STAT-IMM, a statistical approach to determine local and background contributions to PM<sub>10</sub> levels

Enke, W.; Kreienkamp, F.; Spekat, A.

doi:https://doi.org/10.5194/asr-2-119-2008

Articles | Volume 2, issue 1

https://doi.org/10.5194/asr-2-119-2008

© Author(s) 2008. This work is distributed under
the Creative Commons Attribution 3.0 License.

https://doi.org/10.5194/asr-2-119-2008

© Author(s) 2008. This work is distributed under
the Creative Commons Attribution 3.0 License.

Articles | Volume 2, issue 1

03 Jul 2008

| 03 Jul 2008

STAT-IMM, a statistical approach to determine local and background contributions to PM₁₀ levels

W. Enke, F. Kreienkamp, and A. Spekat

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Total article views: 1,833 (including HTML, PDF, and XML)

HTML	PDF	XML	Total	BibTeX	EndNote
797	892	144	1,833	139	129

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PDF: 892
XML: 144
Total: 1,833
BibTeX: 139
EndNote: 129

Views and downloads (calculated since 01 Feb 2013)

Month	HTML	PDF	XML	Total
Feb 2013	3	0	3
Mar 2013	1	7	1	9
Apr 2013	4	5	1	10
May 2013	7	0	7
Jun 2013	4	7	0	11
Jul 2013	2	9	1	12
Aug 2013	5	9	1	15
Sep 2013	1	9	0	10
Oct 2013	2	14	2	18
Nov 2013	2	16	0	18
Dec 2013	4	11	1	16
Jan 2014	5	15	4	24
Feb 2014	9	18	3	30
Mar 2014	12	11	3	26
Apr 2014	7	9	2	18
May 2014	1	13	2	16
Jun 2014	2	20	4	26
Jul 2014	4	15	1	20
Aug 2014	4	15	3	22
Sep 2014	3	26	1	30
Oct 2014	2	13	0	15
Nov 2014	3	13	1	17
Dec 2014	12	1	13
Jan 2015	2	19	1	22
Feb 2015	8	3	1	12
Mar 2015	6	14	6	26
Apr 2015	9	2	0	11
May 2015	1	5	1	7
Jun 2015	17	4	1	22
Jul 2015	16	1	0	17
Aug 2015	3	6	0	9
Sep 2015	3	6	1	10
Oct 2015	5	3	0	8
Nov 2015	9	3	0	12
Dec 2015	3	6	2	11
Jan 2016	8	7	0	15
Feb 2016	5	16	1	22
Mar 2016	6	2	0	8
Apr 2016	5	2	0	7
May 2016	4	6	1	11
Jun 2016	4	2	1	7
Jul 2016	6	2	2	10
Aug 2016	3	3	0	6
Sep 2016	4	2	1	7
Oct 2016	2	1	0	3
Nov 2016	3	2	0	5
Dec 2016	4	2	6
Jan 2017	5	2	0	7
Feb 2017	2	1	0	3
Mar 2017	9	4	1	14
Apr 2017	10	3	0	13
May 2017	11	6	0	17
Jun 2017	13	2	2	17
Jul 2017	7	5	1	13
Aug 2017	5	6	1	12
Sep 2017	3	4	0	7
Oct 2017	2	2	0	4
Nov 2017	3	2	0	5
Dec 2017	2	4	1	7
Jan 2018	3	4	0	7
Feb 2018	10	3	3	16
Mar 2018	7	3	1	11
Apr 2018	3	7	0	10
May 2018	8	5	0	13
Jun 2018	4	5	1	10
Jul 2018	4	3	1	8
Aug 2018	8	6	0	14
Sep 2018	6	7	0	13
Oct 2018	4	5	1	10
Nov 2018	6	7	0	13
Dec 2018	5	4	0	9
Jan 2019	3	5	0	8
Feb 2019	3	6	1	10
Mar 2019	3	4	0	7
Apr 2019	2	7	0	9
May 2019	5	4	0	9
Jun 2019	6	8	0	14
Jul 2019	4	2	0	6
Aug 2019	5	5	0	10
Sep 2019	1	5	0	6
Oct 2019	1	2	0	3
Nov 2019	2	8	2	12
Dec 2019	8	6	0	14
Jan 2020	5	3	0	8
Feb 2020	4	5	0	9
Mar 2020	1	6	0	7
Apr 2020	2	4	0	6
May 2020	5	4	0	9
Jun 2020	24	6	2	32
Jul 2020	41	39	31	111
Aug 2020	5	6	3	14
Sep 2020	8	4	0	12
Oct 2020	5	6	1	12
Nov 2020	7	11	0	18
Dec 2020	7	6	1	14
Jan 2021	6	10	0	16
Feb 2021	4	6	0	10
Mar 2021	8	7	2	17
Apr 2021	3	3	0	6
May 2021	11	6	2	19
Jun 2021	3	9	3	15
Jul 2021	6	0	6
Aug 2021	13	5	0	18
Sep 2021	1	5	1	7
Oct 2021	2	16	0	18
Nov 2021	2	13	0	15
Dec 2021	10	6	1	17
Jan 2022	7	6	0	13
Feb 2022	8	3	1	12
Mar 2022	5	5	0	10
Apr 2022	5	3	1	9
May 2022	4	5	1	10
Jun 2022	3	3	0	6
Jul 2022	3	7	2	12
Aug 2022	2	2	0	4
Sep 2022	4	3	0	7
Oct 2022	1	6	2	9
Nov 2022	3	7	0	10
Dec 2022	7	11	1	19
Jan 2023	3	8	0	11
Feb 2023	3	3	0	6
Mar 2023	9	4	0	13
Apr 2023	1	0	1
May 2023	6	6	1	13
Jun 2023	2	3	0	5
Jul 2023	3	3	0	6
Aug 2023	3	3	0	6
Sep 2023	1	10	0	11
Oct 2023	3	4	1	8
Nov 2023	1	3	0	4
Dec 2023	8	1	1	10
Jan 2024	2	1	0	3
Feb 2024	4	3	0	7
Mar 2024	6	0	6
Apr 2024	2	3	2	7
May 2024	3	5	2	10
Jun 2024	35	2	3	40
Jul 2024	12	2	4	18
Aug 2024	43	2	4	49
Sep 2024	14	0	14
Oct 2024	7	3	1	11
Nov 2024	4	5	0	9
Dec 2024	4	2	1	7

Cumulative views and downloads (calculated since 01 Feb 2013)

Month	HTML	PDF	XML	Total
Feb 2013	3	0	3
Mar 2013	1	7	1	9
Apr 2013	4	5	1	10
May 2013	7	0	7
Jun 2013	4	7	0	11
Jul 2013	2	9	1	12
Aug 2013	5	9	1	15
Sep 2013	1	9	0	10
Oct 2013	2	14	2	18
Nov 2013	2	16	0	18
Dec 2013	4	11	1	16
Jan 2014	5	15	4	24
Feb 2014	9	18	3	30
Mar 2014	12	11	3	26
Apr 2014	7	9	2	18
May 2014	1	13	2	16
Jun 2014	2	20	4	26
Jul 2014	4	15	1	20
Aug 2014	4	15	3	22
Sep 2014	3	26	1	30
Oct 2014	2	13	0	15
Nov 2014	3	13	1	17
Dec 2014	12	1	13
Jan 2015	2	19	1	22
Feb 2015	8	3	1	12
Mar 2015	6	14	6	26
Apr 2015	9	2	0	11
May 2015	1	5	1	7
Jun 2015	17	4	1	22
Jul 2015	16	1	0	17
Aug 2015	3	6	0	9
Sep 2015	3	6	1	10
Oct 2015	5	3	0	8
Nov 2015	9	3	0	12
Dec 2015	3	6	2	11
Jan 2016	8	7	0	15
Feb 2016	5	16	1	22
Mar 2016	6	2	0	8
Apr 2016	5	2	0	7
May 2016	4	6	1	11
Jun 2016	4	2	1	7
Jul 2016	6	2	2	10
Aug 2016	3	3	0	6
Sep 2016	4	2	1	7
Oct 2016	2	1	0	3
Nov 2016	3	2	0	5
Dec 2016	4	2	6
Jan 2017	5	2	0	7
Feb 2017	2	1	0	3
Mar 2017	9	4	1	14
Apr 2017	10	3	0	13
May 2017	11	6	0	17
Jun 2017	13	2	2	17
Jul 2017	7	5	1	13
Aug 2017	5	6	1	12
Sep 2017	3	4	0	7
Oct 2017	2	2	0	4
Nov 2017	3	2	0	5
Dec 2017	2	4	1	7
Jan 2018	3	4	0	7
Feb 2018	10	3	3	16
Mar 2018	7	3	1	11
Apr 2018	3	7	0	10
May 2018	8	5	0	13
Jun 2018	4	5	1	10
Jul 2018	4	3	1	8
Aug 2018	8	6	0	14
Sep 2018	6	7	0	13
Oct 2018	4	5	1	10
Nov 2018	6	7	0	13
Dec 2018	5	4	0	9
Jan 2019	3	5	0	8
Feb 2019	3	6	1	10
Mar 2019	3	4	0	7
Apr 2019	2	7	0	9
May 2019	5	4	0	9
Jun 2019	6	8	0	14
Jul 2019	4	2	0	6
Aug 2019	5	5	0	10
Sep 2019	1	5	0	6
Oct 2019	1	2	0	3
Nov 2019	2	8	2	12
Dec 2019	8	6	0	14
Jan 2020	5	3	0	8
Feb 2020	4	5	0	9
Mar 2020	1	6	0	7
Apr 2020	2	4	0	6
May 2020	5	4	0	9
Jun 2020	24	6	2	32
Jul 2020	41	39	31	111
Aug 2020	5	6	3	14
Sep 2020	8	4	0	12
Oct 2020	5	6	1	12
Nov 2020	7	11	0	18
Dec 2020	7	6	1	14
Jan 2021	6	10	0	16
Feb 2021	4	6	0	10
Mar 2021	8	7	2	17
Apr 2021	3	3	0	6
May 2021	11	6	2	19
Jun 2021	3	9	3	15
Jul 2021	6	0	6
Aug 2021	13	5	0	18
Sep 2021	1	5	1	7
Oct 2021	2	16	0	18
Nov 2021	2	13	0	15
Dec 2021	10	6	1	17
Jan 2022	7	6	0	13
Feb 2022	8	3	1	12
Mar 2022	5	5	0	10
Apr 2022	5	3	1	9
May 2022	4	5	1	10
Jun 2022	3	3	0	6
Jul 2022	3	7	2	12
Aug 2022	2	2	0	4
Sep 2022	4	3	0	7
Oct 2022	1	6	2	9
Nov 2022	3	7	0	10
Dec 2022	7	11	1	19
Jan 2023	3	8	0	11
Feb 2023	3	3	0	6
Mar 2023	9	4	0	13
Apr 2023	1	0	1
May 2023	6	6	1	13
Jun 2023	2	3	0	5
Jul 2023	3	3	0	6
Aug 2023	3	3	0	6
Sep 2023	1	10	0	11
Oct 2023	3	4	1	8
Nov 2023	1	3	0	4
Dec 2023	8	1	1	10
Jan 2024	2	1	0	3
Feb 2024	4	3	0	7
Mar 2024	6	0	6
Apr 2024	2	3	2	7
May 2024	3	5	2	10
Jun 2024	35	2	3	40
Jul 2024	12	2	4	18
Aug 2024	43	2	4	49
Sep 2024	14	0	14
Oct 2024	7	3	1	11
Nov 2024	4	5	0	9
Dec 2024	4	2	1	7

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Latest update: 26 Dec 2024

STAT-IMM, a statistical approach to determine local and background contributions to PM10 levels

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STAT-IMM, a statistical approach to determine local and background contributions to PM₁₀ levels