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Purpose: This paper aims to promote urban–rural synergy in carbon reduction and achieve the dual carbon goal, reconstruct the low-carbon urban–rural spatial pattern and explore planning strategies for carbon mitigation in urban agglomerations. Design/methodology/approach: The authors propose the idea of land governance zoning based on low-carbon scenario simulation, using the Beijing–Tianjin–Hebei (BTH) urban agglomeration as the empirical research area. Specifically, the authors analyze its spatiotemporal evolution characteristics of carbon balance over the past two decades and simulate the land use pattern under the scenario of low-carbon emission in 2030. Furthermore, the authors create spatial zoning rules combined with land use transition characteristics to classify the urban agglomeration into carbon sink restoration zone, carbon sink protection zone, carbon control development zone and carbon transition agriculture zone and put forward corresponding targeted governance principals. Findings: The study findings classify the BTH urban agglomeration into carbon sink restoration zone, carbon sink protection zone, carbon control development zone and carbon transition agriculture zone, which account for 28.1%, 17.2%, 20.1% and 34.6% of the total area, respectively. The carbon sink restoration zone and carbon sink protection zone are mainly distributed in the northern and western parts and Bohai Rim region. The carbon transition agriculture zone and carbon control development zone are mainly distributed in the southeastern plain and Zhangjiakou. Research limitations/implications: The authors suggest restoring and rebuilding ecosystems mainly in the northwest and east parts to increase the number of carbon sinks and the stability of the ecosystem. Besides, measures should be taken to promote collaborative emission reduction work between cities and optimize industrial and energy structures within cities such as Beijing, Langfang, Tianjin and Baoding. Furthermore, the authors recommend promoting sustainable intensification of agriculture and carefully balance between both economic development and ecological protection in Zhangjiakou and plain area. Originality/value: The authors propose a zoning method based on the optimization of land use towards low-carbon development by combining "top-down" and "bottom-up" strategies and provide targeted governance suggestions for each region. This study provides policy implications to implement the regional low-carbon economic transition under the "double carbon" target in urban agglomerations in China. [ABSTRACT FROM AUTHOR]

This paper constructs a novel stress measurement system of carbon market from the perspective of trading, emission reduction, and external shocks and simulates the stress indices of national and pilot carbon markets of China with the methods of functional data analysis and criteria importance through intercriteria correlation. It concludes that the overall carbon market stress is in the shape of "W" and still at a high level, with frequent fluctuations and an upward trend. In addition, the stress of Hubei, Beijing, and Shanghai carbon market fluctuates and rises, while the stress of Guangdong carbon market decreases. Moreover, carbon market stress mainly comes from trading and emission reduction. Furthermore, stress fluctuation of Guangdong and Beijing carbon market is more prone to "big waves," indicating that the two markets are sensitive to big events. Finally, the pilot carbon markets are divided into stress-driven and stress-release market and the type of which keeps change in different period. [ABSTRACT FROM AUTHOR]

In the context of global carbon emission reduction, solar photovoltaic (PV) technology is experiencing rapid development. Using high-resolution remote sensing images to accurately obtain PV information over a large region, including location and size, has the advantages of high statistical efficiency and timely data update for the PV energy management. Due to the intra-class diversity of PV panels and the intricate variability in their deployment environments, existing semantic segmentation methods often have problems such as under-segmentation and mis-segmentation. To alleviate these problems, this paper proposes an improved DeepLabv3+ semantic segmentation network to more accurately extract PV panels from high-resolution remote sensing images. With the aim of alleviating under-segmentation, a multi-level context aggregation module is developed. This module can enhance the model's ability to learn the characteristics of PV panels and their surrounding environment by aggregating rich contextual information from multi-scale and semantic levels. To alleviate the problem of mis-segmentation, a hybrid attention module is introduced. This module sequentially and adaptively adjusts the weight distribution in both the channel and spatial dimensions, thus enabling the model to focus more on the feature information and spatial positions of PV objects. Experiments conducted on a self-constructed Beijing PV segmentation dataset show that the method in this paper has advantages of completeness and accuracy in extracting PV panels compared to the baseline model and current mainstream semantic segmentation network. In addition, the results of experiments on extracting PV panels in real region show that our model also has good stability and generalization capability. [ABSTRACT FROM AUTHOR]

Nowadays, sustainability-related issues have attracted growing attention due to fossil fuel depletion and environmental concerns. Considering many cities have gradually replaced taxis with electric vehicles (EVs), to reduce greenhouse gas emissions and traditional energy consumption, this paper studies the optimization strategy of battery swapping for electric taxis (ETs), and it is not only to ease congestion in the battery swapping station (BSS) but also for electric taxis to address their range anxiety and maximize their benefits. Firstly, based on the road network, the Dijkstra algorithm is adopted to provide the optimal path for ETs to BSSs with the minimum energy consumption. Then, this paper proposes the optimization objective function with minimum cost, which contains the battery service cost based on the battery's state of charge, waiting cost caused by waiting for swapping battery in BSSs and the carbon emission reduction benefit generated during ETs driving to BSSs, and uses a mixed-integer linear programming (MILP) algorithm to solve this function. Finally, taking the Leisure Park of Laoshan City in Beijing as an example, the numerical simulation is carried out and the proposed battery swapping strategy is efficient to alleviate the congestion of BSSs and maximize the total benefit of ETs, and the cost based on the proposed strategy is 14.21% less than that of disorderly swapping. [ABSTRACT FROM AUTHOR]

Since the 18th National Congress of Chinese Communist Party, ecological civilization construction has been incorporated into Five-sphere Integrated Plan, that is, to promote coordinated progress in the economic, political, cultural, social, and eco-environmental fields. The Chinese government has proposed the goal of "carbon peak" and "carbon neutrality". Low-carbon transportation becomes the mainstream. To achieve carbon peak and carbon neutrality in public transport, this paper takes Beijing's public transport sector as a case study, using system dynamics model with relevant policies and the current situation. It calculates and predicts carbon emissions under electric vehicle substitution scenario, clean energy generation, and carbon capture, utilization and storage scenario for the period of 2020–2060. The following main conclusions are obtained: Direct carbon emissions have peaked and started to decline based on the current measures, while indirect carbon emissions have peaked and started to decline under the suggested intervention. The direct carbon emissions peaked at 2.58005 × 106 tons in 2014. The indirect carbon emissions peaked at 1.59027 × 106 in 2025. They all achieved carbon neutrality under the suggested intervention. Electric vehicle substitution and carbon capture, clean energy generation, utilization and storage are the main factors of carbon emission reduction. The outcomes of this study can provide essential information for policy-makers to advance Beijing's future low-carbon development in public transport. The electric vehicle substitution, clean energy generation and carbon capture, utilization and storage provide a new perspective to research carbon emissions in the transport sector. [ABSTRACT FROM AUTHOR]

Whether logistics agglomeration and pollution reduction can form a perfect combination in space is one of the important breakthroughs for the successful green transformation of the logistics industry in the future. This paper attempts to clarify the nonlinear change law of logistics agglomeration evolution on environmental quality in China and further clarify the interpretation of informatization and legalization factors on macro-regulatory functions. Based on the panel data of 31 provincial-level administrative regions in China from 2010 to 2020, the empirical verification is carried out by means of two-way fixed effects, quantile regression, instrumental variables, and spatial econometrics. The research finds that (1) there is an inverted U-shaped change trend between logistics agglomeration and environmental quality and the low-level logistics agglomeration period has a blocking effect on pollution emission reduction. However, from the starting point of the sample interval, representative regions such as Beijing and Shanghai gradually break through the bottleneck of logistics agglomeration in the form of a pyramid, which has an incentive effect on pollution emission reduction. The above conclusions are supported by robustness tests in six ways, including eliminating extreme data disturbance, eliminating the impact of the COVID-19, controlling the impact of other factors, pollutant sensitivity testing, avoiding the interference of pollution prevention and control, and correcting the endogenous bias of the model. (2) Further analysis of superimposed spatial effects and regulatory effects shows that regional spillover pollution has spatial dependence in both geographical and economic distribution. The effect of logistics agglomeration also produces an inverted U-shaped spatial spillover effect on the environmental quality of adjacent areas. Both informatization and legalization factors help alleviate the pollution increasing effect in the low-level logistics agglomeration stage. Under the regulatory effect of informatization, the arrival of the critical point for logistics agglomeration and emission reduction will be relatively delayed. Under the regulatory effect of legalization, the arrival of the critical point for logistics agglomeration and emission reduction will be relatively accelerated. (3) There is significant regional heterogeneity in the environmental effects of logistics agglomeration. Each region needs to "suit the remedy to the case" in combination with its own situation to break through the threshold of pollution reduction as soon as possible. [ABSTRACT FROM AUTHOR]

Large-scale clean-heating renovations are being carried out in northern China as part of important measures to optimize energy infrastructure, improve the atmospheric environment, and minimize peak CO2 emissions. Because rural areas in the urban–rural fringe are close to the city center, they have several advantages in centralized heating reforms, but there are no effective means to measure whether a transformation is economical or has good environmental effects. In this paper, based on an actual reconstruction project, 100 typical households were selected for a related test. These typical households evinced convergence and possessed certain regional characteristics; therefore, the applicability of the models had certain limitations. To make sure that the relevant factors were fully considered in establishing the model, a prediction model group was established regarding heat consumption in winter (four models in total) that could predict the actual effect well. Lastly, the authors used the model group to calculate economic effects and CO2 emission reduction in rural heating transformations in Beijing under different heating methods. [ABSTRACT FROM AUTHOR]

With the continuous calls for energy conservation and emission reduction in recent years, more and more people choose walking as their travel mode. The improvement of the quality of street space will directly affect people's willingness to walk.By sorting out relevant research on street quality measurement, extracting quality keywords with high frequency of reference as impact factors, and using street view image data from different eras, semantic segmentation technology, factor analysis, and questionnaire survey methods, this paper evaluates the street quality of Jingshan East Street, Dongcheng District, Beijing, further explores the impact of different factors on street quality, and analyzes possible ways to improve it. [ABSTRACT FROM AUTHOR]

It is important to know how much of the increased atmospheric CO2 is derived from fossil fuel emissions. Here, we review the progress in atmospheric fossil fuel CO2 (CO2ff) tracing over recent years by measurement of Δ14C in Chinese cities. In this paper we make progress by expanding the analysis from some locations to more regional views, by combining observations with modeling, and by making a preliminary comparison of observation-derived CO2ff with inventory-derived CO2ff. We have obtained a general picture of Chinese urban CO2ff and characteristics of its spatio-temporal variations at different scale, and identified the corresponding influencing factors. Interestingly, we found that the weekend effect of CO2ff was less evident in Chinese cities. In addition, we observed simultaneous variations in CO2ff and PM2.5 in a winter haze event in Beijing and a simultaneous decrease in annual averages of CO2ff and PM2.5 in Xi'an based on multi-year (2011–2016) Δ14CO2 monitoring. We found that local coal combustion was the main source of CO2ff in Xi'an, which is located in the Guanzhong basin, by applying a WRF-Chem model and looking at δ13C signatures. Thus, reduction of coal consumption is a crucial target for carbon emissions reduction in China. [ABSTRACT FROM AUTHOR]

Research on the enhanced control and emission-reduction measures to improve air quality during major events could provide data theory and scientific support for air-quality improvement during non-activities. Based on the air-quality data published by the China Environmental Monitoring Station and the meteorological elements and weather conditions released by the China Meteorological Administration, this paper explored the characteristics of air-quality evolution in Beijing from 5 August to 18 September 2015 and the weather situation during the Military Parade. The results showed that: (1) Emission-reduction measures implemented for air quality by Beijing and its surrounding area were induced, and we explored the contribution of these measures to pollutants or AQI in the locality. (2) During the 2015 Military Parade, Beijing was in the front or lower part of the high-pressure system. Due to the strong effect of North or Northeast winds, the weather situation was conducive to the diffusion of pollutants. When before or after the implementation, once the atmospheric diffusion was poor, the pollutants would accumulate gradually. Thus, it can be seen that the weather situation had a great impact on air quality. (3) During the implementation, PM2.5, PM10, NO2 and other pollutants decreased significantly, of which the concentration of PM10 decreased the most, from 109 μg·m−3 down to 34 μg·m−3, and the concentration of PM2.5 decreased by 72.73%. According to the changes between before and during the implementation or during and after the implementation, the concentration of PM10 and PM2.5 increased when the implementation of the emission-reduction measures had been finished, indicating that the enhanced control measures made a great contribution to the emission reduction in particles. (4) In addition, the annual average of AQI in the three years is 87.49, and the average value of a normal year was the average value of 2013 and 2014. The average value of the normal year during the military parade is 64.63, which was 70.40% lower than the average value of AQI during the military parade. The goal of reaching the secondary standard of GB-3095-2012 was achieved, and there was still a long way to go from the primary standard. In a few words, in order to achieve the goal of better air quality throughout the year, all parties still needed to coordinate control and make joint efforts. [ABSTRACT FROM AUTHOR]

A good risk warning model is an effective way to guarantee the stable operation of the carbon market and exert its emission reduction function. This paper takes the China's pilot carbon market as the research object and measures the carbon market risk by ARMA-GARCH-VaR. Then, influential factors are selected as non-market characteristics from the perspective of causality and incorporated into the risk warning model, and SMOTE and SMOTEENN are introduced to deal with the unbalanced samples. Results show that (1) The risk fluctuations of Beijing and Shenzhen carbon market are large, and the risk fluctuations of Guangdong carbon market are relatively smooth in the early period and larger in the recent period. (2) Air quality, average daily temperature, CSI 300, power coal, natural gas, European carbon market, exchange rate, and Baidu index are all important factors in the risk volatility of carbon market. (3) The Classification Decision Tree (CDT) has the best performance. CDT has the best performance in Guangdong carbon market, SMOTE-CDT has the best performance in Hubei carbon market, and SMOTEENN-CDT has the best performance in Shanghai carbon market, in which SMOTEENN-CDT has a 76% Recall. The non-equilibrium treatment improves the overall Recall, and the risk warning model after non-equilibrium treatment can avoid missing important risk points. This paper can provide a certain degree of reference for the improvement of carbon trading market and risk management. [Display omitted] • A carbon market warning model is constructed. • The average VaR of the carbon trading markets in Shenzhen and Beijing is larger. • CDT performs better in market risk warning. • The model improves 34.8% in the avoidance of risk compared with other models. [ABSTRACT FROM AUTHOR]

The Olympic Games are striking a balance between economic and ecological benefits. Taking the 5 ice event venues of the 2018 PyeongChang Winter Olympic Games as the research object, the CO 2 emissions under the 2018 PyeongChang Low-carbon scenario and 2022 Beijing Low-carbon scenario are compared. The empirical results show that, in terms of venue operation, the Beijing strategies can reduce CO 2 emissions by 715.7 t compared with the PyeongChang strategies. In terms of the refrigerant escape, Beijing's adoption of CO 2 refrigerant can reduce the emission of CO 2 by 1202.2 t compared with the R404 refrigerant used in PyeongChang. This paper confirms the progress of the Green Winter Olympic Games, and may provide implications for the future host countries as well as the cities which in the green transformation. [ABSTRACT FROM AUTHOR]

In the context of China's dual carbon target, Beijing, as the capital of China, should play an exemplary role in carbon emission reduction. On the premise of optimizing high-emission sectors such as coal and industry, Beijing is still a certain distance from the goal of carbon neutrality. Therefore, on the basis of Beijing's energy resource endowment, considering Beijing's economic development and carbon neutrality goals and scientifically and reasonably planning Beijing's carbon emission reduction path are important tasks. We construct an energy structure optimization model to achieve the goal of carbon neutrality by 2050. The model analysis concludes that the residents and transportation sectors will account for a large proportion of Beijing's total carbon emissions in the future. To achieve the goal of carbon neutrality, the electricity substitution of fossil energy and the high proportion of external power are two necessary measures, and the optimal path of carbon emission reduction is proposed. [ABSTRACT FROM AUTHOR]

The widespread adoption of electric vehicles has become pivotal in attaining emissions reduction objectives, and the rationale behind designing and situating charging stations determines the unfurling of electric vehicles. This scholarly work fully mines the geographical situational particulars underlying the functioning statistics of charging stations in Beijing during the period from January to March 2016. By incorporating the urban road network, we construct a charging stations accessibility index to investigate the influence of stations accessibility on utilization rates. The findings reveal a substantial positive relationship between the overall accessibility of charging stations and their utilization rates. However, the limited number of charging stations hinders the agglomeration effect from significantly boosting utilization rates. Moreover, the impact of charging station accessibility on utilization rates varies significantly across regions with different levels of development, indicating pronounced heterogeneity. The research conclusions of this paper provide useful suggestions for promoting the rational layout of charging stations. [Display omitted] • Charging station accessibility depends on driving distance to important city areas. • The accessibility of charging stations significantly impacts their utilization rate. • Charging station accessibility's impact on utilization rate varies significantly across regions. • Insufficient charging stations limit agglomeration's impact on utilization rates. [ABSTRACT FROM AUTHOR]

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This research tries to establish the emissions diffusion model of high-speed motor vehicles on the Capital Ring Expressway (CRE) around Beijing, China, applying the MOVES and the CALPUFF models. Data required for this study have been collected from different sources. The results show that small buses and large trucks have the highest pollutant emissions on the CRE. The pollutants like CO and HC mainly comes from gasoline vehicles, while NOx, PM10 and PM2.5 comes from diesel vehicles. The average concentrations of the diffusion of CO, NOx, CH4, PM10, and PM2.5 along with the CRE are 6.5 mg/m3, 2.3 mg/m3, 0.27 mg/m3, 0.055 mg/m3 and 0.056 mg/m3 respectively. The results of this study have practical significance and influence on the emission reduction and concentration control strategies under different circumstances, and put forward suggestions on changing transportation modes, strengthening supervision and so on. It has produced a number of recommendations for the policy makers including (1) active promotion of new energy vehicles on expressways, (2) strategic change of the mode of passenger and freight transportation on expressways, (3) strengthen traffic management and supervision of motor vehicles on expressways, and (4) strengthen vegetation protection in rural and ecologically sound areas along the route. [ABSTRACT FROM AUTHOR]

An integrated energy system (IES) plays a key role in transforming energy consumption patterns and solving serious environmental and economic problems. However, the abundant optional schemes and the complex coupling relationship among each piece of equipment make the optimization of an IES very complicated, and most of the current literature focuses on optimization of a specific system. In this work, a simulation-based two-step decoupling method is proposed to simplify the optimization of an IES. The generalized IES is split into four subsystems, and a two-layer optimization method is applied for optimization of the capacity of each piece of equipment. The proposed method enables fast comparison among abundant optional configurations of an IES, and it is applied to a hospital in Beijing, China. The optimized coupling system includes the gas-fired trigeneration system, the GSHP, and the electric chiller. Compared with the traditional distributed systems, the emission reduction rate of CO2 and NOX for the coupling system reaches 153.8% and 314.5%, respectively. Moreover, the primary energy consumption of the coupling system is 82.67% less than that of the traditional distributed energy system, while the annual cost is almost at the same level. [ABSTRACT FROM AUTHOR]

To effectively solve the environmental pollution caused by greenhouse gases, countries around the world have successively set up carbon emission trading markets in recent years. At present, China's carbon trading market is only in its infancy, making various mechanisms and policies insufficient. As the core issue of carbon trading market, the fluctuations of carbon trading price are related to the investment decisions of market participants, the formulation of enterprise production and operation plans, and the realization of global emission reduction targets. Therefore, it is of great practical significance to study the influencing factors of carbon price fluctuations and to predict future carbon prices. In this paper, we take the carbon trading week data of the Beijing carbon trading market in China from May to September 2020 as the research object. Firstly, the gray correlation technique is employed to measure the rationality of the selected factors affecting carbon price fluctuations. Secondly, through the principal component analysis method to analyze the various influencing factors, it is found that energy prices and macroeconomic development are the main factors affecting carbon prices, and weather conditions will also cause carbon price fluctuations. Then, four different models are proposed to predict carbon trading prices, and the forecast results are evaluated through the performance evaluation index system. The results show that the GA-ELM model has the best prognosis effect. Finally, according to the analysis results, it provides a useful theoretical reference for carbon market decision makers and participants. [ABSTRACT FROM AUTHOR]

As major carbon (C) pools in cities, urban green spaces play a crucial role in reducing atmospheric carbon. To determine the importance of litterfall C storage in urban green spaces, we selected the leaf area index (LAI) as a proxy indicator for litterfall C density (LCD), and established a log-linear regression model between LCD and LAI to predict the annual litterfall C pool in large-scale urban green spaces using Sentinel-2 satellite remote sensing data. Forty-five sample units were randomly selected in typical urban green spaces in Beijing, China. A high-temperature combustion method was used to measure the LCD of the sampling units, and stepwise linear regression was used to filter the proxy indicator for LCD. The annual litterfall C pool in regions within the Fifth Ring Road was also estimated with inversion using remote sensing data. From 2015 to 2021, the estimated annual litterfall C pool was in the range of 4.5–5.8 × 1010 g, i.e., approximately 18.9% of the total C storage recorded for the urban green space, which was far greater than that observed in forest ecosystems. We concluded that the litterfall C pool in urban green spaces is seriously underestimated, and that urban tree litterfall has the potential to reduce greenhouse gas emissions if used as a carbon-neutral resource. [ABSTRACT FROM AUTHOR]

Beijing-Tianjin-Hebei metropolitan area is a significant carbon emission center. The region's early achievement of peak carbon targets is critical to the nation's achievement of peak carbon targets. In this paper, it is proposed to use different orders of grey models to classify into three scenarios. Based on three scenarios, the grey multivariate convolutional model with new information priority accumulation is adopted to predict carbon emissions in the Beijing-Tianjin-Hebei region and select the scenario suitable for local development. The results show that: (1) The Beijing region has already achieved peak carbon, the Tianjin region may not reach its peak carbon target by 2030, and the Hebei region is expected to reach its peak carbon target by 2030. (2) The high rate of carbon emission reduction scenario will greatly improve the air quality of Beijing. The low-speed growth carbon emission scenario is more in line with the future development of Tianjin city. The low-rate carbon reduction scenario is more in line with the synergistic governance of pollution reduction and carbon reduction in Hebei Province. (3) Beijing's population policy in the most recent years has been conducive to improving the local environment. Tianjin's medium-term population policy is more in line with the local area. Hebei's medium-term industrial structure reform is favorable to local development. • Grey correlation analysis is used to analyze the factors affected carbon emissions in a region. • The factors with high correlation are predicted by using grey prediction models of different orders. • The high rate of carbon emission reduction scenario will greatly improve the air quality of Beijing. [ABSTRACT FROM AUTHOR]

A reasonable allocation of carbon emission quotas is essential to improving the national unified carbon trading market. A bankruptcy game model is developed for allocating carbon emission quotas to Chinese provinces based on bankruptcy theory and the Nash bargaining game. The model takes into account the disparities that exist among these provinces. The allocation scheme under the carbon peak target can be obtained by using the projection pursuit model and the subject satisfaction function. The findings reveal that certain eastern provinces bear a greater responsibility in terms of historical carbon emissions. Furthermore, the rampant transfer of carbon emissions from energy-rich to energy-demanding regions has exacerbated the imbalance in regional development. Interestingly, the carbon emission demands are fulfilled in some provinces situated in the coastal regions of the southwest and southeast, such as Beijing, Tianjin, and Fujian. However, certain provinces in the northeast express the lowest levels of satisfaction with their carbon quota allocation, necessitating a greater burden of carbon emission reduction in the future. The research offers significant implications for regional development and carbon reduction efforts. • A bankruptcy game model is developed for allocating carbon emission quotas. • The model takes into account disparities between the provinces. • The bankruptcy theory and Nash bargaining game are used in this paper. [ABSTRACT FROM AUTHOR]

In recent years, China has been vigorously carrying out the construction and development of a sponge city. To prove that the material and energy consumption involved in the implementation of a sponge city is much less than that of the integrated urban drainage system (IUDS) in addition to saved energy and reduced carbon in the sponge city, it was important to calculate the corresponding carbon source and sink and analyze its key influence factors. The emission factor method was used to calculate carbon emissions. In view of this, based on the Intergovernmental Panel on Climate Change (IPCC) guidelines and life cycle assessment (LCA), this research established a systematic accounting method for carbon emissions from the IUDS and the sponge city, which focused on improving the calculation method of the carbon sink stage. A case study was conducted in Beijing, China, and the carbon emission reduction effect of the construction of the sponge city was discussed. The results showed that the carbon emission reduction potential (CRP) of sponge facilities in this project for 50 years was 612.45 tons of CO2 equivalent after the renovation. Compared with IUDS, sponge city construction had a positive effect on carbon emission reduction and reduced carbon emissions by 87.08% on average. For the IUDS and the sponge city, the stormwater pipe network had the largest contribution of carbon emission, and its material, transportation, pipeline laying, and maintenance of stormwater pipe networks had important influences. Morris global analysis method was used to analyze the sensitivity of LCA results and obtained that the influence degree of sensitivity factors on carbon emissions in the life cycle was in the order of annual rainfall > carbon sequestration rate of green space > high-density polyethylene (HDPE) > transport distance > fertilization and insecticide. This study can provide a positive contribution to the construction of a sponge city and planning the low-carbon development of the city in the future in China. [ABSTRACT FROM AUTHOR]

This study addresses the comparative carbon emissions of different transportation modes within a unified evaluation framework, focusing on their carbon footprints from inception to disposal. Specifically, the entire life cycle carbon emissions of High-Speed Rail (HSR), battery electric vehicles, conventional internal combustion engine vehicles, battery electric buses, and conventional internal combustion engine buses are analyzed. The life cycle is segmented into vehicle manufacturing, fuel or electricity production, operational, and dismantlingrecycling stages. This analysis is applied to the Beijing-Tianjin intercity transportation system to explore emission reduction strategies. Results indicate that HSR demonstrates significant carbon emission reduction, with an intensity of only 24 %-32 % compared to private vehicles and 47 %-89 % compared to buses. Notably, HSR travel for Beijing-Tianjin intercity emits only 24 % of private vehicle emissions, demonstrating the emission reduction benefits of transportation structure optimization. Additionally, predictive modeling reveals the potential for carbon emission reduction through energy structure optimization, providing a guideline for the development of effective transportation management systems. [ABSTRACT FROM AUTHOR]

Currently, air pollution is primarily characterized by PM 2.5 and O 3. Therefore, the co-control of PM 2.5 and O 3 has become an important task of atmosphere pollution prevention and control in China. However, few studies have been conducted on the emissions from vapor recovery and processes, which is an important source of VOCs. This paper analyzed the VOC emissions of three vapor process technologies in service stations and first proposed key pollutants for priority control based on the coordinated reactivity of O 3 and SOA. The concentration of VOCs emitted from the vapor processor was 3.14–9.95 g m−3, compared to 631.2–717.8 g m−3 for uncontrolled vapor. Alkanes, alkenes, and halocarbons accounted for a high proportion of the vapor both before and after control. Among the emissions, i -pentane, n -butane, and i -butane were the most abundant species. Then, the species of OFP and SOAP were calculated through the maximum incremental reactivity (MIR) and fractional aerosol coefficient (FAC). The average source reactivity (SR) value of the VOC emissions from three service stations was 1.9 g g−1, while the OFP ranged from 8.2 to 13.9 g m−3 and SOAP ranged from 0.18 to 0.36 g m−3. By considering the coordinated chemical reactivity of O 3 and SOA, a comprehensive control index (CCI) was proposed for the control of key pollutant species that have multiplier effects on environment. For adsorption, trans -2-butene and p -xylene were the key co-control pollutants, while toluene and trans -2-butene were the most important for membrane and condensation + membrane control. A 50% emission reduction of the top two key species that emission account for 4.3% averagely will reduce O 3 by 18.4% and SOA by 17.9%. [Display omitted] • The organized emissions of VOCs from three vapor processors were studied in service stations. • The species composition of VOCs before and after control were analyzed. • The OFP and SOAP were calculated to evaluate the secondary pollution. • The co-control of key pollutants based on SOA and O 3 has great environmental benefits. [ABSTRACT FROM AUTHOR]

Sand and gravel aggregate (SGA) transportation accounts for over 30% of the freight volume in China, which is greater than that of any other cargo; low-carbon development can effectively promote the decarbonization of freight transportation. This study presents a four-step evaluation method to assess CO 2 emission reductions in freight transportation; the proposed method helps determine the relationship between the policy, CO 2 emission reductions, demand, and mode market share. Using Beijing as a case study, this paper estimates the potential of reducing CO 2 emissions from SGA transportation under various scenarios. The scenarios are set based on the avoid, shift, and improve strategies; the results of the Beijing case indicate that the CO 2 emission for SGA transportation is 920.86 kt, which is approximately 1% of the total CO 2 emissions in Beijing. The maximum reductions in CO 2 emissions that can be achieved using the avoid, shift, and improve strategies are 0.92 kt (0.1% of total), 560.52 kt (60.9% of total), and 78.59 kt (8.5% of total), respectively. The shift strategy is confirmed to be the most realistic and cost-effective approach for reducing CO 2 emissions from SGA transportation. In addition, the implementation of subsidy policies is discussed. Marginal abatement costs under the subsidy scenarios are higher than 224 CNY/t, which is higher than the price in the Chinese carbon trading market. • We evaluated CO 2 emission of aggregate transportation in Beijing at the OD level. • CO 2 emission reductions of the avoid, shift, and improve strategies were tested. • Shift strategy performed the best in reducing CO 2 emission. • Avoid and improve strategies can reduce CO 2 emission; but the effects were limited. • Subsidizing rail transport reduced more emission than subsidizing electric trucks. [ABSTRACT FROM AUTHOR]

• The effects of social norm are analyzed through an agent-based model in the provision of recycling infrastructure within the local context for different business models. • Potential CO 2 savings through improving household participation in recycling are revealed in Beijing. • Guidelines for infrastructure to support the norm-based business models are proposed with value captured from carbon emission reduction through recycling. The potential for carbon emissions avoidance through post-consumer recycling has been highlighted in the "Zero-Waste City" initiatives in China, which call for increasing household participation in the community recycling programs. A shift from a facility-oriented strategy to behavior-oriented norm building at the community level provides the local niches for emerging business models in post-consumer recycling. This paper proposes a framework based on the Theory of Planned Behavior to simulate the impact on the participation rate of households in community-based recycling program in the context of different recycling business models in Beijing. Firstly, a questionnaire survey was conducted in 2021 in Beijing (N = 1153) to test the key factors which affect household recycling behavior. Secondly, an agent-based model for community-based recycling which was developed in 2016 has been updated to incorporate the institutional change in the development of zero-waste city initiatives. Scenario analysis is adopted to compare the effects of introducing two new business models to the baseline situation that is prevalent at present. The settings for the two new business models represent the diversified directions of the upgrading of urban recycling sector: one is to improve the intelligence of the collection facilities to save labors, and the other is to involve the informal recyclers to provide door-to-door collection services in person so as to save time for the residents. Additional scenario shows the effects of norm-based solutions in combination with the two strategies addressed above in the long run. The simulation results show that the potential for carbon emissions reduction through post-consumer recycling in Beijing can range from 1 million tons per year at the basic scenario to more than 4.5 million tons per year in the community level norm-based solution scenario. In conclusion, the proposal for sustaining the community-based new business models through the capture of value in the carbon emission reduction is put forward as a guideline for urban recycling infrastructure design. The two dimensions for the upgrading of urban recycling sector. (MSW: Municipal Solid Waste). [Display omitted] [ABSTRACT FROM AUTHOR]

Staggered-peak production (SP)—a measure to halt industrial production in the heating season—has been implemented in North China Plain to alleviate air pollution. We compared the variations of PM1 composition in Beijing during the SP period in the 2016 heating season (SPhs) with those in the normal production (NP) periods during the 2015 heating season (NPhs) and 2016 non-heating season (NPnhs) to investigate the effectiveness of SP. The PM1 mass concentration decreased from 70.0 ± 54.4 μg m−3 in NPhs to 53.0 ± 56.4 μg m−3 in SPhs, with prominent reductions in primary emissions. However, the fraction of nitrate during SPhs (20.2%) was roughly twice that during NPhs (12.7%) despite a large decrease of NOx, suggesting an efficient transformation of NOx to nitrate during the SP period. This is consistent with the increase of oxygenated organic aerosol (OOA), which almost doubled from NPhs (22.5%) to SPhs (43.0%) in the total organic aerosol (OA) fraction, highlighting efficient secondary formation during SP. The PM1 loading was similar between SPhs (53.0 ± 56.4 μg m−3) and NPnhs (50.7 ± 49.4 μg m−3), indicating a smaller difference in PM pollution between heating and non-heating seasons after the implementation of the SP measure. In addition, a machine learning technique was used to decouple the impact of meteorology on air pollutants. The deweathered results were comparable with the observed results, indicating that meteorological conditions did not have a large impact on the comparison results. Our study indicates that the SP policy is effective in reducing primary emissions but promotes the formation of secondary species. [ABSTRACT FROM AUTHOR]

Scientific prediction of net carbon emissions in the Beijing–Tianjin–Hebei (BTH) region is of significance to examine carbon emission reduction in the context of the "double carbon" target. In this study, the carbon peak and carbon neutrality states in the BTH region are determined through a regional double carbon target analysis framework, and a logistic chaotic sparrow search algorithm backpropagation neural network hybrid model (LCSSA-BP) optimized by a logistic chaotic sparrow search algorithm (LCSSA) is used to forecast the net carbon emissions. The findings reveal that the net carbon emissions in the BTH region generally increased during the study period; Beijing, Tianjin, and Hebei are in different stages toward the realization of the double carbon target; population size, affluence, and urbanization rate are positively correlated, whereas the proportion of foreign direct investment and energy intensity is negatively associated with net carbon emissions; the prediction accuracy of the LCSSA-BP is superior to that of the SSA-BP and BP neural network, and it can be used to forecast the net carbon emissions in the BTH region. [ABSTRACT FROM AUTHOR]

Strict air pollution control strategies have been implemented in recent decades in the North China Plain (NCP), previously one of the most polluted regions in the world, and have resulted in considerable changes in emissions of air pollutants. However, little is so far known about the long-term trends of the regional background level of NOx and SO2 , along with the increase and decrease processes of regional emissions. In this study, the seasonal and diurnal variations of NOx and SO2 as well as their long-term trends at a regional background station in the NCP were characterized from 2004 to 2016. On average, SO2 and NOx mixing ratios were 5.7 ± 8.4 and 14.2 ± 12.4 ppb , respectively. The seasonal variations in SO2 and NOx mixing ratios showed a similar pattern, with a peak in winter and a valley in summer. However, the diurnal variations in SO2 and NOx mixing ratios greatly differed for all seasons, indicating different sources for SO2 and NOx and meteorological effects on their concentrations. Overall, the annual mean SO2 exhibited a significant decreasing trend of - 6.1 %yr-1 (R = - 0.84, P < 0.01) from 2004 to 2016, which is very close to - 6.3 %yr-1 of the annual SO2 emission in Beijing, and a greater decreasing trend of - 7.4 %yr-1 (R = - 0.95, P < 0.01) from 2008 to 2016. The annual mean of NOx showed a fluctuating rise of + 3.4 %yr-1 (R = 0.38, P = 0.40) from 2005 to 2010, reaching the peak value (16.9 ppb) in 2010, and then exhibited an extremely significant fluctuating downward trend of - 4.5 %yr-1 (R = 0.95, P < 0.01) from 2010 to 2016. After 2010, the annual mean NOx mixing ratios correlated significantly (R = 0.94, P < 0.01) with the annual NOx emission in North China. The decreasing rate (- 4.8 %yr-1 , R = - 0.92, P < 0.01) of the annual mean NOx mixing ratios from 2011 to 2016 at the Shangdianzi (SDZ) regional atmospheric background station is lower than the one (- 8.8 %yr-1 , R = - 0.94, P < 0.01) for the annual NOx emission in the NCP and in Beijing (- 9.0 %yr-1 , R = - 0.96, P < 0.01). This indicated that surface NOx mixing ratios at SDZ had a weaker influence than SO2 on the emission reduction in Beijing and its surrounding areas in the NCP. The increase in the number of motor vehicles led to an increase in traffic emissions for NOx. This study supported conclusions from previous studies that the measures taken for controlling NOx and SO2 in the NCP in the past decades were generally successful. However, NOx emission control should be strengthened in the future. [ABSTRACT FROM AUTHOR]

China has started to focus on the reduction in pollutants from diesel vehicles with high emission intensities in recent years. Therefore, it is essential and valuable to conduct a deep and detailed exploration of the reduction potential from diesel vehicles and compare the abatement effect from different control measures in upcoming decades. This study attempted to estimate the present emissions of four conventional pollutants from diesel vehicles by applying the Computer Program to Calculate Emissions from Road Transport (COPERT) model, and to predict the future emission trends under different scenarios during 2019–2030, taking the Beijing–Tianjin–Hebei (BTH) region as the case study area. In addition, we analyzed the emission reduction potential of diesel vehicles and compared the reduction effects from different control measures. The results showed that the CO and NOX emissions from diesel vehicles in this region could increase by 104.8% and 83.9%, respectively, given no any additional control measures adopted over the next decade. The largest emission reduction effect could be achieved under the comprehensive scenario, which means that vehicular diesel emissions in 2030 could decrease by 74.8–94.0% compared to values in 2018. The effect of emission reduction under the emission standards' upgrade scenario could cause a gradual increase and achieve a 19.8–82.6% reduction for the four pollutants in 2030. Furthermore, the new energy vehicle promotion scenario could achieve a considerable reduction effect. It could also offer better emission reduction effects under the highway to railway scenario for Tianjin and Hebei provinces. The old vehicle elimination scenario could have a considerable reduction effect, but only in the short term. Furthermore, emission reductions could be mainly influenced by heavy diesel trucks. These results can provide scientific support to formulate effective reduction measures to diesel vehicles for policy makers. [ABSTRACT FROM AUTHOR]

PM 2.5 , generated via both direct emission and secondary formation, can have varying environmental impacts due to different physical and chemical properties of its components. However, traditional methods to quantify different PM 2.5 components are often based on online or offline observations and numerical models, which are generally high economic cost- or labor-intensive. In this study, we develop a new method, named Multi-Tracer Estimation Algorithm (MTEA), to identify the primary and secondary components from routine observation of PM 2.5. By comparing with long-term and short-term measurements of aerosol chemical components in China and the United States, it is proven that MTEA can successfully capture the magnitude and variation of the primary PM 2.5 (PPM) and secondary PM 2.5 (SPM). Applying MTEA to the China National Air Quality Network, we find that (1) SPM accounted for 63.5 % of the PM 2.5 in cities in southern China on average during 2014–2018, while the proportion dropped to 57.1 % in the north of China, and at the same time the secondary proportion in regional background regions was ∼ 19 % higher than that in populous regions; (2) the summertime secondary PM 2.5 proportion presented a slight but consistent increasing trend (from 58.5 % to 59.2 %) in most populous cities, mainly because of the recent increase in O 3 pollution in China; (3) the secondary PM 2.5 proportion in Beijing significantly increased by 34 % during the COVID-19 lockdown, which might be the main reason for the observed unexpected PM pollution in this special period; and finally, (4) SPM and O 3 showed similar positive correlations in the Beijing-Tianjin-Hebei (BTH) and Yangtze River Delta (YRD) regions, but the correlations between total PM 2.5 and O 3 in these two regions, as determined from PPM levels, were quite different. In general, MTEA is a promising tool for efficiently estimating PPM and SPM, and has huge potential for future PM mitigation. [ABSTRACT FROM AUTHOR]