Carbon and water footprints in Brazilian coffee plantations - the spatial and temporal distribution Article Swipe
Lima Deleon Martins
,
Fernando Coelho Eugênio
,
Wagner Nunes Rodrigues
,
Marcelo Antônio Tomaz
,
Alexandre Rosa dos Santos
,
José C. Ramalho
·
YOU?
·
· 2018
· Open Access
·
· DOI: https://doi.org/10.9755/ejfa.2018.v30.i6.1718
YOU?
·
· 2018
· Open Access
·
· DOI: https://doi.org/10.9755/ejfa.2018.v30.i6.1718
The future of many coffee growing regions, such as Brazil, depends on strategies to allow the minimization of the negative impacts of climate change. Still the own contribution of coffee cultivation for global warming is largely unknown. Water and carbon footprints are concepts that indicate the potential negative impact of a specific product, underlining which part of the process is the major responsible for it. In this context, the objective of this study was to quantify and spatialize the water and carbon footprints from coffee crop in different regions of Brazil, and to find the proportional weight of coffee production in the total emission of CO2 and water consumption in the context of Brazilian agriculture. For this end, water and carbon footprints were estimated and spatialized for Brazilian regions along 10 productive seasons (from 2004/2005 to 2014/2015), based on data of plantation area (ha) and coffee production (tons of beans). It is concluded that the estimates of annual carbon and water footprints were 19.791 million t CO2-equivalent and 49,284 million m3 of water, with higher values from the Southeast region. This corresponded to a moderate (ca. 5%) value for the emissions of greenhouse gases, but a relevant water footprint in the context of Brazilian agriculture
Related Topics
Concepts
Metadata
- Type
- article
- Language
- en
- Landing Page
- http://hdl.handle.net/10400.5/16048
- OA Status
- gold
- Cited By
- 18
- Related Works
- 20
- OpenAlex ID
- https://openalex.org/W2903671056
All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
-
https://openalex.org/W2903671056Canonical identifier for this work in OpenAlex
- DOI
-
https://doi.org/10.9755/ejfa.2018.v30.i6.1718Digital Object Identifier
- Title
-
Carbon and water footprints in Brazilian coffee plantations - the spatial and temporal distributionWork title
- Type
-
articleOpenAlex work type
- Language
-
enPrimary language
- Publication year
-
2018Year of publication
- Publication date
-
2018-07-06Full publication date if available
- Authors
-
Lima Deleon Martins, Fernando Coelho Eugênio, Wagner Nunes Rodrigues, Marcelo Antônio Tomaz, Alexandre Rosa dos Santos, José C. RamalhoList of authors in order
- Landing page
-
https://hdl.handle.net/10400.5/16048Publisher landing page
- Open access
-
YesWhether a free full text is available
- OA status
-
goldOpen access status per OpenAlex
- OA URL
-
https://hdl.handle.net/10400.5/16048Direct OA link when available
- Concepts
-
Spatial distribution, Distribution (mathematics), Environmental science, Carbon fibers, Agroforestry, Geography, Forestry, Mathematics, Remote sensing, Algorithm, Composite number, Mathematical analysisTop concepts (fields/topics) attached by OpenAlex
- Cited by
-
18Total citation count in OpenAlex
- Citations by year (recent)
-
2025: 1, 2024: 4, 2023: 3, 2022: 6, 2021: 2Per-year citation counts (last 5 years)
- Related works (count)
-
20Other works algorithmically related by OpenAlex
Full payload
| id | https://openalex.org/W2903671056 |
|---|---|
| doi | https://doi.org/10.9755/ejfa.2018.v30.i6.1718 |
| ids.mag | 2903671056 |
| ids.openalex | https://openalex.org/W2903671056 |
| fwci | 0.52882085 |
| type | article |
| title | Carbon and water footprints in Brazilian coffee plantations - the spatial and temporal distribution |
| biblio.issue | 6 |
| biblio.volume | 30 |
| biblio.last_page | 487 |
| biblio.first_page | 482 |
| topics[0].id | https://openalex.org/T12838 |
| topics[0].field.id | https://openalex.org/fields/23 |
| topics[0].field.display_name | Environmental Science |
| topics[0].score | 0.6794000267982483 |
| topics[0].domain.id | https://openalex.org/domains/3 |
| topics[0].domain.display_name | Physical Sciences |
| topics[0].subfield.id | https://openalex.org/subfields/2305 |
| topics[0].subfield.display_name | Environmental Engineering |
| topics[0].display_name | Photovoltaic Systems and Sustainability |
| is_xpac | False |
| apc_list | |
| apc_paid | |
| concepts[0].id | https://openalex.org/C2777016058 |
| concepts[0].level | 2 |
| concepts[0].score | 0.6677418351173401 |
| concepts[0].wikidata | https://www.wikidata.org/wiki/Q7574061 |
| concepts[0].display_name | Spatial distribution |
| concepts[1].id | https://openalex.org/C110121322 |
| concepts[1].level | 2 |
| concepts[1].score | 0.5661026239395142 |
| concepts[1].wikidata | https://www.wikidata.org/wiki/Q865811 |
| concepts[1].display_name | Distribution (mathematics) |
| concepts[2].id | https://openalex.org/C39432304 |
| concepts[2].level | 0 |
| concepts[2].score | 0.5443056225776672 |
| concepts[2].wikidata | https://www.wikidata.org/wiki/Q188847 |
| concepts[2].display_name | Environmental science |
| concepts[3].id | https://openalex.org/C140205800 |
| concepts[3].level | 3 |
| concepts[3].score | 0.5420194268226624 |
| concepts[3].wikidata | https://www.wikidata.org/wiki/Q5860 |
| concepts[3].display_name | Carbon fibers |
| concepts[4].id | https://openalex.org/C54286561 |
| concepts[4].level | 1 |
| concepts[4].score | 0.46913406252861023 |
| concepts[4].wikidata | https://www.wikidata.org/wiki/Q397350 |
| concepts[4].display_name | Agroforestry |
| concepts[5].id | https://openalex.org/C205649164 |
| concepts[5].level | 0 |
| concepts[5].score | 0.3811954855918884 |
| concepts[5].wikidata | https://www.wikidata.org/wiki/Q1071 |
| concepts[5].display_name | Geography |
| concepts[6].id | https://openalex.org/C97137747 |
| concepts[6].level | 1 |
| concepts[6].score | 0.32979273796081543 |
| concepts[6].wikidata | https://www.wikidata.org/wiki/Q38112 |
| concepts[6].display_name | Forestry |
| concepts[7].id | https://openalex.org/C33923547 |
| concepts[7].level | 0 |
| concepts[7].score | 0.15881642699241638 |
| concepts[7].wikidata | https://www.wikidata.org/wiki/Q395 |
| concepts[7].display_name | Mathematics |
| concepts[8].id | https://openalex.org/C62649853 |
| concepts[8].level | 1 |
| concepts[8].score | 0.12785550951957703 |
| concepts[8].wikidata | https://www.wikidata.org/wiki/Q199687 |
| concepts[8].display_name | Remote sensing |
| concepts[9].id | https://openalex.org/C11413529 |
| concepts[9].level | 1 |
| concepts[9].score | 0.0 |
| concepts[9].wikidata | https://www.wikidata.org/wiki/Q8366 |
| concepts[9].display_name | Algorithm |
| concepts[10].id | https://openalex.org/C104779481 |
| concepts[10].level | 2 |
| concepts[10].score | 0.0 |
| concepts[10].wikidata | https://www.wikidata.org/wiki/Q50707 |
| concepts[10].display_name | Composite number |
| concepts[11].id | https://openalex.org/C134306372 |
| concepts[11].level | 1 |
| concepts[11].score | 0.0 |
| concepts[11].wikidata | https://www.wikidata.org/wiki/Q7754 |
| concepts[11].display_name | Mathematical analysis |
| keywords[0].id | https://openalex.org/keywords/spatial-distribution |
| keywords[0].score | 0.6677418351173401 |
| keywords[0].display_name | Spatial distribution |
| keywords[1].id | https://openalex.org/keywords/distribution |
| keywords[1].score | 0.5661026239395142 |
| keywords[1].display_name | Distribution (mathematics) |
| keywords[2].id | https://openalex.org/keywords/environmental-science |
| keywords[2].score | 0.5443056225776672 |
| keywords[2].display_name | Environmental science |
| keywords[3].id | https://openalex.org/keywords/carbon-fibers |
| keywords[3].score | 0.5420194268226624 |
| keywords[3].display_name | Carbon fibers |
| keywords[4].id | https://openalex.org/keywords/agroforestry |
| keywords[4].score | 0.46913406252861023 |
| keywords[4].display_name | Agroforestry |
| keywords[5].id | https://openalex.org/keywords/geography |
| keywords[5].score | 0.3811954855918884 |
| keywords[5].display_name | Geography |
| keywords[6].id | https://openalex.org/keywords/forestry |
| keywords[6].score | 0.32979273796081543 |
| keywords[6].display_name | Forestry |
| keywords[7].id | https://openalex.org/keywords/mathematics |
| keywords[7].score | 0.15881642699241638 |
| keywords[7].display_name | Mathematics |
| keywords[8].id | https://openalex.org/keywords/remote-sensing |
| keywords[8].score | 0.12785550951957703 |
| keywords[8].display_name | Remote sensing |
| language | en |
| locations[0].id | pmh:oai:repositorio.ulisboa.pt:10400.5/16048 |
| locations[0].is_oa | True |
| locations[0].source | |
| locations[0].license | other-oa |
| locations[0].pdf_url | |
| locations[0].version | publishedVersion |
| locations[0].raw_type | info:eu-repo/semantics/article |
| locations[0].license_id | https://openalex.org/licenses/other-oa |
| locations[0].is_accepted | True |
| locations[0].is_published | True |
| locations[0].raw_source_name | |
| locations[0].landing_page_url | http://hdl.handle.net/10400.5/16048 |
| locations[1].id | mag:2903671056 |
| locations[1].is_oa | True |
| locations[1].source.id | https://openalex.org/S2764415477 |
| locations[1].source.issn | 2079-052X, 2079-0538 |
| locations[1].source.type | journal |
| locations[1].source.is_oa | True |
| locations[1].source.issn_l | 2079-052X |
| locations[1].source.is_core | True |
| locations[1].source.is_in_doaj | True |
| locations[1].source.display_name | Emirates Journal of Food and Agriculture |
| locations[1].source.host_organization | https://openalex.org/P4310319397 |
| locations[1].source.host_organization_name | United Arab Emirates University |
| locations[1].source.host_organization_lineage | https://openalex.org/P4310319397 |
| locations[1].license | cc-by |
| locations[1].pdf_url | |
| locations[1].version | |
| locations[1].raw_type | |
| locations[1].license_id | https://openalex.org/licenses/cc-by |
| locations[1].is_accepted | False |
| locations[1].is_published | |
| locations[1].raw_source_name | Emirates Journal of Food and Agriculture |
| locations[1].landing_page_url | https://www.cabdirect.org/cabdirect/abstract/20193359337 |
| authorships[0].author.id | https://openalex.org/A5064045515 |
| authorships[0].author.orcid | https://orcid.org/0000-0003-3921-8640 |
| authorships[0].author.display_name | Lima Deleon Martins |
| authorships[0].author_position | first |
| authorships[0].raw_author_name | L. D. Martins |
| authorships[0].is_corresponding | False |
| authorships[1].author.id | https://openalex.org/A5042858977 |
| authorships[1].author.orcid | https://orcid.org/0000-0002-1148-1167 |
| authorships[1].author.display_name | Fernando Coelho Eugênio |
| authorships[1].author_position | middle |
| authorships[1].raw_author_name | F. C. Eugenio |
| authorships[1].is_corresponding | False |
| authorships[2].author.id | https://openalex.org/A5031761820 |
| authorships[2].author.orcid | https://orcid.org/0000-0002-4830-0040 |
| authorships[2].author.display_name | Wagner Nunes Rodrigues |
| authorships[2].author_position | middle |
| authorships[2].raw_author_name | W. N. Rodrigues |
| authorships[2].is_corresponding | False |
| authorships[3].author.id | https://openalex.org/A5013142279 |
| authorships[3].author.orcid | https://orcid.org/0000-0002-9228-7541 |
| authorships[3].author.display_name | Marcelo Antônio Tomaz |
| authorships[3].author_position | middle |
| authorships[3].raw_author_name | M. A. Tomaz |
| authorships[3].is_corresponding | False |
| authorships[4].author.id | https://openalex.org/A5032091278 |
| authorships[4].author.orcid | https://orcid.org/0000-0003-2617-9451 |
| authorships[4].author.display_name | Alexandre Rosa dos Santos |
| authorships[4].author_position | middle |
| authorships[4].raw_author_name | A. R. dos Santos |
| authorships[4].is_corresponding | False |
| authorships[5].author.id | https://openalex.org/A5027138364 |
| authorships[5].author.orcid | https://orcid.org/0000-0002-7639-7214 |
| authorships[5].author.display_name | José C. Ramalho |
| authorships[5].author_position | last |
| authorships[5].raw_author_name | J. C. Ramalho |
| authorships[5].is_corresponding | False |
| has_content.pdf | False |
| has_content.grobid_xml | False |
| is_paratext | False |
| open_access.is_oa | True |
| open_access.oa_url | http://hdl.handle.net/10400.5/16048 |
| open_access.oa_status | gold |
| open_access.any_repository_has_fulltext | False |
| created_date | 2025-10-10T00:00:00 |
| display_name | Carbon and water footprints in Brazilian coffee plantations - the spatial and temporal distribution |
| has_fulltext | False |
| is_retracted | False |
| updated_date | 2025-10-10T17:16:08.811792 |
| primary_topic.id | https://openalex.org/T12838 |
| primary_topic.field.id | https://openalex.org/fields/23 |
| primary_topic.field.display_name | Environmental Science |
| primary_topic.score | 0.6794000267982483 |
| primary_topic.domain.id | https://openalex.org/domains/3 |
| primary_topic.domain.display_name | Physical Sciences |
| primary_topic.subfield.id | https://openalex.org/subfields/2305 |
| primary_topic.subfield.display_name | Environmental Engineering |
| primary_topic.display_name | Photovoltaic Systems and Sustainability |
| related_works | https://openalex.org/W2954888666, https://openalex.org/W2530813298, https://openalex.org/W1782164002, https://openalex.org/W3157080227, https://openalex.org/W2572227254, https://openalex.org/W3035241038, https://openalex.org/W332213718, https://openalex.org/W2982459434, https://openalex.org/W2798174035, https://openalex.org/W2995187434, https://openalex.org/W2607211349, https://openalex.org/W2787345616, https://openalex.org/W2082118357, https://openalex.org/W3149166408, https://openalex.org/W2560112848, https://openalex.org/W2149088583, https://openalex.org/W1972393189, https://openalex.org/W2625117367, https://openalex.org/W3007308323, https://openalex.org/W1435732094 |
| cited_by_count | 18 |
| counts_by_year[0].year | 2025 |
| counts_by_year[0].cited_by_count | 1 |
| counts_by_year[1].year | 2024 |
| counts_by_year[1].cited_by_count | 4 |
| counts_by_year[2].year | 2023 |
| counts_by_year[2].cited_by_count | 3 |
| counts_by_year[3].year | 2022 |
| counts_by_year[3].cited_by_count | 6 |
| counts_by_year[4].year | 2021 |
| counts_by_year[4].cited_by_count | 2 |
| counts_by_year[5].year | 2020 |
| counts_by_year[5].cited_by_count | 1 |
| counts_by_year[6].year | 2019 |
| counts_by_year[6].cited_by_count | 1 |
| locations_count | 2 |
| best_oa_location.id | pmh:oai:repositorio.ulisboa.pt:10400.5/16048 |
| best_oa_location.is_oa | True |
| best_oa_location.source | |
| best_oa_location.license | other-oa |
| best_oa_location.pdf_url | |
| best_oa_location.version | publishedVersion |
| best_oa_location.raw_type | info:eu-repo/semantics/article |
| best_oa_location.license_id | https://openalex.org/licenses/other-oa |
| best_oa_location.is_accepted | True |
| best_oa_location.is_published | True |
| best_oa_location.raw_source_name | |
| best_oa_location.landing_page_url | http://hdl.handle.net/10400.5/16048 |
| primary_location.id | pmh:oai:repositorio.ulisboa.pt:10400.5/16048 |
| primary_location.is_oa | True |
| primary_location.source | |
| primary_location.license | other-oa |
| primary_location.pdf_url | |
| primary_location.version | publishedVersion |
| primary_location.raw_type | info:eu-repo/semantics/article |
| primary_location.license_id | https://openalex.org/licenses/other-oa |
| primary_location.is_accepted | True |
| primary_location.is_published | True |
| primary_location.raw_source_name | |
| primary_location.landing_page_url | http://hdl.handle.net/10400.5/16048 |
| publication_date | 2018-07-06 |
| publication_year | 2018 |
| referenced_works_count | 0 |
| abstract_inverted_index.a | 50, 183, 195 |
| abstract_inverted_index.t | 165 |
| abstract_inverted_index.10 | 130 |
| abstract_inverted_index.In | 65 |
| abstract_inverted_index.It | 150 |
| abstract_inverted_index.as | 8 |
| abstract_inverted_index.in | 86, 100, 109, 199 |
| abstract_inverted_index.is | 34, 59, 151 |
| abstract_inverted_index.m3 | 170 |
| abstract_inverted_index.of | 2, 17, 21, 28, 49, 56, 70, 89, 97, 104, 112, 140, 148, 156, 171, 191, 202 |
| abstract_inverted_index.on | 11, 138 |
| abstract_inverted_index.to | 13, 74, 92, 135, 182 |
| abstract_inverted_index.5%) | 186 |
| abstract_inverted_index.CO2 | 105 |
| abstract_inverted_index.For | 115 |
| abstract_inverted_index.The | 0 |
| abstract_inverted_index.and | 38, 76, 80, 91, 106, 119, 124, 144, 159, 167 |
| abstract_inverted_index.are | 41 |
| abstract_inverted_index.but | 194 |
| abstract_inverted_index.for | 31, 63, 126, 188 |
| abstract_inverted_index.it. | 64 |
| abstract_inverted_index.own | 26 |
| abstract_inverted_index.the | 15, 18, 25, 45, 57, 60, 68, 78, 94, 101, 110, 154, 177, 189, 200 |
| abstract_inverted_index.was | 73 |
| abstract_inverted_index.(ca. | 185 |
| abstract_inverted_index.(ha) | 143 |
| abstract_inverted_index.This | 180 |
| abstract_inverted_index.area | 142 |
| abstract_inverted_index.crop | 85 |
| abstract_inverted_index.data | 139 |
| abstract_inverted_index.end, | 117 |
| abstract_inverted_index.find | 93 |
| abstract_inverted_index.from | 83, 176 |
| abstract_inverted_index.many | 3 |
| abstract_inverted_index.part | 55 |
| abstract_inverted_index.such | 7 |
| abstract_inverted_index.that | 43, 153 |
| abstract_inverted_index.this | 66, 71, 116 |
| abstract_inverted_index.were | 122, 162 |
| abstract_inverted_index.with | 173 |
| abstract_inverted_index.(from | 133 |
| abstract_inverted_index.(tons | 147 |
| abstract_inverted_index.Still | 24 |
| abstract_inverted_index.Water | 37 |
| abstract_inverted_index.allow | 14 |
| abstract_inverted_index.along | 129 |
| abstract_inverted_index.based | 137 |
| abstract_inverted_index.major | 61 |
| abstract_inverted_index.study | 72 |
| abstract_inverted_index.total | 102 |
| abstract_inverted_index.value | 187 |
| abstract_inverted_index.water | 79, 107, 118, 160, 197 |
| abstract_inverted_index.which | 54 |
| abstract_inverted_index.19.791 | 163 |
| abstract_inverted_index.49,284 | 168 |
| abstract_inverted_index.annual | 157 |
| abstract_inverted_index.carbon | 39, 81, 120, 158 |
| abstract_inverted_index.coffee | 4, 29, 84, 98, 145 |
| abstract_inverted_index.future | 1 |
| abstract_inverted_index.gases, | 193 |
| abstract_inverted_index.global | 32 |
| abstract_inverted_index.higher | 174 |
| abstract_inverted_index.impact | 48 |
| abstract_inverted_index.values | 175 |
| abstract_inverted_index.water, | 172 |
| abstract_inverted_index.weight | 96 |
| abstract_inverted_index.Brazil, | 9, 90 |
| abstract_inverted_index.beans). | 149 |
| abstract_inverted_index.change. | 23 |
| abstract_inverted_index.climate | 22 |
| abstract_inverted_index.context | 111, 201 |
| abstract_inverted_index.depends | 10 |
| abstract_inverted_index.growing | 5 |
| abstract_inverted_index.impacts | 20 |
| abstract_inverted_index.largely | 35 |
| abstract_inverted_index.million | 164, 169 |
| abstract_inverted_index.process | 58 |
| abstract_inverted_index.region. | 179 |
| abstract_inverted_index.regions | 88, 128 |
| abstract_inverted_index.seasons | 132 |
| abstract_inverted_index.warming | 33 |
| abstract_inverted_index.concepts | 42 |
| abstract_inverted_index.context, | 67 |
| abstract_inverted_index.emission | 103 |
| abstract_inverted_index.indicate | 44 |
| abstract_inverted_index.moderate | 184 |
| abstract_inverted_index.negative | 19, 47 |
| abstract_inverted_index.product, | 52 |
| abstract_inverted_index.quantify | 75 |
| abstract_inverted_index.regions, | 6 |
| abstract_inverted_index.relevant | 196 |
| abstract_inverted_index.specific | 51 |
| abstract_inverted_index.unknown. | 36 |
| abstract_inverted_index.2004/2005 | 134 |
| abstract_inverted_index.Brazilian | 113, 127, 203 |
| abstract_inverted_index.Southeast | 178 |
| abstract_inverted_index.concluded | 152 |
| abstract_inverted_index.different | 87 |
| abstract_inverted_index.emissions | 190 |
| abstract_inverted_index.estimated | 123 |
| abstract_inverted_index.estimates | 155 |
| abstract_inverted_index.footprint | 198 |
| abstract_inverted_index.objective | 69 |
| abstract_inverted_index.potential | 46 |
| abstract_inverted_index.footprints | 40, 82, 121, 161 |
| abstract_inverted_index.greenhouse | 192 |
| abstract_inverted_index.plantation | 141 |
| abstract_inverted_index.production | 99, 146 |
| abstract_inverted_index.productive | 131 |
| abstract_inverted_index.spatialize | 77 |
| abstract_inverted_index.strategies | 12 |
| abstract_inverted_index.2014/2015), | 136 |
| abstract_inverted_index.agriculture | 204 |
| abstract_inverted_index.consumption | 108 |
| abstract_inverted_index.cultivation | 30 |
| abstract_inverted_index.responsible | 62 |
| abstract_inverted_index.spatialized | 125 |
| abstract_inverted_index.underlining | 53 |
| abstract_inverted_index.agriculture. | 114 |
| abstract_inverted_index.contribution | 27 |
| abstract_inverted_index.corresponded | 181 |
| abstract_inverted_index.minimization | 16 |
| abstract_inverted_index.proportional | 95 |
| abstract_inverted_index.CO2-equivalent | 166 |
| cited_by_percentile_year.max | 98 |
| cited_by_percentile_year.min | 89 |
| countries_distinct_count | 0 |
| institutions_distinct_count | 6 |
| sustainable_development_goals[0].id | https://metadata.un.org/sdg/2 |
| sustainable_development_goals[0].score | 0.7200000286102295 |
| sustainable_development_goals[0].display_name | Zero hunger |
| citation_normalized_percentile.value | 0.65872564 |
| citation_normalized_percentile.is_in_top_1_percent | False |
| citation_normalized_percentile.is_in_top_10_percent | False |