1
|
Huang YQ, Zeng Y, Mai JL, Huang ZS, Guan YF, Chen SJ. Disposable Plastic Waste and Associated Antioxidants and Plasticizers Generated by Online Food Delivery Services in China: National Mass Inventories and Environmental Release. ENVIRONMENTAL SCIENCE & TECHNOLOGY 2024. [PMID: 38316131 DOI: 10.1021/acs.est.3c06345] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/07/2024]
Abstract
China's online food delivery (OFD) services consume enormous amounts of disposable plastics. Here, we investigated and modeled the national mass inventories and environmental release of plastics and chemical additives in the plastic. The extra-tree regression identified six key descriptors in determining OFD sales in Chinese cities. Approximately 847 kt of OFD plastic waste was generated in 2021 (per capita 1.10 kg/yr in the megacities and 0.39 kg/yr in other cities). Various additives were extensively detected, with geomean concentrations of 140.96, 4.76, and 0.25 μg/g for ∑8antioxidants, ∑21phthalates, and bisphenol A (BPA), respectively. The estimated mass inventory of these additives in the OFD plastics was 164.7 t, of which 51.1 t was released into the atmosphere via incineration plants and 51.0 t was landfilled. The incineration also released 8.07 t of polycyclic aromatic hydrocarbons and 39.1 kt of particulate matter into the atmosphere. Takeout food may increase the dietary intake of phthalates and BPA by 30% to 50% and raise concerns about considerable exposure to antioxidant transformation products. This study provides profound environmental implications for plastic waste in the Chinese OFD industry. We call for a sustainable circular economy action plan for waste disposal, but mitigating the hazardous substance content and their emissions is urgent.
Collapse
Affiliation(s)
- Yu-Qi Huang
- Guangdong Provincial Key Laboratory of Chemical Pollution and Environmental Safety & MOE Key Laboratory of Theoretical Chemistry of Environment, School of Environment, South China Normal University, Guangzhou 510006, China
| | - Yuan Zeng
- Guangdong Provincial Key Laboratory of Chemical Pollution and Environmental Safety & MOE Key Laboratory of Theoretical Chemistry of Environment, School of Environment, South China Normal University, Guangzhou 510006, China
| | - Jin-Long Mai
- Guangdong Provincial Key Laboratory of Chemical Pollution and Environmental Safety & MOE Key Laboratory of Theoretical Chemistry of Environment, School of Environment, South China Normal University, Guangzhou 510006, China
| | - Zhen-Shan Huang
- Guangdong Provincial Key Laboratory of Chemical Pollution and Environmental Safety & MOE Key Laboratory of Theoretical Chemistry of Environment, School of Environment, South China Normal University, Guangzhou 510006, China
| | - Yu-Feng Guan
- Guangdong Provincial Key Laboratory of Chemical Pollution and Environmental Safety & MOE Key Laboratory of Theoretical Chemistry of Environment, School of Environment, South China Normal University, Guangzhou 510006, China
| | - She-Jun Chen
- Guangdong Provincial Key Laboratory of Chemical Pollution and Environmental Safety & MOE Key Laboratory of Theoretical Chemistry of Environment, School of Environment, South China Normal University, Guangzhou 510006, China
| |
Collapse
|
2
|
Du Z, Tian Z, Yin Y, Wei J, Mu Y, Cai J, Song Z, Cen K. Bioavailability-based risk assessment of various heavy metals via multi-exposure routes for children and teenagers in Beijing, China. ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH INTERNATIONAL 2023; 30:114985-115002. [PMID: 37878177 DOI: 10.1007/s11356-023-30436-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/19/2023] [Accepted: 10/09/2023] [Indexed: 10/26/2023]
Abstract
Assessing the health risks of sensitive population, such as children and teenagers, through multiple exposure routes (MERs) such as ingestion, inhalation, and dermal contact is critical for policy creation that protects or reduces exposure to pollutants for all populations. Heavy metal (HM) contents in food and environmental media in Beijing, capital of China, were collected. Furthermore, on the basis of considering the bioavailability of HMs, we evaluated the multiple environmental routes and health risks to HMs in children and teenagers of eight age groups (2-<3, 3-<4, 4-<5, 5-<6, 6-<9, 9-<12, 12-<15, and 15-<18) in Beijing, China by Monte Carlo simulation approach. The main findings are as follows: lead exposure in children aged 2-<3 years exceeds the exposure dose (0.3 μg·kg-1·d-1) of 0.5 point reduction in intelligence quotient. Moreover, children aged 2-<3 and 6-<9 years have relatively high non-carcinogenic risk (NCR) of 1.32 and 1.30, respectively. The carcinogenic risk (CR) for children aged 6-<9 and 9-<12 years is 2.73×10-6 and 2.39×10-6, respectively. Specifically, the contributions of oral ingestion, dermal contact, and inhalation to the NCR were 69.5%, 18.9%, and 11.6%, respectively. Moreover, the combined NCR contributions of copper, cadmium, mercury, and arsenic (As) were about 69.4%. The contributions of the above three routes to the CR were 93.4%, 4.1%, and 2.5%, in that order, with the largest CR contribution of As being about 92.0%. This study can provide new ideas for accurately assessing the exposure and health risks of HMs in the population, and we believe that it is necessary to update the national standards for food and soil based on the bioavailability of HMs.
Collapse
Affiliation(s)
- Zhongwen Du
- Baoding University of Technology, Baoding, 071000, China
| | - Zuguang Tian
- Baoding Productivity Promotion Center, Baoding, 071000, China
| | - Yelan Yin
- No. 4 Drilling Engineering Branch Company, CNPC Bohai Drilling Engineering Company Limited, Hejian, 062400, Hebei, China
| | - Junxiao Wei
- School of Chemistry and Environment, Guangdong Ocean University, Zhanjiang, 524088, China.
| | - Yue Mu
- Chongqing Key Laboratory of Agricultural Resources and Environment, College of Resources and Environment, Southwest University, Chongqing, 400715, China
| | - Jianjun Cai
- School of Architecture and Traffic, Guilin University of Electronic Technology, Guilin, 541004, China
| | - Zefeng Song
- Institute of Resources and Environmental Engineering, Hebei GEO University, Shijiazhuang, 050031, China
| | - Kuang Cen
- School of Earth Sciences and Resources, China University of Geosciences (Beijing), Beijing, 100083, China
| |
Collapse
|
3
|
Lan DY, He PJ, Qi YP, Wu TW, Xian HY, Wang RH, Lü F, Zhang H. Optimizing the Quality of Machine Learning for Identifying the Share of Biogenic and Fossil Carbon in Solid Waste. Anal Chem 2023; 95:4412-4420. [PMID: 36820858 DOI: 10.1021/acs.analchem.2c04940] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/24/2023]
Abstract
Insights into carbon sources (biogenic and fossil carbon) and contents in solid waste are vital for estimating the carbon emissions from incineration plants. However, the traditional methods are time-, labor-, and cost-intensive. Herein, high-quality data sets were established after analyzing the carbon contents and infrared spectra of substantial samples using elemental analysis and attenuated total reflectance-Fourier transform infrared spectroscopy (ATR-FTIR), respectively. Then, five classification and eight regression machine learning (ML) models were evaluated to recognize the proportion of biogenic and fossil carbon in solid waste. Using the optimized data preprocessing approach, the random forest (RF) classifier with hyperparameter tuning ranked first in classifying the carbon group with a test accuracy of 0.969, and the carbon contents were successfully predicted by the RF regressor with R2 = 0.926 considering performance-interpretability-computation time competition. The above proposed algorithms were further validated with real environmental samples, which exhibited robust performance with an accuracy of 0.898 for carbon group classification and an R2 value of 0.851 for carbon content prediction. The reliable results indicate that ATR-FTIR coupled with ML algorithms is feasible for rapidly identifying both carbon groups and content, facilitating the calculation and assessment of carbon emissions from solid waste incineration.
Collapse
Affiliation(s)
- Dong-Ying Lan
- Institute of Waste Treatment & Reclamation, College of Environmental Science and Engineering, Tongji University, Shanghai 200092, China
| | - Pin-Jing He
- Institute of Waste Treatment & Reclamation, College of Environmental Science and Engineering, Tongji University, Shanghai 200092, China.,Shanghai Institute of Pollution Control and Ecological Security, Shanghai 200092, China
| | - Ya-Ping Qi
- Institute of Waste Treatment & Reclamation, College of Environmental Science and Engineering, Tongji University, Shanghai 200092, China
| | - Ting-Wei Wu
- Institute of Waste Treatment & Reclamation, College of Environmental Science and Engineering, Tongji University, Shanghai 200092, China
| | - Hao-Yang Xian
- Institute of Waste Treatment & Reclamation, College of Environmental Science and Engineering, Tongji University, Shanghai 200092, China
| | - Rui-Heng Wang
- Institute of Waste Treatment & Reclamation, College of Environmental Science and Engineering, Tongji University, Shanghai 200092, China
| | - Fan Lü
- Institute of Waste Treatment & Reclamation, College of Environmental Science and Engineering, Tongji University, Shanghai 200092, China.,Shanghai Institute of Pollution Control and Ecological Security, Shanghai 200092, China
| | - Hua Zhang
- Institute of Waste Treatment & Reclamation, College of Environmental Science and Engineering, Tongji University, Shanghai 200092, China.,Shanghai Institute of Pollution Control and Ecological Security, Shanghai 200092, China
| |
Collapse
|
4
|
Bai X, Tian H, Zhu C, Luo L, Hao Y, Liu S, Guo Z, Lv Y, Chen D, Chu B, Wang S, Hao J. Present Knowledge and Future Perspectives of Atmospheric Emission Inventories of Toxic Trace Elements: A Critical Review. ENVIRONMENTAL SCIENCE & TECHNOLOGY 2023; 57:1551-1567. [PMID: 36661479 DOI: 10.1021/acs.est.2c07147] [Citation(s) in RCA: 11] [Impact Index Per Article: 11.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/17/2023]
Abstract
Toxic trace elements (TEs) can pose serious risks to ecosystems and human health. However, a comprehensive understanding of atmospheric emission inventories for several concerning TEs has not yet been developed. In this study, we systematically reviewed the status and progress of existing research in developing atmospheric emission inventories of TEs focusing on global, regional, and sectoral scales. Multiple studies have strengthened our understanding of the global emission of TEs, despite attention being mainly focused on Hg and source classification in different studies showing large discrepancies. In contrast to those of developed countries and regions, the officially published emission inventory is still lacking in developing countries, despite the fact that studies on evaluating the emissions of TEs on a national scale or one specific source category have been numerous in recent years. Additionally, emissions of TEs emitted from waste incineration and traffic-related sources have produced growing concern with worldwide rapid urbanization. Although several studies attempt to estimate the emissions of TEs based on PM emissions and its source-specific chemical profiles, the emission factor approach is still the universal method. We call for more extensive and in-depth studies to establish a precise localization national emission inventory of TEs based on adequate field measurements and comprehensive investigation to reduce uncertainty.
Collapse
Affiliation(s)
- Xiaoxuan Bai
- State Key Joint Laboratory of Environmental Simulation & Pollution Control, School of Environment, Beijing Normal University, Beijing 100875, China
- Center for Atmospheric Environmental Studies, Beijing Normal University, Beijing 100875, China
| | - Hezhong Tian
- State Key Joint Laboratory of Environmental Simulation & Pollution Control, School of Environment, Beijing Normal University, Beijing 100875, China
- Center for Atmospheric Environmental Studies, Beijing Normal University, Beijing 100875, China
| | - Chuanyong Zhu
- College of Environmental Science and Engineering, Qilu University of Technology (Shandong Academy of Sciences), Jinan 250353, China
| | - Lining Luo
- State Key Joint Laboratory of Environmental Simulation & Pollution Control, School of Environment, Beijing Normal University, Beijing 100875, China
- Center for Atmospheric Environmental Studies, Beijing Normal University, Beijing 100875, China
| | - Yan Hao
- State Key Joint Laboratory of Environmental Simulation & Pollution Control, School of Environment, Beijing Normal University, Beijing 100875, China
- Center for Atmospheric Environmental Studies, Beijing Normal University, Beijing 100875, China
| | - Shuhan Liu
- State Key Joint Laboratory of Environmental Simulation & Pollution Control, School of Environment, Beijing Normal University, Beijing 100875, China
- Center for Atmospheric Environmental Studies, Beijing Normal University, Beijing 100875, China
| | - Zhihui Guo
- State Key Joint Laboratory of Environmental Simulation & Pollution Control, School of Environment, Beijing Normal University, Beijing 100875, China
- Center for Atmospheric Environmental Studies, Beijing Normal University, Beijing 100875, China
| | - Yunqian Lv
- State Key Joint Laboratory of Environmental Simulation & Pollution Control, School of Environment, Beijing Normal University, Beijing 100875, China
- Center for Atmospheric Environmental Studies, Beijing Normal University, Beijing 100875, China
| | - Dongxue Chen
- State Key Laboratory of Earth Surface Processes and Resource Ecology, Faculty of Geographical Science, Beijing Normal University, Beijing 100875, China
| | - Biwu Chu
- State Key Joint Laboratory of Environment Simulation and Pollution Control, Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing 100085, China
| | - Shuxiao Wang
- State Key Joint Laboratory of Environment Simulation and Pollution Control, School of Environment, Tsinghua University, Beijing 100875, China
| | - Jiming Hao
- State Key Joint Laboratory of Environment Simulation and Pollution Control, School of Environment, Tsinghua University, Beijing 100875, China
| |
Collapse
|
5
|
Ma W, Cui J, Abdoulaye B, Wang Y, Du H, Bourtsalas AC, Chen G. Air Pollutant Emission Inventory of Waste-to-Energy Plants in China and Prediction by the Artificial Neural Network Approach. ENVIRONMENTAL SCIENCE & TECHNOLOGY 2023; 57:874-883. [PMID: 36172640 DOI: 10.1021/acs.est.2c01087] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/16/2023]
Abstract
The waste-to-energy (WTE) plant has been deployed in 205 cities in China. However, it always faces public resistance to be built because of the great concerns on flue gas pollutants (FGPs). There are limited studies on the socioeconomic heterogeneity analysis and prediction models of WTE capacity/ FGP emission inventories (EIs) based on big data. In this study, the incinerator level emission factors (EFs) in 2020 of PM, SO2, NOx, CO, HCl, dioxins, Hg, Cd + Tl, and Sb + As+ Pb + Cr + Co + Cu + Mn + Ni were calculated based on 322,926 monitoring values of all the 481 WTE plants (1140 processing lines) operating in China, with uncertainties in the range of ±34.70%. The EFs were significantly 45-96% lower than the national standard (GB18485-2014) and had negative relationships with local socioeconomic elements, while WTE capacity and FGP EIs had significantly positive correlations. Gross domestic product, area of built district, and municipal solid waste generation were the main driving forces of WTE capacity. The WTE capacity increased by 150% from 2015 to 2020, while the total emission of PM, SO2, CO, dioxins, Hg, and Sb + As + Pb + Cr + Co + Cu + Mn + Ni decreased by 42.46-88.24%. The artificial neural network models were established to predict WTE capacity and FGP EIs in the city level, with the mean square errors ranging from 0.003 to 0.19 within the model validation limits. This study provides data and model support for the formulation of appropriate WTE plans and a pollutant emission control scheme in different economic regions.
Collapse
Affiliation(s)
- Wenchao Ma
- School of Environmental Science and Engineering/Key Laboratory of Efficient Utilization of Low and Medium Grade Energy (MoE)/Tianjin Key Lab of Biomass-wastes Utilization, Tianjin University, Tianjin 300072, China
- Earth Engineering Center, Columbia University, New York, New York 10027, United States
| | - Jicui Cui
- School of Environmental Science and Engineering/Key Laboratory of Efficient Utilization of Low and Medium Grade Energy (MoE)/Tianjin Key Lab of Biomass-wastes Utilization, Tianjin University, Tianjin 300072, China
| | - Boré Abdoulaye
- School of Environmental Science and Engineering/Key Laboratory of Efficient Utilization of Low and Medium Grade Energy (MoE)/Tianjin Key Lab of Biomass-wastes Utilization, Tianjin University, Tianjin 300072, China
| | - Yuan Wang
- School of Environmental Science and Engineering/Key Laboratory of Efficient Utilization of Low and Medium Grade Energy (MoE)/Tianjin Key Lab of Biomass-wastes Utilization, Tianjin University, Tianjin 300072, China
| | - Huibin Du
- College of Management and Economics, Tianjin University, Tianjin 300072, China
| | | | - Guanyi Chen
- School of Environmental Science and Engineering/Key Laboratory of Efficient Utilization of Low and Medium Grade Energy (MoE)/Tianjin Key Lab of Biomass-wastes Utilization, Tianjin University, Tianjin 300072, China
- School of Science, Tibet University, Lhasa 850012, China
| |
Collapse
|
6
|
Chen Y, Zhang Q, Cai X, Zhang H, Lin H, Zheng C, Guo Z, Hu S, Chen L, Tao S, Liu M, Wang X. Rapid Increase in China's Industrial Ammonia Emissions: Evidence from Unit-Based Mapping. ENVIRONMENTAL SCIENCE & TECHNOLOGY 2022; 56:3375-3385. [PMID: 35107276 DOI: 10.1021/acs.est.1c08369] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/14/2023]
Abstract
Ammonia (NH3) is an important precursor of secondary inorganic aerosols and greatly impacts nitrogen deposition and acid rain. Previous studies have mainly focused on the agricultural NH3 emissions, while recent research has noted that industrial sources could be significant in China. However, detailed estimates of NH3 emitted from industrial sectors in China are lacking. Here, we established an unprecedented high-spatial-resolution data set of China's industrial NH3 emissions using up-to-date measurements of NH3 and point source-level information covering eight major industries and 27 subdivided process categories. We found that China emitted 798 (90% confidence interval: 668-933) gigagrams of industrial NH3 into the atmosphere in 2019, equivalent to 44 ± 20% of the industrial emissions worldwide; this flux is 3-fold larger than that in 1998 and has fluctuated since 2014. Furthermore, although fertilizer production is responsible for approximately half of the emissions in China, the emissions from cement production and coal-fired power plants increased dramatically from near zero to 164 and 41 gigagrams, respectively, in the past two decades, primarily due to the NH3 escape caused by the large-scale application of the denitration process. Our results reveal that, unlike other major air pollutants, China's industrial NH3 emission control is still in a critical period, and stricter NH3 emission standards and innovation in pollution control technologies are highly desirable.
Collapse
Affiliation(s)
- Yuang Chen
- Ministry of Education Laboratory of Earth Surface Process, College of Urban and Environmental Sciences, Peking University, Beijing 100871, China
| | - Qianru Zhang
- Ministry of Education Laboratory of Earth Surface Process, College of Urban and Environmental Sciences, Peking University, Beijing 100871, China
- School of Earth and Atmospheric Sciences, Georgia Institute of Technology, Atlanta, Georgia 30332, United States
| | - Xingrui Cai
- Ministry of Education Laboratory of Earth Surface Process, College of Urban and Environmental Sciences, Peking University, Beijing 100871, China
| | - Haoran Zhang
- Ministry of Education Laboratory of Earth Surface Process, College of Urban and Environmental Sciences, Peking University, Beijing 100871, China
| | - Huiming Lin
- Ministry of Education Laboratory of Earth Surface Process, College of Urban and Environmental Sciences, Peking University, Beijing 100871, China
| | - Chaoyue Zheng
- Ministry of Education Laboratory of Earth Surface Process, College of Urban and Environmental Sciences, Peking University, Beijing 100871, China
| | - Zhanqiang Guo
- China Association of Circular Economy, Beijing 100037, China
| | - Shanying Hu
- Center for Industrial Ecology, Department of Chemical Engineering, Tsinghua University, Beijing 100084, China
| | - Long Chen
- Key Laboratory of Geographic Information Science (Ministry of Education), School of Geographic Sciences, East China Normal University, Shanghai 200241, China
| | - Shu Tao
- Ministry of Education Laboratory of Earth Surface Process, College of Urban and Environmental Sciences, Peking University, Beijing 100871, China
| | - Maodian Liu
- School of the Environment, Yale University, New Haven, Connecticut 06511, United States
| | - Xuejun Wang
- Ministry of Education Laboratory of Earth Surface Process, College of Urban and Environmental Sciences, Peking University, Beijing 100871, China
| |
Collapse
|
7
|
Li Q, Yuan M, Shangguan J, Guo M, Wu J, Zhang Y, Pei M, Zhang Z, Zhang M, Sun Y, Tian C, Li J, Zhang G. Insights into Persistent Toxic Substances in Protective Cases of Mobile Phones: Occurrence, Health Risks, and Implications. ENVIRONMENTAL SCIENCE & TECHNOLOGY 2021; 55:6076-6086. [PMID: 33856783 DOI: 10.1021/acs.est.0c07603] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/12/2023]
Abstract
Despite the popularity of smartphones worldwide, persistent toxic substances (PTSs) in protective cases of mobile phones (PCMPs) and their health risks via direct skin contact have been ignored. This study investigated PTSs in PCMPs made in China with different materials and sales territory and their potential harm to human health. Polybrominated diphenyl ethers (PBDEs, 6.40 ng/g), new brominated flame retardants (NBFRs, 144 ng/g), organophosphate esters (OPEs, 10.1 μg/g), short-chain chlorinated paraffins (SCCPs, 3.58 μg/g), medium-chain chlorinated paraffins (MCCPs, 3.17 μg/g), and heavy metals (HMs, 72.3 μg/g) were detected. It was found that the different concentrations and compositions depend on the material, region, and use. Moreover, the raw materials used to fabricate PCMPs are of variable quality and may include recycled plastic waste. There are no standard quality specifications for PCMPs, and different materials have different properties, including specific surface area and adsorption ability. The risk assessment performed by Monte Carlo simulations indicated that the PTSs evaluated pose no health risks to the general population and may have adverse effects on individual high-exposure populations. According to the results of this work, it is suggested that more stringent global specifications for the selection of raw materials should be established, including the content and structural characteristics of PTSs, limitations on the use of additives in the production process, and the handling after use.
Collapse
Affiliation(s)
- Qilu Li
- Key Laboratory for Yellow River and Huai River Water Environment and Pollution Control, Ministry of Education, Henan Key Laboratory for Environmental Pollution Control, School of Environment, Henan Normal University, Xinxiang, Henan 453007, China
| | - Meng Yuan
- Key Laboratory for Yellow River and Huai River Water Environment and Pollution Control, Ministry of Education, Henan Key Laboratory for Environmental Pollution Control, School of Environment, Henan Normal University, Xinxiang, Henan 453007, China
| | - Jingfang Shangguan
- School of Pharmacy, Xinxiang Medical University, Xinxiang, Henan 453003, China
| | - Mengran Guo
- Key Laboratory for Yellow River and Huai River Water Environment and Pollution Control, Ministry of Education, Henan Key Laboratory for Environmental Pollution Control, School of Environment, Henan Normal University, Xinxiang, Henan 453007, China
| | - Jiajia Wu
- Agilent Technologies (China), Inc., Beijing 100102, China
| | - Ying Zhang
- Key Laboratory for Yellow River and Huai River Water Environment and Pollution Control, Ministry of Education, Henan Key Laboratory for Environmental Pollution Control, School of Environment, Henan Normal University, Xinxiang, Henan 453007, China
| | - Mengyuan Pei
- Key Laboratory for Yellow River and Huai River Water Environment and Pollution Control, Ministry of Education, Henan Key Laboratory for Environmental Pollution Control, School of Environment, Henan Normal University, Xinxiang, Henan 453007, China
| | - Ziyi Zhang
- Key Laboratory for Yellow River and Huai River Water Environment and Pollution Control, Ministry of Education, Henan Key Laboratory for Environmental Pollution Control, School of Environment, Henan Normal University, Xinxiang, Henan 453007, China
| | - Mengqiong Zhang
- Key Laboratory for Yellow River and Huai River Water Environment and Pollution Control, Ministry of Education, Henan Key Laboratory for Environmental Pollution Control, School of Environment, Henan Normal University, Xinxiang, Henan 453007, China
| | - Yujing Sun
- Key Laboratory for Yellow River and Huai River Water Environment and Pollution Control, Ministry of Education, Henan Key Laboratory for Environmental Pollution Control, School of Environment, Henan Normal University, Xinxiang, Henan 453007, China
| | - Chongguo Tian
- Key Laboratory of Coastal Environmental Processes and Ecological Remediation, Yantai Institute of Coastal Zone Research, Chinese Academy of Sciences, Yantai 264003, China
| | - Jun Li
- State Key Laboratory of Organic Geochemistry, Guangzhou Institute of Geochemistry, Chinese Academy of Sciences, Guangzhou 510640, China
| | - Gan Zhang
- State Key Laboratory of Organic Geochemistry, Guangzhou Institute of Geochemistry, Chinese Academy of Sciences, Guangzhou 510640, China
| |
Collapse
|
8
|
Ma S, Bie X, Gong C, Qu B, Liu D. Scale-up experiments of SO 2 removal and the promoting behavior of NO in moving beds at medium temperatures. RSC Adv 2021; 11:8846-8856. [PMID: 35423385 PMCID: PMC8695364 DOI: 10.1039/d0ra10164h] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/02/2020] [Accepted: 02/12/2021] [Indexed: 11/21/2022] Open
Abstract
The dry flue gas desulfurization (FGD) method was studied, which is a part of the integrated removal of multi-pollutants at medium temperatures. Although dry flue gas treatment is a simple and effective method, it is still a highly empirical-led application technology. A superior desulfurization adsorbent, fine powder of NaHCO3 (hereinafter called fine NaHCO3), was selected by scale-up experiments. A deep understanding of the reaction process and mechanism is then explored, which helps the further optimization of dry desulfurization. Based on the multi-factor experiments for NaHCO3, the effect mechanism of NO on desulfurization using NaHCO3 is also proposed. The conversion of SO32− → SO42− is promoted by the existence of NO. Therefore, a slight decline can be found. According to the influences of the SO2 concentration and the residence time, it is concluded that the diffusion of SO2 into the channel of NaHCO3 is the rate-limiting step. Impressively, the reaction process of reactants was clearly studied by in situ FTIR spectroscopy to determine the whole process. Moreover, the recycling of NaHCO3 is the main direction for reducing adsorbent consumption in the next step. The predictable insights are beneficial for profoundly understanding the gas composition synergetic interaction for the SO2 removal by the dry treatment using NaHCO3. A superior desulfurizer, fine NaHCO3 was selected by scale-up experiments. A deep understanding of the reaction process and mechanism was explored. The effect mechanism of NO on desulfurization using NaHCO3 was proposed by in situ FTIR results.![]()
Collapse
Affiliation(s)
- Shuangchen Ma
- Hebei Key Lab of Power Plant Flue Gas Multi-Pollutants Control, Department of Environmental Science and Engineering, North China Electric Power University Baoding 071003 PR China +86-312-7525521 +86-312-7525521.,MOE Key Laboratory of Resources and Environmental Systems Optimization, College of Environmental Science and Engineering, North China Electric Power University Beijing 102206 PR China
| | - Xuan Bie
- Hebei Key Lab of Power Plant Flue Gas Multi-Pollutants Control, Department of Environmental Science and Engineering, North China Electric Power University Baoding 071003 PR China +86-312-7525521 +86-312-7525521.,MOE Key Laboratory of Resources and Environmental Systems Optimization, College of Environmental Science and Engineering, North China Electric Power University Beijing 102206 PR China
| | - Chunqin Gong
- Hebei Key Lab of Power Plant Flue Gas Multi-Pollutants Control, Department of Environmental Science and Engineering, North China Electric Power University Baoding 071003 PR China +86-312-7525521 +86-312-7525521
| | - Baozhong Qu
- Hebei Key Lab of Power Plant Flue Gas Multi-Pollutants Control, Department of Environmental Science and Engineering, North China Electric Power University Baoding 071003 PR China +86-312-7525521 +86-312-7525521
| | - Daokuan Liu
- Hebei Key Lab of Power Plant Flue Gas Multi-Pollutants Control, Department of Environmental Science and Engineering, North China Electric Power University Baoding 071003 PR China +86-312-7525521 +86-312-7525521
| |
Collapse
|
9
|
Wu J, Kong S, Zeng X, Cheng Y, Yan Q, Zheng H, Yan Y, Zheng S, Liu D, Zhang X, Fu P, Wang S, Qi S. First High-Resolution Emission Inventory of Levoglucosan for Biomass Burning and Non-Biomass Burning Sources in China. ENVIRONMENTAL SCIENCE & TECHNOLOGY 2021; 55:1497-1507. [PMID: 33423493 DOI: 10.1021/acs.est.0c06675] [Citation(s) in RCA: 21] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/12/2023]
Abstract
Levoglucosan (LG) emitted from non-biomass burning (non-BB) sources has given rise to biased or even unreasonable source identification results when adopting LG as a distinct marker of biomass burning (BB). The estimation of LG emission and its spatiotemporal variation for various sources are the keys to reducing uncertainty. This study first developed a LG emission inventory for China from 25 sub-type sources belonging to eight categories, with a 3 km × 3 km spatial resolution and monthly distribution. The total LG emission in 2014 was 145.7 Gg. Domestic BB and open BB contributed 39.2 and 34.3% of the total emission. Non-BB sources, including municipal solid waste burning (9.7%), firework burning (9.6%), meat cooking (5.4%), domestic coal burning (1.5%), ritual item burning (0.2%), and industrial coal burning (0.1%), contributed to 26.5% of the total emission. LG emission varied spatially and temporally. Non-BB sources have a significant spatiotemporal impact on BB source contributions, even in high BB emission regions or in sowing, harvesting, and winter heating seasons. The local BB contributions have been substantially overestimated by 4.28-369% in previous studies, wherein LG was solely referred to as the BB source. By 2018, LG emission from BB might decrease to 63.9% of its total emission. This high-resolution LG emission inventory can be greatly useful for source identification studies in China. It also supports future research on the modeling of smoke aging and pollution control.
Collapse
Affiliation(s)
- Jian Wu
- Department of Atmospheric Sciences, School of Environmental Studies, China University of Geosciences, Wuhan 430074, China
- Department of Environmental Science and Technology, School of Environmental Studies, China University of Geosciences, Wuhan 430074, China
| | - Shaofei Kong
- Department of Atmospheric Sciences, School of Environmental Studies, China University of Geosciences, Wuhan 430074, China
- Department of Environmental Science and Technology, School of Environmental Studies, China University of Geosciences, Wuhan 430074, China
| | - Xin Zeng
- Department of Atmospheric Sciences, School of Environmental Studies, China University of Geosciences, Wuhan 430074, China
- Department of Environmental Science and Technology, School of Environmental Studies, China University of Geosciences, Wuhan 430074, China
| | - Yi Cheng
- Department of Atmospheric Sciences, School of Environmental Studies, China University of Geosciences, Wuhan 430074, China
- Department of Environmental Science and Technology, School of Environmental Studies, China University of Geosciences, Wuhan 430074, China
| | - Qin Yan
- Department of Atmospheric Sciences, School of Environmental Studies, China University of Geosciences, Wuhan 430074, China
- Department of Environmental Science and Technology, School of Environmental Studies, China University of Geosciences, Wuhan 430074, China
| | - Huang Zheng
- Department of Atmospheric Sciences, School of Environmental Studies, China University of Geosciences, Wuhan 430074, China
- Department of Environmental Science and Technology, School of Environmental Studies, China University of Geosciences, Wuhan 430074, China
| | - Yingying Yan
- Department of Atmospheric Sciences, School of Environmental Studies, China University of Geosciences, Wuhan 430074, China
| | - Shurui Zheng
- Department of Atmospheric Sciences, School of Environmental Studies, China University of Geosciences, Wuhan 430074, China
- Department of Environmental Science and Technology, School of Environmental Studies, China University of Geosciences, Wuhan 430074, China
| | - Dantong Liu
- Department of Atmospheric Sciences, School of Earth Sciences, Zhejiang University, Hangzhou 310027, China
| | - Xiaoyang Zhang
- Geospatial Sciences Center of Excellence Department of Geography, South Dakota State University, Brookings, South Dakota 57007, United States
| | - Pingqing Fu
- Institute of Surface-Earth System Science, School of Earth System Science, Tianjin University, Tianjin 300072, China
| | - Shuxiao Wang
- State Key Joint Laboratory of Environment Simulation and Pollution Control, School of Environment, Tsinghua University, Beijing 100089, China
| | - Shihua Qi
- State Key Laboratory of Biogeology and Environmental Geology, China University of Geosciences, Wuhan 430074, China
| |
Collapse
|
10
|
Wang X, Jacob DJ, Fu X, Wang T, Breton ML, Hallquist M, Liu Z, McDuffie EE, Liao H. Effects of Anthropogenic Chlorine on PM 2.5 and Ozone Air Quality in China. ENVIRONMENTAL SCIENCE & TECHNOLOGY 2020; 54:9908-9916. [PMID: 32600027 DOI: 10.1021/acs.est.0c02296] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/04/2023]
Abstract
China has large anthropogenic chlorine emissions from agricultural fires, residential biofuel, waste incineration, coal combustion, and industrial processes. Here we quantify the effects of chlorine on fine particulate matter (PM2.5) and ozone air quality across China by using the GEOS-Chem chemical transport model with comprehensive anthropogenic emissions and detailed representation of gas-phase and heterogeneous chlorine chemistry. Comparison of the model to observed ClNO2, HCl, and particulate Cl- concentrations shows that reactive chlorine in China is mainly anthropogenic, unlike in other continental regions where it is mostly of marine origin. The model is successful in reproducing observed concentrations and their distributions, lending confidence in the anthropogenic chlorine emission estimates and the resulting chemistry. We find that anthropogenic chlorine emissions increase total inorganic PM2.5 by as much as 3.2 μg m-3 on an annual mean basis through the formation of ammonium chloride, partly compensated by a decrease of nitrate because ClNO2 formation competes with N2O5 hydrolysis. Annual mean MDA8 surface ozone increases by up to 1.9 ppb, mainly from ClNO2 chemistry, while reactivities of volatile organic compounds increase (by up to 48% for ethane). We find that a sufficient representation of chlorine chemistry in air quality models can be obtained from consideration of HCl/Cl- thermodynamics and ClNO2 chemistry, because other more complicated aspects of chlorine chemistry have a relatively minor effect.
Collapse
Affiliation(s)
- Xuan Wang
- School of Energy and Environment, City University of Hong Kong, Hong Kong SAR, China
- School of Engineering and Applied Sciences, Harvard University, Cambridge, Massachusetts 02138, United States
| | - Daniel J Jacob
- School of Engineering and Applied Sciences, Harvard University, Cambridge, Massachusetts 02138, United States
| | - Xiao Fu
- Department of Civil and Environmental Engineering, Hong Kong Polytechnic University, Hong Kong SAR, China
| | - Tao Wang
- Department of Civil and Environmental Engineering, Hong Kong Polytechnic University, Hong Kong SAR, China
| | - Michael Le Breton
- Department of Chemistry and Molecular Biology, University of Gothenburg, Gothenburg, Sweden
| | - Mattias Hallquist
- Department of Chemistry and Molecular Biology, University of Gothenburg, Gothenburg, Sweden
| | - Zirui Liu
- State Key Laboratory of Atmospheric Boundary Layer Physics and Atmospheric Chemistry, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing, China
| | - Erin E McDuffie
- Department of Physics and Atmospheric Science, Dalhousie University, Halifax, Nova Scotia, Canada
- Department of Energy, Environment, and Chemical Engineering, Washington University in St. Louis, St. Louis, Missouri 63130, United States
| | - Hong Liao
- School of Environmental Science and Engineering, Nanjing University of Information Science and Technology, Nanjing, China
| |
Collapse
|
11
|
Liu Y, Shan Y, Wang Y. Novel Simultaneous Removal Technology of NO and SO 2 Using a Semi-Dry Microwave Activation Persulfate System. ENVIRONMENTAL SCIENCE & TECHNOLOGY 2020; 54:2031-2042. [PMID: 31894977 DOI: 10.1021/acs.est.9b07221] [Citation(s) in RCA: 30] [Impact Index Per Article: 7.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/10/2023]
Abstract
As it has a simple system and a small floor area, flue gas simultaneous desulfurization and denitrification technology has a good development prospect, and related research has become a hot topic in the field of flue gas purification. In this work, a novel simultaneous removal technology of NO and SO2 from flue gas using a semi-dry microwave activation persulfate system was developed for the first time. A series of experiments and characterization analyses had been implemented to research the feasibility of this new flue gas purification technology. The oxidation products, free radicals, and mechanism of NO and SO2 simultaneous removal were revealed. The effect of the main technological parameters on NO and SO2 simultaneous removal was also studied. Relevant results demonstrated that an increase in the microwave radiation power, persulfate concentration, and O2 concentration enhanced NO and SO2 simultaneous removal. The increase of NO and SO2 concentrations weakened NO and SO2 simultaneous removal. The reagent dosage, pH value of the solution, and reaction temperature showed a dual influence on NO and SO2 simultaneous removal. Free-radical capture experiments revealed that both SO4-• and •OH that were produced by microwave activation of persulfate were the major active species and played very key roles in NO and SO2 simultaneous removal. The main products (sulfate and nitrate) and byproducts (NO2) in the tail gas were found. The process application and product post-treatment routes were also proposed. The result may provide the necessary inspiration and guidance for the development and application of microwave-activated advanced oxidation technology in the flue gas treatment area.
Collapse
Affiliation(s)
- Yangxian Liu
- School of Energy and Power Engineering , Jiangsu University , Zhenjiang , Jiangsu 212013 , China
| | - Ye Shan
- School of Energy and Power Engineering , Jiangsu University , Zhenjiang , Jiangsu 212013 , China
| | - Yan Wang
- School of Energy and Power Engineering , Jiangsu University , Zhenjiang , Jiangsu 212013 , China
| |
Collapse
|
12
|
HCl Removal Using Calcined Ca–Mg–Al Layered Double Hydroxide in the Presence of CO2 at Medium–High Temperature. Catalysts 2019. [DOI: 10.3390/catal10010022] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022] Open
Abstract
This present work aimed to investigate the influence of CO2 on HCl removal using calcined Ca–Mg–Al layered double hydroxides (CaMgAl-LDHs) at medium–high temperature (400–800 °C) in a fixed-bed reactor. It was revealed that a moderate CO2 concentration (~6%) in the flue gas of the municipal solid-waste incinerators could reduce the HCl capacity of the CaMgAl-layered double oxides (CaMgAl-LDOs). The highest capacity for HCl removal was observed over the CaMgAl-LDOs at 600 °C. However, sintering was also detected when the reaction temperature was below the calcination temperature (600 °C). Moreover, the decreasing HCl adsorption capacity of CaMgAl-LDOs was attributed to the existence of CO2 in the flue gas, which could efficiently inhibit the decomposition of carbonates as well as the conversion into metal chloride during the HCl removal process.
Collapse
|
13
|
Xing Y, Zhang H, Su W, Wang Q, Yu H, Wang J, Li R, Cai C, Ma Z. The bibliometric analysis and review of dioxin in waste incineration and steel sintering. ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH INTERNATIONAL 2019; 26:35687-35703. [PMID: 31745800 DOI: 10.1007/s11356-019-06744-0] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/25/2019] [Accepted: 10/10/2019] [Indexed: 06/10/2023]
Abstract
Facing the common treatment problems of dioxin whose major sources come from waste incineration and steel sintering, we handled a massive literature dataset from the Web of Science database and analyzed the research hotspot and development trend in this field in the past 40 years by bibliometric method. The result indicates that the field of dioxins generated from waste incineration and steel sintering has entered a stage of rapid development since 1990. China occupies a leading position in terms of comprehensive strength with the largest publications output as well as a greater influence in recent years. The most productive institutions and journals are Zhejiang University and Chemosphere, respectively. In addition, the most commonly used keywords in statistical analysis are "fly ash," "emission control," "risk assessment," "congener profile," "formation mechanisms," "sources," "catalysis," and "inhibition," which reflects the current main research direction in this field. The similarities and differences of dioxins generated in waste incineration and steel sintering are reviewed in this paper, which will provide guidance for the future research.
Collapse
Affiliation(s)
- Yi Xing
- School of Energy and Environmental Engineering, University of Science and Technology Beijing, Beijing, 100083, China
- Beijing Key Laboratory of Resource-Oriented Treatment of Industrial Pollutants, University of Science and Technology Beijing, Beijing, 100083, China
| | - Hui Zhang
- School of Energy and Environmental Engineering, University of Science and Technology Beijing, Beijing, 100083, China
- Beijing Key Laboratory of Resource-Oriented Treatment of Industrial Pollutants, University of Science and Technology Beijing, Beijing, 100083, China
| | - Wei Su
- School of Energy and Environmental Engineering, University of Science and Technology Beijing, Beijing, 100083, China.
- Beijing Key Laboratory of Resource-Oriented Treatment of Industrial Pollutants, University of Science and Technology Beijing, Beijing, 100083, China.
| | - Qunhui Wang
- School of Energy and Environmental Engineering, University of Science and Technology Beijing, Beijing, 100083, China
- Beijing Key Laboratory of Resource-Oriented Treatment of Industrial Pollutants, University of Science and Technology Beijing, Beijing, 100083, China
| | - Haibin Yu
- China National Environmental Monitoring Centre, Beijing, 100012, China
| | - Jiaqing Wang
- School of Energy and Environmental Engineering, University of Science and Technology Beijing, Beijing, 100083, China
- Beijing Key Laboratory of Resource-Oriented Treatment of Industrial Pollutants, University of Science and Technology Beijing, Beijing, 100083, China
| | - Rui Li
- School of Energy and Environmental Engineering, University of Science and Technology Beijing, Beijing, 100083, China
- Beijing Key Laboratory of Resource-Oriented Treatment of Industrial Pollutants, University of Science and Technology Beijing, Beijing, 100083, China
| | - Changqing Cai
- School of Energy and Environmental Engineering, University of Science and Technology Beijing, Beijing, 100083, China
- Beijing Key Laboratory of Resource-Oriented Treatment of Industrial Pollutants, University of Science and Technology Beijing, Beijing, 100083, China
| | - Zhiliang Ma
- School of Energy and Environmental Engineering, University of Science and Technology Beijing, Beijing, 100083, China
- Beijing Key Laboratory of Resource-Oriented Treatment of Industrial Pollutants, University of Science and Technology Beijing, Beijing, 100083, China
| |
Collapse
|
14
|
Wang Y, Han X, Liu Y. Removal of Carbon Monoxide from Simulated Flue Gas Using Two New Fenton Systems: Mechanism and Kinetics. ENVIRONMENTAL SCIENCE & TECHNOLOGY 2019; 53:10387-10397. [PMID: 31389232 DOI: 10.1021/acs.est.9b02975] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/10/2023]
Abstract
Two novel removal processes of carbon monoxide using two new Fenton systems (i.e., Cu2+/Fe2+ and Mn2+/Fe2+ coactivated H2O2 systems) were developed. The effect of several process parameters (concentrations of H2O2, Fe2+, Cu2+, and Mn2+, reagent pH value, solution temperature, and simulated flue gas components) on CO removal was studied in a bubbling reactor. The mechanism and kinetics of CO removal were also revealed. Results show that adding Cu2+ or Mn2+ obviously enhances the removal process of CO in new Fenton systems. The measured results of free radical yield demonstrate that the enhancing role is derived from producing more ·OH (they are produced due to the synergistic activation role of Cu2+/Fe2+ or Mn2+/Fe2+ in new Fenton systems. The removal efficiency of CO is raised by increasing concentrations of Fe2+, Cu2+, and Mn2+ and is reduced by raising concentrations of CO, NO, and SO2. Increasing H2O2 concentration, reagent pH, and solution temperature demonstrates a dual impact on CO absorption. Three oxidation pathways are found to be responsible for CO removal in new Fenton systems. Results of mass-transfer reaction kinetics reveal that CO removal processes are located in a fast-speed reaction kinetics region (the CO removal process is controlled by the mass transfer rate).
Collapse
Affiliation(s)
- Yan Wang
- School of Energy and Power Engineering , Jiangsu University , Zhenjiang 212013 , China
| | - Xuan Han
- School of Energy and Power Engineering , Jiangsu University , Zhenjiang 212013 , China
| | - Yangxian Liu
- School of Energy and Power Engineering , Jiangsu University , Zhenjiang 212013 , China
| |
Collapse
|