The current port development situation requires detailed logic and supporting analysis for the expected energy and air emissions impact of new projects. This article defines a process for using advanced simulation model output to support a container terminal planning process. This article is a proposed approach to the support of environmental planning documents for container and intermodal terminals, including a detailed analytical support for emissions studies, using simulation models. These models provide an accurate representation of air and noise emissions, and consumption of energy, not only by location of operating hours, but also emissions for high acceleration and idling areas. The models also allow for the evaluation of energy saving technologies, such as energy regeneration and start-stop systems on engines. We provide sample results for a representative terminal.
Results from an analysis of this kind provide the following
• Understanding of energy and environmental impacts of container terminal alternatives, in much higher detail than spreadsheet calculations
• Differences between operating modes and strategies
• Support for permission efforts, showing relative environmental benefits of the proposed actions
• Support for board presentations to show that a given project is‘green’, or reduces energy use
One result of the output is the ability to provide data on pointsource emission within a facility. This is in contrast to data that is aggregated for a whole facility or region.
In Figure 1, the result is intuitively interesting, and supports an increased level of study where concern for proximity of employees to emission sources is relevant. This proximity has now become an issue at Southern California ports, since the California Air Resources Board (ARB) declared diesel particulate matter (PM) a toxic air contaminant: ‘Diesel engines emit a complex mixture of air pollutants, composed of gaseous and solid material. The visible emissions in diesel exhaust are known as particulate matter, or PM, which includes carbon particles or ‘soot.’ In 1998, ARB identified diesel PM as a toxic air contaminant, based on its potential to cause cancer, premature deaths, and other health problems. Health risks from diesel PM are highest in areas of concentrated emissions, such as near ports, rail yards, freeways, or warehouse distribution centers. Exposure to diesel PM is a health hazard, particularly to children, whose lungs are still developing, and the elderly, who may have other serious health problems.’
Besides PM, diesel emissions include the following potentially harmful pollutants: nitrogen oxides (NOx), sulfur oxides (SOx),carbon dioxide (CO2), and hydrocarbons (HC). In excessive quantities, each of these can have harmful health effects. This paper will not expound on the pollutants, but will focus on how to study the engines and site options. These results can then feed into an evaluation of pollutant levels that also considers the engine and fuel type, and local sensitivity and limits. It is the focus of many ports to reduce diesel exhaust and other potentially negative effects of terminal operations. This paper presents a way to extend the study of future port alternatives (renovation or new-build) to the relative environmental impacts of the options.
We demonstrate the application of simulation models in energy consumption and pollution investigations for a fictitious container terminal. In our detailed simulation tool TIMESQUARE, we have built a typical rubber tired gantry crane (RTG) terminal designed for 700,000 TEU/yr throughput, with six ship-to-shore (STS) cranes and 26 RTGs. Quay cranes are served with five dedicated Terminal Trucks (TT) each. We assume TTs and street trucks will drive a maximum 30 km/h (8.4 m/s) on the terminal.
The terminal consists of 24 RTG storage blocks, separated into a dedicated export/transshipment area and a dedicated import area.Empty handlers operate a separate empty stack area. The terminal in this experiment is considered to have a transshipment ratio of 20 per cent, and an equal distribution of load and discharge moves at the quay. Of the containers, 85 per cent are non-reefer loads; 12 per cent empty and three per cent reefers. No special containers are considered in this example. Figures 1 and 2 are based on a peak scenario, where all six quay cranes are in operation for two vessels, and 80 trucks arrive at the terminal through the gate.
With the simulation model, we are able to measure a variety of data for each piece of equipment that is present on the terminal. In this case we measure energy use, fuel consumption, and emissions of CO2, CO, NOx and HC. All of these are configurable parameters in our model and are dependent on machine velocity, cargo weight, and acceleration or deceleration. We measure power consumption and emissions every second, based on assumptions made for our fictitious terminal. In the case of a real terminal, we would typically consult experts from the terminal and equipment manufacturers, to use accurate engine and fuel-dependent emission levels.