Mathematical relationships for metal build-up on urban road surfaces based on traffic and land use characteristics

The study investigated the influence of traffic and land use parameters on metal build-up on urban road surfaces. Mathematical relationships were developed to predict metals originating from fuel combustion and vehicle wear. The analysis undertaken found that nickel and chromium originate from exhaust emissions, lead, copper and zinc from vehicle wear, cadmium from both exhaust and wear and manganese from geogenic sources. Land use does not demonstrate a clear pattern in relation to the metal build-up process, though its inherent characteristics such as traffic activities exert influence. The equation derived for fuel related metal load has high cross-validated coefficient of determination (Q2) and low Standard Error of Cross-Validation (SECV) values indicates that the model is reliable, while the equation derived for wear-related metal load has low Q2 and high SECV values suggesting its use only in preliminary investigations. Relative Prediction Error values for both equations are considered to be well within the error limits for a complex system such as an urban road surface. These equations will be beneficial for developing reliable stormwater treatment strategies in urban areas which specifically focus on mitigation of metal pollution.

Identifying the spatial scale of land use that most strongly influences overall river ecosystem health score

Catchment and riparian degradation has resulted in declining ecosystem health of streams worldwide. With restoration a priority in many regions, there is an increasing interest in the scale at which land use influences stream ecosystem health. Our goal was to use a substantial data set collected as part of a monitoring program (the Southeast Queensland, Australia, Ecological Health Monitoring Program data set, collected at 116 sites over six years) to identify the spatial scale of land use, or the combination of spatial scales, that most strongly influences overall ecosystem health. In addition, we aimed to determine whether the most influential scale differed for different aspects of ecosystem health. We used linear-mixed models and a Bayesian model-averaging approach to generate models for the overall aggregated ecosystem health score and for each of the five component indicators (fish, macroinvertebrates, water quality, nutrients, and ecosystem processes) that make up the score. Dense forest close to the survey site, mid-dense forest in the hydrologically active nearstream areas of the catchment, urbanization in the riparian buffer, and tree cover at the reach scale were all significant in explaining ecosystem health, suggesting an overriding influence of forest cover, particularly close to the stream. Season and antecedent rainfall were also important explanatory variables, with some land-use variables showing significant seasonal interactions. There were also differential influences of land use for each of the component indicators. Our approach is useful given that restoring general ecosystem health is the focus of many stream restoration projects; it allowed us to predict the scale and catchment position of restoration that would result in the greatest improvement of ecosystem health in the regions streams and rivers. The models we generated suggested that good ecosystem health can be maintained in catchments where 80% of hydrologically active areas in close proximity to the stream have mid-dense forest cover and moderate health can be obtained with 60% cover.

Methane and nitrous oxide fluxes in annual and perennial land-use systems of the irrigated areas in the Aral Sea Basin

Land use and agricultural practices can result in important contributions to the global source strength of atmospheric nitrous oxide (N2O) and methane (CH4). However, knowledge of gas flux from irrigated agriculture is very limited. From April 2005 to October 2006, a study was conducted in the Aral Sea Basin, Uzbekistan, to quantify and compare emissions of N2O and CH4 in various annual and perennial land-use systems: irrigated cotton, winter wheat and rice crops, a poplar plantation and a natural Tugai (floodplain) forest. In the annual systems, average N2O emissions ranged from 10 to 150 μg N2O-N m−2 h−1 with highest N2O emissions in the cotton fields, covering a similar range of previous studies from irrigated cropping systems. Emission factors (uncorrected for background emission), used to determine the fertilizer-induced N2O emission as a percentage of N fertilizer applied, ranged from 0.2% to 2.6%. Seasonal variations in N2O emissions were principally controlled by fertilization and irrigation management. Pulses of N2O emissions occurred after concomitant N-fertilizer application and irrigation. The unfertilized poplar plantation showed high N2O emissions over the entire study period (30 μg N2O-N m−2 h−1), whereas only negligible fluxes of N2O (<2 μg N2O-N m−2 h−1) occurred in the Tugai. Significant CH4 fluxes only were determined from the flooded rice field: Fluxes were low with mean flux rates of 32 mg CH4 m−2 day−1 and a low seasonal total of 35.2 kg CH4 ha−1. The global warming potential (GWP) of the N2O and CH4 fluxes was highest under rice and cotton, with seasonal changes between 500 and 3000 kg CO2 eq. ha−1. The biennial cotton–wheat–rice crop rotation commonly practiced in the region would average a GWP of 2500 kg CO2 eq. ha−1 yr−1. The analyses point out opportunities for reducing the GWP of these irrigated agricultural systems by (i) optimization of fertilization and irrigation practices and (ii) conversion of annual cropping systems into perennial forest plantations, especially on less profitable, marginal lands.

A national satellite-based land-use regression model for air pollution exposure assessment in Australia

Land-use regression (LUR) is a technique that can improve the accuracy of air pollution exposure assessment in epidemiological studies. Most LUR models are developed for single cities, which places limitations on their applicability to other locations. We sought to develop a model to predict nitrogen dioxide (NO2) concentrations with national coverage of Australia by using satellite observations of tropospheric NO2 columns combined with other predictor variables. We used a generalised estimating equation (GEE) model to predict annual and monthly average ambient NO2 concentrations measured by a national monitoring network from 2006 through 2011. The best annual model explained 81% of spatial variation in NO2 (absolute RMS error=1.4 ppb), while the best monthly model explained 76% (absolute RMS error=1.9 ppb). We applied our models to predict NO2 concentrations at the ~350,000 census mesh blocks across the country (a mesh block is the smallest spatial unit in the Australian census). National population-weighted average concentrations ranged from 7.3 ppb (2006) to 6.3 ppb (2011). We found that a simple approach using tropospheric NO2 column data yielded models with slightly better predictive ability than those produced using a more involved approach that required simulation of surface-to-column ratios. The models were capable of capturing within-urban variability in NO2, and offer the ability to estimate ambient NO2 concentrations at monthly and annual time scales across Australia from 2006–2011. We are making our model predictions freely available for research.

A life cycle assessment approach to quantifying greenhouse gas emissions from land-use change for beef production in eastern Australia

In life cycle assessment studies, greenhouse gas (GHG) emissions from direct land-use change have been estimated to make a significant contribution to the global warming potential of agricultural products. However, these estimates have a high uncertainty due to the complexity of data requirements and difficulty in attribution of land-use change. This paper presents estimates of GHG emissions from direct land-use change from native woodland to grazing land for two beef production regions in eastern Australia, which were the subject of a multi-impact life cycle assessment study for premium beef production. Spatially- and temporally consistent datasets were derived for areas of forest cover and biomass carbon stocks using published remotely sensed tree-cover data and regionally applicable allometric equations consistent with Australia's national GHG inventory report. Standard life cycle assessment methodology was used to estimate GHG emissions and removals from direct land-use change attributed to beef production. For the northern-central New South Wales region of Australia estimates ranged from a net emission of 0.03 t CO2-e ha-1 year-1 to net removal of 0.12 t CO2-e ha-1 year-1 using low and high scenarios, respectively, for sequestration in regrowing forests. For the same period (1990-2010), the study region in southern-central Queensland was estimated to have net emissions from land-use change in the range of 0.45-0.25 t CO2-e ha-1 year-1. The difference between regions reflects continuation of higher rates of deforestation in Queensland until strict regulation in 2006 whereas native vegetation protection laws were introduced earlier in New South Wales. On the basis of liveweight produced at the farm-gate, emissions from direct land-use change for 1990-2010 were comparable in magnitude to those from other on-farm sources, which were dominated by enteric methane. However, calculation of land-use change impacts for the Queensland region for a period starting 2006, gave a range from net emissions of 0.11 t CO2-e ha-1 year-1 to net removals of 0.07 t CO2-e ha-1 year-1. This study demonstrated a method for deriving spatially- and temporally consistent datasets to improve estimates for direct land-use change impacts in life cycle assessment. It identified areas of uncertainty, including rates of sequestration in woody regrowth and impacts of land-use change on soil carbon stocks in grazed woodlands, but also showed the potential for direct land-use change to represent a net sink for GHG.

Spatially explicit perceptions of ecosystem services and land cover change in forested regions of Borneo

Spatially explicit information on local perceptions of ecosystem services is needed to inform land use planning within rapidly changing landscapes. In this paper we spatially modelled local people's use and perceptions of benefits from forest ecosystem services in Borneo, from interviews of 1837 people in 185 villages. Questions related to provisioning, cultural/spiritual, regulating and supporting ecosystem services derived from forest, and attitudes towards forest conversion. We used boosted regression trees (BRTs) to combine interview data with social and environmental predictors to understand spatial variation of perceptions across Borneo. Our results show that people use a variety of products from intact and highly degraded forests. Perceptions of benefits from forests were strongest: in human-altered forest landscapes for cultural and spiritual benefits; in human-altered and intact forests landscapes for health benefits; intact forest for direct health benefits, such as medicinal plants; and in regions with little forest and extensive plantations, for environmental benefits, such as climatic impacts from deforestation. Forest clearing for small scale agriculture was predicted to be widely supported yet less so for large-scale agriculture. Understanding perceptions of rural communities in dynamic, multi-use landscapes is important where people are often directly affected by the decline in ecosystem services.

Human health risk of toxic chemical pollutants generated from traffic and land use activities

The research project developed a quantitative approach to assess the risk to human health from heavy metals and polycyclic aromatic hydrocarbons in urban stormwater based on traffic and land use factors. The research outcomes are expected to strengthen the scientifically robust management and reuse of urban stormwater. The innovative methodology developed can be applied to evaluate human health risk in relation to toxic chemical pollutants in urban stormwater runoff and for the development of effective risk mitigation strategies.

Predictive technology and natural hazards: Risk for Australian planning authorities?

Purpose The object of this paper is to examine whether the improvements in technology that enhance community understanding of the frequency and severity of natural hazards also increased the risk of potential liability of planning authorities in negligence. In Australia, the National Strategy imposes a resilience based approach to disaster management and stresses that responsible land use planning can reduce or prevent the impact of natural hazards upon communities. Design/methodology/approach This paper analyses how the principles of negligence allocate responsibility for loss suffered by a landowner in a hazard prone area between the landowner and local government. Findings The analysis in this paper concludes that despite being able to establish a causal link between the loss suffered by a landowner and the approval of a local authority to build in a hazard prone area, it would be in the rarest of circumstances a negligence action may be proven. Research limitations/implications The focus of this paper is on planning policies and land development, not on the negligent provision of advice or information by the local authority. Practical implications This paper identifies the issues a landowner may face when seeking compensation from a local authority for loss suffered due to the occurrence of a natural hazard known or predicted to be possible in the area. Originality/value The paper establishes that as risk managers, local authorities must place reliance upon scientific modelling and predictive technology when determining planning processes in order to fulfil their responsibilities under the National Strategy and to limit any possible liability in negligence.

Land use regression model (LUR) for ultrafine particles in Brisbane

Traffic-related air pollution has been associated with a wide range of adverse health effects. One component of traffic emissions that has been receiving increasing attention is ultrafine particles(UFP, < 100 nm), which are of concern to human health due to their small diameters. Vehicles are the dominant source of UFP in urban environments. Small-scale variation in ultrafine particle number concentration (PNC) can be attributed to local changes in land use and road abundance. UFPs are also formed as a result of particle formation events. Modelling the spatial patterns in PNC is integral to understanding human UFP exposure and also provides insight into particle formation mechanisms that contribute to air pollution in urban environments. Land-use regression (LUR) is a technique that can use to improve the prediction of air pollution.

Cities in the airports 'shadow' : underlying interests and discretionary power in airport-region development

The previously distinct boundary between airports and their cities has become increasingly blurred as new interests and actors are identified as important stakeholders in the decision making process. As a consequence airport entities are more than ever seeking an integrated existence with their surrounding regions. While current planning strategies provide insights on how to improve and leverage land use planning in and around airports, emerging challenges for implementing and protecting these planning ideals stem from the governance shadows of development decisions. The thesis of this paper is that improving the identification, articulation and consideration of city and airport interests in the development approval process (between planning and implementation) can help avoid outcomes that hinder the ability of cities and their airports to meet their separate/mutual long-term objectives. By applying a network governance perspective to the pilot case study of Brisbane, analysis of overlapping and competing actor interests show how different governance arrangements facilitate (or impede) decision making that protects sustainable ‘airport region’ development. ---------- Contributions are made to airport and city development decision makers through the identification and analysis of effective and ineffective decision making pathways, and to governance literature by way of forwarding empirically derived frameworks for showing how actors protect their interests in the ‘crowded decision making domain’ of airport region development. This work was carried out through the Airport Metropolis Research Project under the Australian Research Council’s Linkage Projects funding scheme (LP0775225).

Integrated sustainable urban infrastructure management: the Brisbane urban growth model

Sustainable urban development and the liveability of a city are increasingly important issues in the context of land use planning and infrastructure management. In recent years, the promotion of sustainable urban development in Australia and overseas is facing various physical, socio-economic and environmental challenges. These challenges and problems arise from the lack of capability of local governments to accommodate the needs of the population and economy in a relatively short timeframe. The planning of economic growth and development is often dealt with separately and not included in the conventional land use planning process. There is also a sharp rise in the responsibilities and roles of local government for infrastructure planning and management. This increase in responsibilities means that local elected officials and urban planners have less time to prepare background information and make decisions. The Brisbane Urban Growth Model has proven initially successful in providing a dynamic platform to ensure timely and coordinated delivery of urban infrastructure. Most importantly, this model is the first step for local governments in moving toward a systematic approach to pursuing sustainable and effective urban infrastructure management.

Brisbane urban growth model : an integrated infrastructure management framework for Brisbane, Australia

In recent years, local government infrastructure management practices have evolved from conventional land use planning to more wide ranging and integrated urban growth and infrastructure management approaches. The roles and responsibilities of local government are no longer simply to manage daily operational functions of a city and provide basic infrastructure. Local governments are now required to undertake economic planning, manage urban growth; be involved in major infrastructure planning; and even engage in achieving sustainable development objectives. The Brisbane Urban Growth model has proven initially successful to ensure timely and coordinated delivery of urban infrastructure. This model may be the first step for many local governments to move toward an integrated, sustainable and effective infrastructure management.

The airport city : a new business model for airport development

The airport city concept has been embraced by many airports of different scales and in varied ways around the world. Airports everywhere have diversified their landside revenues with non-aviation commercial and industrial development in order to increase revenues and spread risk in the notoriously volatile aviation market. As intermodal hubs in a connected, globalised world, airports have evolved from transportation nodes into multi-faceted business enterprises. They have assumed a critical role as ‘transactional’ spaces in the global economy (Gottdiener 2001).

Carrying capacity dashboard analyses : Australian case studies of populations scaled to place

In a globalised world, it makes sense to examine our demands on the landscape through the wide-angle lens of ecological footprint analysis. However, the important impetus towards a more localised societal system suggests a review of this approach and a return to its origins in carrying capacity assessment. The determination of whether we live within or beyond our carrying capacity is entirely scalar, with national, regional and local assessments dependent not only on the choices of the population but the capability of a landscape - at scale. The Carrying Capacity Dashboard, an openly accessible online modelling interface, has been developed for Australian conditions, facilitating analysis at various scales. Like ecological footprint analysis it allows users to test a variety of societal behaviours such as diet, consumption patterns, farming systems and ecological protection practices; but unlike the footprint approach, the results are uniquely tailored to place. This paper examines population estimates generated by the Carrying Capacity Dashboard. It compares results in various scales of analysis, from national to local. It examines the key behavioural choices influencing Australian carrying capacity estimates. For instance, the assumption that the consumption of red meat automatically lowers carrying capacity is examined and in some cases, debunked. Lastly, it examines the implications of implementing carrying capacity assessment globally, but not through a wide angle lens; rather, by examining the landscape one locality at a time.

The potential influence of Neoliberalism on the capacity and form of spatial adaptation

Human spatial environments must adapt to climate change. Spatial planning is central to climate change adaptation and potentially well suited to the task, however neoliberal influences and trends threaten this capacity. This paper explores the potential interaction of emerging research areas, the first of which pursues climate change adaptation through spatial planning and the second of which has observed the neoliberalisation of urban planning, The potential capacity and form of spatial adaptation within the context a planning environment influenced by neoliberal principles is evaluated. This influence relates to the themes of spatial scale, temporal scale, responsibility for action, strategies and mechanisms, accrual of benefits, negotiation of priorities and approach to uncertainty. This paper presents a conceptual framework of the influence of neoliberalism on spatial adaptation and presents examples of this approach in documents which underpin adaptation in Australia. It identifies the potential characteristics and the challenges and opportunities of spatial adaptation under a neoliberal frame. The neoliberal frame does not entirely preclude spatial adaptation but significantly influence its form. Neoliberal approaches involve individual action in response to private incentives and near term impacts while collective action, regulatory mechanisms and long term planning is approached cautiously. Challenges concern the degree to which collective action and a long term orientation are necessary, how individual adaptation relates to collective vulnerability and the prioritisation of adaptation by markets. Opportunities might involve the operability of individual and local adaptation, the existence of private incentives to adapt and the potential to align adaptation with entrepreneurial projects.