Environmental implications of increased US oil production and liberal growth agenda in post -Paris Agreement era

Oil price shocks and policy uncertainty: New evidence on the effects of US and non-US oil production

Important interaction has been established for US economic policy uncertainty with a number of economic and financial variables including oil prices. This paper examines the dynamic effects of US and non-US oil production shocks on economic policy uncertainty using a structural VAR model. Such an examination is motivated by the substantial increases in US oil production in recent years with implications for US political and economic security. Positive innovations in US oil production are associated with decreases in US economic policy uncertainty. The economic forecast interquartile ranges about the US CPI and about federal/state/local government expenditures are particularly sensitive to innovations in US oil supply shocks. Shocks to US oil supply disruption causes rises in the CPI forecast uncertainty and accounts for 21% of the overall variation of the CPI forecaster disagreement. Dis-aggregation of oil production shocks into US and non-US oil production yield novel results. Oil supply shocks identified by US and non-US origins explain as much of the variation in economic policy uncertainty as structural shocks on the demand side of the oil market.

Important interaction has been established for US economic policy uncertainty with a number of economic and financial variables including oil prices. This paper examines the dynamic effects of US and non-US oil production shocks on economic policy uncertainty using a structural VAR model. Such an examination is motivated by the substantial increases in US oil production in recent years with implications for US political and economic security. Positive innovations in US oil production are associated with decreases in US economic policy uncertainty. The economic forecast interquartile ranges about the US CPI and about federal/state/local government expenditures are particularly sensitive to innovations in US oil supply shocks. Shocks to US oil supply disruption causes rises in the CPI forecast uncertainty and accounts for 21% of the overall variation of the CPI forecaster disagreement. Dis-aggregation of oil production shocks into US and non-US oil production yield novel results. Oil supply shocks identified by US and non-US origins explain as much of the variation in economic policy uncertainty as structural shocks on the demand side of the oil market.

Effectively addressing today’s energy challenges requires advanced technologies along with policies that influence economic markets while advancing the public good.

Carbon pricing, carbon equity, and the RCEP framework

The most significant cost of increase in economic growth is an increase in energy consumption and carbon emissions as well. Energy consumption triggers carbon dioxide emissions, which is the main cause of environmental pollution. In recent years, struggling with climate changes, global warming and carbon dioxide emissions based environmental problems became critical issues. In doing so, this study investigates the relationship between carbon emissions and economic growth for BRICS-T countries for the period of 1992-2016. We apply Pedroni and, Westerlund and Edgerton panel cointegration approaches for examining cointegration between the variabes. The FMOLS approach is applied for testing long-term relationship between economic growth and carbon emissions. The empirical results indicate that a 1% increase in economic growth increases carbon emissions by 0.79% but 1% increase in carbon emissions leads economic growth by 0.5%. The causality analysis reveals the presence of bidirectional relationship between carbon emissions and economic growth.

Editor's column With the shale industry still awash in red ink, and oil prices falling, it may take more consolidation to try to bring some financial stability to the sector. The financing strategy of the shale sector has always differed from onshore conventional oil business models. The small and medium-sized independents that have dominated shale have operated with much higher levels of debt and, since the beginning of the unconventional rise, have operated with negative free cash flow. Although production has skyrocketed, profitability has not, and Wall Street investors have grown tired of financing a largely unprofitable piece of the oil and gas business. The International Energy Agency (IEA) predicted last year that the shale industry would finally achieve positive free cash flow this year as oil prices rebounded and new pipelines relieved bottlenecks that had depressed prices. But the sharp downturn in oil prices in the fourth quarter and the recent decline to near $50/bbl (WTI) has not helped. When the shale boom was taking off between 2010 and 2014, high oil prices led to huge financial backing. Investment quadruped during that period, according to the IEA, as oil production increased from 0.44 million B/D to 3.6 million B/D, the fastest oil growth since the advent of Saudi Arabia’s giant oil fields in the 1960s. When oil prices tanked beginning in 2014, shale firms, along with the rest of the industry, switched to sharply cutting costs and trying to instill capital discipline. It was too much for some. More than a hundred shale firms filed for bankruptcy during 2015–16. Banks became more reluctant to lend money, even after oil prices began to recover, leading to a wave of lending from private equity firms. Production from the sector continued to defy odds, but profitability was still not in sight. BP’s most recent bellwether Statistical Review of World Energy, released in June, noted that US oil and gas production growth accelerated in 2018 at another record pace. The production growth “exceeded any other country’s annual increase in our 50-year history” of publishing the review, said BP Chief Economist Dale Spencer. “Indeed, the US achieved a unique double-first last year, recording the single largest-ever annual increase by any country in both oil and gas production. In case there was any doubt, the US shale revolution is alive and kicking,” he said. Since 2012, US oil production, including natural gas liquids, has grown by more than 7 million B/D, “broadly equivalent to Saudi Arabia’s crude oil exports, an astonishing increase which has trans-formed both the structure of the US economy and global market dynamics,” he added. But how long this revolution can continue without solid economic footing is unclear. One trend under way is consolidation. Two years ago, many independents began selling off assets so they could continue drilling. Today, many are pursuing assets sales, drilling partnerships, and other alternative financing strategies, according to an article in The Wall Street Journal. A new wave of company consolidations and buyouts by larger firms may have started. Chevron attempted to buy Anadarko and its sizable presence in the Permian Basin but was beat out by Occidental. Although Shell and other majors have indicated that, while interested, current selling prices for some companies appear too steep, the Anadarko deal could be the first of many that attempts to bring some stability to the shale sector and increases the presence of larger, more diversified firms.

ABSTRACTThis paper provides new evidence by examining the impact of oil price changes on environmental quality. Having utilized three co-integrating estimators and a dataset from 1983 to 2014, we found that lower oil price can increase carbon emissions and reduce environmental quality. On the other hand, higher oil price can mitigate carbon emissions and improve environmental quality. We recommend the use of cleaner energy sources to improve environmental quality during lower oil price.

In this study, a spatio-temporal dynamic carbon emission factor model is proposed, and a framework for air conditioning(AC) carbon emission calculation is constructed by coupling dynamic load and real-time energy structure. The spatio-temporal dynamic carbon emission factor model realises the spatio-temporal dynamic calibration of carbon emission by integrating real-time load fluctuation, grid cleanliness level, and power loss, which more accurately reflects the carbon emission characteristics of the regional power grid than the traditional static method. Taking office buildings in hot-summer and cold-winter (HSCW) regions as an example, we quantitatively analyze the impact of users’ AC behaviours on AC energy consumption and carbon emissions. The results show that under the simulated conditions, when the cooling/heating temperature is adjusted from 26/18°C to 16/28°C, the annual energy consumption increases by 4,233 kWh, and the carbon emission increases by 2,186 kgCO2; when the fresh air volume is increased from 0 to 90 m3/h, the energy consumption and carbon emission increase by 5,916 kWh and 3,064 kgCO2, respectively. The synergistic effect of the dual-track carbon reduction strategy (behavioural optimisation + photovoltaic integration) was verified, with a maximum annual carbon reduction of 6,180 kgCO2 (71% efficiency gain compared to a single photovoltaic measure).

With ever increasing usage of IT infrastructure around the globe, the increase in energy consumption and carbon emission is a worrisome situation for everyone because of its direct effect on environment. The environment is being dangerously impacted by Information Technology infrastructure extensive use and its waste. Cloud computing has emerged as one step further solution to deploy all virtualized IT resources as per need on self-service basis as a rental method for the users. Different cloud deployment methods have emerged according to the need of users, institutions and communities. In last decade virtualization has been a milestone in enabling optimal usage of information technology resources. Cloud computing has provided a platform for deploying everything as a Service in IT, which has changed the economics of IT based business and organizations from Capital Expenditure to Operational Expenditure. For enabling Cloud services we first need to understand our existing infrastructure. In second step we should be able to virtualize it for optimal usage. Then with the help of existing cloud applications we can deliver and deploy information technology as a resource at various levels such as infrastructure, platform, and software. Keywords; cloud computing, carbon emission, energy consumption, IT waste, virtualization. The Advancement in the field of information technology has enabled us to optimize the use of physical infrastructure with the help of virtualization, most of which is only used in specific applications like vitalizing a local area network on switch or vitalizing a compute resource to run more than one operating system on a desktop. The benefits of same has not been completely implemented and utilized in industrial environments where we require a large amount of IT resources. The advantage of using cloud is to enable complete utilization of Information technology resources, where most of the resources are underutilized. The cost involved in maintenance and management of those resources is huge which can be saved due to centralized management of private cloud infrastructure. We create private cloud keeping in mind. • Availability and performance requirements for the cloud • Infrastructure sizing, performance and continual availability requirements • The need for data security or isolation • The appropriate user interface With advent of IT as a service in cloud computing technology energy consumption and related carbon emissions and waste are considerably lesser than in-house implementation. Technology in Cloud Computing creates an able structure for sharing resources with the help of virtualization among many; it greatly decreases or abolishes the need for most products, equipment, utilities and facilities. The results are more sustainable IT infrastructures and processes which help in keeping environment safe. • Highest resource consumption and effectiveness • Reduced energy consumption by up to 95 % with the help of virtualization which optimizes the use of physical infrastructure and thereby helps IT to be delivered as a service. • Displaced utility costs Workstation utility costs are cut by 90% due to change of capital expenditure into operational expenditure in industries or organizations across the world. • Reduced electronic waste as No more batteries and minimal software/hardware waste. • Reduced waste overall due to consumption of computational power as service, no more as infrastructure. • Reduced ecological impact of workstations as compared to thin clients as anything related to computation can be provided as a service on a client connected with internet to the cloud provider.

Methane emissions along biomethane and biogas supply chains are underestimated

Global warming continues to be an intimidating factor for environmental protection, and reducing carbon emissions is an effective way to deal with the phenomenon. However, the energy sector is a significant contributor to greenhouse gas emissions. Therefore, investment in environmental regulations and research and development (R&D), is critical for fostering a low-carbon growth model. This study focuses on 30 provinces in China from 2004 to 2019. We used the spatial Durbin model to investigate how the spatial spillover effect of R&D and environmental regulation impacts carbon emissions. In addition, we applied the dynamic threshold panel model to mitigate potential problems of endogeneity. The results reveal that carbon emissions have a considerable spatial correlation in both temporal and spatial dimensions, exhibiting high and low-value accumulation characteristics. Furthermore, the combined effect of R&D intensity, environmental regulation, and energy consumption were found to contribute to the increase in carbon emissions across China's provinces, and they also suggest different influencing mechanisms. The spillover effects of increased carbon emissions in neighboring regions also contribute to the increase in local carbon emissions. The study also found that R&D and stringent environmental regulations measures strongly moderate the link between energy consumption and carbon emissions. In promoting carbon reduction, by breaking the dynamic equilibrium in China, the provincial investment outflow on R&D intensity could be optimized, and the regional levels should focus more on tightening environmental regulatory measures and promoting the development of energy-conserving technologies.

This article did some simulation in allusion to Shanghai's carbon emissions before 2050 and discussed research methods of urban carbon emissions trends. In allusion to urban problems, this paper used the Logistic curve to approach urban population growth rate and employed Nonlinear Economic Dynamics to predict Shanghai's economic growth rate before 2050. Adopting the optimal growth model proposed by Yongbin Zhu and Zheng Wang (2009), this paper carried out some researches on Shanghai's energy consumption and carbon emissions. The results show that Shanghai's energy consumption and carbon emission increase in the curve of inversed “U”. The peak of energy consumption and carbon emissions will be in 2040. The value of reaching peak in Shanghai is a litter bigger than other provinces relatively, reflecting that reducing carbon dioxide in Shanghai still has a long way to go.

Carbon emissions calculation at the sub-provincial level has issues in limited data and non-unified measurements. This paper calculated the life cycle energy consumption and carbon emissions of the building industry in Wuhan, China. The findings showed that the proportion of carbon emissions in the construction operation phase was the largest, followed by the carbon emissions of the indirect energy consumption and the construction material preparation phase. With the purpose of analyzing the contributors of the construction carbon emissions, this paper conducted decomposition analysis using Logarithmic Mean Divisia Index (LMDI). The results indicated that the increasing buidling area was the major driver of energy consumption and carbon emissions increase, followed by the behavior factor. Population growth and urbanization, to some extent, increased the carbon emissions as well. On the contrary, energy efficiency was the main inhibitory factor for reducing the carbon emissions. Policy implications in terms of low-carbon construction development were highlighted.

PurposeThis paper aims to analyze the impact of the relations between the US oil prices, carbon emissions and GDP through the analysis of data between 1987 and 2017.Design/methodology/approachARIMA, VAR and VEC models are used to establish synthesis integration model. Furthermore, the stability test, cointegration test and Granger causality test of the model were carried out.FindingsThe results indicate that, in both short and long term, change in oil prices is the reason for change in carbon emissions, while GDP is not the reason for the growth of carbon emissions.Originality/valueIncrease of oil prices would have a negative impact on carbon emissions, and GDP growth does not lead to an increase in carbon emissions.