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The majority of currently installed photovoltaic (PV) systems are based on mono- and polycrystalline silicon PV modules. Manufacturers of competing technologies often argue that due to the characteristics of their PV technologies, PV systems based on their modules are able to achieve higher annual energy yield, due to a smaller effect of temperature on module performance and/or a better performance at low light intensities. While these benefits have been confirmed in local studies many times, there is still limited insight as to the locations at which a particular technology actually performs best. In this study we have analysed the performance of a large set of PV modules, based on irradiance time series that were taken from satellite measurements. Using these data, and combining it with a PV performance model, we have made a geospatial analysis of the energy yield of different types of PV modules. We aim to make the energy yield of the investigated modules spatially explicit, allowing PV system installers to choose the best module type for every location investigated. Our results show that there is large geographical variety in the performance of PV modules, in terms of energy yield but also in terms of relative performance or performance ratio. While some technologies clearly exhibit a decrease in performance ratio at locations where they operate at higher temperatures, for some technologies this effect is much smaller. As a result of the variation in performance, the environmental footprint of PV modules also shows large geographical variations. However, even at low irradiance locations the environmental footprint of PV modules in general is much lower compared to that of fossil fuel based electricity generation.

The specifications of photovoltaic modules show performance under standard testing conditions (STC), but only limited information relating to performance at non-STC conditions. While performance is affected by irradiance, temperature, spectral composition of irradiance, angle-of-incidence of the irradiance and other parameters, specifications only partly give detail to consumers or retailers about the effect of irradiance and temperature. In this study, we characterise and analyse the performance of eight different, commercially available photovoltaic modules. We establish the effect of four different parameters on module performance: irradiance, temperature, spectral composition of irradiance (via the parameter average photon energy) and angle-of-incidence, by performing linear and nonlinear optimisation of physical or empirical models. Furthermore, we characterise the operating conditions and analyse the seasonal and annual development and contribution of the four parameters to energy losses or gains relative to STC operating conditions. We show a comprehensive way of presenting the deviation of performance from STC, combining the variation in operating conditions and the resulting variation in performance. Our results show that some effects on performance are attributable to the semiconductor material used in the modules (spectral composition and temperature), while especially angle-of-incidence effects seem more related to the type of glass used on as the front cover of the module. Variation in irradiance and module temperature generally affect performance the strongest, resulting in a performance effect ranging from + 2.8% to − 3.2% and − 0.5% to − 2.2%, respectively. The combined effect of all parameters results in an annual yield deviation ranging from + 1.2% to − 5.9%.

Carbon Capture and Storage (CCS) can be a valuable CO2 mitigation option, but what role CCS will play in the future is uncertain. In this paper we analyze the results of different integrated assessment models (IAMs) taking part in the 27th round of the Energy Modeling Forum (EMF) with respect to the role of CCS in long term mitigation scenarios. Specifically we look into the use of CCS as a function of time, mitigation targets, availability of renewables and its use with different fuels. Furthermore, we explore the possibility to relate model results to general and CCS specific model assumptions. The results show a wide range of cumulative capture in the 2010-2100 period (600-3050 GtCO2), but the fact that no model projects less than 600 GtCO2 indicates that CCS is considered to be important by all these models. Interestingly, CCS storage rates are often projected to be still increasing in the second half of this century. Depending on the scenario, at least six out of eight, up to all models show higher storage rates in 2100 than in 2050. CCS shares in cumulative primary energy use are in most models increasing with the stringency of the target or under conservative availability of renewables. The strong variations of CCS deployment projection rates could not be related to the reported differences in the assumptions of the models by means of a cross-model comparison in this sample.

Carbon Capture and Storage (CCS) could be an interesting option to mitigate greenhouse gas emissions in the Netherlands. This study compares a mitigation strategy for the Dutch power sector that includes CCS to one without on several socio-economic indicators. In particular, we calculate incremental gross value added (GVA), employment and import dependency impacts of two such low-carbon power production portfolios for the Netherlands. We combine technology specific techno-economic bottom-up data with a macro-economic multi-regional Input-Output-Table containing high sectoral detail. For the total economy, we find the differences between these scenarios to be small. Still, gross value added, and employment are lower under the CCS-inclusive strategy, while import dependency is higher. For the power sector, the differences between the scenarios are, however, considerable. Furthermore, our analysis shows that also for other sectors the differences between the scenarios could be large. For instance, a CCS-exclusive strategy leads to considerably higher GVA and employment in domestic construction services, while the CCS-inclusive strategy comes with considerably higher GVA and employment for natural gas mining and related upstream sectors. © 2016 Elsevier Ltd

This study assesses whether the deployment of CO 2 capture technologies in the European industrial sector would result in significant changes in the emissions of air pollutants (NO x , SO 2 , PM, and NH 3 ) in the short term. The industrial sectors investigated were: cement, petroleum refineries, and iron and steel. The analysis included onsite emissions and changes associated with grid electricity consumption due to CO 2 capture. Post-combustion capture using monoethanolamine (MEA) was considered for the cement sector and petroleum refineries, and Top Gas Recycling Blast Furnace (TGRBF) with vacuum-pressure swing adsorption (VPSA) for the iron and steel sector. The results show that when all three industrial sectors in the EU-27 are fully equipped with CO 2 capture, industrial SO 2 emissions in the EU-27 may decrease by 40–70% whereas NH 3 emissions may increase by 120–520% (equivalent to 2–8% of total European emissions). The large increase in NH 3 emissions is due to the degradation of MEA. Cement and petroleum refineries account for nearly all these changes. The results also show limited impact (within ±10% of EU-27 industrial emissions) on NO x and PM emissions. Emission changes due to electricity import/export are found to be equally important as onsite emission changes. For the iron and steel sector, the changes in National Emissions Ceilings Directive (NECD) emissions are found to be limited for the selected CO 2 capture technique under conservative assumptions. However, the changes in the NECD emissions could vary largely depending on how the steel mill will adapt and operate their coke oven batteries that supply the coke to the blast furnace (BF).