Driving factors of spatial-temporal difference in China's transportation sector carbon productivity: an empirical analysis based on Geodetector method.

Carbon productivity is the core index to measure the performance of carbon emission reduction. Exploring the driving factors of the spatial-temporal differences in China's transportation sector, carbon productivity (TSCP) is conducive to the low-carbon sustainable development of the transportation sector. Based on the calculation of TSCP in 30 provinces in China from 2000 to 2019, we use time series, spatial visualization, and Dagum Gini coefficient to reveal the characteristics of spatial-temporal evolution and regional differences of TSCP, and uses Geodetector to identify the driving factors that affecting the spatial-temporal differences of TSCP. The results are as follows: (1) from 2000 to 2019, China's TSCP shows a U-shaped change trend of "decline to rise," and shows a spatial pattern of "high in the eastern and central, low in the western". (2) There are obvious regional differences in China's TSCP. The differences within each region show the trend of "eastern > central > western," while the differences between regions show the trend of "central-western > eastern-western > eastern-central," and the differences between regions are the main reason for the overall differences. (3) The spatial-temporal differences in China's TSCP are affected by many factors, such as social economy and self-endowment. Overall, energy intensity, foreign trade, technological innovation level, energy structure, and industrial structure are the dominant factors. Additionally, the interaction between the driving factors enhances the impact on the spatial-temporal differences of TSCP. Finally, according to the analysis results, some policy suggestions are put forward to improve TSCP.

Direct and economy-wide energy rebound effects in China's transportation sector: a comparative analysis.

Although the existing literature has evaluated the energy rebound effect (ERE) from various aspects, the estimates of different types of ERE obtained by different methods still deserve further discussion. For this reason, by analyzing the pros and cons of assessment methods, this study offers a comparison between the direct and economy-wide EREs based on China's transportation sector during the period of 2003-2019. Specifically, on the basis of the translog cost function, we use the dynamic ordinary least square (DOLS) method with seemingly unrelated regression (SUR) to evaluate the sectoral direct ERE. Considering that the direct ERE estimation is limited by its strict assumptions, this article further assesses the sectoral ERE from a macro perspective. By constructing the dynamic two-stage panel function, the generalized method of moments (GMM) was adopted to estimate the sectoral economy-wide ERE. The empirical results demonstrate that first, capital and labor relative to energy are Morishima substitutes; second, the sectoral short-term economy-wide ERE in China was 71.60%, while the long-term economy-wide ERE was 32.00% during the study period; third, there are significant regional differences in the EREs of Chinese transportation industry both for the short and long term, and the east China demonstrated the highest sectoral economy-wide ERE.

Carbon Mitigation Pathways of Urban Transportation under Cold Climatic Conditions.

Climate heterogeneity has enormous impacts on CO2 emissions of the transportation sector, especially in cold regions where the demand for in-car heating and anti-skid measures leads to high energy consumption, and the penetration rate of electric vehicles is low. It entails to propose targeted emission reduction measures in cold regions for peaking CO2 emissions as soon as possible. This paper constructs an integrated long-range energy alternatives planning system (LEAP) model that incorporates multi-transportation modes and multi-energy types to predict the CO2 emission trend of the urban transportation sector in a typical cold province of China. Five scenarios are set based on distinct level emission control for simulating the future trends during 2017-2050. The results indicate that the peak value is 704.7-742.1 thousand metric tons (TMT), and the peak time is 2023-2035. Energy-saving-low-carbon scenario (ELS) is the optimal scenario with the peak value of 716.6 TMT in 2028. Energy intensity plays a dominant role in increasing CO2 emissions of the urban transportation sector. Under ELS, CO2 emissions can be reduced by 68.66%, 6.56% and 1.38% through decreasing energy intensity, increasing the proportion of public transportation and reducing the proportion of fossil fuels, respectively. Simultaneously, this study provides practical reference for other cold regions to formulate CO2 reduction roadmaps.

A novel method for carbon emission forecasting based on EKC hypothesis and nonlinear multivariate grey model: evidence from transportation sector.

Greenhouse gas emissions have brought a serious challenge to the global environment and climate. Efficient and accurate prediction of carbon emissions is essential for the decision-making sectors to control growth and formulate policies. Firstly, considering the economic, demographic, and energy factors, a novel nonlinear multivariate grey model (ENGM(1,4)) based on environmental Kuznets curve (EKC) is proposed with respect to the data characteristics of the incomplete information of carbon emission of transportation sector. The model integrates the IPAT ("Influence = Population, Affluence, Technology") equation and the extended atochastic impacts by regression on population, affluence, and technology model (STIRPAT). Secondly, the derivation method is used to solve the time response equation of the model and the quantum particle swarm optimization algorithm (QPSO) is designed to optimize the model parameters. Then, 18 years of carbon emission data from China, the USA, and Japan are selected as the validation set. Comparative analysis indicates that the prediction accuracy of the statistical models and the intelligent models depends on sufficient samples and complex variables, and has certain limitations in limited sample prediction. The calculation results show that the new model outperforms other models in various evaluation indicators, indicating that its prediction accuracy is higher. Finally, the projections show that in 2019-2025, the average increase in carbon emissions from the transport sector in China and the USA was 2.837% and 2.394%, respectively, while Japan shows a downward trend with an average decline rate of 1.2231%. The analyzed prediction results are consistent with current situation of the three countries and the transport sectors, demonstrating the high accuracy and reliability of the new model.

Improving Decision-Making for Population Health in Nonhealth Sectors in Urban Environments: the Example of the Transportation Sector in Three Megacities-the 3-D Commission.

Noncommunicable diseases (NCDs) represent a significant global public health burden. As more countries experience both epidemiologic transition and increasing urbanization, it is clear that we need approaches to mitigate the growing burden of NCDs. Large and growing urban environments play an important role in shaping risk factors that influence NCDs, pointing to the ineluctable need to engage sectors beyond the health sector in these settings if we are to improve health. By way of one example, the transportation sector plays a critical role in building and sustaining health outcomes in urban environments in general and in megacities in particular. We conducted a qualitative comparative case study design. We compared Bus Rapid Transit (BRT) policies in 3 megacities-Lagos (Africa), Bogotá (South America), and Beijing (Asia). We examined the extent to which data on the social determinants of health, equity considerations, and multisectoral approaches were incorporated into local politics and the decision-making processes surrounding BRT. We found that all three megacities paid inadequate attention to health in their agenda-setting, despite having considerable healthy transportation policies in principle. BRT system policies have the opportunity to improve lifestyle choices for NCDs through a focus on safe, affordable, and effective forms of transportation. There are opportunities to improve decision-making for health by involving more available data for health, building on existing infrastructures, building stronger political leadership and commitments, and establishing formal frameworks to improve multisectoral collaborations within megacities. Future research will benefit from addressing the political and bureaucratic processes of using health data when designing public transportation services, the political and social obstacles involved, and the cross-national lessons that can be learned from other megacities.

Does technological innovation improve energy-environmental efficiency? New evidence from China's transportation sector.

The rapid modernization of the transportation sector has greatly escalated many problems, especially the high energy consumption and vehicle exhaust pollution. How to reduce pollution in the transportation sector has attracted widespread attention in recent years. Based on a balanced panel dataset of 30 Chinese provinces spanning the period of 2005-2017, this study attempts to investigate the influence of technological innovation on the energy-environmental efficiency of the transportation sector (EETS) using the spatial econometric approach. The empirical results suggest that first, transportation-related technological innovation and EETS exhibited obvious hot spots and cold spots at the provincial level in China. Second, technological innovation could facilitate the energy-environmental efficiency of transportation sector in China. Third, one province developing transportation-related technological innovations might promote EETS in its neighboring provinces. Fourth, the transportation-related technological innovation in eastern China could boost EETS, while the transportation-related technological innovation in central and western China had a rebound effect on EETS. One possible innovation is that this study extends the relationship between technological innovation and energy-environmental efficiency to the transportation sector.

Dynamic evaluation on the energy and environmental performance of China's transportation sector: a ZSG-MEA window analysis.

The transportation sector is one of the important energy consumption and carbon emission sources. This paper extends the multi-directional efficiency analysis (MEA) to zero-sum game MEA (ZSG-MEA) with considering the CO2 emission as a fixed-sum undesirable output to measure the energy and environmental performance (EEP) of the transportation sector. The ZSG-MEA window analysis is applied to dynamically evaluate the EEP of China's transportation sector in 30 provincial-level regions during 2008-2017. Some interesting findings are obtained: (i) the EEP of the transportation sector in most regions has not been performed well but the average EEP of the transportation sector in most regions has been gradually improved since 2011. A general trend is that the transportation sector in the east area wins the best average EEP, and the average EEP of the central area is better than that of the west area, but their gap is narrowing from 2012. (ii) The EEP fluctuation verifies the greatest imbalance of EEP among the east area's regions. Both the east area and the central area are narrowing the imbalance in recent years, but the west area has an inverse trend. (iii) The performance of CO2 emissions is better than that of energy consumption in all three areas, which implies that China's transportation sector seems to have paid more attention on emission reduction than energy conservation. Besides, the east area has the best performance of energy consumption and CO2 emissions from an overall perspective. And the energy consumption and CO2 emissions in the central area perform better than the west area before 2013, but then shows an entangled state from 2013. (iv) From the average variable specific ZSG-MEA efficiency, the industrial added value of transportation sector performs better than other variables in the east area and central area, but the situation in the west area is inverse. Some useful insights are provided according to these findings.

Infrastructure policy and public health: Evidence from OECD countries.

When making infrastructure policies, decision makers insufficiently consider negative consequences for the environment or health. This lack of multi-sectorial awareness in policymaking triggers poor public health outcomes. To illustrate this issue, this interdisciplinary work presents evidence for the association of road infrastructure investment (as infrastructure policy) with the incidences of deaths due to transport accidents, chronic obstructive pulmonary disease, and pneumonia using nationally aggregated data from the Organisation for Economic Co-operation and Development for 27 countries over an 18-year period (1995-2012). We conduct an explorative analysis using descriptive statistics and fixed-effects panel-data regression models that include the interaction of the policy variable with the Environmental Policy Stringency Index, which proxies the awareness of negative consequences of policies. We show that countries which never achieved a score of 3 or higher for the Environmental Policy Stringency Index had higher levels of standardized death rates. This is supported by Pearson's correlation coefficients and by the results of t-tests for deaths due to transport accidents. Following the fixed-effects analysis, we find that an increase in road infrastructure investment of 1% of gross domestic product is associated, on average, with about three additional deaths per 100,000 population due to transport accidents and about 18 fewer deaths per 100,000 population due to chronic obstructive pulmonary disease using standardized death rates. A one unit increase in the Environmental Policy Stringency Index is related to about 7 fewer deaths per 100,000 population due to chronic obstructive pulmonary diseases. Marginal effects of the interaction of road infrastructure investment and the Environmental Policy Stringency Index are significant for standardized death rates due to transport accidents and chronic obstructive pulmonary disease. Multi-sectorial awareness in infrastructure policy mediates health effects for deaths due to transport accidents and chronic obstructive pulmonary disease.

The impact of technology-environmental innovation on CO2 emissions in China's transportation sector.

Along with the development of urbanization and informationization, an increasing attention has been attracted to CO2 emissions of China's transportation sector and its influencing factors. Such researches mainly utilize single indicator or two indicators to represent technology process. This research aims to verify the influence of technology-environmental innovation indicator system on CO2 emissions of China's transportation sector by decoupling elasticity and econometric model. We firstly recognize the decoupling status of CO2 emissions of China's transportation sector from social economic development and aggregate China's 30 provinces into two groups according to the varied decoupling status, namely expansive coupling and weak decoupling groups. Then, we develop a relatively comprehensive technology-environmental innovation indicator system to measure technology process. Finally, the multi-region comparison of emission drivers is studied among overall China and the two groups. The result shows that the decoupling elasticity of China's transportation has experienced an evolution process trending to desired development status and all the provinces have experienced expansive coupling and weak decoupling from 2001 to 2016, except Qinghai. Innovation performance indicators exert most important influence on the CO2 emissions of transportation sector. Finally, the influences of technology-environmental innovation indicators are similar across groups with different magnitude, suggesting that common but differentiated strategies should be provided when mitigating CO2 emissions with technology process. Graphical abstract.

The CO2 emission changes in China's transportation sector during 1992-2015: a structural decomposition analysis.

Based on a structural decomposition approach, the present paper simultaneously analyzes seven driving factors and forty sectors, which contribute to CO2 emission changes for China's transportation sector during 1992-2015. Based on the analysis of the driving factors, the total output and the energy intensity are found to be the primary positive and negative factor, respectively. From the sector analysis, top five sectors causing the increase of the transportation CO2 emissions are identified. Particularly, information transmission, computer services and software sector (no. 28); construction sector (no. 26); transportation sector (no. 27); chemical sector (no. 12); and leasing and business service sector (no. 33) are the five most relevant contributions to the increase of CO2 emissions of the transportation sector during 2002-2015. As a view to suppress CO2 emission growth, besides the promotion of public transportation, low-carbon emission energy, and energy-saving technologies, policymakers should pay attention to the impacts of key sectors on transportation.

A VIKOR based approach for assessing the social, environmental and economic effects of "smog" on human health.

Nowadays, the excessive industrialization, increased use of fossil fuels, elevated levels of vehicular emissions are causing high level of air pollution reaching epidemic levels. The effects of "smog" or in other words of air pollution can be very dangerous for humans, and plants. In fact, air pollution can be linked to many health-related issues, as it is one of the leading causes of pulmonary, respiratory and skin diseases across the globe. In this context, Pakistan being an underdeveloped country, faces the hazardous impacts of smog on health, environment, transportation and educational sectors. The aim of the present research was to establish a correlation between smog/air pollution (the independent variable) and different dependent variables. The final goal was to define different precautionary measures and find their practicality and selection. Fuzzy VIKOR, a multi-criteria decision-making tool, was proposed in this research. It was applied to select an optimal alternative based on closeness to positive-ideal solution and deviation from the negative-ideal solution. Through this research, an environmental-friendly and health-promoting policy can be reach. This research will also help government in making future policies regarding environmental and industrial pollution. A case study settled in Pakistan was used to demonstrate the effectiveness of the proposed fuzzy model.

Impacts of transportation sector emissions on future U.S. air quality in a changing climate. Part I: Projected emissions, simulation design, and model evaluation.

Emissions from the transportation sector are rapidly changing worldwide; however, the interplay of such emission changes in the face of climate change are not as well understood. This two-part study examines the impact of projected emissions from the U.S. transportation sector (Part I) on ambient air quality in the face of climate change (Part II). In Part I of this study, we describe the methodology and results of a novel Technology Driver Model (see graphical abstract) that includes 1) transportation emission projections (including on-road vehicles, non-road engines, aircraft, rail, and ship) derived from a dynamic technology model that accounts for various technology and policy options under an IPCC emission scenario, and 2) the configuration/evaluation of a dynamically downscaled Weather Research and Forecasting/Community Multiscale Air Quality modeling system. By 2046-2050, the annual domain-average transportation emissions of carbon monoxide (CO), nitrogen oxides (NOx), volatile organic compounds (VOCs), ammonia (NH3), and sulfur dioxide (SO2) are projected to decrease over the continental U.S. The decreases in gaseous emissions are mainly due to reduced emissions from on-road vehicles and non-road engines, which exhibit spatial and seasonal variations across the U.S. Although particulate matter (PM) emissions widely decrease, some areas in the U.S. experience relatively large increases due to increases in ship emissions. The on-road vehicle emissions dominate the emission changes for CO, NOx, VOC, and NH3, while emissions from both the on-road and non-road modes have strong contributions to PM and SO2 emission changes. The evaluation of the baseline 2005 WRF simulation indicates that annual biases are close to or within the acceptable criteria for meteorological performance in the literature, and there is an overall good agreement in the 2005 CMAQ simulations of chemical variables against both surface and satellite observations.

Impacts of transportation sector emissions on future U.S. air quality in a changing climate. Part II: Air quality projections and the interplay between emissions and climate change.

In Part II of this work we present the results of the downscaled offline Weather Research and Forecasting/Community Multiscale Air Quality (WRF/CMAQ) model, included in the "Technology Driver Model" (TDM) approach to future U.S. air quality projections (2046-2050) compared to a current-year period (2001-2005), and the interplay between future emission and climate changes. By 2046-2050, there are widespread decreases in future concentrations of carbon monoxide (CO), nitrogen oxides (NOx = NO + NO2), volatile organic compounds (VOCs), ammonia (NH3), sulfur dioxide (SO2), and particulate matter with an aerodynamic diameter ≤ 2.5 µm (PM2.5) due mainly to decreasing on-road vehicle (ORV) emissions near urban centers as well as decreases in other transportation modes that include non-road engines (NRE). However, there are widespread increases in daily maximum 8-hr ozone (O3) across the U.S., which are due to enhanced greenhouse gases (GHG) including methane (CH4) and carbon dioxide (CO2) under the Intergovernmental Panel on Climate Change (IPCC) A1B scenario, and isolated areas of larger reduction in transportation emissions of NOx compared to that of VOCs over regions with VOC-limited O3 chemistry. Other notable future changes are reduced haze and improved visibility, increased primary organic to elemental carbon ratio, decreases in PM2.5 and its species, decreases and increases in dry deposition of SO2 and O3, respectively, and decreases in total nitrogen (TN) deposition. There is a tendency for transportation emission and CH4 changes to dominate the increases in O3, while climate change may either enhance or mitigate these increases in the west or east U.S., respectively. Climate change also decreases PM2.5 in the future. Other variable changes exhibit stronger susceptibility to either emission (e.g., CO, NOx, and TN deposition) or climate changes (e.g., VOC, NH3, SO2, and total sulfate deposition), which also have a strong dependence on season and specific U.S. regions.

Assessment of Co-benefits of vehicle emission reduction measures for 2015-2020 in the Pearl River Delta region, China.

Vehicle emissions have become one of the key factors affecting the urban air quality and climate change in the Pearl River Delta (PRD) region, so it is important to design policies of emission reduction based on quantitative Co-benefits for air pollutants and greenhouse gas (GHG). Emissions of air pollutants and GHG by 2020 was predicted firstly based on the no-control scenario, and five vehicle emissions reduction scenarios were designed in view of the economy, technology and policy, whose emissions reduction were calculated. Then Co-benefits between air pollutants and GHG were quantitatively analyzed by the methods of coordinate system and cross-elasticity. Results show that the emissions reduction effects and the Co-benefits of different measures vary greatly in 2015-2020. If no control scheme was applied, most air pollutants and GHG would increase substantially by 20-64% by 2020, with the exception of CO, VOC and PM2.5. Different control measures had different reduction effects for single air pollutant and GHG. The worst reduction measure was Eliminating Motorcycles with average reducing rate 0.09% for air pollutants and GHG, while the rate from Updated Emission Standard was 41.74%. Eliminating Yellow-label Vehicle scenario had an obvious reduction effect for every single pollutant in the earlier years, but Co-benefits would descent to zero in later by 2020. From the perspective of emission reductions and co-control effect, Updated Emission Standard scenario was best for reducing air pollutants and GHG substantially (tanα=1.43 and Els=1.77).

Decomposition analysis of energy-related carbon emissions from the transportation sector in Beijing.

In the process of rapid development and urbanization in Beijing, identifying the potential factors of carbon emissions in the transportation sector is an important prerequisite to controlling carbon emissions. Based on the expanded Kaya identity, we built a multivariate generalized Fisher index (GFI) decomposition model to measure the influence of the energy structure, energy intensity, output value of per unit traffic turnover, transportation intensity, economic growth and population size on carbon emissions from 1995 to 2012 in the transportation sector of Beijing. Compared to most methods used in previous studies, the GFI model possesses the advantage of eliminating decomposition residuals, which enables it to display better decomposition characteristics (Ang et al., 2004). The results show: (i) The primary positive drivers of carbon emissions in the transportation sector include the economic growth, energy intensity and population size. The cumulative contribution of economic growth to transportation carbon emissions reaches 334.5%. (ii) The negative drivers are the transportation intensity and energy structure, while the transportation intensity is the main factor that restrains transportation carbon emissions. The energy structure displays a certain inhibition effect, but its inhibition is not obvious. (iii) The contribution rate of the output value of per unit traffic turnover on transportation carbon emissions appears as a flat "M". To suppress the growth of carbon emissions in transportation further, the government of Beijing should take the measures of promoting the development of new energy vehicles, limiting private vehicles' increase and promoting public transportation, evacuating non-core functions of Beijing and continuingly controlling population size.

Labor, trabalho e ação: elementos pertinentes aos conceitos arendtianos em relatos autobiográficos de trabalhadores do setor de transportes / Labor, work, and action: relevant elements regarding Arendt’s concepts in autobiographical reports of workers from the transportation sector

A reflexão, junto à classe trabalhadora, sobre questões relacionadas à saúde no ambiente de trabalho, visando à criticidade e às ações que resultem no enfrentamento de seus problemas é um importante instrumento de mudança da realidade. O objetivo desta pesquisa exploratória é identificar elementos pertinentes aos conceitos arendtianos (labor, trabalho e ação) presentes no discurso de trabalhadores do setor de transportes participantes de um projeto de extensão universitária. A abordagem é qualitativa e a metodologia consiste em relato autobiográfico. As histórias dos trabalhadores foram gravadas em DVD e posteriormente transcritas. Para a análise, optou-se pela definição de categorias a priori (labor, trabalho e ação), uma vez que o marco teórico era a obra de Hannah Arendt. Como resultado, foram encontrados: insegurança alimentar, doenças crônicas não transmissíveis relacionadas ao conceito de labor; riscos ergonômicos e distúrbios psíquicos relacionados ao trabalho; e participação coletiva e inclusão digital como elementos da ação. Concluiu-se que conhecer, compreender e discutir essas três categorias para o incremento da reflexão acerca da saúde do trabalhador pode ser importante, uma vez que todas elas foram expressas nos relatos de vida, mostrando sua permanência e relevância na história de todos e de cada um...

Reflection, along with the working class, on health-related issues at the workplace, aiming at criticality and actions that result in facing its problems, is a significant instrument to change reality. The purpose of this exploratory research is identifying relevant elements with regard to Arendt’s concepts (labor, work, and action) observed in the discourse of workers from the transportation sector participating in a university outreach project. The approach is qualitative and the methodology is autobiographical account. Workers’ histories were recorded on DVD and then transcribed. For the analysis, we chose to define a priori categories (labor, work, and action), since the theoretical framework was Hannah Arendt’s work. As a result, we found: food insecurity, chronic noncommunicable diseases related to the concept of labor; ergonomic hazards and psychic disorders related to work; and collective participation and digital inclusion as elements of action. It was concluded that knowing, understanding, and discussing these three categories in order to increase the reflection on occupational health may be important, since all of them were expressed in life accounts, showing their permanence and relevance in the history of everybody and each one...