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Good Practice Guide on Assessing Discharges to Air from Land Transport

Foreword by the Ministry

Acknowledgements

Key Data Sources & Models

1 Introduction

2 Legislative and Policy Context

3 Assessing Discharges to Air from Transport

4 The Assessment Process

5 Air Quality Criteria

6 Tier 1 Screening Assessment Process

7 Tier 2 Conservative Assessment Process

8 Tier 3 Detailed Assessment Process

9 Assessment of Community Impacts and Comparison of Project Options

10 Mitigation Options

11 Monitoring Project Effects

References

Appendix 1: Calculations and Data

Appendix 2: Traffic and Transport Data

Appendix 3: Vehicle Emissions and Effects

8 Tier 3 Detailed Assessment Process

The aim of a tier 3 assessment is to provide reasonably accurate estimates and a detailed assessment of the likely air quality impacts associated with a project. This is usually done through the use of detailed traffic information, emission factors, ambient air quality data and dispersion modelling. For any aspect of the assessment where detailed information is not available, it is appropriate to adopt the conservative assumptions discussed for tier 2 assessments.

A tier 3 assessment should be carried out by people who are expert in their field. This may necessitate input from a multidisciplinary team including experts in traffic, vehicle emissions and air quality. A tier 3 assessment should be undertaken for the current year and for future years with, and without, the proposal so that the effect of the proposal can be assessed. The future assessment years may depend on the availability of traffic demand models but should include a long-term forecast (at least 10 to 20 years).

This section of the guide provides an outline of the issues to be considered, and recommends good practice protocols for undertaking a tier 3 assessment. An overview of the tier 3 assessment process is provided in Figure 8-1.

8.1 Characterising the discharges to air

Characterising the discharges to air from a transport project typically includes:

• a detailed description of the proposal
• estimating the effect of the proposal on traffic
• estimating fleet composition

The following sections provide guidance on estimating and reporting traffic effects and emission factors for the purposes of an air quality assessment.

8.1.1 Description of the proposal

The description of the proposal should be sufficient to enable a full understanding of the proposal from an air discharge viewpoint, and should also provide sufficient information to ascertain whether any consents are required. The depth of information required will vary depending on the type of activity, but the following should generally be provided:

• a detailed site plan, including maps with all relevant features and the location of sensitive receptors
• a written summary of the project proposal focusing on aspects that give rise to emissions to air
• details of the alternatives considered and the reasons for their rejection
• details of any relevant historical information, including past changes to the activity
• details of any proposed changes to an existing activity
• any relevant timeframes or constraints for undertaking the activity
• any mitigation and/or preventive measures undertaken to manage discharges to air
• details of traffic data and emission factors, as discussed in the following sections.

8.1.2 Traffic data requirements

A key component of transport project assessment is the calculation of changes to traffic as a result of the project. Traffic and transport models provide traffic flows and speeds, which are used to estimate shifts and changes in pollutant loadings. Traffic and transport models are described in Appendix 2.

Traffic measurements or models used to determine traffic volumes and composition for air quality impact assessments should generally comply with the requirements of the Transfund Project Evaluation Manual (Transfund, 2004, available at www.ltsa.govt.nz/funding/manuals.html).

Traffic modelling results should be reported effectively and concisely in an air quality assessment report. The results need to be communicated in a way that can be understood by people who may not be experienced in interpreting modelling, and the results need to be relevant to the air quality impacts being assessed.

Documentation for the air quality assessment should include:

• a summary of the basis of the model, its validation, performance and forecasting
• a summary of how the area of influence was determined, to demonstrate that all roads affected by the proposal are being assessed
• sensitivity analysis for traffic speeds and traffic volumes, particularly model results, growth rates, and the assessment of diverted and induced traffic.

Traffic analysts need to be particularly aware of the need for conservatism in air quality assessments. In particular, traffic projections developed in accordance with the Project Evaluation Manual generally assume that projects do not induce new trips which may not always be the case. This is a common criticism of traffic projections produced for environmental assessments, and should be addressed in a tier 3 assessment. If appropriate, an allowance for induced traffic should be included in projections.

The assessment should be undertaken for the opening year, and for future years with, and without, the proposal. The future assessment years may depend on the availability of traffic demand models but should include a long-term forecast (for at least 10 to 20 years). Assumptions made in deriving projections should be clearly stated, including the basis for the assumed traffic growth rate and any induced traffic.

The error associated with current and predicted traffic volume and composition estimates should also be estimated and stated in the report.

The traffic data requirements will depend on the type of emission factor model being used. (The types of emission factor models are discussed further below.) However, most assessments will be based on NZTER. The following traffic information is generally required for a tier 3 assessment using NZTER:

• one-hour, eight-hour and 24-hour traffic flows on the links being evaluated (including confidence limits, where possible)
• LOS / average speed on each link
• vehicle class composition (if it is likely to be different to the default).

If detailed traffic data are not readily available, a tier 3 screening assessment could be based on adjusted annual average daily traffic (AADT) and worst-case congestion levels, as discussed for the tier 2 assessment.

It is critical that the assessor be absolutely clear about the basis and meaning of any traffic data within the confines of the assessment. Many traffic studies provide estimates of daily and peak-hour traffic for an average day, whereas air quality studies must estimate worst-case air quality. The main aim of an air quality assessment is to determine the effects of a roading proposal on air quality. The ambient air quality standards only allow between one and 24 hours of exceedance per year, depending on the pollutant. To assess whether these criteria are likely to be exceeded, traffic data for a "high traffic day" are needed.

Ideally, the assessment should estimate traffic flows and speeds on a "high traffic emissions" day and a "most likely" day. The high traffic emissions will be a day with high traffic flow and associated low speed / LOS. Where there are adequate data, confidence limits associated with the traffic estimates should be reported.

Analysts must use their judgement to define a high traffic emissions day. For instance, in some cases, the most appropriate 'day' will be an average one, in others it might be a particular weekday, and in yet others it may be a day of a special event (say peak traffic near a local stadium when a major event is occurring).

Average speed/level of service

Most emission factors (including NZTER) provide estimated average emissions in grams per kilometre (g/km) for a typical drive cycle. This means the emission factor represents average emissions from an average vehicle over a typical length of road. For example, at low speeds (or congested LOS), the drive cycle includes some allowance for stopping and starting, queuing at intersections, etc. Vehicle emissions are highly speed dependent, and most emission factor models require an estimate of average speed on each link.

NZTER emission factors are provided for three different LOS. LOS is a representation of traffic congestion, and includes:

• free − little or no vehicle impedance, with warm running (LOS A or B)
• interrupted − moderate vehicle interaction, with warm running (LOS C or D)
• congested − severe vehicle interactions such as traffic jams, with warm running (LOS E or F).

These LOS are described in terms of road type and average speed in section 8.1.3. NZTER emission factors provide estimated average emissions for a typical New Zealand drive cycle, including intersection delays. This means average speeds for each link should be determined from the total link travel time and intersection delay at the downstream end of the link. That is, if the traffic model explicitly represents intersection delay at the end of the link rather than as part of the link travel time, the downstream intersection delay needs to be added to the link travel time before calculating the level of service on the link.

For assessing air quality at a specific location (eg, a receptor close to an intersection), the emission factor should be selected based on the expected speed or LOS at that location, as opposed to the average for the link.

For some projects, much more detailed traffic information is available. Microsimulation traffic models represent the travel behaviour of individual vehicles, and with an appropriate emissions model, can provide much more accurate estimates of emissions from a transport corridor. This is discussed further in section 8.1.3 (microsimulation of emissions).

Vehicle fleet composition

Vehicle fleet composition is an important parameter in air quality assessments because of the high degree of variation in emissions from different sizes and types of vehicles, especially for particulates. The health effects of air pollution are dominated by particulates, and particulate emissions from transport are dominated by heavy commercial vehicles (HCVs).

Traffic composition can be estimated from traffic surveys, traffic models, or from vehicle size classification information associated with automated traffic counts. Wherever possible, site-specific data, or information from nearby locations, should be used to estimate the proportion of HCVs. Vehicle size classification information may be available from territorial local authorities (for local roads), Transit NZ (for state highways), or the Ministry of Transport (for national/regional estimates).

There are a number of vehicle classification systems in use in New Zealand, and, unfortunately, there is limited consistency across these. The vehicle classification systems commonly used in New Zealand are summarised in Appendix 2.

Site-specific data should be estimated for any projects where the proportion of HCVs is expected to be significantly higher than the default values provided in Table 8-1 (eg, in busways, port access roads and quarry access roads).

Table 8-1: Percentage of VKT, by vehicle class [Percentages are based on vehicle kilometres travelled by vehicle class in the VKT Results worksheet of the Vehicle Fleet Model fuel hub (NZ DOT Fuel Hub C, which includes fleet information to 2002). VKT for all petrol HCV and buses have been added to petrol LCVs; VKT for light diesel buses have been added to LCVs; and VKT for small diesel buses have been added to HCV Small (because these classes are not included in NZTER).] (VFM) for New Zealand

Notes: VKT = vehicle kilometres travelled; VFM = Vehicle Fleet Model; LCV = light commercial vehicle; HCV = heavy commercial vehicle.

Where relevant size classification or other composition data are available, these should be used to adjust the national average default values provided in Table 8-1. The most conservative approach assumes the highest proportion of heavy commercial vehicles based on either local information or the default data. Where the estimated proportion of heavy commercial vehicles (or buses) is higher than the default, the most conservative way to adjust data would be to simply reduce the proportion of light-duty vehicles by the corresponding amount.

For urban areas, the regional council will generally have information on the amount of bus travel associated with public transport. However, these figures generally will not include private coaches, so some care would be needed in estimating the proportion of buses from these figures.

The Ministry of Transport Vehicle Fleet Model (VFM) provides estimated vehicle kilometres travelled, by vehicle class. The estimates are based on registration data, including odometer information. The basis of the model, including projections, is fully documented in The New Zealand Vehicle Fleet Emissions Model (Ministry of Transport, 1998c). Table 8-1 shows the estimated proportion of VKT by vehicle class from the VFM for 2004, 2011 and 2021.

Where site-specific or local data are not available, VFM data should be used to provide default fleet composition data. The Transfund Project Evaluation Manual data may then be used to adjust the VFM data for different road types, and time periods, if appropriate. The Project Evaluation Manual provides traffic composition data for different road types but does not include projections and does not differentiate petrol and diesel vehicles.

The Research Unit of Land Transport New Zealand (formerly LTSA) plans to report national estimates of vehicle kilometres travelled by vehicle type on a regular basis. Any updated national estimates should be used to provide default data as they become available.

The Motor Vehicle Register is another source of data that can provide regional vehicle classification information. However, care must be taken when using vehicle classification data to ensure the proportions are adjusted to reflect utilisation. Commercial vehicles tend to travel higher kilometres than cars, so it is generally not valid to assume that the proportion of vehicle kilometres travelled by vehicle class is the same as the proportion of vehicles in each class.

8.1.3 Emission factors

Emission factors provide an estimate of emissions from individual vehicles. When combined with traffic information, they are used to estimate discharges of contaminants from roads as follows:

Emission rate = Σ_v Σ_r Σ_d Σ_p (VKT_v,r,d,p x emission factor_v,r,d,p)

where: v = vehicle type, including fuel type

r = road type

d = driving conditions

p = emission process (exhaust, evaporation or tyre wear).

Emission rates should be calculated using emission factors determined for the New Zealand fleet. The Vehicle Fleet Model and associated NZTER are currently the most readily available emissions information sources for the New Zealand fleet.

Using NZTER exhaust emission factors

The NZTER includes emission factors dependent on road type, LOS and vehicle class. The emission factors provide average emissions in g/km for a typical drive cycle for the type of road and LOS selected. Descriptions of the road types are as follows.

• Central urban: routes with a combination of one-block links, essentially all with signalised intersections, an approximate minimum of six per kilometre; a maximum speed limit of 50 km/h.
• Motorway: a multi-lane divided freeway without intersections but with the frequency of on/off ramps reflecting a routing through an urban zone; maximum speed limit of 100 km/h.
• Suburban: a mixed route representing daily commuter / local trip traffic (outside of the CBD) with a high frequency of intersections, mainly uncontrolled and relying on queuing and gap acceptance to change or join traffic flows; a maximum speed limit of 50 km/h.
• Rural highway: routes in rural areas [The distinction between urban and rural roads is that made in the annual Roading Statistics, published by Transit NZ, which distinguishes state highways from roads controlled by territorial local authorities.] with uncontrolled intersections, with overtaking dependent on oncoming traffic; maximum speed limit of 100 km/h.

LOS are described as follows.

• Free flow: little or no vehicle impedance with warm running; LOS level A/B, defined as having speed ≥ 80 km/h on motorways and ≥ 45 km/h on central urban and suburban roads.
• Interrupted: moderate vehicle interaction with warm running; LOS level C/D, defined as 67 km/h ≤ speed < 80 km/h on motorways and 25 km/h ≤ speed < 45 km/h on central urban and suburban roads.
• Congested: severe vehicle interactions such as traffic jams, with warm running; LOS level E/F, defined as speed < 67 km/h on motorways and < 25 km/h on central urban and suburban roads.
• Cold start: this is not a congestion level. Cold start describes the emissions from vehicles that have not warmed up. This can be assumed to be the first three minutes of any trip. In urban areas it is conservative to assume that 20 percent of vehicles are operating under cold-start conditions.

Fleet-weighted NZTER emission factors for the default vehicle class composition defined above are provided for the tier 2 assessment procedure. These fleet-weighted emission factors are appropriate for a tier 3 assessment unless better information is available, or the vehicle class composition is expected to be different to the default.

Issues relating to the use of NZTER in effects assessment

Users have raised a number of concerns regarding the use of NZTER for assessing air quality impacts. These are documented in section 3.2.1 of the Good Practice Guide to Atmospheric Dispersion Modelling (Ministry for the Environment, 2004). Updated emission factors are being developed, but until these become available NZTER is the recommended tool. Alternative emission factors are discussed below.

Emissions calculated using NZTER have been compared to emissions calculated using Australian emission factors (Auckland Regional Council, 2005a). This analysis shows that Australian emission factors result in significantly lower emissions estimates, particularly for future years. However, this analysis does give some confidence that NZTER emission factors are conservative.

Non-exhaust emission factors

The NZTER database does not include non-exhaust emission factors. However, tyre wear, brake wear and evaporative VOC emission factors have been developed for the Auckland Regional Council emissions inventory based on fleet information from the New Zealand Vehicle Fleet Model (Auckland Regional Council, 2005b).

VOC evaporative emission factors

Volatile organic compound (VOC) emission factors may be required for assessments of airshed air quality impacts (see section 8.4.3), or for an assessment of local impacts that includes consideration of one or more VOCs (eg, benzene).

Evaporative emissions are highly variable. The emission factors provided take into account some of the main variables involved, and provide an indication of relative emissions from petrol vehicles. Diesel vehicles are often not considered, because their evaporative emissions are small compared with petrol vehicles (in the order of 0.2 g/km). The emission factors are summarised in Table 8-2.

The evaporative VOC emission factors for petrol vehicles are expected to decrease over time due to reduced petrol vapour pressure and improved vehicle technology. Key assumptions are:

• the evaporative emissions from vehicles with no control technology are in the range of three to six g/km
• the evaporative emissions from vehicles with control technology are less than 0.08 g/km
• the maximum vapour pressure for summer grade petrol of 85 kPa reducing to 65 kPa in 2006
• the percentage of vehicles in the fleet with evaporative emissions control is predicted to be:
  • none in 1993
  • five percent by 1998
  • 55 percent by 2011
  • 100 percent by 2021.

Table 8-2: Evaporative VOC emissions

* HCVs and buses were assumed to have the same evaporative VOC emissions as LCVs. HCV = heavy commercial vehicle; LCV = light commercial vehicle.

Source: Auckland Regional Council, 2005a

Tyre-wear and brake-wear emission factors

Tyre-wear and brake-wear emission factors have been derived from Ministry of Transport studies on potential water contamination from road transport. These emission factors for PM₁₀ assume that 15 percent of tyre-wear particulate emissions are PM₁₀ and 40 percent of brake-wear particulate emissions are PM₁₀. These emission factors are similar to those used internationally. However, there is a great deal of uncertainty about tyre- and brake-wear emissions, and the factors are based on very few measurements. Tables 8-3 and 8-4 show the emission factors.

Table 8-3: Tyre wear PM₁₀ emission factors

Notes (Tables 8-3 and 8-4): LCV = light commercial vehicle; HCV = heavy commercial vehicle.

Source: Auckland Regional Council, 2005a

Table 8-4: Brake wear PM₁₀ emission factors

Source: Auckland Regional Council, 2005a.

Previously, brake- and tyre-wear emissions have not generally been included in assessing transport effects, mainly due to the lack of data on these factors. For future tier 3 assessments, it is recommended they be considered, since for busy roads these can be a significant source of PM₁₀. However, due to the high level of uncertainty associated with these emission factors, it is recommended that sensitivity analysis be undertaken.

A recent review by the UK Department for Environment, Food and Rural Affairs (Air Quality Expert Group, 2004) suggested actual tyre-wear emission factors could be anywhere between 10 percent and 1,000 percent of published results. In New Zealand, analysis has been undertaken to attempt to quantify non-tailpipe PM₁₀ (Kuschel and Bluett, 2002). This analysis found that dispersion modelling results, based on NZTER exhaust PM₁₀ emission factors, correlated reasonably well with measured PM₁₀. Although further work is required, this analysis suggests that non-exhaust PM₁₀ emission factors are not significant compared to exhaust emissions. For the purposes of sensitivity analysis, it should be assumed that non-tailpipe emission factors are between 10 percent and 200 percent of the values quoted above.

Benzene emission factors

Benzene emission factors for petrol and diesel vehicles have been estimated (see Appendix 1) using the Australian National Pollutant Inventory (Environment Australia, 2000a). It is assumed evaporative emissions from diesel vehicles are negligible. Recommended benzene emission factors are provided in Table 8-5.

Table 8-5: Benzene emission factors

Rail emission factors

The Ministry of Transport has developed a spreadsheet for calculating emission rates from the New Zealand rail fleet based on the locomotives used and the tracks that travel throughout the country. The publication, Impacts of Rail Transport on Local Air Quality (Ministry of Transport, 1999) and accompanying database provides data and information on the calculations and emission factors.

The emission factors are based on USEPA data for rail-sector emissions inventories. The Ministry of Transport spreadsheet should be used for determining emissions from rail, but the user needs to be aware any new or upgraded fleet may differ from that defined in the spreadsheet.

Bus emission factors

The Auckland Regional Council has developed a Bus Emissions Prediction Model (BEPM) (Auckland Regional Council, 2005b). This model is based on overseas emissions databases, and allows the user to define:

• average speed
• fleet profile (percentage of each vehicle type by country of origin, technology, year of manufacture)
• fuel (sulphur content, biodiesel, water-blend fuel)
• percentage retrofit of diesel-oxidising catalysts or particle traps.

The BEPM provides fleet average-emission factors for the defined fleet and average speed, and allows the user to compare scenarios.

Alternatives to NZTER emission factors

Auckland Regional Council is developing a model similar to the BEPM for other vehicle classes. This will enable updated emission factors to be developed for the New Zealand fleet. In the meantime, it is possible to estimate emission factors based on reported overseas databases and New Zealand fleet information. This will mean the assumptions and errors associated with the emission factors are well understood.

However, it is important that fleet composite emission factors from overseas are not used. The New Zealand fleet has much higher fleet average emissions than most comparable countries (like Australia) because of the delayed introduction of vehicle emissions standards in New Zealand. This means any emission factors must be based on detailed New Zealand (or local) fleet information, including the proportion of vehicles by class, and emissions build standard (or year of manufacture and country of origin). This information is available from the Ministry of Transport Vehicle Fleet Model.

Estimation of emission factors should be undertaken by professionals with specific vehicle emissions expertise. The BEPM is an example of how overseas emissions databases can be used to predict emissions from the New Zealand (in this case, bus) fleet.

Intersections and idle emissions

As discussed above, most emission factors (including NZTER) provide an estimate of emissions for a typical drive cycle. For example, for the congested level of service, the drive cycle includes some allowance for stopping and starting, idling at intersections, etc. This effect is also implicitly considered in most speed-related emission factors (like BEPM), since the variability of speed during a trip is closely related to the average speed. Slow-speed journeys in towns involve frequent speed changes in response to the traffic conditions, while higher-speed trips are normally driven more smoothly (National Roads Authority and DEFRA, 1992/2003). Nevertheless, for two trips at the same average speed (or for the same LOS/road combination in NZTER), emissions can vary substantially depending on speed variability.

This effect is not usually significant over the averaging times being considered. For an air quality assessment, average emissions over an hour or longer are needed, so an emission factor for an average drive cycle is generally appropriate.

However, emissions at locations such as intersections may give cause for concern because of the high proportion of vehicles idling and accelerating. To address this, the congested/central urban emission factors from NZTER should be used. This will provide a reasonably good representation of emissions around intersections, because it includes a high proportion of idling and acceleration/deceleration. Similarly, a speed-dependent emission factor for low average speed (say 10 km/h) should be reasonably representative of average emissions around intersections.

Microsimulation of emissions

In circumstances where more detail about the variability of emission factors is required, microsimulation of emissions can be undertaken. The use of microsimulation traffic models, which represent the travel behaviour of individual vehicles, is becoming more common in New Zealand. Many of these models provide for microsimulation of emissions, but at the time of writing these have not been calibrated for the New Zealand fleet.

The accuracy of any assessment based on microsimulation of emissions is likely to be limited by the availability and accuracy of local fleet information, and background air quality and meteorological data. As such, microsimulation of emissions should only be used in special circumstances, and then only with detailed justification. For an air quality assessment, average emissions over an hour or longer are needed, so an emission factor for an average drive cycle is generally appropriate.

As for any development of emission factors, this should only be undertaken by professionals with specific vehicle emissions expertise.

8.2 Characterising the receiving environment

8.2.1 Existing air quality and meteorological data

To assess the cumulative effect of any proposal on air quality, the predicted traffic-derived concentration of air pollutants must be added to existing air quality, including concentrations discharged by other sources.

Existing air quality should be considered in all assessments of discharges to air. The level of detail and accuracy required is influenced by:

• the anticipated air quality - areas anticipated to have poor air quality due to a combination of existing emission sources and/or adverse terrain or meteorology would require a more robust definition of the existing air quality
• the sensitivity of the receiving environment - where discharges have the potential to affect highly sensitive receiving environments, existing air quality would be expected to be well defined. Facilities where there are likely to be sensitive subgroups (the young, old, sick), such as schools and hospitals, should be identified and considered.

It is the combination of these considerations that determines the extent to which existing air quality should be addressed. A small increase in emissions within a commercial/light industrial area, for example, might only require a qualitative statement on existing air quality, which identifies the reasons existing air quality is anticipated to be good. Conversely, a large-scale transport development with the potential to affect residential suburbs might be expected to provide good-quality, representative and quantitative air quality data.

Using pre-existing air quality data

Pre-existing air quality data can be obtained from a range of sources. Usually, the consenting authority will have the best knowledge of the full range of data available within its region. The consenting authority will also be able to provide an opinion on whether the pre-existing data are sufficient for the assessment proposed. The range of air quality data sources is identified in section 6.4.1 of the Ministry for the Environment's Good Practice Guide to Atmospheric Dispersion Modelling (Ministry for the Environment 2004).

Before using pre-existing air quality data in an assessment, it is important to audit the monitoring technique and protocols (and document the results of the audit for inclusion in the assessment) to demonstrate that the existing air quality data are of appropriate quality. Methods should be audited against the requirements of the Standards and the Good Practice Guide for Air Quality Monitoring and Data Management (Ministry for the Environment, 2000).

The location of a monitoring site and the time of the monitoring also affect how representative existing air quality data might be. The site should be representative in terms of location, ideally within the affected airshed, but also representative in terms of land use, physical setting, etc. The specific location of the monitoring site (eg, its proximity to major sources such as roads) will also be important.

The time of the monitoring is also relevant, in that data collected at the site in previous years may not be representative if the character of the area has changed markedly since monitoring was last undertaken. For example, historical data from a roadside monitoring site in an area that has experienced significant traffic growth would no longer be representative of current levels.

Trends in air quality should be considered, and it is preferable for several years of data to be analysed so that any improvement or deterioration of the air quality of an area can be ascertained. As a minimum, one year of data could be used if there are other longer-term monitoring sites in similar locations which can be used to provide an indication of long-term trends. Ideally, 10 years of data are required to determine trends.

As identified above, monitoring data should be reviewed with reference to techniques identified in Schedule 2 of the Standards and other Ministry for the Environment guidance (Ministry for the Environment, 2000, 2002, and 2004).

When local existing air quality data are not available

Section 6.4 of the Good Practice Guide to Atmospheric Dispersion Modelling (Ministry for the Environment, 2004) includes options for estimating existing air quality (without project) when local data are not available. These options include:

• comparing the location with somewhere similar
• making a worst-case assumption
• modelling other sources in the area
• starting a new monitoring programme.

The most straightforward options are to compare the location with somewhere similar or make a worst-case assumption.If the area does not have significant large sources, and does not have any complex geographical or meteorological features, then it can be assumed that the air quality will be similar to another area of similar population density, emission sources and meteorology. This method requires that such an area can be identified and that monitoring data are available.

In the absence of air quality data from local or similar areas, it might be necessary to simply estimate the existing air quality. The safest guess is to assume a concentration at the upper end of what might be feasible.

The most conservative (and straightforward) approach to estimating existing air quality without the project is to make worst-case assumptions, as outlined in Figure 8-2 below. This approach is very conservative, and a health risk assessment will be required if this results in a prediction of unacceptable air quality effects.

Some examples of worst-case assumptions are outlined in Table 8-6 below. It is important to ensure that the "existing air quality without project" concentration selected is appropriate and relevant to the location of the proposed project. For example, to avoid double counting, it is important to select existing air quality data from an area that is not influenced by traffic, if the assessment includes dispersion modelling to predict the impact of any existing and proposed traffic from the proposal.

Table 8-6: Examples of existing NO₂, PM₁₀ and CO concentration "without project"

For significant projects, where the issue is likely to be of importance, it is recommended that an air quality monitoring programme be undertaken when local data are not available. Monitoring should determine concentrations of the critical indicator contaminants (generally CO, NOx and PM₁₀, and possibly benzene) as well as meteorology, and traffic counts where appropriate. Comprehensive guidance on setting up ambient air quality monitoring stations is provided in the Guide to Air Quality Monitoring and Data Management (Ministry for the Environment, 2000).

There are two general categories of monitoring site that can be used for background monitoring of ambient air quality concentrations for transport developments.

• Receptor monitoring sites: a monitoring station can be established in the grounds of a receptor located within the potential zone of influence of the proposed project. The aim of this monitoring is to measure the background or baseline concentrations of selected contaminants so that the impact of the project on that specific receptor can be determined by ongoing monitoring at the same site after the project has been established. It may be suitable to select a particularly sensitive receptor for this type of site, such as a school, residential dwelling or area where concerns have been raised during a submission process.
• Representative monitoring sites: these sites are usually located in the area a proposed development will go through, where the aim is to obtain a representative measure of the background ambient air concentrations over most of the area of concern.

Site-specific background monitoring should be undertaken over a sufficient period to obtain representative data. The assessor should justify any monitoring period that is less than 12 months.

8.2.2 The built environment

Sensitivity to air quality impacts will vary with land-use type. For example, residential land use (including schools) will typically have greater sensitivity than an industrial setting.

The land use surrounding a proposed development should be reviewed and described in any assessment of air quality impacts. Any facilities where there are likely to be sensitive groups of people (young, old, elderly), such as hospitals and schools, should be identified. The review will provide both an indication to any developer of the likely acceptability of, or objection to, a proposal and provide a guide to the depth of consultation required. The sensitivity will also be one factor which influences the level of Assessment of Environmental Effects required for a proposed development.

Conversely, when considering changes to land use in areas surrounding transport corridors, "reverse sensitivity" should be considered. The separation distance between transport corridors and sensitive receiving environments should be maintained for the duration of the corridor. Maintaining the existing separation distance should be a consideration in any notice of requirement for new corridors.

8.3 Exposure estimates

8.3.1 Dispersion modelling

Atmospheric dispersion models are used to estimate contaminant concentrations downwind of a discharge source. The information generated by dispersion models can be used in a number of ways, including to:

• assess the potential adverse effects of proposed activities or changes to existing activities − dispersion modelling is usually the only way to assess the potential effects of an activity that has not yet been constructed
• predict the effects of changes in emission rates or parameters over time (eg, change in traffic flows)
• estimate the influence of factors such as terrain, buildings and meteorology on an activity and their effect on the dispersion of the contaminants discharged by the activity
• estimate the effect of any mitigation options.

Local and community effects will need to be assessed near the roads by atmospheric dispersion modelling (using a "near-road" model). In New Zealand, the most common dispersion model used for this type of assessment is CALINE4.

The Good Practice Guide to Atmospheric Dispersion Modelling (Ministry for the Environment, 2004) gives extensive guidance on dispersion models, including those used for transport assessments (Ministry for the Environment, 2004). They include Gaussian line source models such as CALINE4, and models that can model line sources or account for regional airshed dispersion and secondary reactions, such as CALPUFF/CALGRID and TAPM. All dispersion modelling should be carried out in accordance with the recommendations of the Good Practice Guide for Atmospheric Dispersion Modelling.

8.4 Assessing the effects

8.4.1 How to incorporate background data

Once background air quality data and model results are available, adding together background peak and predicted peak concentrations provides a conservative estimate of the cumulative impact of the discharge. This conservative approach is recommended as a first step. However, if this approach predicts a breach of assessment criteria due to high background concentrations, a more robust assessment may be necessary.

Adding background and predicted concentrations can result in overestimates due to spatial and time co-incidence problems. Careful examination of the locations and conditions under which measured and modelled peaks occur, may help determine whether the peaks are likely to occur at the same time and place. Any alternative to adding peak background and peak predicted concentrations should be fully explained and justified.

8.4.2 Assessment of local effects

It is generally sufficient to assess health effects by comparing model predictions with appropriate health assessment criteria. This primarily consists of the ambient air quality standards, ambient air quality guidelines and regional air quality targets.

As discussed in section 3.1, transport activities have the potential to discharge a large number of different contaminants. However, unless there are special circumstances (such as elevated background concentrations of another compound), most assessments will provide adequate coverage of all potential effects if based on CO, PM₁₀ and NO₂. As we have seen, these three do not explicitly cover a range of other toxics, in particular carcinogenic compounds such as benzene and 1,3 butadiene. The concentrations and effects of these other compounds are still being researched, but preliminary results (from the New Zealand research under the Health and Air pollution in New Zealand programme - further details at www.hapinz.org.nz) suggest the overall health effects are substantially less than those due to CO, PM₁₀ and NO₂. In other words, unless there are very specific local circumstances, transport proposals that result in acceptable effects for CO, PM₁₀ and NO₂ will also have acceptable effects for other toxics. (Note that this is subject to research results that may appear subsequent to the publication of this document).

However, elevated levels of benzene have been measured in some urban areas of New Zealand (Ministry for the Environment, 2003c), and an exception to the above rule of thumb may need to be applied for benzene. Thus, it is recommended an assessment of the effects of benzene be considered for any tier 3 assessments in locations where elevated levels are known or considered likely. Consultation with the regional council should clarify the level of assessment required.

8.4.3 Assessment of airshed effects

The tier 3 assessment procedure has so far focused on the assessment of local effects. For projects that are likely to significantly increase total emissions, it is recommended the assessment include an estimate of the likely cost of health effects (as detailed in section 9).

In some circumstances, an assessment of air quality impacts across the airshed may also be required. In this context, an airshed is defined as an area or region defined by settlement patterns or geology that results in discrete atmospheric conditions. This may not be the same as the NES airsheds used by regional councils for air quality management, although in most cases, the two will be similar.

Airshed assessments will be more commonly used for policy development. However, a very large scheme or transport strategy may require an assessment of airshed effects if there is likely to be a significant increase in emissions. This could involve working with regional council air quality staff to revise the regional emissions inventory. Urban airshed modelling may also be necessary to assess photochemical smog or other regional-scale impacts. Figure 8-3 illustrates the process for modelling air quality impacts across an airshed.

In cases where a significant net increase in emissions is expected, early consultation with the regional council is recommended to determine whether an assessment of regional effects is required.

Some general guidance on assessing the regional effects of transport projects is provided in the Guidelines for Conducting Air Quality Studies AP R17 (Austroads, 2000). Further guidance on emission inventories is provided in the Good Practice Guide for Preparing Emissions Inventories (Ministry for the Environment, 2001), and the Good Practice Guide to Atmospheric Dispersion Modelling (Ministry for the Environment 2004) provides some guidance on urban airshed modelling.

8.5 When a health risk assessment is required

In special circumstances, it may be necessary to undertake a more comprehensive air pollution health risk assessment as part of a detailed study. For example, this may be required when the predicted effects exceed ambient air quality criteria, and decision-makers require more specific information about the likely health effects of the breach.

An air pollution health risk assessment would include determining exposure and dose via a number of different pathways (inhalation, dermal, ingestion, etc), assessment of dose-response data, and characterisation of health risks from the exposure/dose assessments.

The ambient air quality standards are health-based standards, which are intended to provide a guaranteed level of protection for the health of all New Zealanders. In most circumstances, it is appropriate to assess the potential health effects of discharges to air from transport by comparing model predictions with the ambient air quality standards, any regional council assessment criteria, and (where appropriate) the Ambient Air Quality Guidelines. Typically, it is only when ambient air quality guidelines or standards are exceeded that an air pollution health risk assessment is required.

Health risk assessments are very specialised tasks, and are often designed to account for very specific local concerns. This section describes some of the issues that might be encountered, but it is recommended that additional expert assistance be sought for any full health risk assessment.

8.5.1 What is risk assessment?

Risk assessment is the process of estimating the potential impact of a chemical, physical, microbiological or psychological hazard on a specified human population or ecological system under a specific set of conditions and for a certain timeframe (eg, EnHealth Council, 2002).

It is a scientific process for evaluating exposure to an agent, and the likely effects of this exposure. Consideration is given to the population potentially exposed, the method of exposure, the dose received and the toxicological effects of such an exposure. Through the risk assessment process, information may be provided to policy makers and managers to help make decisions on the management of human health and environmental risks. Quantitative health risk assessments are highly technical and complex studies, and should be undertaken by qualified professionals with experience in this specialised field.

For air exposures, health risk assessment is the backbone of the process used to derive ambient air quality standards and goals, and for plant design limits used throughout the world. The ambient air quality goals are usually based on conservative assumptions (eg, lifetime exposure), and sometimes take into consideration sensitive receptors such as children and the elderly. For particular chemicals, ecological considerations may be more stringent than human health, such as in the case of fluoride emissions or some organochlorine compounds such as DDT. Consideration is also given to the scale of exposure, as ambient air quality goals apply to large populations (eg, entire cities).

It should be able to adequately address most assessments using air dispersion modelling and comparison with appropriate ambient air criteria. There are, however, a number of situations where a site-specific risk assessment may be required. These are discussed in the following sections.

8.5.2 Criteria exceeded or nearly exceeded

Comparing ground-level concentrations with ambient air quality criteria would usually precede any formal site-specific risk assessment, and usually becomes the basis for triggering this course of action. If the maximum, cumulative (ie, including background), predicted ground-level pollutant concentration exceeds or nearly exceeds (say 80 percent of) a guideline value, then consideration should be given to conducting a site-specific health risk assessment.

There are a number of reasons and considerations for conducting a site-specific risk assessment. These are outlined as follows.

Exposure averaging time

When modelling the dispersion of air pollutants, it is important the appropriate averaging time be used to match the averaging time for toxicity and people's likely exposure. If toxicity is associated with long-term chronic exposure, then an annual average concentration should be used to estimate health risk. If the toxic effects occur only at times of the day when people are not present, then this should be considered in the total risk exposure assessment.

Sensitivity analysis

There is uncertainty in any risk assessment and dispersion modelling. Evaluation of uncertainty by examining the sensitivity of key parameters is important in risk assessment. By varying modelling and risk assessment parameters, additional information can be obtained on the sensitivity of the risk assessment results to these factors.

Multiple chemical exposure

Most guideline values are based on the assumption that exposure to a chemical is independent of any other chemical exposure, but this is not always true. Cumulative effects may occur between chemicals that exhibit similar toxicological effects on target human organs. In addition, incremental cancer risk is usually added for all non-threshold (cancer-causing) chemicals, for all exposure pathways. In order to determine whether multiple chemical exposure is a potential issue, the individual percentage exceedances can be totalled to determine a hazard index. For example, if the ground-level concentration of one chemical was 60 percent of the guideline value and another chemical was 70 percent of its guideline value, then individually both chemicals satisfy the requirements for compliance, but combined they exceed it with a total of 130 percent. A risk assessment may therefore be required to evaluate the health endpoints of these chemicals to determine if cumulative effects are likely to be significant.

Unlisted chemicals

Ambient air quality guidelines usually cover fairly comprehensive lists of chemicals, but compared to the hundreds of thousands of known chemicals in common use the list is quite small. Ambient air criteria have been derived for the most well-known air pollutants associated with transport emissions, but if an air quality assessment is required to assess a chemical for which there are no criteria, a risk assessment approach may be used either to estimate risks from a particular exposure scenario, or to derive an acceptable ambient air concentration for that chemical.

Change of default exposure assumptions

Design criteria are usually based on the most conservative assumptions to protect the majority of the general population, including the sick and young children. Exposure is usually assumed to occur for 24 hours per day, 365 days per year for 70 years (ie, a continuous lifetime exposure). This is usually the requirement where emissions impact on a residential neighbourhood.

In commercial and industrial areas, however, long-term exposure usually does not occur to children. Likewise, exposure to an individual usually does not occur for 24 hours per day, every day. Through the use of risk assessment it can be shown the risk posed by emissions is generally less to commercial/industrial workers than to residents and children. Hence, in some situations, it may be possible to allow ground-level concentrations greater than the ambient air criteria in these regions. Risk assessment may be used to derive these alternative criteria.

Care should be taken that the toxicity endpoint is appropriately selected. Air quality criteria for chemicals based on acute (short-term) exposure impacts cannot be modified in this way.

Exposure duration and non-threshold chemicals

When assessing exposure to emissions it is important to consider the time basis of the guideline values. If the dominating consideration is toxicity, then exposure duration becomes an important consideration, particularly for non-threshold chemicals. Non-threshold (also known as carcinogenic) chemicals are potential cancer-causing agents that have been assumed to have no safe threshold to presenting a potential health risk.

The non-threshold model of toxicity assumes linearity between the lowest, experimentally derived dose response and the zero dose. This implies there is a calculable probability of an adverse health risk no matter how small the dose. The toxicity criteria for such chemicals are represented by slope factors or the inhalation unit risk. For a particular dose, the incremental lifetime cancer risk can be calculated, and compared with predefined goals for acceptable risk.

In New Zealand, an acceptable environmental risk for exposure to environmental pollution of one in 100,000 has been adopted by the Ministry for the Environment in a range of guidelines for the management of contaminated land, most recently in the Oil Industry Guidelines (Ministry for the Environment, 1999).

The significance of incremental cancer risk is that it is averaged over a lifetime. Conservative ambient air quality goals assume a lifetime of exposure (70 years by convention). However, if exposure is expected to be of shorter duration, then the incremental cancer risk will be less than the default 70-year exposure scenario.

Generally, transport infrastructure must be assumed to be operating for 70 years to be conservative, because there is no way to know the real operational duration of project. However, there are some circumstances where shorter duration is known.

Particulate deposition

Particulate deposition, by itself, is generally not a major concern except for the amenity impacts associated with dust deposition. However, non-volatile toxic chemicals can be emitted in the form of particulate matter or adsorbed on the surface of particulate matter. Particles smaller than 10 µm diameter may be inhaled and trapped within the respiratory system. Guideline values for ground-level pollutant concentrations are usually based on inhalation exposure only. However, if the emission is primarily in particulate form, then accumulation of contaminants in soil occurs over time, and exposure from other pathways is then possible (eg, lead particulate deposited on soil and then absorbed by vegetables).

A site-specific risk assessment may be required if it is determined that accumulation of a toxicant in soil could potentially become high enough to pose a health risk to the occupants of the premises. In such situations, the exposure needs to consider not only the inhalation pathway but also ingestion and even dermal contact with contaminated soil.

Where it is known that home-grown produce is consumed, contaminant uptake and produce ingestion need to be considered. Special consideration also needs to be given if the location is a primary production site for food - such as milking cows or farm crops - because there are strict guidelines with respect to residual contamination in food products (Australia and New Zealand Food Standards Code, July 2001).

To determine if there is a potential issue with respect to particulate deposition, soil chemical criteria can be used as an indicator of potential risks. Using dispersion modelling techniques, it is possible to estimate the mass of the chemical deposited in a particular location over a lifetime (ie, 70 years). By assuming a soil-mixing depth (say 5 cm), a soil concentration can be estimated, which may then be compared to national or international soil criteria. If the resulting soil concentration is within 10 percent of the soil criterion for residential land use, then this is considered significant enough to warrant a site-specific risk assessment. A site-specific risk assessment should also be conducted for special circumstances, such as deposition on crop production.

Things to consider in the risk assessment are particulate size distribution and the locations of greatest deposition. If the particulate is primarily fine fractions then inhalation would be potentially of greatest concern, whereas if particulates are coarse then inhalation risks would be less significant because only small particles are likely to be inhaled and the potential accumulation of chemicals in soil might be more significant. Both degradation and bioaccumulation of chemicals also need consideration in the risk assessment.

Health risk assessments are very specialised tasks, and are often designed to account for very specific local concerns. Generic approaches, or recommended methodologies, are beyond the scope of this good practice guide.

8.6 Accuracy

The Good Practice Guide for Atmospheric Dispersion Modelling (Ministry for the Environment, 2004) includes guidance on accounting for, and reporting of, model error and uncertainty. This includes consideration of source characteristics, meteorological data, terrain, model performance and the misapplication of models.

Careful consideration of accuracy is especially important in transport assessments, which usually rely on models to estimate traffic and vehicle emission factors, as well as dispersion. With three or more levels of modelling there is plenty of room for error and − perhaps more importantly − mistrust of the results. It is important errors and uncertainty be considered throughout the assessment, and that the report clearly demonstrates this.

Ideally, the uncertainty associated with each aspect of the assessment should be estimated and stated. Where this is not possible, sensitivity analysis should be carried out. The results of the sensitivity analysis could be used to present a "worst-case" estimate, and a "most likely" estimate of the effects. For example, a "worst-case" estimate might be based on unusually high traffic levels, high emission factors, a high proportion of heavy commercial vehicles, high background concentrations and poor meteorological conditions. In reality, it is unlikely that all of these variables will be "worst-case" at the same time, so a more realistic "most likely" scenario is also recommended.

8.7 Reporting a tier 3 assessment

The results of a tier 3 assessment should be documented for inclusion into any AEE. The report should summarise the findings of the assessment, including the basis of the traffic information, air quality information, any assumptions and their justification. Section 4.5 describes the recommended content of an assessment report. The size and nature of the report will depend on the project, but it is anticipated that for any tier 3 assessments each of the sections described will be included.