From fb2a41cacd9f4e0e60f52deeca97e9e6b120b51f Mon Sep 17 00:00:00 2001 From: romainsacchi Date: Tue, 20 Aug 2024 19:16:41 +0200 Subject: [PATCH 1/6] Align wrt master --- MANIFEST.in | 7 + dev/Untitled1.ipynb | 393 ++++++------ docs/transform.rst | 568 +++++++++--------- premise/__init__.py | 2 +- .../additional_inventories/lci-PV-GaAs.xlsx | Bin 27955 -> 28237 bytes premise/electricity.py | 120 ++-- tests/test_utils.py | 2 +- 7 files changed, 535 insertions(+), 557 deletions(-) diff --git a/MANIFEST.in b/MANIFEST.in index 8e516db8..f6bc07a6 100644 --- a/MANIFEST.in +++ b/MANIFEST.in @@ -31,6 +31,13 @@ include premise/data/metals/*.csv include premise/data/metals/*.yml include premise/data/metals/*.yaml include premise/data/transport/*.yaml +include premise/data/transport/*.csv +include premise/data/transport/bus/*.csv +include premise/data/transport/car/*.csv +include premise/data/transport/truck/*.csv +include premise/data/transport/two-wheeler/*.csv +include premise/data/battery/*.yaml +include premise/data/battery/*.csv include premise/data/GAINS_emission_factors/*.csv include premise/data/GAINS_emission_factors/*.yaml include premise/data/GAINS_emission_factors/iam_data/CLE/*.csv diff --git a/dev/Untitled1.ipynb b/dev/Untitled1.ipynb index ed5f77e5..3e9e9c73 100644 --- a/dev/Untitled1.ipynb +++ b/dev/Untitled1.ipynb @@ -124,207 +124,191 @@ "name": "stdout", "output_type": "stream", "text": [ - "photovoltaic facade installation, 3kWp, single-Si, laminated, integrated, at building 0.13591961170485328 0.27 0.20475 0.3\n", - "photovoltaic facade installation, 3kWp, single-Si, laminated, integrated, at building 0.1399972000559989 0.27 0.20475 0.3\n", - "photovoltaic slanted-roof installation, 3kWp, a-Si, panel, mounted, on roof 0.06449948400412797 [] [] []\n", - "photovoltaic slanted-roof installation, 3kWp, a-Si, panel, mounted, on roof 0.06262085825643492 [] [] []\n", - "photovoltaic slanted-roof installation, 3kWp, multi-Si, panel, 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"photovoltaic flat-roof installation, 3kWp, single-Si, on roof 0.19499512512187195 0.27 0.20475 0.3\n", - "photovoltaic flat-roof installation, 3kWp, single-Si, on roof 0.18932222642938282 0.27 0.20475 0.3\n", - "photovoltaic flat-roof installation, 3kWp, single-Si, on roof 0.19499512512187195 0.27 0.20475 0.3\n", - "photovoltaic flat-roof installation, 3kWp, single-Si, on roof 0.18932222642938282 0.27 0.20475 0.3\n", - "photovoltaic flat-roof installation, 3kWp, single-Si, on roof 0.19499512512187195 0.27 0.20475 0.3\n", - "photovoltaic flat-roof installation, 3kWp, single-Si, on roof 0.18932222642938282 0.27 0.20475 0.3\n", - "photovoltaic flat-roof installation, 3kWp, single-Si, on roof 0.19499512512187195 0.27 0.20475 0.3\n", - "photovoltaic flat-roof installation, 3kWp, single-Si, on roof 0.18932222642938282 0.27 0.20475 0.3\n", - "photovoltaic slanted-roof installation, 3kWp, CIS, panel, mounted, on roof 0.16 0.23 0.1755 0.2925\n", - "photovoltaic slanted-roof installation, 3kWp, CIS, panel, mounted, on roof 0.15534382767191382 0.23 0.1755 0.2925\n", - "photovoltaic slanted-roof installation, 3kWp, CdTe, laminated, integrated, on roof 0.17822135091783997 0.226 0.22 0.25\n", - "photovoltaic slanted-roof installation, 3kWp, CdTe, laminated, integrated, on roof 0.17999640007199855 0.226 0.22 0.25\n", - "photovoltaic slanted-roof installation, 3kWp, multi-Si, laminated, integrated, on roof 0.17475388827401409 0.24 0.183 0.3\n", - "photovoltaic slanted-roof installation, 3kWp, multi-Si, laminated, integrated, on roof 0.17999640007199855 0.24 0.183 0.3\n", - "photovoltaic slanted-roof installation, 3kWp, multi-Si, laminated, integrated, on roof 0.17475388827401409 0.24 0.183 0.3\n", - "photovoltaic slanted-roof installation, 3kWp, multi-Si, laminated, integrated, on roof 0.17999640007199855 0.24 0.183 0.3\n", - "photovoltaic slanted-roof installation, 3kWp, multi-Si, laminated, integrated, on roof 0.17475388827401409 0.24 0.183 0.3\n", - "photovoltaic slanted-roof installation, 3kWp, multi-Si, laminated, integrated, on roof 0.17999640007199855 0.24 0.183 0.3\n", - "photovoltaic slanted-roof installation, 3kWp, multi-Si, laminated, integrated, on roof 0.17475388827401409 0.24 0.183 0.3\n", - "photovoltaic slanted-roof installation, 3kWp, multi-Si, laminated, integrated, on roof 0.17999640007199855 0.24 0.183 0.3\n", - "photovoltaic slanted-roof installation, 3kWp, multi-Si, panel, mounted, on roof 0.17999640007199855 0.24 0.183 0.3\n", - "photovoltaic slanted-roof installation, 3kWp, multi-Si, panel, mounted, on roof 0.17475388827401409 0.24 0.183 0.3\n", - "photovoltaic slanted-roof installation, 3kWp, multi-Si, panel, mounted, on roof 0.17999640007199855 0.24 0.183 0.3\n", - "photovoltaic slanted-roof installation, 3kWp, multi-Si, panel, mounted, on roof 0.17475388827401409 0.24 0.183 0.3\n", - "photovoltaic slanted-roof installation, 3kWp, multi-Si, panel, mounted, on roof 0.17999640007199855 0.24 0.183 0.3\n", - "photovoltaic slanted-roof installation, 3kWp, multi-Si, panel, mounted, on roof 0.17475388827401409 0.24 0.183 0.3\n", - "photovoltaic slanted-roof installation, 3kWp, multi-Si, panel, mounted, on roof 0.17999640007199855 0.24 0.183 0.3\n", - "photovoltaic slanted-roof installation, 3kWp, multi-Si, panel, mounted, on roof 0.17475388827401409 0.24 0.183 0.3\n", - "photovoltaic slanted-roof installation, 3kWp, single-Si, laminated, integrated, on roof 0.18932222642938282 0.27 0.20475 0.3\n", - "photovoltaic slanted-roof installation, 3kWp, single-Si, laminated, integrated, on roof 0.19499512512187195 0.27 0.20475 0.3\n", - "photovoltaic slanted-roof installation, 3kWp, single-Si, laminated, integrated, on roof 0.18932222642938282 0.27 0.20475 0.3\n", - "photovoltaic slanted-roof installation, 3kWp, single-Si, laminated, integrated, on roof 0.19499512512187195 0.27 0.20475 0.3\n", - "photovoltaic slanted-roof installation, 3kWp, single-Si, laminated, integrated, on roof 0.18932222642938282 0.27 0.20475 0.3\n", - "photovoltaic slanted-roof installation, 3kWp, single-Si, laminated, integrated, on roof 0.19499512512187195 0.27 0.20475 0.3\n", - "photovoltaic slanted-roof installation, 3kWp, single-Si, laminated, integrated, on roof 0.18932222642938282 0.27 0.20475 0.3\n", - "photovoltaic slanted-roof installation, 3kWp, single-Si, laminated, integrated, on roof 0.19499512512187195 0.27 0.20475 0.3\n", - "photovoltaic slanted-roof installation, 3kWp, single-Si, panel, mounted, on roof 0.19499512512187195 0.27 0.20475 0.3\n", - "photovoltaic slanted-roof installation, 3kWp, single-Si, panel, mounted, on roof 0.18932222642938282 0.27 0.20475 0.3\n", - "photovoltaic slanted-roof installation, 3kWp, single-Si, panel, mounted, on roof 0.19499512512187195 0.27 0.20475 0.3\n", - "photovoltaic slanted-roof installation, 3kWp, single-Si, panel, mounted, on roof 0.18932222642938282 0.27 0.20475 0.3\n", - "photovoltaic slanted-roof installation, 3kWp, single-Si, panel, mounted, on roof 0.19499512512187195 0.27 0.20475 0.3\n", - "photovoltaic slanted-roof installation, 3kWp, single-Si, panel, mounted, on roof 0.18932222642938282 0.27 0.20475 0.3\n", - "photovoltaic slanted-roof installation, 3kWp, single-Si, panel, mounted, on roof 0.19499512512187195 0.27 0.20475 0.3\n", - "photovoltaic slanted-roof installation, 3kWp, single-Si, panel, mounted, on roof 0.18932222642938282 0.27 0.20475 0.3\n", - "photovoltaic installation, 0.28kWp, GaAs 0.013066405338559897 0.28 0.25 0.28\n", - "photovoltaic installation, 0.28kWp, GaAs 0.012686330478908976 0.28 0.25 0.28\n", - "photovoltaic panel installation, 0.5kWp, perovskite 0.25 0.252 0.22 0.3\n" + "photovoltaic facade installation, 3kWp, single-Si, laminated, integrated, at building single-Si 0.13591961170485328 0.27 0.20475 0.3\n", + "photovoltaic facade installation, 3kWp, single-Si, laminated, integrated, at building single-Si 0.1399972000559989 0.27 0.20475 0.3\n", + "photovoltaic slanted-roof installation, 3kWp, multi-Si, panel, mounted, on roof multi-Si 0.13163668275559456 0.24 0.183 0.3\n", + "photovoltaic slanted-roof installation, 3kWp, multi-Si, panel, mounted, on roof multi-Si 0.12780097128738177 0.24 0.183 0.3\n", + "photovoltaic flat-roof installation, 3kWp, single-Si, on roof single-Si 0.1399972000559989 0.27 0.20475 0.3\n", + "photovoltaic flat-roof installation, 3kWp, single-Si, on roof single-Si 0.13592496941688187 0.27 0.20475 0.3\n", + "photovoltaic facade installation, 3kWp, single-Si, panel, mounted, at building single-Si 0.1399972000559989 0.27 0.20475 0.3\n", + "photovoltaic facade installation, 3kWp, single-Si, panel, mounted, at building single-Si 0.13591961170485328 0.27 0.20475 0.3\n", + "photovoltaic slanted-roof installation, 3kWp, single-Si, laminated, integrated, on roof single-Si 0.13591961170485328 0.27 0.20475 0.3\n", + "photovoltaic slanted-roof installation, 3kWp, single-Si, laminated, integrated, on roof single-Si 0.1399972000559989 0.27 0.20475 0.3\n", + "photovoltaic facade installation, 3kWp, multi-Si, laminated, integrated, at building multi-Si 0.12780097128738177 0.24 0.183 0.3\n", + "photovoltaic facade installation, 3kWp, multi-Si, laminated, integrated, at building multi-Si 0.13163668275559456 0.24 0.183 0.3\n", + "photovoltaic facade installation, 3kWp, multi-Si, panel, mounted, at building multi-Si 0.13163668275559456 0.24 0.183 0.3\n", + "photovoltaic facade installation, 3kWp, multi-Si, panel, mounted, at building multi-Si 0.12780097128738177 0.24 0.183 0.3\n", + "photovoltaic slanted-roof installation, 3kWp, multi-Si, panel, mounted, on roof multi-Si 0.13163668275559456 0.24 0.183 0.3\n", + "photovoltaic slanted-roof installation, 3kWp, multi-Si, panel, mounted, on roof multi-Si 0.1278026046170821 0.24 0.183 0.3\n", + "photovoltaic flat-roof installation, 3kWp, multi-Si, on roof multi-Si 0.13163668275559456 0.24 0.183 0.3\n", + "photovoltaic flat-roof installation, 3kWp, multi-Si, on roof multi-Si 0.12780097128738177 0.24 0.183 0.3\n", + "photovoltaic slanted-roof installation, 3kWp, single-Si, laminated, integrated, on roof single-Si 0.13592496941688187 0.27 0.20475 0.3\n", + "photovoltaic slanted-roof installation, 3kWp, single-Si, laminated, integrated, on roof single-Si 0.1399972000559989 0.27 0.20475 0.3\n", + "photovoltaic slanted-roof installation, 3kWp, CIS, panel, mounted, on roof CIS 0.1068452168957903 0.23 0.1755 0.2925\n", + "photovoltaic slanted-roof installation, 3kWp, CIS, panel, mounted, on roof CIS 0.10373085301338128 0.23 0.1755 0.2925\n", + "photovoltaic slanted-roof installation, 3kWp, single-Si, panel, mounted, on roof single-Si 0.1399972000559989 0.27 0.20475 0.3\n", + "photovoltaic slanted-roof installation, 3kWp, single-Si, panel, mounted, on roof single-Si 0.13592496941688187 0.27 0.20475 0.3\n", + "photovoltaic slanted-roof installation, 3kWp, multi-Si, laminated, integrated, on roof multi-Si 0.1278026046170821 0.24 0.183 0.3\n", + "photovoltaic slanted-roof installation, 3kWp, multi-Si, laminated, integrated, on roof multi-Si 0.13163668275559456 0.24 0.183 0.3\n", + "photovoltaic plant construction, 570kWp, multi-Si, on open ground multi-Si 0.13338013338013338 0.24 0.183 0.3\n", + "photovoltaic plant construction, 570kWp, multi-Si, on open ground multi-Si 0.1294952751263431 0.24 0.183 0.3\n", + "photovoltaic slanted-roof installation, 3kWp, CIS, panel, mounted, on roof CIS 0.1068452168957903 0.23 0.1755 0.2925\n", + "photovoltaic slanted-roof installation, 3kWp, CIS, panel, mounted, on roof CIS 0.10373322028717505 0.23 0.1755 0.2925\n", + "photovoltaic facade installation, 3kWp, multi-Si, panel, mounted, at building multi-Si 0.13163668275559456 0.24 0.183 0.3\n", + "photovoltaic facade installation, 3kWp, multi-Si, panel, mounted, at building multi-Si 0.1278026046170821 0.24 0.183 0.3\n", + "photovoltaic flat-roof installation, 3kWp, single-Si, on roof single-Si 0.1399972000559989 0.27 0.20475 0.3\n", + "photovoltaic flat-roof installation, 3kWp, single-Si, on roof single-Si 0.13591961170485328 0.27 0.20475 0.3\n", + "photovoltaic facade installation, 3kWp, single-Si, laminated, integrated, at building single-Si 0.13592496941688187 0.27 0.20475 0.3\n", + "photovoltaic facade installation, 3kWp, single-Si, laminated, integrated, at building single-Si 0.1399972000559989 0.27 0.20475 0.3\n", + "photovoltaic slanted-roof installation, 3kWp, single-Si, panel, mounted, on roof single-Si 0.1399972000559989 0.27 0.20475 0.3\n", + "photovoltaic slanted-roof installation, 3kWp, single-Si, panel, mounted, on roof single-Si 0.13591961170485328 0.27 0.20475 0.3\n", + "photovoltaic slanted-roof installation, 3kWp, multi-Si, laminated, integrated, on roof multi-Si 0.12780097128738177 0.24 0.183 0.3\n", + "photovoltaic slanted-roof installation, 3kWp, multi-Si, laminated, integrated, on roof multi-Si 0.13163668275559456 0.24 0.183 0.3\n", + "photovoltaic facade installation, 3kWp, multi-Si, laminated, integrated, at building multi-Si 0.1278026046170821 0.24 0.183 0.3\n", + "photovoltaic facade installation, 3kWp, multi-Si, laminated, integrated, at building multi-Si 0.13163668275559456 0.24 0.183 0.3\n", + "photovoltaic facade installation, 3kWp, single-Si, panel, mounted, at building single-Si 0.1399972000559989 0.27 0.20475 0.3\n", + "photovoltaic facade installation, 3kWp, single-Si, panel, mounted, at building single-Si 0.13592496941688187 0.27 0.20475 0.3\n", + "photovoltaic slanted-roof installation, 3kWp, CdTe, laminated, integrated, on roof CdTe 0.08737948912125361 0.226 0.22 0.25\n", + "photovoltaic slanted-roof installation, 3kWp, CdTe, laminated, integrated, on roof CdTe 0.0900009000090001 0.226 0.22 0.25\n", + "photovoltaic flat-roof installation, 3kWp, multi-Si, on roof multi-Si 0.13163668275559456 0.24 0.183 0.3\n", + "photovoltaic flat-roof installation, 3kWp, multi-Si, on roof multi-Si 0.1278026046170821 0.24 0.183 0.3\n", + "photovoltaic slanted-roof installation, 3kWp, CdTe, laminated, integrated, on roof CdTe 0.1059135039717564 0.226 0.22 0.25\n", + "photovoltaic slanted-roof installation, 3kWp, CdTe, laminated, integrated, on roof CdTe 0.10909090909090909 0.226 0.22 0.25\n", + "photovoltaic slanted-roof installation, 1.3 MWp, multi-Si, panel, mounted, on roof multi-Si 0.1747570205272285 0.24 0.183 0.3\n", + "photovoltaic flat-roof installation, 156 kWp, multi-Si, on roof multi-Si 0.1799993076949704 0.24 0.183 0.3\n", + "photovoltaic flat-roof installation, 156 kWp, multi-Si, on roof multi-Si 0.1747566289894362 0.24 0.183 0.3\n", + "photovoltaic flat-roof installation, 156 kWp, single-Si, on roof single-Si 0.195 0.27 0.20475 0.3\n", + "photovoltaic flat-roof installation, 156 kWp, single-Si, on roof single-Si 0.18932038834951456 0.27 0.20475 0.3\n", + "photovoltaic flat-roof installation, 280 kWp, multi-Si, on roof multi-Si 0.17999485728979173 0.24 0.183 0.3\n", + "photovoltaic flat-roof installation, 280 kWp, multi-Si, on roof multi-Si 0.17475970540506802 0.24 0.183 0.3\n", + "photovoltaic flat-roof installation, 280 kWp, single-Si, on roof single-Si 0.19499965178633608 0.27 0.20475 0.3\n", + "photovoltaic flat-roof installation, 280 kWp, single-Si, on roof single-Si 0.18931710615280595 0.27 0.20475 0.3\n", + "photovoltaic flat-roof installation, 324 kWp, multi-Si, on roof multi-Si 0.18 0.24 0.183 0.3\n", + "photovoltaic flat-roof installation, 324 kWp, multi-Si, on roof multi-Si 0.17475728155339806 0.24 0.183 0.3\n", + "photovoltaic slanted-roof installation, 3 kWp, CIS, laminated, integrated, on roof CIS 0.15534382767191382 0.23 0.1755 0.2925\n", + "photovoltaic slanted-roof installation, 3 kWp, CIS, laminated, integrated, on roof CIS 0.16 0.23 0.1755 0.2925\n", + "photovoltaic slanted-roof installation, 3 kWp, CIS, laminated, integrated, on roof CIS 0.15534382767191382 0.23 0.1755 0.2925\n", + "photovoltaic slanted-roof installation, 3 kWp, CIS, laminated, integrated, on roof CIS 0.16 0.23 0.1755 0.2925\n", + "photovoltaic slanted-roof installation, 3 kWp, CdTe, panel, mounted, on roof CdTe 0.17822135091783997 0.226 0.22 0.25\n", + "photovoltaic slanted-roof installation, 3 kWp, CdTe, panel, mounted, on roof CdTe 0.17999640007199855 0.226 0.22 0.25\n", + "photovoltaic slanted-roof installation, 3 kWp, CdTe, panel, mounted, on roof CdTe 0.17822135091783997 0.226 0.22 0.25\n", + "photovoltaic slanted-roof installation, 3 kWp, CdTe, panel, mounted, on roof CdTe 0.17999640007199855 0.226 0.22 0.25\n", + "photovoltaic slanted-roof installation, 3 kWp, micro-Si, laminated, integrated, on roof micro-Si 0.0970873786407767 0.13 0.1 0.15625\n", + "photovoltaic slanted-roof installation, 3 kWp, micro-Si, laminated, integrated, on roof micro-Si 0.1 0.13 0.1 0.15625\n", + "photovoltaic slanted-roof installation, 3 kWp, micro-Si, panel, mounted, on roof micro-Si 0.1 0.13 0.1 0.15625\n", + "photovoltaic slanted-roof installation, 3 kWp, micro-Si, panel, mounted, on roof micro-Si 0.0970873786407767 0.13 0.1 0.15625\n", + "photovoltaic flat-roof installation, 450 kWp, single-Si, on roof single-Si 0.19499935000216667 0.27 0.20475 0.3\n", + "photovoltaic flat-roof installation, 450 kWp, single-Si, on roof single-Si 0.1893222264293828 0.27 0.20475 0.3\n", + "photovoltaic open ground installation, 560 kWp, single-Si, on open ground single-Si 0.1893235065418033 0.27 0.20475 0.3\n", + "photovoltaic open ground installation, 569 kWp, multi-Si, on open ground multi-Si 0.17475966706594181 0.24 0.183 0.3\n", + "photovoltaic open ground installation, 570 kWp, CIS, on open ground CIS 0.1553387474791519 0.23 0.1755 0.2925\n", + "photovoltaic open ground installation, 570 kWp, CdTe, on open ground CdTe 0.17821967920457743 0.226 0.22 0.25\n", + "photovoltaic open ground installation, 570 kWp, micro-Si, on open ground micro-Si 0.0970873786407767 0.13 0.1 0.15625\n", + "photovoltaic open ground installation, 570 kWp, multi-Si, on open ground multi-Si 0.17475549560045375 0.24 0.183 0.3\n", + "photovoltaic open ground installation, 570 kWp, multi-Si, on open ground multi-Si 0.17475549560045375 0.24 0.183 0.3\n", + "photovoltaic open ground installation, 570 kWp, single-Si, on open ground single-Si 0.1893184535671582 0.27 0.20475 0.3\n", + "photovoltaic slanted-roof installation, 93 kWp, multi-Si, laminated, integrated, on roof multi-Si 0.17475618693274708 0.24 0.183 0.3\n", + "photovoltaic slanted-roof installation, 93 kWp, multi-Si, laminated, integrated, on roof multi-Si 0.17999883871716957 0.24 0.183 0.3\n", + "photovoltaic slanted-roof installation, 93 kWp, multi-Si, panel, mounted, on roof multi-Si 0.17999883871716957 0.24 0.183 0.3\n", + "photovoltaic slanted-roof installation, 93 kWp, multi-Si, panel, mounted, on roof multi-Si 0.17475618693274708 0.24 0.183 0.3\n", + "photovoltaic slanted-roof installation, 93 kWp, single-Si, laminated, integrated, on roof single-Si 0.18932068481159536 0.27 0.20475 0.3\n", + "photovoltaic slanted-roof installation, 93 kWp, single-Si, laminated, integrated, on roof single-Si 0.19500125807263272 0.27 0.20475 0.3\n", + "photovoltaic slanted-roof installation, 93 kWp, single-Si, panel, mounted, on roof single-Si 0.19500125807263272 0.27 0.20475 0.3\n", + "photovoltaic slanted-roof installation, 93 kWp, single-Si, panel, mounted, on roof single-Si 0.18932068481159536 0.27 0.20475 0.3\n", + "photovoltaic facade installation, 3kWp, multi-Si, laminated, integrated, at building multi-Si 0.17475388827401409 0.24 0.183 0.3\n", + "photovoltaic facade installation, 3kWp, multi-Si, laminated, integrated, at building multi-Si 0.17999640007199855 0.24 0.183 0.3\n", + "photovoltaic facade installation, 3kWp, multi-Si, laminated, integrated, at building multi-Si 0.17475388827401409 0.24 0.183 0.3\n", + "photovoltaic facade installation, 3kWp, multi-Si, laminated, integrated, at building multi-Si 0.17999640007199855 0.24 0.183 0.3\n", + "photovoltaic facade installation, 3kWp, multi-Si, laminated, integrated, at building multi-Si 0.17475388827401409 0.24 0.183 0.3\n", + "photovoltaic facade installation, 3kWp, multi-Si, laminated, integrated, at building multi-Si 0.17999640007199855 0.24 0.183 0.3\n", + "photovoltaic facade installation, 3kWp, multi-Si, laminated, integrated, at building multi-Si 0.17475388827401409 0.24 0.183 0.3\n", + "photovoltaic facade installation, 3kWp, multi-Si, laminated, integrated, at building multi-Si 0.17999640007199855 0.24 0.183 0.3\n", + "photovoltaic facade installation, 3kWp, multi-Si, panel, mounted, at building multi-Si 0.17999640007199855 0.24 0.183 0.3\n", + "photovoltaic facade installation, 3kWp, multi-Si, panel, mounted, at building multi-Si 0.17475388827401409 0.24 0.183 0.3\n", + "photovoltaic facade installation, 3kWp, multi-Si, panel, mounted, at building multi-Si 0.17999640007199855 0.24 0.183 0.3\n", + "photovoltaic facade installation, 3kWp, multi-Si, panel, mounted, at building multi-Si 0.17475388827401409 0.24 0.183 0.3\n", + "photovoltaic facade installation, 3kWp, multi-Si, panel, mounted, at building multi-Si 0.17999640007199855 0.24 0.183 0.3\n", + "photovoltaic facade installation, 3kWp, multi-Si, panel, mounted, at building multi-Si 0.17475388827401409 0.24 0.183 0.3\n", + "photovoltaic facade installation, 3kWp, multi-Si, panel, mounted, at building multi-Si 0.17999640007199855 0.24 0.183 0.3\n", + "photovoltaic facade installation, 3kWp, multi-Si, panel, mounted, at building multi-Si 0.17475388827401409 0.24 0.183 0.3\n", + "photovoltaic facade installation, 3kWp, single-Si, laminated, integrated, at building single-Si 0.18932222642938282 0.27 0.20475 0.3\n", + "photovoltaic facade installation, 3kWp, single-Si, laminated, integrated, at building single-Si 0.19499512512187195 0.27 0.20475 0.3\n", + "photovoltaic facade installation, 3kWp, single-Si, laminated, integrated, at building single-Si 0.18932222642938282 0.27 0.20475 0.3\n", + "photovoltaic facade installation, 3kWp, single-Si, laminated, integrated, at building single-Si 0.19499512512187195 0.27 0.20475 0.3\n", + "photovoltaic facade installation, 3kWp, single-Si, laminated, integrated, at building single-Si 0.18932222642938282 0.27 0.20475 0.3\n", + "photovoltaic facade installation, 3kWp, single-Si, laminated, integrated, at building single-Si 0.19499512512187195 0.27 0.20475 0.3\n", + "photovoltaic facade installation, 3kWp, single-Si, laminated, integrated, at building single-Si 0.18932222642938282 0.27 0.20475 0.3\n", + "photovoltaic facade installation, 3kWp, single-Si, laminated, integrated, at building single-Si 0.19499512512187195 0.27 0.20475 0.3\n", + "photovoltaic facade installation, 3kWp, single-Si, panel, mounted, at building single-Si 0.19499512512187195 0.27 0.20475 0.3\n", + "photovoltaic facade installation, 3kWp, single-Si, panel, mounted, at building single-Si 0.18932222642938282 0.27 0.20475 0.3\n", + "photovoltaic facade installation, 3kWp, single-Si, panel, mounted, at building single-Si 0.19499512512187195 0.27 0.20475 0.3\n", + "photovoltaic facade installation, 3kWp, single-Si, panel, mounted, at building single-Si 0.18932222642938282 0.27 0.20475 0.3\n", + "photovoltaic facade installation, 3kWp, single-Si, panel, mounted, at building single-Si 0.19499512512187195 0.27 0.20475 0.3\n", + "photovoltaic facade installation, 3kWp, single-Si, panel, mounted, at building single-Si 0.18932222642938282 0.27 0.20475 0.3\n", + "photovoltaic facade installation, 3kWp, single-Si, panel, mounted, at building single-Si 0.19499512512187195 0.27 0.20475 0.3\n", + "photovoltaic facade installation, 3kWp, single-Si, panel, mounted, at building single-Si 0.18932222642938282 0.27 0.20475 0.3\n", + "photovoltaic flat-roof installation, 3kWp, multi-Si, on roof multi-Si 0.17999640007199855 0.24 0.183 0.3\n", + "photovoltaic flat-roof installation, 3kWp, multi-Si, on roof multi-Si 0.17475388827401409 0.24 0.183 0.3\n", + "photovoltaic flat-roof installation, 3kWp, multi-Si, on roof multi-Si 0.17999640007199855 0.24 0.183 0.3\n", + "photovoltaic flat-roof installation, 3kWp, multi-Si, on roof multi-Si 0.17475388827401409 0.24 0.183 0.3\n", + "photovoltaic flat-roof installation, 3kWp, multi-Si, on roof multi-Si 0.17999640007199855 0.24 0.183 0.3\n", + "photovoltaic flat-roof installation, 3kWp, multi-Si, on roof multi-Si 0.17475388827401409 0.24 0.183 0.3\n", + "photovoltaic flat-roof installation, 3kWp, multi-Si, on roof multi-Si 0.17999640007199855 0.24 0.183 0.3\n", + "photovoltaic flat-roof installation, 3kWp, multi-Si, on roof multi-Si 0.17475388827401409 0.24 0.183 0.3\n", + "photovoltaic flat-roof installation, 3kWp, single-Si, on roof single-Si 0.19499512512187195 0.27 0.20475 0.3\n", + "photovoltaic flat-roof installation, 3kWp, single-Si, on roof single-Si 0.18932222642938282 0.27 0.20475 0.3\n", + "photovoltaic flat-roof installation, 3kWp, single-Si, on roof single-Si 0.19499512512187195 0.27 0.20475 0.3\n", + "photovoltaic flat-roof installation, 3kWp, single-Si, on roof single-Si 0.18932222642938282 0.27 0.20475 0.3\n", + "photovoltaic flat-roof installation, 3kWp, single-Si, on roof single-Si 0.19499512512187195 0.27 0.20475 0.3\n", + "photovoltaic flat-roof installation, 3kWp, single-Si, on roof single-Si 0.18932222642938282 0.27 0.20475 0.3\n", + "photovoltaic flat-roof installation, 3kWp, single-Si, on roof single-Si 0.19499512512187195 0.27 0.20475 0.3\n", + "photovoltaic flat-roof installation, 3kWp, single-Si, on roof single-Si 0.18932222642938282 0.27 0.20475 0.3\n", + "photovoltaic slanted-roof installation, 3kWp, CIS, panel, mounted, on roof CIS 0.16 0.23 0.1755 0.2925\n", + "photovoltaic slanted-roof installation, 3kWp, CIS, panel, mounted, on roof CIS 0.15534382767191382 0.23 0.1755 0.2925\n", + "photovoltaic slanted-roof installation, 3kWp, CdTe, laminated, integrated, on roof CdTe 0.17822135091783997 0.226 0.22 0.25\n", + "photovoltaic slanted-roof installation, 3kWp, CdTe, laminated, integrated, on roof CdTe 0.17999640007199855 0.226 0.22 0.25\n", + "photovoltaic slanted-roof installation, 3kWp, multi-Si, laminated, integrated, on roof multi-Si 0.17475388827401409 0.24 0.183 0.3\n", + "photovoltaic slanted-roof installation, 3kWp, multi-Si, laminated, integrated, on roof multi-Si 0.17999640007199855 0.24 0.183 0.3\n", + "photovoltaic slanted-roof installation, 3kWp, multi-Si, laminated, integrated, on roof multi-Si 0.17475388827401409 0.24 0.183 0.3\n", + "photovoltaic slanted-roof installation, 3kWp, multi-Si, laminated, integrated, on roof multi-Si 0.17999640007199855 0.24 0.183 0.3\n", + "photovoltaic slanted-roof installation, 3kWp, multi-Si, laminated, integrated, on roof multi-Si 0.17475388827401409 0.24 0.183 0.3\n", + "photovoltaic slanted-roof installation, 3kWp, multi-Si, laminated, integrated, on roof multi-Si 0.17999640007199855 0.24 0.183 0.3\n", + "photovoltaic slanted-roof installation, 3kWp, multi-Si, laminated, integrated, on roof multi-Si 0.17475388827401409 0.24 0.183 0.3\n", + "photovoltaic slanted-roof installation, 3kWp, multi-Si, laminated, integrated, on roof multi-Si 0.17999640007199855 0.24 0.183 0.3\n", + "photovoltaic slanted-roof installation, 3kWp, multi-Si, panel, mounted, on roof multi-Si 0.17999640007199855 0.24 0.183 0.3\n", + "photovoltaic slanted-roof installation, 3kWp, multi-Si, panel, mounted, on roof multi-Si 0.17475388827401409 0.24 0.183 0.3\n", + "photovoltaic slanted-roof installation, 3kWp, multi-Si, panel, mounted, on roof multi-Si 0.17999640007199855 0.24 0.183 0.3\n", + "photovoltaic slanted-roof installation, 3kWp, multi-Si, panel, mounted, on roof multi-Si 0.17475388827401409 0.24 0.183 0.3\n", + "photovoltaic slanted-roof installation, 3kWp, multi-Si, panel, mounted, on roof multi-Si 0.17999640007199855 0.24 0.183 0.3\n", + "photovoltaic slanted-roof installation, 3kWp, multi-Si, panel, mounted, on roof multi-Si 0.17475388827401409 0.24 0.183 0.3\n", + "photovoltaic slanted-roof installation, 3kWp, multi-Si, panel, mounted, on roof multi-Si 0.17999640007199855 0.24 0.183 0.3\n", + "photovoltaic slanted-roof installation, 3kWp, multi-Si, panel, mounted, on roof multi-Si 0.17475388827401409 0.24 0.183 0.3\n", + "photovoltaic slanted-roof installation, 3kWp, single-Si, laminated, integrated, on roof single-Si 0.18932222642938282 0.27 0.20475 0.3\n", + "photovoltaic slanted-roof installation, 3kWp, single-Si, laminated, integrated, on roof single-Si 0.19499512512187195 0.27 0.20475 0.3\n", + "photovoltaic slanted-roof installation, 3kWp, single-Si, laminated, integrated, on roof single-Si 0.18932222642938282 0.27 0.20475 0.3\n", + "photovoltaic slanted-roof installation, 3kWp, single-Si, laminated, integrated, on roof single-Si 0.19499512512187195 0.27 0.20475 0.3\n", + "photovoltaic slanted-roof installation, 3kWp, single-Si, laminated, integrated, on roof single-Si 0.18932222642938282 0.27 0.20475 0.3\n", + "photovoltaic slanted-roof installation, 3kWp, single-Si, laminated, integrated, on roof single-Si 0.19499512512187195 0.27 0.20475 0.3\n", + "photovoltaic slanted-roof installation, 3kWp, single-Si, laminated, integrated, on roof single-Si 0.18932222642938282 0.27 0.20475 0.3\n", + "photovoltaic slanted-roof installation, 3kWp, single-Si, laminated, integrated, on roof single-Si 0.19499512512187195 0.27 0.20475 0.3\n", + "photovoltaic slanted-roof installation, 3kWp, single-Si, panel, mounted, on roof single-Si 0.19499512512187195 0.27 0.20475 0.3\n", + "photovoltaic slanted-roof installation, 3kWp, single-Si, panel, mounted, on roof single-Si 0.18932222642938282 0.27 0.20475 0.3\n", + "photovoltaic slanted-roof installation, 3kWp, single-Si, panel, mounted, on roof single-Si 0.19499512512187195 0.27 0.20475 0.3\n", + "photovoltaic slanted-roof installation, 3kWp, single-Si, panel, mounted, on roof single-Si 0.18932222642938282 0.27 0.20475 0.3\n", + "photovoltaic slanted-roof installation, 3kWp, single-Si, panel, mounted, on roof single-Si 0.19499512512187195 0.27 0.20475 0.3\n", + "photovoltaic slanted-roof installation, 3kWp, single-Si, panel, mounted, on roof single-Si 0.18932222642938282 0.27 0.20475 0.3\n", + "photovoltaic slanted-roof installation, 3kWp, single-Si, panel, mounted, on roof single-Si 0.19499512512187195 0.27 0.20475 0.3\n", + "photovoltaic slanted-roof installation, 3kWp, single-Si, panel, mounted, on roof single-Si 0.18932222642938282 0.27 0.20475 0.3\n", + "photovoltaic installation, 0.28kWp, GaAs GaAs 0.28 0.28 0.25 0.28\n", + "photovoltaic installation, 0.28kWp, GaAs GaAs 0.28 0.28 0.25 0.28\n", + "photovoltaic panel installation, 0.5kWp, perovskite perovskite 0.25 0.252 0.22 0.3\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "Processing scenarios: 100%|█████████████| 1/1 [00:23<00:00, 23.98s/it]" + "Processing scenarios: 100%|█████████████| 1/1 [00:24<00:00, 24.09s/it]" ] }, { @@ -916,7 +900,7 @@ }, { "cell_type": "code", - "execution_count": 5, + "execution_count": 4, "id": "ae500bd7-bbe7-4620-b50c-700041ca807b", "metadata": {}, "outputs": [], @@ -928,7 +912,7 @@ }, { "cell_type": "code", - "execution_count": 6, + "execution_count": 5, "id": "d034ab28-3cb3-491f-affe-00198fc7ec6e", "metadata": {}, "outputs": [ @@ -937,12 +921,13 @@ "output_type": "stream", "text": [ "ds photovoltaic installation, 0.28kWp, GaAs photovoltaic installation, GaAs\n", - "photovoltaic installation, 0.28kWp, GaAs 1\n", - "market for inverter, 2.5kW 0.224\n", - "market for photovoltaic mounting system, for slanted-roof installation 0.9999999999999999\n", - "market for photovoltaics, electric installation for 3kWp module, at building 1\n", - "metal organic vapor phase epitaxy (MOVPE), for GaAs photovoltaic panel 1.0\n", - "market group for electricity, low voltage 0.23\n" + "photovoltaic installation, 0.28kWp, GaAs 1 None None None\n", + "market for inverter, 2.5kW 0.224 0 None None\n", + "market for photovoltaic mounting system, for slanted-roof installation 1.0 5 0.8928571428571428 1.0\n", + "market for photovoltaics, electric installation for 3kWp module, at building 0.04666573335199963 0 None None\n", + "epitaxial lift-off (ELO) 0.01 0 None None\n", + "market for photovoltaic cell, single-Si wafer 1.0 5 0.8928571428571428 1.0\n", + "market group for electricity, low voltage 0.010733118670959916 None None None\n" ] } ], @@ -951,7 +936,7 @@ " if ds[\"name\"].startswith(\"photovoltaic installation, 0.28kWp, GaAs\"):\n", " print(\"ds\", ds[\"name\"], ds[\"reference product\"])\n", " for e in ds[\"exchanges\"]:\n", - " print(e[\"name\"], e[\"amount\"])" + " print(e[\"name\"], e[\"amount\"], e.get(\"uncertainty type\"), e.get(\"minimum\"), e.get(\"maximum\"))" ] }, { diff --git a/docs/transform.rst b/docs/transform.rst index d0858b09..4c54742d 100644 --- a/docs/transform.rst +++ b/docs/transform.rst @@ -5,7 +5,7 @@ A series of transformations are applied to the Life Cycle Inventory (LCI) databa and technology market shares with the outputs from the Integrated Assessment Model (IAM) scenario. Mobile batteries -"""""""""""""""" +++++++++++++++++ Inventories for several battery technologies for mobile applications are provided in *premise*. See EXTRACT/Import of additional inventories/Li-ion batteries for @@ -132,7 +132,7 @@ under https://github.com/polca/premise/blob/master/premise/data/battery/scenari Stationary batteries -"""""""""""""""""""" +++++++++++++++++++++ Inventories for several battery technologies for stationary applications are provided: @@ -217,7 +217,7 @@ market for battery capacity, stationary (TC scenario) GLO Vanadium R capacity needed in high voltage electricity markets. Biomass -""""""" ++++++++ Run @@ -295,7 +295,7 @@ and transport it to the powerplant, but no other forestry-related burden is incl Power generation -"""""""""""""""" +++++++++++++++++ Run @@ -607,7 +607,7 @@ Regional electricity markets ---------------------------- High voltage regional markets -============================= +----------------------------- *premise* creates high, medium and low-voltage electricity markets for each IAM region. It starts by creating high-voltage markets and define the share of each supplying technology @@ -668,7 +668,7 @@ ecoinvent). This is not ideal as it supposes that future country-specific production volumes will remain the same in respect to one another. High voltage regional markets for aluminium smelters -==================================================== +---------------------------------------------------- Aluminium production is a significant consumer of electricity. In the ecoinvent database, aluminium smelters are represented by @@ -716,10 +716,8 @@ regional mixes defined by the International Energy Agency (IEA). .. _IAI Beyond 2 Degrees Aluminium Roadmap: https://international-aluminium.org/resource/aluminium-sector-greenhouse-gas-pathways-to-2050-2021/ - - Storage -======= +------- If the IAM scenario requires the use of storage, *premise* adds a storage dataset to the high voltage market. *premise* can add two types of storage: @@ -741,7 +739,7 @@ The efficiency of the H2-fed gas turbine is based on the parameters of Ozawa_ et Medium voltage regional markets -=============================== +------------------------------- The workflow is not too different from that of high voltage markets. There are however only two possible providers of electricity in medium @@ -753,7 +751,7 @@ market to itself. Distribution losses are modelled the same way as for high voltage markets and are added to the input from high voltage market. Low voltage regional markets -============================ +---------------------------- Low voltage regional markets receive an input from the medium voltage market, as well as from residential photovoltaic power. @@ -818,7 +816,7 @@ The rest of the modelling is similar to that of regular regional electricity markets described above. Original market datasets -======================== +------------------------ Market datasets originally present in the ecoinvent LCI database are cleared from any inputs. Instead, an input from the newly created regional market @@ -840,14 +838,14 @@ regional market, which "includes" it in terms of geography. ============================================ =========== ================ =========== Relinking -========= +--------- Once the new markets are created, *premise* re-links all electricity-consuming activities to the new regional markets. The regional market it re-links to depends on the location of the consumer. Cement production -""""""""""""""""" ++++++++++++++++++ The modelling of future improvements in the cement sector is relatively simple at the moment, and does not involve the emergence of new @@ -873,7 +871,7 @@ Run ndb.update("cement") Dataset proxies -+++++++++++++++ +--------------- *premise* duplicates clinker production datasets in ecoinvent (called "clinker production") so as to create a proxy dataset for each IAM region. @@ -886,7 +884,7 @@ in different fields, such as that of *production volume*. Efficiency adjustment -+++++++++++++++++++++ +--------------------- *premise* then adjusts the thermal efficiency of the process. It does so by calculating the technology-weighted energy requirements @@ -939,7 +937,7 @@ at a fix emission rate of 525 kg CO2/t clinker. Carbon Capture and Storage -++++++++++++++++++++++++++ +-------------------------- If the IAM scenario indicates that a share of the CO2 emissions for the cement sector in a given region and year is sequestered and stored, @@ -975,7 +973,7 @@ the 2018 IEA_ cement roadmap report. ndb.generate_scenario_report() Cement markets -++++++++++++++ +-------------- Run @@ -1004,7 +1002,7 @@ as well. These cement production datasets link the newly created clinker production dataset, corresponding to their IAM region. Clinker-to-cement ratio -+++++++++++++++++++++++ +----------------------- *premise* used to modify the composition of cement markets to reflect a lower clinker content over time, based on external projections. This is @@ -1012,7 +1010,7 @@ no longer performed, as it is not an assumption stemming from the IAM model, but rather a projection of the cement industry. Original market datasets -======================== +------------------------ Market datasets originally present in the ecoinvent LCI database are cleared from any inputs. Instead, an input from the newly created regional market @@ -1035,7 +1033,7 @@ regional market, which "includes" it in terms of geography. Relinking -+++++++++ +--------- Once cement production and market datasets are created, *premise* re-links cement-consuming activities to the new regional markets for @@ -1043,7 +1041,7 @@ cement. The regional market it re-links to depends on the location of the consumer. Steel production -"""""""""""""""" +++++++++++++++++ Run @@ -1071,7 +1069,7 @@ simple at the moment, and does not involve the emergence of new technologies (e.g., hydrogen-based DRI, electro-winning). Dataset proxies -+++++++++++++++ +--------------- *premise* duplicates steel production datasets in ecoinvent for the production of primary and secondary steel (called respectively @@ -1086,7 +1084,7 @@ to using a rest-of-the-world (RoW) dataset to represent the IAM region. in different fields, such as that of *production volume*. Efficiency adjustment -+++++++++++++++++++++ +--------------------- Regarding primary steel production (using BO-BOF), *premise* adjusts the inputs of fuels found in: @@ -1125,7 +1123,7 @@ provided by the IAM scenario. by *premise*. Therefore, there is a large modelling uncertainty. Carbon Capture and Storage -++++++++++++++++++++++++++ +-------------------------- If the IAM scenario indicates that a share of the CO2 emissions from the steel sector in a given region and year is sequestered and stored, @@ -1150,7 +1148,7 @@ case of a steel mill. Steel markets -+++++++++++++ +------------- *premise* create a dataset "market for steel, low-alloyed" for each IAM region. Within each dataset, the supply shares of primary and secondary steel @@ -1180,7 +1178,7 @@ furnace process (secondary steel). Original market datasets -======================== +------------------------ Market datasets originally present in the ecoinvent LCI database are cleared from any inputs. Instead, an input from the newly created regional market @@ -1203,7 +1201,7 @@ regional market, which "includes" it in terms of geography. Relinking -+++++++++ +--------- Once steel production and market datasets are created, *premise* re-links steel-consuming activities to the new regional markets for @@ -1211,7 +1209,7 @@ steel. The regional market it re-links to depends on the location of the consumer. Transport -""""""""" ++++++++++ Run @@ -1250,7 +1248,7 @@ are obtained by scaling down the current inventories based on the vehicle efficiency improvements projected by the IAM scenario. Trucks -++++++ +------ The following size classes of medium and heavy duty trucks are imported: @@ -1425,7 +1423,7 @@ of India. ================================================================= ============ ================ =========== Direct Air Capture -"""""""""""""""""" +++++++++++++++++++ Run @@ -1457,7 +1455,7 @@ and heat of the DAC datasets to reflect changes in efficiency. .. _Qiu: https://doi.org/10.1038/s41467-022-31146-1 Fuels -""""" ++++++ Run @@ -1485,10 +1483,10 @@ and fuel markets, based on data from the IAM scenario. Efficiency adjustment -+++++++++++++++++++++ +--------------------- Biofuels -======== +-------- The biomass-to-fuel efficiency ratio of bioethanol and biodiesel production datasets is adjusted according to the IAM scenario projections. @@ -1496,54 +1494,8 @@ production datasets is adjusted according to the IAM scenario projections. Inputs to the biofuel production datasets are multiplied by a *scaling factor* that represents the change in efficiency relative to today (2020). -Hydrogen -======== - -Several pathways for hydrogen production are modeled in *premise*: - -- electrolysis -- steam methane reforming of natural gas -- steam methane reforming of biomethane -- gasification of coal -- gasification of woody biomass - -The last four pathways are modeled with and without CCS. - -Inventories for these pathways are available under: - -* premise/data/additional_inventories/lci-hydrogen-electrolysis.xlsx -* premise/data/additional_inventories/lci-smr-atr-natgas.xlsx -* premise/data/additional_inventories/lci-smr-atr-biogas.xlsx -* premise/data/additional_inventories/lci-hydrogen-coal-gasification.xlsx -* premise/data/additional_inventories/lci-hydrogen-wood-gasification.xlsx - - -In case the IAM variable that relates to a given hydrogen pathway's -efficiency is not available, the process' efficiency is not modified, -with the exception of electrolysis, which is modified regardless. - -A scaling factor is calculated for each pathway, which is the ratio -between the IAM variable value for the year in question -and the current efficiency value (i.e., in 2020). *premise* -uses this scaling factor to adjust the amount of feedstock -input to produce 1 kg of hydrogen (e.g., m3 of natural gas per kg hydrogen). - -If the IAM variable that relates to the efficiency of -the electrolysis hydrogen process is not available, -*premise* adjusts the amount of electricity needed -to produce 1 kg of hydrogen by electrolysis, on the basis of the following -requirements, which are sourced from Bauer_ et al, 2022: - - ==================== ======= ======= ======= - kWh/kg H2, 25 bar 2010 2020 2050 - ==================== ======= ======= ======= - electricity 58 55 48 - ==================== ======= ======= ======= - -.. _Bauer: https://www.psi.ch/en/media/77703/download?attachment - Land use and land use change -++++++++++++++++++++++++++++ +---------------------------- When building a database using IMAGE, land use and land use change emissions are available. Upon the import of crops farming datasets, *premise* adjusts @@ -1579,7 +1531,7 @@ CO2 emissions per kg of crop farmed are calculated as:: land_use_co2 = land_use_co2 [kg CO2/GJ] / 1000 [MJ/GJ] * LHV [MJ/kg] Regional supply chains -++++++++++++++++++++++ +---------------------- *premise* builds several supply chains for synthetic fuels, for each IAM region. THe reason for this is that synthetic fuels can be produced from @@ -1587,7 +1539,33 @@ a variety of hydrogen and CO2 sources. Additionally, hydrogen can be supplied by different means of transport, and in different states. Hydrogen -======== +-------- + +Several pathways for hydrogen production are modeled in *premise*: + +- electrolysis +- steam methane reforming of natural gas +- steam methane reforming of biomethane +- gasification of coal +- gasification of woody biomass +- natural gas pyrolysis +- thermochemical water splitting + +Each pathways are modeled with and without CCS, +with the exception of electrolysis, natural gas pyrolysis +and thermochemical water splitting. + +In case the IAM variable that relates to a given hydrogen pathway's +efficiency is not available, the process' efficiency is not modified. + +A scaling factor is calculated for each pathway, which is the ratio +between the IAM variable value for the year in question +and the current efficiency value (i.e., in 2020). *premise* +uses this scaling factor to adjust the amount of feedstock +input to produce 1 kg of hydrogen (e.g., m3 of natural gas per kg hydrogen). + +Hydrogen supply chains +---------------------- *premise* starts by building different supply chains for hydrogen by varying: @@ -1686,7 +1664,7 @@ Also, in this same case, electricity is used: Fuel markets -++++++++++++ +------------ *premise* builds markets for the following fuels: @@ -1716,7 +1694,7 @@ data and the fuel markets is described under: https://github.com/polca/premise/t the choice is made to supply it by truck over 500 km, in a gaseous state. Influence of differing LHV on fuel market composition -===================================================== +----------------------------------------------------- Because not all competing fuels of a same type have similar calorific values, some adjustments are made. The table below shows the example of the market for @@ -1799,7 +1777,7 @@ hardwood chips) relink to the dataset `market for biomass, used as fuel` if CO2 emissions update -++++++++++++++++++++ +-------------------- *premise* iterates through activities that consume any of the newly created fuel markets to update the way CO2 emissions are modelled. Based on the fuel @@ -1833,7 +1811,7 @@ new diesel market of the REMIND region for India. Geographical mapping -"""""""""""""""""""" +++++++++++++++++++++ IAM models have slightly different geographical resolutions and definitions. @@ -1859,208 +1837,209 @@ implementation in the wurst_ library. .. _constructive_geometries: https://github.com/cmutel/constructive_geometries .. _wurst: https://github.com/polca/wurst -=============== ================================= =============================== ======================== =========================== ======================== - Country Code message-topology.json gcam-topology.json tiam-ucl-topology.json remind-topology.json image-topology.json -============== ================================= =============================== ======================== =========================== ======================== - AF R12_SAS South Asia ODA OAS RSAS - AG R12_LAM Central America and Caribbean CSA LAM N/A - AI R12_LAM Central America and Caribbean CSA LAM RCAM - AL R12_EEU Europe_Non_EU WEU NEU CEU - AM R12_FSU Central Asia FSU REF RUS - AO R12_AFR Africa_Southern AFR SSA RSAF - AR R12_LAM Argentina CSA LAM RSAM - AS R12_PAS Southeast Asia ODA OAS OCE - AT R12_WEU EU-15 WEU EUR WEU - AU R12_PAO Australia_NZ AUS CAZ OCE - AZ R12_FSU Central Asia FSU REF RUS - BA R12_EEU Europe_Non_EU EEU NEU CEU - BD R12_SAS South Asia ODA OAS RSAS - BE R12_WEU EU-15 WEU EUR WEU - BF R12_AFR Africa_Western AFR SSA WAF - BG R12_EEU EU-12 EEU EUR CEU - BH R12_MEA Middle East MEA MEA ME - BI R12_AFR Africa_Eastern AFR SSA EAF - BJ R12_AFR Africa_Western AFR SSA WAF - BN R12_PAS Southeast Asia MEA OAS SEAS - BO R12_LAM South America_Southern CSA LAM RSAM - BR R12_LAM Brazil CSA LAM BRA - BS R12_LAM Central America and Caribbean CSA LAM RCAM - BT R12_SAS South Asia ODA OAS RSAS - BW R12_AFR Africa_Southern AFR SSA RSAF - BY R12_FSU Europe_Eastern FSU REF UKR - BZ R12_LAM Central America and Caribbean CSA LAM RCAM - CA R12_NAM Canada CAN CAZ CAN - CD R12_AFR Africa_Western AFR SSA WAF - CF R12_AFR Africa_Western AFR SSA WAF - CG R12_AFR Africa_Western AFR SSA WAF - CH R12_WEU European Free Trade Association WEU NEU WEU - CI R12_AFR Africa_Western AFR SSA WAF - CL R12_LAM South America_Southern CSA LAM RSAM - CM R12_AFR Africa_Western AFR SSA WAF - CN R12_CHN China CHI CHA CHN - CO R12_LAM Colombia CSA LAM RSAM - CR R12_LAM Central America and Caribbean CSA LAM RCAM - CU R12_LAM Central America and Caribbean CSA LAM RCAM - CY R12_WEU EU-12 MEA EUR N/A - CZ R12_EEU EU-12 EEU EUR CEU - DE R12_WEU EU-15 WEU EUR WEU - DJ R12_AFR Africa_Eastern AFR SSA EAF - DK R12_WEU EU-15 WEU EUR WEU - DM R12_LAM Central America and Caribbean CSA LAM RCAM - DO R12_LAM Central America and Caribbean CSA LAM RCAM - DZ R12_MEA Africa_Northern AFR MEA NAF - EC R12_LAM South America_Southern CSA LAM RSAM - EE R12_EEU EU-12 FSU EUR CEU - EG R12_MEA Africa_Northern AFR MEA NAF - ER R12_AFR Africa_Eastern AFR SSA EAF - ES R12_WEU EU-15 WEU EUR WEU - ET R12_AFR Africa_Eastern AFR SSA EAF - FI R12_WEU EU-15 WEU EUR WEU - FJ R12_PAS Southeast Asia ODA OAS OCE - FR R12_WEU EU-15 WEU EUR WEU - GA R12_AFR Africa_Western AFR SSA WAF - GB R12_WEU EU-15 UK EUR WEU - GE R12_FSU Central Asia FSU REF RUS - GF R12_LAM South America_Northern CSA LAM RSAM - GH R12_AFR Africa_Western AFR SSA WAF - GI R12_WEU EU-15 WEU EUR WEU - GL R12_WEU EU-15 NEU NEU WEU - GM R12_AFR Africa_Western AFR SSA WAF - GN R12_AFR Africa_Western AFR SSA WAF - GQ R12_AFR Africa_Western AFR SSA WAF - GR R12_WEU EU-15 WEU EUR WEU - GT R12_LAM Central America and Caribbean CSA LAM RCAM - GW R12_AFR Africa_Western AFR SSA WAF - GY R12_LAM South America_Northern CSA LAM RSAM - HK R12_CHN China CHI CHA CHN - HN R12_LAM Central America and Caribbean CSA LAM RCAM - HR R12_EEU Europe_Non_EU EEU EUR CEU - HT R12_LAM Central America and Caribbean CSA LAM RCAM - HU R12_EEU EU-12 EEU EUR CEU - ID R12_PAS Indonesia ODA OAS INDO - IE R12_WEU EU-15 WEU EUR WEU - IL R12_MEA Middle East MEA MEA ME - IN R12_SAS India IND IND INDIA - IQ R12_MEA Middle East MEA MEA ME - IR R12_MEA Middle East MEA MEA ME - IS R12_WEU European Free Trade Association WEU NEU WEU - IT R12_WEU EU-15 WEU EUR WEU - JM R12_LAM Central America and Caribbean CSA LAM RCAM - JO R12_MEA Middle East MEA MEA ME - JP R12_PAO Japan JPN JPN JAP - KE R12_AFR Africa_Eastern AFR SSA EAF - KG R12_FSU Central Asia FSU REF STAN - KH R12_RCPA Southeast Asia ODA OAS SEAS - KI R12_PAS Southeast Asia ODA OAS OCE - KM R12_AFR Africa_Eastern AFR SSA EAF - KN R12_LAM Central America and Caribbean CSA LAM RCAM - KP R12_RCPA Southeast Asia ODA OAS KOR - KR R12_PAS South Korea SKO OAS KOR - KW R12_MEA Middle East MEA MEA ME - KY R12_LAM Central America and Caribbean CSA LAM RCAM - KZ R12_FSU Central Asia FSU REF STAN - LA R12_RCPA Southeast Asia ODA OAS SEAS - LB R12_MEA Middle East MEA MEA ME - LC R12_LAM Central America and Caribbean CSA LAM RCAM - LI R12_WEU EU-15 WEU NEU WEU - LK R12_SAS South Asia ODA OAS RSAS - LR R12_AFR Africa_Western AFR SSA WAF - LS R12_AFR Africa_Southern AFR SSA RSAF - LT R12_EEU EU-12 FSU EUR CEU - LU R12_WEU EU-15 WEU EUR WEU - LV R12_EEU EU-12 FSU EUR CEU - LY R12_MEA Africa_Northern AFR MEA NAF - MA R12_MEA Africa_Northern AFR MEA NAF - MC R12_WEU EU-15 WEU NEU WEU - MD R12_FSU Europe_Eastern FSU REF UKR - ME R12_EEU Europe_Non_EU EEU NEU CEU - MG R12_AFR Africa_Eastern AFR SSA RSAF - MK R12_EEU Europe_Non_EU EEU NEU CEU - ML R12_AFR Africa_Western AFR SSA WAF - MM R12_PAS Southeast Asia ODA OAS SEAS - MN R12_RCPA Central Asia ODA OAS CHN - MO R12_CHN China CHI CHA CHN - MR R12_AFR Africa_Western AFR SSA WAF - MS R12_LAM Central America and Caribbean CSA LAM RCAM - MT R12_WEU EU-12 WEU EUR WEU - MU R12_AFR Africa_Eastern ODA SSA EAF - MW R12_AFR Africa_Southern AFR SSA RSAF - MX R12_LAM Mexico MEX MEX MEX - MY R12_PAS Southeast Asia ODA OAS SEAS - MZ R12_AFR Africa_Southern AFR SSA RSAF - NA R12_AFR Africa_Southern AFR SSA RSAF - NE R12_AFR Africa_Western AFR SSA WAF - NG R12_AFR Africa_Western AFR SSA WAF - NI R12_LAM Central America and Caribbean CSA LAM RCAM - NL R12_WEU EU-15 WEU EUR WEU - NO R12_WEU European Free Trade Association WEU NEU WEU - NP R12_SAS South Asia ODA OAS RSAS - NR R12_PAS Southeast Asia ODA OAS OCE - NU R12_PAS Southeast Asia ODA OAS OCE - NZ R12_PAO Australia_NZ AUS CAZ OCE - OM R12_MEA Middle East MEA MEA ME - PA R12_LAM Central America and Caribbean CSA LAM RCAM - PE R12_LAM South America_Southern CSA LAM RSAM - PF R12_PAS Southeast Asia ODA OAS OCE - PG R12_PAS Southeast Asia ODA OAS INDO - PH R12_PAS Southeast Asia ODA OAS SEAS - PK R12_SAS Pakistan ODA OAS RSAS - PL R12_EEU EU-12 EEU EUR CEU - PT R12_WEU EU-15 WEU EUR WEU - PY R12_LAM South America_Southern CSA LAM RSAM - QA R12_MEA Middle East MEA MEA ME - RE R12_AFR Africa_Eastern AFR SSA EAF - RO R12_EEU EU-12 EEU EUR CEU - RS R12_EEU Europe_Non_EU EEU NEU CEU - RW R12_AFR Africa_Eastern AFR SSA EAF - SA R12_MEA Middle East MEA MEA ME - SB R12_PAS Southeast Asia ODA OAS OCE - SC R12_AFR Africa_Eastern AFR SSA EAF - SD R12_MEA Africa_Eastern AFR MEA EAF - SE R12_WEU EU-15 WEU EUR WEU - SG R12_PAS Southeast Asia ODA OAS SEAS - SH R12_AFR Africa_Western AFR SSA WAF - SI R12_EEU EU-12 EEU EUR CEU - SK R12_EEU EU-12 EEU EUR CEU - SL R12_AFR Africa_Western AFR SSA WAF - SM R12_WEU EU-15 WEU NEU WEU - SN R12_AFR Africa_Western AFR SSA WAF - SO R12_AFR Africa_Eastern AFR SSA EAF - SR R12_LAM South America_Northern CSA LAM RSAM - SS R12_AFR Africa_Eastern AFR SSA EAF - ST R12_AFR Africa_Western AFR SSA WAF - SV R12_LAM Central America and Caribbean CSA LAM RCAM - SY R12_MEA Middle East MEA MEA ME - SZ R12_AFR Africa_Southern AFR SSA RSAF - TC R12_LAM Central America and Caribbean CSA LAM RCAM - TD R12_AFR Africa_Western AFR SSA WAF - TG R12_AFR Africa_Western AFR SSA WAF - TH R12_PAS Southeast Asia ODA OAS SEAS - TJ R12_FSU Central Asia FSU REF STAN - TL R12_PAS Southeast Asia ODA OAS INDO - TM R12_FSU Central Asia FSU REF STAN - TN R12_MEA Africa_Northern AFR MEA NAF - TO R12_PAS Southeast Asia ODA OAS OCE - TR R12_WEU EU-15 MEA MEA TUR - TT R12_LAM Central America and Caribbean CSA LAM RCAM - TV R12_PAS Southeast Asia ODA OAS OCE - TZ R12_AFR Africa_Southern AFR SSA RSAF - UA R12_FSU Europe_Eastern FSU REF UKR - UG R12_AFR Africa_Eastern AFR SSA EAF - US R12_NAM USA USA USA USA - UY R12_LAM South America_Southern CSA LAM RSAM - UZ R12_FSU Central Asia FSU REF STAN - VC R12_LAM Central America and Caribbean CSA LAM RCAM - VE R12_LAM South America_Northern CSA LAM RSAM - VG N/A N/A N/A LAM RCAM - VI R12_NAM Central America and Caribbean CSA LAM RCAM - VN R12_RCPA Southeast Asia ODA OAS SEAS - VU R12_PAS Southeast Asia ODA OAS OCE - YE R12_MEA Middle East MEA MEA ME - ZA R12_AFR South Africa AFR SSA SAF - ZM R12_AFR Africa_Southern AFR SSA RSAF - ZW R12_AFR Africa_Southern AFR SSA RSAF -=============== ================================= =============================== ======================== =========================== ======================== + + =============== ================================= ================================ ======================== =========================== ======================== + Country Code message-topology.json gcam-topology.json tiam-ucl-topology.json remind-topology.json image-topology.json + =============== ================================= ================================ ======================== =========================== ======================== + AF R12_SAS South Asia ODA OAS RSAS + AG R12_LAM Central America and Caribbean CSA LAM N/A + AI R12_LAM Central America and Caribbean CSA LAM RCAM + AL R12_EEU Europe_Non_EU WEU NEU CEU + AM R12_FSU Central Asia FSU REF RUS + AO R12_AFR Africa_Southern AFR SSA RSAF + AR R12_LAM Argentina CSA LAM RSAM + AS R12_PAS Southeast Asia ODA OAS OCE + AT R12_WEU EU-15 WEU EUR WEU + AU R12_PAO Australia_NZ AUS CAZ OCE + AZ R12_FSU Central Asia FSU REF RUS + BA R12_EEU Europe_Non_EU EEU NEU CEU + BD R12_SAS South Asia ODA OAS RSAS + BE R12_WEU EU-15 WEU EUR WEU + BF R12_AFR Africa_Western AFR SSA WAF + BG R12_EEU EU-12 EEU EUR CEU + BH R12_MEA Middle East MEA MEA ME + BI R12_AFR Africa_Eastern AFR SSA EAF + BJ R12_AFR Africa_Western AFR SSA WAF + BN R12_PAS Southeast Asia MEA OAS SEAS + BO R12_LAM South America_Southern CSA LAM RSAM + BR R12_LAM Brazil CSA LAM BRA + BS R12_LAM Central America and Caribbean CSA LAM RCAM + BT R12_SAS South Asia ODA OAS RSAS + BW R12_AFR Africa_Southern AFR SSA RSAF + BY R12_FSU Europe_Eastern FSU REF UKR + BZ R12_LAM Central America and Caribbean CSA LAM RCAM + CA R12_NAM Canada CAN CAZ CAN + CD R12_AFR Africa_Western AFR SSA WAF + CF R12_AFR Africa_Western AFR SSA WAF + CG R12_AFR Africa_Western AFR SSA WAF + CH R12_WEU European Free Trade Association WEU NEU WEU + CI R12_AFR Africa_Western AFR SSA WAF + CL R12_LAM South America_Southern CSA LAM RSAM + CM R12_AFR Africa_Western AFR SSA WAF + CN R12_CHN China CHI CHA CHN + CO R12_LAM Colombia CSA LAM RSAM + CR R12_LAM Central America and Caribbean CSA LAM RCAM + CU R12_LAM Central America and Caribbean CSA LAM RCAM + CY R12_WEU EU-12 MEA EUR N/A + CZ R12_EEU EU-12 EEU EUR CEU + DE R12_WEU EU-15 WEU EUR WEU + DJ R12_AFR Africa_Eastern AFR SSA EAF + DK R12_WEU EU-15 WEU EUR WEU + DM R12_LAM Central America and Caribbean CSA LAM RCAM + DO R12_LAM Central America and Caribbean CSA LAM RCAM + DZ R12_MEA Africa_Northern AFR MEA NAF + EC R12_LAM South America_Southern CSA LAM RSAM + EE R12_EEU EU-12 FSU EUR CEU + EG R12_MEA Africa_Northern AFR MEA NAF + ER R12_AFR Africa_Eastern AFR SSA EAF + ES R12_WEU EU-15 WEU EUR WEU + ET R12_AFR Africa_Eastern AFR SSA EAF + FI R12_WEU EU-15 WEU EUR WEU + FJ R12_PAS Southeast Asia ODA OAS OCE + FR R12_WEU EU-15 WEU EUR WEU + GA R12_AFR Africa_Western AFR SSA WAF + GB R12_WEU EU-15 UK EUR WEU + GE R12_FSU Central Asia FSU REF RUS + GF R12_LAM South America_Northern CSA LAM RSAM + GH R12_AFR Africa_Western AFR SSA WAF + GI R12_WEU EU-15 WEU EUR WEU + GL R12_WEU EU-15 NEU NEU WEU + GM R12_AFR Africa_Western AFR SSA WAF + GN R12_AFR Africa_Western AFR SSA WAF + GQ R12_AFR Africa_Western AFR SSA WAF + GR R12_WEU EU-15 WEU EUR WEU + GT R12_LAM Central America and Caribbean CSA LAM RCAM + GW R12_AFR Africa_Western AFR SSA WAF + GY R12_LAM South America_Northern CSA LAM RSAM + HK R12_CHN China CHI CHA CHN + HN R12_LAM Central America and Caribbean CSA LAM RCAM + HR R12_EEU Europe_Non_EU EEU EUR CEU + HT R12_LAM Central America and Caribbean CSA LAM RCAM + HU R12_EEU EU-12 EEU EUR CEU + ID R12_PAS Indonesia ODA OAS INDO + IE R12_WEU EU-15 WEU EUR WEU + IL R12_MEA Middle East MEA MEA ME + IN R12_SAS India IND IND INDIA + IQ R12_MEA Middle East MEA MEA ME + IR R12_MEA Middle East MEA MEA ME + IS R12_WEU European Free Trade Association WEU NEU WEU + IT R12_WEU EU-15 WEU EUR WEU + JM R12_LAM Central America and Caribbean CSA LAM RCAM + JO R12_MEA Middle East MEA MEA ME + JP R12_PAO Japan JPN JPN JAP + KE R12_AFR Africa_Eastern AFR SSA EAF + KG R12_FSU Central Asia FSU REF STAN + KH R12_RCPA Southeast Asia ODA OAS SEAS + KI R12_PAS Southeast Asia ODA OAS OCE + KM R12_AFR Africa_Eastern AFR SSA EAF + KN R12_LAM Central America and Caribbean CSA LAM RCAM + KP R12_RCPA Southeast Asia ODA OAS KOR + KR R12_PAS South Korea SKO OAS KOR + KW R12_MEA Middle East MEA MEA ME + KY R12_LAM Central America and Caribbean CSA LAM RCAM + KZ R12_FSU Central Asia FSU REF STAN + LA R12_RCPA Southeast Asia ODA OAS SEAS + LB R12_MEA Middle East MEA MEA ME + LC R12_LAM Central America and Caribbean CSA LAM RCAM + LI R12_WEU EU-15 WEU NEU WEU + LK R12_SAS South Asia ODA OAS RSAS + LR R12_AFR Africa_Western AFR SSA WAF + LS R12_AFR Africa_Southern AFR SSA RSAF + LT R12_EEU EU-12 FSU EUR CEU + LU R12_WEU EU-15 WEU EUR WEU + LV R12_EEU EU-12 FSU EUR CEU + LY R12_MEA Africa_Northern AFR MEA NAF + MA R12_MEA Africa_Northern AFR MEA NAF + MC R12_WEU EU-15 WEU NEU WEU + MD R12_FSU Europe_Eastern FSU REF UKR + ME R12_EEU Europe_Non_EU EEU NEU CEU + MG R12_AFR Africa_Eastern AFR SSA RSAF + MK R12_EEU Europe_Non_EU EEU NEU CEU + ML R12_AFR Africa_Western AFR SSA WAF + MM R12_PAS Southeast Asia ODA OAS SEAS + MN R12_RCPA Central Asia ODA OAS CHN + MO R12_CHN China CHI CHA CHN + MR R12_AFR Africa_Western AFR SSA WAF + MS R12_LAM Central America and Caribbean CSA LAM RCAM + MT R12_WEU EU-12 WEU EUR WEU + MU R12_AFR Africa_Eastern ODA SSA EAF + MW R12_AFR Africa_Southern AFR SSA RSAF + MX R12_LAM Mexico MEX MEX MEX + MY R12_PAS Southeast Asia ODA OAS SEAS + MZ R12_AFR Africa_Southern AFR SSA RSAF + NA R12_AFR Africa_Southern AFR SSA RSAF + NE R12_AFR Africa_Western AFR SSA WAF + NG R12_AFR Africa_Western AFR SSA WAF + NI R12_LAM Central America and Caribbean CSA LAM RCAM + NL R12_WEU EU-15 WEU EUR WEU + NO R12_WEU European Free Trade Association WEU NEU WEU + NP R12_SAS South Asia ODA OAS RSAS + NR R12_PAS Southeast Asia ODA OAS OCE + NU R12_PAS Southeast Asia ODA OAS OCE + NZ R12_PAO Australia_NZ AUS CAZ OCE + OM R12_MEA Middle East MEA MEA ME + PA R12_LAM Central America and Caribbean CSA LAM RCAM + PE R12_LAM South America_Southern CSA LAM RSAM + PF R12_PAS Southeast Asia ODA OAS OCE + PG R12_PAS Southeast Asia ODA OAS INDO + PH R12_PAS Southeast Asia ODA OAS SEAS + PK R12_SAS Pakistan ODA OAS RSAS + PL R12_EEU EU-12 EEU EUR CEU + PT R12_WEU EU-15 WEU EUR WEU + PY R12_LAM South America_Southern CSA LAM RSAM + QA R12_MEA Middle East MEA MEA ME + RE R12_AFR Africa_Eastern AFR SSA EAF + RO R12_EEU EU-12 EEU EUR CEU + RS R12_EEU Europe_Non_EU EEU NEU CEU + RW R12_AFR Africa_Eastern AFR SSA EAF + SA R12_MEA Middle East MEA MEA ME + SB R12_PAS Southeast Asia ODA OAS OCE + SC R12_AFR Africa_Eastern AFR SSA EAF + SD R12_MEA Africa_Eastern AFR MEA EAF + SE R12_WEU EU-15 WEU EUR WEU + SG R12_PAS Southeast Asia ODA OAS SEAS + SH R12_AFR Africa_Western AFR SSA WAF + SI R12_EEU EU-12 EEU EUR CEU + SK R12_EEU EU-12 EEU EUR CEU + SL R12_AFR Africa_Western AFR SSA WAF + SM R12_WEU EU-15 WEU NEU WEU + SN R12_AFR Africa_Western AFR SSA WAF + SO R12_AFR Africa_Eastern AFR SSA EAF + SR R12_LAM South America_Northern CSA LAM RSAM + SS R12_AFR Africa_Eastern AFR SSA EAF + ST R12_AFR Africa_Western AFR SSA WAF + SV R12_LAM Central America and Caribbean CSA LAM RCAM + SY R12_MEA Middle East MEA MEA ME + SZ R12_AFR Africa_Southern AFR SSA RSAF + TC R12_LAM Central America and Caribbean CSA LAM RCAM + TD R12_AFR Africa_Western AFR SSA WAF + TG R12_AFR Africa_Western AFR SSA WAF + TH R12_PAS Southeast Asia ODA OAS SEAS + TJ R12_FSU Central Asia FSU REF STAN + TL R12_PAS Southeast Asia ODA OAS INDO + TM R12_FSU Central Asia FSU REF STAN + TN R12_MEA Africa_Northern AFR MEA NAF + TO R12_PAS Southeast Asia ODA OAS OCE + TR R12_WEU EU-15 MEA MEA TUR + TT R12_LAM Central America and Caribbean CSA LAM RCAM + TV R12_PAS Southeast Asia ODA OAS OCE + TZ R12_AFR Africa_Southern AFR SSA RSAF + UA R12_FSU Europe_Eastern FSU REF UKR + UG R12_AFR Africa_Eastern AFR SSA EAF + US R12_NAM USA USA USA USA + UY R12_LAM South America_Southern CSA LAM RSAM + UZ R12_FSU Central Asia FSU REF STAN + VC R12_LAM Central America and Caribbean CSA LAM RCAM + VE R12_LAM South America_Northern CSA LAM RSAM + VG N/A N/A N/A LAM RCAM + VI R12_NAM Central America and Caribbean CSA LAM RCAM + VN R12_RCPA Southeast Asia ODA OAS SEAS + VU R12_PAS Southeast Asia ODA OAS OCE + YE R12_MEA Middle East MEA MEA ME + ZA R12_AFR South Africa AFR SSA SAF + ZM R12_AFR Africa_Southern AFR SSA RSAF + ZW R12_AFR Africa_Southern AFR SSA RSAF + =============== ================================= ================================ ======================== =========================== ======================== @@ -2068,7 +2047,7 @@ The mapping between ecoinvent locations and IAM regions is available under the f https://github.com/polca/premise/blob/master/premise/iam_variables_mapping/topologies Regionalization -""""""""""""""" ++++++++++++++++ Several of the integration steps described above involve the regionalization of datasets. It is the case, for example, when introducing @@ -2177,7 +2156,12 @@ Final Steps GAINS emission factors -"""""""""""""""""""""" +++++++++++++++++++++++ + +Emissions factors from the air pollution model GAINS are used to scale +non-CO2 emissions in various datasets. The emission factors are available under: + +premise/data/GAINS_emission_factors Run @@ -2295,7 +2279,7 @@ For questions related to GAINS modelling, please contact the respective GAINS te * GAINS-IAM: https://gains.iiasa.ac.at/gains/IAM/index.login Logs -"""" +++++ *premise* generates a spreadsheet report detailing changes made to the database for each scenario. The report is saved in the current working directory and diff --git a/premise/__init__.py b/premise/__init__.py index b0ef335c..ea53423b 100644 --- a/premise/__init__.py +++ b/premise/__init__.py @@ -5,7 +5,7 @@ "clear_inventory_cache", "get_regions_definition", ) -__version__ = (2, 1, 1, "dev8") +__version__ = (2, 1, 1, "dev9") from premise.new_database import NewDatabase diff --git a/premise/data/additional_inventories/lci-PV-GaAs.xlsx b/premise/data/additional_inventories/lci-PV-GaAs.xlsx index 1ded0ed9b5a601b8e20f5238b4fd4a856b748518..4ff739178dccb696b0388bb45d542235c55d984d 100644 GIT binary patch delta 18293 zcmXt%h=v4|TbKygK<-{om~3Oss6$ zIZ-jov+Q^FsTt^I%~4CZj1top$FVKPlW)u4Yg*W5G>0h{F8WNmXq`7`Ph$nDcB&Pt;(IJ%_&W!hS~%fEYAF&h5MF z*BDl#)lICD3vBf$78+8jml%_Q>x>6@xRJ*jD0~k)!=N=6UMc7=0}l!NVLoQ9Ad3Ik z4u>E3qfHAqHO;@#9Z~wO$Smh8+@@-Fs#3Dau2pjHN13y8gq5r`?n8-Faw)X$QfkBI zq6Akzi_EkwfM^dN)Ev}t`2QeZ+mHdqu4`mliugs0^|igO>yjm+_+!%1f5##BR%ZUo-%y6jZJ%s7Tcin|IA8mrr$jnzw;sP*gR(Q 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ws.technosphere( - dataset, - ws.contains("name", "photovoltaic"), - ws.equals("unit", "square meter"), - ): - surface = float(exc["amount"]) - max_power = surface # in kW, since we assume a constant 1,000W/m^2 - current_eff = power / max_power - - if self.year in module_eff.coords["year"].values: - new_mean_eff = module_eff.sel( - technology=pv_tech, year=self.year, efficiency_type="mean" - ).values - new_min_eff = module_eff.sel( - technology=pv_tech, year=self.year, efficiency_type="min" - ).values - new_max_eff = module_eff.sel( - technology=pv_tech, year=self.year, efficiency_type="max" - ).values - else: - new_mean_eff = ( - module_eff.sel(technology=pv_tech, efficiency_type="mean") - .interp(year=self.year, kwargs={"fill_value": "extrapolate"}) - .values - ) - new_min_eff = ( - module_eff.sel(technology=pv_tech, efficiency_type="min") - .interp(year=self.year, kwargs={"fill_value": "extrapolate"}) - .values - ) - new_max_eff = ( - module_eff.sel(technology=pv_tech, efficiency_type="max") - .interp(year=self.year, kwargs={"fill_value": "extrapolate"}) - .values - ) + if pv_tech: - # in case self.year <10 or >2050 - new_mean_eff = np.clip(new_mean_eff, 0.1, 0.30) - new_min_eff = np.clip(new_min_eff, 0.1, 0.30) - new_max_eff = np.clip(new_max_eff, 0.1, 0.30) - - # We only update the efficiency if it is higher than the current one. - if new_mean_eff.sum() > current_eff: - exc["amount"] *= float(current_eff / new_mean_eff) - exc["uncertainty type"] = 5 - exc["loc"] = exc["amount"] - exc["minimum"] = exc["amount"] * (new_min_eff / new_mean_eff) - exc["maximum"] = exc["amount"] * (new_max_eff / new_mean_eff) - - dataset["comment"] = ( - f"`premise` has changed the efficiency " - f"of this photovoltaic installation " - f"from {int(current_eff * 100)} pct. to {int(new_mean_eff * 100)} pt." - ) + for exc in ws.technosphere( + dataset, + ws.contains("name", "photovoltaic"), + ws.equals("unit", "square meter"), + ): + surface = float(exc["amount"]) + max_power = surface # in kW, since we assume a constant 1,000W/m^2 + current_eff = power / max_power + + if self.year in module_eff.coords["year"].values: + new_mean_eff = module_eff.sel( + technology=pv_tech, year=self.year, efficiency_type="mean" + ).values + new_min_eff = module_eff.sel( + technology=pv_tech, year=self.year, efficiency_type="min" + ).values + new_max_eff = module_eff.sel( + technology=pv_tech, year=self.year, efficiency_type="max" + ).values + else: + new_mean_eff = ( + module_eff.sel(technology=pv_tech, efficiency_type="mean") + .interp(year=self.year, kwargs={"fill_value": "extrapolate"}) + .values + ) + new_min_eff = ( + module_eff.sel(technology=pv_tech, efficiency_type="min") + .interp(year=self.year, kwargs={"fill_value": "extrapolate"}) + .values + ) + new_max_eff = ( + module_eff.sel(technology=pv_tech, efficiency_type="max") + .interp(year=self.year, kwargs={"fill_value": "extrapolate"}) + .values + ) - if "log parameters" not in dataset: - dataset["log parameters"] = {} + # in case self.year <10 or >2050 + new_mean_eff = np.clip(new_mean_eff, 0.1, 0.30) + new_min_eff = np.clip(new_min_eff, 0.1, 0.30) + new_max_eff = np.clip(new_max_eff, 0.1, 0.30) + + # We only update the efficiency if it is higher than the current one. + if new_mean_eff.sum() >= current_eff: + exc["amount"] *= float(current_eff / new_mean_eff) + exc["uncertainty type"] = 5 + exc["loc"] = exc["amount"] + exc["minimum"] = exc["amount"] * (new_min_eff / new_mean_eff) + exc["maximum"] = exc["amount"] * (new_max_eff / new_mean_eff) + + dataset["comment"] = ( + f"`premise` has changed the efficiency " + f"of this photovoltaic installation " + f"from {int(current_eff * 100)} pct. to {int(new_mean_eff * 100)} pt." + ) - dataset["log parameters"].update({"old efficiency": current_eff}) - dataset["log parameters"].update({"new efficiency": new_mean_eff}) + if "log parameters" not in dataset: + dataset["log parameters"] = {} - # add to log - self.write_log(dataset=dataset, status="updated") + dataset["log parameters"].update({"old efficiency": current_eff}) + dataset["log parameters"].update({"new efficiency": new_mean_eff}) + + # add to log + self.write_log(dataset=dataset, status="updated") def create_region_specific_power_plants(self): """ diff --git a/tests/test_utils.py b/tests/test_utils.py index 7e87b807..b97e2587 100644 --- a/tests/test_utils.py +++ b/tests/test_utils.py @@ -37,7 +37,7 @@ def test_fuels_properties(): def test_eff_solar_PV(): eff_PV = get_efficiency_solar_photovoltaics() assert type(eff_PV) == xr.DataArray - assert eff_PV.sel(technology="multi-Si", year=2010) == 0.14 + assert eff_PV.sel(technology="multi-Si", year=2010, efficiency_type="mean") == 0.14 assert "moni-Si" not in eff_PV.technology.values From ee625311d7ba5c2d88deea6eaacc7ea46500fac1 Mon Sep 17 00:00:00 2001 From: romainsacchi Date: Tue, 20 Aug 2024 17:17:18 +0000 Subject: [PATCH 2/6] Black reformating --- premise/electricity.py | 20 +++++++++++++++----- 1 file changed, 15 insertions(+), 5 deletions(-) diff --git a/premise/electricity.py b/premise/electricity.py index fe8f7e5a..c57cb6ee 100644 --- a/premise/electricity.py +++ b/premise/electricity.py @@ -1466,17 +1466,23 @@ def update_efficiency_of_solar_pv(self) -> None: else: new_mean_eff = ( module_eff.sel(technology=pv_tech, efficiency_type="mean") - .interp(year=self.year, kwargs={"fill_value": "extrapolate"}) + .interp( + year=self.year, kwargs={"fill_value": "extrapolate"} + ) .values ) new_min_eff = ( module_eff.sel(technology=pv_tech, efficiency_type="min") - .interp(year=self.year, kwargs={"fill_value": "extrapolate"}) + .interp( + year=self.year, kwargs={"fill_value": "extrapolate"} + ) .values ) new_max_eff = ( module_eff.sel(technology=pv_tech, efficiency_type="max") - .interp(year=self.year, kwargs={"fill_value": "extrapolate"}) + .interp( + year=self.year, kwargs={"fill_value": "extrapolate"} + ) .values ) @@ -1502,8 +1508,12 @@ def update_efficiency_of_solar_pv(self) -> None: if "log parameters" not in dataset: dataset["log parameters"] = {} - dataset["log parameters"].update({"old efficiency": current_eff}) - dataset["log parameters"].update({"new efficiency": new_mean_eff}) + dataset["log parameters"].update( + {"old efficiency": current_eff} + ) + dataset["log parameters"].update( + {"new efficiency": new_mean_eff} + ) # add to log self.write_log(dataset=dataset, status="updated") From 9b73e70097818111bc51b71aae079300b17bf742 Mon Sep 17 00:00:00 2001 From: romainsacchi Date: Wed, 21 Aug 2024 21:22:07 +0200 Subject: [PATCH 3/6] Align wrt master --- MANIFEST.in | 2 + .../lci-battery-capacity.xlsx | Bin 33670 -> 33719 bytes .../additional_inventories/lci-trucks.xlsx | Bin 300088 -> 300066 bytes premise/data/transport/battery_size.yaml | 128 +++++++++++++ premise/data/transport/vehicles_map.yaml | 128 ++++++++++--- premise/transport.py | 169 +++++++++++++++--- 6 files changed, 376 insertions(+), 51 deletions(-) create mode 100644 premise/data/transport/battery_size.yaml diff --git a/MANIFEST.in b/MANIFEST.in index f6bc07a6..9c31ce74 100644 --- a/MANIFEST.in +++ b/MANIFEST.in @@ -50,6 +50,8 @@ include premise/data/transport/car/*.csv include premise/data/transport/bus/*.csv include premise/data/transport/truck/*.csv include premise/data/transport/two-wheeler/*.csv +include premise/data/battery/*.csv +include premise/data/battery/*.yaml include premise/data/utils/*.csv include premise/data/utils/*.yml include premise/data/utils/*.yaml diff --git a/premise/data/additional_inventories/lci-battery-capacity.xlsx b/premise/data/additional_inventories/lci-battery-capacity.xlsx index 8d7afd2736ab3fd711a6eb476d758f93791a25cf..e1a62683c7cdd52debc331996d34da1d67387394 100644 GIT binary patch delta 16799 zcmZ6TV{{}@|E(w1B$-SmwrzXjiEZ09JGLf0v2EM7ZQHhPzwiHIt=nIAowLsBs`~A- zpHsc6szXA-n?k{>&!GVbY5FWv5Z}J-zmWlN|L_Lm!DC3~ss z7Jfu1IbXk|7qA{$=*&tsNJ7$ufj={wA+#*078VuLgu7Q_sE&?76(`pOl(^*0vyQU1 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NLpbqmlOW)S{}1uZb9Vp$ diff --git a/premise/data/transport/battery_size.yaml b/premise/data/transport/battery_size.yaml new file mode 100644 index 00000000..56c1c9b8 --- /dev/null +++ b/premise/data/transport/battery_size.yaml @@ -0,0 +1,128 @@ +# battery size, in kWh +# for long-haul trucks +# provided by carculator_truck +# min: size for a range autonomy of 400 km +# max for a range autonomy of 800 km +# mean: value in between min and max +--- + +truck: + 3.5t: + 2020: + min: 160 + max: 383 + mean: 272 + 2030: + min: 134 + max: 300 + mean: 217 + 2040: + min: 120 + max: 267 + mean: 194 + 2050: + min: 108 + max: 236 + mean: 172 + 7.5t: + 2020: + min: 272 + max: 639 + mean: 456 + 2030: + min: 203 + max: 479 + mean: 341 + 2040: + min: 182 + max: 479 + mean: 330 + 2050: + min: 168 + max: 370 + mean: 269 + 18t: + 2020: + min: 394 + max: 1110 + mean: 752 + 2030: + min: 323 + max: 802 + mean: 562 + 2040: + min: 296 + max: 726 + mean: 511 + 2050: + min: 273 + max: 666 + mean: 470 + 26t: + 2020: + min: 509 + max: 1291 + mean: 900 + 2030: + min: 390 + max: 978 + mean: 684 + 2040: + min: 362 + max: 906 + mean: 634 + 2050: + min: 360 + max: 845 + mean: 603 + 32t: + 2020: + min: 660 + max: 1515 + mean: 1088 + 2030: + min: 550 + max: 1207 + mean: 879 + 2040: + min: 530 + max: 1124 + mean: 827 + 2050: + min: 490 + max: 1038 + mean: 764 + 40t: + 2020: + min: 665 + max: 1542 + mean: 1104 + 2030: + min: 550 + max: 1200 + mean: 875 + 2040: + min: 530 + max: 1123 + mean: 826 + 2050: + min: 490 + max: 1067 + mean: 779 + 60t: + 2020: + min: 835 + max: 1804 + mean: 1320 + 2030: + min: 670 + max: 1349 + mean: 1010 + 2040: + min: 630 + max: 1255 + mean: 942 + 2050: + min: 603 + max: 1188 + mean: 896 \ No newline at end of file diff --git a/premise/data/transport/vehicles_map.yaml b/premise/data/transport/vehicles_map.yaml index d49b3e1a..0b02ca44 100644 --- a/premise/data/transport/vehicles_map.yaml +++ b/premise/data/transport/vehicles_map.yaml @@ -43,32 +43,108 @@ truck: unit: ton kilometer name: transport, freight, lorry old_trucks: - remind: - transport, freight, lorry, unspecified: transport, freight, lorry, unspecified - transport, freight, lorry 16-32 metric ton: transport, freight, lorry, 26t gross weight, unspecified powertrain - transport, freight, lorry 28 metric ton, fatty acid methyl ester 100%: transport, freight, lorry, 26t gross weight, unspecified powertrain - transport, freight, lorry 3.5-7.5 metric ton: transport, freight, lorry, 3.5t gross weight, unspecified powertrain - transport, freight, lorry 7.5-16 metric ton: transport, freight, lorry, 7.5t gross weight, unspecified powertrain - transport, freight, lorry >32 metric ton: transport, freight, lorry, 40t gross weight, unspecified powertrain - transport, freight, lorry with reefer, cooling: transport, freight, lorry, unspecified - transport, freight, lorry with reefer, freezing: transport, freight, lorry, unspecified - transport, freight, lorry with refrigeration machine, 3.5-7.5 ton: transport, freight, lorry, 3.5t gross weight, unspecified powertrain - transport, freight, lorry with refrigeration machine, 7.5-16 ton: transport, freight, lorry, 7.5t gross weight, unspecified powertrain - transport, freight, lorry with refrigeration machine, cooling: transport, freight, lorry, unspecified - transport, freight, lorry with refrigeration machine, freezing: transport, freight, lorry, unspecified - image: - transport, freight, lorry, unspecified: transport, freight, lorry, unspecified - transport, freight, lorry 16-32 metric ton: transport, freight, lorry, 26t gross weight, unspecified powertrain - transport, freight, lorry 28 metric ton, fatty acid methyl ester 100%: transport, freight, lorry, 26t gross weight, unspecified powertrain - transport, freight, lorry 3.5-7.5 metric ton: transport, freight, lorry, 26t gross weight, unspecified powertrain - transport, freight, lorry 7.5-16 metric ton: transport, freight, lorry, 26t gross weight, unspecified powertrain - transport, freight, lorry >32 metric ton: transport, freight, lorry, 40t gross weight, unspecified powertrain - transport, freight, lorry with reefer, cooling: transport, freight, lorry, unspecified - transport, freight, lorry with reefer, freezing: transport, freight, lorry, unspecified - transport, freight, lorry with refrigeration machine, 3.5-7.5 ton: transport, freight, lorry, 26t gross weight, unspecified powertrain - transport, freight, lorry with refrigeration machine, 7.5-16 ton: transport, freight, lorry, 26t gross weight, unspecified powertrain - transport, freight, lorry with refrigeration machine, cooling: transport, freight, lorry, unspecified - transport, freight, lorry with refrigeration machine, freezing: transport, freight, lorry, unspecified + transport, freight, lorry 16-32 metric ton, EURO1: + remind: transport, freight, lorry, 26t gross weight, unspecified powertrain, long haul + image: transport, freight, lorry, 18t gross weight, unspecified powertrain, long haul + transport, freight, lorry 3.5-7.5 metric ton, EURO3: + remind: transport, freight, lorry, 7.5t gross weight, unspecified powertrain, long haul + image: transport, freight, lorry, 18t gross weight, unspecified powertrain, long haul + transport, freight, lorry 16-32 metric ton, EURO5: + remind: transport, freight, lorry, 26t gross weight, unspecified powertrain, long haul + image: transport, freight, lorry, 18t gross weight, unspecified powertrain, long haul + transport, freight, lorry >32 metric ton, EURO1: + remind: transport, freight, lorry, 40t gross weight, unspecified powertrain, long haul + image: transport, freight, lorry, 40t gross weight, unspecified powertrain, long haul + transport, freight, lorry 3.5-7.5 metric ton, EURO4: + remind: transport, freight, lorry, 7.5t gross weight, unspecified powertrain, long haul + image: transport, freight, lorry, 18t gross weight, unspecified powertrain, long haul + transport, freight, lorry, all sizes, EURO1 to generic market for transport, freight, lorry, unspecified: + remind: transport, freight, lorry, unspecified, long haul + image: transport, freight, lorry, unspecified, long haul + transport, freight, lorry 7.5-16 metric ton, EURO6: + remind: transport, freight, lorry, 18t gross weight, unspecified powertrain, long haul + image: transport, freight, lorry, 18t gross weight, unspecified powertrain, long haul + transport, freight, lorry 7.5-16 metric ton, EURO1: + remind: transport, freight, lorry, 18t gross weight, unspecified powertrain, long haul + image: transport, freight, lorry, 18t gross weight, unspecified powertrain, long haul + transport, freight, lorry, all sizes, EURO3 to generic market for transport, freight, lorry, unspecified: + remind: transport, freight, lorry, unspecified, long haul + image: transport, freight, lorry, unspecified, long haul + transport, freight, lorry 16-32 metric ton, EURO6: + remind: transport, freight, lorry, 26t gross weight, unspecified powertrain, long haul + image: transport, freight, lorry, 18t gross weight, unspecified powertrain, long haul + transport, freight, lorry 7.5-16 metric ton, EURO2: + remind: transport, freight, lorry, 18t gross weight, unspecified powertrain, long haul + image: transport, freight, lorry, 18t gross weight, unspecified powertrain, long haul + transport, freight, lorry 7.5-16 metric ton, EURO3: + remind: transport, freight, lorry, 18t gross weight, unspecified powertrain, long haul + image: transport, freight, lorry, 18t gross weight, unspecified powertrain, long haul + transport, freight, lorry 7.5-16 metric ton, EURO4: + remind: transport, freight, lorry, 18t gross weight, unspecified powertrain, long haul + image: transport, freight, lorry, 18t gross weight, unspecified powertrain, long haul + transport, freight, lorry 16-32 metric ton, EURO2: + remind: transport, freight, lorry, 26t gross weight, unspecified powertrain, long haul + image: transport, freight, lorry, 18t gross weight, unspecified powertrain, long haul + transport, freight, lorry >32 metric ton, EURO6: + remind: transport, freight, lorry, 40t gross weight, unspecified powertrain, long haul + image: transport, freight, lorry, 40t gross weight, unspecified powertrain, long haul + transport, freight, lorry 3.5-7.5 metric ton, EURO2: + remind: transport, freight, lorry, 7.5t gross weight, unspecified powertrain, long haul + image: transport, freight, lorry, 18t gross weight, unspecified powertrain, long haul + transport, freight, lorry 3.5-7.5 metric ton, EURO1: + remind: transport, freight, lorry, 7.5t gross weight, unspecified powertrain, long haul + image: transport, freight, lorry, 18t gross weight, unspecified powertrain, long haul + transport, freight, lorry, all sizes, EURO2 to generic market for transport, freight, lorry, unspecified: + remind: transport, freight, lorry, unspecified, long haul + image: transport, freight, lorry, unspecified, long haul + transport, freight, lorry 16-32 metric ton, unregulated: + remind: transport, freight, lorry, 26t gross weight, unspecified powertrain, long haul + image: transport, freight, lorry, 18t gross weight, unspecified powertrain, long haul + transport, freight, lorry >32 metric ton, unregulated: + remind: transport, freight, lorry, 40t gross weight, unspecified powertrain, long haul + image: transport, freight, lorry, 40t gross weight, unspecified powertrain, long haul + transport, freight, lorry >32 metric ton, EURO3: + remind: transport, freight, lorry, 40t gross weight, unspecified powertrain, long haul + image: transport, freight, lorry, 40t gross weight, unspecified powertrain, long haul + transport, freight, lorry 3.5-7.5 metric ton, unregulated: + remind: transport, freight, lorry, 7.5t gross weight, unspecified powertrain, long haul + image: transport, freight, lorry, 18t gross weight, unspecified powertrain, long haul + transport, freight, lorry 7.5-16 metric ton, EURO5: + remind: transport, freight, lorry, 18t gross weight, unspecified powertrain, long haul + image: transport, freight, lorry, 18t gross weight, unspecified powertrain, long haul + transport, freight, lorry 3.5-7.5 metric ton, EURO6: + remind: transport, freight, lorry, 7.5t gross weight, unspecified powertrain, long haul + image: transport, freight, lorry, 18t gross weight, unspecified powertrain, long haul + transport, freight, lorry 7.5-16 metric ton, unregulated: + remind: transport, freight, lorry, 18t gross weight, unspecified powertrain, long haul + image: transport, freight, lorry, 18t gross weight, unspecified powertrain, long haul + transport, freight, lorry 3.5-7.5 metric ton, EURO5: + remind: transport, freight, lorry, 7.5t gross weight, unspecified powertrain, long haul + image: transport, freight, lorry, 18t gross weight, unspecified powertrain, long haul + transport, freight, lorry >32 metric ton, EURO2: + remind: transport, freight, lorry, 40t gross weight, unspecified powertrain, long haul + image: transport, freight, lorry, 40t gross weight, unspecified powertrain, long haul + transport, freight, lorry 16-32 metric ton, EURO3: + remind: transport, freight, lorry, 26t gross weight, unspecified powertrain, long haul + image: transport, freight, lorry, 18t gross weight, unspecified powertrain, long haul + transport, freight, lorry, all sizes, EURO5 to generic market for transport, freight, lorry, unspecified: + remind: transport, freight, lorry, unspecified, long haul + image: transport, freight, lorry, unspecified, long haul + transport, freight, lorry, all sizes, EURO6 to generic market for transport, freight, lorry, unspecified: + remind: transport, freight, lorry, unspecified, long haul + image: transport, freight, lorry, unspecified, long haul + transport, freight, lorry 16-32 metric ton, EURO4: + remind: transport, freight, lorry, 26t gross weight, unspecified powertrain, long haul + image: transport, freight, lorry, 18t gross weight, unspecified powertrain, long haul + transport, freight, lorry >32 metric ton, EURO4: + remind: transport, freight, lorry, 40t gross weight, unspecified powertrain, long haul + image: transport, freight, lorry, 40t gross weight, unspecified powertrain, long haul + transport, freight, lorry >32 metric ton, EURO5: + remind: transport, freight, lorry, 40t gross weight, unspecified powertrain, long haul + image: transport, freight, lorry, 40t gross weight, unspecified powertrain, long haul + transport, freight, lorry, all sizes, unregulated to generic market for transport, freight, lorry, unspecified: + remind: transport, freight, lorry, unspecified, long haul + image: transport, freight, lorry, unspecified, long haul powertrain: fuel cell electric: FCEV diff --git a/premise/transport.py b/premise/transport.py index e6b166d7..235d4bee 100644 --- a/premise/transport.py +++ b/premise/transport.py @@ -86,6 +86,19 @@ def _update_vehicles(scenario, vehicle_type, version, system_model): return scenario +def get_battery_size() -> dict: + """ + Return a dictionary that contains the size of the battery + for each vehicle type and powertrain. + :return: dictionary with battery sizes + """ + with open( + DATA_DIR / "transport" / "battery_size.yaml", "r", encoding="utf-8" + ) as stream: + out = yaml.safe_load(stream) + return out + + def get_average_truck_load_factors() -> Dict[str, Dict[str, Dict[str, float]]]: """ Load average load factors for trucks @@ -373,6 +386,7 @@ def __init__( self.vehicle_fuel_map = mapping.generate_vehicle_fuel_map( transport_type=vehicle_type ) + self.battery_size = get_battery_size() # check if vehicle map is empty for v in self.vehicle_map.values(): @@ -418,6 +432,7 @@ def create_vehicle_markets(self) -> list: for new_ds in new_datasets: new_ds = self.adjust_transport_efficiency(new_ds) + if not self.is_in_index(new_ds): self.add_to_index(new_ds) self.database.append(new_ds) @@ -459,10 +474,21 @@ def create_vehicle_markets(self) -> list: ) ) + # if trucks, adjust battery size + if self.vehicle_type == "truck": + for ds in ws.get_many( + self.database, + ws.contains("name", "battery electric"), + ws.contains("name", "truck"), + ws.equals("unit", "unit"), + ): + self.adjust_battery_size(ds) + # if trucks, need to reconnect everything # loop through datasets that use truck transport if self.vehicle_type == "truck": - list_created_trucks = [(a["name"], a["location"]) for a in fleet_act] + + list_created_vehicles = [(v["name"], v["location"]) for v in fleet_act] for dataset in ws.get_many( self.database, @@ -471,37 +497,74 @@ def create_vehicle_markets(self) -> list: ): for exc in ws.technosphere( dataset, - ws.contains("name", "transport, freight, lorry"), + ws.either( + *[ + ws.equals("name", v) + for v in self.mapping["truck"]["old_trucks"] + ] + ), ws.equals("unit", "ton kilometer"), ): - key = [ - k - for k in self.mapping["truck"]["old_trucks"][self.model] - if k.lower() in exc["name"].lower() - ][0] - - if "input" in exc: - del exc["input"] - - if dataset["unit"] == "kilogram": - name = f"{self.mapping['truck']['old_trucks'][self.model][key]}, long haul" - loc = self.geo.ecoinvent_to_iam_location(dataset["location"]) - - if (name, loc) in list_created_trucks: - exc["name"] = name - else: - exc["name"] = ( - f"transport, freight, lorry, unspecified, long haul" - ) + + new_name = self.mapping["truck"]["old_trucks"][exc["name"]][ + self.model + ] + new_loc = self.geo.ecoinvent_to_iam_location(dataset["location"]) + + if (new_name, new_loc) in list_created_vehicles: + exc["name"] = new_name + exc["product"] = "transport, freight, lorry" + exc["location"] = new_loc else: + print(f"Could not find dataset for {new_name} in {new_loc}.") exc["name"] = ( "transport, freight, lorry, unspecified, long haul" ) + exc["product"] = "transport, freight, lorry" + exc["location"] = "World" - exc["product"] = "transport, freight, lorry" - exc["location"] = self.geo.ecoinvent_to_iam_location( - dataset["location"] - ) + # also we need to empty the old transport datasets + for dataset in ws.get_many( + self.database, + ws.either( + *[ws.equals("name", v) for v in self.mapping["truck"]["old_trucks"]] + ), + ): + dataset["exchanges"] = [ + e for e in dataset["exchanges"] if e["type"] == "production" + ] + dataset["comment"] = ( + "This dataset has been replaced by new fleet-average vehicles." + ) + + # add new truck as exchange + new_name = self.mapping["truck"]["old_trucks"][dataset["name"]][ + self.model + ] + new_loc = self.geo.ecoinvent_to_iam_location(dataset["location"]) + + if (new_name, new_loc) in list_created_vehicles: + new_exc = { + "name": new_name, + "product": "transport, freight, lorry", + "unit": "ton kilometer", + "location": new_loc, + "type": "technosphere", + "amount": 1, + "uncertainty type": 0, + } + else: + print(f"Could not find dataset for {new_name} in {new_loc}.") + new_exc = { + "name": "transport, freight, lorry, unspecified, long haul", + "product": "transport, freight, lorry", + "unit": "ton kilometer", + "location": "World", + "type": "technosphere", + "amount": 1, + "uncertainty type": 0, + } + dataset["exchanges"].append(new_exc) return fleet_act @@ -559,6 +622,62 @@ def adjust_transport_efficiency(self, dataset): return dataset + def adjust_battery_size(self, ds): + """ + Adjust battery size for truck datasets. + """ + + # detect size in name + size = [s for s in self.battery_size["truck"] if s in ds["name"]][0] + + print(self.battery_size["truck"][size]) + + if self.year <= min(self.battery_size["truck"][size].keys()): + mean_battery_size = self.battery_size["truck"][size][ + min(self.battery_size["truck"][size].keys()) + ]["mean"] + min_battery_size = self.battery_size["truck"][size][ + min(self.battery_size["truck"][size].keys()) + ]["min"] + max_battery_size = self.battery_size["truck"][size][ + min(self.battery_size["truck"][size].keys()) + ]["max"] + elif self.year >= max(self.battery_size["truck"][size].keys()): + mean_battery_size = self.battery_size["truck"][size][ + max(self.battery_size["truck"][size].keys()) + ]["mean"] + min_battery_size = self.battery_size["truck"][size][ + max(self.battery_size["truck"][size].keys()) + ]["min"] + max_battery_size = self.battery_size["truck"][size][ + max(self.battery_size["truck"][size].keys()) + ]["max"] + else: + mean_battery_size = np.interp( + self.year, + list(self.battery_size["truck"][size].keys()), + [v["mean"] for v in self.battery_size["truck"][size].values()], + ) + min_battery_size = np.interp( + self.year, + list(self.battery_size["truck"][size].keys()), + [v["min"] for v in self.battery_size["truck"][size].values()], + ) + max_battery_size = np.interp( + self.year, + list(self.battery_size["truck"][size].keys()), + [v["max"] for v in self.battery_size["truck"][size].values()], + ) + + for exc in ws.technosphere(ds, ws.contains("name", "market for battery")): + exc["amount"] = mean_battery_size + exc["uncertainty type"] = 5 + exc["loc"] = exc["amount"] + exc["minimum"] = min_battery_size + exc["maximum"] = max_battery_size + + ds["comment"] += f" Battery size adjusted to {mean_battery_size} kWh." + def write_log(self, dataset, status="created"): """ Write log file. From d38f26dd49b8e50ba79d75b702dbd35f394f9f1a Mon Sep 17 00:00:00 2001 From: romainsacchi Date: Thu, 12 Sep 2024 16:38:11 +0200 Subject: [PATCH 4/6] Align wrt master. --- docs/load.rst | 6 +- docs/transform.rst | 113 +- premise/__init__.py | 2 +- premise/biomass.py | 70 +- .../lci-PV-perovskite.xlsx | Bin 48304 -> 48839 bytes .../additional_inventories/lci-buses.xlsx | Bin 242826 -> 244939 bytes .../additional_inventories/lci-fuel_cell.xlsx | Bin 30958 -> 32368 bytes .../additional_inventories/lci-pass_cars.xlsx | Bin 1223754 -> 1212669 bytes .../additional_inventories/lci-trucks.xlsx | Bin 300066 -> 296558 bytes .../lci-two_wheelers.xlsx | Bin 595204 -> 596700 bytes .../additional_inventories/lci-waste-CHP.xlsx | Bin 306783 -> 304593 bytes .../additional_inventories/migration_map.csv | 18 +- premise/data/consequential/leadtimes.yaml | 4 +- premise/data/consequential/lifetimes.yaml | 3 + .../coal_power_emissions_2012_v1.csv | 15724 ++++++++-------- premise/data/renewables/hydropower.yaml | 15 + .../correspondence_biosphere_flows.yaml | 2 + .../data/utils/export/simapro_categories.csv | 186 +- premise/electricity.py | 34 +- premise/export.py | 2 + premise/external.py | 65 +- premise/filesystem_constants.py | 23 +- .../electricity_variables.yaml | 4 +- .../fuels_variables.yaml | 40 +- .../steel_variables.yaml | 129 +- .../transport_bus_variables.yaml | 44 + premise/inventory_imports.py | 51 +- premise/new_database.py | 10 +- premise/transport.py | 2 - premise/utils.py | 32 +- premise/validation.py | 3 + tests/test_process_ei38_conseq.py | 82 + tests/test_process_ei38_cutoff.py | 81 + tests/test_process_ei39_conseq.py | 82 + 34 files changed, 8730 insertions(+), 8097 deletions(-) create mode 100644 premise/data/renewables/hydropower.yaml create mode 100644 tests/test_process_ei38_conseq.py create mode 100644 tests/test_process_ei38_cutoff.py create mode 100644 tests/test_process_ei39_conseq.py diff --git a/docs/load.rst b/docs/load.rst index c0d54769..0a988f5a 100644 --- a/docs/load.rst +++ b/docs/load.rst @@ -187,8 +187,10 @@ Finally, once imported, unlinked flows remain. They can be found under these hig :align: center -To link them, you need to import an additional mapping flow that you can find here -("Tools" > "Flow mapping" > "Open file"). +To link them, you need to import an additional mapping flow that you can find at the following path: +https://github.com/polca/premise/blob/master/premise/data/utils/export/flow_mapping_olca.csv + +Then, you can import this file in OpenLCA: ("Tools" > "Flow mapping" > "Open file"). .. image:: olca_fig4.png :width: 500pt diff --git a/docs/transform.rst b/docs/transform.rst index 4c54742d..d5729e16 100644 --- a/docs/transform.rst +++ b/docs/transform.rst @@ -535,19 +535,30 @@ improving its performance in the past, relative to today. Photovoltaics panels -------------------- -Photovoltaic panels are expected to improve over time. The following module efficiencies -are considered for the different types of PV panels: - - - ====================== =========== ============ =========== ======= ====== ======= - % module efficiency micro-Si single-Si multi-Si CIGS CIS CdTe - ====================== =========== ============ =========== ======= ====== ======= - 2010 10 15.1 14 11 11 10 - 2020 11.9 17.9 16.8 14 14 16.8 - 2050 12.5 26.7 24.4 23.4 23.4 21 - ====================== =========== ============ =========== ======= ====== ======= - -The sources for these efficiencies are given in the inventory file LCI_PV_: +Photovoltaic panels are expected to improve over time. The following module efficiencies (mena, minimum, maximum) +are considered for the different types of PV panels, applied as a triangular distribution on the panel surface +required to reach the peak power output of the dataset: + +===================== ==================== ==================== =================== ================== ================== ================= ================== ================== ========================================= + module efficiency micro-Si single-Si multi-Si CIGS CIS CdTe GaAs perovskite Source +===================== ==================== ==================== =================== ================== ================== ================= ================== ================== ========================================= + 2010 10.0 (7.5-12.5) 15.0 (11.3-18.9) 14.0 (10.5-17.5) 11.0 (8.3-13.8) 11.0 (8.3-13.8) 10.0 (8.8-12.0) 28.0 (21.0-35.0) 25.0 (19.0-31.0) [1], [2], [3], [4], [5], [6], [7], [8] + 2020 11.9 (9.0-15.0) 17.9 (13.0-22.0) 16.8 (12.0-21.0) 14.0 (10.5-18.0) 14.0 (10.5-18.0) 16.8 (13.0-21.0) 28.0 (21.0-35.0) 25.0 (19.0-31.0) [1], [2], [3], [4], [5], [6], [7], [8] + 2023 - 22.0 (17.0-24.0) - 15.0 (11.3-19.0) - 19.0 (15.0-20.0) - - [2], [4], [6] + 2050 12.5 (9.0-16.0) 26.7 (20.0-34.0) 24.4 (16.0-30.0) 23.4 (17.3-29.0) 23.4 (17.3-29.0) 21.0 (17.5-25.0) 28.0 (25.0-28.0) 25.0 (22.0-31.0) [1], [2], [3], [4], [5], [6], [7], [8] +===================== ==================== ==================== =================== ================== ================== ================= ================== ================== ========================================= + +.. [1] https://www.ise.fraunhofer.de/content/dam/ise/de/documents/publications/studies/Photovoltaics-Report.pdf +.. [2] https://www.ise.fraunhofer.de/content/dam/ise/de/documents/publications/studies/Photovoltaics-Report.pdf +.. [3] https://www.ise.fraunhofer.de/content/dam/ise/de/documents/publications/studies/Photovoltaics-Report.pdf +.. [4] https://www.ise.fraunhofer.de/content/dam/ise/de/documents/publications/studies/Photovoltaics-Report.pdf. For future efficiency: own assumption, -+25%. +.. [5] Future eff: Fraunhofer ISE Photovoltaics Report 2019; Uncertainty: Own assumption: -+25%. +.. [6] https://www.sciencedirect.com/science/article/pii/S0927024823001101 +.. [7] https://link.springer.com/article/10.1007/s11367-020-01791-z +.. [8] https://pubs.rsc.org/en/content/articlelanding/2022/se/d2se00096b; https://www.csem.ch/en/news/photovoltaic-technology-breakthrough-achieving-31.25-efficiency/ + + +The sources for these efficiencies are also given in the inventory file LCI_PV_: .. _LCI_PV: https://github.com/polca/premise/blob/master/premise/data/additional_inventories/lci-PV.xlsx @@ -847,9 +858,45 @@ depends on the location of the consumer. Cement production +++++++++++++++++ -The modelling of future improvements in the cement sector is relatively -simple at the moment, and does not involve the emergence of new -technologies (e.g., electric kilns). +The modelling of future improvements in the cement sector is dependent on the IAM model chosen. + +When choosing IMAGE, scenarios include the emergence of a new, more efficient kiln, as well +as kilns fitted with three types of carbon capture technologies: + +* using monoethanolamine (MEA) as a solvent, +* using oxyfuel combustion, +* using Direct Separation (Leilac process). + +The implementation of the corresponding datasets for these new kiln technologies are based on the work of +Muller_ et al., 2024. + +.. _Muller: https://doi.org/10.1016/j.jclepro.2024.141884 + +We differ slightly from the implementation of Muller_ et al., 2024, in that: + +* the heat necessary for the regeneration of the MEA solvent is assumed to be provided by a natural gas boiler (instead of a fuel mix resembling that of the kiln itself), with up to 30% coming from recovered heat from the kiln by 2050, +* the amount of heat needed for the regeneration of the MEA solvent goes from 3.76 GJ/ton CO2 in 2020, to 2.6 GJ/ton CO2 in 2050, +* the provision of oxygen for the Direct Separation option comes from an existing air separation dataset from ecoinvent, +* the fuel mix for the kiln is that of ecoinvent, further scaled down by the change of efficiency of the kiln (in Müller et al., 2024, they use directly the fuel mix provided by the IMAGE scenario, which we do not find representative, as it also includes the fuel used by other activities in the non-metallic minerals, notably a large share of natural gas). + +In a nutshell, *premise*: + +* makes copies of the `clinker production` dataset, +* adjusts the fuel consumption and related CO2 emissions, +* adjusts specific hot pollutant emissions removed by the carbon capture process (Mercury, NOx, SOx), +* adds an input from the carbon capture process, based on a capture efficiency share, +* and removes a corresponding amount from the outgoing CO2 emissions. + +The Direct Separation process only captures calcination emissions, while the other two technologies capture +both combustion and calcination emissions. + +When choosing another IAM, the current implementation is relatively +simpler at the moment, and does not involve the emergence of new +technologies. In these scenarios, the production volumes of kilns +equipped with CCS is not given. Instead, the share of CO2 emissions +that is sequestered is given. We use the ratio of the CO2 emissions +sequestered over the total CO2 emissions to determine the share of +the CO2 emissions that is sequestered in the clinker production dataset Run @@ -887,17 +934,9 @@ Efficiency adjustment --------------------- *premise* then adjusts the thermal efficiency of the process. -It does so by calculating the technology-weighted energy requirements -per ton of clinker. -Based on GNR/IEA roadmap data, *premise* uses: - -* the share of kiln technology for a given region today (2020): - * wet, - * dry, - * dry with pre-heater, - * and dry with pre-heater and pre-calciner -* the energy requirement for each of these technologies today (2020). +It first calculates the energy input in teh current (original) dataset, +by looking up the fuel inputs and their respective lower heating values. Once the energy required per ton clinker today (2020) is known, it is multiplied by a *scaling factor* that represents a change in efficiency @@ -916,15 +955,16 @@ between today and the scenario year. .. note:: *premise* enforces a lower limit on the fuel consumption per ton of clinker. - This limit is set to 2.8 GJ/t clinker and corresponds to the minimum + This limit is set to 3.1 GJ/t clinker and is close to the minimum theoretical fuel consumption with an moisture content of the raw materials, - as considered in the 2018 IEA_ cement roadmap report. Hence, regardless of the - scaling factor, the fuel consumption per ton of clinker will never be less than - 2.8 GJ/t. + as considered in the 2018 IEA_ cement roadmap report (i.e., 2.8 GJ/t clinker). + Hence, regardless of the scaling factor, the fuel consumption per ton of clinker + will never be less than 3.1 GJ/t. .. _IEA: https://iea.blob.core.windows.net/assets/cbaa3da1-fd61-4c2a-8719-31538f59b54f/TechnologyRoadmapLowCarbonTransitionintheCementIndustry.pdf + Once the new energy input is determined, *premise* scales down the fuel, and the fossil and biogenic CO2 emissions accordingly, based on the Lower Heating Value and CO2 emission factors for these fuels. @@ -943,22 +983,21 @@ If the IAM scenario indicates that a share of the CO2 emissions for the cement sector in a given region and year is sequestered and stored, *premise* adds CCS to the corresponding clinker production dataset. -The CCS dataset used to that effect is from Meunier_ et al., 2020. -The dataset described the capture of CO2 from a cement plant. +The CCS dataset used to that effect is from Muller_ et al., 2024. +The dataset described the capture of CO2 from a cement plant, +using a monoethanolamine-based sorbent. To that dataset, *premise* adds another dataset that models the storage of the CO2 underground, from Volkart_ et al, 2013. Besides electricity, the CCS process requires heat, water and others inputs to regenerate the amine-based sorbent. We use two data points to approximate the heat -requirement: 3.66 MJ/kg CO2 captured in 2020, and 2.6 MJ/kg in 2050. -The first number is from Meunier_ et al., 2020, while the second number is described +requirement: 3.76 MJ/kg CO2 captured in 2020 (minus 30% coming from the kiln as recovered heat), +and 2.6 MJ/kg in 2050. The first number is from Muller_ et al., 2024, while the second number is described as the best-performing pilot project today, according to the 2022 review of pilot projects by the Global CCS Institute_. It is further assumed that the heat requirement -is fulfilled to an extent of 15% by the recovery of excess heat, as mentioned in -the 2018 IEA_ cement roadmap report. +is fulfilled to an extent of 30% by the recovery of excess heat, as found in numerous studies. -.. _Meunier: https://www.sciencedirect.com/science/article/pii/S0960148119310304 .. _Volkart: https://doi.org/10.1016/j.ijggc.2013.03.003 .. _Institute: https://www.globalccsinstitute.com/wp-content/uploads/2022/05/State-of-the-Art-CCS-Technologies-2022.pdf diff --git a/premise/__init__.py b/premise/__init__.py index ea53423b..1009466c 100644 --- a/premise/__init__.py +++ b/premise/__init__.py @@ -5,7 +5,7 @@ "clear_inventory_cache", "get_regions_definition", ) -__version__ = (2, 1, 1, "dev9") +__version__ = (2, 1, 3) from premise.new_database import NewDatabase diff --git a/premise/biomass.py b/premise/biomass.py index 1d050649..8d173fdd 100644 --- a/premise/biomass.py +++ b/premise/biomass.py @@ -163,31 +163,38 @@ def create_biomass_markets(self) -> None: if v in self.iam_data.production_volumes.variables.values ] + if self.year in self.iam_data.production_volumes.coords["year"].values: + total_prod_vol = np.clip( + ( + self.iam_data.production_volumes.sel( + variables=available_biomass_vars, + region=region, + year=self.year, + ).sum(dim="variables") + ), + 1e-6, + None, + ) + else: + total_prod_vol = np.clip( + ( + self.iam_data.production_volumes.sel( + variables=available_biomass_vars, region=region + ) + .interp(year=self.year) + .sum(dim="variables") + ), + 1e-6, + None, + ) + for biomass_type, biomass_act in biomass_map.items(): - if self.year in self.iam_data.production_volumes.coords["year"].values: - total_prod_vol = np.clip( - ( - self.iam_data.production_volumes.sel( - variables=available_biomass_vars, - region=region, - year=self.year, - ).sum(dim="variables") - ), - 1e-6, - None, - ) - else: - total_prod_vol = np.clip( - ( - self.iam_data.production_volumes.sel( - variables=available_biomass_vars, region=region - ) - .interp(year=self.year) - .sum(dim="variables") - ), - 1e-6, - None, - ) + + if ( + total_prod_vol < 1e-5 + and biomass_type != "biomass crops - purpose grown" + ): + continue if biomass_type in available_biomass_vars: if ( @@ -227,6 +234,12 @@ def create_biomass_markets(self) -> None: else: share = 0 + if ( + total_prod_vol < 1e-5 + and biomass_type == "biomass crops - purpose grown" + ): + share = 1 + if share > 0: ecoinvent_regions = self.geo.iam_to_ecoinvent_location( dataset["location"] @@ -288,6 +301,15 @@ def create_biomass_markets(self) -> None: } ) + # check that dataset has exchanges + number_tech_exchanges = len( + [exc for exc in dataset["exchanges"] if exc["type"] == "technosphere"] + ) + if number_tech_exchanges == 0: + raise ValueError( + f"Dataset {dataset['name']} has no technosphere exchanges." + ) + self.database.append(dataset) # add log diff --git a/premise/data/additional_inventories/lci-PV-perovskite.xlsx 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zybBGSz!1;bW2h2DF$^0g;CwceP~G7Tw$vmCvyLSvwhbEU#OPQ|&Qb~ya>C-gNf!(r zY%=%?V%SwbWA)gtTOnpFh^Su&nj4}4FD@V=1CD=_+`$~;wGB{HFn3>C|Fn@r9tUFw zh%S=0oI-?{my7;*L@kqx?&%__b_1Y#j7F);_0&m}Nvx~4Y~D@SFszO`a_z%e@~)jc zv4cX0L=wAjrh8b`mtbR~?y!7ZmOFlgN{N=yO=6Dzt6^93)n|rt(Iehz;x6exEJ%{Q z6qtja5X?Sgy;b!7U!t~}{(|v_MntFlyzqd5fQU@rDS%Oe{E^O92*XU=wBu4^rv?E* z_Z12PAADZq|Nc%)+P^FcCKjZ&9A0q+*Ev*L8S5*Q(= 2020: @@ -1384,6 +1385,37 @@ def generate_world_market( return dataset + def correct_hydropower_water_emissions(self) -> None: + """ + Correct the emissions of water for hydropower plants. + In Swiss datasets, water evaoporation is too high. + We use a new factor from Flury and Frischknecht (2021) to correct this. + https://treeze.ch/fileadmin/user_upload/downloads/Publications/Case_Studies/Energy/flury-2012-hydroelectric-power-generation.pdf + """ + + water_factor = get_water_consumption_factors() + + hydropower_datasets = ws.get_many( + self.database, + *[ + ws.contains("name", "electricity production, hydro, reservoir"), + ws.equals("location", "CH"), + ws.equals("unit", "kilowatt hour"), + ], + ) + + for name, flows in water_factor.items(): + for dataset in hydropower_datasets: + if name in dataset["name"]: + for flow in flows: + for exc in ws.biosphere( + dataset, + ws.equals("name", flow["name"]), + ws.equals("unit", flow["unit"]), + ws.equals("categories", (flow["categories"],)), + ): + exc["amount"] = flow["amount"] + def update_efficiency_of_solar_pv(self) -> None: """ Update the efficiency of solar PV modules. diff --git a/premise/export.py b/premise/export.py index 0869fb8b..69cbfa19 100644 --- a/premise/export.py +++ b/premise/export.py @@ -888,6 +888,8 @@ def generate_superstructure_db( # should not be any, but just in case before = len(df) df = df.drop_duplicates() + # detect duplicate based on `from key` and `to key` + df = df.drop_duplicates(subset=["from key", "to key"]) after = len(df) print(f"Dropped {before - after} duplicate(s).") diff --git a/premise/external.py b/premise/external.py index 2d7a1fa4..298dbde0 100644 --- a/premise/external.py +++ b/premise/external.py @@ -1480,33 +1480,44 @@ def redefine_loc(e): if len(new_loc) > 0: for loc, share in new_loc: # add new exchange - new_exchanges.append( - { - "amount": exc["amount"] * ratio * share, - "type": "technosphere", - "unit": exc["unit"], - "location": loc, - "name": new_name, - "product": new_ref, - "uncertainty type": exc.get("uncertainty type", 0), - "loc": redefine_loc(exc), - "scale": ( - exc.get("scale", 0) if "scale" in exc else None - ), - "minimum": ( - exc.get("minimum", 0) - * (exc["amount"] * ratio * share / exc["amount"]) - if "minimum" in exc - else None - ), - "maximum": ( - exc.get("maximum", 0) - * (exc["amount"] * ratio * share / exc["amount"]) - if "maximum" in exc - else None - ), - } - ) + if exc["amount"] * ratio * share != 0: + new_exchanges.append( + { + "amount": exc["amount"] * ratio * share, + "type": "technosphere", + "unit": exc["unit"], + "location": loc, + "name": new_name, + "product": new_ref, + "uncertainty type": exc.get("uncertainty type", 0), + "loc": redefine_loc(exc), + "scale": ( + exc.get("scale", 0) if "scale" in exc else None + ), + "minimum": ( + exc.get("minimum", 0) + * ( + exc["amount"] + * ratio + * share + / exc["amount"] + ) + if "minimum" in exc + else None + ), + "maximum": ( + exc.get("maximum", 0) + * ( + exc["amount"] + * ratio + * share + / exc["amount"] + ) + if "maximum" in exc + else None + ), + } + ) if isfuel: fuel_amount += exc["amount"] * ratio * share diff --git a/premise/filesystem_constants.py b/premise/filesystem_constants.py index ea865457..7f6c95e7 100644 --- a/premise/filesystem_constants.py +++ b/premise/filesystem_constants.py @@ -5,6 +5,20 @@ from pathlib import Path import platformdirs +import yaml + + +def load_var_file(): + """Check if the variable file exists and load it.""" + var_file = Path.cwd() / "variables.yaml" + if var_file.exists(): + with open(var_file, "r") as f: + return yaml.safe_load(f) + else: + return None + + +VARIABLES = load_var_file() or {} # Directories for data which comes with Premise DATA_DIR = Path(__file__).resolve().parent / "data" @@ -12,8 +26,13 @@ VARIABLES_DIR = Path(__file__).resolve().parent / "iam_variables_mapping" IAM_OUTPUT_DIR = DATA_DIR / "iam_output_files" -# Directories for user-created data -USER_DATA_BASE_DIR = platformdirs.user_data_path(appname="premise", appauthor="pylca") +if "USER_DATA_BASE_DIR" in VARIABLES: + USER_DATA_BASE_DIR = Path(VARIABLES.get("USER_DATA_BASE_DIR")) + print(f"USER_DATA_BASE_DIR: {USER_DATA_BASE_DIR}") +else: + USER_DATA_BASE_DIR = platformdirs.user_data_path( + appname="premise", appauthor="pylca" + ) USER_DATA_BASE_DIR.mkdir(parents=True, exist_ok=True) DIR_CACHED_DB = USER_DATA_BASE_DIR / "cache" diff --git a/premise/iam_variables_mapping/electricity_variables.yaml b/premise/iam_variables_mapping/electricity_variables.yaml index 71189267..7641243f 100644 --- a/premise/iam_variables_mapping/electricity_variables.yaml +++ b/premise/iam_variables_mapping/electricity_variables.yaml @@ -10,7 +10,7 @@ Biogas CHP: eff_aliases: tiam-ucl: Efficiency|Electricity|Biogas|w/o CCS iam_aliases: - tiam-ucl: Electricity|Biogas|w/o CCS + tiam-ucl: Secondary Energy|Electricity|Biogas|w/o CCS max_efficiency: 0.6 Biomass CHP: ecoinvent_aliases: @@ -32,7 +32,7 @@ Biomass CHP: iam_aliases: image: Secondary Energy|Electricity|Biomass|w/o CCS|3 remind: SE|Electricity|Biomass|++|Combined Heat and Power w/o CC - tiam-ucl: Electricity|Biomass CHP|w/o CCS + tiam-ucl: Secondary Energy|Electricity|Biomass CHP|w/o CCS max_efficiency: 0.3 Biomass CHP (existing): ecoinvent_aliases: diff --git a/premise/iam_variables_mapping/fuels_variables.yaml b/premise/iam_variables_mapping/fuels_variables.yaml index 0d5feb42..fdb9f6b8 100644 --- a/premise/iam_variables_mapping/fuels_variables.yaml +++ b/premise/iam_variables_mapping/fuels_variables.yaml @@ -202,7 +202,7 @@ biomethane: co2: 0.06 biogenic_share: 1 iam_aliases: - # tiam-ucl: Secondary Energy|Liquids|Biomass|Biomethane + tiam-ucl: Secondary Energy|Liquids|Biomass|Biomethane|Biogas remind: SE|Gases|+|Biomass eff_aliases: remind: Tech|Gases|Biomass|w/o CC|Efficiency @@ -394,7 +394,7 @@ diesel, synthetic, from coal: tiam-ucl: Efficiency|Liquids|Coal|FT fuel mix (diesel, kerosene, naptha, ELC)|w/o CCS gcam: Efficiency|Coal to Liquids|w/oCCS iam_aliases: - tiam-ucl: Secondary Energy|Liquids|Coal|FT Diesel|w/o CCS + tiam-ucl: Secondary Energy|Liquids|Coal|FT|Diesel|w/o CCS gcam: Secondary Energy|Production|Coal to Liquids|w/oCCS remind: SE|Liquids|Fossil|Coal|+|w/o CC ecoinvent_aliases: @@ -410,7 +410,7 @@ diesel, synthetic, from coal, with CCS: tiam-ucl: Efficiency|Liquids|Coal|FT fuel mix (diesel, kerosene, naptha, ELC)|w CCS gcam: Efficiency|Coal to Liquids|w/CCS iam_aliases: - tiam-ucl: Secondary Energy|Liquids|Coal|FT Diesel|w CCS + tiam-ucl: Secondary Energy|Liquids|Coal|FT|Diesel|w CCS gcam: Secondary Energy|Production|Coal to Liquids|w/CCS remind: SE|Liquids|Fossil|Coal|+|w/ CC ecoinvent_aliases: @@ -423,7 +423,7 @@ diesel, synthetic, from wood: co2: 0.0732 biogenic_share: 1 iam_aliases: - tiam-ucl: Secondary Energy|Liquids|Biomass residues|FT Diesel|w/o CCS + tiam-ucl: Secondary Energy|Liquids|Biomass|FT|Diesel|w/o CCS gcam: Secondary Energy|Production|Refined Liquids|Biomass|FT Biofuels|w/oCCS remind: SE|Liquids|Biomass|BioFTR|w/o CC image: Secondary Energy|Consumption|Liquids|Biomass|FT Diesel|Woody|w/oCCS @@ -440,7 +440,7 @@ diesel, synthetic, from wood, with CCS: co2: 0.0732 biogenic_share: 1 iam_aliases: - tiam-ucl: Secondary Energy|Liquids|Biomass residues|FT Diesel|w CCS + tiam-ucl: Secondary Energy|Liquids|Biomass|FT|Diesel|w CCS gcam: Secondary Energy|Production|Refined Liquids|Biomass|FT Biofuels|w/CCS remind: SE|Liquids|Biomass|BioFTR|w/ CC image: Secondary Energy|Consumption|Liquids|Biomass|FT Diesel|Woody|w/CCS @@ -485,7 +485,7 @@ diesel, synthetic, from natural gas: co2: 0.0732 biogenic_share: 0 iam_aliases: - tiam-ucl: Secondary Energy|Liquids|Natural Gas|FT Diesel|w/o CCS + tiam-ucl: Secondary Energy|Liquids|Natural Gas|FT|Diesel|w/o CCS eff_aliases: tiam-ucl: Efficiency|Liquids|Natural gas|FT fuel mix (diesel, kerosene, naptha, ELC)|w/o CCS ecoinvent_aliases: @@ -497,7 +497,7 @@ diesel, synthetic, from natural gas, with CCS: co2: 0.0732 biogenic_share: 0 iam_aliases: - tiam-ucl: Secondary Energy|Liquids|Natural Gas|FT Diesel|w CCS + tiam-ucl: Secondary Energy|Liquids|Natural Gas|FT|Diesel|w CCS eff_aliases: tiam-ucl: Efficiency|Liquids|Natural gas|FT fuel mix (diesel, kerosene, naptha, ELC)|w CCS ecoinvent_aliases: @@ -1039,14 +1039,14 @@ liquefied petroleum gas: - liquefied petroleum gas production, petroleum refinery operation - market for liquefied petroleum gas iam_aliases: - tiam-ucl: Secondary Energy|Liquids|Oil|LPG + tiam-ucl: Secondary Energy|Liquids|Oil|Liquid Petroleum Gas liquefied petroleum gas, synthetic, from natural gas: lhv: 45.5 co2: 0.0631 biogenic_share: 0 iam_aliases: - tiam-ucl: Secondary Energy|Liquids|Natural Gas|FT LPG|w/o CCS + tiam-ucl: Secondary Energy|Liquids|Natural Gas|FT|Liquid Petroleum Gas|w/o CCS ecoinvent_aliases: fltr: - liquefied petroleum gas production, synthetic, Fischer Tropsch process, from natural gas, energy allocation @@ -1058,7 +1058,7 @@ liquefied petroleum gas, synthetic, from natural gas, with CCS: co2: 0.0631 biogenic_share: 0 iam_aliases: - tiam-ucl: Secondary Energy|Liquids|Natural Gas|FT LPG|w CCS + tiam-ucl: Secondary Energy|Liquids|Natural Gas|FT|Liquid Petroleum Gas|w CCS ecoinvent_aliases: fltr: - liquefied petroleum gas production, synthetic, Fischer Tropsch process, from natural gas, energy allocation, with carbon capture and storage @@ -1070,7 +1070,7 @@ liquefied petroleum gas, synthetic, from biomass: co2: 0.0631 biogenic_share: 1 iam_aliases: - tiam-ucl: Secondary Energy|Liquids|Biomass|FT LPG|w/o CCS + tiam-ucl: Secondary Energy|Liquids|Biomass|FT|Liquid Petroleum Gas|w/o CCS ecoinvent_aliases: fltr: - liquefied petroleum gas production, synthetic, Fischer Tropsch process, hydrogen from wood gasification, energy allocation @@ -1082,7 +1082,7 @@ liquefied petroleum gas, synthetic, from biomass, with CCS: co2: 0.0631 biogenic_share: 1 iam_aliases: - tiam-ucl: Secondary Energy|Liquids|Biomass|FT LPG|w CCS + tiam-ucl: Secondary Energy|Liquids|Biomass|FT|Liquid Petroleum Gas|w CCS ecoinvent_aliases: fltr: - liquefied petroleum gas production, synthetic, Fischer Tropsch process, hydrogen from wood gasification, energy allocation, with carbon capture and storage @@ -1098,7 +1098,7 @@ liquefied petroleum gas, synthetic, from coal: name: synthetic fuel production, from coal, high temperature Fisher-Tropsch operations reference product: liquefied petroleum gas iam_aliases: - tiam-ucl: Secondary Energy|Liquids|Coal|FT LPG|w/o CCS + tiam-ucl: Secondary Energy|Liquids|Coal|FT|Liquid Petroleum Gas|w/o CCS eff_aliases: tiam-ucl: Efficiency|Liquids|Coal|FT fuel mix (diesel, kerosene, naptha, ELC)|w/o CCS @@ -1108,7 +1108,7 @@ liquefied petroleum gas, synthetic, from coal, with CCS: co2: 0.0631 biogenic_share: 0 iam_aliases: - tiam-ucl: Secondary Energy|Liquids|Coal|FT LPG|w CCS + tiam-ucl: Secondary Energy|Liquids|Coal|FT|Liquid Petroleum Gas|w CCS ecoinvent_aliases: fltr: - liquefied petroleum gas production, synthetic, Fischer Tropsch process, from coal, energy allocation, with carbon capture and storage @@ -1310,7 +1310,7 @@ kerosene, synthetic, from coal, energy allocation: fltr: - kerosene production, synthetic, Fischer Tropsch process, hydrogen from coal gasification, energy allocation iam_aliases: - tiam-ucl: Secondary Energy|Liquids|Coal|FT Kerosene|w/o CCS + tiam-ucl: Secondary Energy|Liquids|Coal|FT|Kerosene|w/o CCS eff_aliases: tiam-ucl: Efficiency|Liquids|Coal|FT fuel mix (diesel, kerosene, naptha, ELC)|w/o CCS @@ -1330,7 +1330,7 @@ kerosene, synthetic, from coal, energy allocation, with CCS: fltr: - kerosene production, synthetic, Fischer Tropsch process, hydrogen from coal gasification, with CCS, energy allocation iam_aliases: - tiam-ucl: Secondary Energy|Liquids|Coal|FT Kerosene|w CCS + tiam-ucl: Secondary Energy|Liquids|Coal|FT|Kerosene|w CCS eff_aliases: tiam-ucl: Efficiency|Liquids|Coal|FT fuel mix (diesel, kerosene, naptha, ELC)|w CCS @@ -1348,7 +1348,7 @@ kerosene, synthetic, from biomass, energy allocation: co2: 0.0715 biogenic_share: 1 iam_aliases: - tiam-ucl: Secondary Energy|Liquids|Biomass|FT Kerosene|w/o CCS + tiam-ucl: Secondary Energy|Liquids|Biomass|FT|Kerosene|w/o CCS eff_aliases: tiam-ucl: Efficiency|Liquids|Biomass|FT fuel mix (diesel, kerosene, naptha, ELC)|w/o CCS ecoinvent_aliases: @@ -1360,7 +1360,7 @@ kerosene, synthetic, from biomass, energy allocation, with CCS: co2: 0.0715 biogenic_share: 1 iam_aliases: - tiam-ucl: Secondary Energy|Liquids|Biomass|FT Kerosene|w CCS + tiam-ucl: Secondary Energy|Liquids|Biomass|FT|Kerosene|w CCS eff_aliases: tiam-ucl: Efficiency|Liquids|Biomass|FT fuel mix (diesel, kerosene, naptha, ELC)|w CCS ecoinvent_aliases: @@ -1372,7 +1372,7 @@ kerosene, synthetic, from natural gas, energy allocation: co2: 0.0715 biogenic_share: 1 iam_aliases: - tiam-ucl: Secondary Energy|Liquids|Natural Gas|FT Kerosene|w/o CCS + tiam-ucl: Secondary Energy|Liquids|Natural Gas|FT|Kerosene|w/o CCS eff_aliases: tiam-ucl: Efficiency|Liquids|Natural gas|FT fuel mix (diesel, kerosene, naptha, ELC)|w/o CCS ecoinvent_aliases: @@ -1384,7 +1384,7 @@ kerosene, synthetic, from natural gas, energy allocation, with CCS: co2: 0.0715 biogenic_share: 1 iam_aliases: - tiam-ucl: Secondary Energy|Liquids|Natural Gas|FT Kerosene|w CCS + tiam-ucl: Secondary Energy|Liquids|Natural Gas|FT|Kerosene|w CCS eff_aliases: tiam-ucl: Efficiency|Liquids|Natural gas|FT fuel mix (diesel, kerosene, naptha, ELC)|w CCS ecoinvent_aliases: diff --git a/premise/iam_variables_mapping/steel_variables.yaml b/premise/iam_variables_mapping/steel_variables.yaml index 844fad24..a4b86a41 100644 --- a/premise/iam_variables_mapping/steel_variables.yaml +++ b/premise/iam_variables_mapping/steel_variables.yaml @@ -41,57 +41,57 @@ steel - primary: - Final Energy|Industry|Steel|Primary|Gas - Final Energy|Industry|Steel|Primary|Biomass tiam-ucl: - - Final Energy|Production|Steel|Primary|BF and BOF 1|w CCS|Biofuels - - Final Energy|Production|Steel|Primary|BF and BOF 1|w CCS|Blast Furnace Gas - - Final Energy|Production|Steel|Primary|BF and BOF 1|w CCS|Coal - - Final Energy|Production|Steel|Primary|BF and BOF 1|w CCS|Coke Oven Coke - - Final Energy|Production|Steel|Primary|BF and BOF 1|w CCS|Coke Oven Gas - - Final Energy|Production|Steel|Primary|BF and BOF 1|w CCS|Electricity - - Final Energy|Production|Steel|Primary|BF and BOF 1|w CCS|Heat - - Final Energy|Production|Steel|Primary|BF and BOF 1|w CCS|Heavy Fuel Oil - - Final Energy|Production|Steel|Primary|BF and BOF 1|w CCS|Liquified Petroleum Gases - - Final Energy|Production|Steel|Primary|BF and BOF 1|w CCS|Natural Gas Mix - - Final Energy|Production|Steel|Primary|BF and BOF 1|w CCS|Petroleum Coke - - Final Energy|Production|Steel|Primary|BF and BOF 1|w CCS|Refined Petroleum Products (Oil) - - Final Energy|Production|Steel|Primary|BF and BOF 1|w/o CCS|Biofuels - - Final Energy|Production|Steel|Primary|BF and BOF 1|w/o CCS|Blast Furnace Gas - - Final Energy|Production|Steel|Primary|BF and BOF 1|w/o CCS|Coal - - Final Energy|Production|Steel|Primary|BF and BOF 1|w/o CCS|Coke Oven Coke - - Final Energy|Production|Steel|Primary|BF and BOF 1|w/o CCS|Coke Oven Gas - - Final Energy|Production|Steel|Primary|BF and BOF 1|w/o CCS|Electricity - - Final Energy|Production|Steel|Primary|BF and BOF 1|w/o CCS|Heat - - Final Energy|Production|Steel|Primary|BF and BOF 1|w/o CCS|Heavy Fuel Oil - - Final Energy|Production|Steel|Primary|BF and BOF 1|w/o CCS|Liquified Petroleum Gases - - Final Energy|Production|Steel|Primary|BF and BOF 1|w/o CCS|Natural Gas Mix - - Final Energy|Production|Steel|Primary|BF and BOF 1|w/o CCS|Petroleum Coke - - Final Energy|Production|Steel|Primary|BF and BOF 1|w/o CCS|Refined Petroleum Products (Oil) + - Final Energy|Production|Steel|Primary|BF and BOF 1|Biofuels|w CCS + - Final Energy|Production|Steel|Primary|BF and BOF 1|Blast Furnace Gas|w CCS + - Final Energy|Production|Steel|Primary|BF and BOF 1|Blast Furnace Gas|w/o CCS + - Final Energy|Production|Steel|Primary|BF and BOF 1|Coal|w CCS + - Final Energy|Production|Steel|Primary|BF and BOF 1|Coal|w/o CCS + - Final Energy|Production|Steel|Primary|BF and BOF 1|Coke Oven Coke|w CCS + - Final Energy|Production|Steel|Primary|BF and BOF 1|Coke Oven Coke|w/o CCS + - Final Energy|Production|Steel|Primary|BF and BOF 1|Coke Oven Gas|w CCS + - Final Energy|Production|Steel|Primary|BF and BOF 1|Coke Oven Gas|w/o CCS + - Final Energy|Production|Steel|Primary|BF and BOF 1|Electricity|w CCS + - Final Energy|Production|Steel|Primary|BF and BOF 1|Electricity|w/o CCS + - Final Energy|Production|Steel|Primary|BF and BOF 1|Heat|w CCS + - Final Energy|Production|Steel|Primary|BF and BOF 1|Heat|w/o CCS + - Final Energy|Production|Steel|Primary|BF and BOF 1|Heavy Fuel Oil|w CCS + - Final Energy|Production|Steel|Primary|BF and BOF 1|Liquefied Petroleum Gas|w CCS + - Final Energy|Production|Steel|Primary|BF and BOF 1|Natural Gas|w CCS + - Final Energy|Production|Steel|Primary|BF and BOF 1|Natural Gas|w/o CCS + - Final Energy|Production|Steel|Primary|BF and BOF 1|Oil|w CCS + - Final Energy|Production|Steel|Primary|BF and BOF 1|Oil|w/o CCS + - Final Energy|Production|Steel|Primary|BF and BOF 1|Petroleum Coke|w CCS - Final Energy|Production|Steel|Primary|BF and BOF 2|Blast Furnace Gas - Final Energy|Production|Steel|Primary|BF and BOF 2|Coal - Final Energy|Production|Steel|Primary|BF and BOF 2|Coke Oven Coke - Final Energy|Production|Steel|Primary|BF and BOF 2|Coke Oven Gas - Final Energy|Production|Steel|Primary|BF and BOF 2|Electricity - - Final Energy|Production|Steel|Primary|BF and BOF 2|Heat - - Final Energy|Production|Steel|Primary|BF and BOF 2|Natural Gas Mix - - Final Energy|Production|Steel|Primary|BF and BOF 2|Refined Petroleum Products (Oil) - - Final Energy|Production|Steel|Primary|BF and BOF 3|w CCS|Biofuels - - Final Energy|Production|Steel|Primary|BF and BOF 3|w CCS|Blast Furnace Gas - - Final Energy|Production|Steel|Primary|BF and BOF 3|w CCS|Coal - - Final Energy|Production|Steel|Primary|BF and BOF 3|w CCS|Coke Oven Coke - - Final Energy|Production|Steel|Primary|BF and BOF 3|w CCS|Coke Oven Gas - - Final Energy|Production|Steel|Primary|BF and BOF 3|w CCS|Electricity - - Final Energy|Production|Steel|Primary|BF and BOF 3|w CCS|Heat - - Final Energy|Production|Steel|Primary|BF and BOF 3|w CCS|Heavy Fuel Oil - - Final Energy|Production|Steel|Primary|BF and BOF 3|w CCS|Liquified Petroleum Gases - - Final Energy|Production|Steel|Primary|BF and BOF 3|w CCS|Natural Gas Mix - - Final Energy|Production|Steel|Primary|BF and BOF 3|w CCS|Petroleum Coke - - Final Energy|Production|Steel|Primary|BF and BOF 3|w CCS|Refined Petroleum Products (Oil) - - Final Energy|Production|Steel|Primary|BF and BOF 3|w/o CCS|Blast Furnace Gas - - Final Energy|Production|Steel|Primary|BF and BOF 3|w/o CCS|Coal - - Final Energy|Production|Steel|Primary|BF and BOF 3|w/o CCS|Coke Oven Coke - - Final Energy|Production|Steel|Primary|BF and BOF 3|w/o CCS|Coke Oven Gas - - Final Energy|Production|Steel|Primary|BF and BOF 3|w/o CCS|Electricity - - Final Energy|Production|Steel|Primary|BF and BOF 3|w/o CCS|Natural Gas Mix - - Final Energy|Production|Steel|Primary|BF and BOF 3|w/o CCS|Refined Petroleum Products (Oil) + - Final Energy|Production|Steel|Primary|BF and BOF 2|Natural Gas + - Final Energy|Production|Steel|Primary|BF and BOF 2|Oil + - Final Energy|Production|Steel|Primary|BF and BOF 3|Biofuels|w CCS + - Final Energy|Production|Steel|Primary|BF and BOF 3|Biofuels|w/o CCS + - Final Energy|Production|Steel|Primary|BF and BOF 3|Blast Furnace Gas|w CCS + - Final Energy|Production|Steel|Primary|BF and BOF 3|Blast Furnace Gas|w/o CCS + - Final Energy|Production|Steel|Primary|BF and BOF 3|Coal|w CCS + - Final Energy|Production|Steel|Primary|BF and BOF 3|Coal|w/o CCS + - Final Energy|Production|Steel|Primary|BF and BOF 3|Coke Oven Coke|w CCS + - Final Energy|Production|Steel|Primary|BF and BOF 3|Coke Oven Coke|w/o CCS + - Final Energy|Production|Steel|Primary|BF and BOF 3|Coke Oven Gas|w CCS + - Final Energy|Production|Steel|Primary|BF and BOF 3|Coke Oven Gas|w/o CCS + - Final Energy|Production|Steel|Primary|BF and BOF 3|Electricity|w CCS + - Final Energy|Production|Steel|Primary|BF and BOF 3|Electricity|w/o CCS + - Final Energy|Production|Steel|Primary|BF and BOF 3|Heat|w CCS + - Final Energy|Production|Steel|Primary|BF and BOF 3|Heat|w/o CCS + - Final Energy|Production|Steel|Primary|BF and BOF 3|Heavy Fuel Oil|w CCS + - Final Energy|Production|Steel|Primary|BF and BOF 3|Heavy Fuel Oil|w/o CCS + - Final Energy|Production|Steel|Primary|BF and BOF 3|Liquefied Petroleum Gas|w CCS + - Final Energy|Production|Steel|Primary|BF and BOF 3|Liquefied Petroleum Gas|w/o CCS + - Final Energy|Production|Steel|Primary|BF and BOF 3|Natural Gas|w CCS + - Final Energy|Production|Steel|Primary|BF and BOF 3|Natural Gas|w/o CCS + - Final Energy|Production|Steel|Primary|BF and BOF 3|Oil|w CCS + - Final Energy|Production|Steel|Primary|BF and BOF 3|Oil|w/o CCS + - Final Energy|Production|Steel|Primary|BF and BOF 3|Petroleum Coke|w CCS + - Final Energy|Production|Steel|Primary|BF and BOF 3|Petroleum Coke|w/o CCS - Final Energy|Production|Steel|Primary|BF and BOF 4|Biofuels - Final Energy|Production|Steel|Primary|BF and BOF 4|Blast Furnace Gas - Final Energy|Production|Steel|Primary|BF and BOF 4|Coal @@ -100,10 +100,19 @@ steel - primary: - Final Energy|Production|Steel|Primary|BF and BOF 4|Electricity - Final Energy|Production|Steel|Primary|BF and BOF 4|Heat - Final Energy|Production|Steel|Primary|BF and BOF 4|Heavy Fuel Oil - - Final Energy|Production|Steel|Primary|BF and BOF 4|Liquified Petroleum Gases - - Final Energy|Production|Steel|Primary|BF and BOF 4|Natural Gas Mix + - Final Energy|Production|Steel|Primary|BF and BOF 4|Liquefied Petroleum Gas + - Final Energy|Production|Steel|Primary|BF and BOF 4|Natural Gas + - Final Energy|Production|Steel|Primary|BF and BOF 4|Oil - Final Energy|Production|Steel|Primary|BF and BOF 4|Petroleum Coke - - Final Energy|Production|Steel|Primary|BF and BOF 4|Refined Petroleum Products (Oil) + - Final Energy|Production|Steel|Primary|BF and BOF 1|Liquefied Petroleum Gas|w/o CCS + - Final Energy|Production|Steel|Primary|BF and BOF 2|Heavy Fuel Oil + - Final Energy|Production|Steel|Primary|BF and BOF 2|Liquefied Petroleum Gas + - Final Energy|Production|Steel|Primary|BF and BOF 1|Heavy Fuel Oil|w/o CCS + - Final Energy|Production|Steel|Primary|BF and BOF 2|Biofuels + - Final Energy|Production|Steel|Primary|BF and BOF 2|Heat + - Final Energy|Production|Steel|Primary|BF and BOF 1|Biofuels|w/o CCS + - Final Energy|Production|Steel|Primary|BF and BOF 2|Petroleum Coke + - Final Energy|Production|Steel|Primary|BF and BOF 1|Petroleum Coke|w/o CCS ecoinvent_aliases: fltr: @@ -142,20 +151,42 @@ steel - secondary: tiam-ucl: - Final Energy|Production|Steel|Secondary|DRH2 and EAF|Electricity - Final Energy|Production|Steel|Secondary|DRH2 and EAF|Hydrogen + - Final Energy|Production|Steel|Secondary|DRI and EAF 1|Coal - Final Energy|Production|Steel|Secondary|DRI and EAF 1|Electricity - Final Energy|Production|Steel|Secondary|DRI and EAF 1|Natural Gas Mix - Final Energy|Production|Steel|Secondary|DRI and EAF 2|w CCS|Electricity - Final Energy|Production|Steel|Secondary|DRI and EAF 2|w CCS|Natural Gas Mix + - Final Energy|Production|Steel|Secondary|DRI and EAF 2|w/o CCS|Coal - Final Energy|Production|Steel|Secondary|DRI and EAF 2|w/o CCS|Electricity - Final Energy|Production|Steel|Secondary|DRI and EAF 2|w/o CCS|Natural Gas Mix - Final Energy|Production|Steel|Secondary|DRI and EAF 3|Electricity - Final Energy|Production|Steel|Secondary|DRI and EAF 3|Natural Gas Mix + - Final Energy|Production|Steel|Secondary|EAF 1|Coal - Final Energy|Production|Steel|Secondary|EAF 1|Electricity - Final Energy|Production|Steel|Secondary|EAF 1|Natural Gas Mix - Final Energy|Production|Steel|Secondary|EAF 2|Electricity - Final Energy|Production|Steel|Secondary|EAF 2|Natural Gas Mix - Final Energy|Production|Steel|Secondary|EAF 3|Electricity - Final Energy|Production|Steel|Secondary|EAF 3|Natural Gas Mix + - Final Energy|Production|Steel|Secondary|DRH2 and EAF|Electricity + - Final Energy|Production|Steel|Secondary|DRH2 and EAF|Hydrogen + - Final Energy|Production|Steel|Secondary|DRI and EAF 1|Electricity + - Final Energy|Production|Steel|Secondary|DRI and EAF 1|Natural Gas + - Final Energy|Production|Steel|Secondary|DRI and EAF 2|Electricity|w CCS + - Final Energy|Production|Steel|Secondary|DRI and EAF 2|Electricity|w/o CCS + - Final Energy|Production|Steel|Secondary|DRI and EAF 2|Natural Gas|w CCS + - Final Energy|Production|Steel|Secondary|DRI and EAF 2|Natural Gas|w/o CCS + - Final Energy|Production|Steel|Secondary|DRI and EAF 3|Electricity + - Final Energy|Production|Steel|Secondary|DRI and EAF 3|Natural Gas + - Final Energy|Production|Steel|Secondary|EAF 1|Electricity + - Final Energy|Production|Steel|Secondary|EAF 1|Natural Gas + - Final Energy|Production|Steel|Secondary|EAF 2|Electricity + - Final Energy|Production|Steel|Secondary|EAF 2|Natural Gas + - Final Energy|Production|Steel|Secondary|EAF 3|Electricity + - Final Energy|Production|Steel|Secondary|EAF 3|Natural Gas + - Final Energy|Production|Steel|Secondary|DRI and EAF 1|Coal + - Final Energy|Production|Steel|Secondary|DRI and EAF 2|Coal|w/o CCS + - Final Energy|Production|Steel|Secondary|EAF 1|Coal ecoinvent_aliases: fltr: diff --git a/premise/iam_variables_mapping/transport_bus_variables.yaml b/premise/iam_variables_mapping/transport_bus_variables.yaml index 818b991a..749922ef 100644 --- a/premise/iam_variables_mapping/transport_bus_variables.yaml +++ b/premise/iam_variables_mapping/transport_bus_variables.yaml @@ -4,30 +4,74 @@ 'bus, diesel': iam_aliases: remind: ES|Transport|Pass|Road|Bus|Liquids + tiam-ucl: Distance|Transport|Bus|Diesel|Diesel energy_use_aliases: remind: FE|Transport|Pass|Road|Bus|Liquids + tiam-ucl: Final Energy|Transport|Bus|Diesel|Diesel ecoinvent_aliases: fltr: - 'transport, passenger bus, diesel, 13m single deck urban bus, EURO-VI' ecoinvent_fuel_aliases: fltr: - diesel + +'bus, gasoline': + iam_aliases: + tiam-ucl: Distance|Transport|Bus|Gasoline|Gasoline + energy_use_aliases: + tiam-ucl: Final Energy|Transport|Bus|Gasoline|Gasoline + ecoinvent_aliases: + fltr: + - 'transport, passenger bus, gasoline, 13m single deck urban bus, EURO-VI' + ecoinvent_fuel_aliases: + fltr: + - petrol, low-sulfur + +'bus, diesel hybrid': + iam_aliases: + tiam-ucl: Distance|Transport|Bus|Gasoline|Gasoline + energy_use_aliases: + tiam-ucl: Final Energy|Transport|Bus|Gasoline|Gasoline + ecoinvent_aliases: + fltr: + - 'transport, passenger bus, gasoline, 13m single deck urban bus, EURO-VI' + ecoinvent_fuel_aliases: + fltr: + - diesel + 'bus, compressed gas': iam_aliases: remind: ES|Transport|Pass|Road|Bus|Gases + tiam-ucl: Distance|Transport|Bus|Natural Gas|Natural Gas energy_use_aliases: remind: FE|Transport|Pass|Road|Bus|Gases + tiam-ucl: Final Energy|Transport|Bus|Natural Gas|Natural Gas ecoinvent_aliases: fltr: - 'transport, passenger bus, compressed gas, 13m single deck urban bus, EURO-VI' ecoinvent_fuel_aliases: fltr: - natural gas + +'bus, liquefied petroleum gas': + iam_aliases: + tiam-ucl: Distance|Transport|Bus|Liquefied Petroleum Gas|Liquefied Petroleum Gas + energy_use_aliases: + tiam-ucl: Final Energy|Transport|Bus|Liquefied Petroleum Gas|Liquefied Petroleum Gas + ecoinvent_aliases: + fltr: + - 'transport, passenger bus, liquefied petroleum gas, 13m single deck urban bus, EURO-VI' + ecoinvent_fuel_aliases: + fltr: + - liquefied petroleum gas + 'bus, fuel cell': iam_aliases: remind: ES|Transport|Pass|Road|Bus|FCEV + tiam-ucl: Distance|Transport|Bus|Hydrogen Fuel Cell|Bus Hydrogen energy_use_aliases: remind: FE|Transport|Pass|Road|Bus|FCEV + tiam-ucl: Final Energy|Transport|Bus|Hydrogen Fuel Cell|Bus Hydrogen ecoinvent_aliases: fltr: - 'transport, passenger bus, fuel cell electric, 13m single deck urban bus' diff --git a/premise/inventory_imports.py b/premise/inventory_imports.py index eb1bd37d..4abbf1df 100644 --- a/premise/inventory_imports.py +++ b/premise/inventory_imports.py @@ -857,13 +857,16 @@ def load_inventory(self) -> bw2io.ExcelImporter: def prepare_inventory(self) -> None: if self.version_in != self.version_out: - # if version_out is 3.9, migrate towards 3.8 first, then 3.9 - if self.version_out in ["3.9", "3.9.1", "3.10"]: - if self.version_in != "3.8": - print("Migrating to 3.8 first") - self.import_db.migrate( - f"migration_{self.version_in.replace('.', '')}_38" - ) + # if version_out is 3.9 or 3.10, migrate towards 3.8 first, then 3.9 or 3.10 + if self.version_out in ["3.9", "3.9.1", "3.10"] and self.version_in in [ + "3.5", + "3.6", + "3.7", + ]: + print("Migrating to 3.8 first") + self.import_db.migrate( + f"migration_{self.version_in.replace('.', '')}_38" + ) self.import_db.migrate( f"migration_38_{self.version_out.replace('.', '')}" ) @@ -948,16 +951,21 @@ def load_inventory(self): def prepare_inventory(self): # if version_out is 3.9, migrate towards 3.8 first, then 3.9 if self.version_out in ["3.9", "3.9.1", "3.10"]: - if self.version_in != "3.8": + if self.version_out in ["3.9", "3.9.1", "3.10"] and self.version_in in [ + "3.5", + "3.6", + "3.7", + ]: print("Migrating to 3.8 first") self.import_db.migrate( f"migration_{self.version_in.replace('.', '')}_38" ) - self.import_db.migrate(f"migration_38_{self.version_out.replace('.', '')}") - - self.import_db.migrate( - f"migration_{self.version_in.replace('.', '')}_{self.version_out.replace('.', '')}" - ) + self.import_db.migrate( + f"migration_38_{self.version_out.replace('.', '')}" + ) + self.import_db.migrate( + f"migration_{self.version_in.replace('.', '')}_{self.version_out.replace('.', '')}" + ) self.lower_case_technosphere_exchanges() self.add_biosphere_links() @@ -1022,13 +1030,16 @@ def load_inventory(self): def prepare_inventory(self): if str(self.version_in) != self.version_out: - # if version_out is 3.9, migrate towards 3.8 first, then 3.9 - if self.version_out in ["3.9", "3.9.1", "3.10"]: - if str(self.version_in) != "3.8": - print("Migrating to 3.8 first") - self.import_db.migrate( - f"migration_{self.version_in.replace('.', '')}_38" - ) + # if version_out is 3.9 or 3.10, migrate towards 3.8 first, then 3.9/3.10 + if self.version_out in ["3.9", "3.9.1", "3.10"] and self.version_in in [ + "3.5", + "3.6", + "3.7", + ]: + print("Migrating to 3.8 first") + self.import_db.migrate( + f"migration_{self.version_in.replace('.', '')}_38" + ) self.import_db.migrate( f"migration_38_{self.version_out.replace('.', '')}" ) diff --git a/premise/new_database.py b/premise/new_database.py index 92cb7c4d..2a830d00 100644 --- a/premise/new_database.py +++ b/premise/new_database.py @@ -504,7 +504,7 @@ def __init__( scenarios: List[dict], source_version: str = "3.10", source_type: str = "brightway", - key: bytes = None, + key: Union[bytes, str] = None, source_db: str = None, source_file_path: str = None, additional_inventories: List[dict] = None, @@ -715,7 +715,7 @@ def __import_inventories(self) -> List[dict]: # with HiddenPrints(): # Manual import # file path and original ecoinvent version - data = [] + data, unlinked = [], [] filepaths = [ (FILEPATH_OIL_GAS_INVENTORIES, "3.7"), (FILEPATH_CARMA_INVENTORIES, "3.5"), @@ -781,7 +781,7 @@ def __import_inventories(self) -> List[dict]: (FILEPATH_NUCLEAR_EPR, "3.8"), (FILEPATH_NUCLEAR_SMR, "3.8"), (FILEPATH_WAVE, "3.8"), - (FILEPATH_FUEL_CELL, "3.9"), + (FILEPATH_FUEL_CELL, "3.10"), (FILEPATH_CSP, "3.9"), (FILEPATH_HYDROGEN_HEATING, "3.9"), (FILEPATH_METHANOL_HEATING, "3.9"), @@ -819,6 +819,10 @@ def __import_inventories(self) -> List[dict]: datasets = inventory.merge_inventory() data.extend(datasets) self.database.extend(datasets) + unlinked.extend(inventory.list_unlinked) + + if len(unlinked) > 0: + raise ValueError("Fix the unlinked exchanges before proceeding") return data diff --git a/premise/transport.py b/premise/transport.py index 235d4bee..e025d93b 100644 --- a/premise/transport.py +++ b/premise/transport.py @@ -630,8 +630,6 @@ def adjust_battery_size(self, ds): # detect size in name size = [s for s in self.battery_size["truck"] if s in ds["name"]][0] - print(self.battery_size["truck"][size]) - if self.year <= min(self.battery_size["truck"][size].keys()): mean_battery_size = self.battery_size["truck"][size][ min(self.battery_size["truck"][size].keys()) diff --git a/premise/utils.py b/premise/utils.py index feeb4e97..c07f7e29 100644 --- a/premise/utils.py +++ b/premise/utils.py @@ -36,11 +36,11 @@ def rescale_exchanges( - ds, - value, - technosphere_filters=None, - biosphere_filters=None, - remove_uncertainty=False, + ds, + value, + technosphere_filters=None, + biosphere_filters=None, + remove_uncertainty=False, ): """ Adapted from wurst's change_exchanges_by_constant_factor @@ -87,9 +87,9 @@ def __exit__(self, exc_type, exc_val, exc_tb): def eidb_label( - scenario: dict, - version: str, - system_model: str = "cutoff", + scenario: dict, + version: str, + system_model: str = "cutoff", ) -> str: """ Return a label to name a scenario. @@ -154,6 +154,17 @@ def get_crops_properties() -> dict: return crop_props +def get_water_consumption_factors() -> dict: + """ + Return a dictionary from renewables/hydropower.yaml + with correction factors for hydropower datasets + """ + with open(DATA_DIR / "renewables" / "hydropower.yaml", "r", encoding="utf-8") as stream: + water_consumption_factors = yaml.safe_load(stream) + + return water_consumption_factors + + def get_efficiency_solar_photovoltaics() -> xr.DataArray: """ Return an array with PV module efficiencies in function of year and technology. @@ -235,8 +246,8 @@ def clear_existing_cache(all_versions: Optional[bool] = False, filter=None) -> N f.unlink() for f in DIR_CACHED_DB.glob("*") if f.is_file() - and (all_versions or "".join(tuple(map(str, __version__))) not in f.name) - and (filter is None or filter in f.name) + and (all_versions or "".join(tuple(map(str, __version__))) not in f.name) + and (filter is None or filter in f.name) ] @@ -357,7 +368,6 @@ def delete_log(): def create_scenario_list(scenarios: list) -> list: - list_scenarios = [] for scenario in scenarios: diff --git a/premise/validation.py b/premise/validation.py index 147d4096..6033490c 100644 --- a/premise/validation.py +++ b/premise/validation.py @@ -469,6 +469,9 @@ def check_database_name(self): if exc["type"] == "biosphere": # check that the first item of the code field # corresponds to biosphere_name + if "input" not in exc: + exc["input"] = (self.biosphere_name, exc["name"]) + if exc["input"][0] != self.biosphere_name: exc["input"] = (self.biosphere_name, exc["input"][1]) diff --git a/tests/test_process_ei38_conseq.py b/tests/test_process_ei38_conseq.py new file mode 100644 index 00000000..7488620b --- /dev/null +++ b/tests/test_process_ei38_conseq.py @@ -0,0 +1,82 @@ +import gc +import os + +import bw2calc +import bw2data +import bw2io +import pytest +from dotenv import load_dotenv + +from premise import NewDatabase, clear_inventory_cache +from premise.utils import delete_all_pickles + +load_dotenv() + + +ei_user = os.environ["EI_USERNAME"] +ei_pass = os.environ["EI_PASSWORD"] +key = os.environ["IAM_FILES_KEY"] +# convert to bytes +key = key.encode() + +ei_version = "3.8" +system_model = "consequential" + + +scenarios = [ + {"model": "remind", "pathway": "SSP2-Base", "year": 2050}, + {"model": "image", "pathway": "SSP2-RCP19", "year": 2050}, +] + + +@pytest.mark.slow +def test_brightway(): + + bw2data.projects.set_current(f"ecoinvent-{ei_version}-{system_model}") + + clear_inventory_cache() + + if f"ecoinvent-{ei_version}-{system_model}" not in bw2data.databases: + bw2io.import_ecoinvent_release( + version=ei_version, + system_model=system_model, + username=ei_user, + password=ei_pass, + ) + + ndb = NewDatabase( + scenarios=scenarios, + source_db=f"ecoinvent-{ei_version}-{system_model}", + source_version=ei_version, + key=key, + system_model=system_model, + biosphere_name=f"ecoinvent-{ei_version}-biosphere", + ) + + ndb.update() + + if "test1" in bw2data.databases: + del bw2data.databases["test1"] + if "test2" in bw2data.databases: + del bw2data.databases["test2"] + + ndb.write_db_to_brightway( + [ + "test1", + "test2", + ] + ) + + method = [m for m in bw2data.methods if "IPCC" in m[0]][0] + + lca = bw2calc.LCA({bw2data.Database("test1").random(): 1}, method) + lca.lci() + lca.lcia() + assert isinstance(lca.score, float) + print(lca.score) + + # destroy all objects + del ndb + del lca + gc.collect() + delete_all_pickles() diff --git a/tests/test_process_ei38_cutoff.py b/tests/test_process_ei38_cutoff.py new file mode 100644 index 00000000..6a19a59b --- /dev/null +++ b/tests/test_process_ei38_cutoff.py @@ -0,0 +1,81 @@ +import gc +import os + +import bw2calc +import bw2data +import bw2io +import pytest +from dotenv import load_dotenv + +from premise import NewDatabase, clear_inventory_cache +from premise.utils import delete_all_pickles + +load_dotenv() + + +ei_user = os.environ["EI_USERNAME"] +ei_pass = os.environ["EI_PASSWORD"] +key = os.environ["IAM_FILES_KEY"] +# convert to bytes +key = key.encode() + +ei_version = "3.8" +system_model = "cutoff" + + +scenarios = [ + {"model": "remind", "pathway": "SSP2-Base", "year": 2050}, + {"model": "image", "pathway": "SSP2-RCP19", "year": 2050}, +] + + +@pytest.mark.slow +def test_brightway(): + + bw2data.projects.set_current(f"ecoinvent-{ei_version}-{system_model}") + clear_inventory_cache() + + if f"ecoinvent-{ei_version}-{system_model}" not in bw2data.databases: + bw2io.import_ecoinvent_release( + version=ei_version, + system_model=system_model, + username=ei_user, + password=ei_pass, + ) + + ndb = NewDatabase( + scenarios=scenarios, + source_db=f"ecoinvent-{ei_version}-{system_model}", + source_version=ei_version, + key=key, + system_model=system_model, + biosphere_name=f"ecoinvent-{ei_version}-biosphere", + ) + + ndb.update() + + if "test1" in bw2data.databases: + del bw2data.databases["test1"] + if "test2" in bw2data.databases: + del bw2data.databases["test2"] + + ndb.write_db_to_brightway( + [ + "test1", + "test2", + ] + ) + + method = [m for m in bw2data.methods if "IPCC" in m[0]][0] + + lca = bw2calc.LCA({bw2data.Database("test1").random(): 1}, method) + lca.lci() + lca.lcia() + assert isinstance(lca.score, float) + print(lca.score) + + # destroy all objects + del ndb + del lca + gc.collect() + delete_all_pickles() diff --git a/tests/test_process_ei39_conseq.py b/tests/test_process_ei39_conseq.py new file mode 100644 index 00000000..6c600f4e --- /dev/null +++ b/tests/test_process_ei39_conseq.py @@ -0,0 +1,82 @@ +import gc +import os + +import bw2calc +import bw2data +import bw2io +import pytest +from dotenv import load_dotenv + +from premise import NewDatabase, clear_inventory_cache +from premise.utils import delete_all_pickles + +load_dotenv() + + +ei_user = os.environ["EI_USERNAME"] +ei_pass = os.environ["EI_PASSWORD"] +key = os.environ["IAM_FILES_KEY"] +# convert to bytes +key = key.encode() + +ei_version = "3.9.1" +system_model = "consequential" + + +scenarios = [ + {"model": "remind", "pathway": "SSP2-Base", "year": 2050}, + {"model": "image", "pathway": "SSP2-RCP19", "year": 2050}, +] + + +@pytest.mark.slow +def test_brightway(): + + bw2data.projects.set_current(f"ecoinvent-{ei_version}-{system_model}") + + clear_inventory_cache() + + if f"ecoinvent-{ei_version}-{system_model}" not in bw2data.databases: + bw2io.import_ecoinvent_release( + version=ei_version, + system_model=system_model, + username=ei_user, + password=ei_pass, + ) + + ndb = NewDatabase( + scenarios=scenarios, + source_db=f"ecoinvent-{ei_version}-{system_model}", + source_version=ei_version, + key=key, + system_model=system_model, + biosphere_name=f"ecoinvent-{ei_version}-biosphere", + ) + + ndb.update() + + if "test1" in bw2data.databases: + del bw2data.databases["test1"] + if "test2" in bw2data.databases: + del bw2data.databases["test2"] + + ndb.write_db_to_brightway( + [ + "test1", + "test2", + ] + ) + + method = [m for m in bw2data.methods if "IPCC" in m[0]][0] + + lca = bw2calc.LCA({bw2data.Database("test1").random(): 1}, method) + lca.lci() + lca.lcia() + assert isinstance(lca.score, float) + print(lca.score) + + # destroy all objects + del ndb + del lca + gc.collect() + delete_all_pickles() From 9ba890a35b35eddf3ab9f34dc917d8636bd446f8 Mon Sep 17 00:00:00 2001 From: romainsacchi Date: Thu, 12 Sep 2024 14:39:07 +0000 Subject: [PATCH 5/6] Black reformating --- premise/electricity.py | 6 +++++- premise/utils.py | 24 +++++++++++++----------- 2 files changed, 18 insertions(+), 12 deletions(-) diff --git a/premise/electricity.py b/premise/electricity.py index 82b91c26..83fc7068 100644 --- a/premise/electricity.py +++ b/premise/electricity.py @@ -30,7 +30,11 @@ uuid, ws, ) -from .utils import get_efficiency_solar_photovoltaics, rescale_exchanges, get_water_consumption_factors +from .utils import ( + get_efficiency_solar_photovoltaics, + get_water_consumption_factors, + rescale_exchanges, +) from .validation import ElectricityValidation POWERPLANT_TECHS = VARIABLES_DIR / "electricity_variables.yaml" diff --git a/premise/utils.py b/premise/utils.py index c07f7e29..2f4df1b6 100644 --- a/premise/utils.py +++ b/premise/utils.py @@ -36,11 +36,11 @@ def rescale_exchanges( - ds, - value, - technosphere_filters=None, - biosphere_filters=None, - remove_uncertainty=False, + ds, + value, + technosphere_filters=None, + biosphere_filters=None, + remove_uncertainty=False, ): """ Adapted from wurst's change_exchanges_by_constant_factor @@ -87,9 +87,9 @@ def __exit__(self, exc_type, exc_val, exc_tb): def eidb_label( - scenario: dict, - version: str, - system_model: str = "cutoff", + scenario: dict, + version: str, + system_model: str = "cutoff", ) -> str: """ Return a label to name a scenario. @@ -159,7 +159,9 @@ def get_water_consumption_factors() -> dict: Return a dictionary from renewables/hydropower.yaml with correction factors for hydropower datasets """ - with open(DATA_DIR / "renewables" / "hydropower.yaml", "r", encoding="utf-8") as stream: + with open( + DATA_DIR / "renewables" / "hydropower.yaml", "r", encoding="utf-8" + ) as stream: water_consumption_factors = yaml.safe_load(stream) return water_consumption_factors @@ -246,8 +248,8 @@ def clear_existing_cache(all_versions: Optional[bool] = False, filter=None) -> N f.unlink() for f in DIR_CACHED_DB.glob("*") if f.is_file() - and (all_versions or "".join(tuple(map(str, __version__))) not in f.name) - and (filter is None or filter in f.name) + and (all_versions or "".join(tuple(map(str, __version__))) not in f.name) + and (filter is None or filter in f.name) ] From 72a160c2c25d84bcd32106095cb50c9dab29de26 Mon Sep 17 00:00:00 2001 From: alvarojhahn Date: Fri, 4 Oct 2024 17:30:59 +0200 Subject: [PATCH 6/6] Fix post-allocation --- .../data/additional_inventories/lci-PGM.xlsx | Bin 201664 -> 201652 bytes .../lci-batteries-vanadium.xlsx | Bin 65292 -> 68166 bytes .../additional_inventories/lci-germanium.xlsx | Bin 91320 -> 90404 bytes .../additional_inventories/lci-rhenium.xlsx | Bin 32010 -> 32398 bytes .../data/metals/mining_shares_mapping.xlsx | Bin 1985935 -> 1985761 bytes .../corrections.yaml | 525 +++++++++++++++++- 6 files changed, 508 insertions(+), 17 deletions(-) diff --git a/premise/data/additional_inventories/lci-PGM.xlsx 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resource::in ground amount: 0.65 unit: kilogram -- name: rare earth element mine operation and beneficiation, bastnaesite and monazite - ore +- name: rare earth element mine operation and beneficiation, bastnaesite and monazite ore reference product: iron ore concentrate location: CN-NM unit: kilogram @@ -584,7 +583,7 @@ unit: kilogram - name: Europium categories: natural resource::in ground - amount: -4.6041578091406e-05 + amount: -0.000046041578091406 unit: kilogram - name: Gadolinium categories: natural resource::in ground @@ -1312,17 +1311,25 @@ categories: natural resource::in ground amount: -0.0166 unit: kilogram - - name: Palladium +# - name: Palladium +# categories: natural resource::in ground +# amount: 0.0005288299634148183 +# unit: kilogram +# - name: Platinum +# categories: natural resource::in ground +# amount: 0.0001447803601218551 +# unit: kilogram + - name: Rhodium categories: natural resource::in ground - amount: 0.0005288299634148183 + amount: -1.37e-05 unit: kilogram - - name: Platinum + - name: Palladium categories: natural resource::in ground - amount: 0.0001447803601218551 + amount: -6.09e-05 unit: kilogram - - name: Rhodium + - name: Platinum categories: natural resource::in ground - amount: -1.37e-05 + amount: -0.000103 unit: kilogram - name: platinum group metal mine operation, ore with high palladium content reference product: platinum @@ -1588,7 +1595,16 @@ location: CN-FJ unit: kilogram additional flow: - - name: Indium + - name: Holmium + categories: natural resource::in ground + amount: 0.8729690395908926 + unit: kilogram +- name: rare earth oxides production, from rare earth carbonate concentrate + reference product: holmium oxide + location: RoW + unit: kilogram + additional flow: + - name: Holmium categories: natural resource::in ground amount: 0.8729690395908926 unit: kilogram @@ -1641,23 +1657,41 @@ categories: natural resource::in ground amount: 1.0 unit: kilogram -- name: silicon production, metallurgical grade - reference product: silicon, metallurgical grade +#- name: silicon production, metallurgical grade +# reference product: silicon, metallurgical grade +# location: RoW +# unit: kilogram +# additional flow: +# - name: Silicon +# categories: natural resource::in ground +# amount: 1.0 +# unit: kilogram +#- name: silicon production, metallurgical grade +# reference product: silicon, metallurgical grade +# location: NO +# unit: kilogram +# additional flow: +# - name: Silicon +# categories: natural resource::in ground +# amount: 1.0 +# unit: kilogram +- name: silica sand production + reference product: silica sand location: RoW unit: kilogram additional flow: - name: Silicon categories: natural resource::in ground - amount: 1.0 + amount: 0.4 unit: kilogram -- name: silicon production, metallurgical grade - reference product: silicon, metallurgical grade - location: 'NO' +- name: silica sand production + reference product: silica sand + location: DE unit: kilogram additional flow: - name: Silicon categories: natural resource::in ground - amount: 1.0 + amount: 0.4 unit: kilogram - name: processing of anode slime from electrorefining of copper, anode reference product: silver @@ -2167,3 +2201,460 @@ categories: natural resource::in ground amount: -0.85718053673914 unit: kilogram +- name: zinc mine operation + reference product: germanium, concentrate + location: GLO + unit: kilogram + additional flow: + - name: Aluminium + categories: natural resource::in ground + amount: -2.558181756 + unit: kilogram + - name: Barium + categories: natural resource::in ground + amount: -0.013598026 + unit: kilogram + - name: Cadmium + categories: natural resource::in ground + amount: -0.084131401 + unit: kilogram + - name: Calcium + categories: natural resource::in ground + amount: -88.905362997 + unit: kilogram + - name: Chromium + categories: natural resource::in ground + amount: -0.003159813 + unit: kilogram + - name: Copper + categories: natural resource::in ground + amount: -19.799383106 + unit: kilogram + - name: Dolomite + categories: natural resource::in ground + amount: -0.002715580 + unit: kilogram + - name: Gold + categories: natural resource::in ground + amount: -0.001253363 + unit: kilogram + - name: Iron + categories: natural resource::in ground + amount: -3.208732688 + unit: kilogram + - name: Lead + categories: natural resource::in ground + amount: -153.053187554 + unit: kilogram + - name: Magnesium + categories: natural resource::in ground + amount: -50.821231966 + unit: kilogram + - name: Manganese + categories: natural resource::in ground + amount: -0.185054254 + unit: kilogram + - name: Mercury + categories: natural resource::in ground + amount: -0.000026071 + unit: kilogram + - name: Nickel + categories: natural resource::in ground + amount: -0.001927191 + unit: kilogram + - name: Phosphorus + categories: natural resource::in ground + amount: -0.021864439 + unit: kilogram + - name: Potassium + categories: natural resource::in ground + amount: -3.203840956 + unit: kilogram + - name: Silver + categories: natural resource::in ground + amount: -0.261411791 + unit: kilogram + - name: Sodium + categories: natural resource::in ground + amount: -0.097827166 + unit: kilogram + - name: Strontium + categories: natural resource::in ground + amount: -0.034484119 + unit: kilogram + - name: Sulfur + categories: natural resource::in ground + amount: -8.422922402 + unit: kilogram + - name: Titanium + categories: natural resource::in ground + amount: -0.120816980 + unit: kilogram + - name: Vanadium + categories: natural resource::in ground + amount: -0.003272314 + unit: kilogram +- name: vanadium bearing magnetite production + reference product: vanadium bearing magnetite + location: ZA + unit: kilogram + additional flow: + - name: Iron + categories: natural resource::in ground + amount: -0.705882353 + unit: kilogram + - name: Titanium + categories: natural resource::in ground + amount: -0.163398693 + unit: kilogram + - name: Vanadium + categories: natural resource::in ground + amount: 0.034 + unit: kilogram +- name: vanadium pentoxide production + reference product: vanadium pentoxide + location: CN + unit: kilogram + additional flow: + - name: Vanadium + categories: natural resource::in ground + amount: 0.56 + unit: kilogram +- name: rare earth element mine operation and beneficiation, ion adsorption clays + reference product: rare earth carbonate concentrate + location: CN + unit: kilogram + additional flow: + - name: Cerium + categories: natural resource::in ground + amount: -0.0135 + unit: kilogram + - name: Dysprosium + categories: natural resource::in ground + amount: -0.0158 + unit: kilogram + - name: Erbium + categories: natural resource::in ground + amount: -0.0081 + unit: kilogram + - name: Europium + categories: natural resource::in ground + amount: -0.0027 + unit: kilogram + - name: Gadolinium + categories: natural resource::in ground + amount: -0.0211 + unit: kilogram + - name: Holmium + categories: natural resource::in ground + amount: -0.0031 + unit: kilogram + - name: Lanthanum + categories: natural resource::in ground + amount: -0.1225 + unit: kilogram + - name: Lutetium + categories: natural resource::in ground + amount: -0.0009 + unit: kilogram + - name: Neodymium + categories: natural resource::in ground + amount: -0.0993 + unit: kilogram + - name: Praseodymium + categories: natural resource::in ground + amount: -0.0273 + unit: kilogram + - name: Samarium + categories: natural resource::in ground + amount: -0.0216 + unit: kilogram + - name: Terbium + categories: natural resource::in ground + amount: -0.0027 + unit: kilogram + - name: Thulium + categories: natural resource::in ground + amount: -0.0009 + unit: kilogram + - name: Ytterbium + categories: natural resource::in ground + amount: -0.008 + unit: kilogram + - name: Yttrium + categories: natural resource::in ground + amount: -0.1025 + unit: kilogram +- name: copper mine operation and beneficiation, sulfide ore + reference product: rhenium + location: CL + unit: kilogram + additional flow: + - name: Copper + categories: natural resource::in ground + amount: -48295.5199820 + unit: kilogram + - name: Gold + categories: natural resource::in ground + amount: -0.4583942 + unit: kilogram + - name: Molybdenum + categories: natural resource::in ground + amount: -749.9250423 + unit: kilogram + - name: Selenium + categories: natural resource::in ground + amount: -134.9219084 + unit: kilogram + - name: Silver + categories: natural resource::in ground + amount: -16.3188327 + unit: kilogram + - name: Tellurium + categories: natural resource::in ground + amount: -11.6230239 + unit: kilogram +- name: copper mine operation and beneficiation, sulfide ore + reference product: rhenium + location: CN + unit: kilogram + additional flow: + - name: Copper + categories: natural resource::in ground + amount: -313.3931874 + unit: kilogram + - name: Gold + categories: natural resource::in ground + amount: -0.0029710 + unit: kilogram + - name: Molybdenum + categories: natural resource::in ground + amount: -29.7837500 + unit: kilogram + - name: Selenium + categories: natural resource::in ground + amount: -0.8744708 + unit: kilogram + - name: Silver + categories: natural resource::in ground + amount: -0.1057674 + unit: kilogram + - name: Tellurium + categories: natural resource::in ground + amount: -0.0753560 + unit: kilogram +- name: copper mine operation and beneficiation, sulfide ore + reference product: rhenium + location: US + unit: kilogram + additional flow: + - name: Copper + categories: natural resource::in ground + amount: -40784.6163310 + unit: kilogram + - name: Gold + categories: natural resource::in ground + amount: -0.3870074 + unit: kilogram + - name: Molybdenum + categories: natural resource::in ground + amount: -2861.4798593 + unit: kilogram + - name: Selenium + categories: natural resource::in ground + amount: -113.9102199 + unit: kilogram + - name: Silver + categories: natural resource::in ground + amount: -13.7774646 + unit: kilogram + - name: Tellurium + categories: natural resource::in ground + amount: -9.8095872 + unit: kilogram +- name: platinum group metal, extraction and refinery operations + reference product: palladium + location: ZA + unit: kilogram + additional flow: + - name: Palladium + categories: natural resource::in ground + amount: 1.0 + unit: kilogram +- name: platinum group metal, extraction and refinery operations + reference product: platinum + location: ZA + unit: kilogram + additional flow: + - name: Platinum + categories: natural resource::in ground + amount: 1.0 + unit: kilogram +- name: platinum group metal, extraction and refinery operations + reference product: gold + location: ZA + unit: kilogram + additional flow: + - name: Gold + categories: natural resource::in ground + amount: 1.0 + unit: kilogram +- name: platinum group metal, extraction and refinery operations + reference product: rhodium + location: ZA + unit: kilogram + additional flow: + - name: Rhodium + categories: natural resource::in ground + amount: 1.0 + unit: kilogram +- name: platinum group metal, extraction and refinery operations + reference product: rhodium + location: RU + unit: kilogram + additional flow: + - name: Rhodium + categories: natural resource::in ground + amount: 1.0 + unit: kilogram +- name: platinum group metal, extraction and refinery operations + reference product: nickel, class 1 + location: ZA + unit: kilogram + additional flow: + - name: Nickel + categories: natural resource::in ground + amount: 1.0 + unit: kilogram +- name: gold mine operation and refining + reference product: gold + location: SE + unit: kilogram + additional flow: + - name: Gold + categories: natural resource::in ground + amount: 0.85932362893 + unit: kilogram + - name: Copper + categories: natural resource::in ground + amount: -5773.65875941088 + unit: kilogram + - name: Lead + categories: natural resource::in ground + amount: -697.8095731118548 + unit: kilogram + - name: Silver + categories: natural resource::in ground + amount: -7.114523826934984 + unit: kilogram + - name: Zinc + categories: natural resource::in ground + amount: -904.5722253966127 + unit: kilogram +- name: gold mine operation and refining + reference product: lead + location: SE + unit: kilogram + additional flow: + - name: Gold + categories: natural resource::in ground + amount: -0.000004165138249175353 + unit: kilogram + - name: Copper + categories: natural resource::in ground + amount: -0.17094617065906273 + unit: kilogram + - name: Lead + categories: natural resource::in ground + amount: 0.97933929258 + unit: kilogram + - name: Silver + categories: natural resource::in ground + amount: -0.0002106464297521615 + unit: kilogram + - name: Zinc + categories: natural resource::in ground + amount: -0.026782524645061572 + unit: kilogram +- name: gold mine operation and refining + reference product: silver + location: SE + unit: kilogram + additional flow: + - name: Gold + categories: natural resource::in ground + amount: -0.0018158509523342249 + unit: kilogram + - name: Copper + categories: natural resource::in ground + amount: -74.52640181886063 + unit: kilogram + - name: Lead + categories: natural resource::in ground + amount: -9.007327728542116 + unit: kilogram + - name: Silver + categories: natural resource::in ground + amount: 0.90816570851 + unit: kilogram + - name: Zinc + categories: natural resource::in ground + amount: -11.67622056537467 + unit: kilogram +- name: gold mine operation and refining + reference product: zinc + location: SE + unit: kilogram + additional flow: + - name: Gold + categories: natural resource::in ground + amount: -0.000005822236262288128 + unit: kilogram + - name: Copper + categories: natural resource::in ground + amount: -0.23895701274922745 + unit: kilogram + - name: Lead + categories: natural resource::in ground + amount: -0.02888055875952679 + unit: kilogram + - name: Silver + categories: natural resource::in ground + amount: -0.00029445199857829025 + unit: kilogram + - name: Zinc + categories: natural resource::in ground + amount: 0.96256206232 + unit: kilogram +- name: 7N arsenic production + reference product: 7N Arsenic + location: GLO + unit: kilogram + additional flow: + - name: Arsenic + categories: natural resource::in ground + amount: 1.0 + unit: kilogram +- name: sodium borate mine operation and beneficiation + reference product: sodium borates + location: US + unit: kilogram + additional flow: + - name: Sodium + categories: natural resource::in ground + amount: 0.136553987 # original content multiplied by 0.136553987 (same ratio as boron) + unit: kilogram +- name: sodium borate mine operation and beneficiation + reference product: sodium borates + location: RoW + unit: kilogram + additional flow: + - name: Sodium + categories: natural resource::in ground + amount: 0.136553987 # original content multiplied by 0.136553987 (same ratio as boron) + unit: kilogram + + + + +

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