Energy Policy Research Articles

Understanding how climate preferences, environmental policy stringency, and energy policy uncertainty shape renewable energy investments in Germany

Understanding how climate preferences, environmental policy stringency, and energy policy uncertainty shape renewable energy investments in Germany

Public perceptions on net zero energy houses in Japan

AbstractFor Japan, which has not operated nearly all of its nuclear power plants since 2011 and is dependent on thermal power generation, the introduction of renewable energy into homes is extremely important for the future formation of a sustainable society. However, the introduction of net zero energy house (ZEH) in detached houses, which account for 55% of all dwellings in Japan, has not progressed. To promote the introduction of ZEH, this study clarified the awareness of owners of detached houses regarding ZEH. We analyzed factors that influence such perception of solar photovoltaics (PV) technology using a 1000-sample online survey questionnaire. The survey was conducted in late January 2020 and included questions examining the public perception of solar installation and factors that were found to be important in previous research. We found that Japanese respondents who live in detached houses generally lack an understanding of renewables and that the level of interest in installing solar PV for the ZEH is low. We also found that awareness of renewables, such as knowing new energy policy and searching information on solar PV, is the critical factor of installing renewables. At the same time, most socio-demographic and neighborhood variables seem not to influence installing solar PV or other technologies for ZEH. This research will contribute to the Japanese government’s goal of strengthening education on renewable energy to promote ZEH.

Consumption-Based Energy Footprints in Iceland: High and Equally Distributed

With the urgent global need to limit warming to 2 °C as well as a localized need in our case study to address rising energy demand amid electrical and thermal network limitations, a critical examination of demand-side energy reductions and the concept of energy sufficiency is needed. This paper contributes to the sparse literature on bottom-up analysis by utilizing Iceland—a leader in renewable energy generation—as a case study to explore the socio-economic factors influencing energy footprints. Our findings reveal significant energy footprints across various consumption domains, particularly housing and mobility, influenced by income levels, urbanization, and lifestyle choices. The study highlights the paradox of a high renewable energy supply leading to potential misconceptions regarding abundant and low-cost energy, resulting in substantial energy consumption-related environmental impacts. Using detailed household consumption survey data, this research provides insights crucial for developing sustainable energy policies that not only target technological advancements but also address the need for a reduction in energy demand and a shift towards energy sufficiency. This work marks a contribution to the literature through the provision of a case study of low income inequality and high energy footprints in a highly renewable energy system context. Further, this work is useful for Icelandic and international policymakers to understand in such high-demand contexts which consumption domains would be most relevant for sufficiency policies. This comprehensive analysis opens pathways for future research to further explore the intersections of energy consumption, socio-economic factors, and well-being, offering a nuanced understanding necessary for crafting sufficiency and demand-side policies aimed at a sustainable energy future.

Renewable Energy Investments in Poland: Goals, Socio-Economic Benefits, and Development Directions

Renewable energy sources (RES) will play a key role in the transition to clean energy. Financial and socio-economic benefits determine the investment management in these energy sources. This article aims to indicate current energy policy goals, present socio-economic benefits resulting from renewable energy investments, and review further development directions in Poland. The research was carried out using desk research, case studies, and literature review methods to provide a broader economic context for RES investments. The scope of the research included both the Polish and the European Union contexts. The authors examined the Polish objectives of investment in renewable energy contained in strategic, planning, and other legal documents compared to EU targets, reviewed possible investments in renewable energy, and indicated wind farms and photovoltaic investments as the most effective ones from the point of view of further development which aims to meet the EU’s goals by 2030. The authors also demonstrated a wide range of socio-economic benefits based on literature reviews, analysis of policy documents, and regulations regarding the energy sector, and examined a specific example of investment implementation and identified the ecosystem of beneficiaries and their benefits.

Stock market reaction to new energy vehicle industry development plan: an event study in China

ABSTRACT The targets of energy conservation, decarbonization, and industry reinvigoration have significantly influenced the design of China’s new energy vehicle (NEV) industrial policies and nationwide electrification. As a monumental policy framework for energy transition in transportation sector, the NEV industry development plan plays an influential role in promoting cleantech diffusion and enhancing NEV competitiveness. This study employs an event study method to investigate the stock market reaction to the NEV plan shocks. The NEV plan announced in 2020 receives a markedly positive stock price effect of 3.72% in the 6-day event window. Heterogeneity tests on subsamples indicate that state-backed entities exhibit a similar effect to the total sample, while the automotive manufacturing class and original equipment manufacturers see a significantly higher market value gain of 6.56% and 13.34%, respectively. However, battery manufacturers, as one of the key participants in the NEV value chain, experience an insignificant stock price effect. This study documents the financial consequences of clean energy policies specific to the emission-intensive automotive manufacturing sector, highlights the effectiveness of government-to-investor signalling in a cleantech diffusion context, and reveals the implications to other economies seeking to deploy clean transport and enhance environmental sustainability.

HOW PASSENGER TRANSPORT IS DEVELOPING IN BULGARIA IN THE CONDITIONS OF A DYNAMIC CHANGING ENVIRONMENT?

The current study seeks to establish the preferences of Bulgarians through exploring how passenger transport in Bulgaria developed from 2012 to 2022. On a theoretical level, the characteristics of this sector are described, such as types of passenger transport vehicles. The research interest is aimed at tracking the dynamics behind all the options for passenger carriage forming the supply of the transport market in Bulgaria: by rail, bus, air, water, and urban electric transport. To achieve this objective, the parameters of activity in the passenger transport segment are used as the main measures – number of passengers, passenger-kilometres and average distance travelled. During the studied period, passenger transport in Bulgaria developed at variable rates and was influenced by environmental factors. The mode of transport most affected by the pandemic in 2020–2021 was by air. A decrease in the total number of passengers and overall performance for 2022 compared to 2012 can be observed. This decline is due to a decrease in bus and rail transport indicators. The study has established that Bulgarians prefer traveling by bus to other public transport alternatives. Although the absolute number of vehicles has decreased in this segment, it has the largest relative share according to the indicators of transported passengers and performed work as part of the total transport activity in the country. In a practical respect, attention is focused on modern solutions related to information and communication technologies, as well as some opportunities to attract more public transport passengers. The author also draws attention to some EU initiatives in the field of air and maritime transport concerning Union-wide energy policy.

Sustainable energy consumption – empirical evidence of a household in Poland Sustainable energy consumption, electricity demand , econometric model, household energy transition, energy policy impact

Sustainable energy consumption – empirical evidence of a household in Poland Sustainable energy consumption, electricity demand , econometric model, household energy transition, energy policy impact

The Impact of Energy-Related Uncertainty on Corporate Investment Decisions in China

This study investigates the impact of the Energy-related Uncertainty Index (EUI) on corporate investment among Chinese non-financial listed companies, focusing on two aspects: the effect of EUI fluctuations on investment behavior, and its differential impact on energy versus non-energy sectors. Utilizing a dataset of 2487 firms from 2007 to 2022, encompassing 22,346 firm-year observations, our analysis reveals that a 1% increase in the EUI leads to a 0.045% decrease in overall corporate investment. Notably, this effect is more pronounced in energy-related firms, where a 1% increase in EUI leads to a 0.057% reduction in investment. In comparison, non-energy-related firms exhibit a milder response, with a 1% increase in EUI resulting in a 0.026% decrease in investment. Given the average annual change in EUI over the sample period [2007–2022] of 27.710%, a 0.045% decrease in investment implies a substantial 1.246% per annum change in investment. This highlights the economically significant impact of EUI fluctuations on corporate investment decisions, particularly during periods of heightened uncertainty. These findings, validated through alternative EUI measures and investment metrics, provide crucial insights for understanding investment behavior under energy uncertainty. Conclusively, our study contributes to the literature by highlighting how energy uncertainty uniquely impacts corporate investment, taking into account the specific financial and operational conditions within different sectors. The findings highlight the importance of incorporating energy policy considerations into corporate strategic planning, particularly for energy-intensive industries within transitional economies like China.

Assessing the impact of renewable energy policies on decarbonization in developing countries

This study offers the first consistent attempt to identify how energy sector decarbonization policies have affected the energy mix over the last four decades across more than 100 developing countries. It applies systematic regression analysis to five energy sector decarbonization outcomes and 75+ policy instruments aggregated into seven policy packages. Combining instrumental variables with country interactions and country and time-fixed effects in regional panels helps address potential endogeneity issues. Only a handful of energy policy packages significantly affect decarbonizing developing countries' energy mix, and they more often achieve a negligible or opposite result than intended three years after implementation. Policies that address counterparty risk have the highest immediate effect. Effects of renewable policies on different decarbonization outcomes improve slightly five and seven years after their implementation.

Targeting strategies for balanced energy and protein (BEP) supplementation in pregnancy: study protocol for the TARGET-BEP cluster-randomized controlled trial in rural Bangladesh

BackgroundThe World Health Organization (WHO) recommends balanced energy and protein (BEP) supplementation be provided to all pregnant women living in undernourished populations, usually defined as having a prevalence > 20% of underweight women, to reduce the risk of stillbirths and small-for-gestational-age neonates. Few geographies meet this threshold, however, and a large proportion of undernourished women and those with inadequate gestational weight gain could miss benefiting from BEP. This study compares the effectiveness of individual targeting approaches for supplementation with micronutrient-fortified BEP vs. multiple micronutrient supplements (MMS) alone as control in pregnancy in improving birth outcomes.MethodsThe TARGET-BEP study is a four-arm, cluster-randomized controlled trial conducted in rural northwestern Bangladesh. Eligible participants are married women aged 15–35 years old identified early in pregnancy using a community-wide, monthly, urine-test-based pregnancy detection system. Beginning at 12–14 weeks of gestation, women in the study area comprising 240 predefined sectors are randomly assigned to one of four intervention arms, with sector serving as the unit of randomization. The interventions involving daily supplementation through end of pregnancy are as follows: (1) MMS (control); (2) BEP; (3) targeted BEP for those with pre-pregnancy body mass index (BMI) < 18.5 kg/m2 and MMS for others; (4) targeted BEP for those with pre-pregnancy BMI < 18.5 kg/m2, MMS for others, and women with inadequate gestational weight gain switched from MMS to BEP until the end of pregnancy. Primary outcomes include birth weight, low birth weight (< 2500 g), and small for gestational age, defined using the 10th percentile of the INTERGROWTH-21st reference, for live-born infants measured within 72 h of birth. Project-hired local female staff visit pregnant women monthly to deliver the assigned supplements, monitor adherence biweekly, and assess weight regularly during pregnancy. Trained data collectors conduct pregnancy outcome assessment and measure newborn anthropometry in the facility or home depending on the place of birth.DiscussionThis study will assess the effectiveness of targeted balanced energy and protein supplementation to improve birth outcomes among pregnant women in rural Bangladesh and similar settings.Trial registrationClinicalTrials.gov NCT05576207. Registered on October 5th, 2022.

Advanced Carbon Management: Innovations in Materials and Process Integration for Carbon Capture, Storage, and Utilization (CCSU)

Purpose: This article systematically explores the complex landscape of Carbon Capture, Storage, and Utilization (CCSU) technologies, emphasizing their critical role in global climate change mitigation. The article aims to provide a strategic framework for stakeholders to understand the integration of CCSU technologies into the broader energy and environmental policy landscape. Methodology: Through an integrated approach, this study examines the latest technological advancements in CCSU, studies the global regulatory frameworks influencing these technologies, and analyzes the economic factors that drive or obstruct their adoption. It also involves evaluating the role of international cooperation in standardizing and disseminating best practices for CCSU implementations worldwide. Findings: The study highlights the profound impact of legislative and financial mechanisms on the pace and scope of CCSU technology deployment. It discusses the potential of innovative materials and processes to reduce costs and increase the efficacy of carbon capture and storage. Furthermore, the review provides valuable insights into the current state and future prospects of CCSU technologies. Unique contribution to theory, policy and practice: The article emphasizes the necessity of robust research and development, supported by a conducive policy environment and strategic economic incentives, to enhance the efficiency, scalability, and commercial viability of CCSU technologies. It concludes with targeted recommendations for policymakers, suggesting ways to refine regulatory approaches and foster market conditions conducive to rapid CCSU adoption.

Comparative assessment and policy analysis of forecasting quarterly renewable energy demand: Fresh evidence from an innovative seasonal approach with superior matching algorithms

In the pursuit of sustainable development, accurate renewable energy demand forecasting holds great significance for climate change mitigation and promoting sustainability. However, renewable energy forecasting has been consistently challenged by seasonality and nonlinearity. Identifying the periodic and nonlinear characteristics concealed within renewable energy sources accurately is still an unexplored problem. Consequently, an innovative nonlinear discrete seasonal grey model is proposed for renewable energy forecasting, which incorporates seasonal dummy variables and a power exponent term for handling the seasonality and nonlinear patterns in time series. Furthermore, an intelligent algorithm matching framework is proposed to augment the flexibility of the newly developed model. For practical purposes, the new methodology is contrasted against a range of benchmarks encompassing statistical, machine-learning, and traditional grey models in forecasting the quarterly total renewable energy consumption in the United States. The proposed model exhibits over 27% improvement rates over its counterparts, achieving the most superior predictive accuracies of 1.45%, 39.27, and 0.79 in MAPEP, RMSEP, and MASEP metrics, respectively. Furthermore, the probability density and sample size analyses are conducted to validate the robustness of the new model, confirming its adaptability and stability towards algorithm randomness and historical information volume. Consequently, the novel model is employed to forecast the short-to-long-terms renewable energy consumption in the U.S., showcasing an upward trend and seasonal fluctuations of the consumption for the forthcoming 24 quarters from 2023Q4 to 2029Q3. These insights can offer valuable implications to the stakeholders such as energy suppliers, utility managers, and policy advocates, highlighting actionable strategies for optimizing renewable energy consumption forecasting and aiding sustainable development initiatives.

Blue Lead‐Free Perovskite Derivatives: Structural Diversity, Luminescence Properties and Light‐Emitting Diode Applications

AbstractHalide perovskite light‐emitting diodes (LEDs) have made remarkable advancements in both efficiency and stability. However, when compared to green and red LEDs, blue perovskite LEDs still lag behind in terms of efficiency and stability. Presently, efficient blue LEDs primarily rely on lead‐based perovskites, which goes against the environmentally friendly practices and restricts potential industrial applications. Consequently, there has been a surge of interest in academic research toward developing blue LEDs using lead‐free perovskites. This paper provides a comprehensive review of the structural diversity of lead‐free perovskite derivatives used for blue emission, encompassing Sn‐, Zr‐, Bi‐, Sb‐, Cu‐, Zn‐based halides as well as double perovskites. Various material synthesis techniques are discussed, such as nanocrystal preparation and film preparation. Additionally, the photoluminescence properties for different energy band structures are outlined, along with the luminescence mechanism involving energy transfer and strategies for enhancing luminous efficiency. The advancement in efficiency and stability of lead‐free perovskite LEDs is also examined in this review. Finally, the current challenges and future opportunities in advancing research on blue lead‐free perovskite derivatives and their potential application in LED technology is emphasized.

Optimal Gasoline Price Predictions: Leveraging the ANFIS Regression Model

This study presents an in-depth analysis of gasoline price forecasting using the adaptive network-based fuzzy inference system (ANFIS), with an emphasis on its implications for policy-making and strategic decisions in the energy sector. The model leverages a comprehensive dataset from the U.S. Energy Information Administration, spanning over 30 years of historical price data from 1993 to 2023, along with relevant temporal features. By combining the strengths of fuzzy logic and neural networks, the ANFIS approach can effectively capture the complex, nonlinear relationships present in the data, enabling reliable price predictions. The dataset’s preprocessing involved decomposing the date into year, month, and day components to enhance the model’s input features. Our methodology entailed a systematic approach to ANFIS regression, including data preparation, model training with the inclusion of the previous week’s prices as an additional feature, and rigorous performance evaluation using MSE, RMSE, and correlation coefficients. The results indicate that incorporating previous prices significantly enhances the model’s accuracy, as reflected by improved scores and correlation metrics. The findings have significant implications for the energy sector, where stakeholders can leverage the ANFIS model’s insights for strategic decision-making. Accurate gasoline price forecasts are instrumental in devising pricing strategies, managing risks associated with price volatility, and guiding policy formulation. The model’s predictive capability enables energy companies to optimize resource allocation, plan for future investments, and maintain competitive advantage in a market influenced by fluctuating prices. Moreover, policymakers can utilize these predictions to assess the impact of energy policies on market prices and consumer behavior, ensuring that regulatory measures align with market dynamics and sustainability goals. In addition to the ANFIS model, we also employed Vector Autoregression (VAR) and Autoregressive Integrated Moving Average (ARIMA) models to validate our approach and provide a comprehensive understanding of time series forecasting within the energy sector. Notably, the ANFIS model achieves a score of 0.9970 and a robust correlation of 0.9985, demonstrating its ability to accurately forecast gasoline prices based on historical data and features. The integration of these traditional techniques with advanced ANFIS modeling offers a robust framework for accurate and reliable gasoline price prediction, which is vital for informed policy-making and strategic planning in the energy industry.

The implications of the ecological footprint and renewable energy usage on the financial stability of South Asian countries

This study explores the complex relationships involving ecological footprints, energy use, carbon emissions, governance efficiency, economic prosperity, and financial stability in South Asian nations spanning the period from 2000 to 2022. Employing various methodologies such as cross-sectional dependence tests, co-integration analysis, and first- and second-generation unit-root tests, we use a panel Autoregressive Distributed Lag model, feasible generalized least squares, and Panel Corrected Standard Errors to ensure the robustness of our findings. We find noteworthy positive correlations between several variables, including heightened ecological consciousness, effective governance structures, increased GDP per capita, and amplified CO2 emissions. These relationships suggest potential pathways to strengthen the financial stability of the entire region; they also highlight the latent potential of embracing ecologically sustainable practices to fortify economic resilience. Our results also underscore the pivotal role of appropriate governance structures and higher income levels in bolstering financial stability in South Asian countries. Interestingly, we also find negative coefficients associated with the use of renewable energy, suggesting that escalating the adoption of renewable energy could create financial instability. This finding stresses the importance of diversification in energy strategies, cautioning policymakers to carefully consider the financial ramifications of potentially costly imports of renewable energy sources while seeking to reduce carbon emissions, emphasizing the need to strike a balance between ambitious sustainability goals and the pursuit of sustained economic robustness in the region. In considering the implications of these findings, it is crucial to consider each country’s broader socioeconomic context. Our results offer valuable insights for policymakers in developing renewable energy strategies.

The time-varying dynamic impact of US renewable energy prices on agricultural prices in China: the case of fuel ethanol.

This paper intends to look into the time-varying dynamic impact of US fuel ethanol, one of the renewable energy sources, on the prices of agricultural products (specifically corn, soybeans, rice, and wheat) in China based on monthly price data from January 2000 to January 2023. To achieve this, a time-varying parameter vector autoregressive (TVP-VAR) model is employed, which takes into account structural changes in emergencies through time-varying parameters. The empirical results show that the equal-interval impulse responses of price fluctuations in agricultural commodities are primarily positive to variations in fuel ethanol prices and production. And the intensity and direction of the effects vary at distinct time lags. Additionally, the magnitude of these responses is most pronounced in the short term for all agricultural commodities except for corn, and the duration of the impulse responses at different time points is generally longer for corn prices compared to other commodities. The study also reveals that the influence of US fuel ethanol on Chinese agricultural commodity prices is not substantial on the whole. Therefore, there is a necessity to advance the growth of biofuels and provide policy support and financial subsidies for agricultural products earmarked for food production. These actions could shed insights into the progression of Chinese renewable energy and food policies, ensuring the stability of the market in the long run.

Solar potential for social benefit: Maps to sustainably address energy poverty utilizing open spatial data in data poor settings

Access to affordable sustainable energy is a significant challenge for many lowincome countries experiencing energy poverty. The United Nations (UN) Sustainable Development Goal (SDG) 7 aims to “ensure access to affordable, reliable, sustainable and modern energy for all.” Simultaneously, the European Union (EU) seeks to reduce emissions by 55 % by 2030. Decarbonization policies must be carefully considered to avoid adverse effects on vulnerable groups experiencing energy poverty. Solar technology offers a viable solution to decarbonize the building sector, reduce energy dependence on fossil fuels, and provide financial benefits to the public. Mapping solar potential is crucial to determine where investment in solar photovoltaic (PV) technology is most advantageous to the populations who stand to benefit the most. We combine a solar potential mapping approach incorporating socio-economic indicators indicative of energy poverty, using off-the-shelf Geographic Information Systems (GIS) tools that are easily replicated across cities facing energy poverty. Utilizing lowest common denominator data and analysis approaches, we offer creative and innovative mapping solutions. The socio-economic factors help to contextualise the benefits of distributed PV systems and highlight the need for mapping solar potential, in combination with energy poverty indicators for sustainable planning and policymaking. Our results for a case study in the city of Plovdiv, Bulgaria, demonstrate high solar energy potential that could meet 29 % of the city's electricity needs, save citizens about M€ 43.84 annually, and pinpoint where to invest first for the highest gains. Finally, we offer suggestions on how to use these results to inform decarbonization policies to benefit low-income populations that are often missed in existing energy policies.

A new information priority grey prediction model for forecasting wind electricity generation with targeted regional hierarchy

Amidst the global transition to renewable energy electricity generation, this study addresses the need for improved wind electricity generation forecasting, which is pivotal in optimizing energy strategies and meeting sustainability targets. The research introduces an innovative adaptation of the grey prediction methods, named UNAGO-GM (1, 1), which is enhanced by the unified new-information priority accumulating generation operator (UNAGO) that emphasizes more recent data. This advanced model significantly improves the model's adaptability and accuracy in forecasting wind electricity generation within the regional hierarchy. To demonstrate the proposed model’s superior forecasting efficacy, the comparative experiments are conducted in the hierarchical forecasting fashion across national, regional, and global levels by contrasting UNAGO-GM (1, 1) with prevailing benchmarks like ARIMA and LSTM. The results indicate UNAGO-GM (1, 1)’ s highest forecasting accuracy and universality, with 54.07% and 156.48% improvement rates concerning MAPEs and RMSEs across all benchmarks and forecasting levels. Furthermore, UNAGO-GM (1, 1)’s output stability is validated through the robustness tests applying Monte Carlo simulations for the intelligent algorithm stability and matrix perturbation analyses. In conclusion, the novel UNAGO-GM (1, 1) model represents a significant breakthrough in renewable energy forecasting, providing precise and adaptable predictions essential for strategic planning and policy formulation in the transition towards sustainable energy sources.

Exploring policy coherence to understand limited progress of gender and social inclusion in the energy sector: The case of Nepal

Goal 7 of the Sustainable Development Goals (SDGs) aims to ensure access to affordable, reliable, sustainable, and modern energy for all by 2030 but securing universal access to energy supplies remains a challenge worldwide. There is increased recognition that gender and social inclusion (GESI) is critical for the transition towards low-carbon energy.Nepal's inclusive 2015 Constitution, and its 2021 federal-level Gender Equality Policy translate this commitment. Likewise, Nepal is committed to SDG 7. Yet energy policy includes only limited provisions for ensuring energy access by marginalized groups and women. This paper focuses on energy policy coherence to identify cohesion between policies and policy instruments at different levels of governance to identify bottlenecks to GESI. Using a policy coherence and feminist policy approach within an energy justice context, it traces the coherence of GESI policy through time and in relation to overall GESI policy objectives. Horizontal and internal coherence are assessed through the parallels/disjoints between energy-related periodic plans, policies, budgets, and GESI aims. The evolution of GESI in energy investments has been slow in part because of a narrow conceptualization of the policy problem and a lack of coherence and synchronization across documents, which undermines implementation of the GESI agenda.

The Long-Run Linkage among the Macroeconomic Factors and CO2 Emissions in terms of Sea Transport Induced EKC Hypothesis in USA

The main aim of this article is to comprehend the long-run relationship among sea transportation, energy use, GDP, and CO2 for USA from 1980 to 2023. In this sense, FMOLS, DOLS, CCR, and ARDL analyses are employed in order to investigate the entity of long-run linkage between the relevant variables. According to results of this manuscript, except energy use there is no both long-run relationship among variables and effects of independent variables (GDP, sea transportation) on dependent variable (CO2 emissions) from 1980 to 2023 in USA. Therefore, the sea transport-induced EKC hypothesis has not been confirmed empirically. Although the hypothesis has not been confirmed, there are some issues to consider in terms of energy consumption. Transportation energy consumption and greenhouse gas emissions are seen as an alarming threat to leaving a livable and sustainable green environment and economy to future generations. Fossil fuels used in transportation have an important place in carbon dioxide emissions. This is seen as a crucial environmental factor that all stakeholders should consider when planning energy and environmental policy decisions. In order to prevent environmental quality from being negatively affected by greenhouse gas and exhaust emissions, policy makers need to encourage more energy efficient and healthier transportation ways. Thus, the harmful effects of transportation energy consumption can be reduced as well.