Research on water environmental indicators prediction method based on EEMD decomposition with CNN-BiLSTM.

Water resources protection is related to the development of the social economy, and the monitoring and prediction of water environmental indicators have important practical significance. In view of the seasonality, periodicity, uncertainty, and nonlinear characteristics of water quality indicators data, traditional prediction models have poor performance. To address this issue, this paper introduces a hybrid water quality index prediction model based on Ensemble Empirical Mode Decomposition (EEMD), combined with Convolutional Neural Network (CNN) and Bidirectional Long Short-Term Memory Network (BiLSTM). We have conducted out experiments to predict dissolved oxygen based on the water quality monitoring indicators of the Liaohe National Control Sanhongcun Village station in Yichun City. The results show that the model proposed in this paper improves the [Formula: see text] index by 5%, 7% and 5% compared to the suboptimal model in the 4-h, 1-day and 2-day index predictions, respectively.

Health benefits from risk information of air pollution in China.

Risk-related information regarding air pollution can help people understand the risk involved and take preventive measures to reduce health loss. However, the health benefits through these protective behaviors and the health threat of information inequality have not been systematically measured. This article reports the health gains and losses caused by the interaction of "air pollution-air pollution information-human", and studies the heterogeneity and impact of this interaction. Based on field investigations and transfer learning algorism, this study compiled the first nationwide city-level risk-related information (ERI) response parameter set in China. Then, we developed a Information-Behavioral Equivalent PM2.5 Exposure Model (I-BEPEM) model to project the health benefits caused by the impact of environmental risk-related information on residents' protective behaviors under different scenarios. The protective behavior led by air pollution risk information reduces 5.7% PM2.5-related premature deaths per year. With a 1% increase in regional ERI reception, PM2.5-related premature mortality decreases by 0.1% on average; If the level of information perception and behavioral protection in all cities is the same as that in Beijing, PM2.5-related premature deaths will decrease by 6.9% annually in China. Further, changing the air quality standard issued by China to the American standard can reduce the overall PM2.5-related premature deaths by 9.9%. Meanwhile, compared with men, other age groups and rural residents, women, older persons, and urban residents are more likely to conceive risk information and adopt protective behaviors to reduce the risk of premature death from air pollution. Air pollution risk information can significantly reduce people's health loss. Changing the real-time air quality monitoring information indicator standard to a more stringent level can quickly and effectively enhance this effect. However, the uneven distribution of this information in regions and populations has resulted in the inequality of health gains and losses.

Changes in environmental degradation parameters in Bangladesh: The role of net savings, natural resource depletion, technological innovation, and democracy.

Most researchers consider CO2 emissions to be the primary indicator of environmental degradation. Similarly, ecological footprint appears to be a significant proxy for environmental degradation in recent research due to its multifaceted impact on the natural environment. With this in mind, this study investigates fluctuations in CO2 emissions and ecological footprint as indicators of environmental degradation in Bangladesh from 1980 to 2020, and how they are influenced by net savings, natural resource depletion, technological innovation, and democracy. The non-linear ARDL (NARDL)-based asymmetric analysis finds that positive changes in net savings, natural resource depletion, and democracy positively impact both parameters of environmental degradation in the long run. On the other hand, a positive change in technological innovation reduces these parameters in the long run. Likewise, negative changes in net savings and technological innovation reduce environmental degradation. In contrast, negative changes in natural resource depletion and democracy exacerbate these two parameters and degrade environmental quality in the long run. However, there are some variations in the short-run influence of the predictors on the predicted variable. Overall, the findings of this study suggest that policymakers must strategically exploit natural resources, net savings, technology diffusion, and democratic principles to preserve the natural environment in Bangladesh.

Does electricity price reduction bring a sustainable development of business: Evidence from fine-grained industrial electricity consumption data in China.

This paper studies the impact of electricity price reduction policy on the economic activities and carbon emissions of different industries. Since 2018, the Chinese government has advocated reducing electricity price for industrial customers in order to alleviate the non-tax burden on businesses. Using monthly electricity consumption and user data from 2016 to 2019, we find that the electricity price reduction has significantly increased the industrial electricity consumption and users. Heterogeneity analyses show that the effect is greater in heavy polluted industries and industries in low and medium GDP regions. The results of threshold impact analysis show that the threshold value of heavy pollution industries was lower than that of general industry and commerce, while heavy pollution industries are more sensitive to electricity prices than general industries. Moreover, the reduction of electricity prices results in a higher percentage of carbon emissions growth in heavy pollution industries. Our result can also help the policymakers access the costs and benefits of electricity price reduction for industrial customers more accurately.

Environmental degradation, renewable energy, and economic growth nexus: Assessing the role of financial and political risks?

Sustainable development goal (SDG), which focuses on affordable and sustainable energy, provides a practical solution to realize sustainable growth. In addition, this target can encourage the realization of SDG 13 (climate action). However, factors like political and financial risk can impact climate actions and renewable energy. Therefore, this research extends the debate on the ecological footprint (EF) mitigation and achievement of SDGs by evaluating the renewable energy, political risk, financial risk, and EF nexus in an Environment Kuznets Curve (EKC) framework from 1986 to 2018. Panel data for the Association of Southeast Asian Nations (ASEAN) is estimated using second-generation approaches. The CuP-FM test results indicated that the EKC is present in ASEAN in the context of renewable energy, financial risk, and political risk. Furthermore, the findings revealed that controlling political and financial risks is a useful mitigation strategy because EF decreases as these risks are reduced. Notably, a decrease in EF has been linked to the use of renewable energy. These results are verified by using CO2 emissions as an alternative proxy for environmental degradation. Moreover, both financial and political risk Granger cause renewable energy and economic growth indicating that controlling financial and political risk is necessary for sustainable development.

The simultaneous impact of education and financial development on renewable energy consumption: an investigation of Next-11 countries.

The use of fossil fuels is a primary source of global warming owing to the greenhouse effect. Renewable energy is the best alternative environment-friendly energy source. Previous studies have highlighted the significant influence of financial development and education on renewable energy. However, the simultaneous effects of these two factors on renewable energy have rarely been examined, especially in emerging economies. This study employed dynamic seemingly unrelated cointegrating regression and the Dumitrescu-Hurlin causality test to analyze the effect of education and financial development on renewable energy consumption in N-11 countries during 1990-2016. Empirical results show that financial development significantly increased renewable energy use; however, education failed to make a positive difference. Additionally, bidirectional- and unidirectional causality was observed for financial development and education, respectively, toward renewable energy. This suggests that policymakers should combine financial development policies with education to improve the efficiency of renewable energy use.

Promoting economic and environmental resilience in the post-COVID-19 era through the city and regional on-road fuel sustainability development.

How to control the global temperature rise within 1.5 °C in the post-COVID-19 era has attracted attention. Road transport accounts for nearly a quarter of global CO2 emissions, and the related sulfur dioxide (SO2) emissions also trigger air pollution issues in population-intensive cities and areas. Many cities and states have announced a timetable for phasing out urban-based fossil fuel vehicles. By combining a Markov-chain model with a dynamic stochastic general equilibrium (DSGE) model, the impacts of on-road energy structural change led by phasing out fossil fuel vehicles in the road transportation sector are evaluated. The impact of automobile emissions (both CO2 and SO2) on the environment is evaluated, taking into consideration of variation between cities, regions, and countries. Two other major driving forces in addition to CO2 emissions reduction in promoting fossil fuel vehicles' transition toward net-zero carbon are identified and analyzed with multiple different indicators. Under the framework of the DSGE model, climate policy instruments' effects on economic development, energy consumption, and their link to economic and environmental resilience are evaluated under exogenous shocks as well.

Trade-off between environmental benefits and time costs for public bicycles: An empirical analysis using streaming data in China.

In recent years, bicycle sharing has become more popular in cities and towns around the world. Public bicycles are one of the important forms of bicycle sharing. The use of public bicycles instead of motor vehicles has brought about changes in environmental benefits for the society, and at the same time, it has also changed the travel time of residents. Because these changes are potential and cannot be measured directly, we put forward the calculation methods of environmental benefits and time costs of public bicycles according to the concept of opportunity cost. Taking Hohhot, the capital city of Inner Mongolia, as an example, according to the streaming data of 9.76×106 valid orders of public bicycle trips in 2016, we found that the use of public bicycles could reduce consumption of standard coal by as much as 5,796.11 tons (accounting 0.16‱ of the total coal consumption in Inner Mongolia) and carbon emissions were reduced by 4,381.28 tons (accounting 0.30‱ of the total carbon emissions in Inner Mongolia). However, the promotion of public bicycles is not without disadvantages. The use of public bicycles has increased the average travel time of residents by 0.06 hours, which is neglected in previous studies. The contribution of public bicycles to saving 1kg standard coal corresponds to 0.10 hours of travel time waste. Thus, reducing 1kg of carbon emissions is corresponding to a waste of 0.14 hours of travel time. The use of public bicycles varies among different income groups, which is caused by the value of travel time. Low-income groups use more frequently than high-income groups. Generally speaking, low-income groups bring more environmental benefits to society through the use of public bicycles, but bear more time costs. Therefore, we propose a carbon tax on high-carbon transportation modes to encourage green travel and balance the environmental benefits and time costs of public bicycles.

Nonrenewable energy-environmental and health effects on human capital: empirical evidence from Pakistan.

This research work reconnoiters the impact of nonrenewable energy (NRE) consumptions, environmental pollution, and mortality rate on human capital in the presence of economic growth and two common diseases, measles and tuberculosis (TB) in Pakistan. The study uses data from 1995 to 2017 and employs the Autoregressive Distributive Lag (ARDL) model to investigate cointegration and long-run dynamics. Results indicate that nonrenewable energy (oil, coal, and gas) increase air pollution, measles, TB cases, and mortality rate, which affect the human capital in Pakistan. The results of the ARDL confirm the long-run and short-run effects of fossils fuels, air pollution, and diseases on human capital. The results of the Granger Causality confirm the feedback hypothesis between nonrenewable consumption and human capital, between air pollution and human capital. Measles and TB diseases Granger cause human capital. The study recommends some essential points for energy management, environmental management, and diseases control programs to uplift the human capital in Pakistan.

Dynamic linkages among CO2 emissions, human development, financial development, and globalization: empirical evidence based on PMG long-run panel estimation.

This study investigates the impact of the human capital index, globalization, and financial development on carbon dioxide of grouping OECD countries using pool mean group estimation technique from 1990 to 2015. This study also applies the second-generation cross-sectional augmented Dickey-Fuller and cross-sectional Im, Pesaran, Shin panel (CIPS) unit root, and the latest (Westerlund 2008) cointegration tests for further investigations. The result shows that both the human development index and financial development stimulate environmental improvement by using PMG long-run panel estimation approach. Furthermore, the pairwise Dumitrescu-Hurlin panel causality results prove the two-way causal association between financial development and carbon emissions. The unidirectional causality running from globalization and human development index towards carbon emission is also supported. Based on the aforementioned results, we provide a set of recommendations for policy implication. Graphical abstract.

The nexus between urbanization, road infrastructure, and transport energy demand: empirical evidence from Pakistan.

Transport sector of Pakistan contributes more than one half to the national energy consumption. This sector is dominated by road transportation and mainly relies on fossil fuels. The country is going through rapid unplanned urbanization, which can lead to detrimental health and ecological consequences by intensifying road transport energy consumption. Therefore, the current study investigates the effect of urbanization on road sector energy consumption controlling for economic growth, road infrastructure, and industrialization. The autoregressive distributed lag (ARDL) approach is used to examine the long-run and short-run relationship between variables over the period 1971 to 2018. The vector error correction model (VECM) is employed to analyze the causality between variables. The results disclose a significant positive contribution of urbanization to road sector energy consumption. Further, road infrastructure, economic growth, and industrialization stimulate road transport energy consumption. Feedback effect exists between urbanization and road transport energy consumption, while economic growth Granger causes road sector energy consumption, urbanization, and road infrastructure. The findings imply that energy conservation and sustainable urbanization policies are a better choice under the current economic situation. Also, road infrastructure development in rural areas may reduce rural to urban migration.

Investigating the impact of human capital on the ecological footprint in India: An empirical analysis.

Many recent studies have focused on the influencing factors of the ecological footprint, but less attention has been given to human capital. Human capital, which is based on education and rate of return on education, may reduce the ecological footprint since environmental issues are human-induced. The current study investigates the impact of human capital on the ecological footprint in India for the period 1971 to 2014. The outcomes of the newly developed combined cointegration test of Bayer and Hanck disclose the long-run equilibrium relationship between variables. The findings reveal a significant negative contribution of human capital to the ecological footprint. The results of the causality test show that human capital Granger causes the ecological footprint without any feedback. In addition, energy consumption adds to the ecological footprint, while the relationship between economic growth and ecological footprint follows an inverted U-shaped pattern. The findings unveil the potential to reduce the ecological footprint by developing human capital.

Renewable energy, economic growth, human capital, and CO2 emission: an empirical analysis.

This study contributes to the literature by estimating the interaction effects of economic growth and renewable energy consumption on carbon dioxide (CO2) emissions with the inclusion of human capital. The interaction between economic growth and renewable energy consumption suggests how income level affects energy consumption and CO2 emissions. The study applies three-stage least square and ridge regression methods with Pakistani data from 1980 to 2014. The empirical findings show that the interaction effect of income and renewable energy contributes to CO2 emissions. Besides, trade openness also increases CO2 emissions, while the human capital mitigates CO2 emissions. Furthermore, the moderating effect of economic growth helps to form the environmental Kuznets curve (EKC) hypothesis in Pakistan.

Does globalization increase the ecological footprint? Empirical evidence from Malaysia.

This study focuses to investigate the relationship between globalization and the ecological footprint for Malaysia from 1971 to 2014. The results of the Bayer and Hanck cointegration test and the ARDL bound test show the existence of cointegration among variables. The findings disclose that globalization is not a significant determinant of the ecological footprint; however, it significantly increases the ecological carbon footprint. Energy consumption and economic growth stimulate the ecological footprint and carbon footprint in Malaysia. Population density reduces the ecological footprint and carbon footprint. Further, financial development mitigates the ecological footprint. The causality results disclose the feedback hypothesis between energy consumption and economic growth in the long run and short run.

Dynamic linkages among CO2 emissions, health expenditures, and economic growth: empirical evidence from Pakistan.

The linkage between high concentration of greenhouse gases (GHGs) and climate change is well recognized as there is severe influence of climate change on public health. Carbon dioxide is most prominent GHG which deteriorates the environment and impacts human health. On the parallel, economic growth also affects health conditions sometimes positively or vice versa. The objective of this research work is to examine the dynamic linkages among CO2 emissions, health expenditures, and economic growth in the presence of gross fixed capital formation and per capita trade by using auto regressive distributive lag (ARDL) model for Pakistan covering annual data from the year 1995-2017. Our empirical results show that there is significant long run as well as short-term causal relationship between health expenditure, CO2 emissions, and economic growth in Pakistan. Bidirectional relationship of Granger causality is found between health expenditures and CO2 emissions, and further between health expenditures and economic growth. Short-run unidirectional causality is running from carbon emissions to health-related expenditures. The bidirectional causal relationship is also investigated between carbon emissions and growth as well as gross fixed capital formation and growth. Then, policy recommendations towards controlling pollution, particularly CO2 emissions and health expenditures without compromising economic growth are suggested. Graphical abstract .

Does biomass energy consumption help to control environmental pollution? Evidence from BRICS countries.

The dilemma of rising environmental pollution in recent decades has raised the demand for clean energy sources. However, some newly developed energy sources, such as biomass energy, may or may not contribute to reducing environmental stress. This study investigates biomass energy consumption and environmental pollution in BRICS countries by applying the generalized system method of moment (GMM) model for empirical estimation from 1992 to 2013. The results show that biomass energy consumption behaves as a clean energy source in reducing environmental pollution. The study also found support for the presence of an N-shaped relationship between income and pollution and found that trade openness is the only factor that contributes to pollution in BRICS countries. These results can assist policymakers in considering biomass energy as a clean source of energy in the effort to achieve both energy security and environmental sustainability.

Will regional economic integration influence carbon dioxide marginal abatement costs? Evidence from Chinese panel data.

With frequent trade and technology diffusion, the barriers between regions are gradually weakening, and regions have become more integrated over recent years. Regional economic integration not only stimulates labour mobility, but also achieve scale economy, both of which may also influence carbon dioxide (CO2) marginal abatement costs through affecting energy consumption, CO2 emissions, productivity growth, and technical progress. Nevertheless, to the best of our knowledge, none of the studies has currently concerned the influence of regional economic integration on CO2 marginal abatement costs. To fill this research gap, this study first theoretically clarifies the influence mechanism of regional economic integration on CO2 marginal abatement cost, and then empirically attempts to investigate their relationship in the context of China, with panel data models. To serve this purpose, the provincial CO2 marginal abatement cost and regional economic integration are estimated by parametric directional distance function and price-based approach, respectively. The results show that China's regional economic integration level indeed gradually improved over 2002-2011 except in 2003-04 and 2006-09 due to the spread of Severe Acute Respiratory Syndrome (SARS) and the sub-prime loan crisis. Moreover, evolution of regional economic integration indeed contributes to the increase of CO2 marginal abatement cost at 5% significance level. Using robust tests, it can be found that the results are also reliable and robust to sub-samples.