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The energy yield of PV systems with horizontal single-axis tracking and bifacial panels was calculated using BIGEYE. BIGEYE is a versatile code developed at ECN part of TNO to calculate the yield of bifacial PV. Comparison to recent measured data with the BIFOROT set-up at the Zurich University of Applied Sciences showed very good agreement. Our BIGEYE results show that the bifacial energy gain and the tracking gain are mostly additive, making the combination of bifacial panels and tracking a very attractive option. For two different locations, Doha and Amsterdam, increases of energy yield in the order of 25% compared to monofacial, fixed tilt systems are possible at relatively modest ground cover values. 35th European Photovoltaic Solar Energy Conference and Exhibition; 1573-1577

The goal of this study is to model the effects of reusing salad from salad bars to reduce product loss, while keeping microbial safety and product quality at acceptable levels. We, therefore, expand our previously developed simulation model by incorporating reuse strategies and a quality decay model. The expanded model is used to simulate different salad reuse scenarios and to quantify the consequences to product loss, microbial safety and product quality. With this study, we show an application of a generic approach for the integrated modelling of product loss, microbial safety and product quality. The most cautious scenario consists of reusing salad for only 1 day after the first use and only if the salad originates from a package with a valid best-before date at the time of reuse (‘minimum reuse of salad with the best-before date criterion’). This scenario decreases product loss at the salad bar considerably from 37% to 29% ()21%). This considerable benefit occurs almost without causing product loss at the cold storage (increase from 0% to 1%), with only a minimal increase in the number of foetal mortality cases because of Listeria monocytogenes (increase from 11.9 to 12.2 cases per year (+3%)) and hardly any decline in product quality

Greenhouse tomato cultivation often requires a high energy input to maintain set-point temperatures. If set-point temperatures could be lowered by a few degrees this would reduce energy consumption significantly. However, this can only be applied when new, more energy-efficient cultivars are developed, i.e. cultivars that can be cultivated at sub-optimal temperatures without loss of production or quality. As variation for temperature response within the current elite tomato cultivars is limited, it is important to look for other sources of variation. One option are wild relatives which originate from South America, where they grow at altitudes up to 3300 m. In this study we examined the effects of temperature (12¿24°C) on growth of young vegetative tomato plants of the cultivar `Moneymaker¿ and two wild relatives (L. hirsutum LA 1777 and L. pennellii LA 716). The aim was to elucidate the physiological and morphological parameters which underlie interspecific differences in growth response to sub-optimal temperatures. During a 28-day period five destructive measurements were carried out in which total dry weight, including root weight, leaf area and leaf dry weight were measured in order to calculate growth parameters. Even though `Moneymaker¿ had a higher relative growth rate (RGR) over a large temperature range (16¿24°C), RGR of `Moneymaker¿ was severely reduced below 20°C, while RGRs of L. hirsutum and L. pennellii were only decreased below 16°C. At 12°C RGR of `Moneymaker¿ was reduced by 41% compared to 20°C, while in L. pennellii and L. hirsutum this decrease was only 27 and 18%, respectively. This decrease in RGR in `Moneymaker¿ was mainly a result of a decreased leaf area ratio (LAR), caused by a 35% decrease in specific leaf area (SLA). In contrast, the decrease in RGR in L. pennellii and L. hirsutum was a result of a decreased net assimilation rate (NAR) of 24 and 14%, respectively. This study illustrates that wild tomato species provide possibilities for the breeding of more energy-efficient tomato greenhouse cultivars

Field measured estimates of aboveground biomass (AGB) in the mountainous region of Bwindi Impenetrable National Park ('Bwindi'), Uganda were used to train remote sensing models in order to estimate AGB within the park. AGB estimates were extrapolated using dual-polarization radar satellite data from ALOS PALSAR, optical imagery from Landsat 7 and a fusion of both, and compared to field estimates as indicators of the model prediction strength. Significant geolocation errors existed in the radar data due to the extreme terrain. Fusing the radar and optical data using the non-parametric algorithm Random Forest (RF) in R, provided lower error than using either radar or optical data alone (RMSE ∼120 Mg ha-1), however, saturation at higher biomass levels was evident. The AGB in Bwindi was estimated at 8.91 Tg ± 0.39 Tg (260.9 Mg ha-1 ± 11.4 Mg ha-1).

Recent severe river flooding in Europe has triggered debates among scientists and policy-makers on future projections of flood frequency and the need for adaptive investments, such as flood protection measures. Because there exists uncertainty about the impact of climate change on flood risk, such investments require a careful analysis of expected benefits and costs. The objective of this paper is to show how climate change uncertainty affects the decision to invest in flood protection measures. We develop a model that incorporates flexible timing of investment decisions and scientific uncertainty on the extent of climate change impact. This model allows decision-makers to cope with the uncertain impact of climate change on the frequency and damage of river flood events and minimizes the risk of under-or over-investment. One of the innovative elements of our paper is that we explicitly distinguish between structural and non-structural flood protection measures. Our results show that the effects of uncertainty on the optimal initial investment depends on the cost structure of these measures which has several important implications for flood management policy.