Quantification of Industrial Wastewater Discharge From the Major Cities in Sichuan Province (China) from 2003 to 2018

Wastewater discharge is produced as a side effect of socio-economic activities and exerts severe pressure on the environment, its characteristics depend on the rate of urbanization and industrialization. We used spatial autocorrelation, environmental Kuznets curve (EKC), and logarithmic mean Divisia index (LMDI) model to study the spatial characteristics and driving factors of industrial wastewater discharge in Sichuan province (2003–2018). We showed that the amount of industrial wastewater discharge in Sichuan province for the period was reduced from 116580 to 42064.96 million tons as observed from the Moran index ranging from -0.31 to 0.30. We identified five types of the EKC (monotonically decreasing, N, inverted N, U, and inverted U shape) in 18 major cities of Sichuan province. The technical effect (from -0.28 to -16.37) can reduce the discharge of industrial wastewater, while structure effect (0.05–3.83), economy effect (0.19–7.79) and population effect (from -0.08 to 0.46) can promote the industrial wastewater discharge. Our findings suggest that industrial wastewater discharge was reduced and showed a scattered distribution characteristic in Sichuan Province from 2003 to 2018. It is necessary to strengthen technical management measures to reduce industrial wastewater discharge in Sichuan province.

Fractional Integral Inequalities for Some Convex Functions

In this paper, we obtained several new integral inequalities using fractional Riemann-Liouville integrals for convex s-Godunova-Levin functions in the second sense and for quasi-convex functions. The results were gained by applying the double Hermite-Hadamard inequality, the classical Holder inequalities, the power mean, and weighted Holder inequalities. In particular, the application of the results for several special computing facilities is given. Some applications to special means for arbitrary real numbers: arithmetic mean, logarithmic mean, and generalized log-mean, are provided.

Characteristics, Decoupling Effect And Driving Factors of Regional Tourism's Carbon Emissions In China

Using the tourism's carbon emission data of 30 provinces (cities) in China from 2007 to 2019, we have established a logarithmic mean Divisia index (LMDI) model to identify the main driving factors of carbon emissions related to tourism and a Tapio decoupling model to analyze the decoupling relationship between tourism's carbon emissions and tourism-driven economic growth. Our analysis suggests that China's regional tourism's carbon emissions are growing significantly with marked differences across its regions. Although there are observed fluctuations in the decoupling relationship between regional tourism's carbon emissions and tourism-driven economic growth in China, the data suggest weak decoupling. Nonetheless, the degree of decoupling is rising to various extents across regions. Three of the five driving factors investigated are also found to affect on emissions. Both tourism scale and tourism consumption lead to the growth of tourism's carbon emissions, while energy intensity has a significant effect on reducing emissions. These effects differ across regions.

Experimental analysis of dropwise condensation heat transfer on a finned tube: Impact of pitch size

Condensation is one of the essential processes in diverse industries due to its widespread use in various industrial applications such as power generation, water desalination, and air conditioning. Much research has been conducted to achieve better efficiencies and better heat transfer performances in condensers in the past decades. Condensation is divided into dropwise and filmwise based on the surface free energy, surface roughnesses, and condensate characteristics. This study investigated the influence of the 1-Octadecanethiol coating on vertically grooved copper tube’s condensation heat transfer characteristics. The hydrophobic surfaces have been created using self-assembled monolayers (SAMs) on the pure copper tubes (99.9% Cu). Moreover, four different pitch sizes of 1.5, 2, 2.5, and 3.5 mm have been implemented on the surface. Finally, the heat flux and the heat transfer coefficient as functions of logarithmic mean temperature difference are reported in the result section. For validation, the results obtained from the experiment were compared with available data in the literature, and an acceptable agreement was achieved. According to the results, it was found that the 1.5-mm pitch size has the highest heat flux, and the 3.5-mm pitch size has the lowest heat flux. Additionally, it can be inferred that the maximum heat flux of 696.71 kW/m2 was attributed to the 1.5-mm pitch size for logarithmic mean temperature differences of 64.3 K, which is approximately 1.24 times higher compared to the plain tube.

Influencing Factors of Carbon Emissions in the Construction Industry Based on Logarithmic Mean Divisia Index: A Case Study of China

Carbon emission is further intensified as urbanization and industrialization continue to accelerate. China has maintained its rapid economic development and urbanization in the last 2 decades. The development of the construction industry has not only consumed a large number of energy sources but also resulted in significant carbon emissions, causing some environmental damage. Recognizing the major influencing factors of carbon emissions in the construction industry has become a research hotspot to alleviate environmental pollution caused by the construction industry and meet industrial demands for energy saving and emission reduction. In this study, the factors that influence annual carbon emissions of different building types in China from 2011 to 2018 were decomposed by Logarithmic Mean Divisia Index (LMDI) through a case study in Henan Province. The major influencing factors of carbon emissions have been identified. Results demonstrate that the per capita carbon emission in the construction industry in Henan Province remains high from 2011 to 2018, but it decreases year by year. Carbon emissions from the construction industry in Henan Province increase due to economic development and energy structure. Energy efficiency can inhibit carbon emissions from the construction industry in Henan Province. The obtained conclusions have a positive effect on analyzing annual variations in carbon emissions from the construction industry in a region, identifying influencing factors, and proposing specific countermeasures of energy saving and emission reduction.

Quantification of Industrial Wastewater Discharge From The Major Cities in Sichuan Province (China) From 2003 To 2018

Wastewater discharge is produced as a side effect of socio-economic activities and exerts severe pressure on the environment, its characteristics depend on the rate of urbanization and industrialization. We used spatial autocorrelation, environmental Kuznets curve (EKC), and logarithmic mean Divisia index (LMDI) model to study the spatial characteristics and driving factors of industrial wastewater discharge in Sichuan province (2003–2018). We showed that the amount of industrial wastewater discharge in Sichuan province for the period was reduced from 116580 to 42064.96 million tons as observed from the Moran index ranging from -0.31 to 0.30. We identified five types of the EKC (monotonically decreasing, N, inverted N, U, and inverted U shape) in 18 major cities of Sichuan province. The technical effect (from -0.28 to -16.37) can reduce the discharge of industrial wastewater, while structure effect (0.05–3.83), economy effect (0.19–7.79) and population effect (from -0.08 to 0.46) can promote the industrial wastewater discharge. Our findings suggest that industrial wastewater discharge was reduced and showed a scattered distribution characteristic in Sichuan Province from 2003 to 2018. It is necessary to strengthen technical management measures to reduce industrial wastewater discharge in Sichuan province.

Multi-Perspective Analysis of Household Carbon Dioxide Emissions from Direct Energy Consumption by the Methods of Logarithmic Mean Divisia Index and σ Convergence in Central China

Currently, household carbon dioxide (CO2) emissions (HCEs) as one of the leading sources of greenhouse gas (GHG) have drawn notable scholarly concern. Thus, here, taking six provinces in the period of 2000–2017 of Central China as a case, we analyzed the characteristics and the driving factors of HCEs from direct energy consumption and three perspectives: Central China as a whole, urban-rural differences, and inter-provincial comparison. The drivers of direct HCEs were analyzed by the Logarithmic Mean Divisia Index (LMDI). The σ convergence was adopted for analyzing the trend of inter-provincial differences on the HCEs. The key findings are as follows. First, all the direct HCEs from three perspectives had an obvious growth trend. The total direct HCEs grew from 9596.20 × 104 tonnes in 2000 to 30,318.35 × 104 tonnes in 2017, with an increase of 2.16 times. Electricity and coal use were the primary sources. The urban and rural increases of direct HCEs were up 2.57 times and 1.77 times, respectively. The urban-rural gap of direct HCEs narrowed first and then widened. The direct HCEs in the six provinces varied significantly, but the gap was narrowing. Second, as a whole the per capita consumption expenditure and energy demand were the main drivers to the increment of HCEs, with cumulative contribution rates of 118.19% and 59.90%. The energy price effect was mainly responsible for the mitigation of HCEs. Third, the similar drivers’ trend can also be seen from the perspective of inter-provincial comparison. However, from the perspective of urban and rural difference, the population urban-rural structure effect played a reverse influence on both urban and rural areas. Thus, raising the energy prices appropriately, upgrading the residents’ consumption to a sustainable pattern, controlling the growth of population size reasonably, and optimizing the household energy structure might effectively mitigate the growth of HCEs in Central China.

Analysis of Changes in the Aggregate Exergy Efficiency of China’s Energy System from 2005 to 2015

Analysis of the change of overall energy efficiency performance of an energy system is a fundamental work for the energy-saving policymaking. However, previous studies seldom focus on energy stages from useful energy to final service, while most attention are paid on stages from energy source to useful energy. In this paper, we develop a high-resolution the Societal Exergy Analysis and Logarithmic Mean Divisia Index (SEA-LMDI) method to analysis changes and driving factors of the aggregate exergy efficiency, in which the boundary of the SEA is extended to passive systems and final services, and a LMDI decomposition method is developed to quantify contributions of efficiency factors and structure factors of all six stages on the aggregate exergy efficiency. A case study of China during 2005–2015 reveals that: (a) the aggregate exergy efficiency from energy source to final service is only from 3.7% to 4.8% during 2005–2015, showing a huge theoretical potential of efficiency improvement. (b) Large passive losses are identified in passive systems and nearly 2/3 of useful energy can be theoretically saved by improving passive systems. (c) Deep analysis of industrial coal-fired boilers indicates that the internal structural adjustments are also important for the aggregate improvement.