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This study is intended to expose the connectedness of green financing and other green policies like renewable energy and technological progress towards identifying the best practice to achieve climate goal cum sustainable environmental development for China within the period 1985–2021. Amid the increased utilization of fossil fuels in China's economic activities and its position as the highest carbon emitting country in the world, China is considered a financial stable economy with access to renewable energy source such as hydroelectric power. For effective research into the objective of this study, the study builds on mechanism of the green finance—renewable—technology and emission nexus with the help of linear dynamics of ARDL bound and VECM granger causality methods. Empirical results from both approaches have given insight to the selected objectives of this study. According to ARDL dynamics: (i) the coefficients of linear (1.802) and non-linear(− 1.860) (i.e. square term) of financial development are positively and negatively connected to the carbon emissions. This confirms the presence of inverted U-shape relationship between the financial development and carbon emissions. (ii) the relationship between hydroelectric power representing renewable energy and CO2 is negative—(− 0.19) and significant at 1% level. This results depicts the reduction power of hydroelectric power on CO2, (iii) also, a negative (− 0.000982) linkage between number of patent application representing technological innovation and environmental development through carbon emissions responses is established. Also, findings from VECM granger causality approach back the findings from ARDL through a nexus between the variables of interest (finance, hydroelectric power, and technology and carbon emissions). Findings point to the ability of green financing to reduce carbon emissions if green financing policies are utilized effectively in regulating carbon emissions. [ABSTRACT FROM AUTHOR]

Extreme flood events have detrimental effects on society, the economy and the environment. Widespread flooding across South East Queensland in 2011 and 2013 resulted in the loss of lives and significant cost to the economy. In this region, flood risk planning and the use of traditional flood frequency analysis (FFA) to estimate both the magnitude and frequency of the 1-in-100 year flood is severely limited by short gauging station records. On average, these records are 42 years in Eastern Australia and many have a poor representation of extreme flood events. The major aim of this study is to test the application of an alternative method to estimate flood frequency in the form of the Probabilistic Regional Envelope Curve (PREC) approach which integrates additional spatial information of extreme flood events. In order to better define and constrain a working definition of an extreme flood, an Australian Envelope Curve is also produced from available gauging station data. Results indicate that the PREC method shows significant changes to the larger recurrence intervals (≥100 years) in gauges with either too few, or too many, extreme flood events. A decision making process is provided to ascertain when this method is preferable for FFA. [ABSTRACT FROM AUTHOR]

This paper presents a general spatio-temporal model for assessing the air quality impact of environmental policies which are introduced as abrupt changes. The estimation method is based on the EM algorithm and the model allows to estimate the impact on air quality over a region and the reduction of human exposure following the considered environmental policy. Moreover, impact testing is proposed as a likelihood ratio test and the number of observations after intervention is computed in order to achieve a certain power for a minimal reduction. An extensive case study is related to the introduction of the congestion charge in Milan city. The consequent estimated reduction of airborne particulate matters and total nitrogen oxides motivates the methods introduced while its derivation illustrates both implementation and inferential issues. [ABSTRACT FROM AUTHOR]

Road transportation has attracted extensive attention throughout the world because of its high energy demands and numerous externalities. Sustainable road transportation has thus become a great challenge for politicians and decision-makers all over the world. There have been a series of studies indicating that appropriate pricing of fuel can be both effective and efficient for reducing overconsumption of transport fuel. However, relatively little research has been done on fuel price approaches in developing country contexts. For a country like China, where road traffic today is growing more than in other countries, there is a strategic interest to do more economic analyses of fair and efficient pricing of fuel. In this study, we present a strategic assessment of fuel pricing in energy conservation and CO reduction from road transportation in China, both in a retrospective and a prospective perspective. First of all, the correlation between fuel price and road transport gasoline demand, based upon data from 1995 to 2007, was examined with an econometric model. Secondly, on basis of the elasticity model, the potential reductions with respect to fuel demand and Green House Gas (GHG) emissions as a consequence of a strategic fuel tax implementation in China were examined up to 2030. The results indicate that such strategic fuel taxation can play a considerable role in steering the growth of road transport gasoline demand, and thus also Chinese GHG emissions. [ABSTRACT FROM AUTHOR]

In the logarithmic curves of the per capita GDP and the urbanization, with the traditional environmental Kuznets equation, this paper presented a coupling equation showing the relationship between urbanization and the atmospheric environment. Based on the 'double exponential' coupling curve, the principles of flattening, advancing and fast-falling that new coupling curve should be followed were discussed. According to the two indicators of environmental assessment, namely the treatment cost and the deterioration degree of the environment, a new dual four times matrix model with the corresponding countermeasures and environment policy were introduced. Taking Shandong Province as an example, the coupling relationship between urbanization and atmospheric environment was investigated. The coupling curve showed that it was in running-in stage, and atmospheric quality tended to be improved. SO curve fluctuated more significantly compared with soot and industrial dust curves. The matrix model shows that the combination of flattening principle and advancing principle is preferable for SO emissions, but the fast-falling principle is recommended for soot and industrial dust emissions. [ABSTRACT FROM AUTHOR]

The Kyoto Protocol calls for industrialized nations to cut greenhouse gas emissions by 5% from 1990 levels by 2008-2012, so developed countries are presenting various policies to reduce greenhouse gas that is produced in transport fields. One of those polices is a modal shift that changes from road freight to sea, inland waterways and railroad transportation that is eco-friendly. The increase of road freight brings road congestion, accidents, logistic costs, air pollution and greenhouse gases. Railroads are superior to the other modes of transportation in mass transportability, high speed, timeliness, safety and environmental-friendliness, but the railway industry has been pushed behind in competition. Korean railroads were used by passengers and for freight transport popularly until the middle of the 20th century. However, because of the sudden change of logistics environments, having time efficiency being most important, railroads lost logistic competitive power against the transportation by truck. This paper intends to examine the modal shift to railroad transportation, which enjoys high interest as environmentally-friendly logistics, i.e., the modal shift strategy. Efficiency analysis is conducted using DEA and exploratory factors are identified for the modal shift of the companies. This paper also proposes an alternative plan for green logistics and environmentally-friendly logistics, by analyzing the characteristics of the railroad cargo transportation system and the conditions of local railroad cargo transportation. [ABSTRACT FROM AUTHOR]

Given a collection of science-based computational models that all estimate states of the same environmental system, we compare the forecast skill of the average of the collection to the skills of the individual members. We illustrate our results through an analysis of regional climate model data and give general criteria for the average to perform more or less skillfully than the most skillful individual model, the “best” model. The average will only be more skillful than the best model if the individual models in the collection produce very different forecasts; if the individual forecasts generally agree, the average will not be as skillful as the best model. [ABSTRACT FROM AUTHOR]

Urbanization is one of the most important anthropogenic activities that create extensive environmental implications at both local and global scales. Dynamic urban expansion models are useful tools to understand the urbanization process, project its spatiotemporal dynamics and provide useful information for assessing the environmental implications of urbanization. A hybrid urban expansion model (NNSCA model) was proposed to simulate rapid urban growth in a typical industrial city, Dongying, China, by coupling a artificial-neural-network-based stochastic cellular automata model and several socioeconomic indictors, i.e., the per capita income of the rural population, the per capita income of the urban population, population and gross domestic products of the city. Good conformity between simulated and actual urban patterns suggested that the NNSCA model was able to effectively simulate historic urban growth and to generate realistic urban patterns. A series of scenario analyses suggested that the expanding urban would threaten the ecosystem health of coastal wetlands in the city unless environmental protection actions are taken in the future. The NNSCA model provides abilities to assess future urban growth under various planning and management scenarios, and can be integrated into ecological or environmental process models to evaluate urbanization’s environmental implications. [ABSTRACT FROM AUTHOR]

We develop methodologies to enable applications of reliability-based design optimization (RBDO) to environmental policy setting problems. RBDO considers uncertainty as random variables and parameters in an optimization framework with probabilistic constraints. Three challenges in environmental decision-making problems not addressed by current RBDO methods are efficient methods in handling: (1) non-normally distributed random parameters, (2) discrete random parameters, and (3) joint reliability constraints (e.g., meeting constraints simultaneously with a single reliability). We propose a modified sequential quadratic programming algorithm to address these challenges. An active set strategy is combined with a reliability contour formulation to solve problems with multiple non-normal random parameters. The reliability contour formulation can also handle discrete random parameters by converting them to equivalent continuous ones. Joint reliability constraints are estimated by their theoretical upper bounds using reliability indexes and angles of normal vectors between active constraints. To demonstrate the methods, we consider a simplified airshed example where CO and NOx standards are violated and are brought into compliance by reducing the speed limits of two nearby highways. This analytical example is based on the CALINE4 model. Results show the potential of this approach to handle complex large-scale environmental regulation problems. [ABSTRACT FROM AUTHOR]

Environmental indices (EI) constitute a common communication tool that is often used to describe the overall status of environmental systems (air, water and soil). EI development entails the use of mathematical operators to aggregate various non-commensurate input parameters in a logical manner. The ordered weighted averaging (OWA) operator is a general mean type operator that provides flexibility in the aggregation process such that the aggregated value is bounded between minimum and maximum values of the input parameters. This flexibility of the OWA operator is realized through the concept of orness, which is a surrogate for decision maker’s attitude. The type of input parameters also affects the choice of aggregation operators. If the input parameters are linguistic or fuzzy, the aggregation through OWA operators is not possible, and the use of fuzzy arithmetic is warranted. The concept of fuzzy number OWA (FN-OWA) operators is explored to handle situations in which one or more input parameter has fuzzy (or linguistic) values. The proposed approach is demonstrated using data provided in an earlier study by Swamee and Tyagi (ASCE J Environ Eng 126(5):451–455, ) for establishing water quality indices. Multiple hypothetical scenarios are also generated to highlight the utility and sensitivity of the proposed approach. [ABSTRACT FROM AUTHOR]

In this study, the turbulent flow structure over the ripples at the bed of open channel was investigated experimentally. An analysis of bursting process was used to recognize the susceptible regions for sediment entrainment and deposition over the ripples. Two artificial ripples were built according to the ripples, formed by nature. Three different configurations of ripples were used by changing the wavelength. According to analysis of bursting event it was found that at the stoss side of ripples, quadrants (II) and (IV) were dominant to the quadrants (I) and (III) and at the lee side of the ripple it was vice versa. Also the transition probabilities of the bursting events were determined. The results showed that stable organizations of each class of the events had highest transition probabilities whereas cross organizations had lowest transition probabilities. Additionally, an effort was made to find the average inclination angle of the bursting events in quadrants (II) and (IV). The results showed that the mean angle of events in quadrants (II) and (IV) increases at the downstream of stoss side to the crest in each experimental test. Also, at the lee side where the sediment particles were deposited, the inclination angles had the highest values. [ABSTRACT FROM AUTHOR]

We propose a research agenda for studying six basic questions about the impacts of alternate international invasive species control mechanisms on economic agents in a nation such as the USA. The six questions are as follows. First, when can one justify a trade ban as an effective regulatory policy? Second, what are the properties of control rules that vary by port of entry and whether a shipment is viewed as a routine or as a first-time entry? Third, when should a port manager in the USA use information about the dollar value of the products being transported by ships from two exporting firms and the expected time it takes to inspect ships from these two firms to grant preferential treatment to one or the other firm? Fourth, what are some reasonable measures of the trade related risk from invasive species? Fifth, how useful is strategic trade policy as an invasive species management tool? Finally, when analyzing a biological invasion, is it more appropriate to focus on the likelihood of this event or, instead, on the magnitude of the event? [ABSTRACT FROM AUTHOR]

High concentrations of ammonia in a river can cause fish kills and harms to other aquatic organisms. A simple water quality model is needed to predict the probability of ammonia concentration violations as compared to the US Environmental Protection Agency’s ammonia criteria. A spreadsheet with Random Monte Carlo (RMC) simulations to model ammonia concentrations at the mixing point (between a river and the effluent of a wastewater treatment plant) was developed with the use of Microsoft Excel and Crystal Ball add-in software. The model uses effluent and river ammonia, alkalinity, and total carbonate data to determine the probability density functions (PDFs) for the Monte Carlo simulations. Normal, lognormal, exponential and uniform probability distributions were tested using the Chi-square method andp-value associated with it to choose the best fit to the random data selected from the East Burlington wastewater treatment plant in North Carolina and the Clinch River in Tennessee. It is suggested that different options be tested with a minimum of three classes and a maximum ofn/5 classes (n= number of data points) and the highest probability (p-value) for the PDF being tested be chosen. The results indicted that six violations to the EPA criterion for maximum concentration (CMC) were predicted when using 2000 RMC simulations and PDFs fitted to the available data, which violate the current criterion of no more than one violation over 3 years. All violations occur when the pH of the blend ranges from 8.0 to 9.0. No violations were found to the criteria of chronic concentration (CCC) using RMC. [ABSTRACT FROM AUTHOR]