Carbon monitoring is critical for the reporting and verification of carbon stocks and change. Remote sensing is a tool increasingly used to estimate the spatial heterogeneity, extent and change of carbon stocks within and across various systems. We designate the use of the term wet carbon system to the interconnected wetlands, ocean, river and streams, lakes and ponds, and permafrost, which are carbon-dense and vital conduits for carbon throughout the terrestrial and aquatic sections of the carbon cycle. We reviewed wet carbon monitoring studies that utilize earth observation to improve our knowledge of data gaps, methods, and future research recommendations. To achieve this, we conducted a systematic review collecting 1622 references and screening them with a combination of text matching and a panel of three experts. The search found 496 references, with an additional 78 references added by experts. Our study found considerable variability of the utilization of remote sensing and global wet carbon monitoring progress across the nine systems analyzed. The review highlighted that remote sensing is routinely used to globally map carbon in mangroves and oceans, whereas seagrass, terrestrial wetlands, tidal marshes, rivers, and permafrost would benefit from more accurate and comprehensive global maps of extent. We identified three critical gaps and twelve recommendations to continue progressing wet carbon systems and increase cross system scientific inquiry.

A new algorithm for estimating particulate inorganic carbon (PIC) concentrations from ocean color measurements is presented. PIC plays an important role in the global carbon cycle through the oceanic carbonate pump, therefore accurate estimations of PIC concentrations from satellite remote sensing are crucial for observing changes on a global scale. An extensive global data set was created from field and satellite observations for investigating the relationship between PIC concentrations and differences in the remote sensing reflectance (R_rs) at green, red, and near‐infrared (NIR) wavebands. Three color indices were defined: two as the relative height of R_rs(667) above a baseline running between R_rs(547) and an R_rs in the NIR (either 748 or 869 nm), and one as the difference between R_rs(547) and R_rs(667). All three color indices were found to explain over 90% of the variance in field‐measured PIC. But, due to the lack of availability of R_rs(NIR) in the standard ocean color data products, most of the further analysis presented here was done using the color index determined from only two bands. The new two‐band color index algorithm was found to retrieve PIC concentrations more accurately than the current standard algorithm used in generating global PIC data products. Application of the new algorithm to satellite imagery showed patterns on the global scale as revealed from field measurements. The new algorithm was more resistant to atmospheric correction errors and residual errors in sun glint corrections, as seen by a reduction in the speckling and patchiness in the satellite‐derived PIC images.

The Gulf of Maine North Atlantic Time Series (GNATS) has been run since 1998, across the Gulf of Maine (GoM), between Maine and Nova Scotia. GNATS goals are to provide ocean color satellite validation and to examine change in this coastal ecosystem. We have sampled hydrographical, biological, chemical, biogeochemical, and bio‐optical variables. After 2008, warm water intrusions (likely North Atlantic Slope Water [NASW]) were observed in the eastern GoM at 50–180 m depths. Shallow waters (<50 m) significantly warmed in winter, summer, and fall but cooled during spring. Surface salinity and density of the GoM also significantly increased over the 20 years. Phytoplankton standing stock and primary production showed highly‐significant decreases during the period. Concentrations of phosphate increased, silicate decreased, residual nitrate [N*; nitrate‐silicate] increased, and the ratio of dissolved inorganic nitrogen:phosphate decreased, suggesting increasing nitrogen limitation. Dissolved organic carbon (DOC) and its optical indices generally increased over two decades, suggesting changes to the DOC cycle. Surface seawater carbonate chemistry showed winter periods where the aragonite saturation (Ω_ar) dropped below 1.6 gulf‐wide due to upward winter mixing of cool, corrosive water. However, associated with increased average GoM temperatures, Ω_ar has significantly increased. These results reinforce the hypothesis that the observed decrease in surface GoM primary production resulted from a switch from Labrador Sea Water to NASW entering the GoM. A multifactor analysis shows that decreasing GoM primary production is most significantly correlated to decreases in chlorophyll and particulate organic carbon plus increases in N* and temperature.

Executive Summary Renewable energy sources – including biomass, geothermal, ocean, solar, and wind energy, as well as hydropower – have a huge potential to provide energy services for the world. The renewable energy resource base is sufficient to meet several times the present world energy demand and potentially even 10 to 100 times this demand. This chapter includes an in-depth examination of technologies to convert these renewable energy sources to energy carriers that can be used to fulfill our energy needs, including their installed capacity, the amount of energy carriers they produced in 2009, the current state of market and technology development, their economic and financial feasibility in 2009 and in the near future, as well as major issues they may face relative to their sustainability or implementation. Present uses of renewable energy Since 1990 the energy provided from renewable sources worldwide has risen at an average rate of nearly 2% a year, but in recent years this rate has increased to about 5% annually (see Figure 11.1.) As a result, the global contribution of renewables has increased from about 74 EJ in 2005 to about 89 EJ in 2009 and represents now 17% of global primary energy supply (528 EJ, see Figure 11.2). Most of this renewable energy comes from the traditional use of biomass (about 39 EJ) and larger-scale hydropower (about 30 EJ), while other renewable technologies provided about 20 EJ.

Understanding the relationship between remote sensing reflectance, R_rs(λ) and the inherent optical properties (IOPs) of natural waters is potentially a key to improving our ability to determine biogeochemical constituents from radiometric measurements. These relationships are usually described as a function of absorption, a(λ), and backscattering, b_b(λ), coefficients, with the literature providing various forms of equation operating on either b_b(λ)/a(λ) or b_b(λ)/[a(λ)+b_b(λ)] to represent the impact of variations in light field geometries and changes in sea‐water composition. The performance of several IOP‐reflectance relationships is assessed using HydroLight radiative transfer simulations covering a broad range of Case 1 and Case 2 water conditions. While early versions of IOP‐reflectance relationships assigned variability to associated proportionality factors (e.g., f/Q) or low‐order polynomial functions, recent studies have demonstrated relationships between R_rs(λ) and b_b(λ)/[a(λ)+b_b(λ)] are well‐characterized by nonlinear (high‐order polynomial), monotonic functions. This study demonstrates that this approach is also valid for relationships operating on b_b(λ)/a(λ) and that there is no intrinsic benefit to functions operating on b_b(λ)/[a(λ)+b_b(λ)] compared to b_b(λ)/a(λ) for Case 2 waters, contrary to recent suggestions in the literature. In all cases it is necessary to carefully consider the performance of best fit relationships across the full range of variability of IOPs and R_rs(λ), with higher order polynomials required to enable equivalent performance across the range of natural variability. The analysis further demonstrates insignificant wavelength sensitivity across the visible region, limited sensitivity to changes in solar zenith angle and extends to relationships for below surface remote sensing reflectance, r_rs(λ).