Greenhouse gas dynamics in an urbanized river system: influence of water quality and land use.
Ecuador
Greenhouse gas
Land use type
Urban river
Water quality
Journal
Environmental science and pollution research international
ISSN: 1614-7499
Titre abrégé: Environ Sci Pollut Res Int
Pays: Germany
ID NLM: 9441769
Informations de publication
Date de publication:
May 2022
May 2022
Historique:
received:
22
06
2021
accepted:
08
12
2021
pubmed:
21
1
2022
medline:
18
5
2022
entrez:
20
1
2022
Statut:
ppublish
Résumé
Rivers act as a natural source of greenhouse gases (GHGs). However, anthropogenic activities can largely alter the chemical composition and microbial communities of rivers, consequently affecting their GHG production. To investigate these impacts, we assessed the accumulation of CO
Identifiants
pubmed: 35048344
doi: 10.1007/s11356-021-18081-2
pii: 10.1007/s11356-021-18081-2
doi:
Substances chimiques
Greenhouse Gases
0
Carbon Dioxide
142M471B3J
Nitrous Oxide
K50XQU1029
Methane
OP0UW79H66
Types de publication
Journal Article
Langues
eng
Sous-ensembles de citation
IM
Pagination
37277-37290Subventions
Organisme : fwo
ID : 1253921N
Informations de copyright
© 2021. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.
Références
Altman DG, Bland JM (2005) Statistics notes - standard deviations and standard errors. BMJ 331(7521):903–903
doi: 10.1136/bmj.331.7521.903
Bates D, Machler M, Bolker BM, Walker SC (2015) Fitting linear mixed-effects models using lme4. J Stat Softw 67(1):1–48
doi: 10.18637/jss.v067.i01
Beaulieu JJ et al (2011) Nitrous oxide emission from denitrification in stream and river networks. Proc Natl Acad Sci USA 108(1):214–219
doi: 10.1073/pnas.1011464108
Beaulieu, J.J., DelSontro, T. and Downing, J.A. (2019) Eutrophication will increase methane emissions from lakes and impoundments during the 21st century. Nature Communications 10
Bischl B et al (2016) mlr: machine learning in R. The Journal of Machine Learning Research 17(1):5938–5942
Borges AV et al (2015) Globally significant greenhouse-gas emissions from African inland waters. Nat Geosci 8(8):637
doi: 10.1038/ngeo2486
Borges AV et al (2019) Variations in dissolved greenhouse gases (CO2, CH4, N2O) in the Congo river network overwhelmingly driven by fluvial-wetland connectivity. Biogeosciences 16(19):3801–3834
doi: 10.5194/bg-16-3801-2019
Breiman L (2001) Random forests. Mach Learn 45(1):5–32
doi: 10.1023/A:1010933404324
Butman D, Raymond PA (2011) Significant efflux of carbon dioxide from streams and rivers in the United States. Nat Geosci 4(12):839–842
doi: 10.1038/ngeo1294
Castro-Barros, C.M., Ho, L.T., Winkler, M.K.H. and Volcke, E.I.P. (2017) Integration of methane removal in aerobic anammox-based granular sludge reactors. Environmental Technology, 1–11
Chang W et al (2015) Package ‘shiny’. http://citeseerx.ist.psu.edu/viewdoc/download
Cole JJ, Caraco NF (2001) Carbon in catchments: connecting terrestrial carbon losses with aquatic metabolism. Mar Freshw Res 52(1):101–110
doi: 10.1071/MF00084
Cude CG (2001) Oregon Water Quality Index: a tool for evaluating water quality management effectiveness. J Am Water Resour Assoc 37(1):125–137
doi: 10.1111/j.1752-1688.2001.tb05480.x
Daelman MR et al (2013) Methane and nitrous oxide emissions from municipal wastewater treatment - results from a long-term study. Water Sci Technol 67(10):2350–2355
doi: 10.2166/wst.2013.109
Damanik-Ambarita MN et al (2018) Impact assessment of local land use on ecological water quality of the Guayas river basin (Ecuador). Eco Inform 48:226–237
doi: 10.1016/j.ecoinf.2018.08.009
Davidson TA et al (2015) Eutrophication effects on greenhouse gas fluxes from shallow-lake mesocosms override those of climate warming. Glob Change Biol 21(12):4449–4463
doi: 10.1111/gcb.13062
Dormann CF et al (2007) Methods to account for spatial autocorrelation in the analysis of species distributional data: a review. Ecography 30(5):609–628
doi: 10.1111/j.2007.0906-7590.05171.x
Drake TW, Raymond PA, Spencer RGM (2018) Terrestrial carbon inputs to inland waters: a current synthesis of estimates and uncertainty. Limnology and Oceanography Letters 3(3):132–142
doi: 10.1002/lol2.10055
Dunnette, D. (1979) A geographically variable water quality index used in Oregon. Journal (Water Pollution Control Federation), 53–61
Fearnside, P.M. (2016) Greenhouse gas emissions from Brazil's Amazonian hydroelectric dams. Environmental Research Letters 11(1)
Forshay KJ, Stanley EH (2005) Rapid nitrate loss and denitrification in a temperate river floodplain. Biogeochemistry 75(1):43–64
doi: 10.1007/s10533-004-6016-4
Gallarotti N et al (2021) In-depth analysis of N2O fluxes in tropical forest soils of the Congo basin combining isotope and functional gene analysis. The ISME Journal
Gallo EL et al (2014) Physical and biological controls on trace gas fluxes in semi-arid urban ephemeral waterways. Biogeochemistry 121(1):189–207
doi: 10.1007/s10533-013-9927-0
Giri S, Qiu ZY (2016) Understanding the relationship of land uses and water quality in Twenty First Century: a review. J Environ Manage 173:41–48
doi: 10.1016/j.jenvman.2016.02.029
Goldenfum JA (2012) Challenges and solutions for assessing the impact of freshwater reservoirs on natural GHG emissions. Ecohydrol Hydrobiol 12(2):115–122
doi: 10.2478/v10104-012-0011-5
Gomez-Gener L et al (2021) Global carbon dioxide efflux from rivers enhanced by high nocturnal emissions. Nature Geoscience 14(5):289
doi: 10.1038/s41561-021-00722-3
Ho L et al (2018) A closer look on spatiotemporal variations of dissolved oxygen in waste stabilization ponds using mixed models. Water 10(2):201
doi: 10.3390/w10020201
Ho, L. and Goethals, P. (2020a) Municipal wastewater treatment with pond technology: historical review and future outlook. Ecological Engineering 148, 105791
Ho, L. and Goethals, P. (2020b) Research hotspots and current challenges of lakes and reservoirs: a bibliometric analysis. Scientometrics
Ho, T.K. (1995) Random decision forests. Proceedings of 3rd International Conference on Document Analysis and Recognition.
Ho L et al (2021a) Dissolved gas concentrations in Cuenca river systems (Ecuador) in 2018 ver 1. Initiative, E.D. (ed).
Ho L et al (2021b) Spatial and temporal variations of greenhouse gas emissions from a waste stabilization pond: effects of sludge distribution and accumulation. Water Research 193:116858
Hotchkiss ER et al (2015) Sources of and processes controlling CO2 emissions change with the size of streams and rivers. Nat Geosci 8:696
doi: 10.1038/ngeo2507
Hu MP, Chen DJ, Dahlgren RA (2016) Modeling nitrous oxide emission from rivers: a global assessment. Glob Change Biol 22(11):3566–3582
doi: 10.1111/gcb.13351
IPCC (2007) The physical science basis. Contribution of working group I to the Fourth Assessment Report of the Intergovernmental Panel on Climate Change 996
Janitza S, Celik E, Boulesteix AL (2018) A computationally fast variable importance test for random forests for high-dimensional data. Adv Data Anal Classif 12(4):885–915
doi: 10.1007/s11634-016-0276-4
Jerves-Cobo R et al (2018a) Biological impact assessment of sewage outfalls in the urbanized area of the Cuenca river basin (Ecuador) in two different seasons. Limnologica 71:8–28
doi: 10.1016/j.limno.2018.05.003
Jerves-Cobo, R., et al. (2018b) Model-based analysis of the potential of macroinvertebrates as indicators for microbial pathogens in rivers. Water 10(4)
Jerves-Cobo, R., et al. (2020) Biological water quality in tropical rivers during dry and rainy seasons: a model-based analysis. Ecological Indicators 108
Kampschreur MJ et al (2009) Nitrous oxide emission during wastewater treatment. Water Res 43(17):4093–4103
doi: 10.1016/j.watres.2009.03.001
Kaushal SS, McDowell WH, Wollheim WM (2014) Tracking evolution of urban biogeochemical cycles: past, present, and future. Biogeochemistry 121(1):1–21
doi: 10.1007/s10533-014-0014-y
Kling GW, Kipphut GW, Miller MC (1992) The flux of CO2 and CH4 from lakes and rivers in Arctic Alaska. Hydrobiologia 240(1–3):23–36
doi: 10.1007/BF00013449
Kroeze C, Dumont E, Seitzinger SP (2005) New estimates of global emissions of N2O from rivers and estuaries. Environ Sci 2(2–3):159–165
doi: 10.1080/15693430500384671
Li, Y., et al. (2021) The role of freshwater eutrophication in greenhouse gas emissions: a review. Science of the Total Environment 768
Lumb A, Sharma TC, Bibeault JF (2011) A review of genesis and evolution of water quality index (WQI) and some future directions. Water Qual Expo Health 3(1):11–24
doi: 10.1007/s12403-011-0040-0
Mannina G et al (2018) Greenhouse gas emissions from integrated urban drainage systems: where do we stand? J Hydrol 559:307–314
doi: 10.1016/j.jhydrol.2018.02.058
Meybeck M (1982) Carbon, nitrogen, and phosphorus transport by world rivers. Am J Sci 282(4):401–450
doi: 10.2475/ajs.282.4.401
Parsons, M., Thoms, M. and Norris, R. (2002) Australian river assessment system: AusRivAS physical assessment protocol. Monitoring river health initiative technical report 22
Prati L, Pavanello R, Pesarin F (1971) Assessment of surface water quality by a single index of pollution. Water Research 5(9):741
doi: 10.1016/0043-1354(71)90097-2
Probst P, Wright MN, Boulesteix A-L (2019) Hyperparameters and tuning strategies for random forest. Wiley Interdisciplinary Reviews: Data Mining and Knowledge Discovery 9(3):e1301
R Core Team (2014) R: A language and environment for statistical computing. ISBN 3–900051–07–0.
Rasanen, T.A., Varis, O., Scherer, L. and Kummu, M. (2018) Greenhouse gas emissions of hydropower in the Mekong river basin. Environmental Research Letters 13(3)
Raven PJ et al (1997) River habitat survey: a new system for classifying rivers according to their habitat quality. Freshwater Quality: Defining the Indefinable?, 215–234
Raymond PA et al (2013) Global carbon dioxide emissions from inland waters. Nature 503(7476):355–359
doi: 10.1038/nature12760
Rosamond MS, Thuss SJ, Schiff SL (2012) Dependence of riverine nitrous oxide emissions on dissolved oxygen levels. Nat Geosci 5(10):715–718
doi: 10.1038/ngeo1556
Saunois M et al (2020) The global methane budget 2000–2017. Earth Syst Sci Data 12(3):1561–1623
doi: 10.5194/essd-12-1561-2020
Schimel DS (1995) Terrestrial ecosystems and the carbon cycle. Glob Change Biol 1(1):77–91
doi: 10.1111/j.1365-2486.1995.tb00008.x
Schreiber, F., Wunderlin, P., Udert, K.M. and Wells, G.F. (2012) Nitric oxide and nitrous oxide turnover in natural and engineered microbial communities: biological pathways, chemical reactions, and novel technologies. Frontiers in Microbiology 3
Sener S, Sener E, Davraz A (2017) Evaluation of water quality using water quality index (WQI) method and GIS in Aksu River (SW-Turkey). Sci Total Environ 584:131–144
doi: 10.1016/j.scitotenv.2017.01.102
Smith RM et al (2017) Influence of infrastructure on water quality and greenhouse gas dynamics in urban streams. Biogeosciences 14(11):2831–2849
doi: 10.5194/bg-14-2831-2017
Stanley EH et al (2016) The ecology of methane in streams and rivers: patterns, controls, and global significance. Ecol Monogr 86(2):146–171
doi: 10.1890/15-1027
Stanley, E., et al. (2015) A global database of methane concentrations and atmospheric fluxes for streams and rivers.
Strobl, C., Boulesteix, A.L., Zeileis, A. and Hothorn, T. (2007) Bias in random forest variable importance measures: illustrations, sources and a solution. Bmc Bioinformatics 8
Sutadian, A.D., Muttil, N., Yilmaz, A.G. and Perera, B.J.C. (2016) Development of river water quality indices-a review. Environmental Monitoring and Assessment 188(1)
Tyagi S, Sharma B, Singh P, Dobhal R (2013) Water quality assessment in terms of water quality index. American Journal of Water Resources 1(3):34–38
doi: 10.12691/ajwr-1-3-3
Tyralis, H., Papacharalampous, G. and Langousis, A. (2019) A brief review of random forests for water scientists and practitioners and their recent history in water resources. Water 11(5)
Venterink HO, Hummelink E, Van den Hoorn MW (2003) Denitrification potential of a river floodplain during flooding with nitrate-rich water: grasslands versus reedbeds. Biogeochemistry 65(2):233–244
doi: 10.1023/A:1026098007360
Wang GQ et al (2021a) Distinctive patterns and controls of nitrous oxide concentrations and fluxes from urban inland waters. Environ Sci Technol 55(12):8422–8431
doi: 10.1021/acs.est.1c00647
Wang GQ et al (2021b) Intense methane ebullition from urban inland waters and its significant contribution to greenhouse gas emissions. Water Research 189
West, B.T., Welch, K.B. and Galecki, A.T. (2014) Linear mixed models: a practical guide using statistical software, CRC Press
Wojciechowski J, Hopkins AM, Upton RN (2015) Interactive pharmacometric applications using R and the shiny package. Cpt-Pharmacometrics & Systems Pharmacology 4(3):146–159
doi: 10.1002/psp4.21
Wright MN, Ziegler A (2017) Ranger: a fast implementation of random forests for high dimensional data in C plus plus and R. J Stat Softw 77(1):1–17
doi: 10.18637/jss.v077.i01
Yu L et al (2020) What can we learn from N2O isotope data? – Analytics, processes and modelling. Rapid Communications in Mass Spectrometry 34(20):e8858
doi: 10.1002/rcm.8858
Yu, C.H. and McCarl, B.A. (2018) The water implications of greenhouse gas mitigation: effects on land use, land use change, and forestry. Sustainability 10(7)
Zotou, I., Tsihrintzis, V.A. and Gikas, G.D. (2019) Performance of seven water quality indices (WQIs) in a Mediterranean river. Environmental Monitoring and Assessment 191(8)