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Journal ArticleDOI

Land-use, transport and vehicle technology futures: An air pollution assessment of policy combinations for the Cambridge Sub-Region of the UK

TL;DR: In this paper, the authors investigated the impact of combinations of urban form development scenarios and vehicle fleet technology changes on air quality in the UK, and proposed a framework for environmental assessment, from land-use transport interaction, through traffic assignment and emissions modelling, through to dispersion calculations.
About: This article is published in Cities.The article was published on 2019-06-01 and is currently open access. It has received 15 citations till now. The article focuses on the topics: Air quality index.

Summary (4 min read)

1. Introduction 1.1 Urban form and air quality

  • Understanding the nature of the intensification paradox clearly requires that assessment goes beyond a consideration of emission to address pollutant concentration that is important to exposure and health impact.
  • Cities in the UK and northern Europe tend to have most issues with compliance to nitrogen dioxide (NO2) standards (DEFRA, 2018; EEA, 2018) , whereas those in Eastern Europe and Asia have greater problems with particulate matter (Tasmin, 2019) due to differences in source types and mixes, fuels and technologies.
  • Some of these factors can be addressed via a very dense network of monitoring sites, but this is generally impractical, hence atmospheric dispersion modelling, which is capable of addressing such complexities is required.
  • To date such models have been little used in the exploration of urban form effects on air quality.

1.2 Urban form, air quality and technology

  • The prior work on sustainable urban form (Echenique et al., 2010; Mitchell et al 2011; Echenique et al., 2012) examined the sustainability of current and proposed spatial planning strategies in the UK.
  • The authors used Land-Use/Transport Interaction (LUTI) modelling to drive a multi-criteria sustainability appraisal of radical, but realistic, alternative urban forms, with an analysis of three UK regions: London and the Wider South East, Tyne and Wear, and Cambridge Sub-Region.
  • The authors analyses addressed global and local emissions but stopped short of addressing implications of form-technology combinations for air quality.
  • Therefore, in this paper the authors report on work, for Cambridge and its sub-region, that examines the impact of packages of measures comprising of complementary urban forms, transport schemes and vehicle technologies.
  • The authors assess impacts in terms of VKT, global and local emissions, and local air quality (PM, NOx, NO2 and HC).

2. Modelling Methodology

  • Given the modelling platform developed in the SOLUTIONS research, use of the coupled MENTOR and SATURN models for the Cambridgeshire region was axiomatic.
  • Historically, both models have enjoyed considerable use both within the UK and internationally, e.g. see Echenique et al. (1990) regarding the use of MEPLAN in three European cities, or Shepherd et al. (2006) regarding SATURN in the UK context.

2.2 Emissions and Dispersion Modelling

  • Dispersion modelling used the commercial ADMS-Urban model (McHugh et al., 1997; CERC, 2018) , a quasi-Gaussian dispersion model, that takes into account meteorology, atmospheric boundary layer structure, height-dependence of wind speed, turbulence and stability, and NOx photochemistry, and able to calculate concentrations over spatial scales from street to region (CERC, 2018) .
  • ADMS is routinely used in the UK for assessment purposes, though it has also seen use in Europe, the United States and Asia (e.g. to study traffic restriction measures associated with the Beijing Olympic Games (CERC, 2018; Cai and Xie, 2010) .
  • Numerous validation studies exist (e.g. ADMS was selected for this study based on its demonstrable utility and accuracy for dispersion modelling, and its appropriateness for modelling at the city scale.
  • Conversion of modelled NOx to NO2 concentrations was done via post-processing ADMS outputs using the DEFRA conversion spreadsheet (DEFRA, 2012a), in the absence of detailed background ozone information for the sub-region.

3.1 Study Area

  • Figure 2 shows the area addressed in this analysis, which comprises four district councils including the main population centres of Cambridge (2011 pop.
  • In terms of form, the area may be described as monocentric, based around Cambridge itself.
  • The scenarios considered in SOLUTIONS are summarised in Table 1 with a brief generic description and specifics for the Cambridge study area.
  • As with the 'Trend' scenario, the base year is 2001 with a modelled target year for the alternate scenarios of 2021.

Table 1: Urban form scenarios considered (Echenique et al., 2010)

  • Data driving the LUTI scenarios was sourced from the Cambridgeshire County Council (CCC) MENCAM model (Echenique et al., 2012) .
  • This was calibrated using 1990's socioeconomic data, with some updating using 2001 household and employment data.

3.4 Dispersion modelling

  • Additional background pollution information, and concentrations arising from non-traffic sources were taken from DEFRA background maps (DEFRA, 2012b).
  • Meteorological information was sourced from the UK Met Office from the Monkswood station, to the north of Cambridge, as the closest available site.

4.1 Vehicle Kilometres Travelled and Emissions

  • Results from the Trend 2021 scenario were first compared to a baseline 2001 scenario.
  • Total vehicle kilometres travelled (VKT) would increase by +11.5%, but technology changes in the fleet resulted in projected CO2 emissions falling by -16%, PM10 by -37% and NOx and HC emissions by over -80%.
  • Primary NO2 emissions only fell by -9%.
  • Over the same period and region, the SOLUTIONS project (Echenique et al., 2012) showed increases in CO2 emissions of 16% for the transport and building energy sectors for the Cambridge subregion.
  • The fall in CO2 emissions reported here are due to more aggressive assumptions on fuel consumption improvements to light-duty IC vehicles than were present in the EFT emissions figures (DEFRA, 2013) in the light of European Union CO2 targets, than in the SOLUTIONS modelling.

Table 3: Network performance (absolute values) of alternate planning scenarios relative to the Trend scenario

  • Table 3 provides the results for the 2021 urban form-technology scenarios, with reductions compared to the 2021 Trend scenario shown as negative values.
  • These results are further illustrated in Figure 4 with results for each scenario (dashed lines) plotted relative to the Trend case (solid blue line).
  • Note that the change in pollutant emissions associated with the scenarios falls into a relatively small range (-12.7% to +7.1%), although these variations in emissions are greater than the changes in vehicle kilometres travelled (-4.2% to +4.7%).
  • This indicates that the vehicle technologies have a larger impact on emissions than the changes in urban form alone, consistent with the findings of Echenique et al.
  • Note that the mass-based changes in emissions , plus the spatial analyses in Figures 5 and 6 , present only a partial picture of the atmospheric impact of the planning scenariosconcentrations of NO2 within Cambridge itself are described in the next section.

5.1 Limitations

  • For NOx speed-dependent discrepancies are large, reaching +63% at free-flow urban speeds (50-60 km/h), and are still significant, but smaller (+36-54%) at lower and higher speeds.
  • Hence the authors would expect an update to this work using the latest emissions factors to be detrimental to the NOx/NO2 results for the Compaction and Market-Led Dispersal options to a greater extent than the other options examined.

Court action against central government for ongoing exceedences of European annual NO2

  • Objectives have also lead to Clean Air Zones (CAZs), wherein certain vehicles are restricted, and 'pollution charges' being examined in several citiesincluding Cambridge (GCP, 2017).
  • A further pledge for a ban on all new petrol and diesel car sales by 2040 also seeks to drive penetration of alternate-fuelled vehicles beyond previously assumed rates, such as those proposed by Wright (2012) , and used in the Compaction+ scenario.
  • The Compaction option would greatly increase the population densities within Cambridge compared to the Trend and so forecasts of the traffic speeds, flows and queuing may be less reliable than for the Trend within and around Cambridge.
  • This is an example of how further, more detailed traffic simulation modelling would be useful in conjunction with other measures to reduce air pollution in a higher density city such as traffic demand management, cleaner fuels and attractive and sustainable alternatives to car use.
  • Likewise, for CO2 emissions there are discrepancies between values (in terms of g/km rates) calculated via the EFT (versions 5 or 8), and those in the National Transport Model (NTM) (Li et al., 2009) or the Greenhouse gas conversion factor repository (Hill et al., 2013; DEFRA, 2013b) used for official reporting of CO2 emissions.

5.2 Interpretation and Conclusions

  • Likewise, disease burden estimations based on the spatial distribution of populations, exposure-response curves and ADMS pollution concentration maps are being included in the PITHEM software, based on the methodology outlined in Mitchell et al. (2000) .
  • This included some relaxation of the green belt constraints and thereby reduced the need to travel compared to the preceding planning policy that had allocated almost all development beyond the green belt.
  • The transport schemes included in the Structure Plan to 2016 were part of the Trend scenario (and were also included in the other urban form scenarios).
  • This scenario reflects that the UK planning policy constrained suburban expansion and prioritised development to brownfield land and areas with good public transport. .

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Citations
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TL;DR: In this paper, the authors examined the effect of technological innovation on green growth on twenty-eight (28) Organization for Economic Cooperation and Development (OECD) economies for the period 2000 to 2014 with data sourced from OECD library statistics and World Bank, World Development Indicators.

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TL;DR: The research explores the nexus between technological innovation and green growth in nine newly industrialized (NI) countries for the period from 2000 to 2016 and reveals that production and processing-related technologies are harmful to green growth.
Abstract: The research explores the nexus between technological innovation and green growth in nine newly industrialized (NI) countries for the period from 2000 to 2016. Cross-sectional dependence and unit root tests are preliminary conducted. Pedroni’s panel cointegration and fully modified OLS (FMOLS) confirm the existence of long-run variables association. The outcome from IPAT, STIRPAT, and MLR reveals that production and processing-related technologies are harmful to green growth. Climate change mitigation technologies linked to transportation, water treatment, and processing have a positive impact on green growth. However, energy consumption, generation, and transmission technologies hurt the environment. Similarly, energy consumption in the agriculture sector adds in greenhouse gas emission, whereas, renewable energy is contributing positively to green production and growth. Environmental taxes and research and development budgets are playing a decisive role in the pursuit of green growth. The results have significant policy implications for policymakers, which can lead to green growth.

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Cites background from "Land-use, transport and vehicle tec..."

  • ...Pedroni (1999, 2004) proposed many test statistics that allow trend coefficients and heterogeneous intercepts across the cross-sections....

    [...]

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TL;DR: Wang et al. as mentioned in this paper evaluated CO2 emissions from light-duty passenger vehicles (LDPVs) at the community level using an integrated model, where the mixed-use development (MXD) model was adopted to estimate travel demand based on mixed land-use and transport accessibility.

17 citations

References
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Journal ArticleDOI
TL;DR: In this article, the authors examined how the built environment affects trip rates and mode choice of residents in the San Francisco Bay Area using 1990 travel diary data and land-use records obtained from the U.S. census, regional inventories, and field surveys.
Abstract: The built environment is thought to influence travel demand along three principal dimensions —density, diversity, and design. This paper tests this proposition by examining how the ‘3Ds’ affect trip rates and mode choice of residents in the San Francisco Bay Area. Using 1990 travel diary data and land-use records obtained from the U.S. census, regional inventories, and field surveys, models are estimated that relate features of the built environment to variations in vehicle miles traveled per household and mode choice, mainly for non-work trips. Factor analysis is used to linearly combine variables into the density and design dimensions of the built environment. The research finds that density, land-use diversity, and pedestrian-oriented designs generally reduce trip rates and encourage non-auto travel in statistically significant ways, though their influences appear to be fairly marginal. Elasticities between variables and factors that capture the 3Ds and various measures of travel demand are generally in the 0.06 to 0.18 range, expressed in absolute terms. Compact development was found to exert the strongest influence on personal business trips. Within-neighborhood retail shops, on the other hand, were most strongly associated with mode choice for work trips. And while a factor capturing ‘walking quality’ was only moderately related to mode choice for non-work trips, those living in neighborhoods with grid-iron street designs and restricted commercial parking were nonetheless found to average significantly less vehicle miles of travel and rely less on single-occupant vehicles for non-work trips. Overall, this research shows that the elasticities between each dimension of the built environment and travel demand are modest to moderate, though certainly not inconsequential. Thus it supports the contention of new urbanists and others that creating more compact, diverse, and pedestrian-orientated neighborhoods, in combination, can meaningfully influence how Americans travel.

3,439 citations


"Land-use, transport and vehicle tec..." refers background in this paper

  • ...It has been argued that dispersed 70 patterns of living and decentralised employment, enabled by ready access to private 71 transportation, increase vehicle kilometres travelled (VKT) (Newman and Kenworthy, 1989; 72 Glaeser and Kahn, 2001), resulting in exacerbation of negative externalities including air 73 pollution (Cervero and Kockelman, 1997; Pourahmad et al., 2007; McCarthy and Kaza, 74 2015)....

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"Land-use, transport and vehicle tec..." refers methods in this paper

  • ...Likewise, disease 530 burden estimations based on the spatial distribution of populations, exposure-response 531 curves and ADMS pollution concentration maps are being included in the PITHEM software, 532 based on the methodology outlined in Mitchell et al. (2000)....

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Book
01 Feb 1999
TL;DR: The concept of sustainability and its relationship to cities the problem of automobile dependence at the end of the 20th century the pattern of car dependence and global cities a vision of reduced automobile dependence greening the automobile dependent city - urban ecology and auto dependence promoting sustainable urban change ethics, spirituality and community in the city as mentioned in this paper.
Abstract: The concept of sustainability and its relationship to cities the problem of automobile dependence at the end of the 20th century the pattern of automobile dependence and global cities a vision of reduced automobile dependence greening the automobile-dependent city - urban ecology and auto dependence promoting sustainable urban change ethics, spirituality and community in the city.

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"Land-use, transport and vehicle tec..." refers background in this paper

  • ...In the transport sector technology mediated interests include: 129 electrification of road transport, ‘intelligent’ mobility (such as ‘Mobility as a Service’ - MaaS), 130 and automation of the driving task (Manyika et al., 2013)....

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TL;DR: In this article, the authors quantify the carbon dioxide emissions associated with new construction in different locations across the country and find that the lowest emissions areas are generally in California and the highest emissions regions are in Texas and Oklahoma.

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Frequently Asked Questions (8)
Q1. What are the contributions in this paper?

This article is distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivs ( CC BY-NC-ND ) licence. This licence only allows you to download this work and share it with others as long as you credit the authors, but you can ’ t change the article in any way or use it commercially. 

The increase in public transport patronage leads to a commensurate reduction in passenger car usage from the fringes and hinterlands of the city. 

Market-led Dispersal(21_Disp)The historic pattern towards dieselification of the private fleet is continued, and compounded by a further trend towards larger-engine (2+ litre) vehicles, both within the city, and in the hinterlands, resulting in ~23% of trips being made by these vehicles, compared to ~13% in the Trend. 

UK Society for Motor Manufacturers and Traders. [online] 737 https://www.smmt.co.uk/2018/07/smmt-urges-government-to-back-new-tech-diesel-as-738 uncertainty-continues-to-impact-new-car-market/ [Accessed: 4/12/18]. 

784Parameter 21_Trend 21_Comp 21_Comp+ 21_Disp 21_Plex UnitsVKT 6320.7 -262.5 (-4.2%) -262.5 (-4.2%) +297.6 (+4.7%) -129.4 (-2%) m.km. 

Will Euro 6 reduce the NOx emissions of new diesel cars – Insights from on-road 763 tests with Portable Emissions Measurement Systems (PEMS). 

Compaction(21_Comp)The historic pattern of uptake of diesel vehicles is reversed within the Cambridge City boundaries, with small, petrol engine ‘city cars’ becoming more prevalent, making ≈60% of trips within the city by 2021. 

uCO2 1018.9 -101.3 (-9.9%) -129.2 (-12.7%) +71.2 (+7%) +37.4 (+3.7%) kTHC 236.8 -11.9 (-5%) -21.3 (-9%) +16.7 (+7.1%) -1.9 (-0.8%) TNOx 1361.7 -63 (-4.6%) -102.5 (-7.5%) +74 (+5.4%) +39.4 (+2.9%) TpNO2 445.2 -17.1 (-3.8%) -30.9 (-6.9%) +22.4 (+5%) -5.2 (-1.2%) TPM10 224.2 -8.3 (-3.7%) -15.5 (-6.9%) +10.8 (+4.8%) +2.4 (+1.1%) TPM2.5 127.6 -4.4 (-3.4%) -8.6 (-6.7%) +6.2 (+4.9%) +1.7 (+1.3%) T785Figure 1: The modelling framework adopted in the ReVISIONS project.