Direct amplification of new cellulase genes from woodland soil purified DNA

Eight genes encoding cellulolytic enzymes were obtained by direct PCR amplification of genomic DNA recovered from woodland soil samples. The direct amplifications were carried out by using primers designed from available online cellulase nucleotide sequences. The isolated genes were all different from each other and homologous to endo-β-1,4-glucanases of Bacillus subtilis. The cellulases were functionally expressed in Escherichia coli and tested on soluble substrate at 37 and 60 °C, showing different cellulolytic activities. Among these, the enzyme renamed CelWS6 exhibited good activity at higher temperatures. Further analysis of CelWS6 showed a high performance in acid environments (between pH 4.0 and 6.0) and at elevated temperatures with its maximum activity at pH 5.0 and 50 °C. At the optimum pH, it was very stable since more than 80 % of its original activity was maintained after an incubation of 120 min at 60 °C. Because the cellulases had different cellulolytic activities, but similar amino acid sequences, it was possible to assess the relationship between sequence and protein function.     

Integrating strategic environmental assessment and material flow accounting: a novel approach for moving towards sustainable urban futures

Purpose

The population living in urban areas of the world continues to grow rapidly. It is, thus, a great priority for the planning practice to embed sustainability concept in their urban development endeavors. Currently, development and expansion of urban systems stress the need to control consumption of resources, especially non-renewable ones. There is also a need to reduce related environmental impacts, while stimulating a sustainable pathway for the population and urban growth.

Methods

Strategic environmental assessment (SEA) is useful for policy design to build an integrated method for supporting the development of a sustainable society. It undertakes territorial assessments and describes urban flows and impacts related to them by using a variety of tools, including material flow accounting (MFA). This study employs MFA, as it fits well within the scope of SEA and supports the growing environmental attention in the urban metabolism approach. Although helpful, MFA has not been systematically applied in the urban development context; for this reason, this paper proposes the integration of SEA and MFA.

Results and discussion

Integration of SEA and MFA generates a new framework for sustainable development planning. The framework is structured in phases oriented to the continual improvement based on the Deming cycle (i.e., plan, do, check, act), a key management approach mainly used in businesses for improving the effectiveness of an organization. It can also be implemented at the urban system level. In order to maintain normative compliance, each process (urban planning, strategic environmental assessment with urban metabolism approach, participatory processes) is standardized in line with a common and mandatory approach. While the processes are integrated among them, highlighting the reciprocal contact points, the results are combined in a holistic perspective. The framework, hence, transforms the voluntary MFA tool into a mandatory process.

Conclusions

The proposed SEA-MFA framework has the potential to unify and standardize the processes of categorizing and quantifying data in order to improve the understanding of urban metabolic principles and scale effects. It also supports management and policy development and meets the requirements of different stakeholders. The framework, thus, generated a novel approach for sustainable urban development planning by providing solutions for specific policy problems and ensuring urban ecological balance and sustainable urban futures.

     

Noise footprint from personal land‐based mobility

A large part of the world population is exposed to noise levels that are unhealthy. Yet noise is often neglected when impact assessment studies are conducted and when policy interventions are designed. In this study, we provide a way to calculate the noise footprint of citizens directly determined by their use of private and public transport on land. The study combines the results of the large transport simulation model MATSim applied to Switzerland, with a noise characterization model, N‐LCA, developed in the context of life cycle assessment. MATSim results allow tracking the use of private and public transportation by agents in the model. The results after characterization provide a consumption‐based noise footprint, thus the total noise and impacts that are caused by the private mobility demand of the citizens of Switzerland. Our results confirm that road transportation is the largest contributor to the total noise footprint of land‐based mobility. We also included a scenario with a full transition to an electrified car fleet, which showed the potential for the reduction of impacts, particularly in urban areas, by about 55% as compared to the modeled regime with combustion engines.     

No Matter – How?: Dealing with Matter‐less Stressors in LCA of Wind Energy Systems

The portfolio of impacts that are quantified in life cycle assessment (LCA) has grown to include rather different stressors than those that were the focus of early LCAs. Some of the newest life cycle impact assessment (LCIA) models are still in an early phase of development and have not yet been included in any LCA study. This is the case for sound emissions and noise impacts, which have been only recently modeled. Sound emissions are matter‐less, time dependent, and bound to the physical properties of waves. The way sound emissions and the relative noise impacts are modeled in LCA can show how new or existing matter‐less impacts can be addressed. In this study, we analyze, through the example of sound emissions, the specific features of a matter‐less impact that does not stem from the use of a kilogram of matter, nor is related to the emission of a kilogram of matter. We take as a case study the production of energy by means of wind turbines, contradicting the commonly held assumption that windmills have no emissions during use. We show how to account for sound emissions in the life cycle inventory phase of the life cycle of a wind turbine and then calculate the relative impacts using a noise LCIA model.     

Towards a general framework for including noise impacts in LCA

Purpose  

Several damages have been associated with the exposure of human beings to noise. These include auditory effects, i.e., hearing impairment, but also non-auditory physiological ones such as hypertension and ischemic heart disease, or psychological ones such as annoyance, depression, sleep disturbance, limited performance of cognitive tasks or inadequate cognitive development. Noise can also interfere with intended activities, both in daytime and nighttime. ISO 14'040 also indicated the necessity of introducing noise, together with other less developed impact categories, in a complete LCA study, possibly changing the results of many LCA studies already available. The attempts available in the literature focused on the integration of transportation noise in LCA. Although being considered the most frequent source of intrusive impact, transportation noise is not the only type of noise that can have a malign impact on public health. Several other sources of noise such as industrial or occupational need to be taken into account to have a complete consideration of noise into LCA. Major life cycle inventories (LCI) typically do not contain data on noise emissions yet and characterisation factors are not yet clearly defined. The aim of the present paper is to briefly review what is already available in the field and propose a new framework for the consideration of human health impacts of any type of noise that could be of interest in the LCA practice, providing indications for the introduction of noise in LCI and analysing what data is already available and, in the form of a research agenda, what other resources would be needed to reach a complete coverage of the problem.     

Life cycle assessment of 3D printing geo‐polymer concrete: An ex‐ante study

Three‐dimensional (3D) printing and geo‐polymers are two environmentally oriented innovations in concrete manufacturing. The 3D printing of concrete components aims to reduce raw material consumption and waste generation. Geo‐polymer is being developed to replace ordinary Portland cement and reduce the carbon footprint of the binder in the concrete. The environmental performance of the combined use of the two innovations is evaluated through an ex‐ante life cycle assessment (LCA). First, an attributional LCA was implemented, using data collected from the manufacturer to identify the hotspots for environmental improvements. Then, scaled‐up scenarios were built in collaboration with the company stakeholder. These scenarios were compared with the existing production system to understand the potential advantages/disadvantages of the innovative system and to identify the potential directions for improvement. The results indicate that 3D printing can potentially lead to waste reduction. However, depending on its recipe, geo‐polymer likely has higher environmental impacts than ordinary concrete. The ex‐ante LCA suggests that after step‐by‐step improvements in the production and transportation of raw materials, 3D printing geo‐polymer concrete is able to reduce the carbon footprint of concrete components, while it does still perform worse on impact categories, such as depletion of abiotic resources and stratospheric ozone depletion. We found that the most effective way to lower the environmental impacts of 3D concrete is to reduce silicate in the recipe of the geo‐polymer. This approach is, however, challenging to realize by the company due to the locked‐in effect of the previous innovation investment. The case study shows that to support technological innovation ex‐ante LCA has to be implemented as early as possible in innovation to allow for maintaining technical flexibility and improving on the identified hotspots.     

Perceived uncertainties of characterization in LCA: a survey

Purpose

Uncertainty analyses in life cycle assessment (LCA) literature have focused primarily on the life cycle inventory (LCI) phase, but LCA experts generally agree that the life cycle impact assessment (LCIA) phase is likely to contribute even more to the overall uncertainty of an LCA result. The magnitude of perceived uncertainties in characterization relative to that in LCI, however, has not been examined in the literature. Here, we use the pedigree approach to gauge the perceived uncertainty in the characterization phase relative to the LCI phase. In addition, we evaluate the level of approval on the pedigree approach as a means to characterize uncertainty in LCA.

Methods

Applying the Numeral Unit Spread Assessment Pedigree (NUSAP) approach to environmental risk assessment literature, we extracted the criteria for evaluating the uncertainty in the characterization phase. We used expert elicitation to identify a pool of experts and conducted a survey, to which 47 LCA practitioners from 12 countries responded. In order to reduce personal biases in perceived geometric standard deviation (GSD) values, we used two reference questions on weight and life expectancy at birth for calibration.

Results

Nearly half (49%) of respondents expressed their approval to the pedigree matrix approach as a means of characterizing uncertainties in LCA, and responses were highly sensitive to the respondent’s familiarity with the pedigree matrix. For instance, respondents who are highly familiar with the pedigree matrix were more polarized, with 15% and 19% of them expressing either strong approval or strong disapproval, respectively. Respondents less familiar with the pedigree approach were generally more favorable to its use. Compared with LCI, variability in characterization factors was influenced more strongly by geographical correlation and reliability of the underlying model, which showed 11 to 16% larger average GSDs when compared with the comparable criteria for LCI. Conversely, temporal correlation criterion was a less significant factor in characterization than in LCI.

Conclusions and discussion

Overall, survey respondents viewed LCIA characterization as only marginally more uncertain than LCI, but with a wider variability in responses on characterization than LCI. This finding indicates the need for additional research to develop more thorough methods for characterizing uncertainties in life cycle impact assessment that are compatible with the uncertainty measures in LCI.