Land use impacts on freshwater regulation, erosion regulation, and water purification: a spatial approach for a global scale level

Purpose

Rarely considered in environmental assessment methods, potential land use impacts on a series of ecosystem services must be accounted for in widely used decision-making tools such as life cycle assessment (LCA). The main goal of this study is to provide an operational life cycle impact assessment characterization method that addresses land use impacts at a global scale by developing spatially differentiated characterization factors (CFs) and assessing the extent of their spatial variability using different regionalization levels.

Methods

The proposed method follows the recommendations of previous work and falls within the framework and principles for land use impact assessment established by the United Nations Environment Programme/Society of Environmental Toxicology and Chemistry Life Cycle Initiative. Based on the spatial approach suggested by Saad et al. (Int J Life Cycle Assess 16: 198–211, 2011), the intended impact pathways that are modeled pertain to impacts on ecosystem services damage potential and focus on three major ecosystem services: (1) erosion regulation potential, (2) freshwater regulation potential, and (3) water purification potential. Spatially-differentiated CFs were calculated for each biogeographic region of all three regionalization scale (Holdridge life regions, Holdridge life zones, and terrestrial biomes) along with a nonspatial world average level. In addition, seven land use types were assessed considering both land occupation and land transformation interventions.

Results and discussion

A comprehensive analysis of the results indicates that, when compared to all resolution schemes, the world generic averaged CF can deviate for various ecosystem types. In the case of groundwater recharge potential impacts, this range varied up to factors of 7, 4.7, and 3 when using the Holdridge life zones, the Holdridge regions, and the terrestrial biomes regionalization levels, respectively. This validates the importance of introducing a regionalized assessment and highlights how a finer scale increases the level of detail and consequently the discriminating power across several biogeographic regions, which could not have been captured using a coarser scale. In practice, the implementation of such regionalized CFs suggests that an LCA practitioner must identify the ecosystem in which land occupation or transformation activities occur in addition to the traditional inventory data required—namely, the land use activity and the inventory flow.

Conclusions

The variability of CFs across all three regionalization levels provides an indication of the uncertainty linked to nonspatial CFs. Among other assumptions and value choices made throughout the study, the use of ecological borders over political boundaries was deemed more relevant to the interpretation of environmental issues related to specific functional ecosystem behaviors.     

IMPACT World+: a globally regionalized life cycle impact assessment method

The International Journal of Life Cycle Assessment - This paper addresses the need for a globally regionalized method for life cycle impact assessment (LCIA), integrating multiple state-of-the-art...     

Farmers’ perception of termites in agriculture production and their indigenous utilization in Northwest Benin

Background

Although termites are considered as agricultural pests, they play an important role in maintaining the ecosystem. Therefore, it matters to investigate the farmers’ perception of the impacts of the termites on the agriculture and their indigenous utilization.

Methods

A semi-structured questionnaire was used to interview 94 farmers through 10 villages of Atacora department, in the northwestern region of Benin, to obtain information for the development of successful strategies of termite management and conservation. Their perceptions on the importance and management of termites along with the indigenous nomenclature and utilization of termite mounds were assessed. Termite species identified by farmers were collected and preserved in 80% alcohol for identification.

Results

Eight crops were identified by farmers as susceptible to termites with maize, sorghum, and yam as being the most susceptible. According to farmers, the susceptibility to termites of these crops is due to their high-water content and sweet taste. A total of 27 vernacular names of termites were recorded corresponding to 10 species, Amitermes evuncifer, Macrotermes subhyalinus, and Trinervitermes oeconomus being the most damaging termite species. All the names given to termite species had a meaning. The drought was identified by farmers as the main factor favouring termite attacks. Demolition of termite mounds in the fields was the most commonly reported control method. Salt and other pesticides were commonly used by farmers to protect stored farm products. The lack of effective control methods is the main constraint for termite management. In northwestern Benin, farmers reported different purpose utilizations of termite mounds and termites.

Conclusions

The study has shown that farmers perceived termites as pests of several agricultural crops and apply various indigenous control practices whose efficiency need to be verified. Utilization of termites and termite mound soil as food and medicinal resources underlines the need for a more focused approach to termite control for the conservation of non-pest termite species. The sensitization of farmers on the importance of termites as well as the development of an integrated control method to combat termite pests proved necessary.

     

Functional Interactions between Sphingolipids and Sterols in Biological Membranes Regulating Cell Physiology

Sterols and sphingolipids are limited to eukaryotic cells, and their interaction has been proposed to favor formation of lipid microdomains. Although there is abundant biophysical evidence demonstrating their interaction in simple systems, convincing evidence is lacking to show that they function together in cells. Using lipid analysis by mass spectrometry and a genetic approach on mutants in sterol metabolism, we show that cells adjust their membrane composition in response to mutant sterol structures preferentially by changing their sphingolipid composition. Systematic combination of mutations in sterol biosynthesis with mutants in sphingolipid hydroxylation and head group turnover give a large number of synthetic and suppression phenotypes. Our unbiased approach provides compelling evidence that sterols and sphingolipids function together in cells. We were not able to correlate any cellular phenotype we measured with plasma membrane fluidity as measured using fluorescence anisotropy. This questions whether the increase in liquid order phases that can be induced by sterol–sphingolipid interactions plays an important role in cells. Our data revealing that cells have a mechanism to sense the quality of their membrane sterol composition has led us to suggest that proteins might recognize sterol–sphingolipid complexes and to hypothesize the coevolution of sterols and sphingolipids.     

Uncertainty and spatial variability in characterization factors for aquatic acidification at the global scale

Purpose

Characterization factors (CFs) quantifying the potential impact of acidifying emissions on inland aquatic environments in life cycle assessment are typically available on a generic level. The lack of spatial differentiation may weaken the relevance of generic CFs since it was shown that regional impact categories such as aquatic acidification were influenced by the surroundings of the emission location. This paper presents a novel approach for the development of spatially differentiated CFs at a global scale for the aquatic acidification impact category.

Methods

CFs were defined as the change in relative decrease of lake fish species richness due to a change in acidifying chemicals emissions. The characterization model includes the modelling steps linking emission to atmospheric acid deposition (atmospheric fate factor) change, which lead to lake H⁺ concentration (receiving environment fate factor) change and a decrease in relative fish species richness (effect factor). We also evaluated the significance of each factor (i.e. atmospheric fate, receiving environment fate and effects) to the overall CFs spatial variability and parameter uncertainty.

Results and discussion

The highest CFs were found for emissions occurring in Canada, Scandinavia and the northern central Asia because of the extensive lake areas in these regions (lake areas being one of the parameters of the CFs; the bigger the lake areas, the higher the CFs). The CFs’ spatial variability ranged over 5, 6 and 8 orders of magnitude for NO_x, SO₂ and NH₃ emissions, respectively. We found that the aquatic receiving environment fate factor is the dominant contributor to the overall spatial variability of the CFs, while the effect factors contributed to 98 % of the total parameter uncertainty.

Conclusions

The resulting characterization model and factors enable a consistent evaluation of spatially explicit acidifying emissions impacts at the global scale.     

Lifting the veil on the correction of double counting incidents in hybrid life cycle assessment

Life cycle assessment (LCA) and environmentally extended input–output analyses (EEIOA) are two techniques commonly used to assess environmental impacts of an activity/product. Their strengths and weaknesses are complementary, and they are thus regularly combined to obtain hybrid LCAs. A number of approaches in hybrid LCA exist, which leads to different results. One of the differences is the method used to ensure that mixed LCA and EEIOA data do not overlap, which is referred to as correction for double counting. This aspect of hybrid LCA is often ignored in reports of hybrid assessments and no comprehensive study has been carried out on it. This article strives to list, compare, and analyze the different existing methods for the correction of double counting. We first harmonize the definitions of the existing correction methods and express them in a common notation, before introducing a streamlined variant. We then compare their respective assumptions and limitations. We discuss the loss of specific information regarding the studied activity/product and the loss of coherent financial representation caused by some of the correction methods. This analysis clarifies which techniques are most applicable to different tasks, from hybridizing individual LCA processes to integrating complete databases. We finally conclude by giving recommendations for future hybrid analyses.     

On the reporting and review requirements of ISO 14044

The International Journal of Life Cycle Assessment -     

Uncertainty analysis in LCA using precalculated aggregated datasets

Purpose

Some LCA software tools use precalculated aggregated datasets because they make LCA calculations much quicker. However, these datasets pose problems for uncertainty analysis. Even when aggregated dataset parameters are expressed as probability distributions, each dataset is sampled independently. This paper explores why independent sampling is incorrect and proposes two techniques to account for dependence in uncertainty analysis. The first is based on an analytical approach, while the other uses precalculated results sampled dependently.

Methods

The algorithm for generating arrays of dependently presampled aggregated inventories and their LCA scores is described. These arrays are used to calculate the correlation across all pairs of aggregated datasets in two ecoinvent LCI databases (2.2, 3.3 cutoff). The arrays are also used in the dependently presampled approach. The uncertainty of LCA results is calculated under different assumptions and using four different techniques and compared for two case studies: a simple water bottle LCA and an LCA of burger recipes.

Results and discussion

The meta-analysis of two LCI databases shows that there is no single correct approximation of correlation between aggregated datasets. The case studies show that the uncertainty of single-product LCA using aggregated datasets is usually underestimated when the correlation across datasets is ignored and that the magnitude of the underestimation is dependent on the system being analysed and the LCIA method chosen. Comparative LCA results show that independent sampling of aggregated datasets drastically overestimates the uncertainty of comparative metrics. The approach based on dependently presampled results yields results functionally identical to those obtained by Monte Carlo analysis using unit process datasets with a negligible computation time.

Conclusions

Independent sampling should not be used for comparative LCA. Moreover, the use of a one-size-fits-all correction factor to correct the calculated variability under independent sampling, as proposed elsewhere, is generally inadequate. The proposed approximate analytical approach is useful to estimate the importance of the covariance of aggregated datasets but not for comparative LCA. The approach based on dependently presampled results provides quick and correct results and has been implemented in EcodEX, a streamlined LCA software used by Nestlé. Dependently presampled results can be used for streamlined LCA software tools. Both presampling and analytical solutions require a preliminary one-time calculation of dependent samples for all aggregated datasets, which could be centrally done by database providers. The dependent presampling approach can be applied to other aspects of the LCA calculation chain.

     

SLC38A9: A lysosomal amino acid transporter at the core of the amino acid-sensing machinery that controls MTORC1

The mechanistic target of rapamycin (serine/threonine kinase) complex 1 (MTORC1) acts as a crucial regulator of cellular metabolism by integrating growth factor presence, energy and nutrient availability to coordinate anabolic and catabolic processes, and controls cell growth and proliferation. Amino acids are critical for MTORC1 activation, but the molecular mechanisms involved in sensing their presence are just beginning to be understood. We recently reported that the previously uncharacterized amino acid transporter SLC38A9 is a member of the lysosomal sensing machinery that signals amino acid availability to MTORC1. SLC38A9 is the first component of this complex shown to physically engage amino acids, suggesting a role at the core of the amino acid-sensing mechanism.