Life Cycle Thinking - Science topic

Hello!

First of all, I'd argue that results for toxicity impact categories should not be compared directly among each other, as they reflect different midpoint impact categories entirely. Many compounds will only have characterization factors (CF) for some of the impact categories, and those that have CFs for more than one, might have disproportionately larger CFs for one (e.g. marine ecotoxicity), compared to for example freshwater ecotoxicity.

Given that these CFs depend on:

1) Dose-response relationship (effective dose causing a disease probability of 50% for a specific intake of the emission).

2) Exposure and Fate (fraction of the mass emitted into a specific compartment and assimilated by the population, by ingestion and inhalation).

The CFs will vary among different categories according to how these two variables are affected, respectively. Also, human toxicity factors many times are extrapolated from those of animal species, thus results for human and animal toxicities, probably should not be directly compared.

I'd suggest you read this thorough manual on the USEtox tool if you want to learn more on the CFs behind toxicity impact categories.

(https://usetox.org/sites/default/files/support-tutorials/USEtox_Manual.pdf). The toxicity model in CML uses the same rationale that USEtox uses.

Moreover, it is also important to note that similar models to USEtox derive CFs for marine and terrestrial ecotoxicity which deviates from consensus in the sense that data for dose-response curves in marine and soil species is more limited. Tipically, there is more data for freshwater species dose-response curves, as well as for humans.

ILCD discusses this a bit more in detail in their 2011 recommendations (https://eplca.jrc.ec.europa.eu/uploads/ILCD-Recommendation-of-methods-for-LCIA-def.pdf).

Hope my answer is helpful!

Kind regards,

Gustavo

Please refer to the database manual attached in the following link:

What a great discussion! Thanks, Geoffrey for asking that important question! During our project on collaborative consumption, I think it is not an understatement to say that we struggled a lot regarding semantics! While semantic is, after all, just semantic, I think it is, however, very critical in this case.

If the goal is to make sure we move toward a more sustainable direction (and maybe it means giving up on growth), then we need to assess all potential social and environmental impacts and come up with solutions to avoid them. [Note that I omit the economic pillar of sustainability because, as mentioned above, maybe the solutions should be harmful to our current economic system (however, we have to stay cautious as social and economic wellbeing can be correlated (a slow and thoughtful degrowth could enhance our social wellbeing, not so sure about a sudden collapse of our current economic system)]. Then it's a matter of properly accounting for all potential social and environmental impacts including those from what we can call "unforeseeable effect" for now. That's where semantics matter: we need to know what method can properly account for what type of unforeseeable impacts and that implies naming those impacts. This is also important to avoid double counting some of those impacts.

Now, I think there is a bit of confusion in this discussion regarding what a traditional LCA can do. Yes, it can account for burden-shifting (from one life cycle stage to another, or one type of environmental impact to another), but needs more refinements for other types of unforeseeable effects. If we want to account for burden-shifting from environmental to social impacts (think biofuels), then we will need LCSA. If we want to account for impacts occurring outside the LCA product system (i.e., its life cycle, from cradle to grave) we need consequential LCA or hybrid LCA (i.e., input-output & LCA) to account for impacts from the whole economy that our product systems (as we often compare several systems) cause. And like you said if we need to know what impacts occur because the consumer thinks "I stopped eating meat, I am already making an effort to have a more sustainable life, so it's okay, today I can take my car rather than the bus", then we probably need a psychology model in addition to LCA. (And so on with probably most of the other types of unforeseeable effect we can come up with). So yes, we've come a long way with LCA and system thinking, but practically, we are often still far from accounting for everything in our assessments (because it is so complex!). Even when doing hybrid-LCA, which can account for the entire global economy, we are still missing the informal economy (just a few trillion $...). Behaviors may change suddenly (a great example is what's happening currently with covid) and so one psychological mechanism creating impacts may not be valid anymore (if we take the example above in a covid context, "I stopped eating meat, I am already making an effort to have a more sustainable life, I don't commute anymore because I work at home due to covid, so it's okay, I can treat myself and take the plane for a vacation abroad (if travel's allowed!)"). So again, it is extremely difficult to account for all impacts occurring in different scenarios.

There is also some caution to take when talking about the rebound effect. It's not a synonym to backfire, so it does not necessarily negate all the benefits of efficiency improvements. Sometimes a rebound effect can also be positive for the environment (e.g., if a consumer has more money because of a lower electricity bill due to improved thermal insulation, he may decide to spend that gain in purchasing the same number of products but of higher quality, for instance, organic food instead of conventional food, a more durable car or purchase new products but with negative carbon footprints (e.g., purchase trees for their garden)). While I agree that the problem is complex, I am not sure we can just say "rebound effect will always negate all improvements we are trying to make, no matter what we do".

So proper semantics, and identifying possible "unforeseeable effects" when designing new products/solutions (and maybe we would need a better name and a clear and rigorous definition for unforeseeable effects) is I think critical to i) choose proper methods, ii) account for as much potential social and environmental impacts as possible, and iii) avoid double-counting (as two combined methods could be assessing the same impacts (e.g., in the case of hybrid-LCA where most proposed methods have mechanisms to avoid double-counting)). It is also crucial to have semantics properly characterizing each of those unforeseeable effects (e.g., based on their causal mechanisms), again, in order to avoid double-counting! (A change of behavior described by a psychological model and a re-spending effect described by an economic theory may give different explanations of a causal mechanism but account for the same unforeseen effect (and so applying both models at the same time to evaluate impacts would not make sense)).

As for the original question:

-Warm glow (also called moral cleansing, guilt reduction): feeling good about an action believed to be sustainable although it may not actually be the most sustainable one. (Doorn & Kurz 2021)

-Pro-environmental behavior spillover: Maki et al. 2019 provide an elegant and succinct definition: "When people engage in a first pro-environmental behaviour (PEB1; for example, conserving energy at home), are they more or less likely (positive and negative spillover, respectively) to engage in other pro-environmental behaviours (‘PEB2’; for example, conserving water at home)?" (Maki et al., 2019).

-Boomerang effect (I think I have seen it used as a synonym of the rebound effect, thus the importance of proper semantics!): based on subjective norms - where consumers realize that their peers consume more (or behave worse) and begin increasing consumption (or behave worse) (Wynes et al., 2018).

-Rebound effects are sometimes called ripple effects.

-Not strictly an unforeseeable effect but regroup some of the effects identified in psychological studies: self-licensing = the way people feel psychologically licensed to act. The consequence is: people are more likely to behave in ways they can justify easily. (Parguel et al., 2017). (Again, it can relate to the sort of mental balance we have regarding how sustainable are each of our activities ("I can let myself do this because I have done that")).

Hope that helps rather than further muddy the waters.

I had a similar comment from a reviewer and solved it by proposing a sensitivity analysis

I believe that based on the time of each crop on land (land occuparion/year - m2a) per year could be an interesting one. This approach have some limitations due to the economic value of each crop and on the differences of cultivation time from one producer to another or even between harvests. The economic approach could also be applied but considering that depending on the year and the climatic conditions (e.g. droughts and frosts) the economic value of the crop could be very low, this situation would result in a high degree of variability.

Thanks

Dear Walther Zeug,its an important question pertaining to LCIA

& LCSA.I hope the following article can help you.

1."Sustainability and Life Cycle Assessment in Industrial Biotechnology: A Review of Current Approaches and Future Needs"

doi: https://doi.org/10.1007/10_2020_122

2. A critical view on the current application of LCA for new technologies and recommendations for improved practice

Regards,

Md OsimAquatar

CSIR-NEERI,INDIA

Following.

Rising costs could be due to many factors. Apart from volatility and supply -demand imbalance ,the reasons could range from political , trade agreements between few countries at the cost of others and calamities(Covid-19). Single source supplier could also create havoc in manipulating prices. As regards resource depletion, it is not as if it happens within a short period. The industries are all well informed about the availability of raw materials and accordingly are working on newer technologies so as to reduce dependence on the depleting resources. In fact tech disruptions have become so common that new products with better features at less cost are replacing the existing ones. Coal( nuclear), petrol( Hybrid) etc are examples of depleting resources and alternatives

Dear all,

sounds very interesting. Just one recommendation: i would also recommend to include social effects (S-LCA) in a holistic (social+environmental+economic) and systemic (complete value-chain and stakeholders) LCA. We have published some papers on S-LCA and at the moment i'am working on a framework for holistic LCSA (social+environmental+economic). This framework will be based on the SDGs and the concept of Societal Relations to Nature (SRN) which was developed by Christoph Görg from the BOKU. Maybe there is some potential in the future to develop things together.

All the best

I believe any LCA study that considers categories such as Cumulative Energy Demand and Water use can generate effective value and results for a company. This types of categories (that might be considered the impact for some and inventory by others) are very straight forward and easy to visualize. Additionally, LCA is currently being carried out as a hybrid methodology, being used jointly to LCC and other cost methodologies and even S-LCA.

Absolutely it has to be curbed by human only because humans have degraded the environment.

Pollution can be reduced by us by strict observation of following aspects:

1. Reducing the use of personal vehicles and using mass transportation facilities

2. Using battery operated vehicles and using sustainable energy

3. Harnessing solar energy and preventing use of coal and non renewable resources

4. Following water efficient theories and water harvesting philosophy

5. Reduce reuse substitute technology implementation

6. Constructing Green Buildings and following green architectural principles- passive building concepts

7. Application of energy conservation in all infrastructure projects

8.Using building automation and controls for reducing energy, water and wastewater generation

9. Implementing drip and such other conservative but successful irrigation techniques and..... and .....

Hello,

I thought this paper might be relevant, but have not been able to access the full text:

Holstein, J. A., & Gubrium, J. F. (2007). Constructionist perspectives on the life course. Sociology Compass, 1(1), 335-352.

I was not sure about constructivist and constructionist, but found this by Charmaz:

Charmaz, K. (2008). Constructionism and the grounded theory method. Handbook of constructionist research, 1, 397-412.

This dissertation using constructivist grounded theory:

Stemmler, M. S. (2012). Methamphetamine Using Mothers: Perceptions of Prepregnancy Sexual Risks, Recognizing Unintended Pregnancy, and Engaging in the Pregnancy.

. . . also used concepts from this paper:

Hser, Y. I., Longshore, D., & Anglin, M. D. (2007). The life course perspective on drug use: A conceptual framework for understanding drug use trajectories. Evaluation Review, 31(6), 515-547.

But apart from these, I have not found anything relevant. It will be interesting is you have responses from anyone who is conversant with both these perspectives. I have only used constructivist grounded theory.

Very best wishes,

Mary

You may find this paper beneficial: Does it matter which Life Cycle Assessment (LCA) tool you choose? – a comparative assessment of SimaPro and GaBi. 

Hello everybody! Does anyone have any idea about translog functional form? 

please message me how i can help out.  thanks

Kim is dead on about so many things.  My experiences with ERP implementation and use at my institution(s) mirrors her experience, and her observations are very accurate.  I often feel like "if they had only asked me, I would have told them."  So many things that I do that are cumbersome as a consequence of the way the system works could be easy and efficient (I am an IT person with an OM background, so I know a good bit about ERP and my expectations are not unreasonable).  It is not that the system is not capable of doing such things, but rather those things were not planned for and done because "no one asked us".  Many of the complaints I hear from those in other job roles besides faculty are essentially the same.  Why must I do it this way?  While I do realize that it is sometimes necessary to adjust one's processes to fit the system (according to best practice, ideally), many times that is not the case.  I suspect at other institutions the IT situation may be similar to that at my current institution--they are overworked and underpaid, and there is simply not sufficient manpower to tailor the system to user needs!

If I understand you correctly then perhaps you 

1. Can stretch your scale intuitively. You can have a 10 point scale with 1-5 for positive/yes/pass (1) and 6-10 for negative/no/fail (0).

2.Might also be interested in Cluster Analysis

Data availability is one of the biggest problems on LCA so very often practitioners have to use "proxy" data. The main problem with proxies is that your result will have a huge uncertainty and probably will be not representative. A approach would be to identify the contributions to impact and to variation. This will show you which are the most important processes. With this information you can try to characterize the data based on your local data. This is still a proxy but your veriablity and ucnertaitny will be known if not reduced. If you can, try to get ecoinvent 3, this database have the option of getting global values, which can be used with a know level of certainty. 

E

Indeed if the same processes are considered there should be no difference. But you have also to consider that the implementation of CeD or Cex on SIMA might differ from other calculations or software. there is also the unceratainty asociated to the implementation of the database. So a difference might appear due to these two factor and not due to the methods on its self.

I have no studies at hand, maybe you want to approach the small appliances industry about that.

As a zeroth approximation just measure the energy consumption during use phase under different usage types, make up a scenario of duration and frequency of usage types and multiply the thus computed life-cycle energy consumption by typical LCA results from the country of operation. This of course assumes, that production, packaging, transport and end-of-life treatment are all negligible in terms of environmenal burdens. Usually a somewhat valid assumption for household appliances.

Depending on the scope of your study, this might suffice or not: As a first approximation: take a microwave oven apart and measure the weight and/ or number of components and estimate their material composition. Then use a professional LCA software with database (GaBi, SimaPro, Umberto plus Ecoinvent, ELCD, etc) and compute the LCA yourself. Since you only have components and weights, you will have to figure out the processing inputs for machining, packaging, etc. There are good estimates on this in most databases. For the use phase, simply ask an appropriate number of users (~30) about their usage patterns: how often and how long do they use it at what power settings, etc. The end-of-life phase can again be based on general recycling quotas for WEEE. I belive you can do this within 2 weeks.

As I said, this is for first approximation. If you wanted data on "the global average microwave oven" you would have to dig a lot deeper and spend considerably more time!

I am curious - have you found the UNEP/SETAC document on global guidance principles for LCA databases useful  in building the Egyptian database?

Hi Diogo,

we did the evaluation of the embodied material, energy and emergy of eucalyptus biomass in Brazil, which may help you on getting data from field. It was both evaluated in volume and energy as functional unit. Links are attached below.

A PhD student of mine is evaluating the biomass options to mitigate GHG emission from fossil liquid fuels in terms of exergy because our goal is to evaluate in terms of useful energy to determine the quality of carbon (energy supply + global warming) instead of quantity (just avoiding global warming).

Best regards,

Many thanks for your information, yes please i need the LCIA computation methods.

If I understand correctly, you need to develop a LCA inventory database for cement. Although many LCA software can be helpful in terms of providing guidance, you need to define the system for yourself. The very first step would be to sketch the life cycle in form of a system (flow diagram) starting from mining, manufacturing, process waste management (such as cement kiln dust (CKD), distribution, use and end of life (demolition of structures and possible land disposal or recycling). We can go through quite a detail discussion here, however, shortly, the most important issue would be to first identify emission sources at each and every step of the life cycle and quantify them. This will need considerable data on previously measured emissions (to air, water and soil) or alternatively you will need to measure them yourself (which I presume would not be quite an option in terms of costs unless you have the adequate funds for that). You can also use emission factors published by various sources such as the US EPA, data base provided by Sima-Pro software (a good one actually) and try to modify them for your country where the technology may or may not be different than US or Europe. For the distribution part you will have to see your national air quality control standards and data. I suggest you have a look at the SimaPro data base and see if you can find relevant data.

Use free softwares such as OpenLCA or paid ones such as GaBi

One reason why LCA was invented is to avoid trade-offs. Since no LCA is ideal, some trade-offs may persist and can be handled with sinsitivity analyses.

Walter Kloepffer

I need to make a comparison among them.

because it works like a black box. It is a big question whether or not its database completely is trustable and so forth. But forget about this negative aspect of this software. It has been used in different studies. I have also applied it in my several studies.

Reading this discussion, I have the feeling that the question of Ahmed has not been answered yet. One of the easiest ways to calculate CO2 (equivalent) emissions of a building is to use the data in the excel tables which an be found at www.ecocostsvalue.com tab data. The tables contain the kg CO2 euqivalent of materials from cradle to gate, applying LCIs from Ecoinvent and Idemat, calculated by Simapro. For the use phase data for electricity, oil and gas are given as well. the way how to make these "fast track LCA" calculations is explained at the same website

try the free and open source software Open LCA