated that NO2 levels decreased by 8% as a result of lockdowns, but concentrations of ozone and PM2.5 increased by 20% and 24%, respectively.


Chemical reactions in the atmosphere are highly nonlinear, and unexpected changes in secondary pollutants (e.g. ozone increases) can occur when primary pollutants such as NO2 are reduced. However, reducing NOx emissions in Australia will almost always lead to better overall air quality in our urban areas. Although there is some nonlinearity in the chemistry, and there are occasions when ozone levels may be more related to VOCs than NOx, policies that reduce primary emissions of NOx and other air pollutants and their precursors will almost always succeed in improving air quality.

Case Study ACT indoor air quality during the summer 2019–20 bushfires

A mobile particulate monitor was placed inside a Canberra house during one of the worst smoke episodes of the summer 2019–20 bushfire period. The house is probably quite ‘average’ in Australia, built around the 1960s. It is not very well sealed, and does not use any kind of filtration system such as a high-efficiency particulate air filters. The occupant describes the house as being hard to heat in winter and keep cool in summer, which suggests that it is ‘leaky’. Five-minute average measurements were taken over a short period during the peak bushfire event. These measurements compared indoor and outdoor concentrations of fine particulate matter (PM2.5) when the smoke was particularly bad (Figure 26). The outdoor measurements are from the nearest monitoring station at Civic, approximately 5 km from the house.

Figure 26 (a) Comparison of PM2.5 measured indoors with outdoor PM2.5 from the nearest fixed air quality monitoring station (Civic) during the summer 2019–20 bushfire season. Both datasets are 5-minute averaged PM2.5. (b) Fraction of total particles 2.5 μm diameter or less

μg/m3 = microgram per cubic metre; µm = micrometre; PM2.5 = fine particulate matter

Note: The red arrow denotes when the indoor sensor was moved to a room with slightly better sealing ability, late in the morning of 1 January 2020.

Source: Health Protection Service, ACT Government

At 10 pm on 31 December 2019, the outdoor peak measurement of PM2.5 was 1,633 micrograms per cubic metre (μg/m3). As the outdoor monitoring station is 5 km away, the times that the smoke plume reached the station and the house would differ. But given the extreme nature of this air quality event and how widespread these smoke plumes were, we can assume that all of Canberra was exposed at approximately these levels. Around 7 am the next morning, levels of PM2.5 inside the house had reached 316 μg/m3 as a 5-minute average. Although the PM2.5 concentration inside the house was around 5 times less than outdoor levels, the 24-hour indoor average was still well above the National Environmental Protection Measures limit of 25 μg/m3. The red arrow in Figure 26 shows when the sensor was moved into a different room, which the occupant was able to seal a little better. Concentrations of PM2.5 decreased by around 70 μg/m3 during this 2-hour period. When the smoke outside passed (shown in the plot at noon on 30 December), the householder benefited from ventilating the house quickly to get the smoke out.

Given the extreme levels outside, the occupant was definitely better off inside. During this elevated smoke period, the particles indoors were almost entirely 2.5 micrometres (μm) or less, which are more likely to travel deeper into the lungs than the larger particles.

The 5-minute average measurements (Figure 26) also highlight how rapidly concentrations outdoors can increase. It took just 50 minutes for PM2.5 concentrations outdoors to increase from around 13 μg/m3 to 1,000 μg/m3 on the evening of 31 December. Doors and windows needed to be sealed before 8 pm to keep the worst of the smoke out of the house.

Most people rely on the smell of smoke to know when to close the house to keep smoke out, and open it for ventilation once the smoke has passed. Access to real-time air quality measurements can help people manage indoor air quality, and protect them from high levels of smoke indoors, when levels outside might be lower. Access to smoke forecasts could also help people prepare their houses for these ‘extremely poor’ category air quality events.

Case Study Thunderstorm asthma

The world’s most severe incident of epidemic thunderstorm asthma (ETSA) occurred on 21 November 2016 in Melbourne, coinciding with the peak in the grass pollen season (Thien et al. 2018). At 5:30 pm local time, many people were commuting or outside enjoying temperatures above 30 °C when a line of dry thunderstorms swept across the city from west to east (Figure 28). The first calls to the emergency services for severe breathing difficulties started within minutes of the storm passing. Over the following 6 hours, 814 ambulances were called (DHHS 2017). Victorian health services were overwhelmed, with a 672% increase in emergency department presentations that night, and a 3,000% increase in intensive care patients with asthma (DHHS 2017). Unfortunately, 10 people died as a result of this storm.

Figure 28 Radar image showing the position of the thunderstorm system at 5:00 pm, and progression of the storm eastwards in half-hourly periods

The majority of ETSA patients tend to be allergic to grass pollen (Knox 1993), and in particular to ryegrass pollen. Ryegrass is a used in agricultural pasture and currently found in regions to the north and west of Melbourne. Distributions of pasture grass may change with climate and agricultural practices (see the Land chapter).

In laboratory studies, grass pollen grains have been observed to rupture when submerged in water, ejecting hundreds of highly allergenic sub-pollen starch grains (Suphioglu et al. 1992). In the atmosphere, it is thought that pollen grains can be swept high into thunderstorm clouds where they rupture, and the sub-pollen grains are then concentrated at ground level by the downdraft (Marks et al. 2001, Taylor & Jonsson 2004).

Epidemic thunderstorm asthma forecasting

ETSA is a relatively infrequent event (Silver et al. 2018), but its potential impact highlights the importance of developing a predictive system to better prepare emergency services for a large influx of patients. For people with hayfever or pollen-exacerbated asthma, a high grass pollen forecast can also influence the use of preventive medications, or encourage people to stay indoors.

In 2017, the Victorian Department of Health and Human Services funded the development of a pilot thunderstorm asthma service (Bannister et al. 2021). This provided 5 additional pollen monitoring sites in Victoria. A statistical model to predict daily mean grass pollen concentrations up to 5 days ahead was developed based on weather data and 21 years of grass pollen measurements at the University of Melbourne (Figure 29). The ambient temperature, relative humidity and wind speed all affect how pollen is emitted and dispersed in the Melbourne atmosphere (Emmerson et al. 2019). The Bureau of Meteorology then developed a simple decision matrix that estimates relative thunderstorm asthma risk by combining forecast pollen concentration (low, moderate, high, extreme) with forecasts of wind gust speed and coverage, and gives a rating to each region (Figure 30).

Figure 29 Example of the Melbourne grass pollen forecast at the peak of the season (mid-November 2020)

Figure 30 Example of the thunderstorm asthma forecast for 23 November 2020

The pilot warning system was implemented in September 2017, in time for the spring pollen season. It successfully identified the increased risk associated with 2 localised asthma events during November 2017, and verification against hospital data showed that the system has some ability to discriminate days with elevated ETSA risk. However, the process of pollen rupturing triggered by high relative humidity caused frequent false alarms of ETSA, as the relative humidity levels during night-time in spring are usually very high (Emmerson et al. 2021).

Research is continuing to understand how weather and pollen interact to cause conditions that lead to ETSA events, which will allow us to refine and improve the system.

Case Study Exposure to wood heater smoke

Tasmania is a state with a small population, relatively low traffic volumes and relatively little heavy industry. It is also influenced by very clean air from the Southern Ocean during westerly or south-westerly winds. However, in winter, the smoke from wood heater use is very noticeable, and forms a large proportion of Tasmania’s annual fine particulate matter (PM2.5) pollution.

Exposure to smoke is a known public health issue for Tasmania. Borchers Arriagada et al. (2020) estimated that, from 2010 to 2019, smoke in Tasmania contributed on average to 69 deaths per year, with 74% attributed to wood heater smoke and 26% to prescribed burning smoke. The estimated annual health cost of wood heater smoke in Tasmania was more than $250 million.

Over the past decade, the Environment Protection Authority Tasmania (EPA) has increased the statewide air monitoring network to better understand and plan for reducing population exposure to smoke.

Using data on wood heater density within a 1 km radius of Tasmania’s air stations, together with wind data, a population exposure relationship was determined that could be applied to regions with no smoke monitoring (Innis 2021). This work is subject to further analysis but may provide a means of estimating the mean wintertime PM2.5 across the state.


Launceston, in the north of Tasmania, is located in a valley where wood smoke is easily trapped in the nocturnal boundary layer. In the winters of 2015 and 2017, the EPA conducted a series of extensive smoke measurement surveys to map the spatial distribution of smoke across the city (Figure 40). These surveys used vehicle-mounted PM2.5 monitors, which provided geolocated measurements every 5 seconds. Consistent patterns in the smoke distribution across the city were seen in both winters, with suburbs such as Ravenswood (north-east), Newnham (north) and Summerhill (south-west) regularly exhibiting some of the highest PM2.5 concentrations.

High levels of PM2.5 were correlated with the number of wood heaters in the area (Innis et al. 2017). These spatial surveys demonstrate how localised the high concentrations of PM2.5 can be, at times even localised to 1 or 2 streets (Figure 40). For example, short-term concentrations of PM2.5 above 150 micrograms per cubic metre (μg/m3) occurred in Summerhill during winter 2017, but 400–500 metres away in an area of lower housing density the concentrations were mostly as low as 20 μg/m3.

High ambient smoke levels typically peak in the later evening. At these times, it is not expected that many people would be outdoors in Tasmania, and hence few people are directly exposed to ambient wood smoke, but leaky buildings allow wood smoke indoors.

Figure 40 Evening smoke surveys of Launceston in 2015 (left) and 2017 (right)

μg/m3 = microgram per cubic metre; PM2.5 = fine particulate matter

Note: Peak instantaneous PM2.5 measurements are represented by symbol colour.

Source: Redrawn from Innis et al. (2017)

Poor wood heater operation occurs when the appliance is kept smouldering overnight, when new fuel is loaded, and when oxygen levels to the burn are damped to a minimum. Modern wood heaters are manufactured to burn more cleanly, but there is currently no requirement in Tasmania to replace older heaters.

A wood heater buy-back scheme was implemented in Launceston in 2001 and removed around 2,000 appliances, possibly more in the central area of the city than in the outer suburbs (J Innis, EPA Tasmania, pers. comm.). This helped to reduce the measured wintertime smoke levels (ABC News 2007).

Case Study Hazelwood mine fire

In February 2014, spot grass fires ignited the coal seam at the Hazelwood open-cut coal mine in the Latrobe Valley in Victoria. The location of the mine is just across the main M1 highway from the town of Morwell, with a population of approximately 14,000 people.

The fire burned for 45 days. Very high levels of fine particulate matter (PM2.5) and carbon monoxide (CO) (peak hourly predictions of 3,730 micrograms per cubic metre (μg/m3) for PM2.5 and 58.6 parts per million (ppm) for CO) were estimated to have occurred in the first 2 days of the burn (Luhar et al. 2020), before smoke monitoring was able to commence. Favourable wind conditions helped to transport smoke away from Morwell towards the end of the first week of the burn, before firefighters gained some control of the fire. However, over the 45-day duration of the fire, residents of Morwell experienced exceedances of the air quality standards for PM2.5 on 23 days and for CO on 8 days.

The Hazelwood Health Study was set up in 2015 with funding from the Victorian Department of Health and Human Services to examine ongoing health effects experienced by residents of the Latrobe Valley, resulting from exposure to the mine fire smoke. The study is expected to continue for 10 years.

Researchers set out to examine whether the mine fire has contributed to adverse health consequences in the short and long terms, including low birth weights of babies born to expectant mothers who were exposed, child development, psychological distress and incidence of cancer. Scientists also studied the health outcomes in a control population in Sale who were not exposed to the mine fire smoke. The Hazelwood study could not study the whole populations of both towns and depended on patient volunteers coming forward.

Respiratory and cardiovascular health in adults

Residents of Morwell began to experience symptoms within 2 days of the fire starting, with increases in visits to the emergency department for respiratory and cardiovascular problems (Guo et al. 2020). For each increase of 10 μg/m3 in PM2.5, there was an 11% increase in visits to doctors and a 22% increase in use of respiratory services (Johnson et al. 2020). Compared with the control population, those exposed to smoke from the mine fire were more likely to experience a cough with phlegm and wheezing (Johnson et al. 2019). Three years after the fire, Morwell residents were reporting a higher level of ongoing respiratory symptoms than residents of Sale (Ikin et al. 2020). However, there was no evidence of ongoing cardiovascular problems 4 years after the fire.

Maternity and child health

With such high concentrations of smoke in the atmosphere, there were concerns about impacts on developing fetuses and the health of children. Thankfully, there were no associations between exposure to smoke from the fire and fetal growth and maturity (Melody et al. 2019). However, mothers were more likely to have gestational diabetes, resulting in heavier babies: there was a 97 g increase per 10 μg/m3 increase in PM2.5 (Melody et al. 2020). There was also a greater incidence of antibiotics being dispensed to infants exposed to the mine fire smoke (Shao et al. 2020a).

The lung function of children aged less than 2 years at the time of the mine fire showed some damage 3 years later, which increased per unit increase of 10 μg/m3 in average PM2.5 (Shao et al. 2020b). These children also showed increases in vascular stiffness (Zhao et al. 2020).

Mental health

Morwell residents were anxious about their exposure to the smoke and impacts on their health (Jones et al. 2018). Exposure to the mine fire smoke was found to be associated with high levels of psychological distress, particularly in young adults (Broder et al. 2020). There were still ongoing post-traumatic stress symptoms 2 years after the fire, suggesting that incident support for communities needs to continue well after the initial event (Maybery et al. 2020).

Some residents were able to evacuate, but, because of the low socio-economic background of this region, most residents stayed in Morwell. Local schools were closed, and children were educated away from Morwell during the day, causing uncertainty and disrupted learning patterns. The use of a trauma-informed approach to teaching was beneficial, taking into account the individual needs and circumstances of each student (Berger et al. 2018).

Residents used a wide range of social media platforms as part of their coping strategies, to help inform others and to feel part of a community. Authorities also used social media as a fast way to get short messages out to communities. However, the increased need for clear information during an extreme event means that social media cannot replace face-to-face contact between authorities and residents (Yell & Duffy 2018).

Faster response for monitoring systems

There was a lag of approximately 4 days between the fire starting and teams from CSIRO and the Environment Protection Authority Victoria mobilising instruments to measure the smoke in Morwell (Reisen et al. 2017). Assistance from the Environment Protection Authority Tasmania arrived 10 days into the fire, with a DustTrak instrument mounted to a vehicle (Innis et al. 2015). It was clear from the air quality modelling that high concentrations of pollutants in Morwell were missed when the fire started. In response to the Hazelwood mine fire inquiry, 10 mobile incident smoke monitors were situated around regional Victoria so that State Emergency Services can deploy them quickly and easily when required (Premier of Victoria 2017). New South Wales also built several portable air quality monitoring pods containing air quality and meteorological instruments, which can quickly be deployed to incidents (New South Wales Government 2017).

Case Study Air quality monitoring by the states and territories

Air quality monitoring is undertaken by the states and territories 365 days a year. This requires significant effort and resourcing, in terms of siting and setting up the station, instrument calibration and maintenance, and quality control of measured data before they are released to the public.

Not all the 211 stations (Figure 45) are compliant with the National Environment Protection Measures (NEPMs). NEPM compliance requires the monitoring station to have a clear sky angle of 120°, and to be sited more than 50 m from a main road and 10 m from the nearest tree. Trees and buildings limit the flow of air to the monitoring site, and pollution may also deposit onto the trees before reaching the station. Having clear sky access should provide an unrestricted measurement. Existing NEPM stations are re-evaluated for compliance every 5 years. Noncompliant stations still provide useful data, and some are industry funded, or use lower-cost instruments for indicative measurements – for example, those in regional New South Wales that contribute to the dust measurements (see Dust storms), and stations in Tasmania outside Hobart, Launceston and Devonport that measure particulate matter.

An air quality monitoring station will typically measure the NEPM criteria pollutants, alongside meteorological variables, such as temperature, wind speed and direction, rainfall and humidity (Table 4).

Table 4 Measurement techniques used to monitor air quality pollutants at state and territory monitoring stations


Measurement technique

Carbon monoxide

Infrared spectrometry


Ultraviolet spectroscopy

Nitrogen dioxide


Fine particulate matter (PM2.5)

Beta attenuation monitor

Coarse particulate matter (PM10)

Tapered element oscillating microbalance

Sulfur dioxide

Pulsed fluorescent spectrophotometry

Recommendations from New South Wales on the design of an air quality monitoring network are to be adopted nationally (OEH 2019). This includes the need to increase the number of monitoring stations as the population of a region expands beyond 25,000 people. This is so that the recent NEPM requirement to assess population exposure to air pollutants can be adequately met.

Once the measurements have been checked, they are processed to their required NEPM averaging time (e.g. hourly) before they are released to the public. The measurements are usually displayed with a colour representing the air quality category (see Approach), which shows the health impact of that measured value.

Case Study Management of dust and odour at Brooklyn Industrial Precinct, Victoria

Dr Rosemary Fedele, Environment Protection Authority Victoria

Brooklyn is a suburb 10 km west of Melbourne that has longstanding issues with odour and dust pollution. Much of this pollution comes from the Brooklyn Industrial Precinct (BIP), which consists of several major industrial, waste and recovery industries (construction and demolition waste, metal waste recycling, organic waste recycling), and skip and transport container storage facilities (Figure 46). The activities in the BIP will continue because the area is designated as one of 22 future key waste and resource recovery hubs in the Strategic Waste Management Plan for Victoria.

Several facilities in the BIP include large areas of open and unsealed land and roads, which are extensively used by heavy vehicles and machinery. They include uncovered material stockpiles, which are prone to wind erosion. BIP also has solid waste material crushing activities that can generate high levels of dust. The number of transport container storage facilities in the BIP continues to increase because of its location close to the Port of Melbourne. The increase in container transport between the port and BIP will lead to large numbers of diesel-fuelled vehicles driving through the nearby residential area. In recent years, several public reports have recognised the need to reduce air pollution in the BIP (Brimbank City Council 2016, VAGO 2018, Inner West Air Quality Community Reference Group 2020).

Figure 46 Container park site in Brooklyn Industrial Precinct (left) and aerial image of Brooklyn Industrial Precinct in 2020 (right)

Photos: left – Geoff Mitchelmore; right – Google Earth

Since the Environment Protection Authority Victoria (EPA Victoria) started monitoring in October 2009, the air quality in Brooklyn has not met state or national ambient air quality standards for coarse particulate matter (PM10) (Figure 47). Victoria has adopted a lower annual PM10 limit of 20 micrograms per cubic metre (µg/m3) called the Environment Reference Standard. This new level aligns with the levels set by the World Health Organization. Brooklyn’s annual average PM10 concentrations have been on average 35% higher (ranging from 22% to 56%) than at EPA Victoria’s other monitoring stations at Alphington, Footscray and Dandenong.

Figure 47 Annual average PM10 concentration over the past 10 years in Brooklyn, Footscray, Alphington and Dandenong

µg/m3 = microgram per cubic metre; NEPM = National Environment Protection Measure; PM10 = coarse particulate matter; SEPP = State Environmental Planning Policy

Note: Horizontal lines represent the national (Ambient Air Quality NEPM) guideline value of 25 µg/m3 and the Victorian (Environment Reference Standard) guideline value of 20 µg/m3) for annual average PM10 concentrations. No data are available for Dandenong from 1 January 2017 to 5 October 2017, and for Footscray from 10 April 2014 to 24 July 2014 and from 29 October 2019 to 8 February 2020 due to technical issues.

Brooklyn exceeded the PM10 24-hourly National Environment Protection Measure level of 50 μg/m3 on more days than in other areas in metropolitan Melbourne (Alphington, Footscray and Dandenong) since 2010 (Figure 48). Between 2016 and 2018, there was a 61% chance that PM10 daily average concentration would exceed the daily standard of 50 μg/m3 if the following 3 conditions occurred:

  • the maximum daily temperature was greater than 22 °C
  • there was less than 0.5 mm rain for the previous 2 days
  • the wind direction was from the north.

Figure 48 Number of days per year that have exceeded the PM10 daily air quality objective of 50 µg/m3 over the past 10 years in Brooklyn, Footscray, Alphington and Dandenong

µg/m3 = microgram per cubic metre; PM10 = coarse particulate matter

Note: No data are available for Dandenong from 1 January 2017 to 5 October 2017, and for Footscray from 10 April 2014 to 24 July 2014 and from 29 October 2019 to 8 February 2020 due to technical issues.

In 2011, there were fewer days that exceeded the PM10 limit. This may be because of the high rainfall experienced that year, which was 20–54% higher than in all other years since 2010. From 2015 to 2018, EPA Victoria’s regulatory and enforcement responses to pollution reports, and the sealing of 2 major roads in the BIP in 2015, resulted in:

  • lower emissions from industrial sources
  • the lowest annual average PM10 concentration recorded at Brooklyn in 2016 (Figure 50)
  • substantial reductions in the number of days that PM10 daily average concentrations exceeded the daily air quality objective of 50 μg/m3 during 2015–18.
  • However, in 2014, 2019 and 2020, bushfire smoke also impacted air quality in metropolitan Melbourne, including Brooklyn. Air quality in Brooklyn also continues to be impacted by industrial activities.
Case Study Indigenous knowledge applied to local climatology better describes patterns in air quality

Stephanie Beaupark, Ngugi and University of Wollongong

Collaborative research in partnership with Australian Indigenous peoples creates an opportunity for the sharing and recognition of immense ecological and cultural knowledge that has resulted from more than 60,000 years of Indigenous custodianship of land and sea Country in Australia (Rose 1996, Rose 2000, Clarkson et al. 2017).

One successful example of knowledge sharing is demonstrated by research that came out of the Clean Air and Urban Landscapes (CAUL) hub (Paton-Walsh et al. 2019). This collaborative research investigated how Indigenous knowledge might inform the creation of a more suitable set of local ‘seasons’ for western Sydney. The research demonstrates that Indigenous ways of accumulating knowledge and adapting to the changing landscape are key to understanding and caring for Country, and in providing new framings for non-Indigenous (including western scientific) understanding of the climate (Roös 2014). A broader aim of this research was to improve understanding of the annual cycles associated with atmospheric pollutant concentrations within the region. Through the development of a set of ‘quasi seasons’, named Indigenous Knowledge Applied to Local Climatology (IKALC) seasons (Figure 49), the project was successful in using Indigenous concepts of weather and time of year for the western Sydney region to understand the times of year when meteorological conditions are most likely to result in poor air quality.

Figure 49 IKALC seasons of western Sydney, based on weather, including temperature, wind speed and rainfall, at different times of year

IKALC = Indigenous Knowledge Applied to Local Climatology

In cities, the key atmospheric pollutants responsible for poor air quality are fine particulate matter (PM2.5), ozone, carbon monoxide (CO) and nitrogen oxides (NOx). High atmospheric concentrations of these pollutants result in various health conditions (Barnett et al. 2006, Jerrett et al. 2009, Broome et al. 2015, Lelieveld et al. 2015, OEH 2017, OEH 2018, Hanigan et al. 2019b). In western Sydney, the meso-scale meteorology is affected by the topography of the landscape, resulting in the worst air pollution within the city. This can be due to phenomena such as cold air drainage from the mountains during colder times of the year, which traps air pollution close to the surface. This research explored the annual variability of air quality and highlighted how it is influenced by seasonal weather patterns such as temperature, rainfall and wind direction (Jiang et al. 2017, Paton-Walsh et al. 2017, Chambers et al. 2019). The allocation of the Eurocentric seasons of ‘summer’, ‘autumn’, ‘winter’ and ‘spring’ is an arbitrary division of the year and is not well aligned with synoptic-scale weather patterns of the Sydney Basin (Giblett 2012, Entwisle 2014). For example, the set annual dates of the ‘winter season’ start too late in the year to fully represent the coldest time of the year.

The set of IKALC seasons for western Sydney was developed by interviewing Indigenous Elders and knowledge holders of the area. The Darug people are the Indigenous language group located in the eastern Sydney area (Bursill et al. 2007). The research reflects perspectives of the individuals interviewed and is not intended as a complete representation of wider views of the Indigenous community of western Sydney. The project used the Indigenous perspectives and knowledge communicated throughout the study of what a ‘season’ is, and associated weather patterns, within an Indigenous cultural framework. This was combined with statistical analysis of local Bureau of Meteorology decadal-scale weather records to create the IKALC seasons.

The Indigenous co-authors communicated that precolonial Indigenous weather and seasonal knowledge are no longer applicable to the region and mostly have been lost in the past 200 years, when the landscape has changed dramatically. This resulted in a shift in focus to acknowledge that Indigenous knowledge has always been dynamic; cultural knowledge is an ongoing process of learning from the landscape, and being a strong custodian of Country requires ongoing refinement of contemporary Indigenous knowledge. These findings are complementary to western science, which constantly collects and interprets data to increase depth of environmental knowledge.

As recommended by Indigenous co-authors, the study was not restricted to western understanding and associated framings of seasonality or calendar months, resulting in a better representation of seasons for air quality. A key discovery was identification of the cold/still time of the year, occurring between 8 May and 27 July. In this period, concentrations of PM2.5, CO and NOx are at their maximum, and ozone is at a minimum in Chullora, Sydney. Compared with the Eurocentric seasons, this better captures the air quality in still, cold conditions from May to July, and the windy, cold conditions of August. Compared with other Australian seasonal calendars, the IKALC seasons also align with important botanical markers in the Sydney region, using qualitative evidence.

This work is incomplete because it only includes weather observations. A future direction for the research is to create a comprehensive calendar for Sydney led by the local Indigenous community. This would include all aspects of the Indigenous climate framework (Figure 50). A more complete Indigenous cultural framing of the seasons would also demonstrate the interrelationship with biological indicators, land management and language, as known within local Indigenous knowledge systems (Woodward et al. 2009, Green et al. 2010, Woodward 2010, Nuggett et al. 2011, Prober et al. 2011). Documentation of this more holistic approach to seasonal understanding could create a resource for knowledge holders to pass on knowledge for future generations of the Darug people (Green et al. 2010, Woodward 2010, Prober et al. 2011). Further, exploration of current seasonal cycles may also improve seasonal definitions over extended periods (incorporating large-scale events such as the El Niño–Southern Oscillation) (Letnic et al. 2005, Zhou et al. 2009).

Figure 50 Indigenous climate framework

Using contemporary Indigenous knowledge of Sydney has enabled better understanding of the local climatology of the Sydney Basin. This approach is essential to understanding the climate of Australia, especially in cities. The methodology used to develop the IKALC seasons for western Sydney can be applied anywhere in the world to identify and predict the times of year when meteorological conditions are likely to result in poor air quality in a region. This can be informative for public policy on suitable emissions controls.

Case Study Land use regression

Land use regression (LUR) techniques have been developed to predict spatial variations in nitrogen dioxide (NO2) as an indicator of traffic-related air pollution (Hanigan et al. 2017, Cowie et al. 2019). LUR has been shown to represent up to 70% of the spatial variability in NO2 concentrations, and can capture peak roadside concentrations as well as background concentrations (Knibbs et al. 2016). The LUR technique has also been applied to predict particulate matter concentrations away from fixed air quality monitoring sites (Dirgawati et al. 2016).

The ability to accurately predict spatial variability in air pollution has been a game changer in epidemiology studies, where location and exposure can be connected to assess disease causation. Whereas it is clear that respiratory and cardiovascular diseases are associated with air pollution, even at low levels (Salimi et al. 2018, Vander Hoorn et al. 2019), other diseases such as Parkinson’s disease are not related to air pollution exposure (Salimi et al. 2020).

Case Study AIRBOX

The Atmospheric Integrated Research facility for Boundaries and OXidative experiments (AIRBOX) is a purpose-built shipping container housing research-grade scientific instruments for making comprehensive atmospheric measurements. AIRBOX can be transported and deployed anywhere in Australia. It has also been installed on the Australian marine research vessels, the RSV Aurora Australis and RV Investigator, on their voyages to Antarctica (Figure 51).

AIRBOX can continuously sample the atmosphere using 9 instruments in tandem, analysing trace gases; aerosol size, mass and speciation; meteorological variables; boundary layer heights; and cloud profiles. Recently, AIRBOX has been measuring biogenic volatile organic compounds in the eucalypt forests between Sydney and Wollongong, aerosol composition at Garden Island in Western Australia, formation of aerosols and cloud condensation nuclei in the Southern Ocean (McFarquhar et al. 2021), and nutrient deposition via atmospheric aerosols to the Great Barrier Reef (Chen et al. 2019, Strzelec et al. 2020).

Figure 51 Clockwise from top left: AIRBOX deployed on Garden Island, Western Australia; AIRBOX on board the RSV Aurora Australis next to the tower and weather radar ‘ball’; AIRBOX on top of the RSV Aurora Australis at Newcomb Bay, Casey Station, Antarctica

Photos: Robyn Schofield and Alan Griffiths