title: The use of microscopic traffic simulation model for the analysis of vehicle emission

authors: Kaushalya, Jani

subjects: vehicle emission

abstract: Road transport is a significant contributor to greenhouse gas emissions and urban air pollution in New Zealand, particularly in the rapidly growing Bay of Plenty region. The high vehicle density during peak hours and the reliance on petrol and diesel fuels in most fleets contribute significantly to vehicle emissions, which contribute to climate change and air quality degradation. This research investigates the use of a microscopic traffic simulation model to analyse vehicle emissions in order to identify practical measures to reduce transport-related emissions. SUMO (Simulation of Urban Mobility), an open-source software was used to construct the road network, generate realistic vehicle demand, and execute the simulation, while the HBEFA (Handbook Emission Factors for Road Transport) emission model was used to estimate vehicle emissions. This simulation utilised vehicle count data provided by the Tauranga City Council, and MongoDB was employed as the main database to facilitate effective storage, retrieval, and real-time querying of the simulation output. Three targeted emission reduction scenarios were developed and tested based on the simulation results: increasing electric vehicle ownership by 20%, introducing trackless trams on high-demand routes, and encouraging carpooling to reduce single-occupancy vehicle usage. As a result of the simulation, each measure resulted in significant reductions in vehicle emissions, and the effectiveness of each scenario was examined and compared. The findings of this study provide practical, data-driven insights for local councils, transport planners, and policymakers in implementing effective strategies to reduce vehicle emissions and contribute to New Zealand’s emission reduction targets.

text: The use of microscopic traffic simulation model for the analysis of vehicle emission Road transport is a significant contributor to greenhouse gas emissions and urban air pollution in New Zealand, particularly in the rapidly growing Bay of Plenty region. The high vehicle density during peak hours and the reliance on petrol and diesel fuels in most fleets contribute significantly to vehicle emissions, which contribute to climate change and air quality degradation. This research investigates the use of a microscopic traffic simulation model to analyse vehicle emissions in order to identify practical measures to reduce transport-related emissions. SUMO (Simulation of Urban Mobility), an open-source software was used to construct the road network, generate realistic vehicle demand, and execute the simulation, while the HBEFA (Handbook Emission Factors for Road Transport) emission model was used to estimate vehicle emissions. This simulation utilised vehicle count data provided by the Tauranga City Council, and MongoDB was employed as the main database to facilitate effective storage, retrieval, and real-time querying of the simulation output. Three targeted emission reduction scenarios were developed and tested based on the simulation results: increasing electric vehicle ownership by 20%, introducing trackless trams on high-demand routes, and encouraging carpooling to reduce single-occupancy vehicle usage. As a result of the simulation, each measure resulted in significant reductions in vehicle emissions, and the effectiveness of each scenario was examined and compared. The findings of this study provide practical, data-driven insights for local councils, transport planners, and policymakers in implementing effective strategies to reduce vehicle emissions and contribute to New Zealand’s emission reduction targets.

year: 2025

title: The extrapolation of social landscape values to a national level in New Zealand using landscape character classification

authors: Brown, Greg

subjects: character

abstract: The human perception and valuation of landscapes is a complex process but has been pragmatically advanced through public participation GIS (PPGIS). PPGIS methods have the capacity to generate spatial data to empirically examine relationships between human landscape values and physical landscape character. In 2011, PPGIS methods were used to identify a range of social landscape values for two regions in southern New Zealand, Otago and Southland. Seven of these landscape values were analysed to identify significant relationships with physical landscape character from the New Zealand Landscape Classification system. In this paper we examine methods to extrapolate landscape values from this regional data set to a national level using these landscape value and character relationships. In the absence of empirical value data at a national level, we examine two quantitative approaches for extrapolating landscape values: (1) landscape component weights based on the percentage of value counts found within landscape components, and (2) landscape component weights based on the ratio of landscape values to the landscape area. We prepare and present maps of seven landscape values for the entire country of New Zealand to demonstrate the method. We conclude that landscape value extrapolation can assist impact assessment for land use change but should be kept simple for decision support.

text: The extrapolation of social landscape values to a national level in New Zealand using landscape character classification The human perception and valuation of landscapes is a complex process but has been pragmatically advanced through public participation GIS (PPGIS). PPGIS methods have the capacity to generate spatial data to empirically examine relationships between human landscape values and physical landscape character. In 2011, PPGIS methods were used to identify a range of social landscape values for two regions in southern New Zealand, Otago and Southland. Seven of these landscape values were analysed to identify significant relationships with physical landscape character from the New Zealand Landscape Classification system. In this paper we examine methods to extrapolate landscape values from this regional data set to a national level using these landscape value and character relationships. In the absence of empirical value data at a national level, we examine two quantitative approaches for extrapolating landscape values: (1) landscape component weights based on the percentage of value counts found within landscape components, and (2) landscape component weights based on the ratio of landscape values to the landscape area. We prepare and present maps of seven landscape values for the entire country of New Zealand to demonstrate the method. We conclude that landscape value extrapolation can assist impact assessment for land use change but should be kept simple for decision support.

year: 2012

title: Urban Rural Differences in Breast Cancer in New Zealand

authors: Lawrenson, Ross

subjects: Science & Technology

abstract: Many rural communities have poor access to health services due to a combination of distance from specialist services and a relative shortage of general practitioners. Our aims were to compare the characteristics of urban and rural women with breast cancer in New Zealand, to assess breast cancer-specific and all-cause survival using the Kaplan–Meier method and Cox proportional hazards model, and to assess whether the impact of rurality is different for Māori and New Zealand (NZ) European women. We found that rural women tended to be older and were more likely to be Māori. Overall there were no differences between urban and rural women with regards their survival. Rural Māori tended to be older, more likely to be diagnosed with metastatic disease and less likely to be screen detected than urban Māori. Rural Māori women had inferior breast cancer-specific survival and all-cause survival at 10 years at 72.1% and 55.8% compared to 77.9% and 64.9% for urban Māori. The study shows that rather than being concerned that more needs to be done for rural women in general it is rural Māori women where we need to make extra efforts to ensure early stage at diagnosis and optimum treatment.

text: Urban Rural Differences in Breast Cancer in New Zealand Many rural communities have poor access to health services due to a combination of distance from specialist services and a relative shortage of general practitioners. Our aims were to compare the characteristics of urban and rural women with breast cancer in New Zealand, to assess breast cancer-specific and all-cause survival using the Kaplan–Meier method and Cox proportional hazards model, and to assess whether the impact of rurality is different for Māori and New Zealand (NZ) European women. We found that rural women tended to be older and were more likely to be Māori. Overall there were no differences between urban and rural women with regards their survival. Rural Māori tended to be older, more likely to be diagnosed with metastatic disease and less likely to be screen detected than urban Māori. Rural Māori women had inferior breast cancer-specific survival and all-cause survival at 10 years at 72.1% and 55.8% compared to 77.9% and 64.9% for urban Māori. The study shows that rather than being concerned that more needs to be done for rural women in general it is rural Māori women where we need to make extra efforts to ensure early stage at diagnosis and optimum treatment.

year: 2016