August 20, 2019 by Jannick Schmidt
Today we have sent out a brief press release on the findings from the Palm Oil Club project which has resulted in a detailed life cycle assessment (LCA) study of palm oil production.
The study compares the environmental impact of RSPO (Roundtable on Sustainable Palm Oil) certified sustainable palm oil with non-certified palm oil in Indonesia and Malaysia.
See the press release here: Certification of palm oil
July 24, 2019 by Ivan Muñoz
In May this year we proudly presented the third version of our wastewater inventory model, WW LCI, at SETAC Europe’s 29th Annual Meeting in Helsinki, Finland (see the presentation). This constitutes the 5th consecutive platform presentation about WW LCI in a SETAC conference, which is a good sign of the scientific interest that our model has received so far from the LCA community. We take this milestone as an opportunity to look back at the story behind our model.
The development of WW LCI started in 2015 as one of our crowdfunded projects, together with the three companies Henkel, Procter & Gamble and Unilever. Our goal was to develop a model and Excel tool to calculate life cycle inventories (LCIs) of chemicals discharged in wastewater. The choice of partners for this project (consumer goods companies) was not a coincidence. Indeed, after use, many of their products, such as shampoos, washing detergents, etc., end up discharged in wastewater around the globe, which makes wastewater LCI modelling a necessity for these companies when carrying out cradle-to-grave LCA studies. Yet, the only commonly available LCI model covering this aspect to date was the one by my good friend Gabor Doka, developed for version 2 of the ecoinvent database. With our project, we aimed at overcoming several limitations of this model. First, we wanted our tool to describe wastewater as a mixture of individual chemical substances rather than a set of generic descriptors such as chemical oxygen demand (COD). Second, we wanted to cover several sludge disposal routes, namely landfarming, landfilling and incineration. Last but not least, we aimed to include the environmental burdens of untreated discharges, which are unfortunately still very common in developing countries. Before the end of 2015, the first version of WW LCI was ready, as well as an article that would ultimately be published the next year in the International Journal of LCA.
Shortly after the development of our model, we got in touch with Prof. Morten Birkved, from the Technical University of Denmark (currently at the University of Southern Denmark), who was involved in the development of SewageLCI, an inventory model to calculate emissions of chemicals through WWTPs. We decided to join forces and integrate the two models, eventually giving rise to the second version of WW LCI, thanks to the hard work of Pradip Kalbar, current Assistant Professor at the Centre for Urban Science & Engineering (CUSE) at IIT Bombay. Pradip’s work led to key improvements in WW LCI, such as the inclusion of wastewater treatment by means of septic tanks, tertiary treatment of wastewater with sand filtration, treatment of wastewater in WWTPs with primary treatment only, treatment of sludge by composting, as well as the integration in the tool of a database containing wastewater and sludge statistics for 56 countries. Also, Pradip was responsible for our second peer-reviewed publication, this time in the journal Science of the Total Environment.
After some quiet time, in 2018 I decided to get to grips with several limitations of the model, such as the fact that it did not support discharges of metals in wastewater, but more importantly, I realized that by describing wastewater as a mixture of individual chemicals, as in e.g. a list of ingredients in a shampoo formulation, I was closing the door to many LCA practitioners who typically can only describe the pollution content in wastewater with the very generic descriptors I had rejected in the first place, namely COD, among others. Thus, I adapted the model to support metals as well as the characterization of wastewater based on the four parameters COD, N-total, P-total and suspended solids. On top of this, many additional features were implemented, mainly aimed at an improved regionalization, that is, to try and make LCIs more country-specific. Some of the improvements made included: emissions of methane from open-stagnant sewers, climate-dependent calculation of heat balance in the WWTPs, capacity-dependent calculation of electricity consumption in the WWTPs, the inclusion of uncontrolled landfilling of sludge, the specification of effluent discharges to sea water or inland water, and last but not least, expanding the geographical coverage of the statistics database from 56 to (currently) 86 countries, representing 90% of the world’s population (figure 1). The result of this effort, in short, is our third and latest version of WW LCI, presented in May at the SETAC conference.
Figure 1. Geographical coverage of the country database in WW LCI.
As an example of the current tool capabilities, the figure below (taken from the SETAC presentation) shows the carbon footprint of discharging 1 m3 of a typical urban wastewater in 81 countries. As it can be seen, there is wide variability between countries (up to a factor 6), with highest emissions in those countries where methane from open and stagnant sewers is expected to occur. On the other hand, emissions are substantially lower in countries where wastewater is properly collected and treated in centralized WWTPs. Obviously, the carbon footprint is not the only relevant metric, and WW LCI can support others just as well, including eco-toxicity.
Figure 1. Country-specific carbon footprint of discharging 1 m3 wastewater with a composition of 500 ppm COD, 30 ppm N, 6 ppm P and 250 ppm SS. Global warming potential for 100 years. Impact assessment calculations in SimaPro 8.5. Biogenic CO2 emissions considered to have global warming potential of zero.
Needless to say, WW LCI is not perfect. We can mention as main model limitations the fact that it does not address uncertainty, its data-demanding nature when used to model specific chemicals, the not-so-easy operation of the excel tool and the export of LCIs being currently limited to the software SimaPro. In spite of this, to our knowledge this is the most complete, flexible and regionalized inventory tool to model urban wastewater discharges in LCA studies and we expect it will eventually become the preferred approach for professional LCA practitioners. We are just a few SETAC presentations away from it.
June 27, 2019 by Bo Weidema
Bio-based plastics with larger effect on global warming than their fossil derived counterparts? Certified forest products that unintendedly are more harmful to biodiversity than the corresponding products from plantation forestry? No environmental effect of demanding recycled paper? All these are examples of LCA results that are not immediately intuitive. Does that mean that they are wrong? Not necessarily.
We are often met by a demand that our results should be immediately understandable and make intuitive sense. And there is no doubt that it is easier to communicate results when they are intuitive. Then they are immediately accepted, although often with a condescending “Ah, that’s typical, science just confirms what we knew already”. But it is when our results are not intuitive, as in the above examples, that there is a chance to learn something new. And this is where real change begins.
Counter-intuitive results are not wrong, they are just harder to communicate. Our common sense – just another word for prejudice – is challenged. Intuition is simply not capable of capturing the results of complex systems – at least not without a deeper explanation. But when that explanation is provided, the counter-intuitive results become intuitively right. Let me demonstrate how that works for the above examples:
Bio-based plastics with larger global warming impact than their fossil derived counterparts? Intuitively, one may think of bio-based plastics as being CO2-neutral due to the uptake of carbon from the air during biomass growth. However, that bio-based plastics have a larger effect on global warming than their fossil derived counterparts moves from being counter-intuitive to be intuitive when we understand that agriculture is not CO2 neutral (due to the need for fuel and fuel-based inputs, such as fertilisers) and even more importantly that up to half of the total greenhouse gas emission from growing biomass can come from the indirect land-use effects (iLUC), see e.g. the data for our life cycle assessments of milk.
Certified forest products that are more harmful to biodiversity than the corresponding products from plantation forestry? Intuitively, we would expect the certification to lead to lower impacts on biodiversity, since that should be one of the main reasons for the certification. And the biodiversity in the specific certified forest may indeed be higher than in non-certified forests. However, that the certification may unintendedly lead to an overall reduction in biodiversity compared to plantation forests moves from being counter-intuitive to be intuitive when we understand that the overall impact on biodiversity needs to be measured per unit of wood produced. Plantation forests have a high impact on biodiversity per area, but a low area per cubic metre of wood. This means that more area can be left untouched, with no biodiversity impact. If you have a lower output per area than plantation forests, you will need more area to produce the same – and thus impact the biodiversity on a larger area. The challenge is then to have a biodiversity impact that is so low per area that it also becomes lower per cubic metre of wood. This is what we call “biodiversity-managed forests”. However, in practice, it is very difficult to have low impact on biodiversity when you harvest even rather small amounts the wood that would otherwise be “food” for a large share of this biodiversity (“deadwood”). Therefore, most certified forests have higher biodiversity impacts per unit of produced wood than a plantation forest, i.e. they lie above the iso-biodiversity line in the figure below, taken from our criteria for good biodiversity indicators for forest management.
No environmental effect of demanding recycled paper? When we know that the production of recycled paper has lower impacts than virgin paper, we intuitively think that it must be beneficial for the environment to buy recycled paper. And companies that use recycled paper want to be credited for this and brag about it on their product labels. However, that there is in practice no beneficial effect moves from being counter-intuitive to be intuitive when we understand that the amount of recycled paper is not driven by demand but by supply. The market for recycled paper is constrained by the availability of waste paper. So, an increase in recycling can only come about by throwing more paper in the recycling bins, not by demanding more recycled paper. This is so for all materials where there is a well-functioning collection system. For other materials, such as plastics, there may still be situations where the market is driven by demand. And the market situation can change over time, which has caused a lot of confusion about how to apportion the burdens and credits for recycling as described in one of our previous blog-posts.
March 13, 2019 by Randi Dalgaard
Yesterday marked the release of a new strategy from Arla Foods launching their targets to accelerate the transition to sustainable dairy production.
The new strategy has an increased focus on the farms and we are pleased to see how our climate tool has now been applied to 5000 individual farms. The tool calculates climate footprints for the milk from each farm and thus demonstrates to the farmer where the CO2 emissions originate.
The numbers are a motivation in themselves, and often climate ’savings’ may also entail cost savings according to Jan Toft Nørgaard, a milk producer himself and chairman of Arla Foods.
In the project for Arla we have calculated climate footprint since 1990 and the Arla farmers have reduced their emissions per kilogram of milk by 24 %. The current average for the Arla farmers in the study is an emission intensity of 1.15 kg CO2 per kilogram of milk, which is approx. half of the global average, which is 2.5 kg CO2 (according to FAO).
Links to more information:
Arla press release (in Danish): https://www.arla.dk/om-arla/nyheder/2019/pressrelease/fremtidens-mejeriprodukter-skal-vaere-klima-neutrale-2845584/
Our project with ARLA is described in more detail here: https://lca-net.com/projects/show/carbon-footprint-milk/