Diagnosis of Nutrient Discharges and Management Alternatives in Developing Countries and the Use of Microalgae as a Potential Solution: A Case Study from Different Provinces in Antioquia, Colombia
Abstract
:1. Introduction
2. Materials and Methods
2.1. Scope of Technologies
2.2. Pollutant Analysis for Municipalities in Antioquia
2.3. Forecast for Current Pollutant Discharges in Antioquia
3. Results and Analysis
3.1. Scope of Microalgae-Based Technologies
3.2. Pollutant Analysis for Municipalities in Antioquia
3.2.1. Nutrient Concentrations in Natural Water
3.2.2. Pollutant Concentrations in Wastewater
3.3. Opportunities for Current Pollutant Discharges in Antioquia
Removal Efficiency (%) | COD | BOD | SST | NT | PT | Refs. | |
---|---|---|---|---|---|---|---|
Conventional sludge treatment | 85–95 | 85–90 | 85–95 | 85–95 | 25–30 | 25–30 | [55], p. 26 |
Extended sludge treatment | 93–98 | 90–95 | 85–95 | 90–95 | 15–25 | 10–20 | [55], p. 26 |
UASB–activated sludge | 85–95 | 83–90 | 85–95 | 75–90 | 15–25 | 10–20 | [55], p. 26 |
Septic tank (48HRT) | 50–60 | 50–60 | 58.3–75 | −5.2 | 20.8 | 26.9 | [56,57] |
Mesh rotating biological reactor (MRBR) | 48–63 | 77–90 | ND | ND | 10–38 | ND | [58,59] |
UASB | 52 | 66 | 60 | 62.4 | [60] |
4. Discussion
5. Conclusions
Author Contributions
Funding
Data Availability Statement
Acknowledgments
Conflicts of Interest
Abbreviations
MDPI | Multidisciplinary Digital Publishing Institute |
DOAJ | Directory of open-access journals |
TLA | Three-letter acronym |
LD | Linear dichroism |
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Search Criteria | Limitations | Date Ranges |
---|---|---|
“Wastewater” + “Tertiary Treatment” + “Microalgae”. | Matches: All/Publication status: Completed/Type of Document: Articles, Review, book chapters/Subject: Environmental sciences/All Open Access Scopus database. | 2002–2022 |
Refs. | Microalgae | Type of Wastewater or Process | Pollutant Removal Yield |
[22] | Spirulina platensis C. vulgaris | Biosorption process | |
[23] | Scenedesmus, Pediastrum, Chlorella mixture | Supernatant sludge sedimentation | |
[14] | Chlorella sp. | Filtered and sterilized agricultural runoff | |
[24] | Scenedesmus sp. | Supernatant sludge sedimentation | |
Chlorella sp. | |||
Hapalosyphon sp. | |||
[25] | Scenedesmus obliquus | SE-WWTP | |
[26] | Chlorella vulgaris | Filt-WW | |
[27] | Chlorella sp. and Stigeoclonium sp. | SE-WWTP | |
Removal efficiency for most emerging | |||
[28] | Scenedesmus sp. | SE-WWTP | |
[29] | Cyanobacteria (cf. Oscillatoria) + Microalgae (Chlorella and Stigeoclonium) | SE-WWTP mixture | , low, even negative with low inorganic carbon |
[30] | Cyanobacteria (cf. Aphanocapsa sp.) + Microalgae (Chlorella and Scenedesmus sp.) | SE-WWTP mixture | |
[5] | Chlorella sp., Scenedesmus sp., and Stigeoclonium sp. | SE-WWTP diluted | |
[31] | Scenedesmus sp. and Aphanocapsa sp. | SE-WWTP mixture | |
[32] | Chlorella sp. among others | SE-WWTP | ; Other pollutants, varied removal efficiencies |
[16,17] | cyanobacteria Synechocystis sp. | SE-WWTP diluted | . Other pollutants, varied removal efficiencies. Pesticides, herbicide mixtures, pharmaceuticals, personal care, flame retardants, and surfactants from negative to 100% removal |
[20] | Non-specified microalgae consortia | SE-WWTP | In 4 different seasons: to to to to |
[33] | Chlorella vulgaris, Nannochloropsis oculata, Scenedesmus acutus, and Scenedesmus obliquus | Synthetic | Diclofenac from 59 to 91.1% |
[34] | Acutodesmus obliquus, Desmodesmus Maximus, and Chlorella vulgaris | SE-WWTP sterilized | D. Maximus: TN = 91% ; A. obliquus: ; C. Vulgaris: |
[35] | Scenedesmus sp. DDVG I | SE-WWTP filtered and sterilized | |
[36] | Chroococcus turgidus | SE-WWTP | |
[21] | Chlorella sorokiniana | Chicken and cow WW filtered | at 3 different temperatures |
[37] | Chlorella vulgaris | Fisheries WW |
Variable | P | ||||||||||
---|---|---|---|---|---|---|---|---|---|---|---|
Units | mg | mg | mg | NTU | mg/L | mg/L | mL/L | mg N/L | mg/L | mg | mg |
Min: | 0.2259 | 0.02 | 2.5 | 0.531 | 3.37 | 7 | 0.1 | 2.5 | 0.05 | 2.84 | 2.65 |
Q1: | 0.2485 | 0.02 | 5 | 6.768 | 82 | 7 | 0.1 | 5 | 0.1 | 17.62 | 19.1 |
Median: | 0.2485 | 0.03 | 5 | 25.25 | 150 | 29 | 0.1 | 5 | 0.237 | 34.75 | 30.35 |
Mean: | 1.545 | 0.0492 | 5.98 | 193.53 | 307.08 | 146.7 | 0.497 | 6.725 | 0.58 | 49.36 | 62.43 |
Q3: | 0.7319 | 0.03 | 5 | 119.5 | 331.75 | 125.2 | 0.3 | 5 | 0.5108 | 60.5 | 60.4 |
Max.: | 114.078 | 1.56 | 59 | 10,000 | 6510 | 5179 | 30 | 79.1 | 14.1 | 361 | 1008 |
Variable | * | ||||||||||
Units | m.s.n.m | L/s | U pH | uS/cm | °C | °C | mg/L | mg | mg | NMP | mg |
Min: | 37 | 0 | 1.65 | 3.08 | 10.8 | 13 | 0.17 | 10 | 2 | −0.3567 | 0.153 |
Q1: | 171.2 | 31 | 6.82 | 51.05 | 19.1 | 21.8 | 6.082 | 12 | 2 | 9.5568 | 0.153 |
Median: | 978.5 | 207 | 7.3 | 95.6 | 22.3 | 25.2 | 7 | 12.45 | 2 | 10.8563 | 0.5 |
Mean: | 1043.4 | 127,604 | 7.248 | 195.29 | 22.81 | 25.45 | 6.411 | 37.61 | 11.154 | 11.196 | 0.9418 |
Q3: | 1690 | 1991 | 7.71 | 194.57 | 26.8 | 29 | 7.49 | 28 | 3.933 | 12.7569 | 0.5 |
Max.: | 2952 | 44,166,000 | 8.96 | 9501 | 37.7 | 50.3 | 10 | 1008 | 620 | 19.2105 | 39.2 |
Cor.Matrix | P | ||||||||||||
---|---|---|---|---|---|---|---|---|---|---|---|---|---|
pH | 1.00 | ||||||||||||
DQO | 0.15 | 1.00 | |||||||||||
DBO | 0.13 | 0.92 | 1.00 | ||||||||||
G&A | 0.10 | 0.50 | 0.54 | 1.00 | |||||||||
SAAM | 0.10 | 0.57 | 0.63 | 0.59 | 1.00 | ||||||||
OrtoP | 0.18 | 0.61 | 0.62 | 0.47 | 0.50 | 1.00 | |||||||
0.26 | 0.36 | 0.36 | 0.19 | 0.19 | 0.43 | 1.00 | |||||||
−0.04 | −0.10 | −0.09 | −0.19 | −0.17 | −0.07 | 0.00 | 1.00 | ||||||
SST | 0.16 | 0.45 | 0.40 | 0.28 | 0.07 | 0.19 | 0.36 | −0.18 | 1.00 | ||||
SSED | 0.14 | 0.45 | 0.42 | 0.30 | 0.20 | 0.34 | 0.36 | −0.13 | 0.63 | 1.00 | |||
NTK | 0.14 | 0.59 | 0.60 | 0.39 | 0.59 | 0.63 | 0.22 | −0.10 | 0.02 | 0.13 | 1.00 | ||
0.19 | 0.52 | 0.52 | 0.40 | 0.52 | 0.62 | 0.18 | −0.14 | 0.05 | 0.15 | 0.86 | 1.00 | ||
P | 0.16 | 0.61 | 0.62 | 0.48 | 0.54 | 0.76 | 0.20 | −0.11 | 0.15 | 0.25 | 0.71 | 0.69 | 1.00 |
P | ||||||||||||
---|---|---|---|---|---|---|---|---|---|---|---|---|
Min | 10.0 | 2.0 | 0.5 | 0.0 | 0.0 | 0.0 | 0.0012 | 3.4 | 0.1 | 2.4 | 0.1 | 0.0 |
Q1 | 98.0 | 27.7 | 10.0 | 0.7 | 0.6 | 1.0 | 0.0200 | 17.2 | 0.1 | 21.8 | 11.1 | 1.8 |
Median | 209.0 | 71.6 | 15.0 | 3.5 | 2.9 | 5.0 | 0.0200 | 37.0 | 0.2 | 43.6 | 26.5 | 3.9 |
Mean | 316.7 | 131.5 | 34.6 | 5.3 | 6.1 | 39.1 | 0.2849 | 82.9 | 1.2 | 62.4 | 37.9 | 5.1 |
Q3 | 447.2 | 195.0 | 40.0 | 7.8 | 8.8 | 44.6 | 0.0800 | 102.1 | 1.0 | 69.9 | 45.3 | 7.0 |
Max | 2290.0 | 968.0 | 311.0 | 27.6 | 46.3 | 464.0 | 10.8000 | 643.0 | 50.0 | 1198.0 | 374.3 | 83.6 |
Min | 12.0 | 2.0 | 1.1 | 0.1 | 0.0 | 0.0 | 0.0150 | 3.0 | 0.1 | 3.6 | 0.0 | 0.1 |
Q1 | 29.5 | 14.6 | 5.0 | 0.3 | 0.6 | 11.2 | 0.0200 | 15.0 | 0.1 | 52.6 | 32.6 | 1.1 |
Median | 354.0 | 162.0 | 10.5 | 1.1 | 14.5 | 40.3 | 0.0200 | 46.0 | 0.2 | 102.4 | 67.2 | 7.4 |
Mean | 655.3 | 303.7 | 25.9 | 3.2 | 27.0 | 63.6 | 4.4140 | 119.6 | 1.5 | 118.6 | 79.8 | 30.6 |
Q3 | 629.0 | 343.0 | 29.3 | 3.4 | 44.6 | 93.0 | 0.0200 | 131.0 | 1.7 | 177.5 | 115.8 | 19.1 |
Max | 3545.0 | 1769.0 | 120.4 | 41.1 | 98.7 | 299.0 | 139.0 | 635.0 | 15.0 | 350.3 | 229.0 | 643.0 |
Min | 10.0 | 2.0 | 1.2 | 0.1 | 0.0 | 0.1 | 0.02 | 3.0 | 0.1 | 2.5 | 2.5 | 0.1 |
Q1 | 12.0 | 2.0 | 5.0 | 0.1 | 0.2 | 4.8 | 0.02 | 34.0 | 0.1 | 5.0 | 5.0 | 0.1 |
Median | 24.8 | 3.6 | 5.0 | 0.1 | 0.2 | 11.7 | 0.027 | 88.5 | 0.1 | 5.0 | 5.0 | 0.2 |
Mean | 166.0 | 46.8 | 8.4 | 0.2 | 0.3 | 30.4 | 0.276 | 1290.0 | 5.9 | 6.7 | 5.4 | 0.6 |
Q3 | 171.2 | 38.4 | 10.0 | 0.1 | 0.2 | 25.6 | 0.118 | 248.2 | 1.0 | 5.0 | 5.0 | 0.4 |
Max | 2312.0 | 968.0 | 48.0 | 3.8 | 16.0 | 318.0 | 5.400 | 74202.0 | 400.0 | 48.8 | 43.8 | 7.4 |
Min | 10.0 | 1.0 | 0.1 | 0.1 | 0.0 | 0.1 | 0.002 | 6.0 | 0.1 | 0.4 | 0.3 | 0.1 |
Q1 | 25.0 | 3.4 | 6.3 | 0.1 | 0.0 | 1.2 | 0.020 | 18.6 | 0.1 | 5.0 | 5.0 | 0.3 |
Median | 167.0 | 38.0 | 10.0 | 0.3 | 0.2 | 5.0 | 0.020 | 51.7 | 0.1 | 10.7 | 5.0 | 1.2 |
Mean | 840.5 | 366.7 | 31.8 | 3.8 | 9.9 | 50.8 | 1.558 | 293.7 | 1.4 | 81.6 | 70.6 | 29.1 |
Q3 | 723.0 | 240.8 | 15.0 | 1.4 | 2.3 | 30.5 | 0.117 | 209.3 | 0.7 | 73.7 | 27.8 | 6.4 |
Max | 9975.0 | 4028.0 | 882.0 | 250.0 | 194.0 | 519.0 | 60.90 | 6079.0 | 22.5 | 1000.0 | 1000.0 | 2973.0 |
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Pérez Mesa, A.; Saldarriaga Molina, J.C.; Ríos, L.A.; Ocampo Echeverri, E.; Ocampo Echeverri, D. Diagnosis of Nutrient Discharges and Management Alternatives in Developing Countries and the Use of Microalgae as a Potential Solution: A Case Study from Different Provinces in Antioquia, Colombia. Water 2024, 16, 2215. https://doi.org/10.3390/w16162215
Pérez Mesa A, Saldarriaga Molina JC, Ríos LA, Ocampo Echeverri E, Ocampo Echeverri D. Diagnosis of Nutrient Discharges and Management Alternatives in Developing Countries and the Use of Microalgae as a Potential Solution: A Case Study from Different Provinces in Antioquia, Colombia. Water. 2024; 16(16):2215. https://doi.org/10.3390/w16162215
Chicago/Turabian StylePérez Mesa, Alejandro, Julio Cesar Saldarriaga Molina, Luis Alberto Ríos, Esteban Ocampo Echeverri, and David Ocampo Echeverri. 2024. "Diagnosis of Nutrient Discharges and Management Alternatives in Developing Countries and the Use of Microalgae as a Potential Solution: A Case Study from Different Provinces in Antioquia, Colombia" Water 16, no. 16: 2215. https://doi.org/10.3390/w16162215
APA StylePérez Mesa, A., Saldarriaga Molina, J. C., Ríos, L. A., Ocampo Echeverri, E., & Ocampo Echeverri, D. (2024). Diagnosis of Nutrient Discharges and Management Alternatives in Developing Countries and the Use of Microalgae as a Potential Solution: A Case Study from Different Provinces in Antioquia, Colombia. Water, 16(16), 2215. https://doi.org/10.3390/w16162215