Preparation of a novel PAN/cellulose acetate-Ag based activated carbon nanofiber and its adsorption performance for low-concentration SO_2

Polyacrylonitrile （PAN）, PAN/cellulose acetate （CA）, and PAN/CA-Ag based activated carbon nanofiber （ACNF） were prepared using electrostatic spinning and further heat treatment. Thermogravimetrylifferential scanning calorimetry （TG-DSC） analysis indicated that the addition of CA or Ag did not have a significant impact on the thermal decomposition of PAN materials but the yields of fibers could be improved. Scanning electron microscopy （SEM） analysis showed that the micromorphologies of produced fibers were greatly influenced by the viscosity and conductivity of precursor solutions. Fourier transform infrared spectroscopy （FT-IR） analysis proved that a cyclized or trapezoidal structure could form and the carbon scaffold composed of C=C bonds appeared in the PAN-based ACNFs. The characteristic dif- fraction peaks in X-ray diffraction （XRD） spectra were the evidence of a turbostratic structure and silver existed in the PAN/CA-Ag based ACNF. Brurmer-Emmett-Teller （BET） analysis showed that the doping of CA and Ag increased surface area and micropore volume of fi- bers; particularly, PAN/CA-Ag based ACNF exhibited the best porosity feature. Furthermore, SO2 adsorption experiments indicated that all the three fibers had good adsorption effects on lower concentrations of SO2 at room temperature; especially, the PAN/CA-Ag based ACNF showed the best adsorption performance, and it may be one of the most promising adsorbents used in the fields of chemical industry and en- vironment protection.

Toward Systemic Thinking in Managing Environmental Risks

1.Introduction The world today is strongly interconnected.Numerous interdependent and complex networks have been formed between environmental,economic,and social systems,through which people,resources,materials,goods,and information are exchanged at unprecedented speeds[1].At the same time,however,such networks are profoundly changing the global risk landscape and making the whole system more vulnerable[2].In particular,there is a growing concern about cascading and systemic risks.In such cases,a localized initial damaging event(e.g.,the coronavirus disease 2019(COVID-19)pandemic)can spread rapidly and globally,resulting in disruptive influences and countless societal costs[3].

Same stimuli,different responses:a pilot study assessing air pollution visibility impacts on emotional well-being in a controlled environment

A growing number of studies have shown that impaired visibility caused by particulate matter pollution influences emotional wellbeing.However,evidence is still scant on how this effect varies across individuals and over repetitive visual exposure in a controlled environment.Herein,we designed a lab-based experiment(41 subjects,6 blocks)where participants were presented with real-scene images of 12 different PM_(2.5) concentrations in each block.Emotional valence(negative to positive)and arousal(calm to excited)were self-rated by participants per image,and the response time for each rating was recorded.We find that as pollution level increases from 10 to 260µg/m3,valence scores decrease,whereas arousal scores decline first and then bounce back,following a U-shaped trend.When air quality deteriorates,individual variability decreases in hedonic valence but increases in arousal.Over blocks,repetitive visual exposure increases valence at a moderate pollution level but aggravates negative emotions in severely polluted conditions(>150µg/m3).Finally,we find females,people who are slow in making responses,and those who are highly aroused by clean air tend to express more negative responses(so-called negativity bias)to ambient pollution than their respective counterparts.These results provide deeper insights into individual-level emotional responses to dirty air in a controlled environment.Although the findings in our pilot study should only be directly applied to the conditions assessed herein,we introduce a framework that can be replicated in different regions to assess the impact of air pollution on local emotional wellbeing.

ADVANCES IN NETWORK FUNCTION VIRTUALIZATION

In traditional networks,enabling new network functions often needs to add new proprietary middleboxes.However,finding the space and power to accommodate these middleboxes is becoming increasingly difficult,

Future research needs for environmental science in China

Environmental science is an interdisciplinary science developed in the process of understanding and solving ecolog-ical and environmental problems.In order to tackle these problems,environmental science research is expected to reveal the source,behavior,fate,exposure,and risks of pollutants in the environment and develop potential solutions to control pollution.It provides the scientific basis for decision-makers to establish environmental and economic poli-cies,and promote concerted efforts for the sustainable development of society.Here,we articulate the development patterns,challenges,and future research needs of environmental science in China based on literature review and expert panel discussion.Environmental science research has evolved significantly in the past decade with an increas-ing diversity of environmental pollutants and health impacts,new technologies and methods,deepening fusion of multiple disciplines,and emerging solutions for pollution control.Its future development relies on the advances in our knowledge on the fate and transport of pollutants,regional environmental processes,ecotoxicological effects,environmental exposure and health effects,environmental analysis and monitoring,source control and reduction,environmental remediation,as well as environmental risk management.For each of these fields,we summarize the significant challenges and highlight the research demands for China.Based on the status quo of China’s environmen-tal science research and future needs,we provide recommendations to promote its future development,including encouraging innovation and interdisciplinary research,providing decision support for national needs,encouraging international collaboration,and improving collaboration mechanisms.

Clean air captures attention whereas pollution distracts:evidence from brain activities

Awareness of the adverse impact of air pollution on attention-related performance such as learning and driving is rapidly growing.However,there is still little known about the underlying neurocognitive mechanisms.Using an adapted dot-probe task paradigm and event-related potential(ERP)technique,we investigated how visual stimuli of air pollution influence the attentional allocation process.Participants were required to make responses to the onset of a target presented at the left or right visual field.The probable location of the target was forewarned by a cue(pollution or clean air images),appearing at either the target location(attention-holding trials)or the opposite location(attention-shifting trials).Behavioral measures showed that when cued by pollution images,subjects had higher response accuracy in attention-shifting trials.ERP analysis results revealed that after the cue onset,pollution images evoked lower N300 amplitudes,indicating less attentioncapturing effects of dirty air.After the target onset,pollution cues were correlated with the higher P300 amplitudes in attention-holding trials but lower amplitudes in attention-shifting trials.It indicates that after visual exposure to air pollution,people need more neurocognitive resources to maintain attention but less effort to shift attention away.The findings provide the first neuroscientific evidence for the distracting effect of air pollution.We conclude with several practical implications and suggest the ERP technique as a promising tool to understand human responses to environmental stressors.

An ensemble machine learning model to uncover potential sites of hazardous waste illegal dumping based on limited supervision experience

With the soaring generation of hazardous waste(HW)during industrialization and urbanization,HW illegal dumping continues to be an intractable global issue.Particularly in developing regions with lax regulations,it has become a major source of soil and groundwater contamination.One dominant challenge for HW illegal dumping supervision is the invisibility of dumping sites,which makes HW illegal dumping difficult to be found,thereby causing a long-term adverse impact on the environment.How to utilize the limited historic supervision records to screen the potential dumping sites in the whole region is a key challenge to be addressed.In this study,a novel machine learning model based on the positive-unlabeled(PU)learning algorithm was proposed to resolve this problem through the ensemble method which could iteratively mine the features of limited historic cases.Validation of the random forest-based PU model showed that the predicted top 30%of high-risk areas could cover 68.1%of newly reported cases in the studied region,indicating the reliability of the model prediction.This novel framework will also be promising in other environmental management scenarios to deal with numerous unknown samples based on limited prior experience.

Appreciating the role of big data in the modernization of environmental governance

1 Introduction The development of the Internet of Things,drones,and new social media platforms opened up an unprecedented space for the autonomy of human society.It promoted the formation of a new form of social relations and social field-cyber society(Jones,1995).The cyber society has already become a digital twin of the actual society and even the extensions.It reconstructed the whole society through impacting social control and social norms.In this context,it is of great theoretical and practical significance to expand the field of social governance from traditional society to cyber society.

A MISR-Based Method for the Estimation of Particle Size Distribution:Comparison with AERONET over China

Aerosol particle size has a crucial impact on the environment and public health.Current satellite-based regression models focus on the total amount of particles and are limited by surface observations.This study proposes an algorithm to derive the long-term normalized volume size distribution(VSD)of aerosol particles,which is independent of ground measurements.The size distribution and aerosol optical depth of Multi-angle Imaging SpectroRadiometer(MISR)components are employed.We find the estimated MISR VSD is consistent with Aerosol Robotic Network(AERONET)observations,with R=0.56,0.54,0.59,and 0.68 for daily,monthly,seasonal,and annual levels.The stratified validations of radius,stations,and years further confirm the stable performance of derived VSD(R=0.28 to 0.73).The application of the random forest model demonstrates the potential improvements of predicted VSD by 10-fold cross-validation R=0.86 at the monthly level.We apply MISR VSD to quantify the normalized volume of fractional aerosol particles at a resolution of 0.2°×0.2°during 2004 to 2016 in China.We also calculate the proportion of small and medium particles to indicate the contribution of anthropogenic aerosols.The highest ratios are concentrated in the northeastern regions especially during winter while relatively lower in the Taklamakan Desert of western China.The case study demonstrates that the application of MISR data can yield valuable and resolved size distributions of aerosol particles.

Epidemic transition of environmental health risk during China's urbanization

China has experienced rapid urbanization in recent decades along with dramatic economic growth. Previous studies have shown that urbanization has both positive and negative effects on health. However, there is a lack of research on the overall effects of urbanization on the epidemic transition of environmental health risks considering various pathways in China. In the present study, we studied the contributions of different aspects of urbanization in China to epidemic transitions using provincial and multi-year （1995, 2000, 2005, and 2010） panel data. Statistical models with fixed and random effects were developed to explore the impacts of different urbanization indicators on the overall epidemic tran- sition of environmental health （general model） and the changes in cause-specific mortality rates of typ- ical diseases （cause-specific models）. The results show that the impacts of non-communicable diseases continue to grow during the urbanization process in China. The ratio of communicable disease-related mortality to non-communicable disease-related mortality continues to decrease over time. The general model shows that the improved medical conditions （coefficient =-0.0011, P= 0.037）, the improved urban infrastructure （e.g., tap water supply） （coefficient = -0.00065, P 〈 0,001）, and the rise in income （coefficient = -0.00027, P = 0.047） during the urbanization process are important factors that promote this overall epidemic transition. The cause-specific models show that the mechanisms behind the general model are complicated. More attention should be paid to non-communicable diseases in urban health management. Specific health policies for different diseases should incorporate the considerations of dif- ferent impact pathwavs of urbanization,

Perception of people for the risk of Tianwan nuclear power plant

A questionnaire survey of residents’risk perceptions related to Taiwan nuclear power plant in China was carried out to explore the determining factors that affect individual risk perception.This study proposed to pursue a more comprehensive understanding of factors that affected individual risk perception to nuclear power plants.Covariance structure analysis was conducted using risk perceptions of nuclear power as dependent variable and including interest and knowledge levels of nuclear power,acceptability,benefit perception,trust in nuclear power operation,and trust in government as independent variables.The use of the hypothesis of Elaboration likelihood model(ELM)was also proposed.The results showed that persons with higher levels of interest and knowledge of nuclear power had their own perceptions of risk closely associated with acceptability and potential benefits of nuclear power.In contrast,persons with no interest in and knowledge of nuclear power would have risk perceptions related to their trust in nuclear operation and the government,which partially supported the ELM hypothesis.All these results indicated that the government in China plays an important role in rational risk perceptions,and well-designed communication of risks will help the public to be involved in risk management and improve people’s rational acceptance of risk.

Cost-benefit analysis of China’s Action Plan for Air Pollution Prevention and Control

China’s rapid economic growth has caused severe air pollution and public health problems.Therefore,the Chinese government launched the Action Plan for Air Pollution Prevention and Control(hereinafter referred to as the“Air Plan”)in 2013-2017 to improve air quality and safeguard public health.In this study,an analytical framework for a cost-benefit analysis applicable to China was constructed,and the costs and benefits of the implementation of the“Air Plan”in 30 cities and provinces in China from 2013 to 2017 were evaluated.Results show that the total cost of implementation of the“Air Plan”is 1.6511 trillion RMB.The benefits of air quality improvement were determined to be 2.4691 trillion RMB through the willingness-to-pay method to calculate the economic loss of premature deaths.The net benefit related to the implementation of the“Air Plan”was 818 billion RMB.The public health benefit of air quality improvement was 1.5 times the cost of the nationwide implementation of the“Air Plan”.At the provincial level,net benefits that reach 279.3 billion RMB were the highest in Guangdong,whereas the benefit-cost ratio,where the benefit was 5.5 times the cost,was the highest in Fujian.Estimations in this study can serve as a reference for China in formulating similar environmental policies and implementing the “3-year Plan to Defend the Blue Sky”.In addition,these estimations have practical significance for advancing the long-term effective mechanisms of the cost-benefit analysis of China5s environmental policies.

Public perception of environmental issues across socioeconomic characteristics:A survey study in Wujin,China

In developing countries,there is controversy over the correct perception regarding environmental and developmental issues.Few studies have examined the perception of low-income nationals in regards to social and environmental issues.This paper looks at the relationship between socio-demographic factors and the groups’perceived priority regarding environmental and social issues in Wujin County.The results indicated that most residents,specifically the young,government employed and the urban community consider environmental issues to be serious,especially in relation to air pollution and water pollution.Furthermore,many residents feel it is important to rank environmental problems that are related to other social and economic issues,and that environmental protection must be set as a priority in Wujin County.Compared to social issues,environmental concern was greater among the young,government employed,and the urban community,because of their higher education and affluence.In addition,66.2%of residents consider environmental protection to be more important than economic development.Thus,environmental protection must be set as a high priority in Wujin County,in order to face the many social and environmental challenges inherent in development.

Drivers and barriers to engage enterprises in environmental management initiatives in Suzhou Industrial Park,China

Small-and medium-sized enterprises(SMEs)play an important role in sustainable development not only for their significant contribution to China’s economy,but also for their large share of total discharged pollutants.Therefore,this research takes the enterprises in Suzhou Industrial Park,China as the case study to investigate the environmental management practices of SMEs,and identify drivers and barriers to engaging businesses in environmental management initiatives.It is shown that,as in other countries,SMEs are less active in adopting environmental management initiatives than larger companies.Legislation remains the key driver to engage SMEs in environmental management initiatives.Based on the analysis,policy recommendations are also presented.

Fuel type preference of taxi driver and its implications for air emissions

Natural gas became an available fuel for taxis in 2005 and had occupied a market share of 43.6% in taxi industry till 2010 in Nanjing, China. To investigate the energy replacement pattern as well as the pollutants reduction potential of the taxi industry, first, the fuel preference determinants of taxi drivers for their next taxis are analyzed. Results show that as an important alternative for the traditional gasoline, natural gas is widely accepted （75%） by taxi drivers. Different from the previous studies which focused on the early stage of cleaner fuel replacement, taxi drivers with various characteristics （such as age, working experience, and education level） are consistent with their fuel preference when they choose their next taxis. Result suggests that policies that concern consumers with specific characteristics may have little effects on the change of the market share, when the alternative fuel market has been developed well. In addition, the increased share of gas in the fuel market achieves a 7.2% reduction of energy consumption. Considering life cycle emissions, the following air pollutants, namely Greenhouse Gases （GHGs）, carbonic oxide （CO）, nitrogen oxide （NOx）, particulate matters （PM） and hydrocarbons （CxHy）, gain 10.0%, 3.5%, 20.5%, 36.1%, and 26.4% of reduction respectively. Assuming all taxi fleets powered by natural gas with local policy intervention, the energy conservation and the five major air pollutant emissions could achieve the maximum reductions with 12.2%, 16.0%, 8.8%, 22.5%, 44.2%, and 49.4% correspondingly.

Material flow analysis(MFA)of an eco-economic system:a case study of Wujin District,Changzhou,China

The economic and ecological aspects of a social system are coherently linked and can be examined by its material and energy flows.In this study,we used the material flow analysis(MFA)to model the material input and output of the Wujin District of Changzhou City,Jiangsu Province in China.It was revealed that:(1)total material input and material input per capita increased with economic development,while the total material out-put and material output per capita decreased consistently;(2)except for water,the total material input continued to increase.Input of solid materials grew faster than that of gaseous materials,while the total material output declined.The gas output accounted for the largest pro-portion of the output resulting in primary environmental pollution as burned fossil fuel;(3)water use in agriculture continued with an increasing trend while that in industrial and residential sectors decreased per capita.The total wastewater discharge and wastewater discharge per capita decreased with a faster decreasing rate of residential was-tewater discharge followed by industrial wastewater discharge;(4)material input per unit GDP fluctuated and material output per unit GDP decreased.A decreasing trend in both water use and wastewater discharge per unit GDP was disclosed.These results suggest that the efficiency of resource use in the Wujin District has improved.This weakened the direct link between economic development and environmental deterioration.Additionally,we discussed the harmonic development between environment and economy.Potential limitations of MFA’s application were also discussed.It is suggested that effective measures should be taken for the enforcement of cir-cular economic strategies and the construction of a resource-saving economy.

The influencing factors of the WTP for the risk reduction of chemical industry accidents in China

To explore the factors that influence respon- dents＇ willingness to pay （WTP） for the risk reduction of chemical industry accidents, a questionnaire survey combined with contingent valuation and psychometric paradigm methods were conducted in the city of Yancheng, Jiangsu Province, China. Both traditional socioeconomic variables and perceived characteristics of the hazards were considered in this study, and a Tobit model was used to find the factors influencing WTP under three risk reduction scenarios. The results showed that three demographic characteristics, age, gender, and income, significantly affected the WTP for chemical risk reduction. In addition, three extracted public risk perception factors, effect, knowledge, and trust, also strongly affected the WTP. The mean WTP value increased as the magnitude of the risk reduction increased. The number of factors influencing the WTP decreased as the reduction level improved, and only the effect factor had a significant influence on the WTP for a higher level （80%） of risk reduction. The cost for chemical safety management of Yancheng was calculated, and the optimized risk reduction level was determined. These findings can assist governments and policy makers to formulate suitable strategies for risk control, to reach target groups of people to develop effective communication, and to provide specific refer- ences for the best investment for the security of local residents.

Leveraging individual-level data to advance air pollution health risk management

1 Introduction Environmental health risk management is a systematic engineering task,engaging multiple disciplines from the academic and government sectors.Reducing environmental health risks has become one of the key targets in the United Nations Sustainable Development Goals(SDGs).This target has been translated into public policies at many jurisdictional levels(Yue et al.,2020).To design region-specific and targeted policy initiatives,understanding how environmental health risks are spatially distributed and temporally resolved is fundamental.