High-resolution forest carbon modelling for climate mitigation planning over the RGGI region, USA

被引:12
|
作者
Ma, L. [1 ]
Hurtt, G. [1 ]
Tang, H. [1 ]
Lamb, R. [1 ]
Campbell, E. [2 ]
Dubayah, R. [1 ]
Guy, M. [1 ]
Huang, W. [1 ,3 ]
Lister, A. [4 ]
Lu, J. [1 ]
O'Neil-Dunne, J. [5 ]
Rudee, A. [6 ]
Shen, Q. [1 ]
Silva, C. [1 ]
机构
[1] Univ Maryland, Dept Geog Sci, College Pk, MD 20742 USA
[2] Maryland Dept Nat Resources, Annapolis, MD 21401 USA
[3] Wuhan Univ, Sch Resource & Environm Sci, Wuhan 430079, Hubei, Peoples R China
[4] US Forest Serv, Northern Res Stn, Forest Inventory & Anal Natl Inventory & Monitori, York, PA 17402 USA
[5] Univ Vermont, Rubenstein Sch Nat Resources & Environm, Burlington, VT 05405 USA
[6] World Resources Inst, Washington, DC 20002 USA
关键词
forest; carbon sequestration; climate mitigation; lidar; ecosystem modelling; BIOMASS CARBON; UNITED-STATES; LIDAR DATA; LAND; VEGETATION; ECOSYSTEMS; MANAGEMENT; SCIENCE; LOSSES; FLUXES;
D O I
10.1088/1748-9326/abe4f4
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
The inclusion of forest carbon in climate change mitigation planning requires the development of models able to project potential future carbon stocks-a step beyond traditional monitoring, reporting and verification frameworks. Here, we updated and expanded a high-resolution forest carbon modelling approach previously developed for the state of Maryland to 11 states in the Regional Greenhouse Gas Initiative (RGGI) domain, which includes Connecticut, Delaware, Maine, Maryland, Massachusetts, New Hampshire, New Jersey, New York, Pennsylvania, Rhode Island, and Vermont. In this study, we employ an updated version of the Ecosystem Demography (ED) model, an improved lidar initialization strategy, and an expanded calibration/validation approach. High resolution (90 m) wall-to-wall maps of present aboveground carbon, aboveground carbon sequestration potential, aboveground carbon sequestration potential gap (CSPG), and time to reach sequestration potential were produced over the RGGI domain where airborne lidar data were available, including 100% of eight states, 62% of Maine, 12% of New Jersey, and 0.65% of New York. For the eight states with complete data, an area of 228 552 km(2), the contemporary forest aboveground carbon stock is estimated to be 1134 Tg C, and the forest aboveground CSPG is estimated to be larger at >1770 Tg C. Importantly, these estimates of the potential for added aboveground carbon sequestration in forests are spatially resolved, are further partitioned between continued growth of existing trees and new afforested/reforested areas, and include time estimates for realization. They are also assessed for sensitivity to potential changes in vegetation productivity and disturbance rate in response to climate change. The results from this study are intended as input into regional, state, and local planning efforts that consider future climate mitigation in forests along with other land-use considerations.
引用
收藏
页数:14
相关论文
共 50 条
  • [41] High-resolution LGM climate of Europe and the Alpine region using the regional climate model WRF
    Russo, Emmanuele
    Buzan, Jonathan
    Lienert, Sebastian
    Jouvet, Guillaume
    Alvarez, Patricio Velasquez
    Davis, Basil
    Ludwig, Patrick
    Joos, Fortunat
    Raible, Christoph C.
    CLIMATE OF THE PAST, 2024, 20 (03) : 449 - 465
  • [42] High-resolution modelling of air pollution and deposition over the Netherlands with plume, grid and hybrid modelling
    van der Swaluw, Eric
    de Vries, Wilco
    Sauter, Ferd
    Aben, Jan
    Velders, Guus
    van Pul, Addo
    ATMOSPHERIC ENVIRONMENT, 2017, 155 : 140 - 153
  • [43] Changes in building climate zones over China based on high-resolution regional climate projections
    Shi, Ying
    Wang, Guiling
    ENVIRONMENTAL RESEARCH LETTERS, 2020, 15 (11)
  • [44] High-resolution spatial databases of monthly climate variables (1961–2010) over a complex terrain region in southwestern China
    Wei Wu
    An-Ding Xu
    Hong-Bin Liu
    Theoretical and Applied Climatology, 2015, 119 : 353 - 362
  • [45] High-Resolution Climate Change Projections of Atmospheric Rivers Over the South Pacific
    Goddard, Felix W.
    Gibson, Peter B.
    Rampal, Neelesh
    JOURNAL OF GEOPHYSICAL RESEARCH-ATMOSPHERES, 2025, 130 (06)
  • [46] High-Resolution Climate Projections Over Minnesota for the 21st century
    Liess, Stefan
    Twine, Tracy E.
    Snyder, Peter K.
    Hutchison, William D.
    Konar-Steenberg, Gabriel
    Keeler, Bonnie L.
    Brauman, Kate A.
    EARTH AND SPACE SCIENCE, 2022, 9 (03)
  • [47] High-resolution climate projection dataset over India using dynamical downscaling
    Barik, Anasuya
    Sahoo, Sanjeeb Kumar
    Kumari, Sarita
    Roy, Somnath Baidya
    GEOSCIENCE DATA JOURNAL, 2024, 11 (04): : 921 - 935
  • [48] HIGH-RESOLUTION RECONSTRUCTION OF CLIMATE CHANGE IN CENTRAL ASIA OVER THE PAST MILLENNIUM
    Darin, Andrey
    Kalugin, Ivan
    Maksimova, Natalya
    Ovchinnikov, Dmitriy
    Vologina, Elena
    Rudaya, Natalia
    Ptitsyn, Aleksei
    Reshetova, Svetlana
    Rakshun, Yakov
    Zolotarev, Konstantin
    10TH INTERNATIONAL MULTIDISCIPLINARY SCIENTIFIC GEOCONFERENCE: SGEM 2010, VOL I, 2010, : 55 - +
  • [49] A high-resolution data set of surface climate over global land areas
    New, M
    Lister, D
    Hulme, M
    Makin, I
    CLIMATE RESEARCH, 2002, 21 (01) : 1 - 25
  • [50] Carbon stock of Banja forest in Banja district, Amhara region, Ethiopia: An implication for climate change mitigation
    Abere, Fentahun
    Belete, Yehualashet
    Kefalew, Alemayehu
    Soromessa, Teshome
    JOURNAL OF SUSTAINABLE FORESTRY, 2017, 36 (06) : 604 - 622