Time-based indicators of forced labour, local employment and equal opportunities in social LCA

The conventional type-1 indicators used in social life cycle assessment have mathematical problems related to aggregation of impacts along product life cycles. This contribution therefore proposes three time-based, quantitative type-2 indicators: (i) the share of the life-cycle labour hours of a product conducted as forced labour, (ii) the share of labour hours conducted locally, and (iii) the share of labour hours conducted by the two genders (females and males). These indicators all have the unit time (e.g. hours) and capture the three subcategories forced labour, local employment and (partly) equal opportunity, respectively. Forced labour and local employment both constitute shares of the total life-cycle labour hours, whereas the shares of labour hours conducted by females and males respectively make up the total labour hours. The absolute values of these indicators can be used for product comparisons, but their distribution along product life cycles might be even more interesting

Energy Efficient Longitudinal Control

Vehicles are contributing to global and local environmental problems as a result of fossil fuels. A majority of the combustion engine population is driven by fossil fuels and electrified vehicles are also to a large extent dependent on electricity production from fossil fuels. Emission legislation and standardized test methods have lead the development of technology for the automotive industry. Increased efficiency, improved combustion control and aftertreatment systems have created cleaner and more fuel efficient drivetrains. Authorities and publications have highlighted an increased gap between in-use and certified vehicle consumption and emissions because of the test-cycles current design. In order to address these differences authorities have conducted changes within the test methods from 2017 and forward and a new test-cycle WLTP is introduced including real-driving-emission test procedures. Decreasing the gap of real driving emissions and consumption can also be improved outside the legislative test-cycles using forward looking sensors, map data and statistical models.The work considers controlling the drivetrain actuators more efficiently in a vehicle with predictive information. For this, dynamic programming is used to optimize engine speed trajectories during depletion mode for a series hybrid drivetrain. The result shows that choice of state and control signals has a direct impact on the engine speed trajectory and thereby the fuel consumption. Up to 21 % lower fuel consumption could be achieved for a series hybrid drivetrain compared to a rule based engine speed demand controller (along the best efficiency line) for the drivecycle analyzed. For a parallel hybrid drivetrain a DP method was compared to a heuristic strategy in order to determine the optimal discharge rate of the battery. In the simulation study done the DP method provided the best fuel consumption results. During evaluation of the physical tests the pre-optimized DP parameter set performed worse than the heuristic strategy. In the rig tests a fuel consumption reduction of 8 % was measured with the heuristic method, compared to a non predictive controller strategy. The DP algorithm provided 4 % reduction of fuel compared to a non predictive controller.The work has also considered different modeling methods of a high voltage battery from recorded fleet data. One individual vehicle recorded battery pack current and voltage for one year. The recorded data was used to identify battery parameters for electric equivalent circuits. The measured current was used to calculate a reference voltage from the circuit equivalent parameters that was compared to the measured voltage. The best result was obtained for a single RC circuit model which obtained the highest average goodness of fit in voltage for the entire training data set

Towards Prospective Exposure Modeling of Nanoparticles - Applying Particle Flow Analysis and Kinetic Exposure Modeling for the Cases of TiO2 and Ag Nanoparticles

The claims regarding the usefulness of nanoparticles (NPs) in different applications, such as wound dressings, solar cells and soil remediation, has been accompanied by concern that NPs may also pose risks to humans and to the environment. Considering the past century, when many substances later shown to cause unacceptable damage were manufactured in large amounts, there are reasons to thoroughly assess the risks of these NPs. This thesis discusses how the exposure assessment step of a risk assessment of NPs may be conducted, focusing on two research aims. The first research aim considered is the magnitude of NP emissions from society. In order to address this aim, the methodology of substance flow analysis (SFA) was adapted to the case of NPs, resulting in the particle flow analysis (PFA) methodology. In PFA, particle number is used as flow and stock metric instead of mass, which is used in SFA. Moreover, a prospective approach is applied by developing an explorative scenario of technology diffusion. This method has been applied for titanium dioxide (TiO2) in sunscreen, paint and self-cleaning cement, and silver (Ag) NPs in wound dressings, textiles and electronics. The second research aim concerns the fate of NPs in the water compartment. It is shown that modeling NP fate using fugacity based on thermodynamic equilibrium, which is normally done when assessing the risks of chemicals (i.e. molecules), is not feasible. Instead, the fate of NPs was modeled using kinetic equations which were borrowed from colloid chemistry. Particle concentration is used as exposure indicator, rather than mass concentration which is normally used in risk assessment of chemicals. This method was applied to the case of TiO2 NPs. The results from the PFA case studies indicate that the currently highest use phase emissions of TiO2 NPs come from the use of sunscreen, and that this will probably be the case in the future as well. However, there is large number of TiO2 NPs in paint, and in the future maybe also in self-cleaning cement, which are not emitted during their use but continue to the waste handling phase. Their fate during waste handling processes thus remains an interesting topic to investigate. Regarding Ag NPs, it is difficult to tell which application that gives rise to the currently largest emissions, but the results indicate that the emissions from textiles may be highest in the future. The kinetic exposure modeling of TiO2 NPs identified parameters and mechanisms which affect the concentration of TiO2 NPs, and the collision efficiency was shown to have the largest effect. Gaps in current knowledge are identifies in all three case studies and recommendations for further studies are given. The methods of PFA and kinetic exposure modeling constitute important steps towards prospective exposure modeling of NPs

Risk Assessments Show Engineered Nanomaterials To Be of Low Environmental Concern

No abstract availabl

Optimal Transient Real-Time Engine-Generator Control in the Series-Hybrid Vehicle

We study the dynamic engine-generator optimal control problem with a goal of minimizing fuel consumption while delivering a requested average electrical power. By using an infinite-horizon formulation and explicitly minimizing fuel consumption, we avoid issues inherent with penalty-based and finite-horizon problems. The solution to the optimal control problem, found using dynamic programming and the successive approximation method, can be expressed as instantaneous non-linear state-feedback. This allows for trivial real-time control, typically requiring 10–20 CPU instructions per control period, a few bytes of RAM, and 5–20 KiB of nonvolatile memory. Simulation results for a passenger vehicle indicate a fuel consumption improvement in the region of 5–7% during the transient phase when compared with the class of controllers found in the industry. Bench-tests, where the optimal controller is executed in native hardware, show an improvement of 3.7%, primarily limited by unmodeled dynamics. Our specific choice of problem formulation, a guaranteed globally optimal solution, and trivial real-time control resolve many of the limitations with the current state of optimal engine-generator controllers

Measuring the immeasurable: The contribution of social sciences to the assessment of social impacts in a life cycle perspective

The UNEP/SETAC guidelines encourage researches in order to overcome some methodological issues related to Social Life Cycle Assessment (SLCA). Possible problems regard the operationalization and measurement of social indicators usually based on the corporate social responsibility structure and on political standards and conventions. To face these issues, possible contributes may come from the adoption of a theoretical and methodological pluralism approach based on social sciences. The aim of this study is to investigate on how social sciences may orient SLCA practitioners towards the development of new indicators related to human well-being. Focusing on social sciences, a literature review will be performed in order to see how human well-being is defined according to the several disciplines and what may be its possible indicators. Expected results regard a deeper knowledge of social realities and an increased awareness of how social sciences could contribute to develop the SLCA