@article{fdi:010072678,
  title = {{I}dentification of spikes associated with local sources in continuous time series of atmospheric {CO}, {CO}2 and {CH}4},
  author = {{E}l {Y}azidi, {A}. and {R}amonet, {M}. and {C}iais, {P}. and {B}roquet, {G}. and {P}ison, {I}. and {A}bbaris, {A}. and {B}runner, {D}. and {C}onil, {S}. and {D}elmotte, {M}. and {G}heusi, {F}. and {G}u{\'e}rin, {F}r{\'e}d{\'e}ric and {H}azan, {L}. and {K}achroudi, {N}. and {K}ouvarakis, {G}. and {M}ihalopoulos, {N}. and {R}ivier, {L}. and {S}erca, {D}.},
  editor = {},
  language = {{ENG}},
  abstract = {{T}his study deals with the problem of identifying atmospheric data influenced by local emissions that can result in spikes in time series of greenhouse gases and long-lived tracer measurements. {W}e considered three spike detection methods known as coefficient of variation ({COV}), robust extraction of baseline signal ({REBS}) and standard deviation of the background ({SD}) to detect and filter positive spikes in continuous greenhouse gas time series from four monitoring stations representative of the {E}uropean {ICOS} ({I}ntegrated {C}arbon {O}bservation {S}ystem) {R}esearch {I}nfrastructure network. {T}he results of the different methods are compared to each other and against a manual detection performed by station managers. {F}our stations were selected as test cases to apply the spike detection methods: a continental rural tower of 100 m height in eastern {F}rance ({OPE}), a high-mountain observatory in the south-west of {F}rance ({PDM}), a regional marine background site in {C}rete ({FKL}) and a marine cleanair background site in the {S}outhern {H}emisphere on {A}msterdam {I}sland ({AMS}). {T}his selection allows us to address spike detection problems in time series with different variability. {T}wo years of continuous measurements of {CO}2, {CH}4 and {CO} were analysed. {A}ll methods were found to be able to detect short-term spikes (lasting from a few seconds to a few minutes) in the time series. {A}nalysis of the results of each method leads us to exclude the {COV} method due to the requirement to arbitrarily specify an a priori percentage of rejected data in the time series, which may over-or underestimate the actual number of spikes. {T}he two other methods freely determine the number of spikes for a given set of parameters, and the values of these parameters were calibrated to provide the best match with spikes known to reflect local emissions episodes that are well documented by the station managers. {M}ore than 96% of the spikes manually identified by station managers were successfully detected both in the {SD} and the {REBS} methods after the best adjustment of parameter values. {A}t {PDM}, measurements made by two analyzers located 200 m from each other allow us to confirm that the {CH}4 spikes identified in one of the time series but not in the other correspond to a local source from a sewage treatment facility in one of the observatory buildings. {F}rom this experiment, we also found that the {REBS} method underestimates the number of positive anomalies in the {CH}4 data caused by local sewage emissions. {A}s a conclusion, we recommend the use of the {SD} method, which also appears to be the easiest one to implement in automatic data processing, used for the operational filtering of spikes in greenhouse gases time series at global and regional monitoring stations of networks like that of the {ICOS} atmosphere network.},
  keywords = {{FRANCE} ; {PYRENEES} ; {CRETE} ; {OCEAN} {INDIEN} ; {TAAF}},
  booktitle = {},
  journal = {{A}tmospheric {M}easurement {T}echniques},
  volume = {11},
  numero = {atmos 3},
  pages = {1599--1614},
  ISSN = {1867-1381},
  year = {2018},
  DOI = {10.5194/amt-11-1599-2018},
  URL = {https://www.documentation.ird.fr/hor/fdi:010072678},
}