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Kohse-Höinghaus K. Combustion in the future: The importance of chemistry. Proc Combust Inst 2020; 38:S1540-7489(20)30501-0. [PMID: 33013234 PMCID: PMC7518234 DOI: 10.1016/j.proci.2020.06.375] [Citation(s) in RCA: 9] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 11/02/2019] [Revised: 05/18/2020] [Accepted: 06/28/2020] [Indexed: 06/11/2023]
Abstract
Combustion involves chemical reactions that are often highly exothermic. Combustion systems utilize the energy of chemical compounds released during this reactive process for transportation, to generate electric power, or to provide heat for various applications. Chemistry and combustion are interlinked in several ways. The outcome of a combustion process in terms of its energy and material balance, regarding the delivery of useful work as well as the generation of harmful emissions, depends sensitively on the molecular nature of the respective fuel. The design of efficient, low-emission combustion processes in compliance with air quality and climate goals suggests a closer inspection of the molecular properties and reactions of conventional, bio-derived, and synthetic fuels. Information about flammability, reaction intensity, and potentially hazardous combustion by-products is important also for safety considerations. Moreover, some of the compounds that serve as fuels can assume important roles in chemical energy storage and conversion. Combustion processes can furthermore be used to synthesize materials with attractive properties. A systematic understanding of the combustion behavior thus demands chemical knowledge. Desirable information includes properties of the thermodynamic states before and after the combustion reactions and relevant details about the dynamic processes that occur during the reactive transformations from the fuel and oxidizer to the products under the given boundary conditions. Combustion systems can be described, tailored, and improved by taking chemical knowledge into account. Combining theory, experiment, model development, simulation, and a systematic analysis of uncertainties enables qualitative or even quantitative predictions for many combustion situations of practical relevance. This article can highlight only a few of the numerous investigations on chemical processes for combustion and combustion-related science and applications, with a main focus on gas-phase reaction systems. It attempts to provide a snapshot of recent progress and a guide to exciting opportunities that drive such research beyond fossil combustion.
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Key Words
- 2M2B, 2-methyl-2-butene
- AFM, atomic force microscopy
- ALS, Advanced Light Source
- APCI, atmospheric pressure chemical ionization
- ARAS, atomic resonance absorption spectroscopy
- ATcT, Active Thermochemical Tables
- BC, black carbon
- BEV, battery electric vehicle
- BTL, biomass-to-liquid
- Biofuels
- CA, crank angle
- CCS, carbon capture and storage
- CEAS, cavity-enhanced absorption spectroscopy
- CFD, computational fluid dynamics
- CI, compression ignition
- CRDS, cavity ring-down spectroscopy
- CTL, coal-to-liquid
- Combustion
- Combustion chemistry
- Combustion diagnostics
- Combustion kinetics
- Combustion modeling
- Combustion synthesis
- DBE, di-n-butyl ether
- DCN, derived cetane number
- DEE, diethyl ether
- DFT, density functional theory
- DFWM, degenerate four-wave mixing
- DMC, dimethyl carbonate
- DME, dimethyl ether
- DMM, dimethoxy methane
- DRIFTS, diffuse reflectance infrared Fourier transform spectroscopy
- EGR, exhaust gas recirculation
- EI, electron ionization
- Emissions
- Energy
- Energy conversion
- FC, fuel cell
- FCEV, fuel cell electric vehicle
- FRET, fluorescence resonance energy transfer
- FT, Fischer-Tropsch
- FTIR, Fourier-transform infrared
- Fuels
- GC, gas chromatography
- GHG, greenhouse gas
- GTL, gas-to-liquid
- GW, global warming
- HAB, height above the burner
- HACA, hydrogen abstraction acetylene addition
- HCCI, homogeneous charge compression ignition
- HFO, heavy fuel oil
- HRTEM, high-resolution transmission electron microscopy
- IC, internal combustion
- ICEV, internal combustion engine vehicle
- IE, ionization energy
- IPCC, Intergovernmental Panel on Climate Change
- IR, infrared
- JSR, jet-stirred reactor
- KDE, kernel density estimation
- KHP, ketohydroperoxide
- LCA, lifecycle analysis
- LH2, liquid hydrogen
- LIF, laser-induced fluorescence
- LIGS, laser-induced grating spectroscopy
- LII, laser-induced incandescence
- LNG, liquefied natural gas
- LOHC, liquid organic hydrogen carrier
- LT, low-temperature
- LTC, low-temperature combustion
- MBMS, molecular-beam MS
- MDO, marine diesel oil
- MS, mass spectrometry
- MTO, methanol-to-olefins
- MVK, methyl vinyl ketone
- NOx, nitrogen oxides
- NTC, negative temperature coefficient
- OME, oxymethylene ether
- OTMS, Orbitrap MS
- PACT, predictive automated computational thermochemistry
- PAH, polycyclic aromatic hydrocarbon
- PDF, probability density function
- PEM, polymer electrolyte membrane
- PEPICO, photoelectron photoion coincidence
- PES, photoelectron spectrum/spectra
- PFR, plug-flow reactor
- PI, photoionization
- PIE, photoionization efficiency
- PIV, particle imaging velocimetry
- PLIF, planar laser-induced fluorescence
- PM, particulate matter
- PM10 PM2,5, sampled fractions with sizes up to ∼10 and ∼2,5 µm
- PRF, primary reference fuel
- QCL, quantum cascade laser
- RCCI, reactivity-controlled compression ignition
- RCM, rapid compression machine
- REMPI, resonance-enhanced multi-photon ionization
- RMG, reaction mechanism generator
- RON, research octane number
- Reaction mechanisms
- SI, spark ignition
- SIMS, secondary ion mass spectrometry
- SNG, synthetic natural gas
- SNR, signal-to-noise ratio
- SOA, secondary organic aerosol
- SOEC, solid-oxide electrolysis cell
- SOFC, solid-oxide fuel cell
- SOx, sulfur oxides
- STM, scanning tunneling microscopy
- SVO, straight vegetable oil
- Synthetic fuels
- TDLAS, tunable diode laser absorption spectroscopy
- TOF-MS, time-of-flight MS
- TPES, threshold photoelectron spectrum/spectra
- TPRF, toluene primary reference fuel
- TSI, threshold sooting index
- TiRe-LII, time-resolved LII
- UFP, ultrafine particle
- VOC, volatile organic compound
- VUV, vacuum ultraviolet
- WLTP, Worldwide Harmonized Light Vehicle Test Procedure
- XAS, X-ray absorption spectroscopy
- YSI, yield sooting index
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Zhang Y, Mo J, Li Y, Sundell J, Wargocki P, Zhang J, Little JC, Corsi R, Deng Q, Leung MH, Fang L, Chen W, Li J, Sun Y. Can commonly-used fan-driven air cleaning technologies improve indoor air quality? A literature review. Atmos Environ (1994) 2011; 45:4329-4343. [PMID: 32362761 PMCID: PMC7185562 DOI: 10.1016/j.atmosenv.2011.05.041] [Citation(s) in RCA: 78] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/04/2011] [Revised: 05/13/2011] [Accepted: 05/14/2011] [Indexed: 05/19/2023]
Abstract
Air cleaning techniques have been applied worldwide with the goal of improving indoor air quality. The effectiveness of applying these techniques varies widely, and pollutant removal efficiency is usually determined in controlled laboratory environments which may not be realized in practice. Some air cleaners are largely ineffective, and some produce harmful by-products. To summarize what is known regarding the effectiveness of fan-driven air cleaning technologies, a state-of-the-art review of the scientific literature was undertaken by a multidisciplinary panel of experts from Europe, North America, and Asia with expertise in air cleaning, aerosol science, medicine, chemistry and ventilation. The effects on health were not examined. Over 26,000 articles were identified in major literature databases; 400 were selected as being relevant based on their titles and abstracts by the first two authors, who further reduced the number of articles to 160 based on the full texts. These articles were reviewed by the panel using predefined inclusion criteria during their first meeting. Additions were also made by the panel. Of these, 133 articles were finally selected for detailed review. Each article was assessed independently by two members of the panel and then judged by the entire panel during a consensus meeting. During this process 59 articles were deemed conclusive and their results were used for final reporting at their second meeting. The conclusions are that: (1) None of the reviewed technologies was able to effectively remove all indoor pollutants and many were found to generate undesirable by-products during operation. (2) Particle filtration and sorption of gaseous pollutants were among the most effective air cleaning technologies, but there is insufficient information regarding long-term performance and proper maintenance. (3) The existing data make it difficult to extract information such as Clean Air Delivery Rate (CADR), which represents a common benchmark for comparing the performance of different air cleaning technologies. (4) To compare and select suitable indoor air cleaning devices, a labeling system accounting for characteristics such as CADR, energy consumption, volume, harmful by-products, and life span is necessary. For that purpose, a standard test room and condition should be built and studied. (5) Although there is evidence that some air cleaning technologies improve indoor air quality, further research is needed before any of them can be confidently recommended for use in indoor environments.
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Key Words
- AC, activated carbon
- Air cleaner
- BTEX, benzene, toluene, ethyl benzene, and xylene
- By-product
- CADR, clean air delivery rate
- CFM, cubic feet per minute
- Clean air delivery rate (CADR)
- DBD, dielectric barrier discharge
- EPA, Environmental Protection Agency
- ESP, electrostatic precipitator
- Electrostatic precipitator
- HEPA, high efficiency particulate air
- High efficiency particulate air (HEPA)
- IAQ, indoor air quality
- Indoor air quality (IAQ)
- Ion generator
- Ozone
- PCO, photocatalytic oxidation
- Photocatalytic oxidation (PCO)
- Plasma
- SOA, secondary organic aerosol
- SP, submicron particles
- SVOC, semi-volatile organic compound
- Sorption
- TCO, thermal catalytic oxidation
- TVOC, total volatile organic compound
- Thermal catalytic oxidation (TCO)
- UV-C, ultraviolet C, wavelength range: 280–100 nm
- UVGI, ultraviolet germicidal irradiation
- Ultraviolet germicidal irradiation (UVGI)
- VOC, volatile organic compound
- WHO, World Health Organization
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Affiliation(s)
- Yinping Zhang
- Institute of Built Environment, Department of Building Science, Tsinghua University, Beijing, China
| | - Jinhan Mo
- Institute of Built Environment, Department of Building Science, Tsinghua University, Beijing, China
- Department of Chemistry, Tsinghua University, Beijing, China
| | - Yuguo Li
- Department of Mechanical Engineering, The University of Hong Kong, Hong Kong, SAR, China
| | - Jan Sundell
- Institute of Built Environment, Department of Building Science, Tsinghua University, Beijing, China
- International Center for Indoor Environment and Energy, Technical University of Denmark, Denmark
| | - Pawel Wargocki
- International Center for Indoor Environment and Energy, Technical University of Denmark, Denmark
| | - Jensen Zhang
- Department of Mechanical and Aerospace Engineering, Syracuse University, NY, USA
| | - John C. Little
- Department of Civil and Environmental Engineering, Virginia Tech., VA, USA
| | - Richard Corsi
- Department of Civil, Architectural and Environmental Engineering, The University of Texas at Austin, Austin, TX, USA
| | - Qihong Deng
- School of Energy Science and Engineering, Central South University, Changsha, China
| | - Michael H.K. Leung
- Department of Mechanical Engineering, The University of Hong Kong, Hong Kong, SAR, China
| | - Lei Fang
- International Center for Indoor Environment and Energy, Technical University of Denmark, Denmark
| | - Wenhao Chen
- Department of Mechanical and Aerospace Engineering, Syracuse University, NY, USA
| | - Jinguang Li
- Institute of Shanghai Building Science, Shanghai, China
| | - Yuexia Sun
- College of Engineering and Computer Science, The University of Texas at Tyler, 3900 University Blvd., Tyler, TX, USA
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