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The present study is motivated by the need to decouple economic growth from environmental degradation given the new wave of chase for higher economic growth trajectories comes with its environmental cost implications, especially among developing blocs like the Emerging 7 (E7) countries. There is a consistent trade-off between economic growth versus environmental quality. Government apparatus are perpetually on the chase for low-carbon emission policies via the pursuit for green economy. To this end, this present study extends the conventional environmental Kuznets curve (EKC) argument by incorporating the role of institution in emerging industrialized economies (E7) and using second-generation panel analysis methods like mean group (MG), augmented mean group (AMG), common correlated effects mean group (CCEMG), and the Dumitrescu and Hurlin causality test for more robust estimates and inferences. To this end, we explore the long-run and causality relationship between economic growth, quadratic form of economic growth, institutional quality, trade flow, investment in energy sector, and financial development in an EKC environment. Empirical analysis established a long-run equilibrium relationship among the outlined variables over the study period. The long-run regression shows the presence of EKC in the E7. Thus, suggesting the preference for GDP growth over environmental quality at the earlier stage of growth curve. Interestingly, investment in energy, trade flow dynamics across the blocs, and financial development dampens the detrimental effect of environmental pollution as we observed negative relationship with the ecological footprint. On the contrary, quality of institution is weak as institutional quality increase (worsen) the quality of environment in the E7 economies. From a policy perspective, this current study proposed the need for more stringent environmental treaties and regulations and promotion of green economy without compromising economic growth. In the conclusion part of the study, more details and specifics about the policy blueprint are presented.

This study highlights how Chinese economic development detrimentally impacted water quality in recent decades and how this has been improved by enormous investment in environmental remediation funded by the Chinese government. To our knowledge, this study is the first to describe the variability of surface water quality in inland waters in China, the affecting drivers behind the changes, and how the government-financed conservation actions have impacted water quality. Water quality was found to be poorest in the North and the Northeast China Plain where there is greater coverage of developed land (cities + cropland), a higher gross domestic product (GDP), and higher population density. There are significant positive relationships between the concentration of the annual mean chemical oxygen demand (COD) and the percentage of developed land use (cities + cropland), GDP, and population density in the individual watersheds (p < 0.001). During the past decade, following Chinese government-financed investments in environmental restoration and reforestation, the water quality of Chinese inland waters has improved markedly, which is particularly evident from the significant and exponentially decreasing GDP-normalized COD and ammonium (NH4+-N) concentrations. It is evident that the increasing GDP in China over the past decade did not occur at the continued expense of its inland water ecosystems. This offers hope for the future, also for other industrializing countries, that with appropriate environmental investments a high GDP can be reached and maintained, while simultaneously preserving inland aquatic ecosystems, particularly through management of sewage discharge.

AbstractThe potential impacts of future climate scenarios on water balance and flow regime are presented and discussed for a temporary river system in southern Italy. Different climate projections for the future (2030–2059) and the recent conditions (1980–2009) were investigated. A hydrological model (Soil and Water Assessment Tool) was used to simulate water balance at the basin scale and streamflow in a number of river sections under various climate change scenarios, based on different combinations of global and regional models (global circulation models and regional climate models). The impact on water balance components was quantified at the basin and subbasin levels as deviation from the baseline (1980–2009), and the flow regime alteration under changing climate was estimated using a number of hydrological indicators. An increase in mean temperature for all months between 0.5–2.4 °C and a reduction in precipitation (by 4–7%) was predicted for the future. As a consequence, a decline of blue water (7–18%) and total water yield (11–28%) was estimated. Although the river type classification remains unvaried, the flow regime distinctly moves towards drier conditions and the divergence from the current status increases in future scenarios, especially for those reaches classified as I‐D (ie, intermittent‐dry) and E (ephemeral). Hydrological indicators showed a decrease in both high flow and low flow magnitudes for various time durations, an extension of the dry season and an exacerbation of extreme low flow conditions. A reduction of snowfall in the mountainous part of the basin and an increase in potential evapotranspiration was also estimated (4–4.4%). Finally, the paper analyses the implications of the climate change for river ecosystems and for River Basin Management Planning. The defined quantitative estimates of water balance alteration could support the identification of priorities that should be addressed in upcoming years to set water‐saving actions.

The potential for global forest cover The restoration of forested land at a global scale could help capture atmospheric carbon and mitigate climate change. Bastin et al. used direct measurements of forest cover to generate a model of forest restoration potential across the globe (see the Perspective by Chazdon and Brancalion). Their spatially explicit maps show how much additional tree cover could exist outside of existing forests and agricultural and urban land. Ecosystems could support an additional 0.9 billion hectares of continuous forest. This would represent a greater than 25% increase in forested area, including more than 200 gigatonnes of additional carbon at maturity.Such a change has the potential to store an equivalent of 25% of the current atmospheric carbon pool. Science , this issue p. 76 ; see also p. 24

AbstractAlthough canopy height has long been a focus of interest in ecology, it has remained difficult to study at large spatial scales. Recently, satellite‐borne LiDAR equipment produced the first systematic high resolution maps of vegetation height worldwide. Here we show that this new resource reveals three marked modes in tropical canopy height ~40, ~12, and ~2 m corresponding to forest, savanna, and treeless landscapes. The distribution of these modes is consistent with the often hypothesized forest‐savanna bistability and suggests that both states can be stable in areas with a mean annual precipitation between ~1,500 and ~2,000 mm. Although the canopy height states correspond largely to the much discussed tree cover states, there are differences, too. For instance, there are places with savanna‐like sparse tree cover that have a forest‐like high canopy, suggesting that rather than true savanna, those are thinned relicts of forest. This illustrates how complementary sets of remotely sensed indicators may provide increasingly sophisticated ways to study ecological phenomena at a global scale.

Abstract Plant competitive interactions influence the effect of herbicides, and the effect of competitive interactions on plant responses may be important to include in the ecological risk assessment of herbicides. In the present study the effect of competitive interactions and sublethal doses of 2 herbicides on plant species was investigated in competition experiments and fitted to empirical competition models. Two nontarget species commonly found in agroecosystems (Centaurea cyanus L. and Silene noctiflora L.) and 2 herbicides (glyphosate and metsulfuron methyl) were used in separate experiments. Plants were sprayed at the 6- to 8-leaf stage. Effects of herbicide treatments and plant density were modeled by generalization of a discrete hyperbolic competition model. The 10% effective dose (ED10) was calculated for C. cyanus. All experiments showed that as density increased, plants were negatively affected. Furthermore, in all cases, C. cyanus remained a better competitor than S. noctiflora. Nevertheless, the density of S. noctiflora (competitor) was an influential element in determining the ED10 of C. cyanus measured at the mature stage. With herbicide exposure, the competitive interactions were further altered; C. cyanus was less affected by glyphosate when S. noctiflora increased to high density. In contrast, at the young stage, conspecific density was important in determining the sensitivity of C. cyanus to metsulfuron methyl, whereas the density of the competitor S. noctiflora had a limited influence. Overall, the results demonstrate the importance of integrating the effect of herbicide and species interactions measured at the reproductive stage into the ecological risk assessments of pesticides. Environ Toxicol Chem 2019;38:2053–2064. © 2019 SETAC.

Electric vehicles (EVs) are considered a substitute for fossil-fueled vehicles due to rising fossil fuel prices and accompanying environmental concerns, and their use is predicted to increase dramatically shortly. However, the widespread use of EVs and their large-scale integration into the energy system will present several operational and technological hurdles. In the energy industry, an innovative solution known as the EVs smart parking lot (SPL) is introduced to handle EV charging and discharging electricity and energy supply challenges. This paper investigates social equity access and mobile charging stations (MCSs) for EVs, where the owner of MCSs is the EV parking lot. Accordingly, a new self-scheduling model for SPLs is presented in this paper that incorporates scheduling of the MCSs as temporary charging infrastructures while considering social equity access and optimizes SPL energy generation and storage schedule. The main objectives of this research are to (i) develop MCSs accessibility measures and quantify the equity impacts of MCSs locations by modeling prioritized demand based on several indices; (ii) determine the optimal set-points of SPL components (i.e., combined heat and power (CHP), photovoltaic system, electrical and heat-energy storage, and MCSs) to manage electrical peak demand and to maximize the economic benefits of SPLs. Results indicate that the proposed demand prioritization function model can meet the required EV charging demands for prioritized events, and the self-scheduling model for SPLs satisfies the charging demand of the EVs in the SPL location. Also, the social equity access to the EV charging stations is satisfied by analyzing the operation of MCSs around the prioritized demand of the prioritized events and social equity access indices.