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16,424 result(s) for "PRIMARY ENERGY RESOURCES"
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Research on Water Quality Indicators at the Rovinari Power Plant
Indicators of: pH, temperature, conductivity, filtered residue at 105°C, suspended matter, ammonium, chemical oxygen consumption-CCOCr, chlorides, biochemical oxygen consumption - CBO5, sulfates, extractable substances with organic solvents, petroleum products, total iron, calcium, magnesium, sulfides and hydrogen sulfide. The excesses recorded in the sulfate and ammonium indicators in the phreatic waters within the unit premises and in the area of the slag and ash deposits are mainly due to natural causes and to a small extent to anthropogenic action. In accordance with the specialized literature, but also with the studies and research carried out, it is found that the exceedances recorded in the Oltenia area of the specified indicators are due to:- for ammonium (NH4+) - the primary conditions in the Pliocene basin for the formation of aquifer sand deposits; - for sulfates (SO42-) - washing by underground waters of lignite layers in which sulfides frequently appear, especially in the form of pyrite.
The global value of water in agriculture
Major environmental functions and human needs critically depend on water. In regions of the world affected by water scarcity economic activities can be constrained by water availability, leading to competition both among sectors and between human uses and environmental needs. While the commodification of water remains a contentious political issue, the valuation of this natural resource is sometime viewed as a strategy to avoid water waste. Likewise, water markets have been invoked as a mechanism to allocate water to economically most efficient uses. The value of water, however, remains difficult to estimate because water markets and market prices exist only in few regions of the world. Despite numerous attempts at estimating the value of water in the absence of markets (i.e., the “shadow price”), a global spatially explicit assessment of the value of water in agriculture is still missing. Here we propose a data-parsimonious biophysical framework to determine the value generated by water in irrigated agriculture and highlight its global spatiotemporal patterns. We find that in much of the world the actual crop distribution does not maximize agricultural water value.
CEO Foreign Experience and Green Innovation: Evidence from China
We examine whether and how CEO foreign experience affects firm’s green innovation. Using a sample of Chinese public companies and hand-collected CEO foreign experience data, we document a positive association between CEO foreign experience and corporate green innovation. Furthermore, consistent with the view that CEOs with foreign experience would play a more significant role when provided with more resources, we find that the positive relationship is more pronounced in less financially constrained firms, in state-owned enterprises, and in less competitive industries. Additional analyses indicate that enhanced environmental ethics and general competency are two potential mechanisms through which CEO foreign experience affects corporate green innovation. Finally, we find that CEO foreign experience is positively related to green innovation quality and internationalization. Collectively, these findings suggest that CEO foreign experience is a significant factor for corporate green innovation in emerging markets.
Climate change and residential electricity consumption in the Yangtze River Delta, China
Estimating the impact of climate change on energy use across the globe is essential for analysis of both mitigation and adaptation policies. Yet existing empirical estimates are concentrated in Western countries, especially the United States. We use daily data on household electricity consumption to estimate how electricity consumption would change in Shanghai in the context of climate change. For colder days <7 °C, a 1 °C increase in daily temperature reduces electricity consumption by 2.8%. On warm days >25 °C, a 1 °C increase in daily temperatures leads to a 14.5% increase in electricity consumption. As income increases, households’ weather sensitivity remains the same for hotter days in the summer but increases during the winter. We use this estimated behavior in conjunction with a collection of downscaled global climate models (GCMs) to construct a relationship between future annual global mean surface temperature (GMST) changes and annual residential electricity consumption. We find that annual electricity consumption increases by 9.2% per +1 °C in annual GMST. In comparison, annual peak electricity use increases by as much as 36.1% per +1 °C in annual GMST. Although most accurate for Shanghai, our findings could be most credibly extended to the urban areas in the Yangtze River Delta, covering roughly one-fifth of China’s urban population and one-fourth of the gross domestic product.
Rethinking Global Food Demand for 2050
Published estimates of 2050 food demand exhibit an enormous range of values. This paper projects a 50–60 percent increase in total global food demand between 2019 and 2050. Our analysis indicates a substantial slowing of rice demand, a growing share of palm oil in world fats and oils markets, and a continued shift to poultry as the dominant form of meat consumption. In contrast to most existing food models, we integrate fish consumption into the analysis of vegetable and animal protein and highlight the dangers of using commonly cited feed ratios for projecting feed grain demand. More broadly, we demonstrate the value of a commodity by region approach for understanding complexities in the world food system.
Impact of Low-carbon City Construction on Financing, Investment, and Total Factor Productivity of Energy-intensive Enterprises
Faced with the global climate change, as a major greenhouse gas emitter, China launched a pilot policy on low-carbon city construction since 2010. Few studies have discussed how climate policies affect the investment and financing behavior of energy-intensive enterprises. Based on the micro data of A-share listed enterprises in China’s energy-intensive industries, this study aims to assess the productivity effect of low-carbon city pilot (LCCP) policy and investigates the mechanism of financing and investment using the difference-in-difference method. Empirical results provide evidence that the LCCP policy has significantly improved the total factor productivity of energy-intensive enterprises. In terms of the mechanisms, the LCCP policy has increased the supply of bank credit to enterprises and encouraged their long-term investment in fixed assets and R&D activities. The productivity effect of the LCCP policy is greater for state-owned enterprises and enterprises with political connection. Urban human capital, industrial agglomeration, and resource endowment contribute to the productivity effect of LCCP policy for enterprises in the energy-intensive industries. The findings show that the LCCP is an effective comprehensive policy to promote the high-quality development of energy-intensive industries, and the findings also provide enlightenment for enacting better climate transition policies.
How Does Green Investment Affect Environmental Pollution? Evidence from China
China is currently undergoing an important stage wherein it is adjusting its development mode and upgrading its industrial structure. Green investment has become a major driving force through which China can achieve green and sustainable development. Based on the panel data of 30 Chinese provinces for the 2006–2017 period, this paper uses a spatial Durbin model and a dynamic threshold model to empirically analyze the impact of green investment and institutional quality on environmental pollution. The research results show that China’s environmental pollution is significantly characterized by spatial dependence. Local environmental pollution is negatively impacted by green investment, but it is not affected by green investment in neighboring areas; this conclusion remains valid after a series of robustness tests. Green investment can reduce environmental pollution by improving efficiency of energy conservation and emission reduction, expanding technological innovation capabilities and upgrading the industrial structure. The regression results of the dynamic threshold model show that green investment has a nonlinear impact on environmental pollution that is dependent on institutional quality. A higher degree of regional corruption can lead to a gradual decrease in the role of green investment in reducing environmental pollution. However, improvements in marketization and intellectual property protection can increase the positive influence of green investment in reducing environmental pollution. Significant regional heterogeneity is also found in the impact of green investment on environmental pollution, and this impact gradually decreases from the eastern coast to the western region.
Ecological footprint, electricity consumption, and economic growth in China: geopolitical risk and natural resources governance
This paper examines the relationship among ecological footprint (EF), electricity consumption, and GDP in China using annual data ranging from 1960 to 2019. However, factors like trade openness, urbanization, and life expectancy might increase EF as ecological distortions are mainly human-induced. This study explores the effect of these variables on the environment, which is captured by EF. Quantile Regression estimates indicate that electricity consumption and real GDP increase environmental degradation, while trade and urbanization reduce EF, allowing for a higher environmental quality. On the other hand, the spectral Granger-causality tests reveal that only urbanization and life expectancy affect environmental degradation over the whole frequency domain. In the current geopolitical scenario, relevant policy implications may be derived.
Testing green fiscal policies for green investment, innovation and green productivity amid the COVID-19 era
This article measures renewable energy firm-level pure innovation efficiency, green productivity, technical efficiency, scale efficiency and total investment efficiency from micro input–output factors using Banker, Charnes and Cooper’s (BCC) data envelopment analysis (DEA) approach. Its main novelty is that it clearly explores the effective impacts of government subsidies and tax rebate policies on renewable energy firms’ investment efficiency using China’s renewable energy firm-level panel data. Our observational findings indicate that between 2001 and 2018, the aggregate degree of total investment performance from renewable energy firms rose steadily before declining. Renewable energy firms had larger ranges of total investment efficiency and size efficiency, and their levels of pure technological efficiency were both greater than 0.457%. At the 16% trust mark, current government subsidies and taxation rebates had dramatically positive effects on pure technological efficiency and total investment efficiency; additionally, government subsidies have a stronger positive impact on total investment efficiency and pure technical efficiency than taxation rebates. Furthermore, the ownership concentrations of renewable energy companies greatly encourage pure technological efficiency, size efficiency and total investment efficiency, and asset returns will significantly increase their average degree of total investment efficiency and pure technical efficiency.
Can China’s Energy Intensity Constraint Policy Promote Total Factor Energy Efficiency? Evidence from the Industrial Sector
As part of the country’s efforts to achieve green development, China implemented a mandatory energy intensity reduction target in its 11th “Five-Year Plan (FYP)” in 2006, and then began to roll out a series of relevant measures. However, existing studies have paid little attention to the actual effects of China’s energy intensity constraint policy (EICP). In this paper, using panel data from China’s 36 industrial sub-sectors covering the years from 2001 to 2014, we adopt the difference-in-differences (DID) method to investigate for the first time the EICP’s (marginal) effect on total factor energy efficiency growth (TFEEG). We also estimate the super-position effect caused by the introduction of a carbon intensity constraint policy (CICP) on TFEEG, through the difference-in-difference-in-differences (DDD) strategy. Finally, using counterfactual, re-grouping and quasi-DID analyses, we conduct a series of robustness tests of the empirical results. The results show that the TFEEG in China’s industrial sector experienced an overall declining trend between 2001 and 2014. The implementation of the EICP has had a significantly negative effect on the improvement of the TFEEG of sub-sectors with higher levels of energy intensity. After the implementation of the EICP, the TFEEG rate of these sub-sectors declined by 4.31%, compared to the rate of the other sub-sectors. The results of a series of robustness tests indicate that such a negative effect is credible. The marginal effect in the first two years after the implementation of the EICP was significantly negative, while the superposition effect of the introduction of a CICP on industrial TFEEG remained negative. Thus, the Chinese government should reinforce the implementation of energy-saving policies by introducing additional market-oriented auxiliary policies to propel the green development transformation of China’s industrial sector.