Air Quality Monitoring - Stage 5

01 Organise an integrated field campaign with the goal of understanding a particular emission source 

You are set to organise a field campaign, which involves carrying out intensive measurements at a carefully selected monitoring site for a period ranging from a few weeks to a couple of months (Airparif, 2025; Kapoor et al., 2025). The aim is to gain a detailed understanding of a particular emission source or pollution event, such as crop-residue burning, winter haze episodes, traffic emissions, or industrial activities. This means that a range of instruments will be deployed, including advanced high-time-resolution instruments alongside standard air quality monitoring equipment. You also want to collect filter samples, as offline sampling allows for detailed chemical composition of PM. The sampling frequency should be designed around the study objectives. For example, when investigating winter haze, daytime and nighttime samples, or even 6-hourly samples, may be collected to capture changes in emissions and atmospheric processes throughout the day. This can provide valuable insights into the sources and processes driving pollution episodes and could be beneficial in informing mitigation measures.

The data generated from these instruments will be processed to produce input files for source apportionment analysis (see Source Attribution Guidance Stage 5, Step1). Data from different instruments can also be combined within the receptor modelling (see Source Attribution Guidance Stage 5, Step 2) to improve source identification and refine source contribution estimates. This can provide policymakers with robust evidence on source contributions, allowing them to prioritise emission control measures, evaluate mitigation strategies, and support the development of targeted air quality management plans.

At this stage, collaboration with academic or research institutions in your jurisdiction becomes particularly important. The specialised software needed to carry out the receptor modelling on the data from advanced instruments often requires licences that may need to be purchased, so access through collaborators can be very helpful. If your country does not yet have this capability, you can approach a research or academic institution in another country. They can share their experience in handling similar datasets. Hands-on training sessions can be organised to help staff understand how to prepare the data correctly, run the models, and interpret the outputs, ensuring that the analysis is carried out consistently and that any issues that arise during the process can be effectively addressed. 

02 Expand Volatile Organic Compounds (VOCs) measurements 

By Stage 4, you have already started monitoring BTEX (BTEX refers to a group of volatile organic compounds (VOCs) consisting of benzene, toluene, ethylbenzene, and xylene) and have generated a substantial long-term dataset. At this point, the focus should be shifted to measure other hazardous air pollutants. For instance, the US EPA lists 188 such species, including BTEX. While it is not necessary to measure all of them, expanding the range of monitored VOCs compounds would provide a more comprehensive understanding of air quality.

At this stage, it would also be beneficial to introduce an additional VOC monitor at the site to capture a wider spectrum of VOCs, especially to better understand key emission sources, associated health impacts, and the compounds (see PAMS’s targeted VOCs list) contributing to ozone formation. This can be effectively achieved using online mass spectrometry instruments, which are well-suited for real-time VOC measurements (Claflin et al., 2021; Koss et al., 2018; Wagner et al., 2021). Existing studies and literature can serve as useful references for selecting appropriate instrumentation and measurement approaches.  

In addition, it would also be good to conduct some measurements near the source. When combined with source-specific tracer measurements and activity data, these measurements can support the development and refinement of locally relevant emission factors for VOCs and other co-emitted pollutants (US EPA, 2024). ​​​​​​​​​​​Such locally derived emission factors are often more representative of real-world conditions than values adopted from the literature and can improve the accuracy of emissions inventories and air quality model predictions. 

03 Expand the regular offline chemical speciation 

By Stage 4 (Step 1), the extended chemical dataset has been developed to support source apportionment studies, including primary organic markers from major sources such as biomass burning and traffic emissions. At this stage, you may consider expanding the input dataset to support advanced source apportionment studies (see Source Attribution Guidance, Stage 5, Step 3) by including secondary marker species. These secondary species are formed through the oxidation of biogenic and anthropogenic VOC precursors, such as isoprene, monoterpenes, and aromatic compounds. Furthermore, including these secondary markers alongside the previous extended dataset will help distinguish between primary and secondary contributions, providing valuable insights into whether pollution originates from local sources or is influenced by regional transport (Lanzafame et al., 2021). This information is particularly useful for informing policy decisions regarding local emissions and regional transport.

At this stage, you should also consider starting to monitor semi-volatile organic compounds (SVOCs) using adsorption tubes or polyurethane foam (PUF) plugs alongside conventional PM filter sampling. This would enable the characterisation of compounds that partition between the gas and particle phases. This information could also help identify effective mitigation strategies, as the partitioning of these compounds can influence their transport, and so the mitigation.

As these types of analyses require a high level of analytical expertise, it would be beneficial to establish a centralised facility if you plan to regularly measure these species, or to collaborate with an existing, well-established laboratory to carry out the measurements. In parallel, providing training to users on advanced analytical techniques is essential for building local capacity. This not only strengthens technical expertise within the network but also creates opportunities for skill development and employment in this specialised field. 

04  Measure PM oxidative potential

At this stage, it is important to strengthen the sampling strategy to better support health-related air pollution studies. Assessing the health impacts of PM remains challenging because toxicity is influenced by multiple factors, including particle size and chemical composition. No single metric can fully capture PM toxicity based on the knowledge we have so far. Several indicators can be used to assess PM toxicity, including ultrafine particle number concentrations, black carbon, toxic metals, polycyclic aromatic hydrocarbons (PAHs), and other organic species. Among these, oxidative potential (OP) has received increasing attention as it provides an indication of a particle's ability to generate oxidative stress, a process linked to adverse health effects. OP has recently been included in the revised EU Ambient Air Quality Directive as a ​“​pollutant of​ emerging​ concern”.

This stage could therefore include the collection of PM or size-segregated PM samples for OP analysis. The most commonly used acellular chemical assays for estimating OP include the dithiothreitol (DTT) assay, ascorbic acid (AA) assay, glutathione (GSH) assay, ferric–xylenol orange (FOX) assay, 9,10-bis(phenylethynyl)anthracene-nitroxide (BPEAnit) ROS assay and 2,7-dichlorofluorescein (DCFH) assays. Each assay responds differently to PM components because of differences in their redox sensitivities and underlying reaction mechanisms. As a result, individual assays may capture different aspects of the oxidative activity of PM. To obtain a more comprehensive assessment of the chemical species that may contribute to oxidative stress, it is therefore advisable to apply multiple assays in parallel (Dominutti et al., 2025; Souza et al., 2025).

This type of analysis would require a dedicated facility, established protocols, and trained personnel. However, if resources are limited, collaborating with institutions that already have established protocols for these types of measurements can greatly enhance efficiency and ensure methodological consistency.

In addition, OP data can be integrated with receptor modelling to better understand the sources contributing to toxicity (see Source Attribution Guidance, Stage 5), ultimately providing useful insights for health-focused policymaking. Developing exposure assessment plans is another key step, for example by involving volunteers equipped with portable monitoring devices (Lin et al., 2020) to generate more accurate health metrics that can be directly shared with local authorities for policy implementation. Another good option would be to conduct monitoring near the most polluted sites and measure pollutant concentrations, which can later be combined with personal activity data to assess exposure risk.

Additionally, you may also want to include a few other compounds (e.g. quinones) in the list of species to be analysed (see Step 3 above), as these can provide additional support for health assessments, particularly in relation to OP modelling. 

05  Measure ultrafine particles 

Ultrafine particles (UFP) originate from both primary sources such as direct emissions from combustion sources (e.g. traffic and biomass burning) and secondary formation through atmospheric chemical reactions (UK DEFRA, 2018). They are widely believed to contribute significantly to the PM toxicity as they can penetrate deep into the respiratory system, allowing interactions with lung tissue and potentially enter the blood stream. However, the extent of their impact remains uncertain, largely due to the limited availability of long-term measurement data. For monitoring purposes, particle counters and mobility spectrometers are among the most commonly used instruments, as they allow for detailed characterisation of UFP number concentrations and size distributions. Overall, long-term measurements of UFPs are recommended (see the revised EU ambient air quality directive) to provide input for the epidemiological studies assessing health impacts and supporting the establishment of regulatory limit values. For policymakers, long-term UFPs monitoring can also provide evidence to identify sources, evaluate the impact of mitigation measures, and refine the framework of future air quality policies and regulations. 

06 Consider mobile monitoring 

At this stage, you may also consider using a mobile van equipped with regulatory or research-grade monitoring instruments (depending on your objectives), which can significantly improve the strength of monitoring data by enhancing spatial variability (Kerckhoffs et al., 2025; Wagner et al., 2021). Compared to stationary measurements, this approach allows for a much more detailed understanding of how pollutant concentrations change over multiple locations. Mobile monitoring can also identify emerging pollution hotspots in developing cities, helping to guide the expansion or redesign of stationary monitoring networks. These measurements can also improve exposure assessments and support the development of land use regression (LUR) models, which are used to map air pollution at a much finer spatial scale.

This involves equipping the van with appropriate instrumentation, ensuring a stable power supply (e.g. battery systems and/or auxiliary engine alternators), and installing monitoring equipment securely within the vehicle. You may need to give careful consideration to inlet positioning and data logging systems. Mobile monitoring will allow flexible deployment across multiple locations, making it particularly useful for targeted investigations, short-term campaigns, and monitoring in areas not covered by regulatory monitoring stations. 

07 Monitor other emerging pollutants

Emerging pollutants such as PFAS, microplastics, dioxins, pesticides and UFPs (see Step 5 above) are receiving increasing attention because, although they are not yet widely regulated, they pose potential risks to both environmental and human health (Boahen et al., 2025; Enyoh et al., 2020; Jin et al., 2022). Monitoring methods vary in cost, reliability, and technical complexity. PFAS, dioxins, and pesticides are typically analysed using mass spectrometry techniques in the laboratory, which provide highly reliable and sensitive measurements but require specialised expertise and can be costly to operate and maintain. Microplastics are commonly measured using microscopy and spectroscopic methods (e.g., FTIR or Raman spectroscopy). In some cases, microplastics can also be analysed using a combination of techniques, such as mass spectrometry and thermal cracking gas chromatography. However, these techniques still have limitations and cannot be applied to all environmental samples. UFPs can be measured in near real time using particle counters and mobility sizers, providing high-time-resolution data but requiring specialised instrumentation and expert data interpretation. As monitoring techniques for these pollutants are still evolving, it is advisable to collaborate with research and academic institutions to initiate measurements and develop a better understanding of suitable protocols, quality assurance procedures, and methodologies. 

08 Conduct instrument intercomparison to assess their performance 

Many high time-resolution instruments are being introduced to monitoring networks at this stage, and their effective use will require appropriate staff training or the recruitment of personnel with Master’s or PhD-level expertise who are capable of operating and troubleshooting these advanced instruments.

For research grade instruments (non-regulatory ones), it is strongly recommended to encourage participation in, or even organisation of, intercomparison exercises to evaluate instrument performance and ensure data quality. A good example is the ACSM intercomparison campaign hosted by the Aerosol Chemical Speciation Monitor Calibration Center (ACMCC) at SIRTA-LSCE in France, which combines hands-on training with sessions on data processing and submission. Similarly, for offline filter analysis, initiatives like the OGTAC intercomparison focus on secondary marker species and provide a useful platform for validating analytical techniques and ensuring consistency across laboratories.

For regulatory instruments, intercomparison activities are also very important as they can improve data comparability between monitoring stations and increase confidence in the data used for policy assessments and decision making. 

09  Establish and publish Standard Operating Procedures (SOPs) for long term monitoring 

Following Stage 4, it is important to develop and publish Standard Operating Procedures (SOPs) that cover instrument operation, data processing, and long-term monitoring protocols. These should ideally be issued by the national environmental or regulatory authority to ensure accessibility, consistency, and credibility across the research community, stakeholders, and policy advisors.

The documentation should be clear and easy to follow, even for users with limited experience. Wherever possible, it should include step-by-step explanations of methods, data treatment procedures, and guidance on how to interpret results. This helps ensure the data are used correctly and consistently across different users and organisations.