| Literature DB >> 35613644 |
Tianling Li1, Zhengguo Wang2, Chenxu Wang2, Jiayu Huang2, Ming Zhou3.
Abstract
During the COVID-19 pandemic, the use of chlorine-based disinfectants has surged due to their excellent performance and cost-effectiveness in intercepting the spread of the virus and bacteria in water and air. Many authorities have demanded strict chlorine dosage for disinfection to ensure sufficient chlorine residual for inactivating viruses and bacteria while not posing harmful effects to humans as well as the environment. Reliable chlorine sensing techniques have therefore become the keys to ensure a balance between chlorine disinfection efficiency and disinfection safety. Up to now, there is still a lack of comprehensive review that collates and appraises the recently available techniques from a practical point of view. In this work, we intend to present a detailed overview of the recent advances in monitoring chlorine in both dissolved and gaseous forms aiming to present valuable information in terms of method accuracy, sensitivity, stability, reliability, and applicability, which in turn guides future sensor development. Data on the analytical performance of different techniques and environmental impacts associated with the dominated chemical-based techniques are thus discussed. Finally, this study concludes with highlights of gaps in knowledge and trends for future chlorine sensing development. Due to the increasing use of chlorine in disinfection and chemical synthesis, we believe the information present in this review is a relevant and timely resource for the water treatment industry, healthcare sector, and environmental organizations.Entities:
Keywords: Chlorine exposure; Disinfection; Free chlorine; Monitoring technique; Pandemic
Mesh:
Substances:
Year: 2022 PMID: 35613644 PMCID: PMC9124365 DOI: 10.1016/j.scitotenv.2022.156193
Source DB: PubMed Journal: Sci Total Environ ISSN: 0048-9697 Impact factor: 10.753
Fig. 1Schematic diagram of chlorine disinfection process and mechanism in water.
Fig. 2Schematic diagram of the mechanism of chlorine exposure risks on human body.
Analytical performance of electrochemistry-based sensors for free chlorine detection.
| Method | Reagent | Linear range | LOD | Error | Known interferences | Ref. |
|---|---|---|---|---|---|---|
| Electrochemical | KI | 0.01–0.1 | 0.001 | ND | Oxidant | ( |
| Electrochemical | None | 0.10–3.0 | 0.10 | <6.0% | Bromine-, triiodide ion-, oxidants | ( |
| Electrochemical | None | 0.10–2.0 | 0.0083 | 2.56% | Ion strength | ( |
| Electrochemical | None | 0.002–0.8 | 0.002 | ND | Oxidants | ( |
| Electrochemical | None | 0.10–1.0 | 0.10 | 20% | pH | ( |
| Electrochemical | None | 0.01–200 | 0.01 | ND | pH | ( |
| Electrochemical | None | 0–20 | 0.03 | 3% | Chloramines | ( |
| Electrochemical | None | 0.01–5.0 | 0.01 | ND | pH | ( |
ND: not determined in the reference.
Fig. 3Typical structure of (a) two-electrode residual chlorine sensor, and (b) three-electrode residual chlorine sensor.
Analytical performance of spectrophotometric sensors for free chlorine detection.
| Method | Reagent | Linear range | LOD | Error | Known interferences | Ref. |
|---|---|---|---|---|---|---|
| Colourimetric | 4-Nitrophenylhydrazine | 0.05–10 | 0.03 | 0.9% | Chlorine-dioxide | ( |
| Colourimetric | DPD | 0.10–5.0 | 0.05 | 2–3% | Nitrite | ( |
| Colourimetric | DPD | 0.15–1.5 | 0.15 | ND | Ammonium | ( |
| Colourimetric | o-Dianisidine | 0.05–1.30 | 0.05 | 1.5% | ND | ( |
| Colourimetric | DPD | 0.01–0.4 | 0.0035 | <5% | Oxidant ions | ( |
| Colourimetric | DPD | 0.04–6.07 | 0.015 | 3.2% | Interference-free | ( |
| Fluorescence | Nitrogen and sulfur co-doped carbon dots | 0–5.2 | 0.0005 | <3.8% | Ferric ions | ( |
| Fluorescence | Protein-stabilized gold nanoclusters | 0.035–56 | 0.035 | <4.2% | Cupric ion | ( |
| Fluorescence | Amino-functionalized metal-organic frameworks | 0.0035–1.0 | 0.0028 | ND | ND | ( |
ND: not determined in the reference.
Fig. 4Schematic diagram of colourimetry and fluorescence spectrophotometry sensors.
Fig. 5Schematic diagram of biosensors.
Analytical performances of typical potentiometric solid-state chlorine sensors reported in the literature.
| Cell arrangement | Linear range | LOD | Response time | Operational temperature | Interferences | Ref. |
|---|---|---|---|---|---|---|
| RuO2 | SrCl2–KCl | AgCl–Ag | 1–100 | 1.0 | 2–3 min | Around 420 °C | O2 | ( |
| RuO2 | BaCl2-KCl| AgCl–Ag | 10–1000 | 10 | >150 s | 250–450 °C | O2 | ( |
| Pb | PbC12 + K2S04 + Al2O3 | RuO2 | 10–106 | 10 | <10 s (>400 ppm) | Room temperature | O2 | ( |
| RuO2 | Na2O-Al2O3-4SiO2| RuO2 - NaCl | 1–10 | 1.0 | 100–300 s | >450 °C | O2 | ( |
| Au| (La0.9Ca0.1)OCl + (Al0.2Zr0.8)4/3.8Nb(PO4)3 | Au | 1000–8000 | 1000 | <3 min | 800 °C | Unknown | ( |
Characteristics of some representative conductometric solid-state electrochemical gaseous chlorine sensors.
| Sensing materials | Linear range | LOD | Response time | Operational temperature | Interferences | Ref. |
|---|---|---|---|---|---|---|
| WO3 thin film | 0.5–1.0 | 0.05 | 1 min | >175 °C | Oxidizing-gases | ( |
| Fe2O3–In2O3 thin film | 0.2–5.0 | 0.20 | 1 min (>5 ppm) | >250 °C | Oxidizing-gases | ( |
| CuO-modified ZnO thick film | >300 | 300 | >1 min | 400 °C | Oxidizing-gases | ( |
| CdIn2O4 thick film | 0.2–1200 | 0.20 | >20 min | >250 °C | Oxidizing-gases | ( |
| CdSnO3 thick film | 0.1–8.0 | 0.10 | >20 min | >250 °C | Oxidizing-gases | ( |
| Sb-doped SnO2 thick nanoporous film | 3–20 | 3.0 | >1 min | >45 °C | HCl, Br2, NO, NO2, H2, NH3 | ( |
| ZnO nanoparticles (thin film) | 5–200 | 5.0 | >1 min | 200 °C | H2S, Moisture | ( |
| Porous SnO2 | 0.5–8 | 0.002 | ~30 s | 160 °C | NO2 Moisture | ( |
| SnO2 nanowire | 0.05–0.4 | 0.048 | 57 s | 50 °C | Moisture | ( |
Fig. 6Comparison of four types of dissolved chlorine monitoring methods in (a) LOD, (b) detection range, and (c) error and interferences.
Fig. 7Comparison of three types of gaseous chlorine monitoring methods in (a) LOD, (b) detection range, (c) response time, and (d) interferences.