Environmental hazard

Parts II – IV will be published in the following issues of ESPR.     

Enhancing our understanding of the role of environmental policy in environmental innovation: adoption explained by the accumulation of policy instruments and agent-based factors

The empirical literature reports conflicting findings on the relation between environmental policy and environmental innovation: environmental policy both encourages and impedes environmental innovation, resulting in competing theoretical explanations. To find a way out of this counterproductive debate requires new and complementary insights into the effects of different policy instruments. This research therefore advances an approach in which a set of specific policy instruments as well as firms’ behavior regarding CHP (cogeneration of heat and power) adoption are considered as two distinct factors explaining environmental innovation in the Dutch paper and board industry. Using a longitudinal research design, the focus was not on any single policy instrument but on the accumulation of policy instruments. In addition, we studied intra-organizational factors influencing the adoption decision.Overall, we can conclude that paper and board factories perceive governmental environmental policies to be relevant, but that this constitutes just one of the factors influencing adoption processes, next to intra-organizational factors. The relative importance of such policies varies over time and per adoption process. The role of top-down regulation appears to be limited, whereas interactive regulation turned out to be important for several factories in the latest period of adoption. Positive economic instruments were important in almost all adoption processes, but were not and will never be the most important reason for adoption. The most important reason for CHP adoption appears to be high energy prices in combination with cost price reduction or the threat of additional regulation. For future policies, we recommend the implementation of a specific mixture of policy instruments, attuned to the specific industry and reinforcing each other. Moreover, goals should be consistent over time to avoid risk-averse behavior.     

Integration studies on a two-stage fermentation process for the production of biohydrogen

Fermentation of biomass residues and second generation biomasses is potentially a way to enable a sustainable production of hydrogen. Simulation models which calculate mass and energy balances, developed with Aspen Plus^®, are used to integrate the process steps necessary to produce pure hydrogen from biomass in a 2-stage fermentation process. Process and heat integration are introduced to reduce the high water and heat demand of the process, connected to the low substrate concentrations in the involved process streams. The results show that the recirculation of process effluents, together with the use of properly designed heat exchangers, can reduce the water and heat demand up to 90% from a non-integrated process, but is also subject to restrictions due to an increase in osmolality in the system.     

Effect of process integration on the exergy balance of a two-stage process for fermentative hydrogen production

In this paper, a process for the fermentative production of hydrogen is analysed with respect to its exergy efficiency. Parametric studies show the influence of used feedstock, applied process parameters as well as process and heat integration measures on exergy efficiency. It is shown that heat integration and recirculation of fermentor effluents reduce process irreversibilites and the amount of exergy leaving the process in waste streams. Nevertheless, depending on the used feedstock, a large amount of exergy leaves the process via by-products. Internal use of by-products and waste materials for providing process heat could increase chemical exergy efficiency up to 74%.     

Floral odor learning within the hive affects honeybees’ foraging decisions

Honeybees learn odor cues quickly and efficiently when visiting rewarding flowers. Memorization of these cues facilitates the localization and recognition of food sources during foraging flights. Bees can also use information gained inside the hive during social interactions with successful foragers. An important information cue that can be learned during these interactions is food odor. However, little is known about how floral odors learned in the hive affect later decisions of foragers in the field. We studied the effect of food scent on foraging preferences when this learning is acquired directly inside the hive. By using in-hive feeders that were removed 24 h before the test, we showed that foragers use the odor information acquired during a 3-day stimulation period with a scented solution during a food-choice situation outside the nest. This bias in food preference is maintained even 24 h after the replacement of all the hive combs. Thus, without being previously collected outside by foragers, food odors learned within the hive can be used during short-range foraging flights. Moreover, correct landings at a dual-choice device after replacing the storing combs suggests that long-term memories formed within the colony can be retrieved while bees search for food in the field.     

Separation and remediation of environmental pollutants using metal–organic framework-based tailored materials

Environmental Science and Pollution Research - Metal–organic frameworks (MOFs) are a polymer hybrid family of compounds comprising metal ions that have been deliberately incorporated in...     

Do Energy‐Based PET Models Require More Input Data than Temperature‐Based Models? — An Evaluation at Four Humid FluxNet Sites

It is well established that wet environment potential evapotranspiration (PET) can be reliably estimated using the energy budget at the canopy or land surface. However, in most cases the necessary radiation measurements are not available and, thus, empirical temperature‐based PET models are still widely used, especially in watershed models. Here we question the presumption that empirical PET models require fewer input data than more physically based models. Specifically, we test whether the energy‐budget‐based Priestley‐Taylor (P‐T) model can reliably predict daily PET using primarily air temperature to estimate the radiation fluxes and associated parameters. This method of calculating PET requires only daily minimum and maximum temperature, day of the year, and latitude. We compared PET estimates using directly measured radiation fluxes to PET calculated from temperature‐based radiation estimates at four humid AmeriFlux sites. We found good agreement between P‐T PET calculated from measured radiation fluxes and P‐T PET determined via air temperature. In addition, in three of the four sites, the temperature‐based radiation approximations had a stronger correlation with measured evapotranspiration (ET) during periods of maximal ET than fully empirical Hargreaves, Hamon and Oudin methods. Of the three fully empirical models, the Hargreaves performed the best. Overall, the results suggest that daily PET estimates can be made using a physically based approach even when radiation measurements are unavailable.