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  1. Admiraal et al., 2016 (A. K. Admiraal, A. F. Hof, M. G. J. den Elzen, D. P. van Vuuren (2016). Costs and benefits of differences in the timing of greenhouse gas emission reductions. Mitigation and Adaptation Strategies for Global Change, 21(8), pp. 1165-1179, doi: http://dx.doi.org/10.1007/s11027-015-9641-4.
    Link to PBL-website: http://www.pbl.nl/en/publications/costs-and-benefits-of-differences-in-the-timing-of-greenhouse-gas-emission-reductions.    )
  2. Aguiar et al., 2016 (Angel Aguiar, Badri Narayanan, Robert McDougall (2016). An Overview of the GTAP 9 Data Base. Journal of Global Economic Analysis, 1(1), doi: http://dx.doi.org/https://doi.org/10.21642/JGEA.010103AF.)
  3. Alcamo et al., 2003 (J. Alcamo, P. Döll, T. Henrichs, F. Kaspar, B. Lehner, T. Rösch, S. Siebert (2003). Development and testing of the Water. GAP 2 global model of water use and availability. Hydrological Sciences, 48(3), pp. 317-337.)
  4. Bartholome et al., 2004 (E. Bartholome, A. Belward, R. Beuchle, H. Eva, S. Fritz, A. Hartley, P. Mayaux, H-J. Stibig (2004). Global Land Cover for the year 2000.European CommissionJoint Research Centre.Access date: 2004.)
  5. Beusen et al., 2016 (A. H. W. Beusen, A. F. Bouwman, L. P. H. Van Beek, J. M. Mogollón, J. J. Middelburg (2016). Global riverine N and P transport to ocean increased during the 20th century despite increased retention along the aquatic continuum. Biogeosciences, 13(8), pp. 2441-2451, doi: http://dx.doi.org/10.5194/bg-13-2441-2016.)
  6. Bianchi et al., 2005 (F. J. J. A. Bianchi, W. K. R. E. van Wingerden, A. J. Griffioen, M. van der Veen, M. J. J. van der Straten, R. M. A. Wegman, H. A. M. Meeuwsen (2005). Landscape factors affecting the control of Mamestra brassicae by natural enemies in Brussels sprout. Agriculture, Ecosystems & Environment, 107(2-3), pp. 145-150, doi: http://dx.doi.org/10.1016/j.agee.2004.11.007.)
  7. Bijl et al., 2016 (D. L. Bijl, P. W. Bogaart, T. Kram, B. J. M. de Vries, D. P. van Vuuren (2016). Long-term water demand for electricity, industry and households. Environmental Science and Policy, 55, pp. 75-86, doi: http://dx.doi.org/10.1016/j.envsci.2015.09.005.)
  8. Bijl et al., 2017 (D.L. Bijl, P.W. Bogaart, S.C. Dekker, E. Stehfest, B.J.M. de Vries, D.P. van Vuuren (2017). A physically-based model of long-term food demand. Global Environmental Change, 45, pp. 47-62, doi: http://dx.doi.org/10.1016/j.gloenvcha.2017.04.003.)
  9. Bijl et al., 2018a (D.L. Bijl, H. Biemans, P.W. Bogaart, S.C. Dekker, J.C. Doelman, E. Stehfest, D.P. van Vuuren (2018). A Global Analysis of Future Water Deficit Based On Different Allocation Mechanisms. Water Resources Research, 54(8), pp. 5803-5824, doi: http://dx.doi.org/10.1029/2017WR021688.)
  10. Bouwman et al., 2002a (A. F. Bouwman, L. J. M. Boumans, N. H. Batjes (2002). Emissions of N2O and NO from fertilized fields: Summary of available measurement data. Global Biogeochemical Cycles, 16(4), pp. 6-1, doi: http://dx.doi.org/10.1029/2001GB001811.
    Link to PBL-website: http://www.pbl.nl/en/publications/2002/Emissions_of_N2O_and_NO_from_fertilized_fields__summary_of_available_measurement_data.    )
  11. Bouwman et al., 2002b (A. F. Bouwman, D. P. Van Vuuren, R. G. Derwent, M. Posch (2002). A global analysis of acidification and eutrophication of terrestrial ecosystems. Water, Air, and Soil Pollution, 141(1-4), pp. 349-382, doi: http://dx.doi.org/10.1023/A:1021398008726.
    Link to PBL-website: http://www.pbl.nl/en/publications/2002/AGlobalAnalysisofAcidificationandEutrophicationofTerrestrialEcosystems.    )
  12. Bouwman et al., 2005 (A. F. Bouwman, K. W. Van Der Hoek, B. Eickhout, I. Soenario (2005). Exploring changes in world ruminant production systems. Agricultural Systems, 84(2), pp. 121-153, doi: http://dx.doi.org/10.1016/j.agsy.2004.05.006.
    Link to PBL-website: http://www.pbl.nl/en/publications/2005/Exploringchangesinworldruminantproductionsystems.    )
  13. Braakhekke et al., 2019 (Braakhekke, M. C., Doelman, J. C., Baas, P., Müller, C., Schaphoff, S., Stehfest, E., van Vuuren, D. P. (2019). Modeling forest plantations for carbon uptake with the LPJmL dynamic global vegetation model. Earth System Dynamics, 10(4), pp. 617-630, doi: http://dx.doi.org/https://doi.org/10.5194/esd-10-617-2019.
    Link to PBL-website: https://www.pbl.nl/en/publications/modeling-forest-plantations-for-carbon-uptake-with-the-lpjml-dynamic-global-vegetation-model.    )
  14. Braspenning Radu et al., 2016 (O. Braspenning Radu, M. van den Berg, Z. Klimont, S. Deetman, G. Janssens-Maenhout, M. Muntean, C. Heyes, F. Dentener, D. P. van Vuuren (2016). Exploring synergies between climate and air quality policies using long-term global and regional emission scenarios. Atmospheric Environment, 140, pp. 577-591, doi: http://dx.doi.org/10.1016/j.atmosenv.2016.05.021.
    Link to PBL-website: http://www.pbl.nl/en/publications/exploring-synergies-between-climate-and-air-quality-policies-using-long-term-global-and-regional-emission-scenarios.    )
  15. Brinkman et al., 2005 (S. Brinkman, B. Strengers, J van Minnen, Nabuurs, G.J., E. Trines (2005). IMAGE 2.2 Carbon Cycle Analysis, Brinkman Climate Change Consultant(URL: http://www.brinkmanclimatechange.com/pdf/ReportIMAGEcarboncycleanalysis.pdf).)
  16. Britz, 2003 (W. Britz (2003). Major enhancements of @2030 Modelling system.URL: http://www.ilr1.uni-bonn.de/agpo/rsrch/at2030/@2030_2003.doc)
  17. Bruinsma, 2003 (J. Bruinsma (2003). World agriculture: towards 2015/2030., An FAO perspective, Earthscan, London.)
  18. Cengic et al., 2020 (Mirza Čengić, Jasmijn Rost, Daniela Remenska, Jan H. Janse, Mark A. J. Huijbregts, and Aafke M. Schipper (2020). On the importance of predictor choice, modelling technique, and number of pseudo‐absences for bioclimatic envelope model performance. Ecology and Evolution, 10(21), pp. 12307–12317, doi: http://dx.doi.org/10.1002/ece3.6859.)
  19. Cofala et al., 2002 (J. Cofala, C. Heyes, Z. Klimont, M. Amann (2002). Acidification, eutrophication and tropospheric ozone impacts for five scenarios of greenhouse gases abatement in Europe, IIASA, Laxenburg, Austria.)
  20. Criqui et al., 2003 (P. Criqui, A. Kitous, M.M. Berk, M.G.J. den Elzen, B. Eickhout, P. Lucas, D.P. van Vuuren, N. Kouvaritakis, D. Vanregemorter (2003). Greenhouse gas reduction pathways in the UNFCCC Process up to 2025 - Technical Report, CNRS-IEPE, Grenoble, France.)
  21. DEA, 2018 (Danish Energy Agency (2018). Note on technology costs for offshore wind farms and the background for updating CAPEX and OPEX in the technology catalogue datasheets, Danish Ministry of Energy, Utilities and Climate(URL: https://ens.dk/sites/ens.dk/files/Analyser/havvindsnotat_translation_eng_final.pdf).)
  22. Dagnachew et al., 2018 (A.G. Dagnachew, P.L. Lucas, A.F. Hof, D.P. van Vuuren (2018). Trade-offs and synergies between universal electricity access and climate change mitigation in Sub-Saharan Africa. Energy Policy, 114, pp. 355-366, doi: http://dx.doi.org/10.1016/j.enpol.2017.12.023.)
  23. Dagnachew et al., 2020 (Anteneh G.Dagnachew, Andries F.Hof, Paul L.Lucas, Detlef P.van Vuuren (2020). Scenario analysis for promoting clean cooking in Sub-Saharan Africa: Costs and benefits. Energy, 192, doi: http://dx.doi.org/https://doi.org/10.1016/j.energy.2019.116641.)
  24. Daioglou et al., 2019 (V. Daioglou, J.C. Doelman, B. Wicke, A. Faaij, D.P. van Vuuren (2019). Integrated assessment of biomass supply and demand in climate change mitigation scenarios. Global Environmental Change, 54, pp. 88-101, doi: http://dx.doi.org/10.1016/j.gloenvcha.2018.11.012.)
  25. Daioglou et al., 2022 (Vassilis Daioglou, Efstratios Mikropoulos, David Gernaat, Detlef P.van Vuuren (2022). Efficiency improvement and technology choice for energy and emission reductions of the residential sector. Energy, 243, doi: http://dx.doi.org/https://doi.org/10.1016/j.energy.2021.122994.)
  26. De Boer and Van Vuuren, 2017 (H.S. de Boer and D.P. van Vuuren (2017). Representation of variable renewable energy source in TIMER, an aggregated energy system simulation model. Energy Economics, 64, pp. 600-611, doi: http://dx.doi.org/http://doi.org/10.1016/j.eneco.2016.12.006.
    Link to PBL-website: http://www.pbl.nl/en/publications/representation-of-variable-renewable-energy-sources-in-timer-an-aggregated-energy-system-simulation-model.    )
  27. De Onis and Blossner, 2003 (M. De Onis, M. Blossner (2003). The world health organization global database on child growth and malnutrition: methodology and applications. International Journal Epidemiology, 32(4), pp. 518-526, doi: http://dx.doi.org/10.1093/ije/dyg099.)
  28. De Vos et al., 2021 (Lotte de Vos, Hester Biemans, Jonathan C Doelman, Elke Stehfest and Detlef P van Vuuren (2021). Trade-offs between water needs for food, utilities, and the environment—a nexus quantification at different scales. Environmental Research Letters, 16(11), doi: http://dx.doi.org/https://doi.org/10.1088/1748-9326/ac2b5e.)
  29. De Vries et al., 2001 (H.J.M. de Vries, D.P. van Vuuren, M.G.J. den Elzen, M.A. Janssen (2001). The targets image energy model regional (TIMER) -Technical documentation., MNP Netherlands Environmental Assessment Agency, Bilthoven, the Netherlands(URL: http://www.rivm.nl/en/Documents_and_publications/Scientific/Reports/2002/juli/Targets_IMage_Energy_Regional_TIMER_Model_Technical_Documentation).)
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    Link to PBL-website: http://www.pbl.nl/en/publications/contribution-of-the-g20-economies-to-the-global-impact-of-the-paris-agreement-climate-proposals.    )
  32. Dixon et al., 2001 (J. Dixon, A. Gulliver, D. Gibbon (2001). Farming systems and poverty, FAO/World bank, Rome/Washington DC.)
  33. Doelman et al., 2018 (J.C. Doelman, E. Stehfest, A. Tabeau, H. van Meijl, L. Lassaletta, K. Neumann-Hermans, D.E.H.J. Gernaat, M. Harmsen, V. Daioglou, H. Biemans, S. van der Sluis, D.P. van Vuuren (2018). Exploring SSP land-use dynamics using the IMAGE model: Regional and gridded scenarios of land-use change and land-based climate change mitigation. Global Environmental Change, 48(January), pp. 119-135, doi: http://dx.doi.org/10.1016/j.gloenvcha.2017.11.014.
    Link to PBL-website: http://www.pbl.nl/en/publications/exploring-ssp-land-use-dynamics-using-the-image-model-regional-and-gridded-scenarios-of-land-use-change-and-land-ba.    )
  34. Doelman et al., 2019 (Doelman, Jonathan C, Stehfest, Elke, van Vuuren, Detlef P, Tabeau, Andrzej, Hof, Andries F, Braakhekke, Maarten C, Gernaat, David EHJ, van den Berg, Maarten, van Zeist, Willem‐Jan, Daioglou, Vassilis (2019). Afforestation for climate change mitigation: Potentials, risks and trade-offs. Global Change Biology, 26(3), pp. 1576-1591, doi: http://dx.doi.org/https://doi.org/10.1111/gcb.14887.
    Link to PBL-website: https://www.pbl.nl/publications/afforestation-for-climate-change-mitigation-potentials-risks-and-trade-offs.    )
  35. Doelman et al., 2020b (Jonathan C. Doelman, Elke Stehfest, Andrzej Tabeau, Hans van Meijl, Luis Lassaletta, David E.H.J. Gernaat, Kathleen Hermans, Mathijs Harmsen, Vassilis Daioglou, Hester Biemans, Sietske van der Sluis, Detlef P.van Vuuren (2020). Exploring SSP land-use dynamics using the IMAGE model: Regional and gridded scenarios of land-use change and land-based climate change mitigation. Global Environmental Change, 48, pp. 119-135, doi: http://dx.doi.org/https://doi.org/10.1016/j.gloenvcha.2017.11.014.)
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