The study was designed to evaluate the impact of differentiated technological innovation efficiencies of industrial enterprises on the local emissions of environmental pollutants in Anhui province, China, during the period of 2012–2016. The econometric models of DEA and SEM-PLS and Malmquist index are used to explore the potential impacts of differentiated technological innovation efficiencies of industrial enterprises on the local emissions of environmental pollutants in Anhui province. After an initial analysis of SEM-PLS model, the models of DEA and Malmquist index are used to evaluate the differentiated degrees and dynamic development levels of local technological innovation efficiencies of industrial enterprises in different regions of Anhui province. With these analyses, the study presents three main results as follows. There is a positive correlation between the technological innovation efficiencies of industrial enterprises and the technological performance levels of environmental disposal. Meanwhile, there is a large gap among the environmental disposing performances of industrial enterprises in different regions of Anhui province. There is also a large gap between the expected and actual technological performances of industrial enterprises’ environmental disposal, according to the results of SEM-PLS analysis. Furthermore, there are several obvious characteristics of geographical distribution in the impact of differentiated technological innovation efficiencies of industrial enterprises on local environmental pollutant emissions observed from the results of the DEA and Malmquist index models. However, it is not consistent with the overall provincial development trend and regional distribution pattern of industrial economics in Anhui province over the period of 2012–2016. Under the rapid development of social economics and modern technological advance, there is a weak impact of differentiated technological innovation efficiency on the technological performance of industrial environmental disposal in different regions of Anhui province. Meanwhile, the environmental disposal capacity of enterprises’ technological innovation become declining too. Finally, some countermeasures and policy suggestions are put forward based on the investigation and comprehensive analyses of the DEA and SEM-PLS and Malmquist index models.

This study involves the climate change impact assessment of wheat producers in Khyber Pakhtunkhwa, Pakistan. An extensive farm survey of 150 farms was designed. From study area, three districts, namely, Chitral, D.I. Khan, and Peshawar, were selected through multistage sampling process. Yield simulation from Crop model DSSAT (Decision Support System for Agro Technology Transfer) was used for socio-economic impact assessment. Future climate scenarios were generated by selecting five GCMs from latest CMIP5 family with two RCPs 4.5 and 8.5, at two carbon concentrations of 499 ppm and 571 ppm, respectively. Yield simulations were analyzed for each GCM. Results of crop model revealed that wheat yield will increase in district Chitral, while in D.I. Khan and Peshawar, yields would be reduced due to climate change. For socio-economic impact assessment, TOA-MD (Trade-Off Analysis for Multi-Dimensional Impact Assessment) version 6 was used. Climate change impacts on poverty, net farm returns, and per capita income were calculated for different scenarios. The analysis was carried out on per-farm basis. The economic model results revealed that climate change has negative impact on wheat producers in D.I. Khan and Peshawar while making wheat producers better off in Chitral. The number of losers ranged from 54 to 66.21% and 50 to 61.99% in D.I. Khan and Peshawar, respectively. Losers are the farmers who would be economically worse off under perturbed climate. With current climate, the observed poverty rate would be 34 to 49 in D.I. Khan while 21.26 to 34.03 in Peshawar. The study recommended need for adaptation strategies to overcome the vulnerabilities of climate change.

China’s industrial energy consumption accounted for approximately 70% of national energy demand in the past four decades. Regarding energy demand and environmental pollution, success in controlling energy demand and reducing energy intensity for industrial sectors in China would play a crucial role for the country’s sustainable growth problems. To formulate targeted energy plans, the features and characters of China’s industrial energy intensity should be carefully evaluated. In this study, a carefully designed econometric model that considers different technological factors including indigenous R&D and technology spillovers from foreign direct investment and trade under a united framework is applied to investigate the β-convergence characteristics for China’s industrial energy intensity by employing a panel dataset covering China’s 34 industrial sectors over 2000–2010. The results verify the existence of β-convergence in industrial energy intensity during the sample period. For the industrial sectors overall and the light industrial sectors, the empirical results indicate that indigenous R&D and technology spillovers from FDI and imports are beneficial in curbing energy intensity. However, technology spillover through exports makes it harder to reduce energy intensity. In addition, not all technological factors have played a significant role in reducing energy intensity for the heavy industrial sectors.

Population growth and world climate changes are putting high pressure on agri-food production systems. Exacerbating use of energy sources and expanding the environmental damaging symptoms are the results of these difficult situations. This study was conducted to determine the energy balance for saffron production cycle and investigate the corresponding greenhouse gas (GHG) emissions in Iran. Saffron (Crocus sativus L.) is one of the main spice that historically cultivated in Iran. Data were obtained from 127 randomly selected saffron growers using a face to face questionnaire technique. The results revealed that in 5 years of saffron production cycle, the overall input and output energy use were to be 163,912.09 and 184,868.28 MJ ha⁻¹, respectively. The highest-level of energy consumption belongs to seeds (23.7 %) followed by chemical fertilizers (23.4 %). Energy use efficiency, specific energy, net energy, and energy productivity of saffron production were 1.1, 13.4 MJ kg⁻¹, 20,956.2 MJ ha⁻¹, and 0.1 kg MJ⁻¹, respectively. The result shows that the cultivation of saffron emits 2325.5 kg CO₂ eq. ha⁻¹ greenhouse gas, in which around 46.5 % belonged to electricity followed by chemical fertilizers. In addition the Cobb-Douglas production function was applied into EViews 7 software to define the functional relationship. The results of econometric model estimation showed that the impact of human labor, electricity, and water for irrigation on stigma, human labor, electricity, and seed on corm and also human labor and farmyard manure (FYM) on flower and leaf yield were found to be statistically significant. Sensitivity analysis results of the energy inputs demonstrated that the marginal physical productivity (MPP) worth of electricity energy was the highest for saffron stigma and corm, although saffron flower and leaf had more sensitivity on chemicals energy inputs. Moreover, MPP values of renewable and indirect energies were higher than non-renewable and direct energies, respectively.

The status of technical efficiency (TE) of environmental protection enterprises is crucial to the sustainable economic development. Based on the micro-survey data of China’s environmental protection enterprises from 2003 to 2013, through a systematic calculation and comparison about TE level under stochastic frontier analysis, this article investigated the distribution characteristics and heterogeneous sources of them comprehensively and found that first, there are wide-ranging technical efficiency differences among sub-sectors, ownership, and regions within China’s environmental protection industry, and this type of heterogeneity was significantly interfered by the institution and policy environment. Second, there is obvious scale economy effect and no scope economy effect in the TE distribution of China’s environmental protection enterprises, and their TE level has a positive response to management improvement and competition enhancement, but has a negative feedback on heavy asset expansion and debt-driven growth mode. Third, the overall TE levels of non-state-owned enterprises are higher than that of state-owned enterprises; the overall TE levels of enterprises located in the eastern provinces are higher than those of enterprises located in the central and western provinces. Fourth, reducing tax burdens of environmental protection enterprises is more effective to promote their TE level than providing governmental subsidies directly. Therefore, to promote the quality of the development for China’s environmental protection industry, it is necessary to emphasize the market mechanism. Based on the market power, we should accelerate the industry integration, cultivate the market demand, and promote market competition. Furthermore, the government should also need to design a targeted support system and differentiated policy arrangements for the development of environmental protection enterprises.

Green growth in manufacturing is critical to the sustainable development of manufacturing, and environmental regulations can help ensure green growth. The impact of environmental regulations on China’s manufacturing industry sectors is investigated to further green development in manufacturing. Using panel data for manufacturing industry sectors from 2008 to 2015, the Malmquist-Luenberger index model is employed to calculate green growth efficiency and an econometric model is constructed to measure the impact of environmental regulations on green growth. By using the system generalized method of moments (system GMM) model and other panel estimation models to generate regression results, it is found that environmental regulation exhibits a U-shaped nonlinear influence on green growth; as the intensity of environmental regulations increases, there is an initial inhibiting effect followed a positive impact on green growth in the manufacturing industry. Once environmental regulation intensity reaches a certain level, it mainly promotes green growth through technological progress. Further findings include the following: impacts of environmental regulation on green growth are heterogeneous across industries, and effects (e.g. U-shaped impacts) are most significant among high-energy industries, high-pollution industries, and medium-pollution industries.

Coal-fired power will remain China’s primary source of electricity for a long time to come. The clean development of coal-fired power generation has become an important strategic choice for China’s energy transformation. Based on collecting and sorting out the driving policies for China’s clean development of coal-fired power generation from 1997 to 2016, firstly, we reviewed the historical evolution of these policies in terms of the policy quantity, policy theme, and policy instrument. Then, we designed the scoring criteria to quantify the policies. Finally, the effectiveness of the overall policies and different policy instruments was empirically analyzed by the econometric model built on the basis of Cobb-Douglas production function. The results show that the annual release amount of driving policies for the clean development of coal-fired power in China presents a trend of fluctuating growth. Policy themes are mainly divided into two parts, namely production capacity management and air pollutants control; policy instruments mainly include elimination of backward units, project approval, standards, generation price regulation, tax incentives, loan policy, and information publicity; the overall policies have significant positive effects on the clean development of coal-fired power industry; in terms of policy instruments, the elimination of backward units and generation price regulation have significant effects on improving the energy efficiency; project approval and generation price regulation are effective for reducing SO₂ emissions rate; and the effects of standards, tax incentives, loan policy, and information publicity on the clean development of coal-fired power are not significant. On these bases, some policy implications to further promote the clean development of coal-fired power industry are provided.

Combining with the spatial variations in environmental technological innovation cross-province in China, this study employs the spatial econometric model to explore how environmental technological innovation responds to changes in command-and-control regulation and three other traditional determinants (the environmental R&D investments, the environmental labor force inputs, and the provincial economic development level) during the study period from 2004 to 2016.The results indicate that there is a clear sign of spatial correlation in the environmental technological innovation according to the global and local indicators of spatial association. Then, considering the spatial interdependence of environmental technological innovation and holding other variables constant, evidence shows that command-and-control regulation has a significant adverse effect on environmental technological innovation in the whole country and the Eastern region, while the effect is statistically positive in the Western region and non-significant in the Central region. We also find that the effects in two sub-periods of 2004–2010 and 2011–2016 are obvious differences because some new command-and-control regulation instruments were formulated and implemented in 2010. In addition, environmental technological innovation is also directly catalyzed by the environmental R&D investments, the environmental labor force inputs, and the provincial economic development level.

Based on the idea of a “Community of Human Destiny,” the Chinese government proposed the “Belt and Road” initiative, and clearly proposed to promote green development and strengthen ecological environmental protection. However, a considerable number of countries are resource-rich economies with serious market misallocations. Using the stochastic frontier analysis (SFA) combined with the directional distance function (DDF) framework, this paper measures the green total factor productivity (GTFP) and its items (i.e., technical change and efficiency change) of 33 countries along the Belt and Road in 1995–2012, and then the impact of market misallocations on GTFP is analyzed. The following conclusions are drawn: (1) The main driving force for GTFP promotion in Asian countries came from technical change, while in European countries, it came from efficiency change. (2) Market misallocations had significantly hindered the GTFP of these economies. Countries with greater market misallocations have smaller GTFP. (3) Results based on counterfactual measures showed that GTFP could be increased by up to 4.04% and the average can be increased by 1.24% after eliminating market misallocations.

This paper explores the effects of finance on environmental degradation and investigates environmental Kuznets curve (EKC) of each country among 52 that participate in the One Belt and One Road Initiative (OBORI) using the latest long panel data span (1980–2016). We utilized panel long run econometric models (fully modified ordinary least square and dynamic ordinary least square) to explore the long-run estimates in full panel and country level. Moreover, the Dumitrescu and Hurlin (2012) causality test is applied to examine the short-run causalities among our considered variables. The empirical findings validate the EKC hypothesis; the long-run estimates point out that finance significantly enhances the environmental degradation (negatively in few cases). The short-run heterogeneous causality confirms the bi-directional causality between finance and environmental degradation. The empirical outcomes suggest that policymakers should consider the environmental degradation issue caused by financial development in the One Belt and One Road region.