R&D and abatement under environmental liability law: Comparing incentives under strict liability and negligence if compensation differs from harm

This paper analyzes equilibrium R&D in pollution control and equilibrium pollution abatement by polluters who are subject to environmental liability law when the level of compensation differs from the level of environmental harm. We contrast the performance of strict liability with that of the negligence rule. Privately optimal levels necessarily deviate from socially optimal ones under strict liability, whereas private decisions are first-best under negligence unless compensation is much smaller than harm. It is established that the way in which privately optimal R&D deviates from the first-best level depends on the kind of technical change in pollution abatement. Counterintuitively polluters might overinvest into R&D in pollution control if compensation falls short of harm, and may underinvest if compensation exceeds harm.     

Optimal household refrigerator replacement policy for life cycle energy,greenhouse gas emissions,and cost

Although the last decade witnessed dramatic progress in refrigerator efficiencies, inefficient, outdated refrigerators are still in operation, sometimes consuming more than twice as much electricity per year compared with modern, efficient models. Replacing old refrigerators before their designed lifetime could be a useful policy to conserve electric energy and greenhouse gas emissions. However, from a life cycle perspective, product replacement decisions also induce additional economic and environmental burdens associated with disposal of old models and production of new models. This paper discusses optimal lifetimes of mid-sized refrigerator models in the US, using a life cycle optimization model based on dynamic programming. Model runs were conducted to find optimal lifetimes that minimize energy, global warming potential (GWP), and cost objectives over a time horizon between 1985 and 2020. The baseline results show that depending on model years, optimal lifetimes range 2–7 years for the energy objective, and 2–11 years for the GWP objective. On the other hand, an 18-year of lifetime minimizes the economic cost incurred during the time horizon. Model runs with a time horizon between 2004 and 2020 show that current owners should replace refrigerators that consume more than 1000 kWh/year of electricity (typical mid-sized 1994 models and older) as an efficient strategy from both cost and energy perspectives.     

Economic structure and pollution intensity within the environmental input–output framework

The environmental input–output approach reveals the channels through which the environmental burdens of production activities are transmitted throughout the economy. This paper uses the input–output framework and analyses the changes in Spanish emission multipliers during the period 1995–2000. By decomposing the total changes in multipliers into different components, it is possible to evaluate separately the effects of economic structure and pollution intensity captured by the environmental input–output model. Specifically, in this study, we distinguish between the effects on multipliers caused by changes in emission coefficients (the pollution intensity effects) and the effects on multipliers caused by changes in technical coefficients (the economic structure effects). Our results show a significant reduction in the pollution intensity of production activities, which contributed negatively to changes in emission multipliers. They also show that the economic structure contributed positively to changes in emission multipliers. Together, these two effects lead to a small reduction in multipliers during the period of analysis. My results also show significant differences in the individual behaviour of different sectors in terms of their contribution to multiplier changes. Since there are considerable differences in the way individual sectors affect the changes in emission levels, and in the intensity of these effects, this means that the final effects will basically depend on the activity considered.     

Thermal–economic–environmental analysis and multi-objective optimization of an internal-reforming solid oxide fuel cell–gas turbine hybrid system

In this article, an internal-reforming solid oxide fuel cell–gas turbine (IRSOFC–GT) hybrid system is modeled and analyzed from thermal (energy and exergy), economic, and environmental points of view. The model is validated using available data in the literature. Utilizing the genetic algorithm optimization technique, multi-objective optimization of modeled system is carried out and the optimal values of system design parameters are obtained. In the multi-objective optimization procedure, the exergy efficiency and the total cost rate of the system (including the capital and maintenance costs, operational cost (fuel cost), and social cost of air pollution for CO, NO_x, and CO₂) are considered as objective functions. A sensitivity analysis is also performed in order to study the effect of variations of the fuel unit cost on the Pareto optimal solutions and their corresponding design parameters. The optimization results indicate that the final optimum design chosen from the Pareto front results in exergy efficiency of 65.60% while it leads to total cost of 3.28 million US$ year⁻¹. It is also demonstrated that the payback time of the chosen design is 6.14 years.     

The energy and environmental impacts of Italian households consumptions: An input–output approach

Promoting sustainable consumption and production patterns is a key challenge for the future, in order to use the Earth resources efficiently, to reduce the greenhouse gas emissions, and to decouple the economic growth from the environmental degradation.New or customized methods have to be applied to support decisions makers in the choice of environmental-friendly products, and to select policy priorities and sustainable strategies.A modified input–output model can aid to analyse the relationships among economic growth, energy consumptions and pollutants, in order to assess the energy and environmental impacts due to the actual production and consumption patterns.The following paper introduces an energy and environmental extended input–output model and combines it with the Life Cycle Assessment (LCA) methodology.The authors apply this model to the Italian context in order to assess the energy and environmental impacts related to the consumptions of the Italian households in the period 1999–2006 and to identify the economic sectors involving the highest impacts.The paper represents one of the first Italian studies aimed at identifying those national economic sectors and final goods and services to be assumed prior in the definition of sustainable production and consumption strategies. Results show that about the 70% of the total energy, needed to meet the household final demand of products, is consumed by the productive sectors. In particular tertiary, “electricity, gas and vapour”, road transports and “food and beverage” sectors are the most contributors, accounting for about 75%.Further, the environmental impact analysis associated to Italian households consumptions is carried out, starting from three different data sources The results point out that, to include emissions arising both from energy and non-energy sources, in the assessment of environmental impacts is of paramount importance to obtain reliable simulations of the link between households consumptions and energy and environmental performances.     

The environmental Kuznets curve hypothesis for water pollution: Do regions matter?

This study revisits the environmental Kuznets curve (EKC) hypothesis for water pollution by using a recent dynamic technique, which is the generalized method of moments (GMM) approach, for a board sample of 97 countries during the period 1980–2001. On a global scale, as we cannot obtain the EKC relationship between real income and biological oxygen demand (BOD) emissions, this paper further classifies these countries into four regional groups – Africa, Asia and Oceania, America, and Europe – to explore whether the different regions have different ECK relationships. The empirical results show evidence of the inverted U-shaped EKC relationships’ existence in America and Europe, but not in Africa and Asia and Oceania. Thus, the regional difference of EKC for water pollution is supported. Furthermore, the estimated turning points are, approximately, US$13,956 and US$38,221 for America and Europe, respectively.     

The relationship between income and environment in Turkey: Is there an environmental Kuznets curve?

In this study, we investigate the relationship between income and environmental quality for Turkey at two levels. First, the relationship between the CO₂ emissions and per capita income is examined by the help of a time series model using cointegration techniques. In the second stage, the relationship between income and air pollution is investigated by using PM₁₀ and SO₂ measurements in Turkish provinces. In this part of the study panel data estimation techniques are utilized. The time series model covers 1968–2003, and the panel data model covers 1992–2001 including observations from 58 provinces. A monotonically increasing relationship between CO₂ and income is found in the long-run according to time series analysis. On the other hand, panel data analysis indicates an N-shape relationship for SO₂ and PM₁₀ emissions. Therefore, the results of our time series and panel data analyses do not support the Environmental Kuznets Curve hypothesis, which assumes an inverted U-shaped relationship between environmental degradation and income.     

Effect of optimal spinning reserve requirement on system pollution emission considering reserve supplying demand response in the electricity market

Pollution emission reduction is becoming an inevitable global goal. Incorporating pollution reduction goals into power system operation affects several different aspects, such as unit scheduling and system reliability. At the same time, changes in the energy scheduling change the required optimal reserve amount. Optimal spinning reserve scheduling also affects the energy market scheduling. Optimal reserve allocation changes the energy scheduling, which affect the amount of pollution emission. Therefore, incorporating pollution emission reduction and optimal spinning reserve scheduling cannot be studied separately. Analysis of the system effects of pollution reduction should be performed considering the ancillary service market, specificity the optimal spinning reserve scheduling. This problem is addressed in this paper by incorporating optimal spinning reserve scheduling in a combined environment economic dispatch (CEED) in one objective function. The framework of this paper enables the study of the effect of optimal reserve scheduling and emission reduction as well as an analysis of the system effects of pollution reduction. With the increased AMI and smart grid realization, the reserve supplying demand response (RSDR) is becoming an important player in the reserve market, and thus, these resources are also taken into account. In this paper, the objective function is social cost minimization, including the costs associated with energy provision, reserve procurement, expected interruptions and environmental pollution. A MIP-based optimization method is developed, which reduces the computational burden considerably while maintaining the ability to reach to the optimal solution. The IEEE RTS 1996 is used as a test case for numerical simulations, and the results are presented. The numerical results show that optimal reserve scheduling and RSDR utilization resources have a considerable impact on environmental–economic cost characteristics.     

The effects of hydrogen addition on engine power and emission in DME premixed charge compression ignition engine

Premixed-charge compression-ignition (PCCI) combustion of dimethyl-ether (DME) with double injection strategy was investigated in a single-cylinder compression-ignition engine. DME main-injection was replaced by hydrogen to reduce carbon dioxide emissions. To study the effect of hydrogen, the injected amount of hydrogen was increased. Engine performance and emission of DME PCCI combustion were compared to those of hydrogen–DME PCCI combustion. In the DME PCCI engine operation, DME was injected directly into the cylinder at −120 crank angle degrees (°CA) after top dead center (aTDC) to simulate homogeneous charge at first, and then DME was injected secondly with varied second injection timing. In this case, DME injection timing in the second stage affected the engine performance and emissions. Delayed combustion phase showed a higher indicated mean effective pressure (IMEP), while it increased NO_x emission when DME second injection is retarded. In the hydrogen–DME PCCI, hydrogen was injected at intake port with fixed injection timing. DME injection timing in hydrogen–DME PCCI combustion was also varied from −120 °CA to TDC, as in the DME PCCI engine operation. The total supplied heating value was fixed at 400 J for all cases. DME injection timing determined the start of combustion for the hydrogen–DME PCCI. With increasing the amount of hydrogen, exhaust emissions were reduced. Hydrogen–DME PCCI engine was operated with minimum amount of DME via the hydrogen addition and DME injection timing control. The optimized DME injection timing, −30 °CA aTDC, resulted in a lower exhaust emission-operation, while maintaining a higher IMEP.     

Optimal replacement of residential air conditioning equipment to minimize energy,greenhouse gas emissions,and consumer cost in the US

A life cycle optimization of the replacement of residential central air conditioners (CACs) was conducted in order to identify replacement schedules that minimized three separate objectives: life cycle energy consumption, greenhouse gas (GHG) emissions, and consumer cost. The analysis was conducted for the time period of 1985–2025 for Ann Arbor, MI and San Antonio, TX. Using annual sales-weighted efficiencies of residential CAC equipment, the tradeoff between potential operational savings and the burdens of producing new, more efficient equipment was evaluated. The optimal replacement schedule for each objective was identified for each location and service scenario. In general, minimizing energy consumption required frequent replacement (4–12 replacements), minimizing GHG required fewer replacements (2–5 replacements), and minimizing cost required the fewest replacements (1–3 replacements) over the time horizon. Scenario analysis of different federal efficiency standards, regional standards, and Energy Star purchases were conducted to quantify each policy's impact. For example, a 16 SEER regional standard in Texas was shown to either reduce primary energy consumption 13%, GHGs emissions by 11%, or cost by 6–7% when performing optimal replacement of CACs from 2005 or before. The results also indicate that proper servicing should be a higher priority than optimal replacement to minimize environmental burdens.     

Exploring the ancillary benefits of the Kyoto Protocol for air pollution in Europe

An integrated approach to climate change and regional air pollution can harvest considerable ancillary benefits in terms of environmental impacts and costs. This is because both problems are caused to a large extent by the same activity (fossil fuel combustion). Substantial ancillary benefits were found for regional air pollution (SO₂, NO_x, VOC and particulate matter) of implementing the Kyoto Protocol (intended to control greenhouse gas emissions) in Europe. For instance, while three different scenarios on Kyoto implementation were found to reduce European CO₂ emissions by 4–7%, they also reduced European emissions of SO₂ by 5–14% compared with a no Kyoto policies case. The magnitude of ancillary benefits depends on how flexible mechanisms and surplus emission allowances are used in meeting the Kyoto targets. The total cost savings for implementing current policies for regional air pollution of the Kyoto Protocol are of an order of 2.5–7 billion Euro. In all cases, this is in the order of half the costs of the climate policy (4–12 billion Euro). Using flexible mechanisms reduces emissions of air pollutants for Europe as a whole even further than domestic implementation (e.g. 10–14% versus 5% for SO₂ emissions), but the reductions are shifted from Western Europe to Central and Eastern Europe and Russia. The use of surplus emission allowances to achieve the Kyoto targets decreases the ancillary benefits, in particular for the latter group of countries (e.g. unprotected area against acidification increases from 1.3 to 1.7 million ha).     

Environmental performance evaluation of Beijing's energy use planning

In line with rapid economic development, urban energy consumption is increasing rapidly, resulting in environmental problems. After considering several methods to evaluate the environmental performance of energy use, including: energy ecological footprint, input–output analysis, emergy–exergy analysis, and multi-criteria decision-making, an environmental performance evaluation model is proposed, which combines the analytical hierarchy process, fuzzy extent analysis, and membership degree analysis. In the model, 18 sub-indicators of environmental performance from energy use planning are classified into four categories: structure of energy use and industry, technology and efficiency of energy use, environmental impacts caused by energy use, and the socio-economic benefits of energy use. Membership degree analysis is applied to each indicator. Three energy use scenarios which are, respectively, environment-friendly, technology-led, and economic policy-led are evaluated. The results show that the technology-led energy use planning is best. The sustainable energy use policies are proposed from three aspects, including optimizing the energy use and industrial structure, encouraging development of energy-saving and air pollution control technologies, and enhancing legislation on energy use management. The policies are helpful to optimize the trade-offs between economic growth and environmental protection in Beijing.     

An integrated assessment of climate change,air pollution,and energy security policy

This article presents an integrated assessment of climate change, air pollution, and energy security policy. Basis of our analysis is the MERGE model, designed to study the interaction between the global economy, energy use, and the impacts of climate change. For our purposes we expanded MERGE with expressions that quantify damages incurred to regional economies as a result of air pollution and lack of energy security. One of the main findings of our cost–benefit analysis is that energy security policy alone does not decrease the use of oil: global oil consumption is only delayed by several decades and oil reserves are still practically depleted before the end of the 21st century. If, on the other hand, energy security policy is integrated with optimal climate change and air pollution policy, the world’s oil reserves will not be depleted, at least not before our modeling horizon well into the 22nd century: total cumulative demand for oil decreases by about 24%. More generally, we demonstrate that there are multiple other benefits of combining climate change, air pollution, and energy security policies and exploiting the possible synergies between them. These benefits can be large: for Europe the achievable CO₂ emission abatement and oil consumption reduction levels are significantly deeper for integrated policy than when a strategy is adopted in which one of the three policies is omitted. Integrated optimal energy policy can reduce the number of premature deaths from air pollution by about 14,000 annually in Europe and over 3 million per year globally, by lowering the chronic exposure to ambient particulate matter. Only the optimal strategy combining the three types of energy policy can constrain the global average atmospheric temperature increase to a limit of 3 °C with respect to the pre-industrial level.     

On backstops and boomerangs: Environmental R&D under technological uncertainty

In areas such as climate change, the recent economic literature has been emphasizing and addressing the pervasive presence of uncertainty. This paper considers a new and salient form of uncertainty, namely uncertainty regarding the environmental characteristics of ‘green’ innovations. Here, R&D may generate both backstop technologies and technologies that turn out to involve a new pollution problem (‘boomerangs’). In the optimum, R&D will therefore typically be undertaken more than once. Extending results from multi-stage optimal control theory, we present a tractable model with a full characterization of the optimal pollution and R&D policies and the role of uncertainty. In this setting, (i) the optimal R&D program is defined by a research trigger condition in which the decision-maker's belief about the probability of finding a backstop enters in an intuitive way; (ii) a decreasing probability of finding a backstop leads to the toleration of higher pollution levels, slower R&D, a slower turnover of technologies, and an ambiguous effect on the expected number of innovations; (iii) learning about the probability of a backstop is driven by failures only and leads to decreasing research incentives; and (iv) small to moderate delays in the resolution of technological uncertainty do not affect the optimal policy.     

Estimating strategic interactions in petroleum exploration

When individual petroleum-producing firms make their exploration decisions, information externalities and extraction externalities may lead them to interact strategically with their neighbors. If they do occur, strategic interactions in exploration would lead to a loss in both firm profit and government royalty revenue. Since these strategic interactions would be inefficient, changes in the government offshore leasing policy would need to be considered. The possibility of strategic interactions thus poses a concern to policy-makers and affects the optimal government policy. This paper examines whether these inefficient strategic interactions take place in U.S. federal lands in the Gulf of Mexico. In particular, it analyzes whether a firm's exploration decisions depend on the decisions of firms owning neighboring tracts of land. A discrete response model of a firm's exploration timing decision that uses variables based on the timing of a neighbor's lease term as instruments for the neighbor's decision is employed. The results suggest that strategic interactions do not actually take place, at least not in exploration, and therefore that the current parameters of the government offshore leasing policy do not lead to inefficient petroleum exploration.     

China's foreign trade and climate change: A case study of CO2 emissions

The globalization of trade has numerous environmental implications. Trade creates a mechanism for consumers to shift environmental pollution associated with their consumption to other countries. Carbon leakage exerts great influences on international trade and economy. Applying an input–output approach, the paper estimates the amount of carbon dioxide (CO₂) embodied in China's foreign trade during 1997–2007. It is found that 10.03–26.54% of China's annual CO₂ emissions are produced during the manufacture of export goods destined for foreign consumers, while the CO₂ emissions embodied in China's imports accounted for only 4.40% (1997) and 9.05% (2007) of that. We also estimate that the rest of world avoided emitting 150.18 Mt CO₂ in 1997, increasing to 593 Mt in 2007, as a result of importing goods from China, rather than manufacturing the same type and quantity of goods domestically. During 1997–2007, the net “additional” global CO₂ emissions resulting from China's exports were 4894 Mt. Then, the paper divides the trade-embodied emissions into scale, composition and technical effect. It was found that scale and composition effect increased the CO₂ emissions embodied in trade while the technical effect offset a small part of them. Finally, its mechanism and policy implications are presented.     

The assessment of health damage caused by air pollution and its implication for policy making in Taiyuan,Shanxi, China

We establish the link between energy use, air pollution, and public health impacts in Taiyuan for 2000, and for 2010 and 2015 under alternative scenarios. We find that in year 2000 more than 2200 excess deaths may have been caused by particulate matter (PM) pollution. Using alternative methods for monetization of health impacts the total health damage amounts to 0.8–1.7 billion Yuan, which is 2.4–4.9% of the city's GDP in 2000. Compared to the business-as-usual scenario, scenarios assuming extensive fuel switch in low-and-medium-stack pollution sources and extension of the district heating system could prevent 200–1100 PM₁₀-related premature deaths in 2010 and substantially reduce population morbidity. The actual PM pollution in 2007 was lower than modeled in these two scenarios. We also find that if air quality in urban Taiyuan were to reach the Chinese National Grade II Standard in 2015, the number of premature deaths would still be around 1330 and the economic cost about 1–2% of the city's GDP in 2015. Our results imply that there are large health benefits to be gained by setting stricter standards for the future in China, and that targeting low-and-medium-stack source effectively reduces health damage.     

Artificial Neural Network based prediction of performance and emission characteristics of a variable compression ratio CI engine using WCO as a biodiesel at different injection timings

Due to the increasing demand for fossil fuels and environmental threat due to pollution a number renewable sources of energy have been studied worldwide. In the present investigation influence of injection timing on the performance and emissions of a single cylinder, four stroke stationary, variable compression ratio, diesel engine was studied using waste cooking oil (WCO) as the biodiesel blended with diesel. The tests were performed at three different injection timings (24°, 27°, 30° CA BTDC) by changing the thickness of the advance shim. The experimental results showed that brake thermal efficiency for the advanced as well as the retarded injection timing was lesser than that for the normal injection timing (27° BTDC) for all sets of compression ratios. Smoke, un-burnt hydrocarbon (UBHC) emissions were reduced for advanced injection timings where as NO_x emissions increased. Artificial Neural Networks (ANN) was used to predict the engine performance and emission characteristics of the engine. Separate models were developed for performance parameters as well as emission characteristics. To train the network, compression ratio, injection timing, blend percentage, percentage load, were used as the input parameters where as engine performance parameters like brake thermal efficiency (BTE), brake specific energy consumption (BSEC), exhaust gas temperature (T_exh) were used as the output parameters for the performance model and engine exhaust emissions such as NO_x, smoke and (UBHC) values were used as the output parameters for the emission model. ANN results showed that there is a good correlation between the ANN predicted values and the experimental values for various engine performance parameters and exhaust emission characteristics and the relative mean error values (MRE) were within 8%, which is acceptable.     

Neuro-evolutionary approach applied for optimizing the PEMFC performance

A multi-objective optimization strategy, based on stacked neural network–genetic algorithm (SNN–GA) hybrid approach, was applied to study the C/PBI content on a high temperature PEMFC performance. The operating conditions of PEMFC were correlated with power density and electrochemical active surface area for electrodes. The structure of the stack was determined in an optimal form related to the contribution of individual neural networks, after applying an interpolation based procedure. Multi-objective optimization using SNN as model and GA as solving procedure provides optimal working conditions which lead to a high PEMFC performance. Simulation results were in agreement with experimental data, both for model validation and system optimization (the C/PBI content in the range of 17–21%).     

An empirical analysis of the dynamic programming model of stockpile acquisition strategies for China's strategic petroleum reserve

The world's future oil price is affected by many factors. The challenge, therefore, is how to select optimal stockpile acquisition strategies to minimize the cost of maintaining a reserve. This paper provides a new method for analyzing this problem using an uncertain dynamic programming model to analyze stockpile acquisition strategies for strategic petroleum reserve. Using this model, we quantify the impact of uncertain world oil price on optimal stockpile acquisition strategies of China's strategic petroleum reserve for the period 2007–2010 and 2011–2020. Our results show that the future stockpile acquisition is related to oil prices and their probability and, if not considering the occurrence of oil supply shortage, China should at least purchase 25 million barrels when world oil price is at an optimal level. The optimal price of stockpile acquisition of every year has a stronger relationship with the probability of high price; and the optimal expected price and size of stockpile acquisition is different in each year.