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Accurate PM 2.5 forecasting provides a possibility for establishing an early warning system to notify the public and take precautionary measures to prevent negative effects on ambient air quality and public health. Considering strong seasonal variation in meteorological conditions, in this paper, a seasonal stacked autoencoder model combining seasonal analysis and deep feature learning is proposed for forecasting the hourly PM 2.5 concentration, named DL-SSAE model. The original data are firstly decomposed into four seasonal subseries according to the Chinese calendar, and then the Kendall correlation coefficient method is employed to search inherent relationships between PM 2.5 concentrations and meteorological parameters within 1-h ahead for each seasonal time series. The inherent relationships of each seasonal subseries are finally extracted, learned, and modeled by different deep neural networks (stacked autoencoders for regression), and the hourly PM 2.5 forecasts are yielded. The addressed model is tested by the dataset collected from three environmental monitoring stations in Beijing, China. The results demonstrate that the proposed model outperforms all other considered models with/without seasonality consideration in this paper. [ABSTRACT FROM AUTHOR]

Within the context of climate change and population growth, the development of urban agriculture is of great environmental and economic significance in rapidly urbanizing China. Based on the primary survey data, this paper evaluated the carbon footprint (CF) and economic efficiency of urban agriculture in Beijing (China) using the life cycle assessment method (from cradle to consumption approach). Two cases were analyzed and compared considering their differences in on-farm cultivation and off-farm supply chains: a conventional small householder farm that sells its vegetables directly to consumers in a local market, and a large home-delivery agriculture (HDA) initiative that delivers its vegetables to the consumers' home directly. Both cases were equipped with greenhouses with plastic covering but no heating system. The CF of the production, transportation and distribution of 1 kg fresh vegetables was estimated at 0.318 kg CO 2 -eq kg−1 and 0.624–0.652 kg CO 2 -eq kg−1 for conventional and HDA initiative farm, respectively. However, the HDA initiative showed a better environmental performance than the conventional operation when taking economic efficiency into consideration. The CF per unit of profit of HDA initiative (0.093–0.097 kg CO 2 -eq per CNY) was lower than conventional farm (0.111 kg CO 2 -eq per CNY). The lower CF per unit of product weight of the conventional farm was largely attributed to the high yield and the lower CF per unit of profit of the HDA initiative was mainly due to the outstanding economic profitability through income optimization. The major hotspots of CF in both cases were greenhouse plastic films in the cultivation phase (from cradle to farm gate) and transportation in the supply chain (from farm gate to consumption). Simulation of a switch to biodiesel instead of gasoline and diesel in combination with the replacement of current fossil-fuel-dominated electricity by hydro-powered electricity resulted in 20.0–21.8% reduction in the total CF. By identifying the CF hotspots of two farm cases, particular inputs and activities can be targeted for adjustment in order to effectively reduce the CF of urban agriculture in Beijing. [ABSTRACT FROM AUTHOR]

From 1990 to 2017, the number of vehicles in China increased sharply from 5 million to 310 million, and vehicle emissions became one of the major sources of air pollution. Among the main sources of PM 2.5 in Beijing, the contributions from vehicle sources increased from 5.6% (2000) to 31.1% (2012) to 45% (2017). In 2010, the CO, hydrocarbon (HC), NO x , and particulate matter (PM) emissions of yellow-label vehicles (YLVs) accounted for 46.1%, 47.9%, 63.1% and 86.1% of the total emissions from on-road vehicles. In recent years, China has been implementing a YLV scrappage subsidy policy to control air pollution, and this policy has cost several hundred billion yuan nationwide. However, China has not evaluated the costs and benefits of the policy. Many people question whether the YLV scrappage subsidy policy is worthwhile, but all the stakeholders involved complicate the process of accurately evaluating the true value of the policy. In this study, we evaluated and compared the costs and benefits of the policy in the Beijing-Tianjin-Hebei (BTH) region based on 1.362 million YLVs from 2008 to 2015. Because of the implementation of the policy, the PM 2.5 , PM 10 , NO x , CO and HC emissions in the BTH region decreased by 16.46, 18.12, 174.44, 669.11, and 91.64 kt, respectively, in 2008–2015. The results show that the policy played an important role in reducing pollutant emissions and improving environmental quality in the BTH region. The costs, benefits, and net benefits of the policy were 13.69, 34.03, and 20.34 billion yuan , respectively. The cost-benefit ratio in the BTH region was 1:2.49; at the city scale, Beijing ranked first (1:7.27), and the cost-benefit ratios of Tianjin and Hebei Province were 1:2.06 and 1:1.14, respectively. Of the 13 cities in the BTH region, Beijing had the highest net benefits, amounting to 16.43 billion yuan , while Handan City has the lowest net benefits, amounting to −0.58 billion yuan. The results may provide scientific support for the promotion of older vehicle and diesel vehicle scrappage subsidy policies, the development of cost-benefit analysis (CBA), and effective environmental decision-making in China. • Based on net number of scrappage YLVs, net benefits of the policy are calculated. • This paper estimates costs and benefits of the policy based on 1.27 million YLVs. • The costs, benefits, and net benefits are 13.69, 34.03, and 20.34 billion yuan. • The results help China promote vehicle scrappage subsidy policy on a large scale. • The results promote the development of the cost-benefit analysis in China. [ABSTRACT FROM AUTHOR]

The urban heat island effect in Beijing is significant, which has become a serious environmental problem posed to Beijing citizens. As an important measure to alleviate the urban heat island effect, cool roof is recommended in relevant Evaluation Standard for Green Building of China. In order to elicit policy implications, this paper investigates Beijing residents' willingness to pay for promoting cold roofs to alleviate the urban heat island effect and its determinants. This research applied double-bounded discrete choice format and face to face interview to elicit public's willingness to pay. 841 Beijing households were randomly selected and interviewed. For 242 (29%) respondents refuse to pay, the spike model was introduced to process the data for it has been proved to outperform the conventional model in dealing with zero responses. The average annual willingness to pay was computed as 1510.854 Chinese Yuan, which is 220.562 US dollars per household. In addition, In terms of the determinants of residents' willingness to pay, other than conventional demographic characteristics, we added and estimated covariance with regard to environmental knowledge and the theory of planned behavior. The result indicated that social norm, perceived behavior control, and previous knowledge of urban heat island effect and cool roof are statistical significantly related with residents' willingness to pay. This research suggests that timely information disclosure with regard to urban environment management and pro-environment education are urgently needed in promoting public participation in alleviating the urban heat island effect. • Willingness to pay for cool roofs for mitigating urban heat island effect is estimated. • The annual mean willingness to pay 1510.854 Chinese Yuan. • TPB theory and environmental knowledge can greatly explain pro-environment behavior. • Government credibility and education is important in promoting public participation. [ABSTRACT FROM AUTHOR]

Abstract This paper investigates the potential expansion and impacts of Electric Vehicle (EV) market in Beijing, China at the micro level with an agent-based integrated urban model (SelfSim-EV), considering the interactions, feedbacks and dynamics found in the complex urban system. Specifically, a calibrated and validated SelfSim-EV Beijing model was firstly used to simulate how the EV market might expand in the context of urban evolution from 2016 to 2020, based on which the potential impacts of EV market expansion on the environment, power grid system and transportation infrastructures were assessed at the multiple resolutions. The results suggest that 1) the adoption rate of Battery Electric Vehicle (BEV) increases over the period, whereas the rate of Plug-in Hybrid Electric Vehicle (PHEV) almost remains the same; Furthermore, the so-called neighbour effects appear to influence the uptake of BEVs, based on the spatial analyses of the residential locations of BEV owners; 2) the EV market expansion could eventually benefit the environment, as evident from the slight decrease in the amounts of HC, CO and CO 2 emissions after 2017; 3) Charging demand accounting for around 4% of total residential electricity demand in 2020 may put slight pressure on the power grid system; 4) the EV market expansion could influence several EV-related transport facilities, including parking lots, refuelling stations, and charging posts at parking lots, in terms of quantity, layout and usage. These results are expected to be useful for different EV-related stakeholders, such as local authorities and manufacturers, to shape polices and invest in technologies and infrastructures for EVs. [ABSTRACT FROM AUTHOR]

Abstract Agricultural nonpoint source pollution (NPS) is the main water-use impairment in the upper watershed of the Miyun Reservoir in Beijing, China. Selection and placement of best management practices (BMPs) in heterogeneous watersheds, requires a multi-objective optimization framework to identify the most cost-effective conservation strategy to achieve desired water quality goals. In this paper, a novel optimization methodology was developed, utilizing a BMP database that includes BMP reduction efficiencies and costs, using a multi-objective sorting genetic algorithm (NSGA-II, nondominated sorting genetic algorithm-II) combined with the Soil Water and Assessment Tool (SWAT) served as the NPS watershed model. Cost-effectiveness curves (optimal fronts) between pollutant reduction and total net cost input were obtained for the upper watershed of Miyun Reservoir. The optimal combination of BMP, which include a combination of conservation tillage, careful timing of 30% less fertilizer application, contour planting, and use of a 10-m edge-of-field buffer strip, indicate that the least costly scenario reduced total nitrogen (TN) and total phosphorus (TP) loads by 33% at a cost of 1.02 × 106 China Yuan. The cost-effective scenario reduced TN and TP loads 44% and 68% at a cost of 2.52 × 107 and 5.64 × 107China Yuan. The greatest reduction scenario reduced TN and TP loads 55% and 76%, respectively, at a cost of 2.01 × 108 and 2.48 × 108 China Yuan. Watershed with poultry operations, required a 30% reduction in number of birds, along with a 30% reduction in the amount of manure applied was needed to achieve water quality goals. Use of the coupled BMP optimization model can assist the policy makers achieve a cost-effective implementation of best management practices to mitigate agricultural nonpoint sources at a watershed scale. Highlights • Multi-objective optimization model for the selection and placement of BMPs for nonpoint source pollution control. • Cost-effectiveness analysis for single and combination BMPs at watershed scale. • Dynamic database were development to achieve the auto-simulation of SWAT model. [ABSTRACT FROM AUTHOR]

Beijing, the capital of China, has experienced rapid industrialization, urbanization and motorization in recent decades. Consequently, air pollution in Beijing, especially fine particulate matter (PM 2.5 ) pollution, has gradually become a severe environmental issue, due to the continuing growth in energy consumption and the resulting multiple pollutant emissions. In response to the increasingly serious PM 2.5 pollution, Beijing's government implemented a series of policies, measures and regulations on air pollution prevention and control and took some concrete actions to improve air quality. In this paper, firstly, we summarize China's ambient air quality standards, China's policies and regulations on air pollution prevention and control. Secondly, we illustrate historical evolution and current status of air pollution in Beijing. Finally, we introduce control measures and actions in Beijing and its surrounding areas. The paper aims to help environmental scientists and policy makers around the world understand the past and current air pollution in Beijing and control strategies and actions taken by Beijing's government. [ABSTRACT FROM AUTHOR]

With China's rapid urbanization and industrialization, carbon emission in Chinese cities deserve special attention, and promoting low-carbon city (LCC) is considered essential for China. However, different cities present different development stages and carbon emission scenarios. This study presents the factors affecting carbon emission by introducing a city development-stage framework. The method of logarithmic mean Divisia index (LMDI) is adopted to decompose emission factors into energy structure, energy intensity, industrial structure, economic output and population scale. Beijing is chosen as the case city in this study, and four development stages for the city are identified by using the Environmental Kuznets Curve (EKC) theory, namely, S 1 (−1991), S 2 (1991–2004), S 3 (2004–2022) and S 4 (2022-). As the data collected for analysis are only available for the period of 1995–2014, this study focuses on the factor analysis for the stage S 2 and S 3 . The results show that the main driving factor for carbon emission increase in the stage S 2 is economic output, followed by population scale, while the main factor contributes to carbon emission reduction in this stage is the industrial structure. In the stage S 3 , the economic output is the top contributor to increase carbon emission, followed by population scale and energy structure, whereas energy intensity is the main influencing factor in curbing the carbon emission. Although the paper refers to the specific case of Beijing, the understanding on the driving emission factors in different development stages not only provides policy-makers and practitioners with valuable references for adopting effective measures to reduce carbon emission, but also provides other cities internationally with important lessons for accelerating the development of LCC. The innovative economic development stage framework incorporates carbon emission characteristics provides a new approach for understanding driving emission factors at city or national level. [ABSTRACT FROM AUTHOR]

Based on analysis of the wetland water resources system in Beijing city, this paper established a system dynamics (SD) model for the water resources carrying capacity (WRCC) in Beijing city. Using a computer simulation of the SD model, the variation trends from 2006 to 2030 in population, economy, water supply and demand, and pressure on the water environment were derived for Beijing, from which 12 core variables of the model were chosen as the WRCC evaluation indices. Five cases were designed in this study. The results indicate that the WRCC will continue to decline annually by following the status quo (Case 1), since the water environment will have difficulty in supporting the long-term social and economic development of Beijing. The status quo of Beijing’s socioeconomic development is therefore not sustainable. In order to address this problem, five optimization cases were put forward to improve the WRCC, and the carrying capacities and trends of the cases were compared and analyzed. Under Case 5, the WRCC (0.8 in 2030) will increase by 50%, compared to that in Case 1 (0.4 in 2030), while the water supply and demand ratio will be 20% higher than the average, and the water pollution will be 35% lower than the average in 2030. According to the analysis results, in order to guarantee sustainable utilization of water resources and social economy development in Beijing, it is necessary to increase water saving policies and pollution control investment in the future. Corresponding measures will need to be taken to ensure the implementation of water saving strategies to improve the water environment. [ABSTRACT FROM AUTHOR]

Self-reported life satisfaction of China's population has not improved as much as expected during the economic boom, which was accompanied by a significant decline in environmental performance. Is environmental pollution the culprit for the lagging subjective well-being? To explore this issue, this paper adopts sentiment analysis to construct a real-time daily subjective well-being metric at the city level based on the big data of online search traces. Using daily data from 13 Chinese cities centred on Beijing between August 2014 and December 2019, we look at the corelation between subjective well-being and air pollution and the heterogeneity in this relationship based on two separate identification strategies. We find that air pollutants are negatively correlated with subjective well-being, and well-being tends to decline more from pollution during hot seasons. In addition, residents in wealthier regions tend to be more sensitive to air pollution. This result may be explained by the differences in the subjective perception of air pollution and personal preferences at different levels of income. These findings provide information about concerns of the public, thereby helping the government to take appropriate actions to respond to the dynamics of subjective well-being. • Sentiment analysis and big data are adopted to construct a daily city-level subjective well-being metric. • Higher levels of airborne particulates lead to a decline in subjective well-being. • Peoples' well-being tends to decline more from pollution during hot seasons. • Residents in wealthier regions tend to be more sensitive to air pollution. [ABSTRACT FROM AUTHOR]

As a basic structural unit of the city, the community plays a crucial role in decreasing carbon emissions and creating a low carbon city. This paper selects a classic and official low carbon community named Min'an Community in Beijing as a case to illustrate the governance mechanism of the low carbon community in China from the perspective of polycentric governance. The paper summarizes the government mechanism, market mechanism, and public participation mechanism in Min'an Community and analyzes the provision, monitoring, and enforcement of each mechanism. We find that unlike the low carbon governance at the city or industry park levels, China's low carbon governance at the community level lacks a dominant mechanism. Even though it involves community-wide governance, the public participation mechanism is also inadequate. For improving low carbon governance at the community level, the government should broaden finance channels to strengthen the incentive mechanisms, make active use of new technologies, such as mobile Internet, encourage innovation of public participation mechanism, and employ various publicity and education measures to cultivate the low carbon culture. [ABSTRACT FROM AUTHOR]

The agricultural sector is extremely vulnerable to climate change and also plays a very important role in the operation of the entire economic system, leading many studies to evaluate the possible agricultural direct economic damage (ADED) of climate change. However, this damage may have an amplification impact through the intricate industrial linkages that exist among sectors, and this impact may be even greater than the original damage. Therefore, to elucidate the economic cascading effect (ECE) in China caused by ADED and industrial linkage, this paper used the ARIO model to evaluate the total ECE and analyse the differences in the 19 sectors by taking the ADED under future annual mean temperature (AMT) increases of 1–5 °C as the input condition and adjusting the exogenous parameters to enhance the adaptability of the model; the goal was to assess the economic impact of climate change in China. The results show that (i) there is a significant amplifying impact of ECE due to industrial linkage under the influence of warming, ECE will be 4.24–5.25 times that of ADED, and the total economic impact (ADED + ECE) will exceed the GDP of the Chinese capital of Beijing in 2012 when the AMT increases by 1.5 °C, while it will exceed one tenth of China's GDP when it increases by 4 °C. (ii) Manufacturing will be the sector most affected by the industrial linkage under ADED, which accounts for 26.58% of total ECE, followed by agriculture (10.39%) and construction (8.5%). (iii) The decrease in cultivated land area will have a significant impact on the economy; when it is reduced to the minimum demand (1.41% less than 2012), ADED increases by 1.65 times and ECE increases by 2.35 times. This paper aims to provide a new perspective from which to evaluate the economic impact of climate change by studying ECEs behind sectoral interactions. [ABSTRACT FROM AUTHOR]

The coordination development among various subsystems, especially among economic, social and environmental subsystems, is an important part of urban sustainability that directly affects the quality of urbanization. This paper evaluated the sustainability of the 9 China's national central cities using the coupling coordination model. In the evaluation process, an objective coupling weighting method was developed by the combination of the coupling analysis and the sequential relationship analysis method. The validity of this method was illustrated by comparing the coordination level of the cities with that obtained by the entropy method. Long-term use of this method can guide the coordination development among economy, society and environment of cities. The assessment results indicate that the coordination development among economy, society and environment of the cities was not ideal. Only one city, Beijing, located in the good coordination grade. The main reason is the lower development of economic sustainability. Policy recommendations were provided to address the problem. In addition, the paper concludes that there is a great room for improvement in the coordinated development of the cities, because they showed an increase trend in coordinated development and the economic growth rate was relatively high. [ABSTRACT FROM AUTHOR]

Abstract: This paper is to investigate the behavior of residents towards electrical and electronic waste (e-waste) recycling in Beijing. For this purpose a large sample questionnaire survey was performed to explore the residents’ characteristics of recycling behavior and preference of e-waste recycling pattern. Besides, the willingness of residents to participate in e-waste recycling was also assessed in our study. For this a logistic regression model was developed to estimate and explain residents’ willingness in e-waste recycling. The model showed that Convenience of recycling facilities and service, Residential conditions, Recycling habit and Economic benefits are four determinants of Beijing residents’ willingness and behavior in e-waste recycling. And centralized recycling pattern by professional recovery spots would have a broad prospect if various kinds of channels can be provided to make the residents feel more convenient in e-waste recycling. [Copyright &y& Elsevier]

Abstract: Since the open door policy in 1978 China has undergone enormous economic and social changes making China to be one of the largest economies and consumers of resources in the world. The pronounced differences in income and lifestyles especially between urban and rural China were also part of China''s economic rebirth. This paper explores current trajectories and scenarios for urbanization and lifestyle changes and other important socio-economic trends in China. The implications of these changes are analysed for Beijing in particular and then compared to China for the year 2020. These changes by 2020 are modelled using input–output analysis in combination with the Ecological Footprint and Water Footprint. [Copyright &y& Elsevier]

Abstract: This paper presents an economic evaluation of three typical recycling processes for the five main types of waste electronic home appliances (EHA) (TV set, refrigerator, washing machine, air conditioner and personal computer) in Beijing, the capital of China. The main purpose is to identify the formal management framework with economic feasibility for the waste EHA generated in large municipalities of China. It is found that the advanced technologies, which have mechanical processing units, should be introduced to recover more valuable materials from the waste appliances. Net revenues with a range of 90–240RMB (Chinese currency unit, 1.0USD≈8.0RMB) per unit, depend on the type of appliance, could be expected in case of using the most complicated procedures which can separate both metals and plastics from the shredded mixtures. However, the recycling of waste refrigerator and waste washing machine will, respectively, spend about 100 and 6RMB per unit if solely by simple manual dismantling. Revenues from recycling of the other three types of appliances are positive but quite low in this case. Although positive revenues could be achieved from the isolated evaluation of recycling, the entire management system, which also covers the phases of collection and transportation, is economically infeasible if the waste appliances are bought from the households still at current prices. Based on a survey of the householder''s attitude to the cost for waste EHA management, which was conducted earlier, the practical way to construct a formal management system for waste EHA in Beijing is to reduce the citizen''s traditional expectation to the values of waste appliances and encourage their transfer to the formal collection system at lower prices. [Copyright &y& Elsevier]

To our knowledge, the previous studies did not answer the following questions: how much does window analysis differ from the original Data Envelopment Analysis (DEA) approaches and how to develop DEA window analysis? To address these questions, we propose three intermediate approaches (cross-sectional approach, window efficiency analysis and window index approach) and statistically compare their performances. The underlying concern is that we need to examine whether a metrological bias exists in our study. The concern is important in guiding policy issues such as energy policy and climate change. Empirically, the proposed approaches are applied to measure the unified efficiency of fossil fuel power plants at a provincial level in China from 2007 to 2017, since these plants are important energy consumers and CO 2 emitters. We obtain two important implications. First, considerable differences were confirmed among the three approaches, thus implying an existence of the methodological bias. Second, Beijing (the capital of China) outperformed the other provinces in terms of their measures, since the government has paid serious attention to air pollution emitted from fossil fuel power plants. The governmental regulation in Beijing is a good example of pollution prevention in China. It is expected that the success on Beijing will be disseminated to the other provinces. This paper proposed three approach, i.e. one conventional approach (cross-sectional approach) and two new approaches (window efficiency analysis and window index approach). The two new approaches were capable of measuring efficiency shifts or technology shifts over time. Empirically, these approaches were adopted to evaluate the performance of Chinese fossil fuel power plants. Image 1 • We evaluate the performance of China's fossil fuel power plants from 2007 to 2017. • Three formulations are utilized for DEA intermediate approach. • The first policy effort was put on Beijing and gradually on other provinces. • China made a progress on economic and environmental measures during this period. [ABSTRACT FROM AUTHOR]

The knowledge of soil environmental quality and its changing trends is important for safe and sustainable land utilization. However, comprehensive information on soil environment carrying capacity, involving environmental, economic and social pressures, is relatively rare. In this study, a modified dynamic capacity model is developed to estimate soil environment carrying capacity in terms of a combined consideration of soil environment capacity, cumulative input/output rate and risk characteristics. Based on the method proposed, this paper demonstrates the current pollution status and remaining soil capacity of the Beijing urban area, and establishes a conceptual "early warning" model for soil environmental quality, to predict time-dependent changing patterns of soil pollutants under different accumulation scenarios. The results showed that for Beijing soil environmental carrying capacity varied with land use type and pollutant. Compared with Cu, Zn and Pb, Cd posed the greatest threat to soil environmental carrying capacity in both residential areas and green parks. Heavy metal carrying capacity in soils in built-up areas in Beijing was not overloaded currently, and will not deteriorate significantly over the short-to medium-term in a hypothetical "decreased input" scenario. The method proposed provides a simple, cost-effective, and quantitative tool for mapping soil quality level, and assessing the need for risk management measures, in China and elsewhere. • Natural attenuation capacity provides basis for soil environment carrying capacity. • Cumulative rate and risk characteristics are other dominant factors in model input. • An early warning system is necessary for effective risk management measures. • Soil environmental carrying capacity varied with land use type and pollutant. • The framework and model are transferable in other international urban settings. [ABSTRACT FROM AUTHOR]

Air pollution has become an emerging environmental issue in developing countries like China in the last two decades. Sulphur dioxide (SO 2 ) is one of the major air pollutants that poses significant risks in many areas undergoing a process of industrialization such as Beijing. Realizing the main factor causing environmental quality changes is the key to solving this problem. By using an extended version of IPAT model, this paper aims to identify the main contributors of air pollution in Beijing from 1989 to 2012. The result shows that the most influential factors affecting air pollution in Beijing are affluence and emission intensity. From analyzing the historical background, we conclude that the air pollution change in Beijing is heavily policy-driven. [ABSTRACT FROM AUTHOR]