“There is no such thing as a free lunch” goes the old adage. Applied to technology and the environment, this saying might be “there are always environmental impacts associated with new (and old) technologies.” One important challenge in a world with limited resources and increasing environmental issues is to consider and assess whether the benefits of a new technology are sufficient to justify the risk of environmental harms. So let’s explore some ways to estimate the cost of the not-so-free lunch of novel and transformative technologies.
Proponents of nanotechnology claim almost limitless applications and opportunities to improve the lives of people. To balance this technological optimism, scientists and engineers should remain skeptical and carefully weigh the cost of nanotechnology with the associated environmental risks.
Consider a few examples. Silver nanoparticles are used as anti-bacterial agents in clothing and medical products to reduce odors and minimize bacterial exposure. But these nanoparticles also end up in wastewater treatment plants where they can also damage the beneficial bacteria used to clean the wastewater. Carbon nanotubes and fullerenes can be used for novel electronics, high strength composites, and medical drug delivery. But the energy required to manufacture and purify these nanomaterials can be orders of magnitude higher compared to current materials.
So, a critical question is: How can we quantify environmental metrics which are robust and transparent?
In recent years, Life Cycle Assessment (LCA) has emerged as a powerful method to quantify environmental impacts. It is a formal methodology, backed by the International Standards Organization (ISO), to assess a wide variety of environmental impacts including the atmosphere, hydrosphere, biosphere, and human health.
LCA considers environmental impacts for all of the life cycle phases for a product from extraction of raw materials to manufacturing to transportation to use and finally to disposal as shown below:
Schematic of the LCA Methodology
Analyzing only a portion of the life cycle can lead to incorrect conclusions regarding overall environmental impacts since benefits in one part of the life cycle might be offset by larger issues in another phase. For example, nanocellulose might be biodegradable and less toxic than other materials for use as a drug delivery system, but the environmental burden may be shifted to the strong acids and solvents required for manufacturing. The boundaries of such analyses must balance the need for a scope that is large enough to include the most significant environmental impacts, but not so large that data collection and analysis is too time-consuming or expensive.
LCA requires a detailed inventory of the inputs from and the outputs to nature for the products, processes or systems being assessed. This inventory typically includes the flows of chemicals, materials, energy and water. These inputs and outputs must then be translated into environmental impacts. For example, the same amount of titanium dioxide in bulk form versus nanoscale is likely to have different impacts due to differences in size, surface area, surface coatings, and reactivity.
The amount of environmental damage caused per amount (usually kilograms or liters) of an input or output is known as the characterization factor. These factors come from research by experts in areas including atmospheric physics, hydrology, soil science, toxicology, and ecology. The environmental impact of any input or output is the product of the amount of that material (inventory) multiplied by its severity (characterization factor). By summing the environmental impacts of all inputs and outputs for a product, an overall environmental impact – like a Consumer Report’s score – can be calculated and used for comparisons. (See our earlier post about how environmental impacts are incorporated into environmental rating systems for consumer goods.)
Up to this point, the analysis is objective, using science-based characterization factors and inventory data compiled by industry or individual analysts. However, to apply these results to decisions, the calculated environmental impacts should be weighted relative to each other for the overall environmental impact score because different stakeholders will not always have the same relative environmental preferences. For example, some people believe that water quality and availability are more important issues than climate change.
Or take chlorofluorocarbons (CFCs) for example. CFCs contribute to both global warming as well as ozone layer depletion. The global warming potential (GWP) and the ozone depletion potential (ODP) of CFCs are objective data, measurable in a chemistry lab. But any discussion on whether we should value the impact of CFCs on global warming over its impact on ozone layer depletion (or vice versa) involves subjective preferences.
Therefore, this aspect of LCA is necessarily subjective, though consensus weighting factors have been developed by various scientific groups and organizations. Because of this subjectivity, weighting is a controversial topic in LCA and it is not allowed by ISO standards for product comparisons in order to avoid bias and conflicts of interest.
Weighting aside, LCA interpretation issues also include the data uncertainty, time and spatial differences for environmental impacts, and the differences between impact assessment methods. To address these issues, LCA can use statistical modeling to consider different design options or to assess the statistical significance of the results given the various uncertainties. For nanotechnology, there are other specific LCA limitations which will be discussed in a follow-up post (Part 2).
LCA can be used to compare different life cycle phases for the same product or overall impacts for products that perform similar functions, whether or not they use nanotechnology. However, LCA is not a panacea for decision-making as environmental impacts should be considered along with economic and social metrics, often referred to as the Triple Bottom Line.
LCA does provide a formal metric for data-driven decisions, as opposed to intuition which is prone to errors due to system complexity or other biases. As a best practice, LCA is used proactively as a design tool for new products in addition to assessing existing products retroactively. This is especially critical for nanotechnology where potential environmental impacts can be much more significant than the materials size or quantities might suggest.