Discussion and conclusion
In sum, including aviation emissions in theEuropeanTradingSystem for carbondioxide appears to be nei- ther effective nor efficient. Of course, the first best solution for an emission reduction policy is to have a permit market that covers all emissions, including those from aviation. However, the current market is partial, and including aviation should not be the first priority for extending market coverage. The effect on emissions is minimal, even if the permit price reach- es heights that are inconceivable today. If this were the only drawback, one may dismiss the inclusion of aviation emissions in the ETS as largely irrelevant, but a step in the right direction. However, in the cur- rent regime of grandparenting permits, this policy is in fact tantamount to a substantial subsidy to the air- line industry – at the expense of travellers and with- out perceptible gains for the environment. European politicians would create the impression of leadership on climate policy while in fact contributing almost nothing to emission reduction.
aspects. 8 This represents a trade-off between broad coverage ofemissions and the avoidance of large MRV transaction costs per unit ofemissions for some regulated companies.
A possible way to decrease transaction cost burdens while preserving effectiveness and broad coverage of regulation would be a strict ‘upstream’ policy design (Joas & Flachsland, 2014; Kerr & Duscha, 2015). In the EU ETS, regulation takes place at the installation level in an ‘end ofthe pipe’ manner. This makes the inclusion of small installations necessary. Under upstream regulation (as interpreted here), thecarbon content of intermediate products (e.g. fossil fuels) is ‘priced’ by the upstream regulation system in the moment the products are put on the market (Kerr & Duscha, 2015). In this case, greenhouse gas emissions are ‘priced’ at the source and not at the level of final (commercial) consumers. In this situation, the overall prices ofcarbon- intensive intermediate products incorporate thecarbon price in case the products are resold. Such
brokers also affects transaction volumes: From 2013 to 2016, 55.7% of allowances in 67.6% of transactions involving the EEX Auction Delivery Account were directed towards these bidders. However, the average transaction volume of 347,500 allowances was considerably lower than that of installation holders, which reached 575,500 allowances. With regard to the average volume per account holder, in turn, banks and brokers are ahead by a considerable margin, reaching 434,000 versus 368,700 allowances. Considering these results, two hypotheses can be formulated as to the role banks play in the auctioning of allowances. First, it is probable that banks predominantly act as brokers or intermediaries by placing bids on behalf of installation operators lacking the skill or infrastructure necessary to participate in allowance auctions. This would explain the exceptionally low number of installation operators receiving transactions directly from ICE or EEX. Second, banks other market participants not directly involved in the ETS may be acting on their own account, acquiring allowances at auctions with the purpose oftrading. According to Art. 18 ofthe Auctioning Regulation (European Commission, 2010), both alternatives are legally viable. However, a transaction-level analysis of accounts operated by two major players – Deutsche Bank and Citigroup Global Markets – fails to provide useful insight on this issue. In concrete terms, this involved searching for transactions with identical volumes in temporal proximity to the transfers issued by either ICE or EEX. Unfortunately, I was unable to identify conclusive patterns using this relatively straightforward approach. Hence, further research using a more sophisticated, algorithm based method is needed to shed light on the business practice of banks or financial institutions involved in the auctioning of allowances.
But what scope do China’s industries have to curb these emissions without damaging economic growth? Being able to properly assess the marginal abatement costs is an important first step for global climate negotiations with China. Not only because helps China’s international partners to persuade China ofthe need to curb emissions but it helps inform the debate by guiding the choice of a more efficient burden‐sharing rule and abatement mechanism. Importantly for China, an accurate cost assessment helps to shape a broad range of domestic environmental policy issues, i.e., it can be used to guide carbon tax rate setting, emission permits trading and regional allocation of reduction obligation, etc. (Färe et al., 1993; Wei et al., 2013).
This paper explores how regulators can improve market efficiency under uncertainty, while reducing the need for discretionary intervention. The analysis is set in the context ofthe EU ETS, although the results are generally applicable.
As part ofthe EU ETS reform, theEuropean Commission has indicated a preference for an automatic quantity- based mechanism, the so-called Market Stability Reserve (MSR). The key rationale for using a quantity-based supply management mechanism is to remove the need to specify a price range for triggering allocation ad- justments. In the current EU context, the prospect of specifying an acceptable price range for a price-collar mechanism has been faced with significant political challenges. Thus, a quantity-based mechanism provides a practical advantage. Still, how the parameters determining the timing and the intensity of quantity-based adjustments are selected remains an open question both in the political and the academic spheres.
second-order dominance is significant) and managerial efficiency (first-order dominance is significant at the 10 % level). With regard to the program efficiency ofthe United States we find that both measures are stochastically undominated so the incorporation ofemissions does not change the location ofthe program frontier relative to the overall frontier. Comparing the results between the regions (see table 13 in the appendix for the related test results) we find for all efficiency measures that Europe is stochastically dominated by Asia as well as the United States with regard to the overall as well as the program efficency. This last result shows that the regional frontier ofEuropean cars lies closer to the overall frontier than the frontiers of Asia or the United States. In fact, the DEA analysis shows that 1287 European cars (43 %) are classified efficient regarding program effiency, so we can conclude that many parts ofthe overall frontier are identical to theEuropean program (regional) frontier when emissions are ignored. For the managerial efficiency we find that results for European cars dominate both the results for Asia as well as those for the United States indicating a greater distance ofEuropean cars to their regional frontier compared to the distance of Asian or United States cars to their regional frontiers. Comparing Asia and the United States we find that the overall efficiency results as well as the managerial efficiency results are undominated for all efficiency measures. Comparing the results ofthe program efficiency for DEA and the DDF O we find that Asia
We have designed a Monte Carlo analysis case study based on the Single Electricity Market (SEM) on the island of Ireland to examine the impact of NAO on power systememissions. A Monte Carlo analysis allows us to isolate the eects of NAO within a power system that is complex and has many stochastic elements, including NAO, fuel and carbon prices and electricity demand. We use the SEM electricity market because its transparency enables thesystem to be relatively easily modelled, though several simplications are made for the purposes of our study. The Irish electricity market has two interconnectors to Great Britain, which we do not model. This is partly because modelling their eects would prove beyond the scope of our model, but also because we wished to isolate the eect of NAO within a single system. The omission of interconnection from our analysis means that the results are attributable to the eect of NAO and not complicated by what happens within interconnected power systems or how the interconnectors are managed (McInerney and Bunn, 2013).
The main market focus of course was on the price. In the early months, carbon prices rose steadily, tracking the rising gas price that determined the cost of switching away from coal in power sector generation. As gas prices continued to soar, the CO 2 price broke free from this marker and oscillated in the range EUR 20–25/tCO 2 for much ofthe year (Figure 1). From several perspectives, 2006 was the defining year for the EU ETS. It started with prices for phase I (2005–07) emission allowances reaching levels higher than anyone predicted, peaking at EUR 30/tCO 2 , whilst governments confidently issued draft National Allocation Plans (NAPs) for how they intended to allocate allowances for phase II, the Kyoto period of 2008–12. The year ended with phase I prices sinking close to zero, and several countries threatening to take legal action to overturn theEuropean Commission’s rejection of almost all the submitted NAPs as inadequate. It was certainly a year of vast learning – as befits the middle ofthe first, learning, period of a major new system.
► Volatility: Volatile carbon prices are an indicator that a market is able to react to newly revealed information. Yet, excessive volatility makes it difficult for market participants to make abatement and trading decisions. Short-term volatility ofthe price of Californian carbon allowances (CCA) is near zero in nearly all phases ofthe program. The major reason seems to be the binding price floor, essentially setting the CCA price at the minimum price level. Another reason might be that due to the consignment of primary allocation (i.e., investor-owned utilities (IOUs) are required to consign all freely allocated allowances to auction), the quarterly auctioned amount of allowances sums up to two third of total allowances. Consequently, there is little trade on secondary markets as the primary
reduces fuel costs and CO 2 emissions, but incurs investment costs to buy and implement thesystem and it incurs operating costs to maintain and manage thesystem. Technical measures mainly concern technical design features of ships and are characterized by high investment and moderate operating costs. An example for such a measure is the implementation of a waste heat recovery system that can be used to generate electricity alternatively to auxiliary engines and thus reduce fuel consumption (Faber et al., 2011a/Wang et al., 2010). Structural changes mainly concern the improvement of common practice, e.g., charter contracts or port efficiency, with regard to energy efficiency. Alternative fuels/power sources mainly concern substitutes, e.g., liquefied natural gas for motive power, for the use ofcarbon-intensive fuels. Both categories of measure types are characterized by high abatement potential, but at the same time are limited in application, e.g., because there is a lack of mature infrastructure for liquefied natural gas, or are difficult to develop (Eide et al., 2011, Faber et al., 2011a).
We can find that many research achievements about CO 2 emissions sprang up in different fields from above listed references. However, few scholars researched on carbondioxide emission in logistics industry. A small quantity of scholars researched CO 2 of logistics. For example, Zając (2011) presented ofthe conception of counting the energy consumption of logistics warehouse systems. Tang, Wang, Yan and Hao (2014) examined the issue of cutting emissions by reducing shipment frequency within the framework of periodic inventory review system. Hammami, Nouira and Frein (2014) developed a deterministic optimization model that incorporates carbonemissions in a multi-echelon production-inventory model with lead time constraints. Logistics is a process of planning, implementing and controlling the efficient, cost- effective flow and storage of raw materials, in-process inventory, finished goods and related information from point of origin to point of consumption for the purpose of conforming to customer requirement (Cooper, Lambert & Pagh, 1997). Logistics has played an extremely important role in economic growth in China (Zhang & Peng, 2009; Peng, 2011; Tan, 2003). On the other hand, it is a relatively energy-intensity industry, such as haul trucks, shipping and aircraft, which seriously rely on fossil fuel, and they emit greenhouse gas. Logistics activities accounted for roughly 5.5% share of global GHG emissions, around 90% of which came from transport, and the rest come from warehouses, load and unload (McKinnon, 2012).
The discrepancy between the price predicted by theory and the price observed in reality might be explained by factoring in uncertainty, which is dealt with in a second strand of literature. Compliance with the emission cap is not only determined by current emissions but by cumulative emissions and therefore total expected emissions might serve as a good indicator for the EUA spot price (Seifert et al. 2008). The current and cumulated emissionsof a firm might follow to a certain extend a stochastic process due to for example unforeseen demand variations, so that the firm has to form expectations on the spot price at the end ofthe period. Consequently, holding a EUA allows either using it for compliance, selling it at the end ofthe period, or retire it if the cap turns out to be non-binding. It therefore provides an option value for the holder (e.g., Chao and Wilson 1993; Chesney and Taschini 2012; Hintermann 2012). As already pointed out by Chao and Wilson (1993) the holding of an emission allowance increases the flexibility to adapt to market conditions so that the allowance price exceeds the marginal abatement costs by the option value. The option value is increasing in the irreversibility of investment in abatement and the uncertainty about future market conditions (Chao and Wilson 1993). With respect to uncertainty about future market conditions, it needs to be taken into account that any news about those conditions require a new optimization, thereby increasing not only the probability of price jumps but obviously also the value of greater flexibility in holding options in terms of EUAs (Schennach 2000). Taking these uncertainties into account, the price path of will never approach zero before the end ofthetrading period as long as a positive probability of exceeding the cap remains (Seifert et al. 2008; Chesney and Taschini 2012). However, if the future probability of a shortfall in permits becomes sufficiently low the price converges to zero as observed at the end of Phase I. In line with these considerations Carmona et al. (2009) show in a numerical simulation that allowance prices are only a poor indicator of marginal abatement costs. These theoretical aspects have, to our knowledge, only been empirically investigated by Hintermann (2012) so far. His results show that an option-value approach of holding emission allowances seems to describe the price dynamics in Phase I much better than the equalization of marginal abatement costs described above. Consequently, the results suggest that firms hold EUAs to hedge against the possibility to pay the penalty.
We limit our Lidar sizing analysis to pulsed, direct detection systems with two wavelengths (on- and offline), using knowledge gained during the planning and design phase of airborne  and spaceborne IPDA Lidars [20,24,25,27,33]. Alternative Lidar methodologies might likewise be applicable [19,22,34]. Plume detection from quickly moving platforms such as satellites, however, requires high spatial resolution, which will only be achievable with a small laser footprint, a high laser pulse repetition frequency (PRF) and a single-measurement (non-averaged) retrieval. These requirements are realizable with a two-wavelength pulsed system. A small surface footprint generally poses certain challenges, as it goes along with high speckle noise  and on-/offline overlap uncertainty . A high PRF implies that there is less energy per pulse available for a given average laser power which mainly drives performance, cost and complexity. As detailed below and based on our airborne experience [18,35] we choose as compromise a PRF of 500 Hz (double-pulse, on-/offline) and a footprint of 50 m diameter, corresponding to a laser beam divergence of 0.1 mrad. This yields overlapping footprints separated by 14 m for a low-earth orbit with typical satellite velocity v SAT ≈ 7 km/s, as the separation between two footprints equals the ratio v SAT /PRF. We use a model developed and described in [25,33] to assess the performance of IPDA Lidar for a baseline set of instrument, platform and environmental parameters listed in Table 2 that influence the precision (random instrument noise; Equation (4)) of space-based Lidar measurements. Use ofthe standard atmosphere described in Section 2 simplifies the simulations, making the weighting function (Equation (3)) as well as its vertical integral (Equation (2)) a constant only dependent on the selected on-/offline pair from Table 1. Typical variations in aerosol load and climate conditions have minor influence on the IPDA Lidar performance , in the absence of clouds . Our analysis does not include systematic errors (measurement biases), extensively discussed in  and found to be sufficiently smaller than the single-measurement noise errors presented here below.
With the suggested response of free allocations to output fluctuations thecarbon costs per unit of output can be better anticipated by installations. Depending on a specified cap for free allowances there might be a need for calibrating once the volume of free allowances at the beginning of a reference period. Both the targeted benchmark emissions intensities for free allowances and the use of more recent or current activity levels enable to eliminate a Cross Sectoral Correction Factor if ad- equate responses for maintaining the overall emissions cap are applied. Linking benchmark emissions intensities to actual activities also ensures that free alloca- tions cannot exceed verified emissions.
on carriers and intensify underlying inequities among them. Although emissionstrading schemes could be an important complementary tool in a CO 2 emissions reduction policy,
they also have similar equity issues (Miyoshi, 2014). Indeed, the first multinational emissionstrading scheme, the EU ETS, has raised many regulatory issues and objections, including from the Chicago Convention. Although it is a cost-effective measure, the ETS produces “winners and losers” among participants due to the timing ofthe scheme implemented. For the global ETS mechanism, equity issues among carriers and countries cannot be avoided. A recent study estimates that 92 percent of fuel burning takes place in the Northern Hemisphere, and 67 percent of this occurs between 30° N and 60° N (Simone et al., 2013).
The high degree of uncertainty with respect to the shapes ofthe marginal cost and beneﬁ t curves also gives rise to combining both price- and quantity-based approaches into so-called hybrid instruments, such as a trading sys- tem with a ﬂ oor for certiﬁ cate prices. Price ﬂ oors would only prove effective in cases of low demand, as they would prevent market prices from falling below a lower bound (Figure 4). A price ﬂ oor then functions like a tax, the rate of which equals the difference between the price ﬂ oor and the hypothetical market price that would be observed in the absence ofthe price ﬂ oor. In situations where the price ﬂ oor is binding, companies would invest in additional abatement measures rather than purchasing more expen- sive allowances, leading to an excess supply (Cap - E A ) of allowances (Figure 4). Then an independent institution, e.g. a European Allowance Bank, would have to buy the excess
Another lesson that other pilots and the to-be-established national scheme could learn is Shanghai’s practice to seek the support of financial institutions to increase the rate of compliance. The Shanghai pilot scheme includes non-compliance in the credit record of non-complying enterprises and make it public to financial institutions and the general public (SMG, 2013). While the penalty for non-complying entities in the Shanghai pilot is not strictest compared to peers, Shanghai achieved the 100% of compliance. Indeed, seeking the support of financial institutions to promote improved corporate environmental performance is not new in China. From 1 April 2007, China’s Ministry of Environmental Protection (MEP) has worked with the People’s Bank of China on a new credit-evaluation system under which companies’ environmental compliance records are incorporated into the bank’s credit-evaluation system. This information will serve as a reference for commercial banks’ consideration of whether or not to provide loans. The bank could turn down requests for loans from firms with poor environmental records (Zhang, 2007 and 2008). In mid-July 2007, MEP announced the “green credit” policy jointly with the People’s Bank of China and China Banking Regulation Commission. They work together to enforce it, with the financial bodies denying loans to firms that MEP identifies as failing to meet environmental standards. MEP later posted on its web site and notified China’s central bank and top banking regulatory commission of 30 offending companies that will be barred from receiving credits (Xinhua Net, 2007). Some bank branches go further. Jiangyin Branch ofthe People’s Bank of China in Jiangsu province issued the color-coded lending guidance, favoring those companies with superior environmental performance. For those green- rated companies, banks will enhance their lending scale and give priority to their
TheEuropean Union established the largest greenhouse gas emissionstrading scheme in the world. The need for such regulatory frameworks to reduce green- house gas emissions became evident, at the latest, when the Intergovernmental Panel on Climate Change published its fourth assessment report in 2007. Accord- ing to this report, an uncontrolled anthropogenic production of greenhouse gases will lead, with almost absolute certainty, to climate change. “Continued green- house gas emissions at or above current rates would cause further warming and induce many changes in the global climate system.” 1 In particular, this would lead to global warming and sea level rises and thus floods, droughts, migration, and negative effects on agriculture and on human health are expectable. 2 The widely noticed Stern Review estimates the global costs of these negative effects of climate change and concludes that the uncontrolled production of greenhouse gases will “reduce welfare by an amount of equivalent to a reduction in consump- tion per head of between 5 and 20%.” 3 Even more problematic, these costs are unevenly distributed and the poorest countries and people will suffer most. Ac- cording to Stern, the costs of stabilization of greenhouse gas concentrations in the atmosphere, at a level that would prevent the most serious damage, are only around 1% of global GDP if actions are taken immediately. To achieve such a
the important role of other contextual factors. Calel and Dechezleprêtre (2016) do not ﬁnd evidence ofthe EU ETS causing spill-over e ﬀects on third parties’ patenting activity, implying a limited scope of innovation eﬀects, so far.
However, it seems that at least a small number of regulated ﬁrms reacted strongly to new constraints under the EU ETS. Petsonk and Cozijnsen (2007) point out that low-carbon solutions were developed at an early stage. A structural break of low-carbon patenting is observed in 2005, at the start ofthe EU-ETS (Figure 4). Calel and Dechezleprêtre (2016) investigate whether this is a consequence ofthe EU ETS applying a di ﬀerence-in-diﬀer- ence design to a large sample of matched EU ETS ﬁrms. The evidence shows that thesystem boosted low- carbon patenting by 36.2% among regulated ﬁrms relative to non-regulated ones. This percentage drops to 8.1% when extrapolating results to the whole non-matched sample of EU ETS ﬁrms, covering 80% of regulated emissions. In all, the EU ETS accounts for only 1% ofthe surge in low-carbon patenting, depicted in Figure 4. Interestingly, the disaggregated level of data shows the strong reaction of a small group of ﬁrms. In parallel, they show that the EU ETS did not crowd out patenting for other technologies and even encouraged it mod- erately. Anderson, Convery, and Di Maria (2011) surveyed Irish EU ETS ﬁrms during the ﬁrst phase and ﬁnd that thesystem stimulated technological change and raised awareness about emissions reduction possibilities, despite decreasing carbon prices and uncertainty.
“the crucial role of economic incentives, in particular by carbon markets, for the necessary investments in climate friendly technologies at large scale.” Today, regional emissionstrading systems are being set up, legislative proposals are put forward, options for creating broad regimes or broadening existing regimes are considered, from personal carbon trad- ing and “domestic offsets” to upstream regimes. Cost control measures of various kinds are also being dis- cussed, as well as allocations and other design issues. The early lessons from the first phase ofthe Euro- pean Emission Trading Scheme (ETS) have been taken into account in the revision of existing and the design of new schemes, and in refreshing the debate on emission trading features. Since the AIXG (Annex I Expert Group on the United Nations Framework Convention Climate Change) October 2006 meeting, there have been updates in the EU ETS on two fronts – the approval and decisions from theEuropean Commission (EC) on the second round of national allocation plans (NAPs); and the review ofthe existing scheme, for which legislation has been passed, and post-2012 developments. The Table shows a summary of NAPs in all 27 EU countries assessed as of October 2007. Member states have to propose a cap (upper limit) of their emissions that can be cut by theEuropean Commission. The States had until June 30, 2007 to set up their second NAPs for the period 2008 to 2012. With regard to the proposed number of allowances, the Commission accepted some of these NAP2 in their entirety (those from Denmark, France, Slo- venia, UK), and imposed relatively minor changes (less than 10 percent) on eleven other countries. But it also cut Hungary’s NAP by 12.4 percent, the Czech Republic’s by 14.8, Slovakia’s by 25.2, Poland’s by 26.7, Malta’s by 29, Luxembourg’s by 37, Lithuania’s by 47, Estonia’s by 47.8, Cyprus’ by 23, Romania’s by 20.7, Bulgaria’s by 37.4, and Latvia’s by 55.5 percent. Poland, alongside the Czech Republic, Lithuania, Estonia, Slovakia, Latvia and Hungary, are suing the Commission for these decisions.