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Appendix 1: Calculations and Data

A1.1 Method for estimating concentrations

Atmospheric dispersion modelling has previously been used to determine dispersion curves for New Zealand conditions (Scoggins et al, 2004; Bluett and Fisher, 2005). As part of this project the curves have been normalised for emissions factors and number of vehicles to provide an estimate of concentration per g/km of emissions as a function of distance from the roadside. To determine concentration, the road emissions are estimated based on the number of vehicles (for the relevant averaging period) and the fleet-weighted emissions factor. There are a number of assumptions and simplifications that need to be made, all described here.

None of these calculations account for existing or background concentrations. These must be added if a cumulative assessment is required. The method only applies the effects due to the transport corridor under consideration. This is relatively straightforward for CO, but can become more complex for NO2 and PM10 because of atmospheric chemistry processes which depend on background concentrations that may not be known.

The dispersion curves for all other gaseous pollutants (here mainly NO2 and PM10, but also any others that may be needed) are held to be equivalent to the CO dispersion curves. This is a simplified approach because the dispersion curves for each pollutant are not identical, due not only to chemical processes but also to subtle differences in dispersion and deposition. However, it is argued that the differences are not great, and that the CO dispersion is a reasonable representation for the other pollutants over the distances and times scales of interest. This is also the methodology followed by Austroads in Australia (see, for example, Austroads, 2004) and DEFRA in the UK (National Roads Authority and DEFRA, 1992/2003).

All measurements in this document are taken from the edge of the driving lane (some methods take the measurements from the road centre line).

A1.2 Dispersion curve basics

The basic dispersion curve is derived from the modelling and experimental measurement of CO. The one-hour dispersion curve for CO was developed based on measured roadside concentrations at an Auckland monitoring site. To determine how the CO concentration varied with distance from the carriageway, CALINE4 was used (eg, Scoggins et al, 2004). NZTER emissions factors were used to estimate emissions. Using a best-fit algorithm, the estimated variation of maximum predicted one-hour concentration with distance from the carriageway can be modelled as:

Maximum 1-hour CO concentration (µg/m3 per vehicle) = 4 exp (-0.3 d0.5).

This equation is based on an assumed NZTER fleet-weighted CO emission factor of 12.302 g/km. Therefore, an alternative normalised equation is:

Maximum 1-hour CO concentration (µg/m3 per g/vkt) = 0.325 exp (-0.3 d0.5).

Notes: VKT = vehicle kilometres travelled.

To evaluate the conservatism of this dispersion curve, a similar normalised curve has been developed using meteorological parameters recommended for screening assessments by Austroads (2004). For screening assessments, the Austroads review recommends the use of CALINE4, assuming a 1 m/s wind speed, stable atmospheric conditions, sigma-theta of 10 and worst-case wind angle. The Austroads review compared maximum concentrations predicted using these assumptions with maximum measured concentrations for a freeway and arterial road. The analysis showed that this approach is adequately conservative for screening assessments. The most significant sources of uncertainty were background concentration and the atmospheric chemistry rates, where these are relevant (eg, in applying the relationship to NO2, see below).

Figure A1.1 shows a comparison of the normalised dispersion curve based on the parameters recommended by Austroads and the methods assumed here. The Austroads curve predicts significantly lower concentrations (approximately half) than the Scoggins et al curve within 50 m of the roadside. This suggests that the Scoggins et al. curve may be most appropriate in situations where worst-case wind speeds of less than 1 m/s are likely. The emphasis of the method developed here is on worst-case circumstances, and these can occur just about anywhere in New Zealand – even in very exposed places, albeit for shorter times. If this assessment is critical, then specific modelling (say, using CALINE4 and on-site meteorological data) should be used.

Figure A1.1: Concentrations of CO at various distances from a carriageway edge

The curve chosen, being the more conservative and applicable to very light wind speeds, is the upper one (Scoggins et al, 2004). This tends to be conservative relative to the Austroads recommendation within 100 m or so of the road, but allows concentrations to fall off more quickly at distances further than 100 m.

A1.3 Averaging periods

The use of these one-hour dispersion curves (with a similar methodology used in Australia and the UK) gives a theoretical worst case for one-hour concentrations. They are based on worst-case meteorology, which may not occur in some locations. Furthermore, the methodology becomes overly conservative when used for averaging times of great than one hour. It is rare for the worst-case meteorological conditions to occur for periods of eight hours or 24 hours.

For instance, in Auckland the calm conditions required for the dispersion curves to apply never occur for more than three consecutive hours. Inland and sheltered places may experience longer periods of calm, but only very rarely for more than 12 hours. Using this methodology to assess 24-hour PM10 or NO2 is thus unrealistic, since it assumes that worst-case hourly conditions persist for the whole 24 hours.

On this basis, the 24-hour calculations have been divided by a factor of 2 to account for those circumstances when the required calm conditions do not occur for 24 hours. In the general case, the magnitude of effects will be lower still; for instance, only 0.125 (3/24) of the calculated effect in cases where the calm period only extends for three hours. Figure A1.1 shows that the Scoggins et al dispersion curve, multiplied by 0.5, still predicts a one-hour concentration that is consistent with the Austroads screening methodology, which is conservative.

The eight-hour averages are based on the one-hour dispersion curve. This is a conservative approach because it assumes that worst-case meteorology applies for the entire eight-hour averaging period.

Worked example of dispersion calculation: 1-hour CO

Assumptions

Emissions factors: as provided in Table 7-1 (NZTER 2004 fleet-weighted average)

Road type: central urban

Congestion level: congested

Cold start: 20%

Central urban road with estimated peak traffic = 1,653 vehicles per hour:

Traffic = 1653 vehicles/hour

Emissions for default fleet profile = (24.3 x 0.8) + (43.7 x 0.2)
= 28 g/km per vehicle of CO

Corridor emissions = 1,653 x 28
= 46,581 g/km

Maximum one-hour concentration at 20 m from the road = 0.325 exp (-0.3 x 200.5) x 46,581
= 3959 µg/m3
= 3.96 mg/m3

A1.4 Generalised dispersion curves

The sections above describe how the dispersion relationship is derived for CO, for one-hour, eight-hour and 24-hour periods. This is now assumed to extend to NO2 and PM10. A detailed validation of this assumption is beyond the scope of this document, and requires a fairly intensive field programme of measurements that cover the light wind-speed conditions of interest. This was partially undertaken as part of the derivations (Bluett and Fisher, 2005) but needs to be further investigated. However, as part of a checking process, the dispersion rates used in one of the more commonly applied models were examined. Using the latest (2006) version of CALINE4, through its GUI processor CalRoads View, a series of model runs were made using the New Zealand fleet-weighted average emission rates and a meteorological field with light wind speeds (1 m/s) in Auckland.

Figure A1.2 shows the results, all normalised for a concentration of 1 at the edge of the carriageway. This figure shows the CALINE4 dispersion curves for CO, NO2, and PM10. Also shown is the generalised dispersion curve based on CO, described earlier.

The data show that the choice of the generalised curve is a reasonable representation of what CALINE4 uses (although some caution needs to be applied when modelling NO2 and PM10). The atmospheric transformation of NO2 is accounted for in CALINE4 by making assumptions about ozone. Secondary production of PM10 is not accounted for, but this is not significant on the short-time scales involved here.

Figure A1.2: Normalised concentrations of CO, NO2, and PM10 at various distances from a carriageway edge

Notes: Figure A1.2 is produced using CALINE 4 with one-hour rates, 1 m/s and Auckland meteorology. Also shown is the general dispersion curve used in this guidance.

Therefore, to the first order and as a very good approximation, the calculation for any gaseous pollutant is made using the following relationship:

Maximum concentration over period T (µg/m3) = 0.325 exp (-0.3 d0.5) x (N/T) x EF

Equation A:1.4.1

where: d = distance from roadside in metres

N = number of vehicles in the period T

T = time period assessed (1 to 8 hours)

EF = emission factor in g/km.

And for 24-hour averages:

Maximum concentration over 24 hours (µg/m3) = 0.325 exp (-0.3 d0.5) x (N/24) x EF x 0.5

Equation A:1.4.2

where: d = distance from roadside in metres

N = number of vehicles in 24 hours

EF = emission factor in g/km.

Note that this relationship is reliable within 250 m of the road, but needs to be used with caution for PM10 and NO2 at greater distances. In practice this is not a serious restriction because compliance would usually be required within 250 m, and cases where non-compliance at 250 m or further would be acceptable will be uncommon.

A1.5 CO 8-hour

Thus the eight-hour CO concentration is calculated based on the one-hour dispersion curve (equation A:1.4.2) using average one-hour traffic for the eight-hour period.

Maximum 8-hour CO concentration (µg/m3) = 0.325 exp (-0.3 d0.5) x (N/8) x EF

where: d = distance from roadside in metres

N = number of vehicles in 8 hours (worst 8 hours)

EF = emission factor in g/km.

A1.6 PM10 24-hour

The 24-hour PM10 concentration is calculated based on the one-hour CO curve adjusted by a factor of 0.5 (equation A:1.4.2).

Maximum 24-hour PM10 concentration (µg/m3) = 0.325 exp (-0.3 d0.5) x (N/24) x EF

where: d = distance from roadside in metres

N = number of vehicles in 24 hours (high traffic day)

EF = PM10 emission factor in g/km.

A1.7 PM10 annual

Annual average PM10 concentrations at the roadside (20 m from the edge of the road) are derived from the annual average CO curve using a scaling argument based on Auckland conditions (Scoggins et al, 2004). This is a difficult factor to generalise because it is strongly dependent on climate factors (eg, the frequency of calm conditions) at the particular site of interest. The method described here is a first-order approach, used in the absence of any more detailed data, and it must be recognised that it is based on Auckland conditions and only applicable at an indicator location 20 m from the roadside edge. This is probably adequate for a comparison of project options, but site-specific modelling should be considered for any more detailed assessment of PM10 effects.

Annual average 20 m from roadside PM10 (µg/m3) = 0.007 x N x EF

where: N = number of vehicles in 1 hour

EF = PM10 emission factor in g/km.

A1.8 NO2 1-hour

In a similar fashion, the one-hour NO2 concentration is calculated based on the one-hour CO curve. However, since most emissions factors are given for NOx, it is necessary to convert the concentration to NO2.

Maximum 1-hour NOx concentration (µg/m3) = 0.325 exp (-0.3 d0.5) x N x EF

where: d = distance from roadside in metres

N = number of vehicles in 1 hour (peak)

EF = NOx emission factor in g/km.

Maximum 1-hour NO2 concentration (µg/m3) = NOx x C

where: C = conversion factor from NOx to NO2, here assumed to be 0.2 (see detailed discussion later in this appendix).

This estimation is similar to that used by Austroads and is discussed in detail below. There are more complex and detailed models that can be used to improve accuracy, based on roadside measurements made in Auckland (eg, Scoggins et al, 2004; Bluett and Fisher, 2005). However, these are not applied here, with the emphasis instead being on establishing a conservative case envelope, which is covered by the 20% conversion factor used. This is maximised at 20-50 m from the roadside, and is lower at closer or further distances.

A1.9 NO2 24-hour

In an identical fashion, the 24-hour NO2 concentration is calculated based on equation A:1.4.2.

24-hour NO2 concentration (µg/m3) = 0.325 exp (-0.3 d0.5) x (N/24) x EF x C x 0.5

where: d = distance from roadside in metres

N = number of vehicles in 24 hours (high traffic day)

EF = NOx emission factor in g/km

C = NOx to NO2 conversion factor, 0.2.

A1.10 NOx to NO2 conversion

Emissions of oxides of nitrogen are generally quantified in terms of NOx, which is mainly composed of NO and NO2. For most combustion sources, the emission is mainly NO, which then oxidises to NO2 in the atmosphere. The contaminant of interest, from the point of view of health effects, standards and guideline compliance, and degradation of visibility, is NO2.

Given NOx emissions, models can fairly easily simulate the dispersion of NOx as if it were an inert gas. But the determination of the fraction of NO2 requires a model that simulates chemical transformations, or some empirically determined formula for the NO2:NOx ratio. Even when a sophisticated model is used to simulate the oxidation of NO to NO2, knowledge of the oxidants taking part in such reactions (eg, ozone, volatile hydrocarbon products) may still not be well quantified. Thus the NO2 concentrations depend not only on the NOx emissions and the distance from the source, but also on the absolute quantity of these emissions and the amount of oxidant in the air, which is not usually known.

In the United Kingdom the problem of modelling NO2 has been addressed by air quality expert groups on behalf of the Department for Environment Food and Rural Affairs (National Roads Authority and DEFRA, 1992/2003). Using air quality data, they developed relationships between the annual mean NO2 and NOx.

When deriving a relationship specific to New Zealand conditions, there are several considerations.

  1. The temporal and spatial variation in the NO2-NOx relationship needs to be assessed. NOx may be emitted as NO, but is transformed to NO2 further downstream, affected by both the distance the emissions travel and the time they have to react with ambient air.
  2. The maximum possible NO2:NOx ratio is 1, but the oxidants may be depleted before all NO is transformed to NO2. In such situations, more NOx may be emitted as NO but little more NO2 will result.
  3. The NO2−NOx relationship must be applicable to the whole region rather than to individual emission sources, because NOx from all sources becomes mixed in the atmosphere.

A simple universal ratio of NO2 to NOx was proposed 15 years ago (Janssen et al, 1988) to change linearly with distance from the source:

[NO2] / [NOx] = 0.2 x

where x is the distance from the source in km, and the concentrations are in units of either parts per billion by volume (ppbv) or µg/m3 as NO2. However, this does not account for the NO2 fraction near the source (x = 0), nor the limiting value at larger distances (ie, the ratio should always be ≤ 1).

Considering air quality observations in Auckland at Khyber Pass, the [NO2]/[NOx] ratio varies from close to 1.0 to quite low values (down to 0.1 during winter), with day-to-day variations of the order of 0.1. At Musick Point, 10 km away, there is a range from around 1.0 to 0.2, with a median value of 0.86. Detail of these ratios from data from the Penrose site is shown in Figures A1.3a and b.

Figure A1.3a: Relationship between NOx and NO2/NOx at the Penrose, Auckland site

Figure A1.3b: Relationship between NOx and NO2/NOx at the Penrose, Auckland site

A further analysis conducted on annual ratios from a number of stations throughout Auckland shows a similar pattern (see Figure A1.4).

Figure A1.4: Annual average NO2-NOx relationship in the Auckland region for the period 1995-2002

It can be seen from these figures that the NOx:NO2 ratio is strongly dependent on the concentration, with more complete conversion (a ratio close to 1.0) occurring at lower concentrations. At the higher end (the concentrations of most interest for standards and health effects) the ratio tends to be lower, levelling out at around 0.2 for the longer-term 24-hour and annual values.

These values are for the 'urban plume' as a whole, but are still applicable to emissions from transport as these are part of the urban air.

To make use of such information in assessing transport emissions, however, the distance-based approach has to be considered. From the observations, a formula can be derived empirically:

[NO2] / [NOx] = 0.1 + 0.2 (x / (1 + x/5)).

The ratio starts at 0.1 when x = 0, increases at a rate of 0.2 per km (as given by Janssen et al, 1988), but then levels off. The factor of 5 in the formula leads to a ratio of 0.20 at x = 0.5 km, 0.60 at x = 5 km, and 1.0 in the far field at x > 40 km. This relationship holds well for longer-range transport, but is not strictly applicable on the roadside scales of a few tens of metres. As shown in Figure A1.4, the conversion rate can vary from 0.1 to close to 1.0 depending on the concentration.

The Austroads (2004) review recommended a maximum conversion of NO to NO2 of 15% at 30 m from the curb (ie, a ratio of 0.15).

The data in Figures A1.3 and A1.4 can be then used to derive an appropriate rate for use in Auckland (and, by implication, other New Zealand areas affected by traffic emissions). At low concentrations, although the conversion ratio is high, the NOx value is low and the resulting NO2 concentration is low. At high concentrations the conversion rate is low but the NOx value is high, resulting in higher NO2 concentrations. The point at which the concentration tends to achieve its conservative maximum is when the NOx is around 1,000 µg/m3 or greater, which gives rise to a maximum one-hour NO2 concentration of 200 µg/m3 – the one-hour national ambient air quality standard. This is illustrated in Figure A1-5.

Figure A1.5: Hourly NOx vs. NO2 for all Auckland stations, 2004

This maximum conversion occurs when the conversion rate is 0.2 (or 20%). This pattern also occurs in data from Christchurch, and in the 24-hour data (not shown here). Thus the appropriate NO to NO2 conversion rate to use within the 20–50 m zone away from a roadside is 20%, or a ratio of 0.2.

A similar best-fit relationship between measured NO2 and NOx was developed by Scoggins et al using annual average NO2 and NOx data from a number of Auckland monitoring sites for the period 1995 to 2002. This showed that for high values of NOx the amount of conversion to NO2 is small. This is due to the other components (such as ozone) being used up. For lower amounts of NOx the conversion to NO2 can be almost complete, because enough ozone is present to complete all the reactions.

As for previous discussions and recommended methodologies, the figures given here are conservative default values, which should be revised in cases where more accurate, site-specific data are available.

A further discussion of NOx conversion schemes is contained in the companion Good Practice Guide for Discharges from Industry (Ministry for the Environment, 2008). These are more relevant to industrial discharges and contain advice and examples on using a slightly different NO to NO2 conversion methodology. However, the industry case is guided by the fact that most industrial NOx discharges arise from combustion sources that have emissions ratios of NO:NO2 of the order of 5:95. Vehicle sources can have higher emissions ratios of up to 20:80, which is where the initial conversion factor of 0.2 arises. The use of this factor is justified on the basis of (a) data presented here on measurements in New Zealand, (b) the approach used by Austroads and DEFRA, and (c) consistency with the recommendation in the Good Practice Guide for Discharges from Industry.

In summary an appropriate NO to NO2 conversion rate to use within the 20−50 m zone away from a roadside is 20%, or a ratio of 0.2.

A1.11 Thresholds for Tier 1 assessment

The Tier 1 assessment thresholds are intended to identify proposals that should be assessed using either the Tier 2 or Tier 3 assessment procedures, and (more importantly) to identify projects that do not require assessment. These thresholds are intentionally conservative because they need to capture relatively small projects that may have significant effects because of their location.

Assessments to date have generally focused on arterial roads and state highways. The Transit definition of an urban arterial road is “arterial and collector roads within urban areas carrying traffic volumes of greater than 7,000 vehicles/day”. This was taken as a starting point for developing an assessment threshold.

The Tier 2 assessment method was used to predict maximum contaminant concentrations for a range of scenarios. The results for a road with 3,000 vehicles under congested conditions, and a road with 7,000 vehicles under free-flow conditions, are summarised in Table A1.1. This shows the most conservative concentrations of various pollutants at various distances, based on the two scenarios (the detailed calculation examples are shown below). The grey shaded figures are below the significance criteria, as discussed in the Tier 2 methodology.

For these two scenarios the predicted concentration of CO and NO2 is below the significance threshold within a few metres of the roadway, and PM10 is below the significance threshold within 10 to 20 m of the roadway. Given the conservatism in the calculations, these are considered to be appropriate assessment thresholds.

Table A1.1: Tier 2 screening method results showing effects due to two traffic flow scenarios at various distances from the road

View tier 2 screening method results showing effects due to two traffic flow scenarios at various distances from the road (large table).

Calculation examples for 7,000 vehicles per day (free flow)

Assumptions

Emissions factors: as provided in Table 7.1 (NZTER 2004 fleet-weighted average)

Road type: central urban

Congestion level: free flow

Cold start: 20%

Carbon monoxide (eight-hour)

Emission factor = (7.80 x 0.8) + (43.7 x 0.2) = 14.98 g/km

Assume that number of vehicles per eight hours = 40% of daily traffic = 2,800

Maximum predicted concentrations of CO calculated using equations above

Nitrogen dioxide (one-hour)

Emission factor = (2.12 x 0.8) + (2.83 x 0.2) = 2.26 g/km

Assume that the maximum number of vehicles per hour = 5% of daily traffic = 350

Maximum predicted concentration of NO2 calculated using equations above

PM10 (24-hour)

Emission factor = (0.158x 0.8) + (0.332 x 0.2) = 0.193 g/km

Number of vehicles per 24 hours = 7,000

Maximum predicted concentration of PM10 calculated using equations above

Calculation examples for 3,000 vehicles per day (congested)

Assumptions

Emissions factors: as provided in Table 7.1 (NZTER 2004 fleet-weighted average)

Road type: central urban

Congestion level: congested

Cold start: 20%

Carbon monoxide (eight-hour)

Emission factor = (24.3 x 0.8) + (43.7 x 0.2) = 28.18 g/km

Assume that number of vehicles per eight hours = 40% of daily traffic = 1,200

Maximum predicted concentrations of CO calculated using equations above

Nitrogen dioxide (one-hour)

Emission factor = 3.32 g/km

Assume that number of vehicles per hour = 5% of daily traffic = 150

Maximum predicted concentration of NO2 calculated using equations above

PM10 (24-hour)

Emission factor = (0.314 x 0.8) + (0.332 x 0.2) = 0.317 g/km

Number of vehicles per 24 hours = 3,000

Maximum predicted concentration of PM10 calculated using equations above

A1.12 Benzene emission factors

The impact of fuel specification on benzene emissions has been assessed for the Review of Fuel Quality Requirements for Australian Transport (Environment Australia, 2000b). According to this review, petrol engine exhaust is responsible for the bulk of benzene emissions, with relatively small contributions from petrol evaporative losses and diesel engine exhaust. Incomplete combustion of fuel benzene and other aromatics results in exhaust emissions of benzene. The introduction of catalyst technology has led to large reductions in benzene emissions.

Relationships to estimate benzene emissions provided by the Environment Australia review are as follows.

  • Petrol catalyst equipped vehicles:
    Percentage benzene of exhaust VOC = 1.077 + 0.7732 x % benzene (vol) + 0.0987 x {% aromatics (vol) - % benzene (vol)}

  • Petrol non-catalyst vehicles:
    % benzene of exhaust VOC = 0.8551 x % benzene (vol) + 0.12198 x % aromatics (vol) - 1.1626

  • Evaporative:
    % benzene (vapour, New Formulation) = % Benzene (liquid, New Formulation) x 0.9/2.6

Benzene emission factors have been estimated based on these relationships, and New Zealand fuel specifications are shown in Table A1.2.

Table A1.2: The fraction of total aromatics and benzene in New Zealand petrol fuels, including estimates of the percentage of volatiles (VOCs) emitted through exhaust and evaporation

View the fraction of total aromatics and benzene in New Zealand petrol fuels, including estimates of the percentage of volatiles (VOCs) emitted through exhaust and evaporation (larege table).

For the sake of simplicity, it is recommended that the highest benzene percentage for any one year be adopted.

A1.13 Comparison of New Zealand and Australian emission factors

Table A1.3 shows ratios of emissions estimates based on different emissions factors compared with factors used in Australia (Environment Protection Authority Victoria, or EPA). Values less than 1 imply Ministry of Transport emissions estimates are higher than the EPAs, indicating that the New Zealand Ministry of Transport estimate is more conservative, in part reflecting the tighter emission standards applying in Australia (Auckland Regional Council, 2005a). The comparison shows that the NZTER emissions factors are conservative when compared with Australian factors.

Table A1.3: Comparison of the emissions factors used in Australia with those used in New Zealand

Pollutant

Ratios of total vehicle emissions based on different emission factors (EPA / MoT)
 

1998

2011

2021

CO

1.11

0.91

0.43

CO2

0.99

0.99

0.99

NOx

0.86

0.74

0.67

SO2

0.69

0.52

0.44

TSP

0.90

0.66

0.62

VOC

0.66

0.57

0.45

Notes: EPA = Environment Protection Authority, Victoria; MoT = Ministry of Transport, New Zealand Transport Emissions rate database; TSP = total suspended particulate.

Source: Ministry of Transport.