Considering the Energy of Labor, Part IV
This posting concludes our discussion of the energy of labor based on a paper published some time ago and the recent thesis of one of my students, Teresa Zhang. The paper, titled “Energy Use per Worker-Hour: A Method of Evaluating the Contribution of Labor to Manufacturing Energy Use,” was presented at the 14th CIRP International Conference on Life Cycle Engineering in 2007.
This does not cover this topic in any sense. But, I hope, it gets the conversation started. There will be more on this in the future for sure.
Now, back to the discussion.
The necessity of excluding industrial energy use from the calculations, as discussed earlier in this series, is observed when comparing net importers and net exporters. For example, consider the $214 billion trade deficit between the United States and China in 2006. Energy used in China to manufacture goods for sale in the United States does not contribute to the Chinese EPWH. Meanwhile, energy the United States imports in the form of products can be captured by process-based LCA.
For simplicity, these results do not consider geographic differences in the number of workers employed for any given task or the purchasing power and related energy consumption of industry workers compared to the general population.
This type of analysis raises a lot of questions and some were hinted at last time. Some industrial processes are more labor intensive than others (think apparel manufacturing or electronics assembly.) Foxconn, a Taiwanese company that is a major manufacturer of electronics products, employs close to 1 million workers and recently was in the news for an explosion at a plant with some 80,000 workers (yep – 80,000 all assembling products) due to a build up of dust (see New York Times article). This plant assembles, among other things, many of Apple’s iPads. (Supply chain issues deja vu!)
Different countries have differing impacts due to energy production or efficiencies in delivering energy to industry. How does this play into the discussion?
The biggest question … does this justify exporting all labor intensive industry to “make our numbers look good?!”
You might recall a posting last March (see Digging Deeper). In that I reviewed the work of Professor Julian Allwood at Cambridge University in the UK. He discussed in detail strategies for reducing the carbon footprint and other impacts of manufacturing. He particularly discussed these with reference to targets for reduction set by governmental agencies in the UK and elsewhere. For example, reduction targets set by the UK and EU to allow surface temperature stabilization called for a 60% absolute cut in yearly carbon emissions by 2050 compared to 1990 levels. He plotted the slope of reductions (in CO2 equivalent) needed to meet this ambitious goal along with the actual reductions observed over the first few years which seemed to track each overt reasonably well, But, then, he showed these actual reductions adjusted to “off shore” effects, that is, moving the production and associated CO2 generation out of the region of calculation (i.e. out of the UK and EU). With that, The curve of “improvement” the moved in the wrong direction – that is, diverging from the desired trajectory – due to the off-shoring.
Without quantifying the energy use of labor, it is easy to underestimate the environmental impacts of labor intensive processes such as those referred to above as well as those used in such tasks as product installation, maintenance, repair, and recycling. For example, energy payback time analyses for solar cells often do not consider panel installation, even though it is a major component of their financial cost. Evaluating the energy use of labor is necessary to determine the impact of expensive and labor-intensive solar cell installation on energy payback time.
Labor-intensive sorting processes for recycling are another important application of the energy use of labor. It is important to know the degree to which the energy expended in sorting processes counteracts the energy savings of recycling. There many benefits to recycling outside of energy savings, but the ratio of energy inputs, including that of labor, to energy savings can serve as a measure of efficiency for recycling operations.
The degree of labor required between industries can vary dramatically as pointed out earlier. In addition to electronics assembly, agriculture, handcraft, textile, and service industries are especially labor-intensive. These industries have typically not been the subject of life-cycle analysis, even though their products are consumed in relatively large quantities. Process-based LCA would in fact grossly underreport the environmental costs of a service or an entirely handmade product.
It is also interesting to note that new industries, such as the renewable energy and nanotechnology industries, typically employ more workers per unit output than more established industries. Emerging industries may present problems for LCA practitioners seeking to perform comprehensive assessments. As EIO-LCA data is not yet available for the industry in question, new technologies must be assessed using process-based or hybrid EIO-LCA. Evaluating the energy use of labor is therefore especially valuable to accurately assess the environmental impacts of new technologies and industries.
Amortizing non-industrial energy supply produces a simple estimate of energy use per worker-hour. However, there are questions regarding how to apply this information.
At first glance, the data in the figure showing electricity equivalent energy use per worker hour in part 3 of this series last time appears to present a strong argument for the export of labor-intensive industries. Yet, energy savings in labor can be easily overturned by energy use in transportation. Intercontinental shipping can consume 1.8 MJ per container-mile, based on industry standard emissions of 85 g CO2 per container-km. In the United States, a container truck expends 750 MJ per mile, in addition to the energy use of the operator. Energy analysis may be a useful tool for siting manufacturing facilities, but the energy requirements of both labor and transportation must be considered.
However, industrial final consumption does not include industrial transportation. This means that the energy use of industrial transport is not subtracted from the first equation in part 3, and is therefore encompassed by energy use per worker-hour. If used in conjunction with process-based LCA, energy use per worker-hour double counts the energy use of industrial transportation. This is a major drawback of this technique that must be addressed to be used with process-based transportation inventories.
It is also not entirely straightforward to decide the number of worker-hours to evaluate in life-cycle assessment. An employee may work eight hours a day, but he or she will continue to expend energy outside of work. Manufacturers reap the rewards of the energy expended during worker- hours in the form of value added to their products and should be responsible for a proportional amount of energy. For the purposes of process-based life-cycle assessment, we recommend calculating the energy corresponding to the number of hours actually worked.
However, one can argue that employers, as a whole, are responsible for the economic activity and corresponding energy consumption employees enjoy outside of work as a result of their hours worked. While the economic activity of both employer and employee are required to sustain manufacturing, consider a factory that employs all workers for only four hours a day. Twice the numbers of workers are needed compared to an identical factory employing workers for eight hours a day. Though these half-time employees would be compensated less and enjoy less economic activity, it is doubtful that their energy demands would be half of that of their full-time colleagues.
Another factor to consider is the effect of feedback. A facility built in a low energy use per worker-hour area may find that its presence spurs economic activity, development, and in turn, increased energy use per worker-hour. It is important to note that energy use, industrial activity, and population can change over time. To be meaningful, energy use per worker- hour should reflect up-to-date statistics.
Evaluating energy use per worker-hour is a simple and effective way to improve the accuracy and scope of life-cycle energy analysis. This 4 part discussion makes note of energy use per worker-hour as it compares to a machine tool and to worker- hours in other major manufacturing regions. The potential applications of the energy use of labor in life-cycle assessment are exceedingly broad.
If you’d like a copy of the paper on which this 4 part series is based “Energy Use per Worker-Hour: A Method of Evaluating the Contribution of Labor to Manufacturing Energy Use,” by Teresa Zhang and myself from the 14th CIRP International Conference on Life Cycle Engineering, 2007 please contact me directly.
David Dornfeld is the Will C. Hall Family Chair in Engineering in Mechanical Engineering at University of California Berkeley. He leads the Laboratory for Manufacturing and Sustainability (LMAS), and he writes the Green Manufacturing blog.
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