• Energy Research
• Frontiers in Environmental Science close

China is the largest producer of carbon in the world. China’s construction industry has received widespread attention in recent years due to its environmental issues. However, little research has been conducted to investigate the environmental efficiency of the domestic part of this industry. As the foreign contribution is beyond China’s control, identification of domestic carbon emissions is necessary to formulate effective policy interventions. Based on a multi-regional input‐output model, this study attempts to reduce the statistical bias associated with international trade, thereby obtaining a more accurate indicator of domestic carbon emission intensity. This study aims to reveal the change in the domestic carbon emission intensity of China’s construction industry during 2000–2014 and analyze the reason behind it. The results show that, first, both the constructed intensity indicator and commonly used measures of carbon emission intensity have exhibited a decreasing trend over the study period. However, the former has been consistently larger than the latter. Moreover, this difference first increased and then suddenly decreased after a particular year. Second, although the domestic carbon emission intensity shows a gradually declining trend, it has moved from second to first in global rankings, implying that China’s domestic construction industry’s carbon emission efficiency, while falling, lags behind other major economies. Third, the structural decomposition results reveal that changes in direct production emission intensity are the leading causes of the decline in domestic carbon emission intensity. In contrast, a change in the intermediate input structure led to an increase in the emission intensity in China’s construction industry. In addition, the enormous gaps of domestic carbon emission intensity in the construction industry between China and the selected countries are mainly attributable to the difference in the intermediate input structure. The study suggests that China’s construction industry needs to promote high value-added output, optimize intermediate input structure, and improve energy and emission efficiency.

The co-production of biohydrogen and methane from the organic fraction of municipal solid waste was investigated using a two-stage AD system, composed of a pilot scale dark fermenter (DF) and a continuous methanogenic biofilm reactor. From the DF process, a biohydrogen yield of 41.7 (± 2.3) ml H2/gVSadded was achieved. The liquid DF effluent (DFE) was rich in short chain volatile fatty acids, i.e., mainly acetic and butyric acid. The DFE was valorized by producing methane in the methanogenic biofilm reactor. Two methanogenic biofilm reactors were used to assess the biotic and abiotic role of the DFE on the performance of the reactors. Regardless of the different DFE feeding (i.e., biotic and abiotic), similar and stable operational performance of the two methanogenic biofilm reactors were observed with a respective methane yield and COD removal efficiency of 280–300 ml CH4/gCODremoved and 80–90%. Both methanogenic biofilm reactors showed significant resistance toward organic shock loads and recovered fast after reactor disturbance. The total estimated energy recovered in the form of hydrogen and methane gas was, respectively, 28 and 72%, of the initial COD.HIGHLIGHTSSimultaneous production of biohydrogen and methane from OFMSW was investigated.A pilot scale dark fermenter and methanogenic biofilm reactor were used for, respectively, biohydrogen and methane production.The biotic and abiotic role of the dark fermentation effluent on the methanogenic biofilm reactor was assessed.Anaerobic biofilm reactors demonstrated a high tolerance toward an increased OLR.H2 and CH4 was 28 and 72%, respectively, of the total energy recovery from the OFMSW.

This paper adds to the existing body of knowledge by incorporating the role of fiscal decentralization (FD) in influencing CO2 emissions. Therefore, this study looked at the effect of FD on CO2 emissions in the presence of nonrenewable energy consumption (NRE), renewable energy consumption (REN), gross domestic product (GDP), and trade openness (TOP) for the period 1994–2018 in Japan. Thus, the current work intends to fill this knowledge gap by employing econometric techniques such as Bayer and Hanck cointegration, dynamic ordinary least squares (DOLS), fully modified ordinary least squares (FMOLS), and canonical cointegration regression (CCR). Additionally, the frequency domain causality analysis is used in the investigation to determine the causal impact of FD, NRE, REN, GDP, and TOP on CO2 emissions. The novelty of the frequency-domain approach is that it can differentiate between nonlinearity and causality levels and show causality among parameters with different frequencies. The DOLS, FMOLS, and CCR results reveal that NRE, GDP, and TOP augment CO2 emissions in Japan, whereas FD and REN increase the quality of the atmosphere. Furthermore, the frequency causality test results show that FD, REN, GDP, and TOP have implications for CO2 emissions in the long run, while NRE raises CO2 emissions in the medium run. As a policy direction, the current study suggests expanding renewable energy consumption in Japan by emphasizing more on Sustainable Development Goals (7, 8, and 13).

Implementing low-carbon houses is inseparable from the carbon tax and subsidy policies. Appropriate carbon taxes and subsidies can help to reduce household carbon emissions. This study aims to identify a suitable carbon tax and subsidy policy and investigate how this policy will affect the adoption of low-carbon housing. We classify programs including carbon taxes and subsidies into four categories: static carbon tax static subsidy, static carbon tax dynamic subsidy, dynamic carbon tax dynamic subsidy, and dynamic carbon tax static subsidy. Additionally, under various carbon tax and subsidy systems, the evolutionary stability strategies (ESS) of real estate developers and governments will be examined using evolutionary game theory. The case simulation results show that static carbon tax and dynamic subsidies are the best strategies. Government regulation is essential for the implementation of low-carbon housing. The higher the carbon tax and the property developer’s profit, the higher the willingness of property developers to implement low-carbon houses and the higher the willingness of government regulation. Appropriate low-carbon subsidies will help property developers implement low-carbon houses. However, after reaching a certain point, low-carbon subsidies will make property developers less inclined to build low-carbon houses. The higher the cost of government regulation, the lower the probability of the low-carbon strategy of property developers, but the cost of government regulation has little impact on the government’s regulation strategy.

This study analyzes the impact of electricity prices on the development of the agriculture sector in Qatar, using annual data from 2003 to 2019. Its findings contribute to addressing a gap in current literature and offer valuable perspectives on the sector’s obstacles and potential prospects. An extended Cobb-Douglas production function was employed as a theoretical framework, in conjunction with several econometric techniques, including Fully Modified Least Squares, Dynamic Ordinary Least Square, Canonical Cointegration Regression, and Gets, to analyze the persistent relationship between electricity prices, and the gross value added of the agriculture sector. Our research found that electricity prices exert a positive effect on agricultural development. Although the magnitude of the impact was small over the long term, it remained statistically significant. Specifically, the elasticity of the electricity prices ranged between 0.097–0.11, whereas the elasticity of another examined variable, labor productivity, was also positive and ranged between 0.67–0.74. These empirical findings support the ongoing government policy to reform energy prices, increase vegetable production using modernized hydroponic systems, and reduce groundwater use for irrigation, among other policies to sustain food production. Clearly, if these policy options are managed properly, the agriculture sector can play a significant role in diversifying the economy, maintaining environmental conditions and improving food sustainability.

The international community has reached a consensus on promoting the sustainable development of global cities. As an important and irreversible space resource in a city, the development and utilization of urban underground space should follow the principle of sustainability and emphasize scientific and forward-looking planning. At present, most cities have formulated urban underground space master plans. However, due to the lack of an effective evaluation method, the plan quality is uneven, which directly affects the sustainability of underground space development and utilization. This paper proposes a set of sustainability evaluation framework of underground space planning based on relevant planning standards and plan quality evaluation protocol, and makes a comparative analysis of the 40 urban underground space master plans formulated in China from 2004 to 2020. The research found that the planning documents generally reflected the problem of emphasizing design strategies and engineering technology while neglecting implementation and humanistic care; administrative region, population density, land price and other variables closely related to the scarcity of urban space resources are the main factors affecting the quality of urban underground space planning. The conclusions of this paper can aid planners and researchers to identify the problems and influencing factors of underground space planning related to sustainability, and summarize the methods to improve the quality of underground space planning.

The collection of publicly available databases about climate change and its impacts on natural and human systems is unprecedented and ever-growing. However, the requirements of information can vary widely among users depending on their region, socioenvironmental context, and interests. Moreover, in the current era of active mitigation and adaptation policies, information needs are frequently not satisfied even by these massive and variated collections of databases. The development and use of emulators can help closing this information gap by allowing users to approximate the output from complex models and create user-defined experiments, without being technically or computational demanding on the user. Here, a simple emulator of the EPIC biophysical crop model is presented which is able to adequately reproduce the changes in rainfed maize and to create projections for user-defined scenarios. Moreover, it allows to produce risk measures that are not available with the original model. The proposed methodology is illustrated with a case study of rainfed maize production in Mexico for a reference emissions scenario (SSP370) and two user-defined international mitigation policy scenarios. These scenarios represent 1) current international mitigation commitments and 2) a scenario in which China withdraws from international mitigation efforts. Results showed that, under the reference scenario, climate change could have widespread consequences on rainfed production all over the country with decreases in yields reaching up to 80% in the southeast and northeast of the country. These impacts can be partially modulated by the moderately ambitious mitigation commitments assumed in recent international agreements if all countries comply. However, a potential withdraw of China from these efforts would significantly reduce any benefits from international mitigation. Under all scenarios, changes in productivity impose increasing risks for already vulnerable populations and considerable economic costs at the state and national levels. These results suggest the urgent need for critical planning for adaptation in the agricultural sector of the country.